U.S. patent application number 10/995561 was filed with the patent office on 2005-12-08 for genetic polymorphisms associated with cardiovascular disorders and drug response, methods of detection and uses thereof.
This patent application is currently assigned to APPLERA CORPORATION. Invention is credited to Cargill, Michele, Devlin, James J., Iakoubova, Olga, Kirchgessner, Todd, Ploughman, Lynn Marie, Ranade, Koustubh, Shaw, Peter, Tsuchihashi, Zenta, Zerba, Kim E..
Application Number | 20050272054 10/995561 |
Document ID | / |
Family ID | 34681478 |
Filed Date | 2005-12-08 |
United States Patent
Application |
20050272054 |
Kind Code |
A1 |
Cargill, Michele ; et
al. |
December 8, 2005 |
Genetic polymorphisms associated with cardiovascular disorders and
drug response, methods of detection and uses thereof
Abstract
The present invention is based on the discovery of genetic
polymorphisms that are associated with cardiovascular disorders,
particularly acute coronary events such as myocardial infarction
and stroke, and genetic polymorphisms that are associated with
responsiveness of an individual to treatment of cardiovascular
disorders with statin. In particular, the present invention relates
to nucleic acid molecules containing the polymorphisms, variant
proteins encoded by such nucleic acid molecules, reagents for
detecting the polymorphic nucleic acid molecules and proteins, and
methods of using the nucleic acid and proteins as well as methods
of using reagents for their detection.
Inventors: |
Cargill, Michele; (San
Francisco, CA) ; Iakoubova, Olga; (Pleasanton,
CA) ; Devlin, James J.; (Lafayette, CA) ;
Tsuchihashi, Zenta; (Skillman, NJ) ; Shaw, Peter;
(Yardley, PA) ; Ploughman, Lynn Marie; (Washington
Crossing, PA) ; Zerba, Kim E.; (New Hope, PA)
; Ranade, Koustubh; (Princeton, NJ) ;
Kirchgessner, Todd; (Flemington, NJ) |
Correspondence
Address: |
CELERA GENOMICS
ATTN: WAYNE MONTGOMERY, VICE PRES, INTEL PROPERTY
45 WEST GUDE DRIVE
C2-4#20
ROCKVILLE
MD
20850
US
|
Assignee: |
APPLERA CORPORATION
Norwalk
CT
|
Family ID: |
34681478 |
Appl. No.: |
10/995561 |
Filed: |
November 24, 2004 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
60524882 |
Nov 26, 2003 |
|
|
|
60568219 |
May 6, 2004 |
|
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Current U.S.
Class: |
435/6.11 ;
514/548 |
Current CPC
Class: |
G01N 2800/324 20130101;
A61K 31/225 20130101; A61K 31/22 20130101; A61P 9/00 20180101; A61P
43/00 20180101; C12Q 2600/106 20130101; A61P 9/10 20180101; G01N
33/6893 20130101; G01N 2800/32 20130101; C12Q 2600/158 20130101;
A61P 9/12 20180101; C12Q 2600/156 20130101; C12Q 2600/172 20130101;
C12Q 2600/136 20130101; C12Q 1/6883 20130101 |
Class at
Publication: |
435/006 ;
514/548 |
International
Class: |
C12Q 001/68; A61K
031/225 |
Claims
What is claimed is:
1. A method for identifying an individual who has an altered risk
for developing a cardiovascular disorder or an altered likelihood
of responding to statin treatment, the method comprising detecting
a single nucleotide polymorphism (SNP) in any one of the nucleotide
sequences of SEQ ID NOS:1-517 and 1035-85,090 in said individual's
nucleic acids, wherein the presence of the SNP is correlated with
an altered risk for developing a cardiovascular disorder or
responding to statin treatment in said individual.
2. The method of claim 1 in which the altered risk is an increased
risk of developing a cardiovascular disorder or an increased
likelihood of responding to statin treatment.
3. The method of claim 1, wherein the cardiovascular disorder is an
acute coronary event selected from the group consisting of
myocardial infarction and stroke.
4. The method of claim 3 in which said individual has previously
had an acute coronary event.
5. The method of claim 1 in which the altered risk is a decreased
risk of developing a cardiovascular disorder or a decreased
likelihood of responding to statin treatment.
6. The method of claim 1, wherein the statin treatment comprises
treatment with pravastatin.
7. The method of claim 1, wherein the SNP is selected from the
group consisting of the SNPs set forth in Tables 6-15.
8. The method of claim 1 in which detection is carried out by a
process selected from the group consisting of: allele-specific
probe hybridization, allele-specific primer extension,
allele-specific amplification, sequencing, 5' nuclease digestion,
molecular beacon assay, oligonucleotide ligation assay, size
analysis, and single-stranded conformation polymorphism.
9. An isolated nucleic acid molecule comprising at least 8
contiguous nucleotides wherein one of the nucleotides is a single
nucleotide polymorphism (SNP) selected from any one of the
nucleotide sequences in SEQ ID NOS:1-517 and 1035-85,090, or a
complement thereof.
10. The isolated nucleic acid molecule of claim 9, wherein the SNP
is selected from the group consisting of the SNPs set forth in
Tables 3 and 4.
11. An isolated nucleic acid molecule that encodes any one of the
amino acid sequences in SEQ ID NOS:518-1034.
12. An isolated polypeptide comprising an amino acid sequence
selected from the group consisting of SEQ ID NOS:518-1034.
13. An antibody that specifically binds to a polypeptide of claim
12, or an antigen-binding fragment thereof.
14. The antibody of claim 13 in which the antibody is a monoclonal
antibody.
15. An amplified polynucleotide containing a single nucleotide
polymorphism (SNP) selected from any one of the nucleotide
sequences of SEQ ID NOS:1-517 and 1035-85,090, or a complement
thereof, wherein the amplified polynucleotide is between about 16
and about 1,000 nucleotides in length.
16. The amplified polynucleotide of claim 15 in which the
nucleotide sequence comprises any one of the nucleotide sequences
of SEQ ID NOS:1-517 and 1035-85,090.
17. An isolated polynucleotide which specifically hybridizes to a
nucleic acid molecule containing a single nucleotide polymorphism
(SNP) in any one of the nucleotide sequences in SEQ ID NOS:1-517
and 1035-85,090.
18. The polynucleotide of claim 17 which is 8-70 nucleotides in
length.
19. The polynucleotide of claim 17 which is an allele-specific
probe.
20. The polynucleotide of claim 17 which is an allele-specific
primer.
21. The polynucleotide of claim 17, wherein the polynucleotide
comprises a nucleotide sequence selected from the group consisting
of the primer sequences set forth in Table 5 (SEQ ID
NOS:85,091-85,702).
22. A kit for detecting a single nucleotide polymorphism (SNP) in a
nucleic acid, comprising the polynucleotide of claim 17, a buffer,
and an enzyme.
23. A method of detecting a single nucleotide polymorphism (SNP) in
a nucleic acid molecule, comprising contacting a test sample with a
reagent which specifically hybridizes to a SNP in any one of the
nucleotide sequences of SEQ ID NOS:1-517 and 1035-85,090 under
stringent hybridization conditions, and detecting the formation of
a hybridized duplex.
24. The method of claim 23 in which detection is carried out by a
process selected from the group consisting of: allele-specific
probe hybridization, allele-specific primer extension,
allele-specific amplification, sequencing, 5' nuclease digestion,
molecular beacon assay, oligonucleotide ligation assay, size
analysis, and single-stranded conformation polymorphism.
25. A method of detecting a variant polypeptide, comprising
contacting a reagent with a variant polypeptide encoded by a single
nucleotide polymorphism (SNIP) in any one of the nucleotide
sequences of SEQ ID NOS:1-517 and 1035-85,090 in a test sample, and
detecting the binding of the reagent to the polypeptide.
26. A method for identifying an agent useful in therapeutically or
prophylactically treating cardiovasacular disorders, comprising
contacting the polypeptide of claim 12 with a candidate agent under
conditions suitable to allow formation of a binding complex between
the polypeptide and the candidate agent, and detecting the
formation of the binding complex, wherein the presence of the
complex identifies said agent.
27. A method of treating a cardiovascular disorder in an
individual, the method comprising administering to said individual
an effective amount of statin based on said individual's likelihood
of responding to statin treatment as predicted by the alleles
present at one or more SNP sites selected from the group consisting
of the SNP sites disclosed in Tables 1-15.
Description
FIELD OF THE INVENTION
[0001] The present invention is in the field of cardiovascular
disorders and drug response, particularly acute coronary events and
statin treatment of acute coronary events. In particular, the
present invention relates to specific single nucleotide
polymorphisms (SNPs) in the human genome, and their association
with acute coronary events and/or variability in the responsiveness
to statin treatment (including preventive treatment) between
different individuals. The naturally-occurring SNPs disclosed
herein can be used as targets for the design of diagnostic reagents
and the development of therapeutic agents, as well as for disease
association and linkage, analysis. In particular, the SNPs of the
present invention are useful for, for example, identifying whether
an individual is likely to experience an acute coronary event
(either a first or recurrent acute coronary event), for predicting
the seriousness or consequences of an acute coronary event in an
individual, for prognosing an individual's recovery from an acute
coronary event, for evaluating the likely response of an individual
to statins for the treatment/prevention of acute coronary events,
for providing clinically important information for the prevention
and/or treatment of acute coronary events, and for screening and
selecting therapeutic agents. The SNPs disclosed herein are also
useful for human identification applications. Methods, assays,
kits, and reagents for detecting the presence of these
polymorphisms and their encoded products are provided.
BACKGROUND OF THE INVENTION
[0002] Cardiovascular Disorders and Response to Statin
TREATMENT
[0003] Cardiovascular disorders include, for example, acute
coronary events such as myocardial infarction and stroke.
[0004] Myocardial Infarction
[0005] Myocardial infarction (MI) is the most common cause of
mortality in developed countries. It is a multifactorial disease
that involves atherogenesis, thrombus formation and propagation.
Thrombosis can result in complete or partial occlusion of coronary
arteries. The luminal narrowing or blockage of coronary arteries
reduces oxygen and nutrient supply to the cardiac muscle (cardiac
ischemia), leading to myocardial necrosis and/or stunning. MI,
unstable angina, or sudden ischemic death are clinical
manifestations of cardiac muscle damage. All three endpoints are
part of the Acute Coronary Syndrome since the underlying mechanisms
of acute complications of atherosclerosis are considered to be the
same.
[0006] Atherogenesis, the first step of pathogenesis of MI, is a
complex interaction between blood elements, mechanical forces,
disturbed blood flow, and vessel wall abnormality. On the cellular
level, these include endothelial dysfunction, monocytes/macrophages
activation by modified lipoproteins, monocytes/macrophages
migration into the neointima and subsequent migration and
proliferation of vascular smooth muscle cells (VSMC) from the media
that results in plaque accumulation.
[0007] In recent years, an unstable (vulnerable) plaque was
recognized as an underlying cause of arterial thrombotic events and
MI. A vulnerable plaque is a plaque, often not stenotic, that has a
high likelihood of becoming disrupted or eroded, thus forming a
thrombogenic focus. Two vulnerable plaque morphologies have been
described. A first type of vulnerable plaque morphology is a
rupture of the protective fibrous cap. It can occur in plaques that
have distinct morphological features such as large and soft lipid
pool with distinct necrotic core and thinning of the fibrous cap in
the region of the plaque shoulders. Fibrous caps have considerable
metabolic activity. The imbalance between matrix synthesis and
matrix degradation thought to be regulated by inflammatory
mediators combined with VSMC apoptosis are the key underlying
mechanisms of plaque rupture. A second type of vulnerable plaque
morphology, known as "plaque erosion", can also lead to a fatal
coronary thrombotic event. Plaque erosion is morphologically
different from plaque rupture. Eroded plaques do not have fractures
in the plaque fibrous cap, only superficial erosion of the intima.
The loss of endothelial cells can expose the thrombogenic
subendothelial matrix that precipitates thrombus formation. This
process could be regulated by inflammatory mediators. The
propagation of the acute thrombi for both plaque rupture and plaque
erosion events depends on the balance between coagulation and
thrombolysis. MI due to a vulnerable plaque is a complex phenomenon
that includes: plaque vulnerability, blood vulnerability
(hypercoagulation, hypothrombolysis), and heart vulnerability
(sensitivity of the heart to ischemia or propensity for
arrhythmia).
[0008] Recurrent myocardial infarction (RMI) can generally be
viewed as a severe form of MI progression caused by multiple
vulnerable plaques that are able to undergo pre-rupture or a
pre-erosive state, coupled with extreme blood coagulability.
[0009] The incidence of MI is still high despite currently
available preventive measures and therapeutic intervention. More
than 1,500,000 people in the US suffer acute MI each year (many
without seeking help due to unrecognized MI), and one third of
these people die. The lifetime risk of coronary-artery disease
events at age 40 years is 42.4% for men (one in two) and 24.9% for
women (one in four) (Lloyd-Jones D M; Lancet, 1999 353: 89-92).
[0010] The current diagnosis of MI is based on the levels of
troponin I or T that indicate the cardiac muscle progressive
necrosis, impaired electrocardiogram (ECG), and detection of
abnormal ventricular wall motion or angiographic data (the presence
of acute thrombi). However, due to the asymptomatic nature of 25%
of acute MIs (absence of atypical chest pain, low ECG sensitivity),
a significant portion of MIs are not diagnosed and therefore not
treated appropriately (e.g., prevention of recurrent MIs).
[0011] Despite a very high prevalence and lifetime risk of MI,
there are no good prognostic markers that can identify an
individual with a high risk of vulnerable plaques and justify
preventive treatments. MI risk assessment and prognosis is
currently done using classic risk factors or the recently
introduced Framingham Risk Index. Both of these assessments put a
significant weight on LDL levels to justify preventive treatment.
However, it is well established that half of all MIs occur in
individuals without overt hyperlipidemia. Hence, there is a need
for additional risk factors for predicting predisposition to
MI.
[0012] Other emerging risk factors are inflammatory biomarkers such
as C-reactive protein (CRP), ICAM-1, SAA, TNF .alpha.,
homocysteine, impaired fasting glucose, new lipid markers (ox LDL,
Lp-a, MAD-LDL, etc.) and pro-thrombotic factors (fibrinogen,
PAI-1). Despite showing some promise, these markers have
significant limitations such as low specificity and low positive
predictive value, and the need for multiple reference intervals to
be used for different groups of people (e.g., males-females,
smokers-non smokers, hormone replacement therapy users, different
age groups). These limitations diminish the utility of such markers
as independent prognostic markers for MI screening.
[0013] Genetics plays an important role in MI risk. Families with a
positive family history of MI account for 14% of the general
population, 72% of premature MIs, and 48% of all MIs (Williams R R,
Am J Cardiology, 2001; 87:129). In addition, replicated linkage
studies have revealed evidence of multiple regions of the genome
that are associated with MI and relevant to MI genetic traits,
including regions on chromosomes 14, 2, 3 and 7 (Broeckel U, Nature
Genetics, 2002; 30: 210; Harrap S, Arterioscler Thromb Vasc Biol,
2002; 22: 874-878, Shearman A, Human Molecular Genetics, 2000, 9;
9, 1315-1320), implying that genetic: risk factors influence the
onset, manifestation, and progression of MI. Recent association
studies have identified allelic variants that are associated with
acute complications of coronary heart disease, including allelic
variants of the ApoE, ApoA5, Lpa, APOCIII, and Klotho genes.
[0014] Genetic markers such as single nucleotide polymorphisms are
preferable to other types of biomarkers. Genetic markers that are
prognostic for MI can be genotyped early in life and could predict
individual response to various risk factors. The combination of
serum protein levels and genetic predisposition revealed by genetic
analysis of susceptibility genes can provide an integrated
assessment of the interaction between genotypes and environmental
factors, resulting in synergistically increased prognostic value of
diagnostic tests.
[0015] Thus, there is an urgent need for novel genetic markers that
are predictive of predisposition to MI, particularly for
individuals who are unrecognized as having a predisposition to MI.
Such genetic markers may enable prognosis of MI in much larger
populations compared with the populations that can currently be
evaluated by using existing risk factors and biomarkers. The
availability of a genetic test may allow, for example, appropriate
preventive treatments for acute coronary events to be provided for
susceptible individuals (such preventive treatments may include,
for example, statin treatments and statin dose escalation, as well
as changes to modifiable risk factors), lowering of the thresholds
for ECG and angiography testing, and allow adequate monitoring of
informative biomarkers.
[0016] Moreover, the discovery of genetic markers associated with
MI will provide novel targets for therapeutic intervention or
preventive treatments of MI, and enable the development of new
therapeutic agents for treating MI and other cardiovascular
disorders.
[0017] Stroke
[0018] Stroke is a prevalent and serious disease. Stroke is the
most common cause of disability, the second leading cause of
dementia, and the third leading cause of mortality in the United
States. It affects 4.7 million individuals in the United States,
with 500,000 first, attacks and 200,000 recurrent cases yearly.
Approximately one in four men and one five women aged 45 years will
have a stroke if they live to their 85th year. About 25% of those
who have a stroke die within a year. For that, stroke is the third
leading cause of mortality in the United States and is responsible
for 170,000 deaths a year. Among those who survive the stroke
attack, 30 to 50% do not regain functional independence.
[0019] Stroke occurs when an artery bringing oxygen or nutrients to
the brain either ruptures, causing the hemorrhagic type of strokes,
or gets occluded, causing the thrombotic/embolic strokes that are
collectively referred to as ischemic strokes. In each case, a
cascade of cellular changes due to ischemia or increased cranial
pressure leads to injuries or death of the brain cells. In the
United States, the majority (about 80-90%) of strokes are ischemic,
including 31% large-vessel thrombotic (also referred to as
large-vessel occlusive disease), 20% small-vessel thrombotic (also
referred to as small-vessel occlusive disease), and 32% embolic or
cardiogenic (caused by a clot originating from elsewhere in the
body, e.g., from blood pooling due to atrial fibrillation, or from
carotid artery stenosis). The ischemic form of stroke shares common
pathological etiology with atherosclerosis and thrombosis. 10-20%
of strokes are of the hemorrhagic type, involving bleeding within
or around the brain. Bleeding within the brain is known as cerebral
hemorrhage, which is often linked to high blood pressure. Bleeding
into the meninges surrounding the brain is known as a subarachnoid
hemorrhage, which could be caused by a ruptured cerebral aneurysm,
an arteriovenous malformation, or a head injury. The hemorrhagic
strokes, although less prevalent, pose a greater danger. Whereas
about 8% of ischemic strokes result in death within 30 days, about
38% of hemorrhagic strokes result in death within the same time
period.
[0020] Known risk factors for stroke can be divided into modifiable
and non-modifiable risk factors. Older age, male sex, black or
Hispanic ethnicity, and family history of stroke are non-modifiable
risk factors. Modifiable risk factors include hypertension,
smoking, increased insulin levels, asymptomatic carotid disease,
cardiac vessel disease, and hyperlipidemia. Information derived
from the Dutch Twin Registry estimates the heritability of stroke
as 0.32 for stroke death and 0.17 for stroke hospitalization.
[0021] The acute nature of stroke leaves physicians with little
time to prevent or lessen the devastation of brain damage.
Strategies to diminish the impact of stroke include prevention and
treatment with thrombolytic and; possibly, neuroprotective agents.
The success of preventive measures will depend on the
identification of risk factors and means to modulate their
impact.
[0022] Although some risk factors for stroke are not modifiable,
such as age and family history, other underlying pathology or risk
factors of stroke such as atherosclerosis, hypertension, smoking,
diabetes, aneurysm, and atrial fibrillation, are chronic and
amenable to effective life-style, medical, and surgical treatments.
Early recognition of patients with these risk factors, and
especially those with a family history, with a non-invasive test of
genetic markers will enable physicians to target the highest risk
individuals for aggressive risk reduction.
[0023] Statin Treatment
[0024] Coronary heart disease (CHD) accounts for approximately
two-thirds of cardiovascular mortality in the United States, with
CHD accounting for 1 in every 5 deaths in 1998, which makes it the
largest single cause of morality (American Heart Association. 2001
Heart and Stroke Statistical Update. Dallas, Tex.: American Heart
Association. 2000). Stroke is the third leading cause of death,
accounting for 1 of every 15 deaths. Reduction of coronary and
cerebrovascular events and total mortality by treatment with
HMG-CoA reductase inhibitors (statins) has been demonstrated in a
number of randomized, double blinded, placebo controlled
prospective trials (Waters, D. D., What do the statin trials tell
us? Clin Cardiol, 2001. 24(8 Suppl): p. III3-7, Singh, B. K. and J.
L. Mehta, Management of dyslipidemia in the primary prevention of
coronary heart disease. Curr Opin Cardiol, 2002. 17(5): p. 503-11).
These drugs have their primary effect through the inhibition of
hepatic cholesterol synthesis, thereby upregulating LDL receptor in
the liver. The resultant increase in LDL catabolism results in
decreased circulating LDL, a major risk factor for cardiovascular
disease. In addition, statins cause relatively small reductions in
triglyceride levels (5 to 10%) and elevations in HDL cholesterol (5
to 10%). In a 5 year primary intervention trial (WOSCOPS),
pravastatin decreased clinical events 29% compared to placebo in
hypercholesterolemic subjects, achieving a 26% reduction in
LDL-cholesterol (LDL-C) (Shepherd, J., et al., Prevention of
coronary heart disease with pravastatin in men with
hypercholesterolemia. West of Scotland Coronary Prevention Study
Group. N Engl. J. Med, 1995. 333(20): p. 1301-7). In a similar
primary prevention trial (AFCAPS/TexCAPS) (Downs, J. R., et al.,
Primary prevention of acute coronary events with lovastatin in men
and women with average cholesterol levels: results of
AFCAPS/TexCAPS. Air Force/Texas Coronary Atherosclerosis Prevention
Study. Jama, 1998. 279(20): p. 1615-22) in which subjects with
average cholesterol levels were treated with lovastatin, LDL-C was
reduced an average of 25% and events decreased by 37%.
[0025] Secondary prevention statin trials include the CARE (Sacks,
F. M., et al., The effect of pravastatin on coronary events after
myocardial infarction in patients with average cholesterol levels.
Cholesterol and Recurrent Events Trial investigators. N Engl J Med,
1996. 335(14): p. 1001-9) and LIPID (treatment with pravastatin)
(Prevention of cardiovascular events and death with pravastatin in
patients with coronary heart disease and a broad range of initial
cholesterol levels. The Long-Term Intervention with Pravastatin in
Ischaemic Disease (LIPID) Study Group. N Engl J Med, 1998. 339(19):
p. 1349-57), and 4S (treatment with simvastatin) (Randomised trial
of cholesterol lowering in 4444 patients with coronary heart
disease: the Scandinavian Simvastatin Survival Study (4S). Lancet,
1994. 344(8934): p. 1383-9) studies. In these trials, clinical
event risk was reduced from between 23% and 34% with achieved LDL-C
lowering ranging between 25% and 35%.
[0026] In addition to LDL-lowering, a variety of potential
non-lipid lowering effects have been suggested to play a role in
cardiovascular risk reduction by statins. These include
anti-inflammatory effects on various vascular cell types including
foam cell macrophages, improved endothelial responses, inhibition
of platelet reactivity thereby decreasing hypercoaguability, and
many others (Puddu, P., G. M. Puddu, and A. Muscari, Current
thinking in statin therapy. Acta Cardiol, 2001. 56(4): p. 225-31,
Albert, M. A., et al., Effect of statin therapy on C-reactive
protein levels: the pravastatin inflammation/CRP evaluation
(PRINCE): a randomized trial and cohort study. Jama, 2001. 286(1):
p. 64-70, Rosenson, R. S., Non-lipid-lowering effects of statins on
atherosclerosis. Curr Cardiol Rep, 1999. 1(3): p. 225-32, Dangas,
G., et al., Pravastatin: an antithrombotic effect independent of
the cholesterol-lowering effect. Thromb Haemost, 2000. 83(5): p.
688-92, Crisby, M., Modulation of the inflammatory process by
statins. Drugs Today (Barc), 2003. 39(2): p. 137-43, Liao, J. K.
Role of statin pleiotropism in acute coronary syndromes and stroke.
Int. J. Clin Pract Suppl, 2003(134): p. 51-7). However, because
hypercholesterolemia is a factor in many of these additional
pathophysiologic mechanisms that are reversed by statins, many of
these statin benefits may be a consequence of LDL lowering.
[0027] Statins as a class of drug are generally well tolerated. The
most common side effects include a variety of muscle-related
complaints or myopathies. While the incidence of muscle side
effects are low, the most serious side effect, myositis with
rhabdomyolysis, is life threatening. This adverse effect has been
highlighted by the recent withdrawal of cerevastatin when the drug
was found to be associated with a relatively high level of
rhabdomyolysis-related deaths. In addition, the development of a
high dose sustained release formulation of simvastatin was
discontinued for rhabdomyolysis-related issues (Davidson, M. H., et
al., The efficacy and six-week tolerability of simvastatin 80 and
160 mg/day. Am J Cardiol, 1997. 79(1): p. 38-42).
[0028] Statins can be divided into two types according to their
physicochemical and pharmacokinetic properties. Statins such as
lovastatin, simvastatin, atorvastatin, and cerevastatin are
hydrophobic in nature and, as such, diffuse across membranes and
thus are highly cell permeable. Hydrophilic statins such as
pravastatin are more polar, such that they require specific cell
surface transporters for cellular uptake (Ziegler, K. and W.
Stunkel, Tissue-selective action of pravastatin due to
hepatocellular uptake via a sodium-independent bile acid
transporter. Biochim Biophys Acta, 1992. 1139(3): p. 203-9,
Yamazaki, M., et al., Na(+)-independent multispecific anion
transporter mediates active transport of pravastatin into rat
liver. Am J Physiol, 1993. 264(1 Pt 1): p. G36-44, Komai, T., et
al., Carrier-mediated uptake of pravastatin by rat hepatocytes in
primary culture. Biochem Pharmacol, 1992. 43(4): p. 667-70). The
latter statin utilizes a transporter, OATP2, whose tissue
distribution is confined to the liver and, therefore, they are
relatively hepato-specific inhibitors (Hsiang, B., et al., A novel
human hepatic organic anion transporting polypeptide (OATP2).
Identification of a liver-specific human organic anion transporting
polypeptide and identification of rat and human
hydroxymethylglutaryl-CoA reductase inhibitor transporters. J Biol
Chem, 1999. 274(52): p. 37161-8). The former statins, not requiring
specific transport mechanisms, are available to all cells and they
can directly impact a much broader spectrum of cells and tissues.
These differences in properties may influence the spectrum of
activities that each statin posesses. Pravastatin, for instance,
has a low myopathic potential in animal models and myocyte cultures
compared to other hydrophobic statins (Masters, B. A., et al., In
vitro myotoxicity of the 3-hydroxy-3-methylglutaryl coenzyme A
reductase inhibitors, pravastatin, lovastatin, and simvastatin,
using neonatal rat skeletal myocytes. Toxicol Appl Pharmacol, 1995.
131(1): p. 163-74. Nakahara, K., et al., Myopathy induced by
HMG-CoA reductase inhibitors in rabbits: a pathological,
electrophysiological, and biochemical study. Toxicol Appl
Pharmacol, 1998. 152(1): p. 99-106, Reijneveld, J. C., et al.,
Differential effects of 3-hydroxy-3-methylglutaryl-coenzyme A
reductase inhibitors on the development of myopathy in young rats.
Pediatr Res, 1996. 39(6): p. 1028-35).
[0029] Cardiovascular mortality in developed countries has
decreased sharply in recent decades (Tunstall-Pedoe, H., et al.,
Estimation of contribution of changes in coronary care to improving
survival, event rates, and coronary heart disease mortality across
the WHO MONICA Project populations. Lancet, 2000. 355(9205): p.
688-700). This is likely due to the development and use of
efficaceous hypertension, thrombolytic and lipid lowering therapies
(Kuulasmaa, K., et al., Estimation of contribution of changes in
classic risk factors to trends in coronary-event rates across the
WHO MONICA Project populations. Lancet, 2000. 355(9205): p.
675-87). Nevertheless, cardiovascular diseases remain the major
cause of death in industrialized countries, at least in part due to
the presence of highly prevalent risk factors and insufficient
treatment (Wong, M. D., et al., Contribution of major diseases to
disparities in mortality. N Engl J Med, 2002. 347(20): p. 1585-92).
Even with appropriate therapy, not all patients respond equally
well to statin treatment. Despite the overwhelming evidence that
statins decrease risk for cardiovascular disease, both in primary
and secondary intervention settings, statin therapy clearly only
achieves partial risk reduction. While a decrease in risk of 23 to
37% seen in the above trials is substantial and extremely important
clinically, the majority of events still are not prevented by
statin treatment. This is not surprising given the complexity of
cardiovascular disease etiology, which is influenced by genetics,
environment, and a variety of additional risk factors including
dyslipidemia, age, gender, hypertension, diabetes, obesity, and
smoking. It is reasonable to assume that all of these
multi-factorial risks modify statin responses and determine the
final benefit that each individual achieves from therapy.
Furthermore, with the increasing incidence of Type 2 diabetes and
obesity in Western countries (Flegal, K. M., et al., Prevalence and
trends in obesity among US adults, 1999-2000. Jama, 2002. 288(14):
p. 1723-7, Boyle, J. P. et al., Projection of diabetes burden
through 2050: impact of changing demography and disease prevalence
in the U.S. Diabetes Care, 2001. 24(11): p. 1936-40), which are two
major risk factors for coronary artery disease, and the emergence
of greater cardiovascular risk factors in the developing world
(Yusuf, S., et al., Global burden of cardiovascular diseases: Part
II: variations in cardiovascular disease by specific ethnic groups
and geographic regions and prevention strategies. Circulation,
2001. 104(23): p. 2855-64, Yusuf, S., et al., Global burden of
cardiovascular diseases: part I: general considerations, the
epidemiologic transition, risk factors, and impact of urbanization.
Circulation, 2001. 104(22): p. 2746-53), the need for ever more
effective treatment of CHD is predicted to steadily increase.
[0030] Thus, there is a growing need for ways to better identify
people who have the highest chance to benefit from statins, and
those who have the lowest risk of developing side-effects. As
indicated above, severe myopathies represent a significant risk for
a low percentage of the patient population. This would be
particularly true for patients that may be treated more
aggressively with statins in the future. There are currently at
least three studies in progress that are investigating whether
treatments aimed at lowering LDL-C to levels below current NCEP
goals by administering higher statin doses to patients: further
reduces CHD risk or provides additional cardiovascular benefits
(reviewed in Clark, L. T., Treating dyslipidemia with stating: the
risk-benefit profile. Am Heart J, 2003. 145(3): p. 387-96). It is
possible that more aggressive statin therapy than is currently
standard practice will become the norm in the future if additional
benefit is observed in such trials. More aggressive statin therapy
will likely increase the incidence of the above adverse events as
well as elevate the cost of treatment. Thus, increased emphasis
will be placed on stratifying responder and non-responder patients
in order for maximum benefit-risk ratios to be achieved at the
lowest cost.
[0031] The Third Report of the Expert Panel on Detection,
Evaluation and Treatment of High Blood Cholesterol in Adults
(ATPIII) contains current recommendations for the management of
high serum cholesterol (Executive Summary of The Third Report of
The National Cholesterol Education Program (NCEP) Expert Panel on
Detection, Evaluation, And Treatment of High Blood Cholesterol In
Adults (Adult Treatment Panel III). Jama, 2001. 285(19): p.
2486-97). A meta-analysis of 38 primary and secondary prevention
trials found that for every 10% decrease in serum cholesterol, CHD
mortality was reduced by 15%. These guidelines took into account
additional risk factors beyond serum cholesterol when making
recommendations for lipid lowering strategies. After considering
additional risk factors and updated information on lipid lowering
clinical trials, more patients are classified in the highest risk
category of CHD or CHD risk equivalent than before and are
recommended to decrease their LDL to less than 100 mg/dl. As a
consequence, more aggressive therapy is recommended and drug
therapy is recommended for 36.5 million Americans. In implementing
these recommendations, cost-effectiveness of treatments is a
primary concern. In lower risk populations, the cost of reducing
one event may exceed $125,000 compared with around $25,000 per
event in a high-risk patient group (Singh, B. K. and J. L. Mehta,
Management of dyslipidemia in the primary prevention of coronary
heart disease. Curr Opin Cardiol, 2002. 17(5): p. 503-11). The cost
of preventing an event in a very low risk patient may exceed $1
million. In the context of cost-containment, further risk
stratification of patients will help to avoid unnecessary treatment
of patients. In addition to the various clinical endpoints that are
currently considered in determining overall risk, the determination
of who and who not to treat with statins based on "statin response"
genotypes could substantially increase the precision of these
determinations in the future.
[0032] Evidence from gene association studies is accumulating to
indicate that responses to drugs are, indeed, at least partly under
genetic control. As such, pharmacogenetics--the study of
variability in drug responses attributed to hereditary factors in
different populations--may significantly assist in providing
answers toward meeting this challenge (Roses, A. D.,
Pharmacogenetics and the practice of medicine. Nature, 2000.
405(6788): p. 857-65, Mooser, V., et al., Cardiovascular
pharmacogenetics in the SNP era. J Thromb Haemost, 2003. 1(7): p.
1398-1402, Humma, L. M. and S. G. Terra, Pharmacogenetics and
cardiovascular disease: impact on drug response and applications to
disease management. Am. J. Health Syst. Pharm, 2002. 59(13): p.
1241-52). Numerous associations have been reported between selected
genotypes, as defined by SNPs and other sequence variations and
specific responses to cardiovascular drugs. Polymorphisms in
several genes have been suggested to influence responses to statins
including CETP (Kuivenhoven, J. A., et al., The role of a common
variant of the cholesteryl ester transfer protein gene in the
progression of coronary atherosclerosis. The Regression Growth
Evaluation Statin Study Group. N Engl J Med, 1998. 338(2): p.
86-93), beta-fibrinogen (de Maat, M. P., et al., -455G/A
polymorphism of the beta-fibrinogen gene is associated with the
progression of coronary atherosclerosis in symptomatic men:
proposed role for an acute-phase reaction pattern of fibrinogen.
REGRESS group. Arterioscler Thromb Vasc Biol, 1998. 18(2): p.
265-71), hepatic lipase (Zambon, A., et al., Common hepatic lipase
gene promoter variant determines clinical response to intensive
lipid-lowering treatment. Circulation, 2001. 103(6): p. 792-8,
lipoprotein lipase (Jukema, J. W., et al., The Asp9 Asn mutation in
the lipoprotein lipase gene is associated with increased
progression of coronary atherosclerosis. REGRESS Study Group,
Interuniversity Cardiology Institute, Utrecht, The Netherlands.
Regression Growth Evaluation Statin Study. Circulation, 1996.
94(8): p. 1913-8), glycoprotein IIIa (Bray, P. F., et al., The
platelet Pl(A2) and angiotensin-converting enzyme (ACE) D allele
polymorphisms and the risk of recurrent events after acute
myocardial infarction. Am J Cardiol, 2001. 88(4): p. 347-52),
stromelysin-1 (de Maat, M. P., et al., Effect of the stromelysin-1
promoter on efficacy of pravastatin in coronary atherosclerosis and
restenosis. Am J Cardiol, 1999. 83(6): p. 852-6), and
apolipoprotein E (Gerdes, L. U., et al., The apolipoprotein
epsilon4 allele determines prognosis and the effect on prognosis of
simvastatin in survivors of myocardial infarction: a substudy of
the Scandinavian simvastatin survival study. Circulation, 2000.
101(12): p. 1366-71, Pedro-Botet, J., et al., Apolipoprotein E
genotype affects plasma lipid response to atorvastatin in a gender
specific manner. Atherosclerosis, 2001. 158(1): p. 183-93).
[0033] Some of these variants were shown to effect clinical events
while others were associated with changes in surrogate endpoints.
The CETP variant alleles B1 and B2 were shown to be correlated with
HDL cholesterol levels. Patients with B1B1 and B1B2 genotypes have
lower HDL cholesterol and greater progression of
angiographically-determined atherosclerosis than B2B2 subjects when
on placebo during the pravastatin. REGRESS clinical trial.
Furthermore, B1B1 and B1B2-had significantly less progression of
atherosclerosis when on pravastatin whereas B2B2 patients derived
no benefit. Similarly, beta-fibrinogen promoter sequence variants
were also associated with disease progression and response to
pravastatin in the same study as were Stomelysin-1 promoter
variants. In the Cholesterol and Recurrent Events (CARE) trial, a
pravastatin secondary intervention study, glycoprotein IIIa
variants were also associated with clinical event: response to
pravastatin. In all of the above cases, genetic subgroups of
placebo-treated patients with CHD were identified who had increased
risk for major coronary events. Treatment with pravastatin
abolished the harmful effects associated with the "riskier"
genotype, while having little effect on patients with genotypes
that were associated with less risk. Finally, the impact of the
apolipoprotein .epsilon.4 genotype on prognosis and the response to
simvastatin or placebo was investigated in the Scandanavian
Simvastatin Survival Study (Pedro-Botet, J., et al., Apolipoprotein
E genotype affects plasma lipid response to atorvastatin in a
gender specific manner. Atherosclerosis, 2001. 158(1): p. 183-93).
Patients with at least one apolipoprotein .epsilon.4 allele had a
higher risk for all cause death than those lacking the allele. As
was the case with pravastatin treatment, simvastatin reversed this
detrimental effect of the "riskier allele". These results suggest
that, in general, high-risk patients with ischemic heart disease
derive the greatest benefit from statin therapy. However, these
initial observations should be repeated in other cohorts to further
support the predictive value of these specific genotypes. Although
it is likely that additional genes beyond the five examples above
impact the final outcome of an individual's response to statins,
these five examples serve to illustrate that it is possible to
identify genes that associate with statin clinical responses that
could be used to predict which patients will benefit from statin
treatment and which will not.
[0034] SNPs
[0035] The genomes of all organisms undergo spontaneous mutation in
the course of their continuing evolution, generating variant forms
of progenitor genetic sequences (Gusella, Ann. Rev. Biochem. 55,
831-854 (1986)). A variant form may confer an evolutionary
advantage or disadvantage relative to a progenitor form or may be
neutral. In some instances, a variant form confers an evolutionary
advantage to the species and is eventually incorporated into the
DNA of many or most species and effectively becomes the progenitor
form. Additionally, the effects of a variant form may be both
beneficial and detrimental, depending on the circumstances. For
example, a heterozygous sickle cell mutation confers resistance to
malaria, but a homozygous sickle cell mutation is usually lethal.
In many cases, both progenitor and variant forms survive and
co-exist in a species population. The coexistence of multiple forms
of a genetic sequence gives rise to genetic polymorphisms,
including SNPs.
[0036] Approximately 90% of all polymorphisms in the human genome
are SNPs. SNPs are single base positions in DNA at which different
alleles, or alternative nucleotides, exist in a population. The SNP
position (interchangeably referred to herein as SNP, SNP site, SNP
locus, SNP marker, or marker) is usually preceded by and followed
by highly conserved sequences of the allele (e.g., sequences that
vary in less than {fraction (1/100)} or {fraction (1/1000)} members
of the populations). An individual may be homozygous or
heterozygous for an allele at each SNP position. A SNP can, in some
instances, be referred to as a "cSNP" to denote that the nucleotide
sequence containing the SNP is an amino acid coding sequence.
[0037] A SNP may arise from a substitution of one nucleotide for
another at the polymorphic site. Substitutions can be transitions
or transversions. A transition is the replacement of one purine
nucleotide by another purine nucleotide, or one pyrimidine by
another pyrimidine. A transversion is the replacement of a purine
by a pyrimidine, or vice versa. A SNP may also be a single base
insertion or deletion variant referred to as an "indel" (Weber et
al., "Human diallelic insertion/deletion polymorphisms", Am J Hum
Genet 2002 October; 71(4):854-62).
[0038] A synonymous codon change, or silent mutation/SNP (terms
such as "SNP", "polymorphism", "mutation", "mutant", "variation",
and "variant" are used herein interchangeably), is one that does
not result in a change of amino acid due to the degeneracy of the
genetic code. A substitution that changes a codon coding for one
amino acid to a codon coding for a different amino acid (i.e., a
non-synonymous codon change) is referred to as a missense mutation.
A nonsense mutation results in a type of non-synonymous codon
change in which a stop codon is formed, thereby leading to
premature termination of a polypeptide chain and a truncated
protein. A read-through mutation is another type of non-synonymous
codon change that, causes the destruction of a stop codon, thereby
resulting in an extended polypeptide product. While SNPs can be
bi-, tri-, or tetra-allelic, the vast majority of the SNPs are
bi-allelic, and are thus often referred to as "bi-allelic markers",
or "di-allelic markers".
[0039] As used herein, references to SNPs and, SNP genotypes
include individual SNPs and/or haplotypes, which are groups of SNPs
that are generally inherited together. Haplotypes can have stronger
correlations with diseases or other phenotypic effects compared
with individual SNPs, and therefore may provide increased
diagnostic accuracy in some cases (Stephens et al. Science 293,
489-493, 20 July 2001).
[0040] Causative SNPs are those SNPs that produce alterations in
gene expression or in the expression, structure, and/or function of
a gene product, and therefore are most predictive of a possible
clinical phenotype. One such class includes SNPs falling within
regions of genes encoding a polypeptide product, i.e. cSNPs. These
SNPs may result in an alteration of the amino acid sequence of the
polypeptide product (i.e., non-synonymous codon changes) and give
rise to the expression of a defective or other variant protein.
Furthermore, in the case of nonsense mutations, a SNP may lead to
premature termination of a polypeptide product. Such variant
products can result in a pathological condition, e.g., genetic
disease. Examples of genes in which a SNP within a coding sequence
causes a genetic disease include sickle cell anemia and cystic
fibrosis.
[0041] Causative SNPs do not necessarily have to occur in coding
regions; causative SNPs can occur in, for example, any genetic
region that can ultimately affect the expression, structure, and/or
activity of the protein encoded by a nucleic acid. Such genetic
regions include, for example, those involved in transcription, such
as SNPs in transcription factor binding domains, SNPs in promoter
regions, in areas involved in transcript processing, such as SNPs
at intron-exon boundaries that may cause defective splicing, or
SNPs in mRNA processing signal sequences such as polyadenylation
signal regions. Some SNPs that are not causative SNPs nevertheless
are in close association with, and therefore segregate with, a
disease-causing sequence. In this situation, the presence of a SNP
correlates with the presence of, or predisposition to, or an
increased, risk in developing the disease. These SNPs although not
causative, are nonetheless also useful for diagnostics, disease
predisposition screening, and other uses.
[0042] An association study of a SNP and a specific disorder
involves determining the presence or frequency of the SNP allele in
biological samples from individuals with the disorder of interest,
such as those individuals who respond to statin treatment
("responders") or those individuals who do not respond to statin
treatment ("non-responders"), and comparing the information to that
of controls (i.e., individuals who do not have the disorder;
controls may be also referred to as "healthy" or "normal"
individuals) who are preferably of similar age and race. The
appropriate selection of patients and controls is important to the
success of SNP association studies. Therefore, a pool of
individuals with well-characterized phenotypes is extremely
desirable.
[0043] A SNP may be screened in diseased tissue samples or any
biological sample obtained from a diseased individual, and compared
to control samples, and selected for its increased (or decreased)
occurrence in a specific phenotype, such as response or
non-response to statin treatment of cardiovascular disease. Once a
statistically significant association is established between one or
more SNP(s) and a pathological condition (or other phenotype) of
interest, then the region around the SNP can optionally be
thoroughly screened to identify the causative genetic
locus/sequence(s) (e.g., causative SNP/mutation, gene, regulatory
region, etc.) that influences the pathological condition or
phenotype. Association studies may be conducted within the general
population and are not limited to studies performed on related
individuals in affected families (linkage studies).
[0044] Clinical trials have shown that patient response to
treatment with pharmaceuticals is often heterogeneous. There is a
continuing need to improve pharmaceutical agent design and therapy.
In that regard, SNPs can be used to identify patients most suited
to therapy with particular pharmaceutical agents such as statins
(this is often termed "pharmacogenomics"). Similarly, SNPs can be
used to exclude patients from certain treatment due to the
patient's increased likelihood of developing toxic side effects or
their likelihood of not responding to the treatment.
Pharmacogenomics can also be used in pharmaceutical research to
assist the drug development and selection process. (Linder et al.
(1997), Clinical Chemistry, 43, 254; Marshall (1997), Nature
Biotechnology, 15, 1249; International Patent Application WO
97/40462, Spectra Biomedical; and Schafer et al. (1998), Nature
Biotechnology, 16, 3).
SUMMARY OF THE INVENTION
[0045] The present invention relates to the identification of novel
SNPs, unique combinations of such SNPs, and haplotypes of SNPs that
are associated with cardiovascular disorders and/or drug response,
particularly acute coronary events (e.g., myocardial infarction and
stroke) and response to statins for the treatment (including
preventive treatment) of cardiovascular disorders such as acute
coronary events. The polymorphisms disclosed herein are directly
useful as targets for the design of diagnostic reagents and the
development of therapeutic agents for use in the diagnosis and
treatment of cardiovascular disorders and related pathologies,
particularly acute coronary events.
[0046] Based on the identification of SNPs associated with
cardiovascular disorders, particularly acute coronary events,
and/or response to statin treatment, the present invention also
provides methods of detecting these variants as well as the design
and preparation of detection reagents needed to accomplish this
task. The invention specifically provides, for example, novel SNPs
in genetic sequences involved in cardiovascular disorders and/or
responsiveness to statin treatment, isolated nucleic acid molecules
(including, for example, DNA and RNA molecules) containing these
SNPs, variant proteins encoded by nucleic acid molecules containing
such SNPs, antibodies to the encoded variant proteins,
computer-based and data storage systems containing the novel SNP
information, methods of detecting these SNPs in a test sample,
methods of determining the risk of an individual of experiencing a
first or recurring acute coronary event, methods for prognosing the
severity or consequences of the acute coronary event, methods of
treating an individual who has an increased risk of experiencing an
acute coronary event, methods of identifying individuals who have
an altered (i.e., increased or decreased) likelihood of responding
to statin treatment based on the presence or absence of one or more
particular nucleotides (alleles) at one or more SNP sites disclosed
herein or the detection of one or more encoded variant products
(e.g., variant mRNA transcripts or variant proteins), methods of
identifying individuals who are more or less likely to respond to a
treatment, particularly statin treatment of a cardiovascular
disorder such as an acute coronary event (or more or less likely to
experience undesirable side effects from a treatment, etc.),
methods of screening for compounds useful in the treatment of a
disorder associated with a variant gene/protein, compounds
identified by these methods, methods of treating disorders mediated
by a variant gene/protein, methods of using the novel SNPs of the
present invention for human identification, etc.
[0047] Since cardiovascular disorders/diseases share certain
similar features that may be due to common genetic factors that are
involved in their underlying mechanisms, the SNPs identified herein
as being particularly associated with acute coronary events and/or
statin response may be used as diagnostic/prognostic markers or
therapeutic targets for a broad spectrum of cardiovascular diseases
such as coronary heart disease (CHD), atherosclerosis,
cerebrovascular disease, congestive heart failure, congenital heart
disease, and pathologies and symptoms associated with various heart
diseases (e.g., angina, hypertension), as well as for predicting
responses to a variety of HMG-CoA reductase inhibitors with
lipid-lowering activities (statins), and even drugs other than
statins that are used to treat cardiovascular diseases. In
addition, the SNPs of the present invention are useful for
predicting primary acute coronary events, as well as their
reoccurrence.
[0048] The present invention further provides methods for selecting
or formulating a treatment regimen (e.g., methods for determining
whether or not to administer statin treatment to an individual
having cardiovascular disease, methods for selecting a particular
statin-based treatment regimen such as dosage and frequency of
administration of statin, or a particular form/type of statin such
as a particular pharmaceutical formulation or compound, methods for
administering an alternative, non-statin-based treatment to
individuals who are predicted to be unlikely to respond positively
to statin treatment, etc.), and methods for determining the
likelihood of experiencing toxicity or other undesirable side
effects from statin treatment, etc. The present invention also
provides methods for selecting individuals to whom a statin or
other therapeutic will be administered based on the individual's
genotype, and methods for selecting individuals for a clinical
trial of a statin or other therapeutic agent based on the genotypes
of the individuals (e.g., selecting individuals to participate in
the trial who are most likely to respond positively from the statin
treatment). Furthermore, the SNPs of the invention are useful for
predicting treatment responsiveness at any stage of CHD, including
the initial decision for prescribing treatment before the
occurrence of the first acute coronary event.
[0049] In Tables 1-2, the present invention provides gene
information, transcript sequences (SEQ ID NOS:1-517), encoded amino
acid sequences (SEQ ID NOS:518-1034), genomic sequences (SEQ ID
NOS:13,194-13,514), transcript-based context sequences (SEQ ID
NOS:1035-13,193) and genomic-based context sequences (SEQ ID
NOS:13,515-85,090) that contain the SNPs of the present invention,
and extensive SNP information that includes observed alleles,
allele frequencies, populations/ethnic groups in which alleles have
been observed, information about the type of SNP and corresponding
functional effect, and, for cSNPs, information about the encoded
polypeptide product. The transcript sequences (SEQ ID NOS:1-517),
amino acid sequences (SEQ ID NOS:518-1034), genomic sequences (SEQ
ID NOS:13,194-13,514), transcript-based SNP context sequences (SEQ
ID NOS:1035-13,193), and genomic-based SNP context sequences (SEQ
ID NOS:13,515-85,090) are also provided in the Sequence Listing
[0050] In a specific embodiment of the present invention, SNPs that
occur naturally in the human genome are provided as isolated
nucleic acid molecules. These SNPs are associated with
cardiovascular disorders, particular acute coronary events, and/or
response to statin treatment, such that they can have a variety of
uses in the diagnosis and/or treatment of cardiovascular disorders
and related pathologies and particularly in the treatment of
cardiovascular disorders with statins. One aspect of the present
invention relates to an isolated nucleic acid molecule comprising a
nucleotide sequence in which at least one nucleotide is a SNP
disclosed in Tables 3 and/or 4. In an alternative embodiment, a
nucleic acid of the invention is an amplified polynucleotide, which
is produced by amplification of a SNP-containing nucleic acid
template. In another embodiment, the invention provides for a
variant protein which is encoded by a nucleic acid molecule
containing a SNP disclosed herein.
[0051] In yet another embodiment of the invention, a reagent for
detecting a SNP in the context of its naturally-occurring flanking
nucleotide sequences (which can be, e.g., either DNA or mRNA) is
provided. In particular, such a reagent may be in the form of, for
example, a hybridization probe or an amplification primer that is
useful in the specific detection of a SNP of interest. In an
alternative embodiment, a protein detection reagent is used to
detect a variant protein that is encoded by a nucleic acid molecule
containing a SNP disclosed herein. A preferred embodiment of a
protein detection reagent is an antibody or an antigen-reactive
antibody fragment.
[0052] Various embodiments of the invention also provide kits
comprising SNP detection reagents, and methods for detecting the
SNPs disclosed herein by employing detection reagents. In a
specific embodiment, the present invention provides for a method of
identifying an individual having an increased or decreased risk of
developing a cardiovascular disorder (e.g. experiencing an acute
coronary event) by detecting the presence or absence of one or more
SNP alleles disclosed herein. The present invention also provides
methods for evaluating whether an individual is likely (or
unlikely) to respond to statin treatment of cardiovascular disease
by detecting the presence or absence of one or more SNP alleles
disclosed herein.
[0053] The nucleic acid molecules of the invention can be inserted
in an expression vector, such as to produce a variant protein in a
host cell. Thus, the present invention also provides for a vector
comprising a SNP-containing nucleic acid molecule,
genetically-engineered host cells containing the vector, and
methods for expressing a recombinant variant protein using such
host cells. In another specific embodiment, the host cells,
SNP-containing nucleic acid molecules, and/or variant proteins can
be used as targets in a method for screening and identifying
therapeutic agents or pharmaceutical compounds useful in the
treatment of cardiovascular diseases.
[0054] An aspect of this invention is a method for treating
cardiovascular disorders, particular acute coronary events, in a
human subject wherein said human subject harbors a SNP, gene,
transcript, and/or encoded protein identified in Tables 1-2, which
method comprises administering to said human subject a
therapeutically or prophylactically effective amount of one or more
agents (e.g. statins) counteracting the effects of the disorder,
such as by inhibiting (or stimulating) the activity of the gene,
transcript, and/or encoded protein identified in Tables 1-2.
[0055] Another aspect of this invention is a method for identifying
an agent useful in therapeutically or prophylactically treating
cardiovascular disorders, particular acute coronary events, in a
human subject wherein said human subject harbors a SNP, gene,
transcript, and/or encoded protein identified in Tables 1-2, which
method comprises contacting the gene, transcript, or encoded
protein with a candidate agent (e.g., statin) under conditions
suitable to allow formation of a binding complex between the gene,
transcript, or encoded protein and the candidate agent (such as a
statin) and detecting the formation of the binding complex, wherein
the presence of the complex identifies said agent.
[0056] Another aspect of this invention is a method for treating a
cardiovascular disorder in a human subject, which method
comprises:
[0057] (i) determining that said human subject harbors a SNP, gene,
transcript, and/or encoded protein identified in Tables 1-2,
and
[0058] (ii) administering to said subject a therapeutically or
prophylactically effective amount of one or more agents (such as a
statin) counteracting the effects of the disease.
[0059] Many other uses and advantages of the present invention will
be apparent to those skilled in the art upon review of the detailed
description of the preferred embodiments herein. Solely for clarity
of discussion, the invention is described in the sections below by
way of non-limiting examples.
[0060] Description of the Files Contained on the CD-R Named
CL001559CDR
[0061] The CD-R named CL001559CDR contains the following five text
(ASCII) files:
[0062] 1) File SEQLIST.sub.--1559.txt provides the
Sequence-Listing. The Sequence Listing provides the transcript
sequences (SEQ ID NOS:1-517) and protein sequences (SEQ ID
NOS:518-1034) as shown in Table 1, and genomic sequences (SEQ ID
NOS:13,194-13,514) as shown in Table 2, for each gene that contains
one or more SNPs of the present invention. Also provided in the
Sequence Listing are context sequences flanking each SNP, including
both transcript-based context sequences as shown in Table 1 (SEQ ID
NOS:1035-13,193) and genomic-based context sequences as shown in
Table 2 (SEQ ID NOS:13,515-85,090). The context sequences generally
provide 100 bp upstream (5') and 100 bp downstream (3') of each
SNP, with the SNP in the middle of the context sequence, for a
total of 200 bp of context sequence surrounding each SNP. File
SEQLIST.sub.--1559.txt is 56,606 KB in size, and was created on
Nov. 18, 2004.
[0063] 2) File-TABLE1.sub.--1559.txt provides Table 1. File
TABLE1.sub.--1559.txt is 9,853 KB in size, and was created on Nov.
17, 2004.
[0064] 3) File TABLE2.sub.--1559.txt provides Table 2. File
TABLE2.sub.--1559.txt is 52,843 KB in size, and was created on Nov.
18, 2004.
[0065] 4) File TABLE3.sub.--1559.txt provides Table 3. File
TABLE3.sub.--1559.txt is 59 KB in size, and was created on Nov. 17,
2004.
[0066] 5) File TABLE4.sub.--1559.txt provides Table 4. File
TABLE4.sub.--1559.txt is 105 KB in size, and was created on Nov.
18, 2004.
[0067] The material contained on the CD-R labeled CL001559CDR is
hereby incorporated by reference pursuant to 37 CFR 1.77(b)(4).
Description of Table 1 and Table 2
[0068] Table 1 and Table 2 (both provided on the CD-R) disclose the
SNP and associated gene/transcript/protein information of the
present invention. For each gene, Table 1 and Table 2 each provide
a header containing gene/transcript/protein information, followed
by a transcript and protein sequence (in Table 1) or genomic
sequence (in Table 2), and then SNP information regarding each SNP
found in that gene/transcript.
[0069] NOTE: SNPs may be included in both Table 1 and Table 2;
Table 1 presents the SNPs relative to their transcript sequences
and encoded protein sequences, whereas Table 2 presents the SNPs
relative to their genomic sequences (in some instances Table 2 may
also include, after the last gene sequence, genomic sequences of
one or more intergenic regions, as well as SNP context sequences
and other SNP information for any SNPs that lie within these
intergenic regions). SNPs can readily be cross-referenced between
Tables based on their hCV (or, in some instances, hDV)
identification numbers.
[0070] The gene/transcript/protein information includes:
[0071] a gene number (1 through n, where n=the total number of
genes in the Table)
[0072] a Celera hCG and UID internal identification numbers for the
gene
[0073] a Celera hCT and UID internal identification numbers for the
transcript (Table 1 only).
[0074] a public Genbank accession number (e.g., RefSeq NM number)
for the transcript (Table 1 only)
[0075] a Celera hCP and UID internal identification numbers for the
protein encoded by the hCT transcript (Table 1 only)
[0076] a public Genbank accession number (e.g., RefSeq NP number)
for the protein (Table 1 only)
[0077] an art-known gene symbol
[0078] an art-known gene/protein name
[0079] Celera genomic axis position (indicating start nucleotide
position-stop nucleotide position)
[0080] the chromosome number of the chromosome on which the gene is
located
[0081] an OMIM (Online Mendelian Inheritance in Man; Johns Hopkins
University/NCBI) public reference number for obtaining further
information regarding the medical significance of each gene
[0082] alternative gene/protein name(s) and/or symbol(s) in the
OMIM entry
[0083] NOTE: Due to the presence of alternative splice forms,
multiple transcript/protein entries can be provided for a single
gene entry in Table 1; i.e., for a single Gene Number, multiple
entries may be provided in series that differ in their
transcript/protein information and sequences.
[0084] Following the gene/transcript/protein information is a
transcript sequence and protein sequence (in Table 1), or a genomic
sequence (in Table 2), for each gene, as follows:
[0085] transcript sequence (Table 1 only) (corresponding to SEQ ID
NOS:1-517 of the Sequence Listing), with SNPs identified by their
IUB codes (transcript sequences can include 5' UTR, protein coding,
and 3' UTR regions). (NOTE: If there are differences between the
nucleotide sequence of the hCT transcript and the corresponding
public transcript sequence identified by the Genbank accession
number, the hCT transcript sequence (and encoded protein) is
provided, unless the public sequence is a RefSeq transcript
sequence identified by an NM number; in which case the RefSeq NM
transcript sequence (and encoded protein) is provided. However,
whether the hCT transcript or RefSeq NM transcript is used as the
transcript sequence, the disclosed SNPs are represented by their
IUB codes within the transcript.)
[0086] the encoded protein sequence (Table 1 only) (corresponding
to SEQ ID, NOS:518-1034 of the Sequence Listing)
[0087] the genomic sequence of the gene (Table 2 only), including 6
kb on each side of the gene boundaries (i.e., 6 kb on the 5' side
of the gene plus 6 kb on the 3' side of the gene) (corresponding to
SEQ ID NOS:13,194-13,514 of the Sequence Listing).
[0088] After the last gene sequence, Table 2 may include additional
genomic sequences of intergenic regions (in such instances, these
sequences are identified as "Intergenic region:" followed by a
numerical identification number), as well as SNP context sequences
and other SNP information for any SNPs that lie within each
intergenic region (and such SNPs are identified as "INTERGENIC" for
SNP type).
[0089] NOTE: The transcript, protein, and transcript-based SNP
context sequences are provided in both Table 1 and in the Sequence
Listing. The genomic and genomic-based SNP context sequences are
provided in both Table 2 and in the Sequence Listing. SEQ ID NOS
are indicated in Table 1 for each transcript sequence (SEQ ID
NOS:1-517), protein sequence (SEQ ID NOS:518-1034), and
transcript-based SNP context sequence (SEQ ID NOS:1035-13,193), and
SEQ ID NOS are indicated in Table 2 for each genomic sequence (SEQ
ID NOS:13,194-13,514), and genomic-based SNP context sequence (SEQ
ID NOS:13,515-85,090).
[0090] The SNP information includes:
[0091] context sequence (taken from the transcript sequence in
Table 1, and taken from the genomic sequence in Table 2) with the
SNP represented by its IUB code, including 100 bp upstream (5') of
the SNP position plus 100 bp downstream (3') of the SNP position
(the transcript-based SNP context sequences in Table 1 are provided
in the Sequence Listing as SEQ ID NOS:1035-13,193; the
genomic-based SNP context sequences in Table 2 are provided in the
Sequence Listing as SEQ ID NOS:13,515-85,090).
[0092] Celera hCV internal identification number for the SNP (in
some instances, an "hDV" number is given instead of an "hCV"
number)
[0093] SNP position [position of the SNP within the given
transcript sequence (Table 1) or within the given genomic sequence
(Table 2)]
[0094] SNP source (may include any combination of one or more of
the following five codes, depending on which internal sequencing
projects and/or public databases the SNP has been observed in:
"Applera"=SNP observed during the re-sequencing of genes and
regulatory regions of 39 individuals, "Celera"=SNP observed-during
shotgun sequencing and assembly of the Celera human genome
sequence, "Celera Diagnostics"=SNP observed during re-sequencing of
nucleic acid samples from individuals who have cardiovascular
disorders (e.g., experienced an acute coronary event), and/or have
undergone statin treatment, "dbSNP"=SNP observed in the dbSNP
public database, "HGBASE"=SNP observed in the HGBASE public
database, "HGMD"=SNP observed in the Human Gene Mutation Database
(HGMD) public database, "HapMap"=SNP observed in the International
HapMap Project public database, "CSNP"=SNP observed in an internal
Applied Biosystems (Foster City, Calif.) database of coding SNPS
(cSNPs)) (NOTE: multiple "Applera" source entries for a single SNP
indicate that the same SNP was covered by multiple overlapping
amplification products and the re-sequencing results (e.g.,
observed allele counts) from each of these amplification products
is being provided)
[0095] Population/allele/allele count information in the format of
[population] (first_allele, count.vertline.second_allele,
count)population2(first_allele, count.vertline.second_allele,
count) total (first_allele, total count.vertline.second_allele,
total count)]. The information in this field includes
populations/ethnic groups in which particular SNP alleles have been
observed ("cau"=Caucasian, "his"=Hispanic, "chn"=Chinese, and
"afr"=African-American, "jpn"=Japanese, "ind"=Indian,
"mex"=Mexican, "ain"="American Indian, "cra"=Celera donor,
"no_pop"=no population information available), identified SNP
alleles, and observed allele counts (within each population group
and total allele counts), where available ["-" in the allele field
represents a deletion allele of an insertion/deletion ("indel")
polymorphism (in which case the corresponding insertion allele,
which may be comprised of one or more nucleotides, is indicated in
the allele field on the opposite side of the ".vertline."); "-" in
the count field indicates that allele count information is not
available]. For certain SNPs from the public dbSNP database,
population/ethnic information is indicated as follows (this
population information is publicly available in dbSNP):
"HISP1"=:humanindividual.DNA (anonymized samples) from 23
individuals of self-described HISPANIC heritage; "PAC1"=human
individual DNA (anonymized samples) from 24 individuals of
self-described PACIFIC RIM heritage; "CAUC1"=human individual DNA
(anonymized samples) from 31 individuals of self-described
CAUCASIAN heritage; "AFR1"=human individual DNA (anonymized
samples) from 24 individuals of self-described AFRICAN/AFRICAN
AMERICAN heritage; "P1"=human individual DNA (anonymized samples)
from 102 individuals of self-described heritage; "PA130299515";
"SC.sub.--12_A"=SANGER 12 DNAs of Asian origin from Corielle cell
repositories, 6 of which are male and 6 female;
"SC.sub.--12_C"=SANGER 12 DNAs of Caucasian origin from Corielle
cell repositories from the CEPH/UTAH library. Six male and 6
female; "SC.sub.--12_AA"=SANGER 12 DNAs of African-American origin
from Corielle cell repositories 6 of which are male and 6 female;
"SC.sub.--95_C"=SANGER 95 DNAs of Caucasian origin from Corielle
cell repositories from the CEPH/UTAH library; and
"SC.sub.--12_A"=Caucasians-1- 2 DNAs from Corielle cell
repositories that are from the CEPH/UTAH library. Six male and 6
female.
[0096] NOTE: For SNPs of "Applera" SNP source, genes/regulatory
regions of 39 individuals (20 Caucasians and 19 African Americans)
were re-sequenced and, since each SNP position is represented by
two chromosomes in each individual (with the exception of SNPs on X
and Y chromosomes in males, for which each SNP position is
represented by a single chromosome), up to 78 chromosomes were
genotyped for each SNP position. Thus, the sum of the
African-American ("afr") allele counts is up to 38, the sum of the
Caucasian allele counts ("cau") is up to 40, and the total sum of
all allele counts is up to 78.
[0097] (NOTE: semicolons separate population/allele/count
information corresponding to each indicated SNP source; i.e., if
four SNP sources are indicated, such as "Celera", "dbSNP",
"HGBASE", and "HGMD", then population/allele/count information is
provided in four groups which are separated by semicolons and
listed in the same order as the listing of SNP sources, with each
population/allele/count information group corresponding to the
respective SNP source based on order; thus, in this example, the
first population/allele/count information group would correspond to
the first listed SNP source (Celera) and the third
population/allele/count information group separated by semicolons
would correspond to the third listed SNP source (HGBASE); if
population/allele/count information is not available for any
particular SNP source, then a pair of semicolons is still inserted
as a place-holder in order to maintain correspondence between the
list of SNP sources and the corresponding listing of
population/allele/count information)
[0098] SNP type (e.g., location within gene/transcript and/or
predicted functional effect) ["MIS-SENSE MUTATION"=SNP causes a
change in the encoded amino acid (i.e., a non-synonymous coding
SNP); "SILENT MUTATION"=SNP does not cause a change in the encoded
amino acid (i.e., a synonymous coding SNP); "STOP CODON
MUTATION"=SNP is located in a stop codon; "NONSENSE MUTATION"=SNP
creates or destroys a stop codon; "UTR 5"=SNP is located in a 5'
UTR of a transcript; "UTR 3"=SNP is located in a 3' UTR of a
transcript; "PUTATIVE UTR 5"=SNP is located in a putative 5' UTR;
"PUTATIVE UTR 3"=SNP is located in a putative 3' UTR; "DONOR SPLICE
SITE"=SNP is located in a donor splice site (5' intron boundary);
"ACCEPTOR SPLICE SITE"=SNP is located in an acceptor splice site
(3' intron boundary); "CODING REGION"=SNP is located in a
protein-coding region of the transcript; "EXON"=SNP is located in
an exon; "INTRON"=SNP is located in an intron; "hmCS"=SNP is
located in a human-mouse conserved segment; "TFBS"=SNP is located
in a transcription factor binding site; "UNKNOWN"=SNP type is not
defined; "INTERGENIC"=SNP is intergenic, i.e., outside of any gene
boundary]
[0099] Protein coding information (Table 1 only), where relevant,
in the format of [protein SEQ ID NO:#, amino acid position, (amino
acid-1, codon1) (amino acid-2, codon2)]. The information in this
field includes SEQ ID NO of the encoded protein sequence, position
of the amino acid residue within the protein identified by the SEQ
ID NO that is encoded by the codon containing the SNP, amino acids
(represented by one-letter amino acid codes) that are encoded by
the alternative SNP alleles (in the case of stop codons, "X" is
used for the one-letter amino acid code), and alternative codons
containing the alternative SNP nucleotides which encode the amino
acid residues (thus, for example, for missense mutation-type SNPs,
at least two different amino acids and at, least two different
codons are generally indicated; for silent mutation-type SNPS, one
amino acid and at least two different codons are generally
indicated, etc.). In instances where the SNP is located outside of
a protein coding region (e.g., in a UTR region), "None" is
indicated following the protein SEQ ID NO.
[0100] Description of Table 3 and Table 4
[0101] Tables 3 and 4 (both provided on the CD-R) provide a list of
a subset of SNPs from Table 1 (in the case of Table 3) or Table 2
(in the case of Table 4) for which the SNP source falls into one of
the following three categories: 1) SNPs for which the SNP source is
only "Applera" and none other, 2) SNPs for which the SNP source is
only "Celera Diagnostics" and none other, and 3) SNPs for which the
SNP source is both "Applera" and "Celera Diagnostics" but none
other.
[0102] These SNPs have not been observed in any of the public
databases (dbSNP, HGBASE, and HGMD), and were also not observed
during shotgun sequencing and assembly of the Celera human genome
sequence (i.e., "Celera" SNP source). Tables 3 and 4 provide the
hCV identification number (or hDV identification number for SNPs
having "Celera Diagnostics" SNP source) and the SEQ ID NO of the
context sequence for each of these SNPs.
[0103] Description of Table 5
[0104] Table 5 provides sequences (SEQ ID NOS:85,091-85,702) of
primers that have been synthesized and used in the laboratory to
carry out allele-specific PCR reactions in order to assay the SNPs
disclosed in Tables 6-15 during the course of association studies
to verify the association of these SNPs with cardiovascular
disorders (particularly acute coronary events such as myocardial
infarction and stroke) and statin response.
[0105] Table 5 provides the following:
[0106] the column labeled "Marker" provides an hCV identification
number for each SNP site
[0107] the column labeled "Alleles" designates the two alternative
alleles at the SNP site identified by the hCV identification number
that are targeted by the allele-specific primers (the
allele-specific primers are shown as "Sequence A" and "Sequence B")
[NOTE: Alleles may be presented in Table 5 based on a different
orientation (i.e., the reverse complement) relative to how the same
alleles are presented in Tables 1-2].
[0108] the column labeled "Sequence A (allele-specific primer)"
provides an allele-specific primer that is specific for an allele
designated in the "Alleles" column
[0109] the column labeled "Sequence B (allele-specific primer)"
provides an allele-specific primer that is specific for the other
allele designated in the "Alleles" column
[0110] the column labeled "Sequence C (common primer)" provides a
common primer that is used in conjunction with each of the
allele-specific primers (the "Sequence A" primer and the "Sequence
B" primer) and which hybridizes at a site away from the SNP
position.
[0111] All primer sequences are given in the 5' to 3'
direction.
[0112] Each of the nucleotides designated in the "Alleles" column
matches or is the reverse complement of (depending on the
orientation of the primer relative to the designated allele) the 3'
nucleotide of the allele-specific primer (either "Sequence A" or
"Sequence B") that is specific for that allele.
[0113] Description of Tables 6-15
[0114] Tables 6-15 provide results of statistical analyses for SNPs
disclosed in Tables 1-4 (SNPs can be cross-referenced between
tables based on their hCV identification numbers), and the
association of these SNPs with various cardiovascular disease
clinical endpoints or drug response traits. The statistical results
shown in Tables 6-15 provide support for the association of these
SNPs with cardiovascular disorders, particularly acute coronary
events such as myocardial infarction and stroke, and/or the
association of these SNPs with response to statin treatment, such
as statin treatment administered as a preventive treatment for
acute coronary events. For example, the statistical results
provided in Tables 6-15 show that the association of these SNPs
with acute coronary events and/or response to statin treatment is
supported by p-values <0.05 in an allelic association test.
[0115] Table 6 presents statistical associations of SNPs with
various trial endpoints. Table 7 presents statistical associations
of SNPs with clinical variables such as lab tests at base line and
at the end of a trial. Table 8 presents statistical associations of
SNPs with cardiovascular endpoints prevention (SNPs predictive of
response to statins as a preventive treatment). Table 9 shows the
association of SNPs with adverse coronary events such as RMI and
stroke in CARE samples. This association of certain SNPs with
adverse coronary events could also be replicated by comparing
associations in samples between initial analysis and replication
(see example section). Table 10 shows association of SNPs
predictive of statin response with cardiovascular events prevention
under statin treatment, justified by stepwise logistic regression
analysis with an adjustment for conventional risk factors such as
age, sex, smoking status, baseline glucose, levels, body mass index
(BMI), history of hypertension, etc. (this adjustment supports
independence of the SNP association from conventional risk
factors). The statistical results provided in Table 11 demonstrate
association of a SNP in the CD6 gene that is predictive of statin
response in the prevention of RMI, justified as a significant
difference in risk associated with the SNP between placebo and
Statin treated strata (Breslow Day p-values <0.05). Table 11
presents the results observed in samples taken from both the CARE
and WOSCOP studies. In both studies the individuals homozygous for
the minor allele were statistically different from heterozygous and
major allele homozygous individuals in the pravastatin treated
group vs. the placebo treated group. Table 12 shows the association
of a SNP in the FCAR gene that is predictive of MI risk and
response to statin treatment. Individuals who participated in both
the CARE and WOSCOPS studies, who did not receive pravastatin
treatment and who were heterozygous or homozygous for the major
allele had a significantly higher risk of having an MI vs.
individuals who were homozygous for the minor allele. However,
individuals in the CARE study who were heterozygous or homozygous
for the FCAR major allele were also statistically significantly
protected by pravastatin treatment against an adverse coronary
event relative to the individuals homozygous for the minor
allele.
[0116] NOTE: SNPs can be cross-referenced between all tables herein
based on the hCV identification number of each SNP. However, eleven
of the SNPs that are included in the tables may possess two
different hCV identification numbers, as follows:
[0117] hCV15871020 is equivalent to hCV22273027
[0118] hCV15962586 is equivalent to hCV22274323
[0119] hCV16192174 is equivalent to hCV22271999.
[0120] hCV22273204 is equivalent to hCV16179443
[0121] hCV25617571 is equivalent to hCV15943347
[0122] hCV25637308 is equivalent to hCV27501445
[0123] hCV25637309 is equivalent to hCV27469009
[0124] hCV25640926 is equivalent to hCV9485713
[0125] hCV7499900 is equivalent to hCV25620145
[0126] hCV16172571 is equivalent to hCV25474627
[0127] hCV16273460 is equivalent to hCV26165616
1 Table 6 column heading Definition Public Locus Link HUGO approved
gene symbol for the gene that contains the tested SNP Marker
Internal hCV identification number for the tested SNP Stratum
Subpopulation used for analysis Phenotype Disease endpoints
(definitions of entries in this column are provided below) Overall*
Result of the Overall Score Test (chi-square test) for the logistic
Chi-square Test: regression model in which the qualitative
phenotype is a statistic/ function of SNP genotype (based on
placebo patients only) p-value SNP effect** Result of the
chi-square test of the SNP effect (based on the Chi-square Test:
logistic regression model for placebo patients only) statistic/
p-value Placebo Patients "n" is the number of placebo patients with
no rare alleles n/total(%) genotype for investigated phenotype. The
"total" is the total 0 Rare Alleles number of placebo patients with
this genotype, and "%" is the percentage of placebo patients with
this genotype. Placebo Patients "n" is the number of placebo
patients with one rare allele n/total(%) genotype for investigated
phenotype. The "total" is the total 1 Rare Allele number of placebo
patients with this genotype, and "%" is the percentage of placebo
patients with this genotype. Placebo Patients "n" is the number of
placebo patients with two rare alleles n/total(%) genotype for
investigated phenotype. The "total" is the total 2 Rare Alleles
number of placebo patients with this genotype, and "%" is the
percentage of placebo patients with this genotype. Odd Ratio (95%
Cl) "Odds ratio" indicates the odds of having this phenotype given
2 Rare Alleles vs. that genotype contains two rare alleles of a SNP
versus the odds 0 Rare Alleles of having this phenotype given a
genotype containing no rare alleles. "95% Cl" is the 95% confidence
interval. Odd Ratio (95% Cl) "Odds ratio" indicates the odds of
having this phenotype given 1 Rare Alleles vs. that genotype
contains one rare allele versus the odds of having 0 Rare Alleles
this phenotype given a genotype containing no rare alleles. "95%
Cl" is the 95% confidence interval Significance Level "Significance
Level" indicates the summary of the result of the "Overall Score
Test (chi-square test)" for the logistic regression model and the
result of the "chi-square test of the SNP effect". If both p-values
are less than 0.05, "<0.05" is indicated. If both p- values are
less than 0.005, "<0.005" is indicated.
[0128]
2 Table 7 column heading Definition Public Locus Link HUGO approved
gene symbol for the gene that contains the tested SNP Marker
Internal hCV identification number for the tested SNP Stratum
Subpopulation used for analysis Phenotype (at Clinical quantitative
variables - lab test results at baseline or Baseline) change from
baseline discharge (definitions of entries in this column are
provided below) Overall* Results of the Overall F-Test for the
analysis of variance model F-Test: in which the quantitative
phenotype is a function of SNP genotype statistic/p-value (based on
placebo patients only) SNP effect** Results of the F-test of the
SNP effect (based on the analysis of F-Test: variance model for
placebo patients only) statistic/ p-value Placebo Patients "n" is
the number of placebo patients with a tested SNP Mean (se)# (N)
genotype (zero rare alleles) and presented phenotype. "Mean" is 0
Rare Alleles the least squares estimate of the mean phenotype
result for placebo patients with this genotype. "se" is the least
squares estimate of the standard error of the mean phenotype for
placebo patients with 0 rare allele genotype Placebo Patients "n"
is the number of placebo patients with a tested SNP Mean (se)# (N)
genotype (one rare allele) and presented phenotype. Mean is the 1
Rare Allele least squares estimate of the mean phenotype result for
placebo patients with this genotype. se is the least squares
estimate of the standard error of the mean phenotype for placebo
patients 1 rare allele genotype Placebo Patients "n" is the number
of placebo patients with a tested SNP Mean (se)# (N) genotype (one
rare allele) and presented phenotype. Mean is the 2 Rare Alleles
least squares estimate of the mean phenotype result for placebo
patients with this genotype. se is the least squares estimate of
the standard error of the mean phenotype for placebo patients 2
rare alleles genotype Significance Level "Significance Level"
indicates the summary of the result of the "Overall F-Test" for the
analysis of variance model and the result of the "F-test of the SNP
effect". If both p-values are less than 0.05, "<0.05" is
indicated. If both p-values are less than 0.005, "<0.005" is
indicated.
[0129]
3 Table 8 column heading Definition Public Locus Link HUGO approved
gene symbol for the gene that contains the tested SNP Marker
Internal hCV identification number for the tested SNP Stratum
Subpopulation used for analysis Phenotype Disease endpoints
(definitions of entries in this column are provided below) Overall*
Results of the Overall Score Test (chi-square test) for the
Chi-square Test: regression model in which the qualitative
phenotype is a statistic/ function of the SNP genotype, treatment
group, and the P-value interaction between SNP genotype and
treatment group Interaction Effect** Results of the chi-square test
of the interaction between SNP Chi-square Test: genotype and
treatment group (based on the logistic regression statistic/
model). p-value 0 Rare Alleles Results for patients under
pravastatin treatment. "n" is the n/total (%) number of pravastatin
patients with no rare allele genotype and Prava the investigated
phenotype. The "total" is the total number of pravastatin patients
with this genotype. "%" is the percentage of pravastatin patients
with this genotype who had the investigated phenotype. 0 Rare
Alleles Results for patients under placebo. "n" is the number of
placebo n/total (%) patients with no rare allele genotype and
investigated phenotype. Placebo "Total" is the total number of
placebo patients with the genotype."%" is the percentage of placebo
patients with no rare allele genotype and the investigated
phenotype. 1 Rare Allele Results for patients under pravastatin
treatment. "n" is the n/total (%) number of patients under
pravastatin with one rare allele Prava genotype and the
investigated phenotype. The "total" is the total number of
pravastatin patients with the genotype. "%" is the percentage of
pravastatin patients with one rare allele genotype and the
investigated phenotype. 1 Rare Allele Results for patients on
placebo. "n" is the number of placebo n/total (%) patients with one
rare allele genotype and the investigated Placebo phenotype. The
"total" is the total number of pravastatin patients with the
genotype. "%" is the percentage of pravastatin patients with one
rare allele genotype and the investigated phenotype. 2 Rare Alleles
Results for patients under pravastatin treatment. "n" is the
n/total (%) number of patients under pravastatin with two rare
allele Prava genotype and the investigated phenotype. The "total"
is the total number of pravastatin patients with the genotype. "%"
is the percentage of pravastatin patients with two rare allele
genotypes and the investigted phenotype 2 Rare Alleles Results for
patients on placebo. "n" is the number of placebo n/total (%)
patients with two rare allele genotype and the investigated Placebo
phenotype. The "total" is the total number of pravastatin patients
with the genotype. "%" is the percentage of pravastatin patients
with two rare allele genotypes and the investigated phenotype Prava
vs Placebo Odds ratio and its 95% confidence interval for patients
with no Odds Ratio rare allele genotype, the odd ratios of having
the event given (95% Cl) pravastatin use versus the odds of having
the event on placebo 0 Rare Alleles Prava vs Placebo Odds ratio and
its 95% confidence interval for patients with one Odds Ratio rare
allele genotype, the odd ratios of having the event given (95% Cl)
pravastatin use versus the odds of having the event on placebo 1
Rare Allele Prava vs Placebo Odds ratio and its 95% confidence
interval for patients with two Odds Ratio rare alleles genotype,
the odd ratio of having the event given (95% Cl) pravastatin use
versus the odds of having the event on placebo 2 Rare Alleles
Significance Level "Significance Level" indicates the summary of
the result of the "Overall Score Test (chi-square test)" for the
regression model and the result of the "chi-square test of the
interaction". If both p-values are less than 0.05, "<0.05" is
indicated. If both p- values are less than 0.005, "<0.005" is
indicated.
[0130]
4 Table 9 column heading Definition Endpoint Endpoint measured in
study Public Locus Link HUGO approved gene symbol for the gene that
contains the tested SNP Marker Internal hCV identification number
for the SNP that is tested Genotype/ Effect seen in major
homozygous ("Maj. Hom"), minor mode homozygous ("Min Hom") or
heterozygous (Het")/recessive ("Rec") or dominant ("Dom") Strata
Indicates whether the analysis of the dataset has been stratified
by genotypes, such as major homozygote ("Maj Hom"), minor
homozygote ("Min Hom"), and heterozygote ("Het") Con- Variables
that change the marker risk estimates by .gtoreq.5% founders P risk
Significance of risk estimated by Wald Test est. RR Relative risk
95% Cl 95% confidence interval for relative risk case Number of
patients (with the corresponding genotype or mode) developed
recurrent MI or Stroke during 5 years follow up Case The allele
frequency of patients (with the corresponding AF (%) genotype or
mode) that developed recurrent MI during 6 years follow up Control
Number of patients (with the corresponding genotype or mode) that
had MI Control The allele frequency of patients (with the
corresponding AF (%) genotype or mode) that had MI Analysis 1
Statistics are based on initial analysis (see examples). Analysis 2
Statistics are based on replication analysis (see examples) Table
10 See Table footnotes and Examples section Table 11 See Table
footnotes and Examples section Table 12 See Table footnotes and
Examples section Table 13 See Table footnotes and Examples section
Table 14 See Table footnotes and Examples section Table 15 See
Table footnotes and Examples section
[0131] Definition of Entries in the "Phenotype" Column of Table
6:
5 Phenotype Definite Nonfatal MI Fatal CHD/Definite Nonfatal MI
CARE MI: Q-Wave MI MI (Fatal/Nonfatal) Fatal Coronary Heart Disease
Total Mortality Cardiovascular Mortality Fatal Atherosclerotic
Cardiovascular Disease History of Diabetes Stroke Percutaneous
Transluminal Coronary Angioplasty Hosp. for Cardiovascular Disease
Fatal/Nonfatal Cerebrovascular Disease Hosp. for Unstable Angina
Total Cardiovascular Disease Events Any Report of Stroke Prior to
or During CARE Any Report of Stroke During CARE 1st Stroke Occurred
During CARE Fatal/Nonfatal MI (def & prob) History of
Congestive Heart Failure (AE) Nonfatal MI (Probable/Definite)
Nonfatal MI (def & prob) Fatal/Nonfatal Atherosclerotic CV
Disease Coronary Artery Bypass Graft Coronary Artery Bypass or
Revascularization Congestive Heart Failure Hosp. for Peripheral
Arterial Disease History of Coronary Artery Bypass Graft CARE MI:
Non Q-Wave MI Fatal MI History of Percutaneous Transluminal
Coronary Angioplasty Catheterization Total Coronary Heart Disease
Events History of Angina Pectoris More Than 1 Prior MI Family
History of CV Disease History of Hypertension History of Stroke
[0132] Definition of Entries in the "Phenotype (at Baseline)"
Column of Table 7:
6 Phenotype (at Baseline) Change from Baseline in Urinary Glucose
(at LOCF) Change from Baseline in Urinary Glucose (at LOCF)
Baseline HDL Baseline Lymphocytes, Absolute (k/cumm) Baseline
HDL
[0133] Definition of Entries in the "Phenotype" Column of Table
8:
7 Phenotype Catheterization Nonfatal MI (Probable/Definite)
Nonfatal MI (def & prob) Family History of CV Disease MI
(Fatal/Nonfatal) Definite Nonfatal MI Fatal/Nonfatal MI (def &
prob) Fatal Coronary Heart Disease Total Mortality Total Coronary
Heart Disease Events Cardiovascular Mortality Fatal Atherosclerotic
Cardiovascular Disease Fatal/Nonfatal Atherosclerotic CV Disease
Hosp. for Cardiovascular Disease Total Cardiovascular Disease
Events History of Angina Pectoris Fatal CHD/Definite Nonfatal MI
Coronary Artery Bypass or Revascularization Coronary Artery Bypass
Graft Hospitalization for Unstable Angina Percutaneous Transluminal
Coronary Angioplasty Fatal/Nonfatal Cerebrovascular Disease
Stroke
DESCRIPTION OF THE FIGURE
[0134] FIG. 1 provides a diagrammatic representation of a
computer-based discovery system containing the SNP information of
the present invention in computer readable form.
DETAILED DESCRIPTION OF THE INVENTION
[0135] The present invention provides SNPs associated with
cardiovascular disorders, particularly acute coronary events such
as myocardial infarction and stroke (including recurrent acute
coronary events such as recurrent myocardial infarction), and SNPs
that are associated with an individual's responsiveness to
therapeutic agents, particularly lipid-lowering compounds such as
statins, that are used for the treatment (including preventive
treatment) of cardiovascular disorders, particularly treatment of
acute coronary events. The present invention further provides
nucleic acid molecules containing these SNPs, methods and reagents
for the detection of the SNPs disclosed herein, uses of these SNPs
for the development of detection reagents, and assays or kits that
utilize such reagents. The acute coronary event-associated SNPs and
statin response-associated SNPs disclosed herein are useful for
diagnosing, screening for, and evaluating an individual's increased
or decreased risk of developing cardiovascular disease as well as
their responsiveness to drug treatment. Furthermore, such SNPs and
their encoded products are useful targets for the development of
therapeutic agents.
[0136] A large number of SNPs have been identified from
re-sequencing DNA from 39 individuals, and they are indicated as
"Applera" SNP source in Tables 1-2. Their allele frequencies
observed in each of the Caucasian and African-American ethnic
groups are provided. Additional SNPs included herein were
previously identified during shotgun sequencing and assembly of the
human genome, and they are indicated as "Celera" SNP source in
Tables 1-2. Furthermore, the information provided in Table 1-2,
particularly the allele frequency information obtained from 39
individuals and the identification of the precise position of each
SNP within each gene/transcript, allows haplotypes (i.e., groups of
SNPs that are co-inherited) to be readily inferred. The present
invention encompasses SNP haplotypes, as well as individual
SNPs.
[0137] Thus, the present invention provides individual SNPs
associated with cardiovascular disorders, particularly acute
coronary events, and SNPs associated with responsiveness to statin
for the treatment of cardiovascular diseases, as well as
combinations of SNPs and haplotypes in genetic regions associated
with cardiovascular disorders and/or statin response,
polymorphic/variant transcript sequences (SEQ ID NOS:1-517) and
genomic sequences (SEQ ID NOS:13,194-13,514) containing SNPs,
encoded amino acid sequences (SEQ ID NOS: 518-1034), and both
transcript-based SNP context sequences (SEQ ID NOS: 1035-13,193)
and genomic-based SNP context sequences (SEQ ID NOS: 13,515-85,090)
(transcript sequences, protein sequences, and transcript-based SNP
context sequences are provided in Table 1 and the Sequence Listing;
genomic sequences and genomic-based SNP context sequences are
provided in Table 2 and the Sequence Listing), methods of detecting
these polymorphisms in a test sample, methods of determining the
risk of an individual of having or developing a cardiovascular
disorder such as an acute coronary event, methods of determining
response to statin treatment of cardiovascular disease, methods of
screening for compounds useful for treating cardiovascular disease,
compounds identified by these screening methods, methods of using
the disclosed SNPs to select a treatment strategy, methods of
treating a disorder associated with a variant gene/protein (i.e.,
therapeutic" methods), and methods of using the SNPs of the present
invention for human identification.
[0138] Since cardiovascular disorders/diseases share certain
similar features that may be due to common genetic factors that are
involved in their underlying mechanisms, the SNPs identified herein
as being particularly associated with acute coronary events and/or
statin response may be used as diagnostic/prognostic markers or
therapeutic targets for a broad spectrum of cardiovascular diseases
such as coronary heart disease (CHD), atherosclerosis,
cerebrovascular disease, congestive heart failure, congenital heart
disease, and pathologies and symptoms associated with various heart
diseases (e.g., angina, hypertension), as well as for predicting
responses to drugs other than statins that are used to treat
cardiovascular diseases.
[0139] The present invention further provides methods for selecting
or formulating a treatment regimen (e.g., methods for determining
whether or not to administer statin treatment to an individual
having cardiovascular disease, methods for selecting a particular
statin-based treatment regimen such as dosage and frequency of
administration of statin, or a particular form/type of statin such
as a particular pharmaceutical formulation or compound, methods for
administering an alternative, non-statin-based treatment to
individuals who are predicted to be unlikely to respond positively
to statin treatment, etc.), and methods for determining the
likelihood of experiencing toxicity or other undesirable side
effects from statin treatment, etc. The present invention also
provides methods for selecting individuals to whom a statin or
other therapeutic will be administered based on the individual's
genotype, and methods for selecting individuals for a clinical
trial of a statin or other therapeutic agent based on the genotypes
of the individuals (e.g., selecting individuals to participate in
the trial who are most likely to respond positively from the statin
treatment).
[0140] The present invention provides novel SNPs associated with
cardiovascular disorders and/or response to statin treatment, as
well as SNPs that were previously known in the art, but were not
previously known to be associated with cardiovascular disorders
and/or statin response. Accordingly, the present invention provides
novel compositions and methods based on the novel SNPs disclosed
herein, and also provides novel methods of using the known, but
previously unassociated, SNPs in methods relating to evaluating an
individual's likelihood of having or developing a cardiovascular
disorder, predicting; the likelihood of an individual experiencing
a reoccurrence of a cardiovascular disorder (e.g., experiencing
recurrent myocardial infarctions), prognosing the severity of a
cardiovascular disorder in an individual, or prognosing an
individual's recovery from a cardiovascular disorder, and methods
relating to evaluating an individual's likelihood of responding to
statin treatment for cardiovascular disease. In Tables 1-2, known
SNPs are identified based on the public database in which they have
been observed, which is indicated as one or more of the following
SNP types: "dbSNP"=SNP observed in dbSNP, "HGBASE"=SNP observed in
HGBASE, and "HGMD"=SNP observed in the Human Gene Mutation Database
(HGMD). Novel SNPs for which the SNP source is only "Applera" and
none other, i.e., those that have not been observed in any public
databases and which were also not observed during shotgun
sequencing and assembly of the Celera human genome sequence (i.e.,
"Celera" SNP source), are indicated in Tables 3-4.
[0141] Particular SNP alleles of the present invention can be
associated with either an increased risk of having a cardiovascular
disorder (e.g., experiencing an acute coronary event) or of
responding to statin treatment of cardiovascular disease, or a
decreased likelihood of having a cardiovascular disorder or of
responding to statin treatment of cardiovascular disease. Thus,
whereas certain SNPs (or their encoded products) can be assayed to
determine whether an individual possesses a SNP allele that is
indicative of an increased likelihood of experiencing a coronary
event or of responding to statin treatment, other SNPs (or their
encoded products) can be assayed to determine whether an individual
possesses a SNP allele that is indicative of a decreased likelihood
of experiencing a coronary event or of responding to statin
treatment. Similarly, particular SNP alleles of the present
invention can be associated with either an increased or decreased
likelihood of having a reoccurrence of a cardiovascular disorder,
of fully recovering from a cardiovascular disorder, of experiencing
toxic effects from a particular treatment or therapeutic compound,
etc. The term "altered" may be used herein to encompass either of
these two possibilities (e.g., an increased or a decreased
risk/likelihood). SNP alleles that are associated with a decreased
risk of having or developing a cardiovascular disorder such as
myocardial infarction may be referred to as "protective" alleles,
and SNP alleles that are associated with an increased risk of
having or developing a cardiovascular disorder may be referred to
as "susceptibility" alleles, "risk" alleles, or "risk factors".
[0142] Those skilled in the art will readily recognize that nucleic
acid molecules may be double-stranded molecules and that reference
to a particular site on one strand refers, as well, to the
corresponding site on a complementary strand. In defining a SNP
position, SNP allele, or nucleotide sequence, reference to an
adenine, a thymine (uridine), a cytosine, or a guanine at a
particular site on one strand of a nucleic acid molecule also
defines the thymine (uridine), adenine, guanine, or cytosine
(respectively) at the corresponding site on a complementary strand
of the nucleic acid molecule. Thus, reference may be made to either
strand in order to refer to a particular SNP position, SNP allele,
or nucleotide sequence. Probes and primers, may be designed to
hybridize to either strand and SNP genotyping methods disclosed
herein may generally target either strand. Throughout the
specification, in identifying a SNP position, reference is
generally made to the protein-encoding strand, only for the purpose
of convenience.
[0143] References to variant peptides, polypeptides, or proteins of
the present invention include peptides, polypeptides, proteins, or
fragments thereof, that contain at least one amino acid residue
that differs from the corresponding amino acid sequence of the
art-known peptide/polypeptide/protein (the art-known protein may be
interchangeably referred to as the "wild-type", "reference", or
"normal" protein). Such variant peptides/polypeptides/proteins can
result from a codon change caused by a nonsynonymous nucleotide
substitution at a protein-coding SNP position (i.e., a missense
mutation) disclosed by the present invention. Variant
peptides/polypeptides/proteins of the present invention can also
result from a nonsense mutation, i.e. a SNP that creates a
premature stop codon, a SNP that generates a read-through mutation
by abolishing a stop codon, or due to any SNP disclosed by the
present invention that otherwise alters the structure,
function/activity, or expression of a protein, such as a SNP in a
regulatory region (e.g. a promoter or enhancer) or a SNP that leads
to alternative or defective splicing, such as a SNP in an intron or
a SNP at an exon/intron boundary. As used herein, the terms
"polypeptide", "peptide", and "protein" are used
interchangeably.
[0144] Isolated Nucleic Acid Molecules And SNP Detection Reagents
& Kits
[0145] Tables 1 and 2 provide a variety of information about each
SNP of the present invention that is associated with cardiovascular
disorders (e.g., acute coronary events such as myocardial
infarction and stroke) and/or responsiveness to statin treatment,
including the transcript sequences (SEQ ID NOS:1-517), genomic
sequences (SEQ ID NOS:13,194-13,514), and protein sequences (SEQ ID
NOS:518-1034) of the encoded gene products (with the SNPs indicated
by IUB codes in the nucleic acid sequences). In addition, Tables 1
and 2 include SNP context sequences, which generally include 100
nucleotide upstream (5') plus 100 nucleotides downstream (3') of
each SNP position (SEQ ID NOS:1035-13,193 correspond to
transcript-based SNP context sequences disclosed in Table 1, and
SEQ ID NOS:13,515-85,090 correspond to genomic-based context
sequences disclosed in Table 2), the alternative nucleotides
(alleles) at each SNP position, and additional information about
the variant where relevant, such as SNP type (coding, missense,
splice site, UTR, etc.), human populations in which the SNP was
observed, observed allele frequencies, information about the
encoded protein, etc.
[0146] Isolated Nucleic Acid Molecules
[0147] The present invention provides isolated nucleic acid
molecules that contain one or more SNPs disclosed Table 1 and/or
Table 2. Preferred isolated nucleic acid molecules contain one or
more SNPs identified in Table 3 and/or Table 4. Isolated nucleic
acid molecules containing one or more SNPs disclosed in at least
one of Tables 1-4 may be interchangeably referred to throughout the
present text as "SNP-containing nucleic acid molecules". Isolated
nucleic acid molecules may optionally encode a full-length variant
protein or fragment thereof. The isolated nucleic acid molecules of
the present invention also include probes and primers (which are
described in greater detail below in the section entitled "SNP
Detection Reagents"), which may be used for assaying the disclosed
SNPs, and isolated full-length genes, transcripts, cDNA molecules,
and fragments thereof, which may be used for such purposes as
expressing an encoded protein.
[0148] As used herein, an "isolated nucleic acid molecule"
generally is one that contains a SNP of the present invention or
one that hybridizes to such molecule such as a nucleic acid with a
complementary sequence, and is separated from most other nucleic
acids present in the natural source of the nucleic acid molecule.
Moreover, an "isolated" nucleic acid molecule, such as a cDNA
molecule containing a SNP, of the present invention, can be
substantially free of other cellular material, or culture medium
when produced by recombinant techniques, or chemical precursors or
other chemicals when chemically synthesized. A nucleic acid
molecule can be fused to other coding or regulatory sequences and
still be considered "isolated". Nucleic acid molecules present in
non-human transgenic animals, which do not naturally occur in the
animal, are also considered "isolated". For example, recombinant
DNA molecules contained in a vector are considered "isolated".
Further examples of "isolated" DNA molecules include recombinant
DNA molecules maintained in heterologous host cells, and purified
(partially or substantially) DNA molecules in solution. Isolated
RNA molecules include in vivo or in vitro RNA transcripts of the
isolated SNP-containing DNA molecules of the present invention.
Isolated nucleic acid molecules according to the present invention
further include such molecules produced synthetically.
[0149] Generally, an isolated SNP-containing nucleic acid molecule
comprises one or more SNP positions disclosed by the present
invention with flanking nucleotide sequences on either side of the
SNP positions. A flanking sequence can include nucleotide residues
that are naturally associated with the SNP site and/or heterologous
nucleotide sequences. Preferably the flanking sequence is up to
about 500, 300, 100, 60, 50, 30, 25, 20, 15, 10, 8, or 4
nucleotides (or any other length in-between) on either side of a
SNP position, or as long as the full-length gene or entire
protein-coding sequence (or any portion thereof such as an exon),
especially if the SNP-containing nucleic acid molecule is to be
used to produce a protein or protein fragment.
[0150] For full-length genes and entire protein-coding sequences, a
SNP flanking sequence can be, for example, up to about 5 KB, 4 KB,
3 KB, 2 KB, 1 KB on either side of the SNP. Furthermore, in such
instances, the isolated nucleic acid molecule comprises exonic
sequences (including protein-coding and/or non-coding exonic
sequences), but may also include intronic sequences. Thus, any
protein coding sequence may be either contiguous or separated by
introns. The important point is that the nucleic acid is isolated
from remote and unimportant flanking sequences and is of
appropriate length such that it can be subjected to the specific
manipulations or uses described-herein such as recombinant protein
expression, preparation of probes and primers for assaying the SNP
position, and other uses specific to the SNP-containing nucleic
acid sequences.
[0151] An isolated SNP-containing nucleic acid molecule can
comprise, for example, a full-length gene or transcript, such as a
gene isolated from genomic DNA (e.g., by cloning or PCR
amplification), a cDNA molecule, or an mRNA transcript molecule.
Polymorphic transcript sequences are provided in Table 1 and in the
Sequence Listing (SEQ ID NOS: 1-517), and polymorphic genomic
sequences are provided in Table 2 and in the Sequence Listing (SEQ
ID NOS:13,194-13,514). Furthermore, fragments of such full-length
genes and transcripts that contain one or more SNPs disclosed
herein are also encompassed by the present invention, and such
fragments may be used, for example, to express any part of a
protein, such as a particular functional domain or an antigenic
epitope.
[0152] Thus, the present invention also encompasses fragments of
the nucleic acid sequences provided in Tables 1-2 (transcript
sequences are provided in Table 1 as SEQ ID NOS:1-517, genomic
sequences are provided in Table 2 as SEQ ID NOS:13,194-13,514,
transcript-based SNP context sequences are provided in Table 1 as
SEQ ID NO:1035-13,193, and genomic-based SNP context sequences are
provided in Table 2 as SEQ ID NO:13,515-85,090) and their
complements. A fragment typically comprises a contiguous nucleotide
sequence at least about 8 or more nucleotides, more preferably at
least about 12 or more nucleotides, and even more preferably at
least about 16 or more nucleotides. Further, a fragment could
comprise at least about 18, 20, 22, 25, 30, 40, 50, 60, 80, 100,
150, 200, 250 or 500 (or any other number in-between) nucleotides
in length. The length of the fragment will be based on its intended
use. For example, the fragment can encode epitope-bearing regions
of a variant peptide or regions of a variant peptide that differ
from the normal/wild-type protein, or can be useful as a
polynucleotide probe or primer. Such fragments can be isolated
using the nucleotide sequences provided in Table 1 and/or Table 2
for the synthesis of a polynucleotide probe. A labeled probe can
then be used, for example, to screen a cDNA library, genomic DNA
library, or mRNA to isolate nucleic acid corresponding to the
coding region. Further, primers can be used in amplification
reactions, such as for purposes of assaying one or more SNPs sites
or for cloning specific regions of a gene.
[0153] An isolated nucleic acid molecule of the present invention
further encompasses a SNP-containing polynucleotide that is the
product of any one of a variety of nucleic acid amplification
methods, which are used to increase the copy numbers of a
polynucleotide of interest in a nucleic acid sample. Such
amplification methods are well known in the art, and they include
but are not limited to, polymerase chain reaction (PCR) (U.S. Pat.
Nos. 4,683,195; and 4,683,202; PCR Technology: Principles and
Applications for DNA Amplification, ed. H. A. Erlich, Freeman
Press, NY, N.Y., 1992), ligase chain reaction (LCR) (Wu and
Wallace, Genomics 4:560, 1989; Landegren et al., Science 241:1077,
1988), strand displacement amplification (SDA) (U.S. Pat. Nos.
5,270,184; and 5,422,252), transcription-mediated amplification
(TMA) (U.S. Pat. No. 5,399,491), linked linear amplification (LLA)
(U.S. Pat. No. 6,027,923), and the like, and isothermal
amplification methods such as nucleic acid sequence based
amplification (NASBA), and self-sustained sequence replication
(Guatelli et al., Proc. Natl. Acad. Sci. USA 87: 1874, 1990). Based
on such methodologies, a person skilled in the art can readily
design primers in any suitable regions 5' and 3' to a SNP disclosed
herein. Such primers may be used to amplify DNA of any length so
long that it contains the SNP of interest in its sequence.
[0154] As used herein, an "amplified polynucleotide" of the
invention is a SNP-containing nucleic acid molecule whose amount
has been increased at least two fold by any nucleic acid
amplification method performed in vitro as compared to its starting
amount in a test sample. In other preferred embodiments, an
amplified polynucleotide is the result of at least ten fold, fifty
fold, one hundred fold, one thousand fold, or even ten thousand
fold increase as compared to its starting amount in a test sample.
In a typical PCR amplification, a polynucleotide of interest is
often amplified at least fifty thousand fold in amount over the
unamplified genomic DNA, but the precise amount of amplification
needed for an assay depends on the sensitivity of the subsequent
detection method used.
[0155] Generally, an amplified polynucleotide is at least about 16
nucleotides in length. More typically, an amplified polynucleotide
is at least about 20 nucleotides in length. In a preferred
embodiment of the invention, an amplified polynucleotide is at
least about 30 nucleotides in length. In a more preferred
embodiment of the invention, an amplified polynucleotide is at
least about 32, 40, 45, 50, or 60 nucleotides in length. In yet
another preferred embodiment of the invention, an amplified
polynucleotide is at least about 100, 200, 300, 400, or 500
nucleotides in length. While the total length of an amplified
polynucleotide of the invention can be as long as an exon, an
intron or the entire gene, where the SNP of interest resides, an
amplified product is typically up to about 1,000 nucleotides in
length (although certain amplification methods may generate
amplified products greater than 1000 nucleotides in length). More
preferably, an amplified polynucleotide is not greater than about
600-700 nucleotides in length. It is understood that irrespective
of the length of an amplified polynucleotide, a SNP of interest may
be located anywhere along its sequence.
[0156] In a specific embodiment of the invention, the amplified
product is at least about 201 nucleotides in length, comprises one
of the transcript-based context sequences or the genomic-based
context sequences shown in Tables 1-2. Such a product may have
additional sequences on its 5' end or 3' end or both. In another
embodiment, the amplified product is about 101 nucleotides in
length, and it contains a SNP disclosed herein. Preferably, the SNP
is located at the middle of the amplified product (e.g., at
position 101 in an amplified product that is 201 nucleotides in
length, or at position 51 in an amplified product that is 101
nucleotides in length), or within 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
12, 15, or 20 nucleotides from the middle of the amplified product
(however, as indicated above, the SNP of interest may be located
anywhere along the length of the amplified product).
[0157] The present invention provides isolated nucleic acid
molecules that comprise, consist of, or consist essentially of one
or more polynucleotide sequences that contain one or more SNPs
disclosed herein, complements thereof, and SNP-containing fragments
thereof.
[0158] Accordingly, the present invention provides nucleic acid
molecules that consist of any of the nucleotide sequences shown in
Table 1 and/or Table 2 (transcript sequences are provided in Table
1 as SEQ ID NOS:1-517, genomic sequences are provided in Table 2 as
SEQ ID NOS:13,194-13,514, transcript-based SNP context sequences
are provided in Table 1 as SEQ ID NO:1035-13,193, and genomic-based
SNP context sequences are provided in Table 2 as SEQ ID
NO:13,515-85,090), or any nucleic acid molecule that encodes any of
the variant proteins provided in Table 1 (SEQ ID NOS:518-1034). A
nucleic acid molecule consists of a nucleotide sequence when the
nucleotide sequence is, the complete nucleotide sequence of the
nucleic acid molecule.
[0159] The present invention further provides nucleic acid
molecules that consist essentially of any of the nucleotide
sequences shown in Table 1 and/or Table 2 (transcript sequences are
provided in Table 1 as SEQ ID NOS:1-517, genomic sequences are
provided in Table 2 as SEQ ID NOS:13,194-13,514, transcript-based
SNP context sequences are provided in Table 1 as SEQ ID
NO:1035-13,193, and genomic-based SNP context sequences are
provided in Table 2 as SEQ ID NO:13,515-85,090), or any nucleic
acid molecule that encodes any of the variant proteins provided in
Table 1 (SEQ ID NOS:518-1034). A nucleic acid molecule consists
essentially of a nucleotide sequence when such a nucleotide
sequence is present with only a few additional nucleotide residues
in the final nucleic acid molecule.
[0160] The present invention further provides nucleic acid
molecules that comprise any of the nucleotide sequences shown in
Table 1 and/or Table 2 or a SNP-containing fragment thereof
(transcript sequences are provided in Table 1 as SEQ ID NOS:1-517,
genomic sequences are provided in Table 2 as SEQ ID
NOS:13,194-13,514, transcript-based SNP context sequences are
provided in Table 1 as SEQ ID NO:1035-13,193, and genomic-based SNP
context sequences are provided in Table 2 as SEQ ID NO:
13,515-85,090), or any nucleic acid molecule that encodes any of
the variant proteins provided in Table 1 (SEQ ID NOS:518-1034). A
nucleic acid molecule comprises a nucleotide sequence when the
nucleotide sequence is at least part of the final nucleotide
sequence of the nucleic acid molecule. In such a fashion, the
nucleic acid molecule can be only the nucleotide sequence or have
additional nucleotide residues, such as residues that are naturally
associated with it or heterologous nucleotide sequences. Such a
nucleic acid molecule can have one to a few additional nucleotides
or can comprise many more additional nucleotides. A brief
description of how various types of these nucleic acid molecules
can be readily made and isolated is provided below, and such
techniques are well known to those of ordinary skill in the art
(Sambrook and Russell, 2000, Molecular Cloning: A Laboratory
Manual, Cold Spring Harbor Press, NY).
[0161] The isolated nucleic acid molecules can encode mature
proteins plus additional amino or carboxyl-terminal amino acids or
both, or amino acids interior to the mature peptide (when the
mature form has more than one peptide chain, for instance). Such
sequences may play a role in processing of a protein from precursor
to a mature form, facilitate protein trafficking, prolong or
shorten protein half-life, or facilitate manipulation of a protein
for assay or production. As generally is the case in situ, the
additional amino acids may be processed away from the mature
protein by cellular enzymes.
[0162] Thus, the isolated nucleic acid molecules include, but are
not limited to, nucleic acid molecules having a sequence encoding a
peptide alone, a sequence-encoding a mature peptide and additional
coding sequences such as a leader or secretory sequence (e.g., a
pre-pro or pro-protein sequence), a sequence encoding a mature
peptide with or without additional coding sequences, plus
additional non-coding sequences, for example introns and non-coding
5' and 3' sequences such as transcribed but untranslated sequences
that play a role in, for example, transcription, mRNA processing
(including splicing and polyadenylation signals), ribosome binding,
and/or stability of mRNA. In addition, the nucleic acid molecules
may be fused to heterologous marker sequences encoding, for
example, a peptide that facilitates purification.
[0163] Isolated nucleic acid molecules can be in the form of RNA,
such as mRNA, or in the form DNA, including cDNA and genomic DNA,
which may be obtained, for example, by molecular cloning or
produced by chemical synthetic techniques or by a combination
thereof (Sambrook and Russell, 2000, Molecular Cloning: A
Laboratory Manual, Cold Spring Harbor Press, NY). Furthermore,
isolated nucleic acid molecules, particularly SNP detection
reagents such as probes and primers, can also be partially or
completely in the form of one or more types of nucleic acid
analogs, such as peptide nucleic acid (PNA) (U.S. Pat. Nos.
5,539,082; 5,527,675; 5,623,049; 5,714,331). The nucleic acid,
especially DNA, can be double-stranded or single-stranded.
Single-stranded nucleic acid can be the coding strand (sense
strand) or the complementary non-coding strand (anti-sense strand).
DNA, RNA, or PNA segments can be assembled, for example, from
fragments of the human genome (in the case of DNA or RNA) or single
nucleotides, short oligonucleotide linkers, or from a series of
oligonucleotides, to provide a synthetic nucleic acid molecule.
Nucleic acid molecules can be readily synthesized using the
sequences provided herein as a reference; oligonucleotide and PNA
oligomer synthesis techniques are well known in the art (see, e.g.,
Corey, "Peptide nucleic acids: expanding the scope of nucleic acid
recognition", Trends Biotechnol. 1997 June; 15(6):224-9, and Hyrup
et al., "Peptide nucleic acids (PNA): synthesis, properties and
potential applications", Bioorg Med Chem. 1996 January; 4(1):5-23).
Furthermore, large-scale automated oligonucleotide/PNA synthesis
(including synthesis on an array or bead surface or other solid
support) can readily be accomplished using commercially available
nucleic acid synthesizers, such as the Applied Biosystems (Foster
City, Calif.) 3900 High-Throughput DNA Synthesizer or Expedite 8909
Nucleic Acid Synthesis System, and the sequence information
provided herein.
[0164] The present invention encompasses nucleic acid analogs that
contain modified, synthetic, or non-naturally occurring nucleotides
or structural-elements or other alternative/modified nucleic acid
chemistries known in the art. Such nucleic acid analogs are useful,
for example, as detection reagents (e.g., primers/probes) for
detecting one or more SNPs identified in Table 1 and/or Table 2.
Furthermore, kits/systems (such as beads, arrays, etc.) that
include these analogs are also encompassed by the present
invention. For example, PNA oligomers that are based on the
polymorphic sequences of the present invention are specifically
contemplated. PNA oligomers are analogs of DNA in which the
phosphate backbone is replaced with a peptide-like backbone
(Lagriffoul et al., Bioorganic & Medicinal Chemistry Letters,
4: 1081-1082 (1994), Petersen et al., Bioorganic & Medicinal
Chemistry Letters, 6: 793-796 (1996), Kumar et al., Organic Letters
3(9): 1269-1272 (2001), WO96/04000). PNA hybridizes to
complementary RNA or DNA with higher affinity and specificity than
conventional oligonucleotides and oligonucleotide analogs. The
properties of PNA enable novel molecular biology and biochemistry
applications unachievable with traditional oligonucleotides and
peptides.
[0165] Additional examples of nucleic acid modifications that
improve the binding properties and/or stability of a nucleic acid
include the use of base analogs such as inosine, intercalators
(U.S. Pat. No. 4,835,263) and the minor groove binders (U.S. Pat.
No. 5,801,115). Thus, references herein to nucleic acid molecules,
SNP-containing nucleic acid molecules, SNP detection reagents
(e.g., probes and primers), oligonucleotides/polynucleotides
include PNA oligomers and other nucleic acid analogs. Other
examples of nucleic acid analogs and alternative/modified nucleic
acid chemistries known in the art are described in Current
Protocols in Nucleic Acid Chemistry, John Wiley & Sons, N.Y.
(2002).
[0166] The present invention further provides nucleic acid
molecules that encode fragments of the variant polypeptides
disclosed herein as well as nucleic acid molecules that encode
obvious variants of such variant polypeptides. Such nucleic acid
molecules may be naturally occurring, such as paralogs (different
locus) and orthologs (different organism), or may be constructed by
recombinant DNA methods or by chemical synthesis. Non-naturally
occurring variants may be made by mutagenesis techniques, including
those applied to nucleic acid molecules, cells, or organisms.
Accordingly, the variants can contain nucleotide substitutions,
deletions, inversions and insertions (in addition to the SNPs
disclosed in Tables 1-2). Variation can occur in either or both the
coding and non-coding regions. The variations can produce
conservative and/or non-conservative amino acid substitutions.
[0167] Further variants of the nucleic acid molecules disclosed in
Tables 1-2, such as naturally occurring allelic variants (as well
as orthologs and paralogs) and synthetic variants produced by
mutagenesis techniques, can be identified and/or produced using
methods well known in the art. Such further variants can comprise a
nucleotide sequence that shares at least 70-80%, 80-85%, 85-90%,
91%, 92%, 93%; 94%, 95%, 96%, 97%, 98%, or 99% sequence identity
with a nucleic acid sequence disclosed in Table 1 and/or Table 2
(or a fragment thereof) and that includes a novel SNP allele
disclosed in Table 1 and/or Table 2. Further, variants can comprise
a nucleotide sequence that encodes a polypeptide that shares at
least 70-80%, 80-85%, 85-90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%,
98%, or 99% sequence identity with a polypeptide sequence disclosed
in Table 1 (or a fragment thereof) and that includes a novel SNP
allele disclosed in Table 1 and/or Table 2. Thus, an aspect of the
present invention that is specifically contemplated are isolated
nucleic acid molecules that have a certain degree of sequence
variation compared with the sequences shown in Tables 1-2, but that
contain a novel SNP allele disclosed herein. In other words, as
long as an isolated nucleic acid molecule contains a novel SNP
allele disclosed herein, other portions of the nucleic acid
molecule that flank the novel SNP allele can vary to some degree
from the specific transcript, genomic, and context sequences shown
in Tables 1-2, and can encode a polypeptide that varies to some
degree from the specific polypeptide sequences shown in Table
1.
[0168] To determine the percent identity of two amino acid
sequences or two nucleotide sequences of two molecules that share
sequence homology, the sequences are aligned for optimal comparison
purposes (e.g., gaps can be introduced in one or both of a first
and a second aminoacid or nucleic acid sequence for optimal
alignment and non-homologous sequences can be disregarded for
comparison purposes). In a preferred embodiment, at least 30%, 40%,
50%, 60%, 70%, 80%, or 90% or more of the length of a reference
sequence is aligned for comparison purposes. The amino acid
residues or nucleotides at corresponding amino acid positions or
nucleotide positions are then compared. When a position in the
first sequence is occupied by the same amino acid residue or
nucleotide as the corresponding position in the second sequence,
then the molecules are identical at that position (as used herein,
amino acid or nucleic acid "identity" is equivalent to amino acid
or nucleic acid "homology"). The percent identity between the two
sequences is a function of the number of identical positions shared
by the sequences, taking into account the number of gaps, and the
length of each gap, which need to be introduced for optimal
alignment of the two sequences.
[0169] The comparison of sequences and determination of percent
identity between two sequences can be accomplished using a
mathematical algorithm. (Computational Molecular Biology, Lesk, A.
M., ed., Oxford University Press, New York, 1988; Biocomputing:
Informatics and Genome Projects, Smith, D. W., ed., Academic Press,
New York, 1993; Computer Analysis of Sequence Data, Part 1,
Griffin, A. M., and Griffin, H. G., eds., Humana Press, New Jersey,
1994; Sequence Analysis in Molecular Biology, von Heinje; G.,
Academic Press, 1987; and Sequence Analysis Primer, Gribskov, M.
and Devereux, J., eds., M Stockton Press, New York, 1991). In a
preferred embodiment, the percent identity between two amino acid
sequences is determined using the Needleman and Wunsch algorithm
(J. Mol. Biol. (48):444-453 (1970)) which has been incorporated
into the GAP program in the GCG software package, using either a
Blossom 62 matrix or a PAM250 matrix, and a gap weight of 16, 14,
12, 10, 8, 6, or 4 and a length weight of 1, 2, 3, 4, 5, or 6.
[0170] In yet another preferred embodiment, the percent identity
between two nucleotide sequences is determined using the GAP
program in the GCG software package (Devereux, J., et al., Nucleic
Acids Res. 12(1):387 (1984)), using a NWSgapdna.CMP matrix and a
gap weight of 40, 50, 60, 70, or 80 and a length weight of 1, 2, 3,
4, 5, or 6. In another embodiment, the percent identity between two
amino acid or nucleotide sequences is determined using the
algorithm of E. Myers and W. Miller (CABIOS, 4:11-17 (1989) which
has been incorporated into the ALIGN program (version 2.0), using a
PAM120 weight residue table, a gap length penalty of 12, and a gap
penalty of 4.
[0171] The nucleotide and amino acid sequences of the present
invention can further be used as a "query sequence" to perform a
search against sequence databases to, for example, identify other
family members or related sequences. Such searches can be performed
using the NBLAST and XBLAST programs (version 2.0) of Altschul, et
al. (J. Mol. Biol. 215:403-10 (1990)). BLAST nucleotide searches
can be performed with the NBLAST program, score=100, wordlength=12
to obtain nucleotide sequences homologous to the nucleic acid
molecules of the invention. BLAST protein searches can be performed
with the XBLAST program, score=50, wordlength=3 to obtain amino
acid sequences homologous to the proteins of the invention. To
obtain gapped alignments for comparison purposes, Gapped BLAST can
be utilized as described in Altschul et al. (Nucleic Acids Res.
25(17):3389-3402 (1997)). When utilizing BLAST and gapped BLAST
programs, the default parameters of the respective programs (e.g.,
XBLAST and NBLAST) can be used. In addition to BLAST, examples of
other search and sequence comparison programs used in the art
include, but are not limited to, FASTA (Pearson, Methods Mol. Biol.
25, 365-389 (1994)) and KERR (Dufresne et al., Nat Biotechnol 2002
December; 20(12):1269-71). For further information regarding
bioinformatics techniques, see Current Protocols in Bioinformatics,
John Wiley & Sons, Inc., N.Y.
[0172] The present invention further provides non-coding fragments
of the nucleic acid molecules disclosed in Table 1 and/or Table 2.
Preferred non-coding fragments include, but are not limited to,
promoter sequences, enhancer sequences, intronic sequences, 5'
untranslated regions (UTRs), 3' untranslated regions, gene
modulating sequences and gene termination sequences. Such fragments
are useful, for example, in controlling heterologous gene
expression and in developing screens to identify gene-modulating
agents.
[0173] SNP Detection Reagents
[0174] In a specific aspect of the present invention, the SNPs
disclosed in Table 1 and/or Table 2, and their associated
transcript sequences (provided in Table 1 as SEQ ID NOS:1-517),
genomic sequences (provided in Table 2 as SEQ ID
NOS:13,194-13,514), and context sequences (transcript-based context
sequences are provided in Table 1 as SEQ ID NOS:1035-13,193;
genomic-based context sequences are provided in Table 2 as SEQ ID
NOS:13,515-85,090), can be used for the design of SNP detection
reagents. As used herein, a "SNP detection reagent" is a reagent
that specifically detects a specific target SNP position disclosed
herein, and that is preferably specific for a particular nucleotide
(allele) of the target SNP position (i.e., the detection reagent
preferably can differentiate between different alternative
nucleotides at a target SNP position, thereby allowing the identity
of the nucleotide present at the target SNP position to be
determined). Typically, such detection reagent hybridizes to a
target SNP-containing nucleic acid molecule by complementary
base-pairing in a sequence specific manner, and discriminates the
target variant sequence from other nucleic acid sequences such as
an art-known form in a test sample. An example of a detection
reagent is a probe that hybridizes to a target nucleic acid
containing one or more of the SNPs provided in Table 1 and/or Table
2. In a preferred embodiment, such a probe can differentiate
between nucleic acids having a particular nucleotide (allele) at a
target SNP position from other nucleic acids that have a different
nucleotide at the same target SNP position. In addition, a
detection reagent may hybridize to a specific region 5' and/or 3'
to a SNP position, particularly a region corresponding to the
context sequences provided in Table 1 and/or Table 2
(transcript-based context sequences are provided in Table 1 as SEQ
ID NOS:1035-13,193; genomic-based context sequences are provided in
Table 2 as SEQ ID NOS:13,515-85,090). Another example of a
detection reagent is a primer which acts as an initiation point of
nucleotide extension along a complementary strand of a target
polynucleotide. The SNP sequence information provided herein is
also useful for designing primers, e.g. allele-specific primers, to
amplify (e.g., using PCR) any SNP of the present invention.
[0175] In one preferred embodiment of the invention, a SNP
detection reagent is an isolated or synthetic DNA or RNA
polynucleotide probe or primer or PNA oligomer, or a combination of
DNA, RNA and/or PNA, that hybridizes to a segment of a target
nucleic acid molecule containing a SNP identified in Table 1 and/or
Table 2. A detection reagent in the form of a polynucleotide may
optionally contain modified base analogs, intercalators or minor
groove binders. Multiple detection reagents such as probes may be,
for example, affixed to a solid support (e.g., arrays or beads) or
supplied in solution (e.g., probe/primer sets for enzymatic
reactions such as PCR, RT-PCR, TaqMan assays, or primer-extension
reactions) to form a SNP detection kit.
[0176] A probe or primer typically is a substantially purified
oligonucleotide or PNA oligomer. Such oligonucleotide typically
comprises a region of complementary nucleotide sequence that
hybridizes under stringent conditions to at least about 8, 10, 12,
16, 18, 20, 22, 25, 30, 40, 50, 55, 60, 65, 70, 80, 90, 100, 120
(or any other number in-between) or more consecutive nucleotides in
a target nucleic acid molecule. Depending on the particular assay,
the consecutive nucleotides can either include the target SNP
position, or be a specific region in close enough proximity 5'
and/or 3' to the SNP position to carry out the desired assay. 25:
Other preferred primer and probe sequences can readily be
determined using the transcript sequences (SEQ ID NOS:1-517),
genomic sequences (SEQ ID NOS:13,194-13,514); and SNP context
sequences (transcript-based context sequences are provided in Table
1 as SEQ ID NOS:1035-13,193; genomic-based context sequences are
provided in Table 2 as SEQ ID NOS:13,515-85,090) disclosed in the
Sequence Listing and in Tables 1-2. It will be apparent to one of
skill in the art that such primers and probes are directly useful
as reagents for genotyping the SNPs of the present invention, and
can be incorporated into any kit/system format.
[0177] In order to produce a probe or primer specific for a target
SNP-containing sequence, the gene/transcript and/or context
sequence surrounding the SNP of interest is typically examined
using a computer algorithm which starts at the 5' or at the 3' end
of the nucleotide sequence. Typical algorithms will then identify
oligomers of defined length that are unique to the gene/SNP context
sequence, have a GC content within a range suitable for
hybridization, lack predicted secondary structure that may
interfere with hybridization, and/or possess other desired
characteristics or that lack other undesired characteristics.
[0178] A primer or probe of the present invention is typically at
least about 8 nucleotides in length. In one embodiment of the
invention, a primer or a probe is at least about 10 nucleotides in
length. In a preferred embodiment, a primer or a probe is at least
about 12 nucleotides in length. In a more preferred embodiment, a
primer or probe is at least about 16, 17, 18, 19, 20, 21, 22, 23,
24 or 25 nucleotides in length. While the maximal length of a probe
can be as long as the target sequence to be detected, depending on
the type of assay in which it is employed, it is typically less
than about 50, 60, 65, or 70 nucleotides in length. In the case of
a primer, it is typically less than about 30 nucleotides in length.
In a specific preferred embodiment of the invention, a primer or a
probe is within the length of about 18 and about 28 nucleotides.
However, in other embodiments, such as nucleic acid arrays and
other embodiments in which probes are affixed to a substrate, the
probes can be longer, such as on the order of 30-70, 75, 80, 90,
100, or more nucleotides in length (see the section below entitled
"SNP Detection Kits and Systems").
[0179] For analyzing SNPs, it may be appropriate to use
oligonucleotides specific for alternative SNP alleles. Such
oligonucleotides which detect single nucleotide variations in
target sequences may be referred to by such terms as
"allele-specific oligonucleotides", "allele-specific probes", or
"allele-specific primers". The design and use of allele-specific
probes for analyzing polymorphisms is described in, e.g., Mutation
Detection A Practical Approach, ed. Cotton et al. Oxford University
Press, 1998; Saiki et al., Nature 324, 163-166 (1986); Dattagupta,
EP235,726; and Saiki, WO 89/11548.
[0180] While the design of each allele-specific primer or probe
depends on variables such as the precise composition of the
nucleotide sequences flanking a SNP position in a target nucleic
acid molecule, and the length of the primer or probe, another
factor in the use of primers and probes is the stringency of the
condition under which the hybridization between the probe or primer
and the target sequence is performed. Higher stringency conditions
utilize buffers with lower ionic strength and/or a higher reaction
temperature, and tend to require a more perfect match between
probe/primer and a target sequence in order to form a stable
duplex. If the stringency is too high, however, hybridization may
not occur at all. In contrast, lower stringency conditions utilize
buffers with higher ionic strength and/or a lower reaction
temperature, and permit the formation of stable duplexes with more
mismatched bases between a probe/primer and a target sequence. By
way of example and not limitation, exemplary conditions for high
stringency hybridization conditions using an allele-specific probe
rate as follows: Prehybridization with a solution containing
5.times. standard saline phosphate-EDTA (SSPE), 0.5% NaDodSO.sub.4
(SDS) at 55.degree. C., and incubating probe with target nucleic
acid molecules in the same solution at the same temperature,
followed by washing with a solution containing 2.times.SSPE, and
0.1% SDS at 55.degree. C. or room temperature.
[0181] Moderate stringency hybridization conditions may be used for
allele-specific primer extension reactions with a solution
containing, e.g., about 50 mM KCl at about 46.degree. C.
Alternatively, the reaction may be carried out at an elevated
temperature such as 60.degree. C. In another embodiment, a
moderately stringent hybridization condition suitable for
oligonucleotide ligation assay (OLA) reactions wherein two probes
are ligated if they are completely complementary to the target
sequence may utilize a solution of about 100 mM KCl at a
temperature of 46.degree. C.
[0182] In a hybridization-based assay, allele-specific probes can
be designed that hybridize to a segment of target DNA from one
individual but do not hybridize to the corresponding segment from
another individual due to the presence of different polymorphic
forms (e.g., alternative SNP alleles/nucleotides) in the respective
DNA segments from the two individuals. Hybridization conditions
should be sufficiently stringent that there is a significant
detectable difference in hybridization intensity between alleles,
and preferably an essentially binary response, whereby a probe
hybridizes to only one of the alleles or significantly more
strongly to one allele. While a probe may be designed to hybridize
to a target sequence that contains a SNP site such that the SNP
site aligns anywhere along the sequence of the probe, the probe is
preferably designed to hybridize to a segment of the target
sequence such that the SNP site aligns with a central position of
the probe (e.g., a position within the probe that is at least three
nucleotides from either end of the probe). This design of probe
generally achieves good discrimination in hybridization between
different allelic forms.
[0183] In another embodiment, a probe or primer may be designed to
hybridize to a segment of target DNA such that the SNP aligns with
either the 5' most end or the 3' most end of the probe or primer.
In a specific preferred embodiment that is particularly suitable
for use in a oligonucleotide ligation assay (U.S. Pat. No.
4,988,617), the 3'most nucleotide of the probe aligns with the SNP
position in the target sequence.
[0184] Oligonucleotide probes and primers may be prepared by
methods well known in the art. Chemical synthetic methods include,
but are limited to, the phosphotriester method described by Narang
et al., 1979, Methods in Enzymology 68:90; the phosphodiester
method described by Brown et al., 1979, Methods in Enzymology
68:109, the diethylphosphoamidate method described by Beaucage et
al., 1981, Tetrahedron Letters 22:1859; and the solid support
method described in U.S. Pat. No. 4,458,066.
[0185] Allele-specific probes are often used in pairs (or, less
commonly, in sets of 3 or 4, such as if a SNP position is known to
have 3 or 4 alleles, respectively, or to assay both strands of a
nucleic acid molecule for a target SNP allele), and such pairs may
be identical except for a one nucleotide mismatch that represents
the allelic variants at the SNP position. Commonly, one member of a
pair perfectly matches a reference form of a target sequence that
has a more common SNP allele (i.e., the allele that is more
frequent in the target population) and the other member of the pair
perfectly matches a form of the target sequence that has a less
common SNP allele (i.e., the allele that is rarer in the target
population). In the case of an array, multiple pairs of probes can
be immobilized on the same support for simultaneous analysis of
multiple different polymorphisms.
[0186] In one type of PCR-based assay, an allele-specific primer
hybridizes to a region on a target nucleic acid molecule that
overlaps a SNP position and only primes amplification of an allelic
form to which the primer exhibits perfect complementarity (Gibbs,
1989, Nucleic Acid Res. 17 2427-2448). Typically, the primer's
3'-most nucleotide is aligned with and complementary to the SNP
position of the target nucleic acid molecule. This primer is used
in conjunction with a second primer that hybridizes at a distal
site. Amplification proceeds from the two primers, producing a
detectable product that indicates which allelic form is present in
the test sample. A control is usually performed with a second pair
of primers, one of which shows a single base mismatch at the
polymorphic site and the other of which exhibits perfect
complementarity to a distal site. The single-base mismatch prevents
amplification or substantially reduces amplification efficiency, so
that either no detectable product is formed or it is formed in
lower amounts or at a slower pace. The method generally works most
effectively when the mismatch is at the 3'-most position of the
oligonucleotide (i.e., the 3-most position of the oligonucleotide
aligns with the target SNP position) because this position is most
destabilizing to elongation from the primer (see, e.g.; WO
93/22456). This PCR-based assay can be utilized as part of the
TaqMan assay, described below.
[0187] In a specific embodiment of the invention, a primer of the
invention contains a sequence substantially complementary to a
segment of a target SNP-containing nucleic acid molecule except
that the primer has a mismatched nucleotide in one of the three
nucleotide positions at the 3'-most end of the primer, such that
the mismatched nucleotide does not base pair with a particular
allele at the SNP site. In a preferred embodiment, the mismatched
nucleotide in the primer is the second from the last nucleotide at
the 3'-most position of the primer. In a more preferred embodiment,
the mismatched nucleotide in the primer is the last nucleotide at
the 3'-most position of the primer.
[0188] In another embodiment of the invention, a SNP detection
reagent of the invention is labeled with a fluorogenic reporter dye
that emits a detectable signal. While the preferred reporter dye is
a fluorescent dye, any reporter dye that can be attached to a
detection reagent such as an oligonucleotide probe or primer is
suitable for use in the invention. Such dyes include, but are not
limited to, Acridine, AMCA, BODIPY, Cascade Blue, Cy2, Cy3, Cy5,
Cy7, Dabcyl, Edans, Eosin, Erythrosin, Fluorescein, 6-Fam, Tet,
Joe, Hex, Oregon Green, Rhodamine, Rhodol Green, Tamra, Rox, and
Texas Red.
[0189] In yet another embodiment of the invention, the detection
reagent may be further labeled with a quencher dye such as Tamra,
especially when the reagent is used as a self-quenching probe such
as a TaqMan (U.S. Pat. Nos. 5,210,015 and 5,538,848) or Molecular
Beacon probe (U.S. Pat. Nos. 5,118,801 and 5,312,728), or other
stemless or linear beacon probe (Livak et al., 1995, PCR Method
Appl. 4:357-362; Tyagi et al., 1996, Nature Biotechnology 14:
303-308; Nazarenko et al., 1997, Nucl. Acids Res. 25:2516-2521;
U.S. Pat. Nos. 5,866,336 and 6,117,635).
[0190] The detection reagents of the invention may also contain
other labels, including but not limited to, biotin for streptavidin
binding, hapten for antibody binding, and oligonucleotide for
binding to another complementary oligonucleotide such as pairs of
zipcodes.
[0191] The present invention also contemplates reagents that do not
contain (or that are complementary to) a SNP nucleotide identified
herein but that are used to assay-one or 3 more SNPs disclosed
herein. For example, primers that flank, but do not hybridize
directly to a target SNP position provided herein are useful in
primer extension reactions in which the primers hybridize to a
region adjacent to the target SNP position (i.e., within one or
more nucleotides from the target SNP site). During the primer
extension reaction, a primer is typically not able to extend past a
target SNP site if a particular nucleotide (allele) is present at
that target SNP site, and the primer extension product can be
detected in order to determine which SNP allele is present at the
target SNP site. For example, particular ddNTPs are typically used
in the primer extension reaction to terminate primer extension once
a ddNTP is incorporated into the extension product (a primer
extension product which includes a ddNTP at the 3'-most end of the
primer extension product, and in which the ddNTP is a nucleotide of
a SNP disclosed herein, is a composition that is specifically
contemplated by the present invention). Thus, reagents that bind to
a nucleic acid molecule in a region adjacent to a SNP site and that
are used for assaying the SNP site, even though the bound sequences
do not necessarily include the SNP site itself, are also
contemplated by the present invention.
[0192] SNP Detection Kits and Systems
[0193] A person skilled in the art will recognize that, based on
the SNP and associated sequence information disclosed herein,
detection reagents can be developed and used to assay any SNP of
the present invention individually or in combination, and such
detection reagents can be readily incorporated into one of the
established kit or system formats which are well known in the art.
The terms "kits" and "systems", as used herein in the context of
SNP detection reagents, are intended to refer to such things as
combinations of multiple SNP detection reagents, or one or more SNP
detection reagents in combination with one or more other types of
elements or components (e.g., other types of biochemical reagents,
containers, packages such as packaging intended for commercial
sale, substrates to which SNP detection reagents are attached,
electronic hardware components, etc.) Accordingly, the present
invention further provides SNP detection kit and systems, including
but unlimited to, packaged probe and primer sets (e.g., TaqMan
probe/primer sets), arrays/microarrays of nucleic acid molecules,
and beads that contain one or more probes, primers, or other
detection reagents for detecting one or more SNPs of the present
invention. The kits/systems can optionally include various
electronic hardware components; for example, arrays ("DNA chips")
and microfluidic systems ("lab-on-a-chip" systems) provided by
various manufacturers typically comprise hardware components. Other
kits/systems (e.g., probe/primer sets) may not include electronic
hardware components, but may be comprised of, for example, one or
more SNP detection reagents (along with, optionally, other
biochemical reagents) packaged in one or more containers.
[0194] In some embodiments, a SNP detection kit typically contains
one or more detection reagents and other components (e.g., a
buffer, enzymes such as DNA polymerases or ligases, chain extension
nucleotides such as deoxynucleotide triphosphates, and in the case
of Sanger-type DNA sequencing reactions, chain terminating
nucleotides, positive control sequences, negative control
sequences, and the like) necessary to carry out an assay or
reaction, such as amplification and/or detection of a
SNP-containing nucleic acid molecule. A kit may further contain
means for determining the amount of a target nucleic acid, and
means for comparing the amount with a standard, and can comprise
instructions for using the kit to detect the SNP-containing nucleic
acid molecule of interest. In one embodiment of the present
invention, kits are provided which contain the necessary reagents
to carry out one or more assays to detect one or more SNPs
disclosed herein. In a preferred embodiment of the present
invention, SNP detection kits/systems are in the form of nucleic
acid arrays, or compartmentalized kits, including
microfluidic/lab-on-a-chip systems.
[0195] SNP detection kits/systems may contain, for example, one or
more probes, or pairs of probes, that hybridize to a nucleic acid
molecule at or near each target SNP position. Multiple pairs of
allele-specific probes may be included in the kit/system to
simultaneously assay large numbers of SNPs, at least one of which
is a SNP of the present invention. In some kits/systems, the
allele-specific probes are immobilized to a substrate such as an
array or bead. For example, the same substrate can comprise
allele-specific probes for detecting at least 1; 10; 10; 1000;
10,000; 100,000 (or any other number in-between) or substantially
all of the SNPs shown in Table 1 and/or Table 2.
[0196] The terms "arrays", "microarrays", and "DNA chips" are used
herein interchangeably to refer to an array of distinct
polynucleotides affixed to a substrate, such as glass, plastic,
paper, nylon or other type of membrane, filter, chip, or any other
suitable solid support. The polynucleotides can be synthesized
directly on the substrate, or synthesized separate from the
substrate and then affixed to the substrate. In one embodiment, the
microarray is prepared and used according to the methods described
in U.S. Pat. No. 5,837,832, Chee et al., PCT application WO95/11995
(Chee et al.), Lockhart, D. J. et al. (1996; Nat. Biotech. 14:
1675-1680) and Schena, M. et al. (1996; Proc. Natl. Acad. Sci. 93:
10614-10619), all of which are incorporated herein in their
entirety by reference. In other embodiments, such arrays are
produced by the methods described by Brown et al., U.S. Pat. No.
5,807,522.
[0197] Nucleic acid arrays are reviewed in the following
references: Zammatteo et al., "New chips for molecular biology and
diagnostics", Biotechnol Annu Rev. 2002; 8:85-101; Sosnowski et
al., "Active microelectronic array system for DNA hybridization,
genotyping and pharmacogenomic applications", Psychiatr Genet. 2002
December; 12(4):181-92; Heller, "DNA microarray technology:
devices, systems, and applications", Annu Rev Biomed Eng. 2002;
4:129-53. Epub 2002 Mar. 22; Kolchinsky et al., "Analysis of SNPs
and other genomic variations using gel-based chips", Hum Mutat.
2002 April; 19(4):343-60; and McGall et al., "High-density genechip
oligonucleotide probe arrays", Adv Biochem Eng Biotechnol. 2002;
77:21-42.
[0198] Any number of probes, such as allele-specific probes, may be
implemented in an array, and each probe or pair of probes can
hybridize to a different SNP position. In the case of
polynucleotide probes, they can be synthesized at designated areas
(or synthesized separately and then affixed to designated areas) on
a substrate using a light-directed chemical process. Each DNA chip
can contain, for example, thousands to millions of individual
synthetic polynucleotide probes arranged in a grid-like pattern and
miniaturized (e.g., to the size of a dime). Preferably, probes are
attached to a solid support in an ordered, addressable array.
[0199] A microarray can be composed of a large number of unique,
single-stranded polynucleotides, usually either synthetic antisense
polynucleotides or fragments of, cDNAs, fixed to a solid support.
Typical polynucleotides are preferably about 6-601 nucleotides in
length, more preferably about 15-30 nucleotides in length, and most
preferably about 18-25 nucleotides in length. For certain types of
microarrays or other detection kits/systems, it may be preferable
to use oligonucleotides that are only about 7-20 nucleotides in
length. In other types of arrays, such as arrays used in
conjunction with chemiluminescent detection technology, preferred
probe lengths can be, for example, about 15-80 nucleotides in
length, preferably about 50-70 nucleotides in length, more
preferably about 55-65 nucleotides in length, and most preferably
about 60 nucleotides in length. The microarray or detection kit can
contain polynucleotides that cover the known 5' or 3' sequence of a
gene/transcript or target SNP site, sequential polynucleotides that
cover the full-length sequence of a gene/transcript; or unique
polynucleotides selected from particular areas along the length of
a target gene/transcript sequence, particularly areas corresponding
to one or more SNPs disclosed in Table 1 and/or Table 2.
Polynucleotides used in the microarray or detection kit can be
specific to a SNP or SNPs of interest (e.g., specific to a
particular SNP allele at a target SNP site, or specific to
particular SNP alleles at multiple different SNP sites), or
specific to a polymorphic gene/transcript or genes/transcripts of
interest.
[0200] Hybridization assays based on polynucleotide arrays rely on
the differences in hybridization stability of the probes to
perfectly matched and mismatched target sequence variants. For SNP
genotyping, it is generally preferable that stringency conditions
used in hybridization assays are high enough such that nucleic acid
molecules that differ from one another at as little as a single SNP
position can be differentiated (e.g., typical SNP hybridization
assays are designed so that hybridization will occur only if one
particular nucleotide is present at a SNP position, but will not
occur if an alternative nucleotide is present at that SNP
position). Such high stringency conditions may be preferable when
using, for example, nucleic acid arrays of allele-specific probes
for SNP detection. Such, high stringency conditions are described
in the preceding section, and are well known to those skilled in
the art and can be found in, for example, Current Protocols in
Molecular Biology, John Wiley & Sons, N.Y. (1989),
6.3.1-6.3.6.
[0201] In other embodiments, the arrays are used in conjunction
with chemiluminescent detection technology. The following patents
and patent applications, which are all hereby incorporated by
reference, provide additional information pertaining to
chemiluminescent detection: U.S. patent application Ser. Nos.
10/620,332 and 10/620,333 describe chemiluminescent approaches for
microarray detection; U.S. Pat. Nos. 6,124,478, 6,107,024,
5,994,073, 5,981,768, 5,871,938, 5,843,681, 5,800,999, and
5,773,628 describe methods and compositions of dioxetane for
performing chemiluminescent detection; and U.S. published
application U.S. 2002/0110828 discloses methods and compositions
for microarray controls.
[0202] In one embodiment of the invention, a nucleic acid array can
comprise an array of probes of about 15-25 nucleotides in length.
In further embodiments, a nucleic acid array can comprise any
number of probes, in which at least one probe is capable of
detecting one or more SNPs disclosed in Table 1 and/or Table 2,
and/or at least one probe comprises a fragment of one of the
sequences selected from the group consisting of those disclosed in
Table 1, Table 2, the Sequence Listing, and sequences complementary
thereto, said fragment comprising at least about 8 consecutive
nucleotides, preferably 10, 12, 15, 16, 18, 20, more preferably 22,
25, 30, 40, 47, 50, 55, 60, 65, 70, 80, 90, 100, or more
consecutive nucleotides (or any other number in-between) and
containing (or being complementary to) a novel SNP allele disclosed
in Table 1 and/or Table 2. In some embodiments, the nucleotide
complementary to the SNP site is within 5, 4, 3, 2, or 1 nucleotide
from the center of the probe, more preferably at the center of said
probe.
[0203] A polynucleotide probe can be synthesized on the surface of
the substrate by using a chemical coupling procedure and an ink jet
application apparatus, as described in PCT application WO95/251116
(Baldeschweiler et al.) which is incorporated herein in its
entirety by reference. In another aspect, a "gridded" array
analogous to a dot (or slot) blot may be used to arrange and link
cDNA fragments or oligonucleotides to the surface of a substrate
using a vacuum system, thermal, UV, mechanical or chemical bonding
procedures. An array, such as those described above, may be
produced by hand or by using available devices (slot blot or dot
blot apparatus), materials (any suitable solid support), and
machines (including robotic instruments), and may contain: 8, 24,
96, 384, 1536, 6144 or more polynucleotides, or any other number
which lends itself to the efficient use of commercially available
instrumentation.
[0204] Using such arrays or other kits/systems, the present
invention provides methods of identifying the SNPs disclosed herein
in, a test sample. Such methods typically involve incubating a test
sample of nucleic acids with an array comprising one or more probes
corresponding to at least one SNP position of the present
invention, and assaying for binding of a nucleic acid from the test
sample with one or more of the probes. Conditions for incubating a
SNP detection reagent (or a kit/system that employs one or more
such SNP detection reagents) with a test sample vary. Incubation
conditions depend on such factors as the format employed in the
assay, the detection methods employed, and the type and nature of
the detection reagents used in the assay. One skilled in the art
will recognize that any one of the commonly available
hybridization, amplification and array assay formats can readily be
adapted to detect the SNPs disclosed herein.
[0205] A SNP detection kit/system of the present invention may
include components that are used to prepare nucleic acids from a
test sample for the subsequent amplification and/or detection of a
SNP-containing nucleic acid molecule. Such sample preparation
components can be used to produce nucleic acid extracts (including
DNA and/or RNA), proteins or membrane extracts from any bodily
fluids (such as blood, serum, plasma, urine, saliva, phlegm,
gastric juices, semen, tears, sweat, etc.), skin, hair, cells
(especially nucleated cells), biopsies, buccal swabs or tissue
specimens. The test samples used in the above-described methods
will vary based on such factors as the assay format, nature of the
detection method, and the specific tissues, cells or extracts used
as the test sample to be assayed. Methods of preparing nucleic
acids, proteins, and cell extracts are well known in the art and
can be readily adapted to obtain a sample that is compatible with
the system utilized. Automated sample preparation systems for
extracting nucleic acids from a test sample are commercially
available, and examples are Qiagen's BioRobot 9600, Applied
Biosystems' PRISM 6700, and Roche Molecular Systems COBAS AmpliPrep
System.
[0206] Another form of kit contemplated by the present invention is
a compartmentalized kit. A compartmentalized kit includes any kit
in which reagents are contained in separate containers. Such
containers include, for example, small glass containers, plastic
containers, strips of plastic, glass or paper, or arraying material
such as silica. Such containers allow one to efficiently transfer
reagents from one compartment to another compartment such that the
test samples and reagents are not cross-contaminated, or from one
container to another vessel not included in the kit, and the agents
or solutions of each container can be added in a quantitative
fashion from one compartment to another or to another vessel. Such
containers may include, for example, one or more containers which
will accept the test sample, one or more containers which contain
at least one probe or other SNP detection reagent for detecting one
or more SNPs of the present invention, one or more containers which
contain wash reagents (such as phosphate buffered saline,
Tris-buffers, etc.), and one or more containers which contain the
reagents used to reveal the presence of the bound probe or other
SNP detection reagents. The kit can optionally further comprise
compartments and/or reagents for, for example, nucleic acid
amplification or other enzymatic reactions such as primer extension
reactions, hybridization, ligation, electrophoresis (preferably
capillary electrophoresis), mass spectrometry, and/or laser-induced
fluorescent detection. The kit may also include instructions for
using the kit. Exemplary compartmentalized kits include
microfluidic devices known in the art (see, e.g., Weigl et al.,
"Lab-on-a-chip for drug development", Adv Drug Deliv Rev. 2003 Feb.
24; 55(3):349-77). In such microfluidic devices, the containers may
be referred to as, for example, microfluidic "compartments",
"chambers", or "channels".
[0207] Microfluidic devices, which may also be referred to as
"lab-on-a-chip" systems, biomedical micro-electro-mechanical
systems (bioMEMs), or multicomponent integrated systems, are
exemplary kits/systems of the present invention for analyzing SNPs.
Such systems miniaturize and compartmentalize processes such as
probe/target hybridization, nucleic acid amplification, and
capillary electrophoresis reactions in a single functional device.
Such microfluidic devices typically utilize detection reagents in
at least one aspect of the system, and such detection reagents may
be used to detect one or more SNPs of the present invention. One
example of a microfluidic system is disclosed in U.S. Pat. No.
5,589,136, which describes the integration of PCR-amplification and
capillary electrophoresis in chips. Exemplary microfluidic systems
comprise a pattern of microchannels designed onto a glass, silicon,
quartz, or plastic wafer included on a microchip. The movements of
the samples may be controlled by electric, electroosmotic or
hydrostatic forces applied across different areas of the microchip
to create functional microscopic valves and pumps with no moving
parts. Varying the voltage can be used as a means to control the
liquid flow at intersections between the micro-machined channels
and to change the liquid flow rate for pumping across different
sections of the microchip. See, for example, U.S. Pat. No.
6,153,073, Dubrow et al., and U.S. Pat. No. 6,156,181, Parce et
al.
[0208] For genotyping SNPs, an exemplary microfluidic system may
integrate, for example, nucleic acid amplification,
primer-extension, capillary electrophoresis, and a detection method
such as laser induced fluorescence detection. In a first step of an
exemplary process for using such an exemplary system, nucleic acid
samples are amplified, preferably by PCR. Then, the amplification
products are subjected to automated primer extension reactions
using ddNTPs (specific fluorescence for each ddNTP) and the
appropriate oligonucleotide primers to carry out primer extension
reactions which hybridize just upstream of the targeted SNP. Once
the extension at the 3' end is completed, the primers are separated
from the unincorporated fluorescent ddNTPs by capillary
electrophoresis. The separation medium used in capillary
electrophoresis can be, for example, polyacrylamide,
polyethyleneglycol or dextran. The incorporated ddNTPs in the
single nucleotide primer extension products are identified by
laser-induced fluorescence detection. Such an exemplary microchip
can be used to process, for example, at least 96 to 384 samples, or
more, in parallel.
[0209] Uses of Nucleic Acid Molecules
[0210] The nucleic acid molecules of the present invention have a
variety of uses, especially in predicting an individual's risk for
developing a cardiovascular disorder (particularly the risk for
experiencing a first or recurrent acute coronary event such as a
myocardial infarction or stroke), for prognosing the progression of
a cardiovascular disorder in an individual (e.g., the severity or
consequences of an acute coronary event), in evaluating the
likelihood of an individual who has a cardiovascular disorder of
responding to treatment of the cardiovascular disorder with statin,
and/or predicting the likelihood that the individual will
experience toxicity or other undesirable side effects from the
statin treatment, etc. For example, the nucleic acid molecules are
useful as hybridization probes, such as for genotyping SNPs in
messenger RNA, transcript, cDNA, genomic DNA, amplified DNA or
other nucleic acid molecules, and for isolating full-length cDNA
and genomic clones encoding the variant peptides disclosed in Table
1 as well as their orthologs.
[0211] A probe can hybridize to any nucleotide sequence along the
entire length of a nucleic acid molecule provided in Table 1 and/or
Table 2. Preferably, a probe of the present invention hybridizes to
a region of a target sequence that encompasses a SNP position
indicated in Table 1 and/or Table 2. More preferably, a probe
hybridizes to a SNP-containing target sequence in a
sequence-specific manner such that it distinguishes the target
sequence from other nucleotide sequences which vary from the target
sequence only by which nucleotide is present at the SNP site. Such
a probe is particularly useful for detecting the presence of a
SNP-containing nucleic acid in a test sample, or for determining
which nucleotide (allele) is present at a particular SNP site
(i.e., genotyping the SNP site).
[0212] A nucleic acid hybridization probe may be used for
determining the presence, level, form, and/or distribution of
nucleic acid expression. The nucleic acid whose level is determined
can be DNA or RNA. Accordingly, probes specific for the SNPs
described herein can be used to assess the presence, expression
and/or gene copy number in a given cell, tissue, or organism. These
uses are relevant for diagnosis of disorders involving an increase
or decrease in gene expression relative to normal levels. In vitro
techniques for detection of mRNA include, for example, Northern
blot hybridizations and in situ hybridizations. In vitro techniques
for detecting DNA include Southern blot hybridizations and in situ
hybridizations (Sambrook and Russell, 2000, Molecular Cloning: A
Laboratory Manual, Cold Spring Harbor Press, Cold Spring Harbor,
N.Y.).
[0213] Probes can be used as part of a diagnostic test kit for
identifying cells or tissues in which a variant protein is
expressed, such as by measuring the level of a variant protein
encoding nucleic acid (e.g., mRNA) in a sample of cells from a
subject or determining if a polynucleotide contains a SNP of
interest.
[0214] Thus, the nucleic acid molecules of the invention can be
used as hybridization probes to detect the SNPs disclosed herein,
thereby determining whether an individual with the polymorphisms is
likely or unlikely to develop a cardiovascular disorder such as an
acute coronary event, or the likelihood that an individual will
respond positively to statin treatment of a cardiovascular
disorder. Detection of a SNP associated with a disease phenotype
provides a diagnostic tool for an active disease and/or genetic
predisposition to the disease.
[0215] Furthermore, the nucleic acid molecules of the invention are
therefore useful for detecting a gene (gene information is
disclosed in Table 2, for example) which contains a SNP disclosed
herein and/or products of such genes, such as expressed mRNA
transcript molecules (transcript information is disclosed in Table
1, for example), and are thus useful for detecting gene expression.
The nucleic acid molecules can optionally be implemented in, for
example, an array or kit format for use in detecting gene
expression.
[0216] The nucleic acid molecules of the invention are also useful
as primers to amplify any given region of a nucleic acid molecule,
particularly a region containing a SNP identified in Table 1 and/or
Table 2.
[0217] The nucleic acid molecules of the invention are also useful
for constructing recombinant vectors (described in greater detail
below). Such vectors include expression vectors that express a
portion of, or all of, any of the variant peptide sequences
provided in Table 1. Vectors also include insertion vectors, used
to integrate into another nucleic acid molecule sequence, such as
into the cellular genome, to alter in situ expression of a gene
and/or gene product. For example, an endogenous coding sequence can
be replaced via homologous recombination with all or part of the
coding region containing one or more specifically introduced
SNPs.
[0218] The nucleic acid molecules of the invention are also useful
for expressing antigenic portions of the variant proteins,
particularly antigenic portions that contain a variant amino acid
sequence (e.g., an amino acid substitution) caused by a SNP
disclosed in Table 1 and/or Table 2.
[0219] The nucleic acid molecules of the invention are also useful
for constructing vectors containing a gene regulatory region of the
nucleic acid molecules of the present invention.
[0220] The nucleic acid molecules of the invention are also useful
for designing ribozymes corresponding to all, or a part, of an mRNA
molecule expressed from a SNP-containing nucleic acid molecule
described herein.
[0221] The nucleic acid molecules of the invention are also useful
for constructing host cells expressing a part, or all, of the
nucleic acid molecules and variant peptides.
[0222] The nucleic acid molecules of the invention are also useful
for constructing transgenic animals expressing all, or a part, of
the nucleic acid molecules and variant peptides. The production of
recombinant cells and transgenic animals having nucleic acid
molecules which contain the SNPs disclosed in Table 1 and/or Table
2 allow, for example, effective clinical design of treatment
compounds and dosage regimens.
[0223] The nucleic acid molecules of the invention are also useful
in assays for drug screening to identify compounds that, for
example, modulate nucleic acid expression.
[0224] The nucleic acid molecules of the invention are also useful
in gene therapy in patients whose cells have aberrant gene
expression. Thus, recombinant cells, which include a patient's
cells that have been engineered ex vivo and returned to the
patient, can be introduced into an individual where the recombinant
cells produce the desired protein to treat the individual.
[0225] SNP Genotyping Methods
[0226] The process of determining which specific nucleotide (i.e.,
allele) is present at each of one or more SNP positions, such as a
SNP position in a nucleic acid molecule disclosed in Table 1 and/or
Table 2, is referred to as SNP genotyping. The present invention
provides methods of SNP genotyping, such as for use in evaluating
an individual's risk for developing a cardiovascular
disease--particularly an acute coronary event (such as myocardial
infarction or stroke) and for evaluating an individual's prognosis
for disease severity and recovery, for predicting the likelihood
that an individual who has previously experienced an acute coronary
event will experience one or more recurrent acute coronary events,
for implementing a preventive or treatment regimen for an
individual based on that individual having an increased
susceptibility for developing a cardiovascular disorder (e.g.,
increased risk for experiencing one or more myocardial infarctions
or strokes), in evaluating an individual's likelihood of responding
to statin treatment for cardiovascular disease, in selecting a
treatment regimen (e.g., in deciding whether or not to administer
statin treatment to an individual having a cardiovascular disease,
or in formulating or selecting a particular statin-based treatment
regimen such as dosage and/or frequency of administration of statin
treatment or choosing which form/type of statin to be administered
such as a particular pharmaceutical composition or compound, etc.),
determining the likelihood of experiencing toxicity or other
undesirable side effects from the statin treatment, or selecting
individuals for a clinical trial of a statin (e.g., selecting
individuals to participate in the trial who are most likely to
respond positively from the statin treatment), etc.
[0227] Nucleic acid samples can be genotyped to determine which
allele(s) is/are present at any given genetic region (e.g., SNP
position) of interest by methods well known in the art. The
neighboring sequence can be used to design SNP-detection reagents
such as oligonucleotide probes, which may optionally be implemented
in a kit format. Exemplary SNP genotyping methods are described in
Chen et al., "Single nucleotide polymorphism genotyping:
biochemistry, protocol, cost and throughput", Pharmacogenomics J.
2003; 3(2):77-96; Kwok et al., "Detection of single nucleotide
polymorphisms", Curr Issues Mol. Biol. 2003 April; 5(2):43-60; Shi,
"Technologies for individual genotyping: detection of genetic
polymorphisms in drug targets and disease genes", Am J
Pharmacogenomics. 2002; 2(3):197-205; and Kwok, "Methods for
genotyping single nucleotide polymorphisms", Annu Rev Genomics Hum
Genet 2001; 2:235-58. Exemplary techniques for high-throughput SNP
genotyping are described in Marnellos, "High-throughput SNP
analysis for genetic association studies", Curr Opin Drug Discov
Devel. 2003 May; 6(3):317-21. Common SNP genotyping methods
include, but are not limited to, TaqMan assays, molecular beacon
assays, nucleic acid arrays, allele-specific primer extension,
allele-specific PCR, arrayed primer extension, homogeneous primer
extension assays, primer extension with detection by mass
spectrometry, pyrosequencing, multiplex primer extension sorted on
genetic arrays, ligation with rolling circle amplification,
homogeneous ligation, OLA (U.S. Pat. No. 4,988,167), multiplex
ligation reaction sorted on genetic arrays, restriction-fragment
length polymorphism, single base extension-tag assays, and the
Invader assay. Such methods may be used in combination with
detection mechanisms such as, for example, luminescence or
chemiluminescence detection, fluorescence detection, time-resolved
fluorescence detection, fluorescence resonance energy transfer,
fluorescence polarization, mass spectrometry, and electrical
detection.
[0228] Various methods for detecting polymorphisms include, but are
not limited to, methods in which protection from cleavage agents is
used to detect mismatched bases in RNA/RNA or RNA/DNA duplexes
(Myers et al., Science 230:1242 (1985); Cotton et al., PNAS 85:4397
(1988); and Saleeba et al., Meth. Enzymol. 217:286-295 (1992)),
comparison of the electrophoretic mobility of variant and wild type
nucleic acid molecules (Orita et al., PNAS 86:2766 (1989); Cotton
et al., Mutat. Res. 285:125-144 (1993); and Hayashi et al, Genet.
Anal. Tech. Appl. 9:73-79 (1992)), and assaying the movement of
polymorphic or wild-type fragments in polyacrylamide gels
containing a gradient of denaturant using denaturing gradient gel
electrophoresis (DGGE) (Myers et al., Nature 313:495 (1985)).
Sequence variations at specific locations can also be assessed by
nuclease protection assays such as RNase and S1 protection or
chemical cleavage methods.
[0229] In a preferred embodiment, SNP genotyping is performed using
the TaqMan assay, which is also known as the 5' nuclease assay
(U.S. Pat. Nos. 5,210,015 and 5,538,848). The TaqMan assay detects
the accumulation of a specific amplified product during PCR. The
TaqMan assay utilizes an oligonucleotide probe labeled with a
fluorescent reporter dye and a quencher dye. The reporter dye is
excited by irradiation at an appropriate wavelength, it transfers
energy to the quencher dye in the same probe via a process called
fluorescence resonance energy transfer (FRET). When attached to the
probe, the excited reporter dye does not emit a signal. The
proximity of the quencher dye to the reporter dye in the intact
probe maintains a reduced fluorescence for the reporter. The
reporter dye and quencher dye may be at the 5' most and the 3' most
ends, respectively, or vice versa. Alternatively, the reporter dye
may be at the 5' or 3' most end while the quencher dye is attached
to an internal nucleotide, or vice versa. In yet another
embodiment, both the reporter and the quencher may be attached to
internal nucleotides at a distance from each other such that
fluorescence of the reporter is reduced.
[0230] During PCR, the 5' nuclease activity of DNA polymerase
cleaves the probe, thereby separating the reporter dye and the
quencher dye and resulting in increased fluorescence of the
reporter. Accumulation of PCR product is detected directly by
monitoring the increase in fluorescence of the reporter dye. The
DNA polymerase cleaves the probe between the reporter dye and the
quencher dye only if the probe hybridizes to the target
SNP-containing template which is amplified during PCR, and the
probe is designed to hybridize to the target SNP site only if a
particular SNP allele is present.
[0231] Preferred TaqMan primer and probe sequences can readily be
determined using the SNP and associated nucleic acid sequence
information provided herein. A number of computer pro grams, such
as Primer Express (Applied Biosystems, Foster City, Calif.), can be
used to rapidly obtain optimal Primer/probe sets. It will be
apparent to one of skill in, the art that such primers and probes
for detecting the SNPs of the present invention are useful in
screening for individuals who are susceptible to developing a
cardiovascular disorder (e.g., an acute coronary event) or in
screening individuals who have a cardiovascular disorder for their
likelihood of responding to statin treatment. These probes and
primers can be readily incorporated into a kit format. The present
invention also includes modifications of the Taqman assay well
known in the art such as the use of Molecular Beacon probes (U.S.
Pat. Nos. 5,118,801 and 5,312,728) and other variant formats (U.S.
Pat. Nos. 5,866,336 and 6,117,635).
[0232] Another preferred method for genotyping the SNPs of the
present invention is the use of two oligonucleotide probes in an
OLA (see, e.g., U.S. Pat. No. 4,988,617). In this method, one probe
hybridizes to a segment of a target nucleic acid with its 3' most
end aligned with the SNP site. A second probe hybridizes to an
adjacent segment of the target nucleic acid molecule directly 3' to
the first probe. The two juxtaposed probes hybridize to the target
nucleic acid molecule, and are ligated in the presence of a linking
agent such as a ligase if there is perfect complementarity between
the 3' most nucleotide of the first probe with the SNP site. If
there is a mismatch, ligation would not occur. After the reaction,
the ligated probes are separated from the target nucleic acid
molecule, and detected as indicators of the presence of a SNP.
[0233] The following patents, patent applications, and published
international patent applications, which are all hereby
incorporated by reference, provide additional information
pertaining to techniques for carrying out various types of OLA:
U.S. Pat. Nos. 6,027,889, 6,268,148, 5,494,810, 5,830,711, and
6,054,564 describe OLA strategies for performing SNP detection; WO
97/31256 and WO 00/56927 describe OLA strategies for performing SNP
detection using universal arrays, wherein a zipcode sequence can be
introduced into one of the hybridization probes, and the resulting
product, or amplified product, hybridized to a universal zip code
array; U.S. application Ser. No. 01/17329 (and 09/584,905)
describes OLA (or LDR) followed by PCR, wherein zipcodes are
incorporated: into OLA probes, and amplified PCR products are
determined by electrophoretic or universal zipcode array readout;
U.S. application 60/427,818, 60/445,636, and 60/445,494 describe
SNPlex methods and software for multiplexed SNP detection using OLA
followed by PCR, wherein zipcodes are incorporated into OLA probes,
and amplified PCR products are hybridized with a zipchute reagent,
and the identity of the SNP determined from electrophoretic readout
of the zipchute. In some embodiments, OLA is carried out prior to
PCR (or another method of nucleic acid amplification). In other
embodiments, PCR (or another method of nucleic acid amplification)
is carried out prior to OLA.
[0234] Another method for SNP genotyping is based on mass
spectrometry. Mass spectrometry takes advantage of the unique mass
of each of the four nucleotides of DNA. SNPs can be unambiguously
genotyped by mass spectrometry by measuring the differences in the
mass of nucleic acids having alternative SNP alleles. MALDI-TOF
(Matrix Assisted Laser Desorption Ionization--Time of Flight) mass
spectrometry technology is preferred for extremely precise
determinations of molecular mass, such as SNPs. Numerous approaches
to SNP analysis have been developed based on mass spectrometry.
Preferred mass spectrometry-based methods of SNP genotyping include
primer extension assays, which can also be utilized in combination
with other approaches, such as traditional gel-based formats and
microarrays.
[0235] Typically, the primer extension assay involves designing and
annealing a primer to a template PCR amplicon upstream (5') from a
target SNP position. A mix of dideoxynucleotide triphosphates
(ddNTPs) and/or deoxynucleotide triphosphates (dNTPs) are added to
a reaction mixture containing template (e.g., a SNP-containing
nucleic acid molecule which has typically been amplified, such as
by PCR), primer, and DNA polymerase. Extension of the primer
terminates at the first position in the template where a nucleotide
complementary to one of the ddNTPs in the mix occurs. The primer
can be either immediately adjacent (i.e., the nucleotide at the 3'
end of the primer hybridizes to the nucleotide next to the target
SNP site) or two or more nucleotides removed from the SNP position.
If the primer is several nucleotides removed from the target SNP
position, the only limitation is that the template sequence between
the 3' end of the primer and the SNP position cannot contain a
nucleotide of the same type as the one to be detected, or this will
cause premature termination of the extension primer. Alternatively,
if all four ddNTPs alone, with no dNTPs, are, added to the reaction
mixture, the primer will always be extended by only one nucleotide,
corresponding to the target SNP position. In this instance, primers
are designed to bind one nucleotide upstream from the SNP position
(i.e., the nucleotide at the 3' end of the primer hybridizes to the
nucleotide that is immediately adjacent to the target SNP site on
the 5' side of the target SNP site). Extension by only one
nucleotide is preferable, as it minimizes the overall mass of the
extended primer, thereby increasing the resolution of mass
differences between alternative SNP nucleotides. Furthermore,
mass-tagged ddNTPs can be employed in the primer extension
reactions in place of unmodified ddNTPs. This increases the mass
difference between primers extended with these ddNTPs, thereby
providing increased sensitivity and accuracy, and is particularly
useful for typing heterozygous base positions. Mass-tagging also
alleviates the need for intensive sample-preparation procedures and
decreases the necessary resolving power of the mass
spectrometer.
[0236] The extended primers can then be purified and analyzed by
MALDI-TOF mass spectrometry to determine the identity of the
nucleotide present at the target SNP position. In one method of
analysis, the products from the primer extension reaction are
combined with light absorbing crystals that form a matrix. The
matrix is then hit with an energy source such as a laser to ionize
and desorb the nucleic acid molecules into the gas-phase. The
ionized molecules are then ejected into a flight tube and
accelerated down the tube towards a detector. The time between the
ionization event, such as a laser pulse, and collision of the
molecule with the detector is the time of flight of that molecule.
The time of flight is precisely correlated with the mass-to-charge
ratio (m/z) of the ionized molecule. Ions with smaller m/z travel
down the tube faster than ions with larger m/z and therefore the
lighter ions reach the detector before the heavier ions. The
time-of-flight is then converted into a corresponding, and highly
precise, m/z. In this manner, SNPs can be identified based on the
slight differences in mass, and the corresponding time of flight
differences, inherent in nucleic acid molecules having different
nucleotides at a single base position. For further information
regarding the use of primer extension assays in conjunction with
MALDI-TOF mass spectrometry for SNP genotyping, see, e.g., Wise et
al., "A standard protocol for single nucleotide primer extension in
the human genome using matrix-assisted laser desorption/ionization
time-of-flight mass spectrometry", Rapid Commun Mass Spectrom.
2003; 17(11):1195-202.
[0237] The following references provide further information
describing mass spectrometry-based methods for SNP genotyping:
Bocker, "SNP and mutation discovery using base-specific cleavage
and MALDI-TOF mass spectrometry", Bioinformatics. 2003 July; 19
Suppl 1:144-153; Storm et al., "MALDI-TOF mass spectrometry-based
SNP genotyping", Methods Mol. Biol. 2003; 212:241-62; Jurinke et
al., "The use of MassARRAY technology for high throughput
genotyping", Adv Biochem Eng Biotechnol. 2002; 77:57-74; and
Jurinke et al., "Automated genotyping using the DNA MassArray
technology", Methods Mol. Biol. 2002; 187:179-92.
[0238] SNPs can also be scored by direct DNA sequencing. A variety
of automated sequencing procedures can be utilized ((1995)
Biotechniques 19:448), including sequencing by mass spectrometry
(see, e.g., PCT International Publication No. WO94/16101; Cohen et
al., Adv. Chromatogr. 36:127-162 (1996); and Griffin et al., Appl.
Biochem. Biotechnol. 38:147-159 (1993)). The nucleic acid sequences
of the present invention enable one of ordinary skill in the art to
readily design sequencing primers for such automated sequencing
procedures. Commercial instrumentation, such as the Applied
Biosystems 377, 3100, 3700, 3730, and 3730x1 DNA Analyzers (Foster
City, Calif.), is commonly used in the art for automated
sequencing.
[0239] Other methods that can be used to genotype the SNPs of the
present invention include single-strand conformational polymorphism
(SSCP), and denaturing gradient gel electrophoresis (DGGE) (Myers
et al., Nature 313:495 (1985)). SSCP identifies base differences by
alteration in electrophoretic migration of single stranded PCR
products, as described in Orita et al., Proc. Nat. Acad.
Single-stranded PCR products can be generated by heating or
otherwise denaturing double stranded PCR products.
Single-stranded-nucleic acids may refold or form secondary
structures that are partially dependent on the base sequence. The
different electrophoretic mobilities of single-stranded
amplification products are related to base-sequence differences at
SNP positions. DGGE differentiates SNP alleles based on the
different sequence-dependent stabilities and melting properties
inherent in polymorphic DNA and the corresponding differences in
electrophoretic migration patterns in a denaturing gradient gel
(Erlich, ed., PCR Technology, Principles and Applications for DNA
Amplification, W.H. Freeman and Co, New York, 1992, Chapter 7).
[0240] Sequence-specific ribozymes (U.S. Pat. No. 5,498,531) can
also be used to score SNPs based on the development or loss of a
ribozyme cleavage site. Perfectly matched sequences can be
distinguished from mismatched sequences by nuclease cleavage
digestion assays or by differences in melting temperature. If the
SNP affects a restriction enzyme cleavage site, the SNP can be
identified by alterations in restriction enzyme digestion patterns,
and the corresponding changes in nucleic acid fragment lengths
determined by gel electrophoresis
[0241] SNP genotyping can include the steps of, for example,
collecting a biological sample from a human subject (e.g., sample
of tissues, cells, fluids, secretions, etc.), isolating nucleic
acids (e.g., genomic DNA, mRNA or both) from the cells of the
sample, contacting the nucleic acids with one or more primers which
specifically hybridize to a region of the isolated nucleic acid
containing a target SNP under conditions such that hybridization
and amplification of the target nucleic acid region occurs, and
determining the nucleotide present at the SNP position of interest,
or, in some assays, detecting the presence or absence of an
amplification product (assays can be designed so that hybridization
and/or amplification will only occur if a particular SNP allele is
present or absent). In some assays, the size of the amplification
product is detected and compared to the length of a control sample;
for example, deletions and insertions can be detected by a change
in size of the amplified product compared to a normal genotype.
[0242] SNP genotyping is useful for numerous practical
applications, as described below. Examples of such applications
include, but are not limited to, SNP-disease association analysis,
disease predisposition screening, disease diagnosis, disease
prognosis, disease progression monitoring, determining therapeutic
strategies based on an individual's genotype ("pharmacogenomics"),
developing therapeutic agents based on SNP genotypes associated
with a disease or likelihood of responding to a drug, stratifying a
patient population for clinical trial for a treatment regimen,
predicting the likelihood that an individual will experience toxic
side effects from a therapeutic agent, and human identification
applications such as forensics.
[0243] Analysis of Genetic Association Between SNPs and Phenotypic
Traits
[0244] SNP genotyping for disease diagnosis, disease predisposition
screening, disease prognosis, determining drug responsiveness
(pharmacogenomics), drug toxicity screening, and other uses
described herein, typically relies on initially establishing a
genetic association between one or more specific SNPs and the
particular phenotypic traits of interest.
[0245] Different study designs may be used for genetic association
studies (Modern Epidemiology, Lippincott Williams & Wilkins
(1998), 609-622). Observational studies are most frequently carried
out in which the response of the patients is not interfered with.
The first type of observational study identifies a sample of
persons in whom the suspected cause of the disease is present and
another sample of persons in whom the suspected cause is absent,
and then the frequency of development of disease in the two samples
is compared. These sampled populations are called cohorts, and the
study is a prospective study. The other type of observational study
is case-control or a retrospective study. In typical case-control
studies, samples are collected from individuals with the phenotype
of interest (cases) such as certain manifestations of a disease,
and from individuals without the phenotype (controls) in a
population (target population) that conclusions are to be drawn
from. Then the possible causes of the disease are investigated
retrospectively. As the time and costs of collecting samples in
case-control studies are considerably less than those for
prospective studies, case-control studies are the more commonly
used study design in genetic association studies, at least during
the exploration and discovery stage.
[0246] In both types of observational studies, there may be
potential confounding factors that should be taken into
consideration. Confounding factors are those that are associated
with both the real cause(s) of the disease and the disease itself,
and they include demographic information such as age, gender,
ethnicity as well as environmental factors. When confounding
factors are not matched in cases and controls in a study, and are
not controlled properly, spurious association results can arise. If
potential confounding factors are identified, they should be
controlled for by analysis methods explained below.
[0247] In a genetic association study, the cause of interest to be
tested is a certain allele or a SNP or a combination of alleles or
a haplotype from several SNPs. Thus, tissue specimens (e.g., whole
blood) from the sampled individuals may be collected and genomic
DNA genotyped for the SNP(s) of interest. In addition to the
phenotypic trait of interest, other information such as demographic
(e.g., age, gender, ethnicity, etc.), clinical, and environmental
information that may influence the outcome of the trait can be
collected to further characterize and define the sample set. In
many cases, these factors are known to be associated with diseases
and/or SNP allele frequencies. There are likely gene-environment
and/or gene-gene interactions as well. Analysis methods to address
gene-environment and gene-gene interactions (for example, the
effects of the presence of both susceptibility alleles at two
different genes can be greater than the effects of the individual
alleles at two genes combined) are discussed below.
[0248] After all the relevant phenotypic and genotypic information
has been obtained, statistical analyses are carried out to
determine if there is any significant correlation between the
presence of an allele or a genotype with the phenotypic
characteristics of an individual. Preferably, data inspection and
cleaning are first performed before carrying out statistical tests
for genetic association. Epidemiological and clinical data of the
samples can be summarized by descriptive statistics with tables and
graphs. Data validation is preferably performed to check for data
completion, inconsistent entries, and outliers. Chi-squared tests
and t-tests (Wilcoxon rank-sum tests if distributions are not
normal) may then be used to check for significant differences
between cases and controls for discrete and continuous variables,
respectively. To ensure genotyping quality, Hardy-Weinberg
disequilibrium tests can be performed on cases and controls
separately. Significant deviation from Hardy-Weinberg equilibrium
(HWE) in both cases and controls for individual markers can be
indicative of genotyping errors. If HWE is violated in a majority
of markers, it is indicative of population substructure that should
be further investigated. Moreover, Hardy-Weinberg disequilibrium in
cases only can indicate genetic association of the markers with the
disease (Genetic Data Analysis, Weir B., Sinauer (1990)).
[0249] To test whether an allele of a single SNP is associated with
the case or control status of a phenotypic trait, one skilled in
the art can compare allele frequencies in cases and controls.
Standard chi-squared tests and Fisher exact tests can be carried
out on a 2.times.2 table (2 SNP alleles.times.2 outcomes in the
categorical trait of interest). To test whether genotypes of a SNP
are associated, chi-squared tests can be carried out on a 3.times.2
table (3 genotypes.times.2 outcomes). Score tests are also carried
out for genotypic association to contrast the three genotypic
frequencies (major homozygotes, heterozygotes and minor
homozygotes) in cases and controls, and to look for trends using 3
different modes of inheritance, namely dominant (with contrast
coefficients 2, -1, -1), additive (with contrast coefficients 1, 0,
-1) and recessive (with contrast coefficients 1, 1, -2). Odds
ratios for minor versus major alleles, and odds ratios for
heterozygote and homozygote variants versus the wild type genotypes
are calculated with the desired confidence limits, usually 95%.
[0250] In order to control for confounders and to test for
interaction and effect modifiers, stratified analyses may be
performed using stratified factors that are likely to be
confounding, including demographic information such as age,
ethnicity, and gender, or an interacting element or effect
modifier, such as a known major gene (e.g., APOE for Alzheimer's
disease or HLA genes for autoimmune diseases), or environmental
factors such as smoking in lung cancer. Stratified association
tests may be carried out using Cochran-Mantel-Haenszel tests that
take into account the ordinal nature of genotypes with 0, 1, and 2
variant alleles. Exact tests by StatXact may also be performed when
computationally possible. Another way to adjust for confounding
effects and test for interactions is to perform stepwise multiple
logistic regression analysis using statistical packages such as SAS
or R. Logistic regression is a model-building technique in which
the best fitting and most parsimonious model is built to describe
the relation between the dichotomous outcome (for instance, getting
a certain disease or not) and a set of independent variables (for
instance, genotypes of different associated genes, and the
associated demographic and environmental factors). The most common
model is one in which the logit transformation of the odds ratios
is expressed as a linear combination of the variables (main
effects) and their cross-product terms (interactions) (Applied
Logistic Regression, Hosmer and Lemeshow, Wiley (2000)). To test
whether a certain variable or interaction is significantly
associated with the outcome, coefficients in the model are first
estimated and then tested for statistical significance of their
departure from zero.
[0251] In addition to performing association tests one marker at a
time, haplotype association analysis may also be performed to study
a number of markers that are closely linked together. Haplotype
association tests can have better power than genotypic or allelic
association tests when the tested markers are not the
disease-causing mutations themselves but are in linkage
disequilibrium with such mutations. The test will even be more
powerful if the disease is indeed caused by a combination of
alleles on a haplotype (e.g., APOE is a haplotype formed by 2 SNPs
that are very close to each other). In order to perform haplotype
association effectively, marker-marker linkage disequilibrium
measures, both D' and R.sup.2, are typically calculated for the
markers within a gene to elucidate the haplotype structure. Recent
studies (Daly et al, Nature Genetics, 29, 232-235, 2001) in linkage
disequilibrium indicate that SNPs within a gene are organized in
block pattern, and a high degree of linkage disequilibrium exists
within blocks and very little linkage disequilibrium exists between
blocks. Haplotype association with the disease status can be
performed using such blocks once they have been elucidated.
[0252] Haplotype association tests can be carried out in a similar
fashion as the allelic and genotypic association tests. Each
haplotype in a gene is analogous to an allele in a multi-allelic
marker. One skilled in the art can either compare the haplotype
frequencies in cases and controls or test genetic association with
different pairs of haplotypes. It has been proposed (Schaid et al,
Am. J. Hum. Genet., 70, 425-434, 2002) that score tests can be done
on haplotypes using the program "haplo.score". In that method,
haplotypes are first inferred by EM algorithm and score tests are
carried out with a generalized linear model (GLM) framework that
allows the adjustment of other factors.
[0253] An important decision in the performance of genetic
association tests is the determination of the significance level at
which significant association can be declared when the p-value of
the tests reaches that level. In an exploratory analysis where
positive hits will be followed up in subsequent confirmatory
testing, an unadjusted p-value <0.1 (a significance level on the
lenient side) may be used for generating hypotheses for significant
association of a SNP with certain phenotypic characteristics of a
disease. It is preferred that a p-value <0.05 (a significance
level traditionally used in the art) is achieved in order for a SNP
to be considered to have an association with a disease. It is more
preferred that a p-value <0.01 (a significance level on the
stringent side) is achieved for an association to be declared. When
hits are followed up in confirmatory analyses in more samples of
the same source or in different samples from different sources,
adjustment for multiple testing will be performed as to avoid
excess number of hits while maintaining the experiment-wise error
rates at 0.05. While there are different methods to adjust for
multiple testing to control for different kinds of error rates, a
commonly used but rather conservative method is Bonferroni
correction to control the experiment-wise or family-wise error rate
(Multiple comparisons and multiple tests, Westfall et al, SAS
Institute (1999)). Permutation tests to control for the false
discovery rates, FDR, can be more powerful (Benjamini and Hochberg,
Journal of the Royal Statistical Society, Series B 57, 1289-1300,
1995, Resampling-based Multiple. Testing, Westfall and Young, Wiley
(1993)). Such methods to control for multiplicity would be
preferred when the tests are dependent and controlling for false
discovery rates is sufficient as opposed to controlling for the
experiment-wise error rates.
[0254] In replication studies using samples from different
populations after statistically significant markers have been
identified in the exploratory stage, meta-analyses can then be
performed by combining evidence of different studies (Modern
Epidemiology, Lippincott Williams & Wilkins, 1998, 643-673). If
available, association results known in the art for the same SNPs
can be included in the meta-analyses.
[0255] Since both genotyping and disease status classification can
involve errors, sensitivity analyses may be performed to see how
odds ratios and p-values would change upon various estimates on
genotyping and disease classification error rates.
[0256] It has been well known that subpopulation-based sampling
bias between cases and controls can lead to spurious results in
case-control association studies (Ewens and Spielman, Am. J. Hum.
Genet. 62, 450-458, 1995) when prevalence of the disease is
associated with different subpopulation groups. Such bias can also
lead to a loss of statistical power in genetic association studies.
To detect population stratification, Pritchard and Rosenberg
(Pritchard et al. Am. J Hum. Gen. 1999, 65:220-228) suggested
typing markers that are unlinked to the disease and using results
of association tests on those markers to determine whether there is
any population stratification. When stratification is detected, the
genomic control (GC) method as proposed by Devlin and Roeder
(Devlin et al. Biometrics 1999, 55:997-1004) can bemused to adjust
for the inflation of test statistics due to population
stratification. GC method is robust to changes in population
structure levels as well as being applicable to DNA pooling designs
(Devlin et al. Genet. Epidem. 20001, 21:273-284).
[0257] While Pritchard's method recommended using 15-20 unlinked
microsatellite markers, it suggested using more than 30 biallelic
markers to get enough power to detect population stratification.
For the GC method, it has been shown (Bacanu et al. Am. J. Hum.
Genet. 2000, 66:1933-1944) that about 60-70 biallelic markers are
sufficient to estimate the inflation factor for the test statistics
due to population stratification. Hence, 70 intergenic SNPs can be
chosen in unlinked regions as indicated in a genome scan (Kehoe et
al. Hum. Mol. Genet. 1999, 8:237-245).
[0258] Once individual risk factors, genetic or non-genetic, have
been found for the 25, predisposition to disease, the next step is
to set up a classification/prediction scheme to predict the
category (for instance, disease or no-disease) that an individual
will be in depending on his genotypes of associated SNPs and other
non-genetic risk factors. Logistic regression for discrete trait
and linear regression for continuous trait are standard techniques
for such tasks (Applied Regression Analysis, Draper and Smith,
Wiley (1998)). Moreover, other techniques can also be used for
setting up classification. Such techniques include, but are not
limited to, MART, CART, neural network, and discriminant analyses
that are suitable for use in comparing the performance of different
methods (The Elements of Statistical Learning, Hastie, Tibshirani
& Friedman, Springer (2002)).
[0259] Disease Diagnosis and Predisposition Screening
[0260] Information on association/correlation between genotypes and
disease-related phenotypes can be exploited in several ways. For
example, in the case of a highly statistically significant
association between one or more SNPs with predisposition to a
disease for which treatment is available, detection of such a
genotype pattern in an individual may justify immediate
administration of treatment, or at least the institution of regular
monitoring of the individual. Detection of the susceptibility
alleles associated with serious disease in a couple contemplating
having children may also be valuable to the couple in their
reproductive decisions. In the case of a weaker but still
statistically significant association between a SNP and a human
disease, immediate therapeutic intervention or monitoring may not
be justified after detecting the susceptibility allele or SNP.
Nevertheless, the subject can be motivated to begin simple
life-style changes (e.g., diet, exercise) that can be accomplished
at little, or no cost to the individual but would confer potential
benefits in reducing the risk of developing conditions for which
that individual may have an increased risk by virtue of having the
susceptibility allele(s).
[0261] The SNPs of the invention may contribute to cardiovascular
disorders such as acute coronary events, or to responsiveness of an
individual to statin treatment, in different ways. Some
polymorphisms occur within a protein coding sequence and contribute
to disease phenotype by affecting protein structure. Other
polymorphisms occur in noncoding regions but may exert phenotypic
effects indirectly via influence on, for example, replication,
transcription, and/or translation. A single SNP may affect more
than one phenotypic trait. Likewise, a single phenotypic trait may
be affected by multiple SNPs in different genes.
[0262] As used herein, the terms "diagnose", "diagnosis", and
"diagnostics" include, but are not limited to any of the following:
detection of a cardiovascular disorders that an individual may
presently have, predisposition/susceptibility screening (e.g.,
determining whether an individual has an increased risk of
experiencing an acute coronary event in the future, or determining
whether an individual has a decreased risk of experiencing an acute
coronary event in the future), determining a particular type or
subclass of cardiovascular disorder in an individual known to
currently have or to have previously experienced a cardiovascular
disorder, confirming or reinforcing a previously made diagnosis of
a cardiovascular disorder, evaluating an individual's likelihood of
responding to statin treatment for cardiovascular disorders,
predisposition screening (e.g., evaluating an individual's
likelihood of responding to statin treatment if the individual were
to develop a cardiovascular disorder in the future), determining a
particular type or subclass of responder/non-responder in an
individual known to respond or not respond to statin treatment,
confirming or reinforcing a previously made classification of an
individual as a responder/non-responder to statin treatment
pharmacogenomic evaluation of an individual to determine which
therapeutic strategy that individual is most likely to positively
respond to or to predict whether a patient is likely to respond to
a particular treatment such as statin treatment, predicting whether
a patient is likely to experience toxic effects from a particular
treatment or therapeutic compound, and evaluating the future
prognosis of an individual having a cardiovascular disorder. Such
diagnostic uses are based on the SNPs individually or in a unique
combination or SNP haplotypes of the present invention.
[0263] Haplotypes are particularly useful in that, for example,
fewer SNPs can be genotyped to determine if a particular
genomic-region harbors a locus that influences a particular
phenotype, such as in linkage disequilibrium-based SNP association
analysis.
[0264] Linkage disequilibrium (LD) refers to the co-inheritance of
alleles (e.g., alternative nucleotides) at two or more different
SNP sites at frequencies greater than would be expected from the
separate frequencies of occurrence of each allele in a given
population. The expected frequency of co-occurrence of two alleles
that are inherited independently is the frequency of the first
allele multiplied by the frequency of the second allele. Alleles
that co-occur at expected frequencies are said to be in "linkage
equilibrium". In contrast, LD refers to any non-random genetic
association between allele(s) at two or more different SNP sites,
which is generally due to the physical proximity of the two loci
along a chromosome. LD can occur when two or more SNPs sites are in
close physical proximity to each other on a given chromosome and
therefore alleles at these SNP sites will tend to remain
unseparated for multiple generations with the consequence that a
particular nucleotide (allele) at one. SN site will show a
non-random association with a particular nucleotide (allele) at a
different SNP site located nearby. Hence, genotyping one of the SNP
sites will give almost the same information as genotyping the other
SNP site that is in LD.
[0265] Various degrees of LD can be encountered between two or more
SNPs with the result being that some SNPs are more closely
associated (i.e., in stronger LD) than others. Furthermore, the
physical distance over which LD extends along a chromosome differs
between different regions of the genome, and therefore the degree
of physical separation between two or more SN sites necessary for
LD to occur can differ between different regions of the genome.
[0266] For diagnostic purposes and similar uses, if a particular
SNP site is found to be useful for, for example, predicting an
individuial's susceptibility to an acute coronary event or an
individual's response to statin treatment, then the skilled artisan
would recognize that other SNP sites which are in LD with this SNP
site would also be useful for predicting an individual's response
to statin treatment. Various degrees of LD can be encountered
between two or more SNPs with the result being that some SNPs are
more closely associated (i.e., in stronger LD) than others.
Furthermore, the physical distance over which LD extends along a
chromosome differs between different regions of the genome, and
therefore the degree of physical separation between two or more SNP
sites necessary for LD to occur can differ between different
regions of the genome. Thus, polymorphisms (e.g., SNPs and/or
haplotypes) that are not the actual disease-causing (causative)
polymorphisms, but are in LD with such causative polymorphisms, are
also useful. In such instances, the genotype of the polymorphism(s)
that is/are in LD with the causative polymorphism is predictive of
the genotype of the causative polymorphism and, consequently,
predictive of the phenotype (e.g., responder/non-responder to
statin treatment) that is influenced by the causative SNP (s).
Therefore, polymorphic markers that are in LD with causative
polymorphisms are useful as diagnostic markers, and are
particularly useful when the actual causative polymorphism(s)
is/are unknown.
[0267] Examples of polymorphisms that can be in LD with one or more
causative polymorphisms (and/or in LD with one or more
polymorphisms that have a significant statistical association with
a condition) and therefore useful for diagnosing the same condition
that the causative/associated SNP(s) is used to diagnose, include,
for example, other SNPs in the same gene, protein-coding, or mRNA
transcript-coding region as the causative/associated SNP, other
SNPs in the same exon or same intron as the causative/associated
SNP, other SNPs in the same haplotype block as the
causative/associated SNP, other SNPs in the same intergenic region
as the causative/associated SNP, SNPs that are outside but near a
gene (e.g., within 6 kb on either side, 5' or 3', of a gene
boundary) that harbors a causative/associated SNP, etc. Such useful
LD SNPs can be selected from among the SNPs disclosed in Tables
1-2, for example.
[0268] Linkage disequilibrium in the human genome is reviewed in:
Wall et al., "Haplotype blocks and linkage disequilibrium in the
human genome", Nat Rev Genet. 2003 August; 4(8):587-97; Garner et
al., "On selecting markers for association studies: patterns of
linkage disequilibrium between two and three dialleic loci", Genet
Epidemiol. 2003 January; 24(1):57-67; Ardlie et al., "Patterns of
linkage disequilibrium in the human genome", Nat Rev Genet. 2002
April; 3(4):299-309 (erratum in Nat Rev Genet 2002 July; 3(7):566);
and Remm et al., "High-density genotyping and linkage
disequilibrium in the human genome using chromosome 22 as a model";
Curr Opin Chem Biol. 2002 February; 6(1):24-30.
[0269] The contribution or association of particular SNPs and/or
SNP haplotypes with disease phenotypes, such as susceptibility to
acute coronary events or responsiveness to statin treatment,
enables the SNPs of the present invention to be used to develop
superior diagnostic tests capable of identifying individuals
who-express a detectable trait, such as predisposition to acute
coronary events or responder/non-responder to statin treatment, as
the result of a specific genotype, or individuals whose genotype
places them at an increased or decreased risk of developing a
detectable trait at a subsequent time as compared to individuals
who do not have that genotype. As described herein, diagnostics may
be based on a single SNP or a group of SNPs. Combined detection of
a plurality of SNPs (for example, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16, 17, 18, 19, 20, 24, 25, 30, 32, 48, 50, 64, 96,
100, or any other number in-between, or more, of the SNPs provided
in Table 1 and/or Table 2) typically increases the probability of
an accurate diagnosis. For example, the presence of a single SNP
known to correlate with response to statin treatment might indicate
a probability of 20% that an individual will respond to statin
treatment, whereas detection of five SNPs, each of which correlates
with response to statin treatment, might indicate a probability of
80% that an individual will respond to statin treatment. To further
increase the accuracy of diagnosis or predisposition screening,
analysis of the SNPs of the present invention can be combined with
that of other polymorphisms or other risk factors that correlate
with disease risk and response to statin treatment, such as family
history.
[0270] It will, of course, be understood by practitioners skilled
in the treatment or diagnosis of cardiovascular disorders that the
present invention generally does not intend to provide an absolute
identification of individuals who will or will not experience an
acute coronary event or develop another cardiovascular disorder, or
those individuals who will or will not respond to statin treatments
of cardiovascular disorders, but rather to indicate a certain
increased (or decreased) degree or likelihood of developing an
acute coronary event or responding to statin treatment based on
statistically significant association results. However, this
information is extremely valuable as it can, for example, indicate
that an individual having a cardiovascular disorder should follow a
particular statin-based treatment regimen, or should follow an
alternative treatment regimen that does not involve statin. This
information can also be used to initiate preventive treatments or
to allow an individual carrying one or more significant SNPs or SNP
haplotypes to foresee warning signs such as minor clinical symptoms
of cardiovascular disease, or to have regularly scheduled physical
exams to monitor for cardiovascular disorders in order to identify
and begin treatment of the disorder at an early stage. Particularly
with diseases that are extremely debilitating or fatal if not
treated on time, the knowledge of a potential predisposition to the
disease or likelihood of responding to available treatments, even
if this predisposition or likelihood is not absolute, would likely
contribute in a very significant manner to treatment efficacy.
[0271] The diagnostic techniques of the present invention may
employ a variety of methodologies to determine whether a test
subject has a SNP or a SNP pattern associated with an increased or
decreased risk of developing a detectable trait or whether the
individual suffers from a detectable trait as a result of a
particular polymorphism/mutation, including, for example, methods
which enable the analysis of individual chromosomes for
haplotyping, family studies, single sperm DNA analysis, or somatic
hybrids. The trait analyzed using the diagnostics of the invention
may be any detectable trait that is commonly observed in
cardiovascular disorders or during the course of statin
treatment.
[0272] Another aspect of the present invention relates to a method
of determining whether an individual is at risk (or less at risk)
of developing one or more traits or whether an individual expresses
one or more traits as a consequence of possessing a particular
trait-causing or trait-influencing allele. These methods generally
involve obtaining a nucleic acid sample from an individual and
assaying the nucleic acid sample to determine which nucleotide(s)
is/are present at one or more SNP positions, wherein the assayed
nucleotide(s) is/are indicative of an increased or decreased risk
of developing the trait or indicative that the individual expresses
the trait asia result of possessing a particular trait-causing or
trait-influencing allele.
[0273] In another embodiment, the SNP detection reagents of the
present invention are used to determine whether an individual has
one or more SNP allele(s) affecting the level (e.g., the
concentration of mRNA or protein in a sample, etc.) or pattern
(e.g., the kinetics of expression, rate of decomposition, stability
profile, Km, Vmax, etc.) of gene expression (collectively, the
"gene response" of a cell or bodily fluid). Such a determination
can be accomplished by screening for mRNA or protein expression
(e.g., by using nucleic acid arrays, RT-PCR, TaqMan assays, or mass
spectrometry), identifying genes having altered expression in an
individual, genotyping SNPs disclosed in Table 1 and/or Table 2
that could affect the expression of the genes having altered
expression (e.g., SNPs that are in and/or around the gene(s) having
altered expression, SNPs in regulatory/control regions, SNPs in
and/or around other genes that are involved in pathways that could
affect the expression of the gene(s) having altered expression, or
all SNPs could be genotyped), and correlating SNP genotypes with
altered gene expression. In this manner, specific SNP alleles at
particular SNP sites can be identified that affect gene
expression.
[0274] Pharmacogenomics and Therapeutics/Drug Development
[0275] The present invention provides methods for assessing the
pharmacogenomics of a subject harboring particular SNP alleles or
haplotypes to a particular therapeutic agent or pharmaceutical
compound, or to a class of such compounds. Pharmacogenomics deals
with the roles which clinically significant hereditary variations
(e.g., SNPs) play in the response to drugs due to altered drug
disposition and/or abnormal action in affected persons. See, e.g.,
Roses, Nature 405, 857-865 (2000); Gould Rothberg, Nature
Biotechnology 19, 209-211 (2001); Eichelbaum, Clin. Exp. Pharmacol.
Physiol. 23(10-11):983-985 (1996); and Linder, Clin. Chem.
43(2):254-266 (1997). The clinical outcomes of these variations can
result in severe toxicity of therapeutic drugs in certain
individuals or therapeutic failure of drugs in certain individuals
as a result of individual variation in metabolism. Thus, the SNP
genotype of an individual can determine the way a therapeutic
compound acts on the body or the way the body metabolizes the
compound. For example, SNPs in drug metabolizing enzymes can affect
the activity of these enzymes, which in turn can affect both the
intensity and duration of drug action, as well as drug metabolism
and clearance.
[0276] The discovery of SNPs in drug metabolizing enzymes, drug
transporters, proteins for pharmaceutical agents, and other drug
targets has explained why some patients do not obtain the expected
drug effects, show an exaggerated drug effect, or experience
serious toxicity from standard drug dosages. SNPs can be expressed
in the phenotype of the extensive metabolizer and in the phenotype
of the poor metabolizer. Accordingly, SNPs may lead to allelic
variants of a protein in which one or more of the protein functions
in one population are different from those in another population.
SNPs and the encoded variant peptides thus provide targets to
ascertain a genetic predisposition that can affect treatment
modality. For example, in a ligand-based treatment, SNPs may give
rise to amino terminal extracellular domains and/or other
ligand-binding regions of a receptor that are more or less active
in ligand binding, thereby affecting subsequent protein activation.
Accordingly, ligand dosage would necessarily be modified to
maximize the therapeutic effect within a given population
containing particular SNP alleles or haplotypes.
[0277] As an alternative to genotyping, specific variant proteins
containing variant amino acid sequences encoded by alternative SNP
alleles could be identified. Thus, pharmacogenomic characterization
of an individual permits the selection of effective compounds and
effective dosages of such compounds for prophylactic or therapeutic
uses based on the individual's SNP genotype, thereby enhancing and
optimizing the effectiveness of the therapy. Furthermore, the
production of recombinant cells and transgenic animals containing
particular SNPs/haplotypes allow effective clinical design and
testing of treatment compounds and dosage regimens. For example,
transgenic animals can be produced that differ only in specific SNP
alleles in a gene that is orthologous to a human disease
susceptibility gene.
[0278] Pharmacogenomic uses of the SNPs of the present invention
provide several significant advantages for patient care,
particularly in predicting an individual's predisposition to acute
coronary events and other cardiovascular disorders and in
predicting an individual's responsiveness to the use of statin for
treating cardiovascular disease. Pharmacogenomic characterization
of an individual, based on an individual's SNP genotype, can
identify those individuals unlikely to respond to treatment with a
particular medication and thereby allows physicians to avoid
prescribing the ineffective medication to those individuals. On the
other hand, SNP genotyping of an individual may enable physicians
to select the appropriate medication and dosage regimen that will
be most effective based on an individual's SNP genotype. This
information increases a physician's confidence in prescribing
medications and motivates patients to comply with their drug
regimens. Furthermore, pharmacogenomics may identify patients
predisposed to toxicity and adverse reactions to particular drugs
or drug dosages. Adverse drug reactions lead to more than 100,000
avoidable deaths per year in the United States alone and therefore
represent a significant cause of hospitalization and death, as well
as a significant economic burden on the healthcare system (Pfost
et. al., Trends in Biotechnology, August 2000.). Thus,
pharmacogenomics based on the SNPs disclosed herein has the
potential to both save lives and reduce healthcare costs
substantially.
[0279] Pharmacogenomics in general is discussed further in Rose et
al., "Pharmacogenetic analysis of clinically relevant genetic
polymorphisms", Methods Mol Med. 2003; 85:225-37. Pharmacogenomics
as it relates to Alzheimer's disease and other neurodegenerative
disorders is discussed in Cacabelos, "Pharmacogenomics for the
treatment of dementia", Ann Med. 2002; 34(5):357-79, Maimone et
al., "Pharmacogenomics of neurodegenerative diseases", Eur J.
Pharmacol. 2001 Feb. 9; 413(1):11-29, and Poirier, "Apolipoprotein
E: a pharmacogenetic target for the treatment of Alzheimer's
disease", Mol Diagn. 1999 December; 4(4):335-41. Pharmacogenomics
as it relates to cardiovascular disorders is discussed in Siest et
al., "Pharmacogenomics of drugs affecting the cardiovascular
system", Clin Chem Lab Med. 2003 April; 41(4):590-9, Mukhejee et
al., "Pharmacogenomics in cardiovascular diseases", Prog Cardiovasc
Dis. 2002 May-June;44(6):479-98, and Mooser et al., "Cardiovascular
pharmacogenetics in the SNP era", J Thromb Haemost. 2003 July;
1(7):1398-402. Pharmacogenomics as it relates to cancer is
discussed in McLeod et al., "Cancer pharmacogenomics: SNPs, chips,
and the individual patient", Cancer Invest. 2003; 21(4):630-40 and
Watters et al., "Cancer pharmacogenomics: current and future
applications", Biochim Biophys Acta. 2003 Mar. 17;
1603(2):99-111.
[0280] The SNPs of the present invention also can be used to
identify novel therapeutic targets for cardiovascular disorders.
For example, genes containing the disease associated variants
("variant genes") or their products, as well as genes or their
products that are directly or indirectly regulated by or
interacting with these variant genes or their products, can be
targeted for the development of therapeutics that, for example,
treat the disease or prevent or delay disease onset. The
therapeutics may be composed of, for example, small molecules,
proteins, protein fragments or peptides, antibodies, nucleic acids,
or their derivatives or mimetics which modulate the functions or
levels of the target genes or gene products.
[0281] The SNP-containing nucleic acid molecules disclosed herein,
and their complementary nucleic acid molecules, may be used as
antisense constructs to control gene expression in cells, tissues,
and organisms. Antisense technology is well established in the art
and extensively reviewed in Antisense Drug Technology: Principles,
Strategies, and Applications, Crooke (ed.), Marcel Dekker, Inc.:
New York (2001). An antisense nucleic acid molecule is generally
designed to be complementary to a region of mRNA expressed by a
gene so that the antisense molecule hybridizes to the mRNA and
thereby blocks translation of mRNA into protein. Various classes of
antisense oligonucleotides are used in the art, two of which are
cleavers and blockers. Cleavers, by binding to target RNAs,
activate intracellular nucleases (e.g., RNaseH or RNase L) that
cleave the target RNA. Blockers, which also bind to target RNAs,
inhibit protein translation through steric hindrance of ribosomes.
Exemplary blockers include peptide nucleic acids, morpholinos,
locked nucleic acids, and methylphosphonates (see, e.g., Thompson,
Drug Discovery Today, 7 (17): 912-917 (2002)). Antisense
oligonucleotides are directly useful as therapeutic agents, and are
also useful for determining and validating gene function (e.g., in
gene knock-out or knock-down experiments).
[0282] Antisense technology is further reviewed in: Lavery et al.,
"Antisense and RNAi: powerful tools in drug target discovery and
validation", Curr Opin Drug Discov Devel. 2003 July; 6(4):561-9;
Stephens et al., "Antisense oligonucleotide therapy in cancer",
Curr Opin Mol Ther. 2003 April; 5(2):118-22; Kurreck, "Antisense
technologies. Improvement through novel chemical modifications",
Eur J. Biochem. 2003 April; 270(8):1628-44; Dias et al., "Antisense
oligonucleotides: basic concepts and mechanisms", Mol Cancer Ther.
2002 March; 1(5):347-55; Chen, "Clinical development of antisense
oligonucleotides as anti-cancer therapeutics", Methods Mol. Med.
2003; 75:621-36; Wang et al., "Antisense anticancer oligonucleotide
therapeutics", Curr Cancer Drug Targets. 2001 November;
1(3):177-96; and Bennett, "Efficiency of antisense oligonucleotide
drug discovery", Antisense Nucleic Acid Drug Dev. 2002 June; 12
(3):215-24.
[0283] The SNPs of the present invention are particularly useful
for designing antisense reagents that are specific for particular
nucleic acid variants. Based on the SNP information disclosed
herein, antisense oligonucleotides can be produced that
specifically target mRNA molecules that contain one or more
particular SNP nucleotides. In this manner, expression of mRNA
molecules that contain one or more undesired polymorphisms (e.g.,
SNP nucleotides that lead to a defective protein such as an amino
acid substitution in a catalytic domain) can be inhibited or
completely blocked. Thus, antisense oligonucleotides can be used to
specifically bind a particular polymorphic form (e.g., a SNP allele
that encodes a defective protein), thereby inhibiting translation
of this form, but which do not bind an alternative polymorphic form
(e.g., an alternative SNP nucleotide that encodes a protein having
normal function).
[0284] Antisense molecules can be used to inactivate mRNA in order
to inhibit gene expression and production of defective proteins.
Accordingly, these molecules can be used to treat a disorder, such
as a cardiovascular disorder, characterized by abnormal or
undesired gene expression or expression of certain defective
proteins. This technique can involve cleavage by means of ribozymes
containing nucleotide sequences complementary to one or more
regions in the mRNA that attenuate the ability of the mRNA to be
translated. Possible mRNA regions include, for example,
protein-coding regions and particularly protein-coding regions
corresponding to catalytic activities, substrate/ligand binding, or
other functional activities of a protein.
[0285] The SNPs of the present invention are also useful for
designing RNA interference reagents that specifically target
nucleic acid molecules having particular SNP variants. RNA
interference (RNAi), also referred to as gene silencing, is based
on using double-stranded RNA (dsRNA) molecules to turn genes off.
When introduced into a cell, dsRNAs are processed by the cell into
short fragments (generally about 21, 22, or 23 nucleotides in
length) known as small interfering RNAs (siRNAs) which the cell
uses in a sequence-specific manner to recognize and destroy
complementary RNAs (Thompson, Drug Discovery Today, 7 (17): 912-917
(2002)). Accordingly, an aspect of the present invention
specifically contemplates isolated nucleic acid molecules that are
about 18-26 nucleotides in length, preferably 19-25 nucleotides in
length, and more preferably 20, 21, 22, or 23 nucleotides in
length, and the use of these nucleic acid molecules for RNAi.
Because RNAi molecules, including siRNAs, act in a
sequence-specific manner, the SNPs of the present invention can be
used to design RNAi reagents that recognize and destroy nucleic
acid molecules having specific SNP alleles/nucleotides (such as
deleterious alleles that lead to the production of defective
proteins), while not affecting nucleic acid molecules having
alternative SNP alleles (such as alleles that encode proteins
having normal function). As with antisense reagents, RNAi reagents
may be directly useful as therapeutic agents (e.g., for turning off
defective, disease-causing genes), and are also useful for
characterizing and validating gene function (e.g., in gene
knock-out or knock-down experiments).
[0286] The following references provide a further review of RNAi:
Reynolds et al., "Rational siRNA design for RNA interference", Nat
Biotechnol. 2004 March; 22(3):326-30. Epub 2004 Feb 1; Chi et al.,
"Genomewide view of gene silencing by small interfering RNAs", PNAS
100(11):6343-6346, 2003; Vickers et al., "Efficient Reduction of
Target RNAs by Small Interfering RNA and RNase H-dependent
Antisense Agents", J. Biol. Chem. 278: 7108-7118, 2003; Agami,
"RNAi and related mechanisms and their potential use for therapy",
Curr Opin Chem Biol. 2002 December; 6(6):829-34; Lavery et al.,
"Antisense and RNAi: powerful tools in drug target discovery and
validation", Curr Opin Drug Discov Devel. 2003 July; 6(4):561-9;
Shi, "Mammalian RNAi for the masses", Trends Genet 2003 January;
19(1):9-12), Shuey et al., "RNAi: gene-silencing in therapeutic
intervention", Drug Discovery Today 2002 October; 7(20):10401046;
McManus et al., Nat Rev Genet 2002 October; 3(10):737-47; Xia et
al., Nat Biotechnol 2002 October; 20(10):1006-10; Plasterk et al.,
Curr Opin Genet Dev 2000 October; 10(5):562-7; Bosher et al., Nat
Cell Biol 2000 February; 2(2):E31-6; and Hunter, Curr Biol 1999
Jun. 17; 9(12):R440-2).
[0287] A subject suffering from a pathological condition, such as a
cardiovascular disorder, ascribed to a SNP may be treated so as to
correct the genetic defect (see Kren et al., Proc. Natl. Acad. Sci.
USA 96:10349-10354 (1999)). Such a subject can be identified by any
method that can detect the polymorphism in a biological sample
drawn from the subject. Such a genetic defect may be permanently
corrected by administering to such a subject a nucleic acid
fragment incorporating a repair sequence that supplies the
normal/wild-type nucleotide at the position of the SNP. This
site-specific repair sequence can encompass an RNA/DNA
oligonucleotide that operates to promote endogenous repair of a
subject's genomic DNA. The site-specific repair sequence is
administered in an appropriate vehicle, such as a complex with
polyethylenimine, encapsulated in anionic liposomes, a viral vector
such as an adenovirus, or other pharmaceutical composition that
promotes intracellular uptake of the administered nucleic acid. A
genetic defect leading to an inborn pathology may then be overcome,
as the chimeric oligonucleotides induce incorporation of the normal
sequence into the subject's genome. Upon incorporation, the normal
gene product is expressed, and the replacement is propagated,
thereby engendering a permanent repair and therapeutic enhancement
of the clinical condition of the subject.
[0288] In cases in which a cSNP results in a variant protein that
is ascribed to be the cause of, or a contributing factor to, a
pathological condition, a method of treating such a condition can
include administering to a subject experiencing the pathology the
wild-type/normal cognate of the variant protein. Once administered
in an effective dosing regimen, the wild-type cognate provides
complementation or remediation of the pathological condition.
[0289] The invention further provides a method for identifying a
compound or agent that can be used to treat cardiovascular
disorders. The SNPs disclosed herein are useful as targets for the
identification and/or development of therapeutic agents. A method
for identifying a therapeutic agent or compound typically includes
assaying the ability of the agent or compound to modulate the
activity and/or expression of a SNP-containing nucleic acid or the
encoded product and thus identifying an agent or a compound that
can be used to treat a disorder characterized by undesired activity
or expression of the SNP-containing nucleic acid or the encoded
product. The assays can be performed in cell-based and cell-free
systems. Cell-based assays can include cells naturally expressing
the nucleic acid molecules of interest or recombinant cells
genetically engineered to express certain nucleic acid
molecules.
[0290] Variant gene expression in a patient having a cardiovascular
disorder or undergoing statin treatment can include, for example,
either expression of a SNP containing nucleic acid sequence (for
instance, a gene that contains a SNP can be transcribed into an
mRNA transcript molecule containing the SNP, which can in turn be
translated into a variant protein) or altered expression of a
normal/wild-type nucleic acid sequence due to one or more SNPs (for
instance, a regulatory/control region can contain a SNP that
affects the level or pattern of expression of a normal
transcript).
[0291] Assays for variant gene expression can involve direct assays
of nucleic acid levels (e.g., mRNA levels), expressed protein
levels, or of collateral compounds involved in a signal pathway.
Further, the expression of genes that are up- or down-regulated in
response to the signal pathway can also be assayed. In this
embodiment, the regulatory regions of these genes can be operably
linked to a reporter gene such as luciferase.
[0292] Modulators of variant gene expression can be identified in a
method wherein, for example, a cell is contacted with a candidate
compound/agent and the expression of mRNA determined. The level of
expression of mRNA in the presence of the candidate compound is
compared to the level of expression of mRNA in the absence of the
candidate compound. The candidate compound can then be identified
as a modulator of variant gene expression based on this comparison
and be used to treat a disorder such as a cardiovascular disorder
that is characterized by variant gene expression (e.g., either
expression of a SNP-containing nucleic acid or altered expression
of a normal/wild-type nucleic acid molecule due to one or more SNPs
that affect expression of the nucleic acid molecule) due to one or
more SNPs of the present invention. When expression of mRNA is
statistically significantly greater in the presence of the
candidate compound than in its absence, the candidate compound is
identified as a stimulator of nucleic acid expression. When nucleic
acid expression is statistically significantly less in the presence
of the candidate compound than in its absence, the candidate
compound is identified as an inhibitor of nucleic acid
expression.
[0293] The invention further provides methods of treatment, with
the SNP or associated nucleic acid domain (e.g., catalytic domain,
ligand/substrate-binding domain, regulatory/control region, etc.)
or gene, or the encoded mRNA transcript, as a target, using a
compound identified through drug screening as a gene modulator to
modulate variant nucleic acid expression. Modulation can include
either up-regulation (i.e., activation or agonization) or
down-regulation (i.e., suppression or antagonization) of nucleic
acid expression.
[0294] Expression of mRNA transcripts and encoded proteins, either
wild type or variant, may be altered in individuals with a
particular SNP allele in a regulatory/control element, such as a
promoter or transcription factor binding domain, that regulates
expression. In this situation, methods of treatment and compounds
can be identified, as discussed herein, that regulate or overcome
the variant regulatory/control element, thereby generating normal,
or healthy, expression levels of either the wild type or variant
protein.
[0295] The SNP-containing nucleic acid molecules of the present
invention are also useful for monitoring the effectiveness of
modulating compounds on the expression or activity of a variant
gene, or encoded product, in clinical trials or in a treatment
regimen. Thus, the gene expression pattern can serve as an
indicator for the continuing effectiveness of treatment with the
compound, particularly with compounds to which a patient can
develop resistance, as well as an indicator for toxicities. The
gene expression pattern can also serve as a marker indicative of a
physiological response of the affected cells to the compound.
Accordingly, such monitoring would allow either increased
administration of the compound or the administration of alternative
compounds to which the patient has not become resistant. Similarly,
if the level of nucleic acid expression falls below a desirable
level, administration of the compound could be commensurately
decreased.
[0296] In another aspect of the present invention, there is
provided a pharmaceutical pack comprising a therapeutic agent
(e.g., a small molecule drug, antibody, peptide, antisense or RNAi
nucleic acid molecule, etc.) and a set of instructions for
administration of the therapeutic agent to humans diagnostically
tested for one or more SNPs or SNP haplotypes provided by the
present invention.
[0297] The SNPs/haplotypes of the present invention are also useful
for improving many different aspects of the drug development
process. For instance, an aspect of the present invention includes
selecting individuals for clinical trials based on their SNP
genotype. For example, individuals with SNP genotypes that
indicates that they are likely to positively respond to a drug can
be included in the trials, whereas those individuals whose SNP
genotypes indicate that they are less likely to or would not
respond to the drug, or who are at risk for suffering toxic effects
or other adverse reactions, can be excluded from the clinical
trials. This not only can improve the safety of clinical trials;
but also can enhance the chances that the trial will demonstrate
statistically significant efficacy. Furthermore, the SNPs of the
present invention may explain why certain previously developed
drugs performed poorly in clinical trials and may help identify a
subset of the population that would benefit from a drug that had
previously performed poorly in clinical trials, thereby "rescuing"
previously developed drugs, and enabling the drug to be made
available to a particular patient population that can benefit from
it.
[0298] SNPs have many important uses in drug-discovery, screening,
and development. A high probability exists that, for any
gene/protein selected as a potential drug target, variants of that
gene/protein will exist in a patient population. Thus, determining
the impact of gene/protein variants on the selection and delivery
of a therapeutic agent should be an integral aspect of the drug
discovery and development process. (Jazwinska, A Trends Guide to
Genetic Variation and Genomic Medicine, 2002 March; S30-S36).
[0299] Knowledge of variants (e.g., SNPs and any corresponding
amino acid polymorphisms) of a particular therapeutic target (e.g.,
a gene, mRNA transcript, or protein) enables parallel screening of
the variants in order to identify therapeutic candidates (e.g.,
small molecule compounds, antibodies, antisense or RNAi nucleic
acid compounds, etc.) that demonstrate efficacy across variants
(Rothberg, Nat Biotechnol 2001 March;19(3):209-11). Such
therapeutic candidates would be expected to show equal efficacy
across a larger segment of the patient population, thereby leading
to a larger potential market for the therapeutic candidate.
[0300] Furthermore, identifying variants of a potential therapeutic
target enables the most common form of the target to be used for
selection of therapeutic candidates, thereby helping to ensure that
the experimental activity that is observed for the selected
candidates reflects the real activity expected in the largest
proportion of a patient population (Jazwinska, A Trends Guide to
Genetic Variation and Genomic Medicine, 2002 March; S30-S36).
[0301] Additionally, screening therapeutic candidates against all
known variants of a target can enable the early identification of
potential toxicities and adverse reactions relating to particular
variants. For example, variability in drug absorption,
distribution, metabolism and excretion (ADME) caused by, for
example, SNPs in therapeutic targets or drug metabolizing genes,
can be identified, and this information can be utilized during the
drug development process to minimize variability in drug
disposition and develop therapeutic agents that are safer across a
wider range of a patient population. The SNPs of the present
invention, including the variant proteins and encoding polymorphic
nucleic acid molecules provided in Tables 1-2, are useful in
conjunction with a variety of toxicology methods established in the
art, such as those set forth in Current Protocols in Toxicology,
John Wiley & Sons, Inc., N.Y.
[0302] Furthermore, therapeutic agents that target any art-known
proteins (or nucleic acid molecules, either RNA or DNA) may
cross-react with the variant proteins (or polymorphic nucleic acid
molecules) disclosed in Table 1, thereby significantly affecting
the pharmacokinetic properties of the drug. Consequently, the
protein variants and the SNP-containing nucleic acid molecules
disclosed in Tables 1-2 are useful in developing, screening, and
evaluating therapeutic agents that target corresponding art-known
protein forms (or nucleic acid molecules). Additionally, as
discussed above, knowledge of all polymorphic forms of a particular
drug target enables the design of therapeutic agents that are
effective against most or all such polymorphic forms of the drug
target.
[0303] Pharmaceutical Compositions and Administration Thereof
[0304] Any of the cardiovascular disease and/or statin
response-associated proteins, and encoding nucleic acid molecules,
disclosed herein can be used as therapeutic targets (or directly
used themselves as therapeutic compounds) for treating
cardiovascular disorders and related pathologies, and the present
disclosure enables therapeutic compounds (e.g., small molecules,
antibodies, therapeutic proteins, RNAI and antisense molecules,
etc.) to be developed that target (or are comprised of) any of
these therapeutic targets.
[0305] In general, a therapeutic compound will be administered in a
therapeutically effective amount by any of the accepted modes of
administration for agents that serve similar utilities. The actual
amount of the therapeutic compound of this invention, i.e., the
active ingredient, will depend upon numerous factors such as the
severity of the disease to be treated, the age and relative health
of the subject, the potency of the compound used, the route and
form of administration, and other factors.
[0306] Therapeutically effective amounts of therapeutic compounds
may range from, for example, approximately 0.01-50 mg per kilogram
body weight of the recipient per day; preferably about 0.1-20
mg/kg/day. Thus, as an example, for administration to a 70 kg
person, the dosage range would most preferably be about 7 mg to 1.4
g per day.
[0307] In general, therapeutic compounds will be administered as
pharmaceutical compositions by any one of the following routes:
oral, systemic (e.g., transdermal, intranasal, or by suppository),
or parenteral (e.g., intramuscular, intravenous, or subcutaneous)
administration. The preferred manner of administration is oral or
parenteral using a convenient daily dosage regimen, which can be
adjusted according to the degree of affliction. Oral compositions
can take the form of tablets, pills, capsules, semisolids, powders,
sustained release formulations, solutions, suspensions, elixirs,
aerosols, or any other appropriate compositions.
[0308] The choice of formulation depends on various factors such as
the mode of drug administration (e.g., for oral administration,
formulations in the form of tablets, pills, or capsules are
preferred) and the bioavailability of the drug substance. Recently,
pharmaceutical formulations have been developed especially for
drugs that show poor bioavailability based upon the principle that
bioavailability can be increased by increasing the surface area,
i.e., decreasing particle size. For example, U.S. Pat. No.
4,107,288 describes a pharmaceutical formulation having particles
in the size range from 10 to 1,000 nm in which the active material
is supported on a cross-linked matrix of macromolecules. U.S. Pat.
No. 5,145,684 describes the production of a pharmaceutical
formulation in which the drug substance is pulverized to
nanoparticles (average particle size of 400 nm) in the presence of
a surface modifier and then dispersed in a liquid medium to give a
pharmaceutical formulation that exhibits remarkably high
bioavailability.
[0309] Pharmaceutical compositions are comprised of, in general, a
therapeutic compound in combination with at least one
pharmaceutically acceptable excipient. Acceptable excipients are
non-toxic, aid administration, and do not adversely affect the
therapeutic benefit of the therapeutic compound. Such excipients
may be any solid, liquid, semi-solid or, in the case of an aerosol
composition, gaseous excipient that is generally available to one
skilled in the art.
[0310] Solid pharmaceutical excipients include starch, cellulose,
talc, glucose, lactose, sucrose, gelatin, malt, rice, flour, chalk,
silica gel, magnesium stearate, sodium stearate, a glycerol
monostearate, sodium chloride, dried skim milk and the like. Liquid
and semisolid excipients may be selected from glycerol, propylene
glycol, water, ethanol and various oils, including those of
petroleum, animal, vegetable or synthetic origin, e.g., peanut oil,
soybean oil, mineral oil, sesame oil, etc. Preferred liquid
carriers, particularly for injectable solutions, include water,
saline, aqueous dextrose, and glycols.
[0311] Compressed gases may be used to disperse a compound of this
invention in aerosol form. Inert gases suitable for this purpose
are nitrogen, carbon dioxide, etc.
[0312] Other suitable pharmaceutical excipients and their
formulations are described in Remington's Pharmaceutical Sciences,
edited by E. W. Martin (Mack Publishing Company, 18th ed.,
1990).
[0313] The amount of the therapeutic compound in a formulation can
vary within the full range employed by those skilled in the art.
Typically, the formulation will contain, on a weight percent (wt %)
basis, from about 0.01-99.99 wt % of the therapeutic compound based
on the total formulation, with the balance being one or more
suitable pharmaceutical excipients. Preferably, the compound is
present at a level of about 1-80 wt %.
[0314] Therapeutic compounds can be administered alone or in
combination with other therapeutic compounds or in combination with
one or more other active ingredient(s). For example, an inhibitor
or stimulator of a cardiovascular disorder-associated protein can
be administered in combination with another agent that inhibits or
stimulates the activity of the same or a different cardiovascular
disorder-associated protein to thereby counteract the affects of a
cardiovascular disorder.
[0315] For further information regarding pharmacology, see Current
Protocols in Pharmacology, John Wiley & Sons, Inc., N.Y.
[0316] Human Identification Applications
[0317] In addition to their diagnostic and therapeutic uses in
cardiovascular disorders and statin treatment of cardiovascular
disorders; the SNPs provided by the present invention are also
useful as human identification markers for such applications as
forensics, paternity testing, and biometrics (see, e.g., Gill, "An
assessment of the utility of single nucleotide polymorphisms (SNPs)
for forensic purposes", Int J Legal Med. 2001; 114(4-5):204-10).
Genetic variations in the nucleic-acid sequences between
individuals can be used as genetic markers to identify individuals
and to associate a biological sample with an individual.
Determination of which nucleotides occupy a set of SNP positions in
an individual identifies a set of SNP markers that distinguishes
the individual. The more SNP positions that are analyzed, the lower
the probability that the set of SNPs in one individual is the same
as that in an unrelated individual. Preferably, if multiple sites
are analyzed, the sites are unlinked (i.e., inherited
independently). Thus, preferred sets of SNPs can be selected from
among the SNPs disclosed herein, which may include SNPs on
different chromosomes, SNPs on different chromosome arms, and/or
SNPs that are dispersed over substantial distances along the same
chromosome arm.
[0318] Furthermore, among the SNPs disclosed herein, preferred SNPs
for use in certain forensic/human identification applications
include SNPs located at degenerate codon positions (i.e., the third
position in certain codons which can be one of two or more
alternative nucleotides and still encode the same amino acid),
since these SNPs do not affect the encoded protein. SNPs that do
not affect the encoded protein are expected to be under less
selective pressure and are therefore expected to be more
polymorphic in a population, which is typically an advantage for
forensic/human identification applications. However, for certain
forensics/human identification applications, such as predicting
phenotypic characteristics (e.g., inferring ancestry or inferring
one or more physical characteristics of an individual) from a DNA
sample, it may be desirable to utilize SNPs that affect the encoded
protein.
[0319] For many of the SNPs disclosed in Tables 1-2 (which are
identified as "Applera" SNP source), Tables 1-2 provide SNP allele
frequencies obtained by re-sequencing the DNA of chromosomes from
39 individuals (Tables 1-2 also provide allele frequency
information for "Celera" source SNPs and, where available, public
SNPs from dbEST, HGBASE, and/or HGMD). The allele frequencies
provided in Tables 1-2 enable these SNPs to be readily used for
human identification applications. Although any SNP disclosed in
Table 1 and/or Table 2 could be used for human identification, the
closer that the frequency of the minor allele at a particular SNP
site is to 50%, the greater the ability of that SNP to discriminate
between different individuals in a population since it becomes
increasingly likely that two randomly selected individuals would
have different alleles at that SNP site. Using the SNP allele
frequencies provided in Tables 1-2, one of ordinary skill in the
art could readily select a subset of SNPs for which the frequency
of the minor allele is, for example, at least 1%, 2%, 5%, 10%, 20%,
25%, 30%, 40%, 45%, or 50%, or any other frequency in-between.
Thus, since Tables 1-2 provide allele frequencies based on the
re-sequencing of the chromosomes from 39 individuals, a subset of
SNPs could readily be selected for human identification in which
the total allele count of the minor allele at a particular SNP site
is, for example, at least 1, 2, 4, 8, 10, 16, 20, 24, 30, 32, 36,
38, 39, 40, or any other number in-between.
[0320] Furthermore, Tables 1-2 also provide population group
(interchangeably referred to herein as ethnic or racial groups)
information coupled with the extensive allele frequency
information. For example, the group of 39 individuals whose DNA was
re-sequenced was made-up of 20 Caucasians and 19 African-Americans.
This population group information enables further refinement of SNP
selection for human identification. For example, preferred SNPs for
human identification can be selected from Tables 1-2 that have
similar allele frequencies in both the Caucasian and
African-American populations; thus, for example, SNPs can be
selected that have equally high discriminatory power in both
populations. Alternatively, SNPs can be selected for which there is
a statistically significant difference in allele frequencies
between the Caucasian and African-American populations (as an
extreme example, a particular allele may be observed only in either
the Caucasian or the African-American population group but not
observed in the other population group); such SNPs are useful, for
example, for predicting the race/ethnicity of an unknown
perpetrator from a biological sample such as a hair or blood stain
recovered at a crime scene. For a discussion of using SNPs to
predict ancestry from a DNA sample, including statistical methods,
see Frudakis et al., "A Classifier for the SNP-Based Inference of
Ancestry", Journal of Forensic Sciences 2003; 48(4):771-782.
[0321] SNPs have numerous advantages over other types of
polymorphic markers, such as short tandem repeats (STRs). For
example, SNPs can be easily scored and are amenable to automation,
making SNPs the markers of choice for large-scale forensic
databases. SNPs are found in much greater abundance throughout the
genome than repeat polymorphisms. Population frequencies of two
polymorphic forms can usually be determined with greater accuracy
than those of multiple polymorphic forms at multi-allelic loci.
SNPs are mutationaly more, stable than repeat polymorphisms. SNPs
are not susceptible to artefacts such as stutter bands that can
hinder analysis. Stutter bands are frequently encountered when
analyzing repeat polymorphisms, and are particularly troublesome
when analyzing samples such as crime scene samples that may contain
mixtures of DNA from multiple sources. Another significant
advantage of SNP markers over STR markers is the much shorter
length of nucleic acid needed to score a SNP. For example, STR
markers are generally several hundred base pairs in length. A SNP,
on the other hand, comprises a single nucleotide, and generally a
short conserved region on either side of the SNP position for
primer and/or probe binding. This makes SNPs more amenable to
typing in highly degraded or aged biological samples that are
frequently encountered in forensic casework in which DNA may be
fragmented into short pieces.
[0322] SNPs also are not subject to microvariant and "off-ladder"
alleles frequently encountered when analyzing STR loci.
Microvariants are deletions or insertions within a repeat unit that
change the size of the amplified DNA product so that the amplified
product does not migrate at the same rate as reference alleles with
normal sized repeat units. When separated by size, such as by
electrophoresis on a polyacrylamide gel, microvariants do not align
with a reference-allelic ladder of standard sized repeat units, but
rather migrate between the reference alleles. The reference allelic
ladder is used for precise sizing of alleles for allele
classification; therefore alleles that do not align with the
reference allelic ladder lead to substantial analysis problems.
Furthermore, when analyzing multi-allelic repeat polymorphisms,
occasionally an allele is found that consists of more or less
repeat units than has been previously seen in the population, or
more or less repeat alleles than are included in a reference
allelic ladder. These alleles will migrate outside the size range
of known alleles in a reference allelic ladder, and therefore are
referred to as "off-ladder" alleles. In extreme cases, the allele
may contain so few or so many repeats that it migrates well out of
the range of the reference allelic ladder. In this situation, the
allele may not even be observed, or, with multiplex analysis, it
may migrate within or close to the size range, for another locus,
further confounding analysis.
[0323] SNP analysis avoids the problems of microvariants and
off-ladder alleles encountered in STR analysis. Importantly,
microvariants and off-ladder alleles may provide significant
problems, and may be completely missed, when using analysis methods
such as oligonucleotide hybridization arrays, which utilize
oligonucleotide probes specific for certain known alleles.
Furthermore, off-ladder alleles and microvariants encountered with
STR analysis, even when correctly typed, may lead to improper
statistical analysis, since their frequencies in the population are
generally unknown or poorly characterized, and therefore the
statistical significance of a matching genotype may be
questionable. All these advantages of SNP analysis are considerable
in light of the consequences of most DNA identification cases,
which may lead to life imprisonment for an individual, or
re-association of remains to the family of a deceased
individual.
[0324] DNA can be isolated from biological samples such as blood,
bone, hair, saliva, or semen, and compared with the DNA from a
reference source at particular SNP positions. Multiple SNP markers
can be assayed simultaneously in order to increase the power of
discrimination and the statistical significance of a matching
genotype. For example, oligonucleotide arrays can be used to
genotype a large number of SNPs simultaneously. The SNPs provided
by the present invention can be assayed in combination with other
polymorphic genetic markers, such as other SNPs known in the art or
STRs, in order to identify an individual or to associate an
individual with a particular biological sample.
[0325] Furthermore, the SNPs provided by the present invention can
be genotyped for inclusion in a database of DNA genotypes, for
example, a criminal DNA databank such as the FBI's Combined DNA
Index System (CODIS) database. A genotype obtained from a
biological sample of unknown source can then be queried against the
database to find a matching genotype, with the SNPs of the present
invention providing nucleotide positions at which to compare the
known and unknown DNA sequences for identity. Accordingly, the
present invention provides a database comprising novel SNPs or SNP
alleles of the present invention (e.g., the database can comprise
information indicating which alleles are possessed by individual
members of a population at one or more novel SNP sites of the
present invention), such as for use in forensics, biometrics, or
other human identification applications. Such a database typically
comprises a computer-based system in which the SNPs or SNP alleles
of the present invention are recorded on a computer readable medium
(see the section of the present specification entitled
"Computer-Related Embodiments").
[0326] The SNPs of the present invention can also be assayed for
use in paternity testing. The object of paternity testing is
usually to determine whether a male is the father of a child. In
most cases, the mother of the child is known and thus, the mother's
contribution to the child's genotype can be traced. Paternity
testing investigates whether the part of the child's genotype not
attributable to the mother is consistent with that of the putative
father. Paternity testing can be performed by analyzing sets of
polymorphisms in the putative father and the child, with the SNPs
of the present invention providing nucleotide positions at which to
compare the putative father's and child's DNA sequences for
identity. If the set of polymorphisms in the child attributable to
the father does not match the set of polymorphisms of the putative
father, it can be concluded, barring experimental error, that the
putative father is not the father of the child. If the set of
polymorphisms in the child attributable to the father match the set
of polymorphisms of the putative father, a statistical calculation
can be performed to determine the probability of coincidental
match, and a conclusion drawn as to the likelihood that the
putative father is the true biological father of the child.
[0327] In addition to paternity testing, SNPs are also useful for
other types of kinship testing, such as for verifying familial
relationships for immigration purposes, or for cases in which an
individual alleges to be related to a deceased individual in order
to claim an inheritance from the deceased individual, etc. For
further information regarding the utility of SNPs for paternity
testing and other types of kinship testing, including methods for
statistical analysis, see Krawczak, "Informativity assessment for
biallelic single nucleotide polymorphisms", Electrophoresis 1999
June; 20(8):1676-81.
[0328] The use of the SNPs of the present invention for human
identification further extends to various authentication systems,
commonly referred to as biometric systems, which typically convert
physical characteristics of humans (or other organisms) into
digital data. Biometric systems include various technological
devices that measure such unique anatomical or physiological
characteristics as finger, thumb, or palm prints; hand geometry;
vein patterning on the back of the hand; blood vessel patterning of
the retina and color and texture of the iris; facial
characteristics; voice patterns; signature, and typing dynamics and
DNA. Such physiological measurements can be used to verify identity
and, for example, restrict or allow access based on the
identification. Examples of applications for biometrics include
physical area security, computer and network security, aircraft
passenger check-in and boarding, financial transactions, medical
records access, government benefit distribution, voting, law
enforcement, passports, visas and immigration, prisons, various
military applications, and for restricting access to expensive or
dangerous items, such as automobiles or guns (see, for example,
O'Connor, Stanford Technology Law Review and U.S. Pat. No.
6,119,096).
[0329] Groups of SNPs, particularly the SNPs provided by the
present invention, can be typed to uniquely identify an individual
for biometric applications such as those described above. Such SNP
typing can readily be accomplished using, for example, DNA
chips/arrays. Preferably, a minimally invasive means for obtaining
a DNA sample is utilized. For example, PCR amplification enables
sufficient quantities of DNA for analysis to be obtained from
buccal swabs or fingerprints, which contain DNA-containing skin
cells and oils that are naturally transferred during contact.
[0330] Further information regarding techniques for using SNPs in
forensic/human identification applications can be found in, for
example, Current Protocols in Human Genetics, John Wiley &
Sons, N.Y. (2002), 14.1-14.7.
[0331] Variant Proteins, Antibodies, Vectors & Host Cells,
& Uses Thereof
[0332] Variant Proteins Encoded by SNP-Containing Nucleic Acid
Molecules
[0333] The present invention provides SNP-containing nucleic acid
molecules, many of which encode proteins having variant amino
acid-sequences as compared to the art-known (i.e., wild-type)
proteins. Amino acid sequences encoded by the polymorphic nucleic
acid molecules of the present invention are provided as SEQ ID
NOS:518-1034 in Table 1 and the Sequence Listing. These variants
will generally be referred to herein as variant
proteins/peptides/polypeptides, or polymorphic
proteins/peptides/polypeptides of the present invention. The terms
"protein", "peptide", and "polypeptide" are used herein
interchangeably.
[0334] A variant protein of the present invention may be encoded
by, for example, a nonsynonymous nucleotide substitution at any one
of the cSNP positions disclosed herein. In addition, variant
proteins may also include proteins whose expression, structure,
and/or function is altered by a SNP disclosed herein, such as a SNP
that creates or destroys a stop codon, a SNP that affects splicing,
and a SNP in control/regulatory elements, e.g. promoters,
enhancers, or transcription factor binding domains.
[0335] As used herein, a protein or peptide is said to be
"isolated" or "purified" when it is substantially free of cellular
material or chemical precursors or other chemicals. The variant
proteins of the present invention can be purified to homogeneity or
other lower degrees of purity. The level of purification will be
based on the intended use. The key feature is that the preparation
allows for the desired function of the variant protein, even if in
the presence of considerable amounts of other components.
[0336] As used herein, "substantially free of cellular material"
includes preparations of the variant protein having less than about
30% (by dry weight) other proteins (i.e., contaminating protein),
less than about 20% other proteins, less than about 10% other
proteins, or less than about 5% other proteins. When the variant
protein is recombinantly produced, it can also be substantially
free of culture medium, i.e., culture medium represents less than
about 20% of the volume of the protein preparation.
[0337] The language "substantially free of chemical precursors or
other chemicals" includes preparations of the variant protein in
which it is separated from chemical precursors or other chemicals
that are involved in its synthesis. In one embodiment, the language
"substantially free of chemical precursors or other chemicals"
includes preparations of the variant protein having less than about
30% (by dry weight) chemical precursors or other chemicals, less
than about 20% chemical precursors or other chemicals, less than
about 10% chemical precursors or other chemicals, or less than
about 5% chemical-precursors or other chemicals.
[0338] An isolated variant protein may be purified from cells that
naturally express it, purified from cells that have been altered to
express it (recombinant host cells), or synthesized using known
protein synthesis methods. For example, a nucleic acid molecule
containing SNP(s) encoding the variant protein can be cloned into
an expression vector, the expression vector introduced into a host
cell, and the variant protein expressed in the host cell. The
variant protein can then be isolated from the cells by any
appropriate purification scheme using standard protein purification
techniques. Examples of these techniques are described in detail
below (Sambrook and Russell, 2000, Molecular Cloning: A Laboratory
Manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor,
N.Y.).
[0339] The present invention provides isolated variant proteins
that comprise, consist of or consist essentially of amino acid
sequences that contain one or more variant amino acids encoded by
one or more codons which contain a SNP of the present
invention.
[0340] Accordingly, the present invention provides variant proteins
that consist of amino acid sequences that contain one or more amino
acid polymorphisms (or truncations or extensions due to creation or
destruction of a stop codon, respectively) encoded by the SNPs
provided in Table 1 and/or Table 2. A protein consists of an amino
acid sequence when the amino acid sequence is the entire amino acid
sequence of the protein.
[0341] The present invention further provides variant proteins that
consist essentially of amino acid sequences that contain one or
more amino acid polymorphisms (or truncations or extensions due to
creation or destruction of a stop codon, respectively) encoded by
the SNPs provided in Table 1 and/or Table 2. A protein consists
essentially of an amino acid sequence when such an amino acid
sequence is present with only a few additional amino acid residues
in the final protein.
[0342] The present invention further provides variant proteins that
comprise amino acid sequences that contain one or more amino acid
polymorphisms (or truncations or extensions due to creation or
destruction of a stop codon, respectively) encoded by the SNPs
provided in Table 1 and/or Table 2. A protein comprises an amino
acid sequence when the amino acid sequence is at least part of the
final amino acid sequence of the protein. In such a fashion, the
protein may contain only the variant amino acid sequence or have
additional amino acid residues, such as a contiguous encoded
sequence that is naturally associated with it or heterologous amino
acid residues. Such a protein can have a few additional amino acids
residues or can comprise many more additional amino acids. A brief
description of how various types of these proteins can be made and
isolated is provided below.
[0343] The variant proteins of the present invention can be
attached to heterologous sequences to form chimeric or fusion
proteins. Such chimeric and fusion proteins comprise a variant
protein operatively linked to a heterologous protein having an
amino acid sequence not substantially homologous to the variant
protein. "Operatively linked" indicates that the coding sequences
for the variant protein and the heterologous protein are ligated
in-frame. The heterologous protein can be fused to the N-terminus
or C-terminus of the variant protein. In another embodiment, the
fusion protein is encoded by a fusion polynucleotide that is
synthesized by conventional techniques including automated DNA
synthesizers. Alternatively, PCR amplification of gene fragments
can be carried out using anchor primers which give rise to
complementary overhangs between two consecutive gene fragments
which can subsequently be annealed and re-amplified to generate a
chimeric gene sequence (see Ausubel et al., Current Protocols in
Molecular Biology, 1992). Moreover, many expression vectors are
commercially available that already encode a fusion moiety (e.g., a
GST protein). A variant protein-encoding nucleic acid can be cloned
into such an expression vector such that the fusion moiety is
linked in-frame to the variant protein.
[0344] In many uses, the fusion protein does not affect the
activity of the variant protein. The fusion protein can include,
but is not limited to, enzymatic fusion proteins, for example,
beta-galactosidase fusions, yeast two-hybrid GAL fusions, poly-His
fusions, MYC-tagged, HI-tagged and Ig fusions. Such fusion
proteins, particularly poly-His fusions, can facilitate their
purification following recombinant expression. In certain host
cells (e.g., mammalian host cells), expression and/or secretion of
a protein can be increased by using a heterologous signal sequence.
Fusion proteins are further described in, for example, Terpe,
"Overview of tag protein fusions: from molecular and biochemical
fundamentals to commercial systems", Appl Microbiol Biotechnol.
2003 January; 60(5):523-33. Epub 2002 Nov. 7; Graddis et al.,
"Designing proteins that work using recombinant technologies", Curr
Pharm Biotechnol. 2002 December; 3(4):285-97; and Nilsson et al.,
"Affinity fusion strategies for detection, purification, and
immobilization of recombinant proteins'"; Protein Expr Purif 1997
October; 11(1):1-16.
[0345] The present invention also relates to further obvious
variants of the variant polypeptides of the present invention, such
as naturally-occurring mature forms (e.g., alleleic variants),
non-naturally occurring recombinantly-derived variants, and
orthologs and, paralogs of such proteins that share sequence
homology. Such variants can readily be generated using art-known
techniques in the fields of recombinant nucleic acid technology and
protein biochemistry. It is understood, however, that variants
exclude those known in the prior art before the present
invention.
[0346] Further variants of the variant polypeptides disclosed in
Table 1 can comprise an amino acid sequence that shares at least
70-80%, 80-85%, 85-90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or
99% sequence identity with an amino acid sequence disclosed in
Table 1 (or a fragment thereof) and that includes a novel amino
acid residue (allele) disclosed in Table 1 (which is encoded by a
novel SNP allele). Thus, an aspect of the present invention that is
specifically contemplated are polypeptides that have a certain
degree of sequence variation compared with the polypeptide
sequences shown in Table 1, but that contain a novel amino acid
residue (allele) encoded by a novel SNP allele disclosed herein. In
other words, as long as a polypeptide contains a novel amino acid
residue disclosed herein, other portions of the polypeptide that
flank the novel amino acid residue can vary to some degree from the
polypeptide sequences shown in Table 1.
[0347] Full-length pre-processed forms, as well as mature processed
forms, of proteins that comprise one of the amino acid sequences
disclosed herein can readily be identified as having complete
sequence identity to one of the variant proteins of the present
invention as well as being encoded by the same genetic locus as the
variant proteins provided herein.
[0348] Orthologs of a variant peptide can readily be identified as
having some degree of significant sequence homology/identity to at
least a portion of a variant peptide as well as being encoded by a
gene from another organism. Preferred orthologs will be isolated
from non-human mammals, preferably primates, for the development of
human therapeutic targets and agents. Such orthologs can be encoded
by a nucleic acid sequence that hybridizes to a variant
peptide-encoding nucleic acid molecule under moderate to stringent
conditions depending on the degree of relatedness of the two
organisms yielding the homologous proteins.
[0349] Variant proteins include, but are not limited to, proteins
containing deletions, additions and substitutions in the amino acid
sequence caused by the SNPs of the present invention. One class of
substitutions is conserved amino acid substitutions in which a
given amino acid in a polypeptide is substituted for another amino
acid of like characteristics. Typical conservative substitutions
are replacements, one for another, among the aliphatic amino acids
Ala, Val, Leu, and Ile; interchange of the hydroxyl residues Ser
and Thr; exchange of the acidic residues Asp and Glu; substitution
between the amide residues Asn and Gln; exchange of the basic
residues Lys and Arg; and replacements among the aromatic residues
Phe and Tyr. Guidance concerning which amino acid changes are
likely to be phenotypically silent are found in, for example, Bowie
et al., Science 247:1306-1310 (1990).
[0350] Variant proteins can be fully functional or can lack
function in one or more activities, e.g. ability to bind another
molecule, ability to catalyze a substrate, ability to mediate
signaling, etc. Fully functional variants typically contain only
conservative variations or variations in non-critical residues or
in non-critical regions. Functional variants can also contain
substitution of similar amino acids that result in no change or an
insignificant change in function. Alternatively, such substitutions
may positively or negatively affect function to some degree.
Non-functional variants typically contain one or more
non-conservative amino acid substitutions, deletions, insertions,
inversions, truncations or extensions, or a substitution,
insertion, inversion, or deletion of a critical residue or in a
critical region.
[0351] Amino acids that are essential for function of a protein can
be identified by methods known in the art, such as site-directed
mutagenesis or alanine-scanning mutagenesis (Cunningham et al.,
Science 244:1081-1085 (1989)), particularly using the amino acid
sequence and polymorphism information provided in Table 1. The
latter procedure introduces single alanine mutations at every
residue in the molecule. The resulting mutant molecules are then
tested for biological activity such as enzyme activity or in assays
such as an in vitro proliferative activity. Sites that are critical
for binding partner/substrate binding can also be determined by
structural analysis such as crystallization, nuclear magnetic
resonance or photoaffinity labeling (Smith et al., J. Mol. Biol.
224:899-904 (1992); de Vos et al Science 255:306-312 (1992)).
[0352] Polypeptides can contain amino acids other than the 20 amino
acids commonly referred to as the 20 naturally occurring amino
acids. Further, many amino acids, including the terminal amino
acids, may be modified by natural processes, such as processing and
other post-translational modifications, or by chemical modification
techniques well known in the art. Accordingly, the variant proteins
of the present invention also encompass derivatives or analogs in
which a substituted amino acid residue is not one encoded by the
genetic code, in which a substituent group is included, in which
the mature polypeptide is fused with another compound, such as a
compound to increase the half-life of the polypeptide (e.g.,
polyethylene glycol), or in which additional amino acids are fused
to the mature polypeptide, such as a leader or secretory sequence
or a sequence for purification of the mature polypeptide or a
pro-protein sequence.
[0353] Known protein modifications include, but are not limited to,
acetylation, acylation, ADP-ribosylation, amidation, covalent
attachment of flavin, covalent attachment of a heme moiety,
covalent attachment of a nucleotide or nucleotide derivative,
covalent attachment of a lipid or lipid derivative, covalent
attachment of phosphotidylinositol, cross-linking, cyclization,
disulfide bond formation, demethylation, formation of covalent
crosslinks, formation of cystine, formation of pyroglutamate,
formylation, gamma carboxylation, glycosylation, GPI anchor
formation, hydroxylation, iodination, methylation, myristoylation,
oxidation, proteolytic processing, phosphorylation, prenylation,
racemization, selenoylation, sulfation, transfer-RNA mediated
addition of amino acids to proteins such as arginylation, and
ubiquitination.
[0354] Such protein modifications are well known to those of skill
in the art and have been described in great detail in the
scientific literature. Several particularly common modifications,
glycosylation, lipid attachment, sulfation, gamma-carboxylation of
glutamic acid residues, hydroxylation and ADP-ribosylation, for
instance, are described in most basic texts, such as
Proteins--Structure and Molecular Properties, 2nd Ed., T. E.
Creighton, W. H. Freeman and Company, New York (1993); Wold, F.,
Posttranslational Covalent Modification of Proteins, B. C. Johnson,
Ed., Academic Press, New York 1-12(1983); Seifter et al., Meth.
Enzymol 182: 626-646 (0.1990); and Rattan et al., Ann. N.Y. Acad.
Sci. 663:48-62 (1992).
[0355] The present invention further provides fragments of the
variant proteins in which the fragments contain one or more amino
acid sequence variations (e.g., substitutions, or truncations or
extensions due to creation for destruction of a stop codon) encoded
by one or more SNPs disclosed herein. The fragments to which the
invention pertains, however, are not to be construed as
encompassing fragments that have been disclosed in the prior art
before the present invention.
[0356] As used herein, a fragment may comprise at least about 4, 8,
10, 12, 14, 16, 18, 20, 25, 30, 50, 100 (or any other number
in-between) or more contiguous amino acid residues from a variant
protein, wherein at least one amino acid residue is affected by a
SNP of the present invention, e.g., a variant amino acid residue
encoded by a nonsynonymous nucleotide substitution at a cSNP
position provided by the present invention. The variant amino acid
encoded by a cSNP may occupy any residue position along the
sequence of the fragment. Such fragments can be chosen based on the
ability to retain one or more of the biological activities of the
variant protein or the ability to perform a function, e.g., act as
an immunogen. Particularly important fragments are biologically
active fragments. Such fragments will typically comprise a domain
or motif of a variant protein of the present invention, e.g.,
active site, transmembrane domain, or ligand/substrate binding
domain. Other fragments include, but are not limited to, domain or
motif-containing fragments, soluble peptide fragments, and
fragments containing immunogenic structures. Predicted domains and
functional sites are readily identifiable by computer programs well
known to those of skill in the art (e.g., PROSITE analysis)
(Current Protocols in Protein Science, John Wiley & Sons, N.Y.
(2002)).
[0357] Uses of Variant Proteins
[0358] The variant proteins of the present invention can be used in
a variety of ways, including but not limited to, in assays to
determine the biological activity of a variant protein, such as in
a panel of multiple proteins for high-throughput screening; to
raise antibodies or to elicit another type of immune response; as a
reagent (including the labeled reagent) in assays designed to
quantitatively determine levels of the variant protein (or its
binding partner) in biological fluids; as a marker for cells or
tissues in which it is preferentially expressed (either
constitutively or at a particular stage of tissue differentiation
or development or in a disease state); as a target for screening
for a therapeutic agent; and as a direct therapeutic agent to be
administered into a human subject. Any of the variant proteins
disclosed herein may be developed into reagent grade or kit format
for commercialization as research products. Methods for performing
the uses listed above are well known to those skilled in the art
(see, e.g., Molecular Cloning: A Laboratory Manual, Cold Spring
Harbor Laboratory Press, Sambrook and Russell, 2000, and Methods in
Enzymology: Guide to Molecular Cloning Techniques, Academic Press,
Berger, S. L. and A. R. Kimmel eds., 1987).
[0359] In a specific embodiment of the invention, the methods of
the present invention include detection of one or more variant
proteins disclosed herein. Variant proteins are disclosed in Table
1 and in the Sequence Listing as SEQ ID NOS: 518-1034. Detection of
such proteins can be accomplished using, for example, antibodies,
small molecule compounds, aptamers, ligands/substrates, other
proteins or protein fragments, or other protein binding agents.
Preferably, protein detection agents are specific for a variant
protein of the present invention and can therefore discriminate
between a variant protein of the present invention and the
wild-type protein or another variant form. This can generally be
accomplished by, for example, selecting or designing detection
agents that bind to the region of a protein that differs between
the variant and wild-type protein, such as a region of a protein
that contains one or more amino acid substitutions that is/are
encoded by a non-synonymous cSNP of the present invention, or a
region of a protein that follows a nonsense mutation-type SNP that
creates a stop codon thereby leading to a shorter polypeptide, or a
region of a protein that follows a read-through mutation-type SNP
that destroys a stop codon thereby leading to a longer polypeptide
in which a portion of the polypeptide is present in one version of
the polypeptide but not the other.
[0360] In another specific aspect of the invention, the variant
proteins of the present invention are used as targets for
evaluating an individual's predisposition to developing a
cardiovascular disorder, particularly an acute coronary event such
as myocardial infarction, or stroke, for treating and/or preventing
cardiovascular disorders, of for predicting an individuals response
to statin treatment of cardiovascular disorders, etc. Accordingly,
the invention provides methods for detecting the presence of, or
levels of; one or more variant proteins of the present invention in
a cell, tissue, or organism. Such methods typically involve
contacting a test sample with an agent (e.g., an antibody, small
molecule compound, or peptide) capable of interacting with the
variant protein such that specific binding of the agent to the
variant protein can be detected. Such an assay can be provided in a
single detection format or a multi-detection format such as an
array, for example, an antibody or aptamer array (arrays for
protein detection may also be referred to as "protein chips"). The
variant protein of interest can be isolated from a test sample and
assayed for the presence of a variant amino acid sequence encoded
by one or more SNPs disclosed by the present invention. The SNPs
may cause changes to the protein and the corresponding protein
function/activity, such as through non-synonymous substitutions in
protein coding regions that can lead to amino acid substitutions,
deletions, insertions, and/or rearrangements; formation or
destruction of stop codons; or alteration of control elements such
as promoters. SNPs may also cause inappropriate post-translational
modifications.
[0361] One preferred agent for detecting a variant protein in a
sample is an antibody capable of selectively binding to a variant
form of the protein (antibodies are described in greater detail in
the next section). Such samples include, for example, tissues,
cells, and biological fluids isolated from a subject, as well as
tissues, cells and fluids present within a subject.
[0362] In vitro methods for detection of the variant proteins
associated with cardiovascular disorders and/or statin response
that are disclosed herein and fragments thereof include, but are
not limited to, enzyme linked immunosorbent assays (ELISAs),
radioimmunoassays (RIA), Western blots, immunoprecipitations,
immunofluorescence, and protein arrays/chips (e.g., arrays of
antibodies or aptamers). For further information regarding
immunoassays and related protein detection methods, see Current
Protocols in Immunology, John Wiley & Sons, N.Y., and Hage,
"Immunoassays", Anal Chem. 1999 Jun. 15; 71(12):294R-304R.
[0363] Additional analytic methods of detecting amino acid variants
include, but are not limited to, altered electrophoretic mobility,
altered tryptic peptide digest, altered protein activity in
cell-based or cell-free assay, alteration in ligand or
antibody-binding pattern, altered isoelectric point, and direct
amino acid sequencing.
[0364] Alternatively, variant proteins can be detected in vivo in a
subject by introducing into the subject a labeled antibody (or
other type of detection reagent) specific for a variant protein.
For example, the antibody can be labeled with a radioactive marker
whose presence and location in a subject can be detected by
standard imaging techniques.
[0365] Other uses of the variant peptides of the present invention
are based on the class or action of the protein. For example,
proteins isolated from humans and their mammalian orthologs serve
as targets for identifying agents (e.g., small molecule drugs or
antibodies) for use in therapeutic applications, particularly for
modulating a biological or pathological response in a cell or
tissue that expresses the protein. Pharmaceutical agents can be
developed that modulate protein activity.
[0366] As an alternative to modulating gene expression, therapeutic
compounds can be developed that modulate protein function. For
example, many SNPs disclosed herein affect the amino acid sequence
of the encoded protein (e.g., non-synonymous cSNPs and nonsense
mutation-type SNPs). Such alterations in the encoded amino acid
sequence may affect protein function, particularly if such amino
acid sequence variations occur in functional protein domains, such
as catalytic domains, ATP-binding domains, or ligand/substrate
binding domains. It is well established in the art that variant
proteins having amino acid sequence variations in functional
domains can cause or influence pathological conditions. In such
instances, compounds (e.g., small molecule drugs or antibodies) can
be developed that target the variant protein and modulate (e.g.,
up- or down-regulate) protein function/activity.
[0367] The therapeutic methods of the present invention further
include methods that target one or more variant proteins of the
present invention. Variant proteins can be targeted using, for
example, small molecule compounds, antibodies, aptamers,
ligands/substrates, other proteins, or other protein-binding
agents. Additionally, the skilled artisan will recognize that the
novel protein variants (and polymorphic nucleic acid molecules)
disclosed in Table 1 may themselves be directly used as therapeutic
agents by acting as competitive inhibitors of corresponding
art-known proteins (or nucleic acid molecules such as mRNA
molecules).
[0368] The variant proteins of the present invention are
particularly useful in drug screening assays, in cell-based or
cell-free systems. Cell-based systems can utilize cells that
naturally express the protein, a biopsy specimen, or cell cultures.
In one embodiment, cell-based assays involve recombinant host cells
expressing the variant protein. Cell-free assays can be used to
detect the ability of a compound to directly bind to a variant
protein or to the corresponding SNP-containing nucleic acid
fragment that encodes the variant protein.
[0369] A variant protein of the present invention, as well as
appropriate fragments thereof, can be used in high-throughput
screening assays to test, candidate compounds for the ability to
bind and/or modulate the activity of the variant protein. These
candidate compounds can be further screened against a protein
having normal function (e.g., a wild-type/non-variant protein) to
further determine the effect of the compound on the protein
activity. Furthermore, these compounds can be tested in animal or
invertebrate systems to determine in vivo activity/effectiveness.
Compounds can be identified that activate (agonists) or inactivate
(antagonists) the variant protein, and different compounds can be
identified that cause various degrees of activation or inactivation
of the variant protein.
[0370] Further, the variant proteins can be used to screen a
compound for the ability to stimulate or inhibit interaction
between the variant protein and a target molecule that normally
interacts with the protein. The target can be a ligand, a substrate
or a binding partner that the protein normally interacts with (for
example, epinephrine or norepinephrine). Such assays typically
include the steps of combining the variant protein with a candidate
compound under conditions that allow the variant protein, or
fragment thereof, to interact with the target molecule, and to
detect the formation of a complex between the protein and the
target or to detect the biochemical consequence of the interaction
with the variant protein and the target, such as any of the
associated effects of signal transduction.
[0371] Candidate compounds include, for example, 1) peptides such
as soluble peptides, including Ig-tailed fusion peptides and
members of random peptide libraries (see, e.g., Lam et al., Nature
354:82-84 (1991); Houghten et al., Nature 354:84-86 (1991)) and
combinatorial chemistry-derived molecular libraries made of D-
and/or L-configuration amino acids; 2) phosphopeptides (e.g.,
members of random and partially degenerate, directed phosphopeptide
libraries, see, e.g., Songyang et al., Cell 72:767-778 (1993)); 3)
antibodies (e.g., polyclonal, monoclonal, humanized,
anti-idiotypic, chimeric, and single chain antibodies as well as
Fab, F(ab').sub.2, Fab expression library fragments, and
epitope-binding fragments of antibodies); and 4) small organic and
inorganic molecules (e.g., molecules obtained from combinatorial
and natural product libraries).
[0372] One candidate compound is a soluble fragment of the variant
protein that competes for ligand binding. Other candidate compounds
include mutant proteins or appropriate fragments containing
mutations that affect variant protein function and thus compete for
ligand. Accordingly, a fragment that compete for ligand, for
example with a higher affinity, or a fragment that binds ligand but
does not allow release, is encompassed by the invention.
[0373] The invention further includes other end point assays to
identify compounds that modulate (stimulate or inhibit) variant
protein activity. The assays typically involve an assay of events
in the signal transduction pathway that indicate protein activity.
Thus, the expression of genes that are up or down-regulated in
response to the variant protein dependent signal cascade can be
assayed. In one embodiment, the regulatory region of such genes can
be operably linked to a marker that is easily detectable, such as
luciferase. Alternatively, phosphorylation of the variant protein,
or a variant protein target, could also be measured. Any of the
biological or biochemical functions mediated by the variant protein
can be used as an endpoint assay. These include all of the
biochemical or biological events described herein, in the
references cited herein, incorporated by reference for these
endpoint assay targets, and other functions known to those of
ordinary skill in the art.
[0374] Binding and/or activating compounds can also be screened by
using chimeric variant proteins in which an amino terminal
extracellular domain or parts thereof, an entire transmembrane
domain or subregions, and/or the carboxyl terminal intracellular
domain or parts thereof, can be replaced by heterologous domains or
subregions. For example, a substrate-binding region can be used
that interacts with a different substrate than that which is
normally recognized by a variant protein. Accordingly, a different
set of signal transduction components is available as an end-point
assay for activation. This allows for assays to be performed in
other than the specific host cell from which the variant protein is
derived.
[0375] The variant proteins are also useful in competition binding
assays in methods designed to discover compounds that interact with
the variant protein. Thus, a compound can be exposed to a variant
protein under conditions that allow the compound to bind or to
otherwise interact with the variant protein. A binding partner,
such as ligand, that normally interacts with the variant protein is
also added to the mixture. If the test compound interacts with the
variant protein or its binding partner, it decreases the amount of
complex formed or activity from the variant protein. This type of
assay is particularly useful in screening for compounds that
interact with specific regions of the variant protein (Hodgson,
Bio/technology, 1992, Sep. 10(9), 973-80).
[0376] To perform cell-free drug screening assays, it is sometimes
desirable to immobilize either the variant protein or a fragment
thereof, or its target molecule, to facilitate separation of
complexes from uncomplexed forms of one or both of the proteins as
well as to accommodate automation of the assay. Any method for
immobilizing proteins on matrices can be used in drug screening
assays. In one embodiment, a fusion protein containing an added
domain allows the protein to be bound to a matrix. For example,
glutathione-S-transferase/.sup.125, fusion proteins can be adsorbed
onto glutathione sepharose beads (Sigma Chemical, St. Louis, Mo.)
or glutathione derivatized microtitre plates, which are then
combined with the cell lysates (e.g., .sup.35S-labeled) and a
candidate compound, such as a drug candidate, and the mixture
incubated under conditions conducive to complex formation (e.g., at
physiological conditions for salt and pH). Following incubation,
the beads can be washed to remove any unbound label, and the matrix
immobilized and radiolabel determined directly, or in the
supernatant after the complexes are dissociated. Alternatively, the
complexes can be dissociated from the matrix, separated by
SDS-PAGE, and the level of bound material found in the bead
fraction quantitated from the gel using standard electrophoretic
techniques.
[0377] Either the variant protein or its target molecule can be
immobilized utilizing conjugation of biotin and streptavidin.
Alternatively, antibodies reactive with the variant protein but
which do not interfere with binding of the variant protein to its
target molecule can be derivatized to the wells of the plate, and
the variant protein trapped in the wells by antibody conjugation.
Preparations of the target molecule and a candidate compound are
incubated in the variant protein-presenting wells and the amount of
complex trapped in the well can be quantitated. Methods for
detecting such complexes, in addition to those described above for
the GST-immobilized complexes, include immunodetection of complexes
using antibodies reactive with the protein target molecule, or
which are reactive with variant protein and compete with the target
molecule, and enzyme-linked assays that rely on detecting an
enzymatic activity associated with the target molecule.
[0378] Modulators of variant protein activity identified according
to these drug screening assays can be used to treat a subject with
a disorder mediated by the protein pathway, such as cardiovascular
disease. These methods of treatment typically include the steps of
administering the modulators of protein activity in a
pharmaceutical composition toga subject in need of such
treatment.
[0379] The variant proteins, or fragments thereof, disclosed herein
can themselves be directly used to treat a disorder characterized
by an absence of, inappropriate, or unwanted expression or activity
of the variant protein. Accordingly, methods for treatment include
the use of a variant protein disclosed herein or fragments
thereof.
[0380] In yet another aspect of the invention, variant proteins can
be used as "bait proteins" in a two-hybrid assay or three-hybrid
assay (see, e.g., U.S. Pat. No. 5,283,317; Zervos et al. (1993)
Cell 72:223-232; Madura et al. (1993) J. Biol. Chem.
268:12046-12054; Bartel et al. (1993) Biotechniques 14:920-924;
Iwabuchi et al. (1993) Oncogene 8:1693-1696; and Brent WO94/10300)
to identify other proteins that bind to or interact with the
variant protein and are involved in variant protein activity. Such
variant protein-binding proteins are also likely to be involved in
the propagation of signals by the variant proteins or variant
protein targets as, for example, elements of a protein-mediated
signaling pathway. Alternatively, such variant protein-binding
proteins are inhibitors of the variant protein.
[0381] The two-hybrid system is based on the modular nature of most
transcription factors, which typically consist of separable
DNA-binding and activation domains. Briefly, the assay typically
utilizes two different DNA constructs. In one construct, the gene
that codes for a variant protein is fused to a gene encoding the
DNA binding domain of a known transcription factor (e.g., GAL-4).
In the other construct, a DNA sequence, from a library of DNA
sequences, that encodes an unidentified protein ("prey" or
"sample") is fused to a gene that codes for the activation domain
of the known transcription factor. If the "bait" and the "prey"
proteins are able to interact, in vivo, forming a variant
protein-dependent complex, the DNA-binding and activation domains
of the transcription factor are brought into close proximity. This
proximity allows transcription of a reporter gene (e.g., LacZ) that
is operably linked to a transcriptional regulatory site responsive
to the transcription factor. Expression of the reporter gene can be
detected, and cell colonies containing the functional transcription
factor can be isolated and used to obtain the cloned gene that
encodes the protein that interacts with the variant protein.
[0382] Antibodies Directed to Variant Proteins
[0383] The present invention also provides antibodies that
selectively bind to the variant proteins disclosed herein and
fragments thereof. Such antibodies may be used to quantitatively or
qualitatively detect the variant proteins of the present invention.
As used herein, an antibody selectively binds a target variant
protein when it binds the variant protein and does not
significantly bind to non-variant proteins, i.e., the antibody does
not significantly bind to normal, wild-type, or art-known proteins
that do not contain a variant amino acid sequence due to one or
more SNPs of the present invention (variant amino acid sequences
may be due to, for example, nonsynonymous cSNPs, nonsense SNPs that
create a stop codon, thereby causing a truncation of a polypeptide
or SNPs that cause read-through mutations resulting in an extension
of a polypeptide).
[0384] As used herein, an antibody is defined in terms consistent
with that recognized in the art: they are multi-subunit proteins
produced by an organism in response to an antigen challenge. The
antibodies of the present invention include both monoclonal
antibodies and polyclonal antibodies, as well as antigen-reactive
proteolytic fragments of such antibodies, such as Fab,
F(ab)'.sub.2, and Fv fragments. In addition, an antibody of the
present invention further includes any of a variety of engineered
antigen-binding molecules such as a chimeric antibody (U.S. Pat.
Nos. 4,816,567 and 4,816,397; Morrison et al., Proc. Natl. Acad.
Sci. USA, 81:6851, 1984; Neuberger et al., Nature 312:604, 1984), a
humanized antibody (U.S. Pat. Nos. 5,693,762; 5,585,089; and
5,565,332), a single-chain Fv (U.S. Pat. No. 4,946,778; Ward et
al., Nature 334:544, 1989), a bispecific antibody with two binding
specificities (Segal et al., J. Immunol. Methods 248:1, 2001;
Carter, J. Immunol. Methods 248:7, 2001), a diabody, a triabody,
and a tetrabody (Todorovska et al., J. Immunol. Methods, 248:47,
2001), as well as a Fab conjugate (dimer or trimer), and a
minibody.
[0385] Many methods are known in the art for generating and/or
identifying antibodies to a given target antigen (Harlow,
Antibodies, Cold Spring Harbor Press, (-1989)). In general, an
isolated peptide (e.g., a variant protein of the present invention)
is used as an immunogen and is administered to a mammalian
organism, such as a rat, rabbit, hamster or mouse an Either a
full-length protein, an antigenic peptide fragment (e.g., a peptide
fragment containing a region that varies between a variant protein
and a corresponding wild-type protein), or a fusion protein can be
used. A protein used as an immunogen may be naturally-occurring,
synthetic or recombinantly produced, and may be administered in
combination with an adjuvant, including but not limited to,
Freund's (complete and incomplete), mineral gels such as aluminum
hydroxide, surface active substance such as lysolecithin, pluronic
polyols, polyanions; peptides, oil emulsions, keyhole limpet
hemocyanin, dinitrophenol, and the like.
[0386] Monoclonal antibodies can be produced by hybridoma
technology (Kohler and Milstein, Nature, 256:495, 1975), which
immortalizes cells secreting a specific monoclonal antibody. The
immortalized cell lines can be created in vitro by fusing two
different cell types, typically lymphocytes, and tumor cells. The
hybridoma cells may be cultivated in vitro or in vivo.
Additionally, fully human antibodies can be generated by transgenic
animals (He et al., J. Immunol., 169:595, 2002). Fd phage and Fd
phagemid technologies may be used to generate and select
recombinant antibodies in vitro (Hoogenboom and Chames, Immunol.
Today 21:371, 2000; Liu et al., J. Mol. Biol. 315:1063, 2002). The
complementarity-determining regions of an antibody can be
identified, and synthetic peptides corresponding to such regions
may be used to mediate antigen binding (U.S. Pat. No.
5,637,677).
[0387] Antibodies are preferably prepared against regions or
discrete fragments of a variant protein containing a variant amino
acid sequence as compared to the corresponding wild-type protein
(e.g., a region of a variant protein that includes an amino acid
encoded by a nonsynonymous cSNP, a region affected by truncation
caused by a nonsense SNP that creates a stop codon, or a region
resulting from the destruction of a stop codon due to read-through
mutation caused by a SNP). Furthermore, preferred regions will
include those involved in function/activity and/or protein/binding
partner interaction. Such fragments can be selected on a physical
property, such as fragments corresponding to regions that are
located on the surface of the protein, e.g., hydrophilic regions,
or can be selected based on sequence uniqueness, or based on the
position of the variant amino acid residue(s) encoded by the SNPs
provided by the present invention. An antigenic fragment will
typically comprise at least about 8-10 contiguous amino acid
residues in which at least one of the amino acid residues is an
amino acid affected by a SNP disclosed herein. The antigenic
peptide can comprise, however, at least 12, 14, 16, 20, 25, 50, 100
(or any other number in-between) or more amino acid residues,
provided that at least one amino acid is affected by a SNP
disclosed herein.
[0388] Detection of an antibody of the present invention can be
facilitated by coupling (i.e., physically linking) the antibody or
an antigen-reactive fragment thereof to a detectable substance.
Detectable substances include, but are not limited to, various
enzymes, prosthetic groups, fluorescent materials, luminescent
materials, bioluminescent materials, and radioactive materials.
Examples of suitable enzymes include horseradish peroxidase,
alkaline phosphatase, .beta.-galactosidase, or
acetylcholinesterase; examples of suitable prosthetic group
complexes include streptavidin/biotin and avidin/biotin; examples
of suitable fluorescent materials include umbelliferone,
fluorescein, fluorescein isothiocyanate, rhodamine,
dichlorotriazinylamine fluorescein, dansyl chloride or
phycoerythrin; an example of a luminescent material includes
luminol; examples of bioluminescent materials include luciferase,
luciferin, and aequorin, and examples of suitable radioactive
material include .sup.125I, .sup.131I, .sup.35S or .sup.3H.
[0389] Antibodies, particularly the use of antibodies as
therapeutic agents, are reviewed in: Morgan, "Antibody therapy for
Alzheimer's disease", Expert Rev Vaccines. 2003 February;
2(1):53-9; Ross et al., "Anticancer antibodies", Am J Clin Pathol.
2003 April; 119 (4):472-85; Goldenberg, "Advancing role of
radiolabeled antibodies in the therapy of cancer", Cancer Immunol
Immunother. 2003 May; 52(5):281-96. Epub 2003 Mar. 11; Ross et al.,
"Antibody-based therapeutics in oncology", Expert Rev Anticancer
Ther. 2003 February; 3(1): 107-21; Cao et al., "Bispecific antibody
conjugates in therapeutics", Adv Drug Deliv Rev. 2003 Feb. 10; 55
(2): 171-97; von Mehren et al., "Monoclonal antibody therapy for
cancer", Annu Rev Med. 2003; 54:343-69. Epub 2001 Dec. 3; Hudson et
al., "Engineered antibodies", Nat Med. 2003 January; 9(1): 129-34;
Brekke et al., "Therapeutic antibodies for human diseases at the
dawn of the twenty-first century", Nat Rev Drug Discov. 2003
January; 2(1):52-62 (Erratum in: Nat Rev Drug Discov. 2003 March;
2(3):240); Houdebine, "Antibody-manufacture in transgenic animals
and comparisons with other systems", Curr Opin Biotechnol. 2002
December; 13(6):625-9; Andreakos et al., "Monoclonal antibodies in
immune and inflammatory diseases", Curr Opin Biotechnol. 2002
December; 13(6):615-20; Kellermann et al., "Antibody discovery: the
use of transgenic mice to generate human monoclonal antibodies for
therapeutics", Curr Opin Biotechnol. 2002 December; 13(6):593-7;
Pini et al., "Phage display and colony filter screening for
high-throughput selection of antibody libraries", Comb Chem High
Throughput Screen. 2002 November; 5(7):503-10; Batra et al.,
"Pharmacokinetics and biodistribution of genetically engineered
antibodies", Curr Opin Biotechnol. 2002 December; 13(6):603-8; and
Tangri et al., "Rationally engineered proteins or antibodies with
absent or reduced immunogenicity", Curr Med. Chem. 2002 December;
9(24):2191-9.
[0390] Uses of Antibodies
[0391] Antibodies can be used to isolate the variant proteins of
the present invention from a natural cell source or from
recombinant host cells by standard techniques, such as affinity
chromatography or immunoprecipitation. In addition, antibodies are
useful for detecting the presence of a variant protein of the
present invention in cells or tissues to determine the pattern of
expression of the variant protein among various tissues in an
organism and over the course of normal development or disease
progression. Further, antibodies can be used to detect variant
protein in situ, in vitro, in a bodily fluid, or in a cell lysate
or supernatant in order to evaluate the amount and pattern of
expression. Also, antibodies can be used to assess abnormal tissue
distribution, abnormal expression during development, or expression
in an abnormal condition, such as in a cardiovascular disorder or
during statin treatment. Additionally, antibody detection of
circulating fragments of the full-length variant protein can be
used to identify turnover.
[0392] Antibodies to the variant proteins of the present invention
are also useful in pharmacogenomic analysis. Thus, antibodies
against variant proteins encoded by alternative SNP alleles can be
used to identify individuals that require modified treatment
modalities.
[0393] Further, antibodies can be used to assess expression of the
variant protein in disease states such as in active stages of the
disease or in an individual with a predisposition to a disease
related to the protein's function, such, as a cardiovascular
disorder, or during the course of a treatment regime, such as
during statin treatment. Antibodies specific for a variant protein
encoded by a SNP-containing nucleic acid molecule of the present
invention can be used to assay for the presence of the variant
protein, such as to predict an individual's response to statin
treatment or predisposition/susceptibility to an acute coronary
event, as indicated by the presence of the variant protein.
[0394] Antibodies are also useful as diagnostic tools for
evaluating the variant proteins in conjunction with analysis by
electrophoretic mobility, isoelectric point, tryptic peptide
digest, and other physical assays well known in the art.
[0395] Antibodies are also useful for tissue typing. Thus, where a
specific variant protein has been correlated with expression in a
specific tissue, antibodies that are specific for this protein can
be used to identify a tissue type.
[0396] Antibodies can also be used to assess aberrant subcellular
localization of a variant protein in cells in various tissues. The
diagnostic uses can be applied, not only in genetic testing, but
also in monitoring a treatment modality. Accordingly, where
treatment is ultimately aimed at correcting the expression level or
the presence of variant protein or aberrant tissue distribution or
developmental expression of a variant protein, antibodies directed
against the variant protein or relevant fragments can be used to
monitor therapeutic efficacy.
[0397] The antibodies are also useful for inhibiting variant
protein function, for example, by blocking the binding of a variant
protein to a binding partner. These uses can also be applied in a
therapeutic context in which treatment involves inhibiting a
variant protein's function. An antibody can be used, for example,
to block or competitively inhibit binding, thus modulating
(agonizing or antagonizing) the activity of a variant protein.
Antibodies can be prepared against specific variant protein
fragments containing sites required for function or against an
intact variant protein that is associated with a cell or cell
membrane. For in vivo administration, an antibody may be linked
with an additional therapeutic payload such as a radionuclide, an
enzyme, an immunogenic epitope, or a cytotoxic agent. Suitable
cytotoxic agents include, but are not limited to, bacterial toxin
such as diphtheria, and plant toxin such as ricin. The in vivo
half-life of an antibody or a fragment thereof may be lengthened by
pegylation through conjugation to polyethylene glycol (Leong et
al., Cytokine 16:106, 2001)
[0398] The invention also encompasses kits for using antibodies,
such as kits for detecting the presence of a variant protein in a
test sample. An exemplary kit can comprise antibodies such as a
labeled or labelable antibody and a compound or agent for detecting
variant proteins in a biological sample; means for determining the
amount, or presence/absence of variant protein in the sample; means
for comparing the amount of variant protein in the sample with a
standard; and instructions for use.
[0399] Vectors and Host Cells
[0400] The present invention also provides vectors containing the
SNP-containing nucleic acid molecules described herein. The term
"vector" refers to a vehicle, preferably a nucleic acid molecule,
which can transport a SNP-containing nucleic acid molecule. When
the vector is a nucleic acid molecule, the SNP-containing nucleic
acid molecule can be covalently linked to the vector nucleic acid.
Such vectors include, but are not limited to, a plasmid, single or
double stranded phage, a single or double stranded RNA or DNA viral
vector, or artificial chromosome, such as a BAC, PAC, YAC, or
MAC.
[0401] A vector can be maintained in a host cell as an
extrachromosomal element where it replicates and produces
additional copies of the SNP-containing nucleic acid molecules.
Alternatively, the vector may integrate into the host cell genome
and produce additional copies of the SNP-containing nucleic acid
molecules when the host cell replicates.
[0402] The invention provides vectors for the maintenance (cloning
vectors) or vectors for expression (expression vectors) of the
SNP-containing nucleic acid molecules. The vectors can function in
prokaryotic or eukaryotic cells or in both (shuttle vectors).
[0403] Expression vectors typically contain cis-acting regulatory
regions that are operably linked in the vector to the
SNP-containing nucleic acid molecules such that transcription of
the SNP-containing nucleic acid molecules is allowed in a host
cell. The SNP-containing nucleic acid molecules can also be
introduced into the host cell with a separate nucleic acid molecule
capable of affecting transcription. Thus, the second nucleic acid
molecule may provide a trans-acting factor interacting with the
cis-regulatory control region to allow transcription of the
SNP-containing nucleic acid molecules from the vector.
Alternatively, a trans-acting factor may be supplied by the host
cell. Finally, a trans-acting factor can be produced from the
vector itself. It is understood, however, that in some embodiments,
transcription and/or translation of the nucleic acid molecules can
occur in a cell-free system.
[0404] The regulatory sequences to which the SNP-containing nucleic
acid molecules described herein can be operably linked include
promoters for directing mRNA transcription. These include, but are
not limited to, the left promoter from bacteriophage .lambda., the
lac, TRP, and TAC promoters from E. coli, the early and late
promoters from SV40, the CMV immediate early promoter, the
adenovirus early and late promoters, and retrovirus long-terminal
repeats.
[0405] In addition to control regions that promote transcription,
expression vectors may also include regions that modulate
transcription, such as repressor binding sites and enhancers.
Examples include the SV40 enhancer, the cytomegalovirus immediate
early enhancer, polyoma enhancer, adenovirus enhancers, and
retrovirus LTR enhancers.
[0406] In addition to containing sites for transcription initiation
and control, expression vectors can also contain sequences
necessary for transcription termination and, in the transcribed
region, a ribosome-binding site for translation. Other regulatory
control elements for expression include initiation and termination
codons as well as polyadenylation signals. A person of ordinary
skill in the art would be aware of the numerous regulatory,
sequences that are useful in expression vectors (see, e.g.,
Sambrook and Russell, 2000, Molecular Cloning: A Laboratory Manual,
Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y.).
[0407] A variety of expression vectors can be used to express a
SNP-containing nucleic acid molecule. Such vectors include
chromosomal, episomal, and virus-derived vectors, for example,
vectors derived from bacterial plasmids, from bacteriophage, from
yeast episomes, from yeast chromosomal elements, including yeast
artificial chromosomes, from viruses such as baculoviruses,
papovaviruses such as SV40, Vaccinia viruses, adenoviruses,
poxviruses, pseudorabies viruses, and retroviruses. Vectors can
also be derived from combinations of these sources such as those
derived from plasmid and bacteriophage genetic elements, e.g.,
cosmids and phagemids. Appropriate cloning and expression vectors
for prokaryotic and eukaryotic hosts are described in Sambrook and
Russell, 2000, Molecular Cloning: A Laboratory Manual, Cold Spring
Harbor Laboratory Press, Cold Spring Harbor,
[0408] The regulatory sequence in a vector may provide constitutive
expression in one or more host cells (e.g., tissue specific
expression) or may provide for inducible expression in one or more
cell types such as by temperature, nutrient additive, or exogenous
factor, e.g., a hormone or other ligand. A variety of vectors that
provide constitutive or inducible expression of a nucleic acid
sequence in prokaryotic and eukaryotic host cells are well known to
those of ordinary skill in the art.
[0409] A SNP-containing nucleic acid molecule can be inserted into
the vector by methodology well-known in the art. Generally, the
SNP-containing nucleic acid molecule that will ultimately be
expressed is joined to an expression vector by cleaving the
SNP-containing nucleic acid molecule and the expression vector with
one or more restriction enzymes and then ligating the fragments
together. Procedures for restriction enzyme digestion and ligation
are well known to those of ordinary skill in the art.
[0410] The vector containing the appropriate nucleic acid molecule
can be introduced into an appropriate host cell for propagation or
expression using well-known techniques. Bacterial host cells
include, but are not limited to, E. coli, Streptomyces, and
Salmonella typhimurium. Eukaryotic host cells include, but are not
limited to, yeast, insect cells such as Drosophila, animal cells
such as COS and CHO cells, and plant cells.
[0411] As described herein, it may be desirable to express the
variant peptide as a fusion protein. Accordingly, the invention
provides fusion vectors that allow for the production of the
variant peptides. Fusion vectors can, for example, increase the
expression of a recombinant protein, increase the solubility of the
recombinant protein, and aid in the purification of the protein by
acting, for example, as a ligand for affinity purification. A
proteolytic cleavage site may be introduced at the junction of the
fusion moiety so that the desired variant peptide can ultimately be
separated from the fusion moiety. Proteolytic enzymes suitable for
such use include, but are not limited to, factor Xa, thrombin, and
enterokinase. Typical fusion expression vectors include pGEX (Smith
et al., Gene 67:3140 (1988)), pMAL (New England Biolabs, Beverly,
Mass.) and pRIT5 (Pharmacia, Piscataway, N.J.) which fuse
glutathione S-transferase (GST), maltose E binding protein, or
protein A, respectively, to the target recombinant protein.
Examples of suitable inducible non-fusion E. coli expression
vectors include pTrc (Amann et al., Gene 69:301-315 (1988)) and pET
11d (Studier et al., Gene Expression Technology: Methods in
Enzymology 185:60-89 (1990)).
[0412] Recombinant protein expression can be maximized in a
bacterial host by providing a genetic background wherein the host
cell has an impaired capacity to proteolytically cleave the
recombinant protein (Gottesman, S., Gene Expression Technology:
Methods in Enzymology 185, Academic Press, San Diego, Calif. (1990)
119-128). Alternatively, the sequence of the SNP-containing nucleic
acid molecule of interest can be altered to provide preferential
codon usage for a specific host cell, for example, E. coli (Wada et
al., Nucleic Acids Res. 20:2111-2118 (1992)).
[0413] The SNP-containing nucleic acid molecules can also be
expressed by expression vectors that are operative in yeast.
Examples of vectors for expression in yeast (e.g., S. cerevisiae)
include pYepSec1 (Baldari, et al., EMBO J. 6:229-234 (1987)), pMFa
(Kurjan et al., Cell 30:933-943(1982)), pJRY88 (Schultz et al.,
Gene 54:113-123 (1987)), and pYES2 (Invitrogen Corporation, San
Diego, Calif.).
[0414] The SNP-containing nucleic acid molecules can also be
expressed in insect cells using, for example, baculovirus
expression vectors. Baculovirus vectors available for expression of
proteins in cultured insect cells (e.g., Sf9 cells) include the pAc
series (Smith et al., Mol. Cell Biol. 3:2156-2165 (1983)) and the
pVL series (Lucklow et al., Virology 170:31-39 (1989)).
[0415] In certain embodiments of the invention, the SNP-containing
nucleic acid molecules described herein are expressed in mammalian
cells using mammalian expression vectors. Examples of mammalian
expression vectors include pCDM8 (Seed, B. Nature 329:840(1987))
and pMT2PC (Kaufman et al., EMBO J. 6:187-195 (1987)).
[0416] The invention also encompasses vectors in which the
SNP-containing nucleic acid molecules described herein are cloned
into the vector in reverse orientation, but operably linked to a
regulatory sequence that permits transcription of antisense RNA.
Thus, an antisense transcript can be produced to the SNP-containing
nucleic acid sequences described herein, including both coding and
non-coding regions. Expression of this antisense RNA is subject to
each of the parameters described above in relation to expression of
the sense RNA (regulatory sequences, constitutive or inducible
expression, tissue-specific expression).
[0417] The invention also relates to recombinant host cells
containing the vectors described herein. Host cells therefore
include, for example, prokaryotic cells, lower eukaryotic cells
such as yeast, other eukaryotic cells such as insect cells, and
higher eukaryotic cells such as mammalian cells.
[0418] The recombinant host cells can be prepared by introducing
the vector constructs described herein into the cells by techniques
readily available to persons of ordinary skill in the art. These
include, but are not limited to, calcium phosphate transfection,
DEAE-dextran-mediated transfection, cationic lipid-mediated
transfection, electroporation, transduction, infection,
lipofection, and other techniques such as those described in
Sambrook and Russell, 2000, Molecular Cloning: A Laboratory Manual,
Cold Spring Harbor Laboratory, Cold Spring Harbor Laboratory Press,
Cold Spring Harbor, N.Y.).
[0419] Host cells can contain more than one vector. Thus, different
SNP-containing nucleotide sequences can be introduced in different
vectors into the same cell. Similarly, the SNP-containing nucleic
acid molecules can be introduced either alone or with other nucleic
acid molecules that are not related to the SNP-containing nucleic
acid molecules, such as those providing trans-acting factors for
expression vectors. When more than one vector is introduced into a
cell, the vectors can be introduced independently, co-introduced,
or joined to the nucleic acid molecule vector.
[0420] In the case of bacteriophage and viral vectors, these can be
introduced into cells as packaged or encapsulated virus by standard
procedures for infection and transduction. Viral vectors can be
replication-competent or replication-defective. In the case in
which viral replication is defective, replication can occur in host
cells that provide functions that complement the defects.
[0421] Vectors generally include selectable markers that enable the
selection of the subpopulation of cells that contain the
recombinant vector constructs. The marker can be inserted in the
same vector that contains the SNP-containing nucleic acid molecules
described herein or may be in a separate vector. Markers include,
for example, tetracycline or ampicillin-resistance genes for
prokaryotic host cells and dihydrofolate reductase or neomycin
resistance genes for eukaryotic host cells. However, any marker
that provides selection for a phenotypic trait can be
effective.
[0422] While the mature variant proteins can be produced in
bacteria, yeast, mammalian cells, and other cells under the control
of the appropriate regulatory sequences, cell-free transcription
and translation systems can also be used to produce these variant
proteins using RNA derived from the DNA constructs described
herein.
[0423] Where secretion of the variant protein is desired, which is
difficult to achieve with multi-transmembrane domain containing
proteins such as G-protein-coupled receptors (GPCRs), appropriate
secretion signals can be incorporated into the vector. The signal
sequence can be endogenous to the peptides or heterologous to these
peptides.
[0424] Where the variant protein is not secreted into the medium,
the protein can be isolated from the host cell by standard
disruption procedures, including freeze/thaw, sonication,
mechanical disruption, use of lysing agents, and the like. The
variant protein can then be recovered and purified by well-known
purification methods including, for example, ammonium sulfate
precipitation, acid extraction, anion or cationic exchange
chromatography, phosphocellulose chromatography,
hydrophobic-interaction chromatography, affinity chromatography,
hydroxylapatite chromatography, lectin chromatography, or high
performance liquid chromatography.
[0425] It is also understood that, depending upon the host cell in
which recombinant production of the variant proteins described
herein occurs, they can have various glycosylation patterns, or may
be non-glycosylated, as when produced in bacteria. In addition, the
variant proteins may include an initial modified methionine in some
cases as a result of a host-mediated process.
[0426] For further information regarding vectors and host cells,
see Current Protocols in Molecular Biology, John Wiley & Sons,
N.Y.
[0427] Uses of Vectors and Host Cells, and Transgenic Animals
[0428] Recombinant host cells that express the variant proteins
described herein have a variety of uses. For example, the cells are
useful for producing a variant protein that can be further purified
into a preparation of desired amounts of the variant protein or
fragments thereof. Thus, host cells containing expression vectors
are useful for variant protein production.
[0429] Host cells are also useful for conducting cell-based assays
involving the variant protein or variant protein fragments, such as
those described above as well as other, formats known in the art.
Thus, a recombinant host cell expressing a variant protein is
useful for assaying compounds that stimulate or inhibit variant
protein function. Such an ability of a compound to modulate variant
protein function may not be apparent from assays of the compound on
the native/wild-type protein, or from cell-free assays of the
compound. Recombinant host cells are also useful for assaying
functional alterations in the variant proteins as compared with a
known function.
[0430] Genetically-engineered host cells can be further used to
produce non-human transgenic animals. A transgenic animal is
preferably a non-human mammal, for example, a rodent, such as a rat
or mouse, in which one or more of the cells of the animal include a
transgene. A transgene is exogenous DNA containing a SNP of the
present invention which is integrated into the genome of a cell
from which a transgenic animal develops and which remains in the
genome of the mature animal in one or more of its cell types or
tissues. Such animals are useful for studying the function of a
variant protein in vivo, and identifying and evaluating modulators
of variant protein activity. Other examples of transgenic animals
include, but are not limited to, non-human primates, sheep, dogs,
cows, goats, chickens, and amphibians. Transgenic non-human mammals
such as cows and goats can be used to produce variant proteins
which can be secreted in the animal's milk and then recovered.
[0431] A transgenic animal can be produced by introducing a
SNP-containing nucleic acid molecule into the male pronuclei of a
fertilized oocyte, e.g., by microinjection or retroviral infection,
and allowing the oocyte to develop in a pseudopregnant female
foster animal. Any nucleic acid molecules that contain one or more
SNPs of the present invention can potentially be introduced as a
transgene into the genome of a non-human animal.
[0432] Any of the regulatory or other sequences useful in
expression vectors can form part of the transgenic sequence. This
includes intronic sequences and polyadenylation signals, if not
already included. A tissue-specific regulatory sequence(s) can be
operably linked to the transgene to direct expression of the
variant protein in particular cells or tissues.
[0433] Methods for generating transgenic animals via embryo
manipulation and microinjection, particularly animals such as mice,
have become conventional in the art and are described in, for
example, U.S. Pat. Nos. 4,736,866 and 4,870,009, both by Leder et
al., U.S. Pat. No. 4,873,191 by Wagner et al., and in Hogan, B.,
Manipulating the Mouse Embryo, (Cold Spring Harbor Laboratory Press
Cold Spring Harbor, N.Y., 1986). Similar methods are used for
production of other transgenic animals. A transgenic founder animal
can be identified based upon the presence of the transgene in its
genome and/or expression of transgenic mRNA in tissues or cells of
the animals. A transgenic founder animal can then be used to breed
additional animals carrying the transgene. Moreover, transgenic
animals carrying a transgene can further be bred to other
transgenic animals carrying other transgenes. A transgenic animal
also includes a non-human animal in which the entire animal or
tissues in the animal have been produced using the homologously
recombinant host cells described herein.
[0434] In another embodiment, transgenic non-human animals can be
produced which contain selected systems that allow for regulated
expression of the transgene. One example of such a system is the
cre/loxP recombinase system of bacteriophage P1 (Lakso et al. PNAS
89:6232-6236 (1992)). Another example of a recombinase system is
the FLP recombinase system of S. cerevisiae (O'Gorman et al.
Science 251:1351-1355 (1991)). If a cre/loxP recombinase system is
used to regulate expression of the transgene, animals containing
transgenes encoding both the Cre recombinase and a selected protein
are generally needed. Such animals can be provided through the
construction of "double" transgenic animals, e.g., by mating two
transgenic animals, one containing a transgene encoding a selected
variant protein and the other containing a transgene encoding a
recombinase.
[0435] Clones of the non-human transgenic animals described herein
can also be produced according to the methods described in, for
example, Wilmut, I. et al. Nature 385:810-813 (1997) and PCT
International Publication Nos. WO 97/07668 and WO 97/07669. In
brief, a cell (e.g., a somatic cell) from the transgenic animal can
be isolated and induced to exit the growth cycle and enter Go
phase. The quiescent cell can then be fused, e.g., through the use
of electrical pulses, to an enucleated oocyte from an animal of the
same species from which the quiescent cell is isolated. The
reconstructed oocyte is then cultured such that it develops to
morula or blastocyst and then transferred to pseudopregnant female
foster animal. The offspring born of this female foster animal will
be a clone of the animal from which the cell (e.g., a somatic cell)
is isolated.
[0436] Transgenic animals containing recombinant cells, that
express the variant proteins described herein are useful for
conducting the assays described, herein in an in vivo context
Accordingly, the various physiological factors that are present in
vivo and that could influence ligand or substrate binding, variant
protein activation, signal transduction, or other processes or
interactions, may not be evident from in vitro cell-free or
cell-based assays. Thus, non-human transgenic animals of the
present invention may be used to assay in vivo variant protein
function as well as the activities of a therapeutic agent or
compound that modulates variant protein function/activity or
expression. Such animals are also suitable for assessing the
effects of null mutations (i.e., mutations that substantially or
completely eliminate one or more variant protein functions).
[0437] For further information regarding transgenic animals, see
Houdebine, "Antibody manufacture in transgenic animals and
comparisons with other systems", Curr Opin Biotechnol. 2002
December; 13(6):625-9; Petters et al., "Transgenic animals as
models for human disease", Transgenic Res. 2000; 9(4-5):347-51;
discussion 345-6; Wolf et al., "Use of transgenic animals in
understanding molecular mechanisms of toxicity", J Pharm Pharmacol.
1998 June; 50(6):567-74; Echelard, "Recombinant protein production
in transgenic animals", Curr Opin Biotechnol. 1996 October;
7(5):536-40; Houdebine, "Transgenic animal bioreactors", Transgenic
Res. 2000; 9(4-5):305-20; Pirity et al., "Embryonic stem cells,
creating transgenic animals", Methods Cell Biol. 1998; 57:279-93;
and Robl et al., "Artificial chromosome vectors and expression of
complex proteins in transgenic animals", Theriogenology. 2003 Jan.
1; 59(1):107-13.
[0438] Computer-Related Embodiments
[0439] The SNPs provided in the present invention may be "provided"
in a variety of mediums to facilitate use thereof. As used in this
section, "provided" refers to a manufacture, other than an isolated
nucleic acid molecule, that contains SNP information of the present
invention. Such a manufacture provides the SNP information in a
form that allows a skilled artisan to examine the manufacture using
means not directly applicable to examining the SNPs or a subset
thereof as they exist in nature or in purified form. The SNP
information that may be provided in such a form includes any of the
SNP information provided by the present invention such as, for
example, polymorphic nucleic acid and/or amino acid sequence
information such as SEQ ID NOS:1-517, SEQ ID NOS:518-1034, SEQ ID
NOS:13,194-13,514, SEQ ID NOS:1035-13,193, and SEQ ID
NOS:13,515-85,090; information about observed SNP alleles,
alternative codons, populations, allele frequencies, SNP types,
and/or affected proteins; or any other information-provided by the
present invention in Tables 1-2 and/or the Sequence Listing.
[0440] In one application of this embodiment, the SNPs of the
present invention can be recorded on a computer readable medium. As
used herein, "computer readable medium"refers to any medium that
can be read and accessed directly by a computer. Such media
include, but are not limited to: magnetic storage media, such as
floppy discs, hard disc storage medium, and magnetic tape; optical
storage media such as CD-ROM; electrical storage media such as RAM
and ROM; and hybrids of these categories such as magnetic/optical
storage media. A skilled artisan can readily appreciate how any of
the presently known computer readable media can be used to create a
manufacture comprising computer readable medium having recorded
thereon a nucleotide sequence of the present invention. One such
medium is provided with the present application, namely, the
present application contains computer readable medium (CD-R) that
has nucleic acid sequences (and encoded protein sequences)
containing SNPs provided/recorded thereon in ASCII text format in a
Sequence Listing along with accompanying Tables that contain
detailed SNP and sequence information (transcript sequences are
provided as SEQ ID NOS:1-517, protein sequences are provided as SEQ
ID NOS:518-1034, genomic sequences are provided as SEQ ID
NOS:13,194-13,514, transcript-based context sequences are provided
as SEQ ID NOS:1035-13,193, and genomic-based context sequences are
provided as SEQ ID NOS:13,515-85,090).
[0441] As used herein, "recorded" refers to a process for storing
information on computer readable medium. A skilled artisan can
readily adopt any of the presently known methods for recording
information on computer readable medium to generate manufactures
comprising the SNP information of the present invention.
[0442] A variety of data storage structures are available to a
skilled artisan for creating a computer readable medium having
recorded thereon a nucleotide or amino acid sequence of the present
invention. The choice of the data storage structure will generally
be based on the means chosen to access the stored information. In
addition, a variety of data processor programs and formats can be
used to store the nucleotide/amino acid sequence information of the
present invention computer readable medium. For example, the
sequence information can be represented in a word processing text
file, formatted in commercially-available software such as
WordPerfect and Microsoft Word, represented in the form of an ASCII
file, or stored in a database application, such as OB2, Sybase,
Oracle, or the like. A skilled artisan can readily adapt any number
of data processor structuring formats (e.g., text file or database)
in order to obtain computer readable medium having recorded thereon
the SNP-information of the present invention.
[0443] By providing the SNPs of the present invention in computer
readable form, a skilled artisan can routinely access the SNP
information for a variety of purposes. Computer software is
publicly available which allows a skilled artisan to access
sequence information provided in a computer readable medium.
Examples of publicly available computer software include BLAST
(Altschul et at, J. Mol. Biol. 215:403-410 (1990)) and BLAZE
(Brutlag et at, Comp. Chem. 17:203-207 (1993)) search
algorithms.
[0444] The present invention further provides systems, particularly
computer-based systems, which contain the SNP information described
herein. Such systems may be designed to store and/or analyze
information on, for example, a large number of SNP positions, or
information on SNP genotypes from a large number of individuals.
The SNP information of the present invention represents a valuable
information source. The SNP information of the present invention
stored/analyzed in a computer-based system may be used for such
computer-intensive applications as determining or analyzing SNP
allele frequencies in a population, mapping disease genes,
genotype-phenotype association studies, grouping SNPs into
haplotypes, correlating SNP haplotypes with response to particular
drugs, or for various other bioinformatic, pharmacogenomic, drug
development, or human identification/forensic applications.
[0445] As used herein, "a computer-based system" refers to the
hardware means, software means, and data storage means used to
analyze the SNP information of the present invention. The minimum
hardware means of the computer-based systems of the present
invention typically comprises a central processing-unit (CPU),
input means, output means, and data storage means. A skilled
artisan can readily appreciate that any one of the currently
available computer-based-systems are suitable for use in the
present invention. Such a system can be changed into a system of
the present invention bye, utilizing the SNP information provided
on the CD-R, or a subset thereof, without any experimentation.
[0446] As stated above, the computer-based systems of the present
invention comprise a data storage means having stored therein SNPs
of the present invention and the necessary hardware means and
software means for supporting and implementing a search means.
[0447] As used herein, "data storage means" refers to memory which
can store SNP information of the present invention, or a memory
access means which can access manufactures a having recorded
thereon the SNP information of the present invention.
[0448] As used herein, "search means" refers to one or more
programs or algorithms that are implemented on the computer-based
system to identify or analyze SNPs in a target sequence based on
the SNP information stored within the data storage means. Search
means can be used to determine which nucleotide is present at a
particular SNP position in the target sequence. As used herein, a
"target sequence" can be any DNA sequence containing the SNP
position(s) to be searched or queried.
[0449] As used herein, "a target structural motif," or "target
motif," refers to any rationally selected sequence or combination
of sequences containing a SNP position in which the sequence(s) is
chosen based on a three-dimensional configuration that is formed
upon the folding of the target motif. There are a variety of target
motifs known in the art. Protein target motifs include, but are not
limited to, enzymatic active sites and signal sequences. Nucleic
acid target motifs include, but are not limited to, promoter
sequences, hairpin structures, and inducible expression elements
(protein binding sequences).
[0450] A variety of structural formats for the input and output
means can be used to input and output the information in the
computer-based systems of the present invention. An exemplary
format for an output means is a display that depicts the presence
or absence of specified nucleotides (alleles) at particular SNP
positions of interest. Such presentation can provide a rapid,
binary scoring system for many SNPs simultaneously.
[0451] One exemplary embodiment of a computer-based system
comprising SNP information of the present invention is provided in
FIG. 1. FIG. 1 provides a block diagram of a computer system 102
that can be used to implement the present invention. The computer
system 102 includes a processor 106 connected to a bus 104. Also
connected to the bus 104 are a main memory 108 (preferably
implemented as random access memory, RAM) and a variety of
secondary storage devices 110, such as a hard drive 112 and a
removable medium storage device 114. The removable medium storage
device 114 may represent, for example, a floppy disk drive, a
CD-ROM drive, a magnetic tape drive, etc. A removable storage
medium 116 (such as a floppy disk, a compact disk, a magnetic tape,
etc.) containing control logic and/or data recorded therein may be
inserted into the removable medium storage device 114. The computer
system 102 includes appropriate software for reading the control
logic and/or the data from the removable storage medium 116 once
inserted in the removable medium storage device 114.
[0452] The SNP information of the present invention may be stored
in a well-known manner in the main memory 108, any of the secondary
storage devices 110, and/or a removable storage medium 116.
Software for accessing and processing the SNP information (such as
SNP scoring tools, search tools, comparing tools, etc.) preferably
resides in main memory 108 during execution.
EXAMPLES
[0453] The following examples are offered to illustrate, but not to
limit the claimed invention.
Example 1
Statistical Analysis of SNP Allele Association with Cardiovascular
Disorders and Statin Response
[0454] Study Design
[0455] In order to identify genetic markers associated with acute
coronary events (e.g. MI, stroke, unstable angina, congestive heart
failure, etc.) or response to statin treatment for the prevention
of coronary events, samples from the Cholesterol and Recurrent
Events (CARE) study (a randomized multicentral double-blinded trial
on secondary prevention of acute coronary events with pravastatin)
(Sacks et al., 1991, Am. J. Cardiol. 68: 1436-1446) were genotyped.
A well-documented myocardial infarction (MI) was one of the
enrollment criteria for for entry into the CARE study. Patients
were enrolled in the CARE trial from 80 participating study
centers. Men and post-menopausal women were eligible for the trial
if they had had an acute MI between 3 and 20 months prior to
randomization, were 21 to 75 years of age, and had plasma total
cholesterol levels of less than 240 mg/deciliter, LDL cholesterol
levels of 115 to 174 mgs/deciliter, fasting triglyceride levels of
less than 350 mgs/deciliter, fasting glucose levels of no more than
220 mgs/deciliter, left ventricular ejection fractions of no less
than 25%, and no symptomatic congestive heart failure. Patients
were randomized to receive either 40 mg of pravastatin once daily
or a matching placebo. The primary endpoint of the trial was death
from coronary heart disease and the median duration of follow-up
was 5.0 years (range, 4.0 to 6.2 years). Patients enrolled in the
CARE study who received placebo had a 5 year risk of having a
recurrent MI (RMI) of 9.5% while those patients enrolled in the
study that received pravastatin had a 5 year risk of having a RMI
of only 7.2% (p.sub.LogRank=0.0234) (25% reduction in risk for RMI
in treatment vs. placebo groups, Cox Proportional Hazard Ratio
[HR.sub.age-adjusted]=0.75 [95% CI: 0.58-0.97, p=0.0256]).
Secondary endpoints of other related cardiovascular or metabolic
disease events, and changes in clinical variables were also
recorded in pravastatin-treated and placebo groups. Examples of
secondary endpoints are listed in Tables 6-8. All individuals
included in the study had signed a written informed consent form
and the study protocol was approved by the respective Institutional
Review Boards (IRBs).
[0456] For genotyping SNPs in CARE patient samples, DNA was
extracted from blood samples using conventional DNA extraction
methods such as the QIA-amp kit from Qiagen. Allele specific
primers were designed for detecting each SNP and they are shown in
Table 5. Genotypes were obtained on an ABI PRISM.RTM. 7900HT
Sequence Detection PCR system (Applied Biosystems, Foster City,
Calif.) by kinetic allele-specific PCR, similar to the method
described by Germer et al. (Germer S., Holland M. J., Higuchi R.
2000, Genome Res. 10: 258-266).
[0457] In the first analysis of samples obtained from patients
enrolled in the CARE study, SNP genotype frequencies in a group of
264 patients who had a second MI during the 5 years of CARE
follow-up (cases) were compared with the frequencies in the group
of 1255.CARE patients who had not experienced second MI (controls).
Logistic regression was used to adjust for the major epidemiologic
risk factors with the specific, emphasis on the interaction between
the risk factors and tested SNPs to identify SNPs significantly
associated with RMI when patients were stratified by sex, family
history, smoking status, body mass index (BMI), ApoE status or
hypertension.
[0458] To replicate initial findings, a second group of 394 CARE
patients were analyzed who had a history of an MI prior to the MI
at CARE enrollment (i.e., patients who had experienced a RMI at
enrollment) but who had not experienced an MI during trial follow
up (cases), and 1221 of CARE MI patients without second MI were
used as controls. No patients from first analysis (cases or
controls) were used in this second analysis (cases or controls).
There are significant clinical differences between the two analyses
e.g., in the first analysis, all MI patients were in a carefully
monitored clinical environment prior to their second MI, which
could modulate effect of genetic polymorphisms, whereas in the
second analysis, only a small portion of patients were treated by
lipid lowering drugs prior to second MI. Despite these differences,
numerous markers associated with RMI in the first analysis were
also found to be associated with RMI in the second analysis (see
Table 9).
[0459] Additionally, genetic markers identified as associated with
acute coronary events or response to statin treatment for the
prevention of coronary events in the CARE samples were also
genotyped in a second sample set, the West of Scotland Coronary
Prevention Study (WOSCOPS) sample set. The design of the original
WOSCOPS cohort and the nested case-control study have been
described (Shepherd et. al, N. Eng. J. Med., Nov. 16: 333 (20), pp.
1301-7 1995; Packard et. al. N. Eng. J. Med., Oct. 19: 343 (16),
pp. 1148-55, 2000). The objective of the WOSCOPS trial was to
assess pravastatin efficacy at reducing risk of primary MI or
coronary death among Scottish men with hypercholesterolemia
(fasting LDL cholesterol >155 mg/dl). Participants in the
WOSCOPS study were 45-64 years of age and followed for an average
of 4.9 years for coronary events. The nested case-control study
included as cases all WOSCOPS patients who experienced a coronary
event (confirmed nonfatal MI, death from coronary heart, disease,
or a revascularization procedure; N=580). Controls were 1160 age
and smoking status-matched unaffected patients. All individuals
included in the study had signed a written informed consent form
and the study protocol was approved by IRBs. DNA was extracted and
genotyped as described above.
[0460] Statistical Analysis for Association of SNPs with Specific
Clinical Endpoints
[0461] Qualitative phenotypes of the patients who were genotyped
(Table 6) were analyzed using an overall logistic regression model
that included an intercept, a parameter for the effect of a
genotype containing two rare alleles versus a genotype containing
no rare alleles, and a parameter for the effect of a genotype
containing one rare allele versus a genotype containing no rare
alleles. The test of the overall model is a chi-square test with
five degrees of freedom for analyses containing all three
genotypes, and four degrees of freedom for analyses containing two
genotypes. An example of a SNP associated with increased risk for
RMI is hCV529710 (Table 6). hCV529710 is strongly associated with
Fatal CHD (Coronary Heart Disease)/Non-fatal MI and Fatal
Atherosclerotic Cardiovascular Disease (Relative Risk=1.5 and 2.3,
and p-values <0.05 and <0.005, respectively.
[0462] Quantitative phenotypes of the patients who were genotyped
(Table 7) were also analyzed using an overall generalized linear
model (GLM) that included an intercept, a parameter for the effect
of a genotype containing two rare alleles, and a parameter for the
effect of a genotype containing one rare allele. The test of the
overall GLM model is an F-test.
[0463] Effect sizes for association of SNPs with endpoints were
estimated through odds ratios in placebo treated patients only,
separately for carriers of each genotype (groups of 0, 1, and 2
minor allele carriers). The effect was considered to be significant
if the p-value for testing whether any of the SNP genotype
parameters in overall model was <0.05. An example of a SNP
associated with increased risk for a quantitative phenotype such as
very low density lipoproteins (VLDL) is hCV22274624 with a p value
<0.0005.
[0464] Statistical analysis for association of SNPs with
pravastatin treatment in cardiovascular events prevention (Table 8)
was carried out using an overall logistic regression model that
included an intercept; a parameter for the effect of a genotype
containing two rare alleles versus a genotype containing no rare
alleles, a parameter for the effect of a genotype containing one
rare allele versus a genotype containing no rare alleles, a
parameter for the effect of use of pravastatin versus the use of
placebo, and parameters for the interaction effects between SNP
genotypes and pravastatin use. The test of the overall model is a
chi-square test with two degrees of freedom for analyses containing
all three genotypes, and one degree of freedom for analyses
containing two genotypes.
[0465] Effect sizes were estimated through odds ratios (pravastatin
group versus placebo) for carriers of each genotype (groups of 0,
1, and 2 minor allele carriers). The effect was considered to be
significant if p-value for testing whether any of the interactions
between SNP genotypes and pravastatin use were <0.05. An example
of a SNP associated with a response to statin treatment in
preventing an adverse coronary event is hCV2741051. When the
pravastatin group is compared to the control group, individuals
with one or two of the rare alleles had odds ratios of 0.43 and
0.26 respectively with a p-value of <0.05. This particular SNP
is also associated with a reduced risk of stroke in the pravastatin
treated group when one or two rare alleles are present in a patient
(odds rations of 0.21 and 0.23 p<0.05). Odds ratios less than
one indicate that the specific SNP allele has a protective effect
and odds ratios greater than one indicate that the specific SNP
allele has an adverse effect.
[0466] Statistical analysis for the association of SNPs with RMI or
stroke (Table 9) was also carried out using stepwise logistic
regression. Relative risk (RR) and 95% confidence intervals
(CI)s--5-6 years relative risk of a RMI event or stroke given the
SNP genotype were calculated by the Wald test. Certain SNPs show
association of SNPs with adverse coronary events such as RMI and
stroke in CARE samples. This association of certain SNPs with
adverse coronary events could also be replicated by comparing
associations observed in the first analysis of the CARE samples and
the second analysis of the CARE samples (see above). An example of
SNPs associated with increased risk for RMI are hCV517658 and hCV
8722981 with RR of 1.34 and 2.01 respectively. RR values <1 are
associated with a reduced risk of the indicated outcome and RR
values >1 are associated with an increased risk of the indicated
outcome. An example of a SNP associated with decreased risk for RMI
that replicated between the first and second analysis of the CARE
data is hCV761961 that had ORs of 0.5 and 0.5 in the first and
second analyses respectively. An example of a SNP associated with
increased risk for RMI that replicated in the first and second
analyses is hCV8851080 that had ORs of 2.7 and 1.9 in the first and
second analyses respectively. An example of a SNP associated with
increased risk for stroke that replicated in the first and second
analyses of the CARE data is hCV11482766 that had ORs of 3.5 and
3.3 in the first and second analyses respectively.
[0467] For statistical analysis of association of SNPs with
pravastatin treatment in RMI prevention (Table 10), effect sizes
were estimated through genotypic RR, including 95% CIs. Homogeneity
of Cochran-Mantel-Haenszel odds ratios was tested across
pravastatin and placebo strata using the Wald test. A SNP was
considered to have a significant association with response to
pravastatin treatment if it exhibited Wald p-value <0.05 in the
allelic association test or in any of the 3 genotypic tests
(dominant, recessive, additive). Table 10 shows association of SNPs
predictive of statin response with cardiovascular events prevention
under statin treatment, with an adjustment for conventional risk
factors such as age, sex, smoking status, baseline glucose levels,
BMI, history of hypertension, etc. (this adjustment supports
independence of the SNP association from conventional risk
factors). This table also provides the frequency data for the at
risk allele in the columns labeled "Case Y PRIMER ALLELE Nucleotide
Frequency" and "Control Y PRIMER ALLELE Nucleotide Frequency".
Allele frequencies for the cases and controls .ltoreq.0.49 indicate
that the at-risk allele is the minor allele. Allele frequencies
.gtoreq.0.50 indicate that the at-risk allele is the major allele.
An example of a SNP associated with increased risk for an adverse
cardiovascular event in the placebo group using a dominant
genotypic test is hCV25644901. The dominant genotype (GG or GA) had
a RR of 1.92 of being associated with an adverse cardiovascular
event in the placebo group. However, this same SNP was protective
in the statin treated group with a RR of 0.58. An example of a SNP
associated with an adverse cardiovascular event in the placebo
group using the allelic association test is hCV16044337 with a RR
of 1.87 for the homozygous AA genotype. This same genotype was
protective in the statin treated group with a RR of 0.56.
[0468] The statistical results provided in Table 11 demonstrate
association of a SNP in the CD6 gene (hCV2553030) that is
predictive of statin response in the prevention of RMI, justified
as a significant difference in risk associated with the SNP between
placebo and statin treated strata (Breslow Day p-values <0.05).
Table 11 presents the results observed in samples taken from both
the CARE and WOSCOP studies. In both studies the individuals
homozygous for the minor allele were statistically different from
heterozygous and major allele homozygous individuals in the
pravastatin treated group vs. the placebo treated group. This SNP
was associated with a reduced risk of an adverse coronary event in
the CARE and WOSCOPS studies with RR or OR of 0.13 and 0.23
respectively in the two studies. Therefore, SNPs identified as
useful for predicting RMI may also be useful for predicting
increased risk for developing primary MI.
[0469] Table 12 shows the association of a SNP in the FCAR gene
(hCV7841642) that is predictive of MI risk and response to statin
treatment. Individuals who participated in both the CARE and
WOSCOPS studies, who did not receive pravastatin treatment and who
were heterozygous or homozygous for the major allele (AG or GG) (OR
of 1.58, 1.52, 1.5, 1.47 in the respective studies) had a
significantly higher risk of having an MI vs. individuals who were
homozygous for the minor allele. However, individuals in the CARE
study who were heterozygous or homozygous for the FCAR major allele
were also statistically significantly protected by pravastatin
treatment against an adverse coronary event relative to the
individuals homozygous for the minor allele (OR 0.31, 0.79).
Therefore, an allele found to be associated with risk for MI, RMI,
stroke, or other adverse cardiovascular event, may also be useful
for predicting responsiveness to statin treatment. SNPs associated
with treatment response to pravastatin may also be predictive of
responsiveness of an individual to other statins as a class.
[0470] The data presented in Table 8 based on an association of
genotypes with pravastatin efficacy of the CARE samples were
further analyzed and presented in Table 13. The further analysis
was performed to align the data obtained from the analysis of the
CARE samples, which was a prospective study, to the analysis of the
WOSCOP samples, which was a case/control study. Table 13 also
presents an analysis of the association of genotypes with
pravastatin efficacy in the WOSCOPs samples. Relative to the
analysis performed on the data presented in Table 8, there are two
significant differences to determine if the SNP influenced
pravastatin efficacy. Data obtained from the CARE samples were
separated by study design into two groups, those in the prospective
study design group and those in the case/control study design
group. The original care study contained 16 protocol defined
cardiovascular, disease defined endpoints and 150 other phenotypes.
The prospective study design presented in Table 13 only looks at
two possible end points, those individuals who had a fatal MI,
sudden death, or a definite non-fatal MI, or those individuals who
had a fatal or non-fatal MI (probable or definite). In the
case/control study design, in addition to only looking at cases
that fell into the two possible endpoints defined above, cases were
only compared to matched controls, ie. controls matched by age,
smoking status and did not have any adverse coronary events or died
due to other causes. The control groups used to compare the data
were also divided into two groups, the "all possible" control group
and the "cleaner" control group. The all possible control group
consists of all of the controls that were white males and were
matched for age and smoking status but had any disease outcome. The
cleaner control group were also matched for age and smoking status
but were further restricted to only those individuals that had MI
as an outcome. Because the participants in the WOSCOPs trial were
all white males, only data obtained from white males in the CARE
study were analysed. Data from the "all possible" and "cleaner"
controls were compared to data obtained from the cases in the
prospective study design while only data from "cleaner" controls
were compared to cases in the case/control study design. The data
from the case/control cohorts were analysed using conditional
logistic regression (as opposed to logistic regression used for the
original anaylsis).
[0471] An example of a SNP associated with fatal MI/sudden
death/non-fatal MI using data from the CARE study is hCV2442143.
Patients with 0 rare alleles (or patients homozygous for the
dominant allele) had an OR of 0.42 of being associated with the
adverse outcome in the presence of statin treatment. Patients with
one or two rare alleles had ORs of 0.78 and 1.16 respectively of
being associated with the adverse outcome. However the 95% CI for
these two genotypes makes the result not statistically
significant.
[0472] The data presented in Table 6 based on an association of
genotypes with adverse cardiovascular outcomes such as fatal or
non-fatal MI were further analyzed and presented in Table 14.
Similar to the data presented in Table 13, the analysis was
modified to align the data obtained from the CARE samples to data
obtained from the a WOSCOPs samples in addition, Table 14 also
presents an analysis of the association of genotypes with adverse
cardiovascular outcomes observed in the WOSCOPs samples. As above,
there are two significant differences. Data obtained from the CARE
samples were separated by study design into a prospective or a
case/control study design group as defined above. Secondly, as
above the control groups were divided into the all possible
controls and the cleaner controls. Controls were age matched for
age and smoking status with the cases. The all possible controls
include individuals as defined above and the cleaner controls also
use individuals as defined above. As above, only data obtained from
samples from white males were analysed and are presented in Table
14.
[0473] An example of a SNP associated with an adverse
cardiovascular event such as a fatal MI or non-fatal MI using data
from the CARE study is hCV529706. Patients with 2 rare alleles vs.
0 rare alleles had an OR of 2.08 of having the adverse event (p,
0.05).
[0474] The statistical results provided in Table 15 demonstrate the
association of a SNP in the PONI gene (hCV2548962) with pravastatin
efficacy in both the CARE and WOSCOPs sample sets. The anaylsis was
refined as described for both Tables 13 and 14. The data show that
patients with 2 rare alleles were significantly protected against a
fatal or non-fatal MI when treated with pravastatin (ORs 0.28-0.34,
p<0.05).
Example 2
Statistical Analysis of SNP Combinations Associated with RMI and
Response to Statin Treatment
[0475] Multiple markers were identified in the CARE study as
associated with the ability of a patient to respond to statin
treatment by having a reduced risk of RMI (specifically see Tables
8 and 10). The data presented in those Tables, especially Table 10
indicate major alleles of NPC1 (hCV25472673) and HSPG2 (hCV1603656)
and the major allele of ABCA1 (hCV2741051) are protective against
RMI in patients that receive statin treatment. The data also show
that certain genotypes of the alleles identified in Table 10 are
protective against RMI in patients that receive statin treatment.
The homozygous minor allele or the heterozygous minor and major
allele of the NPC1 gene (CC, CT) and the HSPG2 gene (TT, TC) are
protective genotypes (low risk genotypes) against RMI in patients
that receive statin treatment. The homozygous major allele of the
ABCA1 gene (CC) is a protective genotype (low risk genotype) in
patients that receive statin treatment.
[0476] The genotype data generated from the DNA of patients who
participated in the CARE study was analyzed to determine the effect
that pravastatin treatment had on the occurrence of RMI in patients
with each of the potential genotypes (low risk, protective or high
risk, non-protective) for the ABCA1 gene, the NPC1 gene and the
HSPG1 gene independently. The data are presented in Table 16.
8 TABLE 16 Age-Adjusted pravastatin effect (by genotype group) N
Label RR 95% CI p-value 1366 High risk ABCA1 0.9567 0.6709 1.3644
0.807 genotype 1441 Low risk ABCA1 0.5883 0.4249 0.8145 0.0014
Total = 2807 genotype 1045 High risk NPC1 1.0824 0.7265 1.6127
0.6971 genotype 1755 Low risk NPC1 0.5938 0.4388 0.8035 0.0007
genotype Total = 2800 2375 High risk HSPG2 0.8097 0.6271 1.0453
0.1053 genotype 428 Low risk HSPG2 0.3934 0.2002 0.7729 0.0068
genotype Total = 2803
[0477] The data show that the low risk genotypes of the ABCA1 gene,
the NPC1 gene and the HSPG2 gene are protective against RMI in
patients that have received statin treatment.
[0478] The effect of pravastatin treatment on the occurrence of RMI
in patients with each of the potential genotypes (protective, low
risk genotype or non-protective, high risk genotype) for each of
the ABCA1 gene, NPC1 gene, and HSPG2 gene alone, and combinations
with the other two genes thereof are presented in Table 17.
9 TABLE 17 Age-adjusted pravastatin effect (by genotype group) N
Label RR 95% CI p-value 436 High risk, non-protective genotypes
1.7175 0.877 3.3637 0.1148 447 Low risk, protective ABCA1 only
0.8765 0.4848 1.5848 0.6627 701 Low risk, protective NPC1 only
0.8954 0.5543 1.4462 0.6514 83 Low risk, protective HSPG2 only
0.2487 0.0304 2.0372 0.1947 784 Low risk ABCA1 and NPC1 only 0.5258
0.3343 0.8271 0.0054 (pattern 2 genotype) 77 Low risk ABCA1 and
HSPG2 only 1.0054 0.2593 3.8982 0.9938 144 Low risk NPC1 and HSPG2
only 0.2964 0.0652 1.3482 0.1156 122 Low risk ABCA1, NPC1 and HSPG2
0.2399 0.0704 0.8177 0.0225 (pattern 3 genotype) Total = 2794
[0479] The data show that patients that have a combination of the
ABCA1 and NPC1 low risk genotypes (pattern 2) or patients that have
a combination of the ABCA1, NPC1 and the HSPG2 low risk genotypes
(pattern 3) have a significantly reduced risk of RMI if they
receive pravastatin treatment relative to those patients who
received placebo.
[0480] Patients in the CARE trial that had a high risk,
non-protective genotype for the ABCA1 gene, the NPC1 gene and the
HSPG2 gene, had the low risk ABCA1 genotype only, had the low risk
ABCA1 and HSPG2 genotypes only, had the low risk NPC1 genotype
only, had the low risk HSPG2 genotype only, or had the low risk
NPC1 and HSPG1 genotype are collectively called pattern 0 patients.
Patients in the CARE trial that had the pattern 0 genotype and
received placebo, had a 5 year risk of a RMI of 8.1%. Patients in
the trial that had the pattern 2 genotype and received placebo had
a 5 year risk of a RMI of 12.5%, or a 64% increase over those
patients that had the pattern 0 genotypes. Patients in the trial
that had the pattern 3 genotype and received placebo had a 5 year
risk of a RMI of 19.3% or a 138% increase over those patients that
had the pattern 0 genotypes. These data show that patients that do
not receive statin treatment and have the pattern 2 or the pattern
3 genotypes have a 64% or a 138% increased risk of a RMI in a 5
year period over patients with a pattern 0 genotype (LogRank
p-value=0.0013).
[0481] Patients in the CARE trial with pattern 0 genotypes who did
not receive statin treatment had a 5 year risk of a RMI of 8.1%.
Patients in the CARE trial with pattern 0 genotypes who did receive
pravastatin treatment had a 5 year risk of a RMI of 7.9% (N=1888,
67.6% of the CARE population, LogRank p-value=0.9345). Patients in
the trial with pattern 2 genotypes, who did not receive statin
treatment had a 5 year risk of a RMI of 12.5%. Patients in the
trial with pattern 2 genotypes who did receive pravastatin
treatment had a 5 year risk of a RMI of 6.8% (HR=0.53, 95% CI:
0.33-0.85, p=0.0081, N=784, 28.1% of the CARE population). This is
a 50% reduction in risk over a 5 year period for RMI. Patients in
the trial with pattern the 3 genotype, who did not receive statin
treatment had a 5 year risk of a RMI of 19.3%. Patients in the
trial with the pattern 3 genotype who did receive pravastatin had a
5 year risk of a RMI of 4.6% (HR=0.2, 95% CI=0.06-0.8, p=0209,
N=122, 4.4% of the CARE population). This is an 80% reduction in
risk over a 5 year period for RMI. These data are summarized in
Table 18.
10 TABLE 18 RMI No RMI Risk RR.sub.Statin RD.sub.Statin All
Pravastatin 106 1367 0.072 0.76 0.023 Placebo 137 1303 0.095
Pattern 0 Pravastatin 78 906 0.079 0.98 0.001 Placebo 73 831 0.081
Pattern 2 Pravastatin 25 342 0.068 0.55 0.057 Placebo 52 365 0.125
Pattern 3 Pravastatin 3 62 0.046 0.24 0.147 Placebo 11 46 0.193
[0482] Measures of prognostic value were calculated from the above
data. The positive predictive value (PPV) of each genotype pattern
can be calculated by dividing the number of individuals with that
genotype who received placebo and had a RMI by the total number of
individuals who had that genotype and received placebo. The PPV of
the pattern 3 genotype is 19.3% and the PPV of the pattern 2
genotype is 12.5%. The negative predictive value (NPV) of each
genotype can be calculated by dividing the total number of
individuals who had those genotypes, received placebo and did not
have a RMI by the total number of individuals who had that genotype
and received placebo. The NPV of pattern 0 is 91.9%. From these
calculations, the entire population can be broken down into
different absolute risk groups. The over all risk of the population
to have a RMI after having an MI is 9.5%. However, for individuals
with the pattern 0 genotype, the risk of a RMI is reduced to 8.1%.
Individuals with pattern 2 and pattern 3 genotypes have a 12.5% and
19.3% risk of a RMI.
[0483] All publications and patents cited in this specification are
herein incorporated by reference in their entirety. Various
modifications and variations of the described compositions, methods
and systems of the invention will be apparent to those skilled in
the art without departing from the scope and spirit of the
invention. Although the invention has been described in connection
with specific preferred embodiments and certain working examples,
it should be understood that the invention as claimed should not be
unduly limited to such specific embodiments. Indeed, various
modifications of the above-described modes for carrying out the
invention that are obvious to those skilled in the field of
molecular biology, genetics and related fields are intended to be
within the scope of the following claims.
11TABLE 5 Marker Alleles Sequence A (allele-specific primer)
Sequence B (allele-specfic primer) hCV1085600 C/G
AGCTGTTCGTGTTCTATGATC AGCTGTTCGTGTTCTATGATG (SEQ ID NO:85091) (SEQ
ID NO:85092) hCV1088055 A/G CACTCACACTGGGGAAGA ACTCACACTGGGGAAGG
(SEQ ID NO:85094) (SEQ ID NO:85095) hCV11225994 A/G
TCCCAATCCCAGGACA CCCAATCCCAGGACG (SEQ ID NO:85097) (SEQ ID
NO:85098) hCV11359098 C/G CAAAATGTAGAAGGTTCATATGAG
CAAAATGTAGAAGGTTCATATGAC (SEQ ID NO:85100) (SEQ ID NO:85101)
hCV11482766 C/T GCGCACCCAGGTCAG GCGCACCCAGGTCAA (SEQ ID NO:85103)
(SEQ ID NO:85104) hCV11571465 C/G GCTGGAGTTCATGTCGC
GCTGGAGTTCATGTCGG (SEQ ID NO:85106) (SEQ ID NO:85107) hCV11696920
A/G GTCTTTAGAAGCCTCTTCAGAATA CTTTAGAAGCCTCTTCAGAATG (SEQ ID
NO:85109) (SEQ ID NO:85110) hCV1180648 G/A GGGTAAAATTCAGTAAGGTTGG
AGGGTAAAATTCAGTAAGGTTGA (SEQ ID NO:85112) (SEQ ID NO:85113)
hCV11852251 C/G GGCTGTTGTCTCACCCTC GGCTGTTGTCTCACCCTG (SEQ ID
NO:85115) (SEQ ID NO:85116) hCV11889257 A/G
CTCTCTTTCTAGAAACTGAAGAAATT TCTCTTTCTAGAAACTGAAGAAA- TC (SEQ ID
NO:85118) (SEQ ID NO:85119) hCV11942529 C/T ACTGTCACCTGTTGGGG
GACTGTCACCTGTTGGGA (SEQ ID NO:85121) (SEQ ID NO:85122) hCV11951095
T/C CGTGACCCTGCCGT CGTGACCCTGCCGC (SEQ ID NO:85124) (SEQ ID
NO:85125) hCV11975296 T/C CAGTCCATGGTTCCTTCAT CAGTCCATGGTTCCTTCAC
(SEQ ID NO:85127) (SEQ ID NO:85128) hCV12020339 G/T GGACCCCCGAAGGC
TGGACCCCCGAAGGA (SEQ ID NO:85130) (SEQ ID NO:85131) hCV1202883 A/G
GCGTGATGATGAAATCGA GCGTGATGATGAAATCGG (SEQ ID NO:85133) (SEQ ID
NO:85134) hCV1207994 A/C GCAGCAGTCGCCCTT GCAGCAGTCGCCCTG (SEQ ID
NO:85136) (SEQ ID NO:85137) hCV12102850 C/T GGTTACAGGCTCCAGGAC
GGTTACAGGCTCCAGGAT (SEQ ID NO:85139) (SEQ ID NO:85140) hCV12108245
A/G GCCCTACAGCGGGT CCTACAGCGGGC (SEQ ID NO:85142) (SEQ ID NO:85143)
hCV12114319 A/G GACACTGCCCTCATCGT CACTGCCCTCATCGC (SEQ ID NO:85145)
(SEQ ID NO:85146) hCV12120554 C/T ACTGTCCTGTCTCTCCTCG
GACTGTCCTGTCTCTCCTCA (SEQ ID NO:85148) (SEQ ID NO:85149) hCV1253630
A/G TCGCAGGTGTCCCTA CGCAGGTGTCCCTG (SEQ ID NO:85151) (SEQ ID
NO:85152) hCV1260328 A/G TCCACGTGGACCAGGT CCACGTGGACCAGGC (SEQ ID
NO:85154) (SEQ ID NO:85l55) hCV1345898 C/T CAGTTTTCCATGGGTTCTACTAC
CAGTTTTCCATGGGTTCTACTAT (SEQ ID NO:85157) (SEQ ID NO:85158)
hCV1345898 T/C CAGTTTTCCATGGGTTCTACTAT CAGTTTTCCATGGGTTCTACTAC (SEQ
ID NO:85160) (SEQ ID NO:85161) hCV1361979 A/G
CCAGTTTTGGTGTCAACTAGAAA CCAGTTTTGGTGTCAACTAGAAG (SEQ ID NO:85163)
(SEQ ID NO:85164) hCV1366366 A/G TCCCTTAGTCCGGATGAT
TCCCTTAGTCCGGATGAC (SEQ ID NO:85166) (SEQ ID NO:85167) hCV1376137
A/G CTCCATCATTGCAGACCA TCCATCATTGCAGACCG (SEQ ID NO:85169) (SEQ ID
NO:85170) hCV1403468 A/C ACTGGCCCCTTGCAT ACTGGCCCCTTGCAG (SEQ ID
NO:85172) (SEQ ID NO:85173) hCV1466546 A/G TCTGGCTTCCGGGAA
TCTGGCTTCCGGGAG (SEQ ID NO:85175) (SEQ ID NO:85176) hCV15757745 C/G
AGATTTTCACCCATCCATG GAGATTTTCACCCATCCATC (SEQ ID NO:85178) (SEQ ID
NO:85179) hCV15760070 A/T TGTCCAGATCCACATAGAACA
TTGTCCAGATCCACATAGAACT (SEQ ID NO:85181) (SEQ ID NO:85182)
hCV15852235 C/T AAGAGGTCCTGAATCTTCTCTC AAGAGGTCCTGAATCTTCTCTT (SEQ
ID NO:85184) (SEQ ID NO:85185) hCV15871020 G/A
ATGTGAACTTAGCACTTTTATCA- G ATGTGAACTTAGCACTTTTATCAA (SEQ ID
NO:85187) (SEQ ID NO:85188) hCV15876071 G/A CGACTTAAGGGTGTAGTGTGAC
CGACTTAAGGGTGTAGTGTGAT (SEQ ID NO:85190) (SEQ ID NO:85191)
hCV15882348 C/T GCTGCTCTGCGCCG GCTGCTCTGCGCCA (SEQ ID NO:85193)
(SEQ ID NO:85194) hCV15943710 A/G CCTCATGGAGATCTTTCA
CCTCATGGAGATCTTTCG (SEQ ID NO:85196) (SEQ ID NO:85197) hCV15954277
A/G TGTCGGTAAACATGGCA GTCGGTAAACATGGCG (SEQ ID NO:85199) (SEQ ID
NO:85200) hCV15962586 C/T GGCTGTGCCTGGGAC GGCTGTGCCTGGGAT (SEQ ID
NO:85202) (SEQ ID NO:85203) hCV1603856 C/T GCTGCCCTCAGTCCG
TGCTGCCCTCAGTCCA (SEQ ID NO:85205) (SEQ ID NO:85206) hCV1603692 C/T
GGCCTCTAGGGGGCC AGGCCTCTAGGGGGCT (SEQ ID NO:85208) (SEQ ID
NO:85209) hCV1603697 C/T CGGCCTGCGTGGAC CGGCCTGCGTGGAT (SEQ ID
NO:85211) (SEQ ID NO:85212) hCV16044337 A/G TCCGGGTGCACGTATA
CGGGTGCACGTATG (SEQ ID NO:85214) (SEQ ID NO:85215) hCV16047108 A/G
TGTTTTCATCCACTTGAACTGT TTTTCATCCACTTGAACTGC (SEQ ID NO:85217) (SEQ
ID NO:85218) hCV16053900 G/T GGACGTGCTCCAGGATG GGACGTGCTCCAGGATT
(SEQ ID NO:85220) (SEQ ID NO:85221) hCV16165996 C/T
CTGAGGCCTATGTCCTC CTGAGGCCTATGTCCTT (SEQ ID NO:85223) (SEQ ID
NO:85224) hCV16166043 A/G CGGTTGAAGTCCTTGAT CGGTTGAAGTCCTTGAC (SEQ
ID NO:85226) (SEQ ID NO:85227) hCV16170435 G/C
ATCTCACAAATGATCGCTATG AATCTCACAAATGATCGCTATC (SEQ ID NO:85229) (SEQ
ID NO:85230) hCV16170900 A/G CGCACACCAGGTTCTCAT CGCACACCAGGTTCTCAC
(SEQ ID NO:85232) (SEQ ID NO:85233) hCV16170911 T/C
GGTTTCATTGCATGGTTTCT GTTTCATTGCATGGTTTCC (SEQ ID NO:85235) (SEQ ID
NO:85236) hCV16170982 C/G CCCCCACTCTCCAGC CCCCCACTCTCCAGG (SEQ ID
NO:85238) (SEQ ID NO:85239) hCV16172087 A/C GACTGCCCGTCAGCA
GACTGCCCGTCAGCC (SEQ ID NO:85241) (SEQ ID NO:85242) hCV16172249 C/G
ACTGTAATTTTTTTAAAGGTCCTG ACTGTAATTTTTTTAAAGGTCCTC (SEQ ID NO:85244)
(SEQ ID NO:85245) hCV16172339 A/T CTGCGGCTCCACCT TGCGGCTCCACCA (SEQ
ID NO:85247) (SEQ ID NO:85248) hCV16172571 A/G
GGTACCATGGACTGTACTCACT GTACCATGGACTGTACTCACC (SEQ ID NO:85250) (SEQ
ID NO:85251) hCV16179493 C/T GGGTCCGGCCACAC GGGTCCGGCCACAT (SEQ ID
NO:85253) (SEQ ID NO:85264) hCV16182835 A/G TGTTCTTCCTTATGATGATGT
GTTCTTCCTTATGATGATGC (SEQ ID NO:85256) (SEQ ID NO:85257)
hCV16189421 C/T GCCATCATTTGCTTCTAACAC GCCATCATTTGCTTCTAACAT (SEQ ID
NO:85259) (SEQ ID NO:85260) hCV16190893 C/T GCAGTACTTGCTTAGGG
CGCAGTACTTGCTTAGGA (SEQ ID NO:85262) (SEQ ID NO:85263) hCV16192174
G/A GAGCACCTTAACTATAGATGGTG TGAGCACCTTAACTATAGATGGTA (SEQ ID
NO:85265) (SEQ ID NO:85266) hCV16196014 C/G TGAAGAAGCTAAGGATTGAGG
TGAAGAAGCTAAGGATTGAGC (SEQ ID NO:85268) (SEQ ID NO:85269)
hCV16273460 C/T GCACTCTTGGACAAGCG TGCACTCTTGGACAAGCA (SEQ ID
NO:85271) (SEQ ID NO:85272) hCV16276495 C/T GTACCTTCACCCATGGAAC
GTACCTTCACCCATGGAAT (SEQ ID NO:85274) (SEQ ID NO:85275) hCV1647371
C/T CTGGCTGGGTCACTAACC GCTGGCTGGGTCACTAACT (SEQ ID NO:85277) (SEQ
ID NO:85278) hCV1662671 A/G CAGCCAAGAGCAGGACA AGCCAAGAGCAGGACG (SEQ
ID NO:85280) (SEQ ID NO:85281) hCV1789791 A/G ACAGAATCAGGCAATATCCA
CAGAATCAGGCAATATCCG (SEQ ID NO:85283) (SEQ ID NO:85284) hCV1819516
C/T CCCCTGTTGAGGAGTATTG GCCCCTGTTGAGGAGTATTA (SEQ ID NO:85286) (SEQ
ID NO:85287) hCV1842400 A/G TTGGTACCTGGCTCTCT TGGTACCTGGCTCTCC (SEQ
ID NO:85289) (SEQ ID NO:85290) hCV190754 C/T TCAAGGCTTAATGCCACTC
TCAAGGCTTAATGCCACTT (SEQ ID NO:85292) (SEQ ID NO:85293) hCV2038 G/A
CACGGCGGTCATGTG CGACGGCGGTCATGTA (SEQ ID NO:85295) (SEQ ID
NO:85296) hCV2126249 C/T CAGGGGAGTAAAGGTGACTC CAGGGGAGTAAAGGTGACTT
(SEQ ID NO:85298) (SEQ ID NO:85299) hCV2188895 A/G
AGAGAATGTTACCTCTCCTGA GAGAATGTTACCTCTCCTGG (SEQ ID NO:85301) (SEQ
ID NO:85302) hCV2200985 C/G GCGCACCAGCTTCAG GCGCACCAGCTTCAC (SEQ ID
NO:85304) (SEQ ID NO:85305) hCV22271841 C/T CATCACGGAGATCCACC
ATCATCACGGAGATCCACT (SEQ ID NO:85307) (SEQ ID NO:85308) hCV22272267
A/G CTCGCAGCGAATGTTAT CTGGCAGCGAATGTTAC (SEQ ID NO:85310) (SEQ ID
NO:85311) hCV22272997 G/A GCGGTAGCAGCAGCG GCGGTAGCAGCAGCA (SEQ ID
NO:85313) (SEQ ID NO:85314) hCV22273204 A/C TCAGCTTCTTCACTGCTA
CAGCTTCTTCACTGCTG (SEQ ID NO:85316) (SEQ ID NO:85317) hCV22274624
C/T CCCTACAGAGGATGTCAG CCCTACAGAGGATGTCAA (SEQ ID NO:85319) (SEQ ID
NO:85320) hCV22274632 A/C TGAATGAGCATCCAAAAGAA TGAATGAGCATCCAAAAGAC
(SEQ ID NO:85322) (SEQ ID NO:85323) hCV2351160 A/G CCACCAGTGGCTATCA
CCACCAGTGGCTATCG (SEQ ID NO:85325) (SEQ ID NO:85326) hCV2442143 C/T
ATTTAAGCATCATAGCATACCAC ATTTAAGCATCATAGCATACCAT (SEQ ID NO:85328)
(SEQ ID NO:85329) hCV2485037 A/G TGCAAGAGGACTAAGCATGA
GCAAGAGGACTAAGCATGG (SEQ ID NO:85331) (SEQ ID NO:85332) hCV2531086
A/G GCCCCCCTCTCTGAAGA CCCCCCTCTCTGAAGG (SEQ ID NO:85334) (SEQ ID
NO:85335) hCV2531431 A/G GCCAATGTGGCGGA GCCAATGTGGCGGG (SEQ ID
NO:85337) (SEQ ID NO:85338) hCV25472673 C/T TGGGCTCCATCCCAC
TGGGCTCCATCCCAT (SEQ ID NO:85340) (SEQ ID NO:85341) hCV25473653 C/T
CTCTAACATCACCGTGTACG CCTCTAACATCACCGTGTACA (SEQ ID NO:85343) (SEQ
ID NO:85344) hCV25474627 A/G GGTACCATGGACTGTACTCACT
GTACCATGGACTGTACTCACC (SEQ ID NO:85346) (SEQ ID NO:85347)
hCV2548962 C/T CAAATACATCTCCCAGGATC CAAATACATCTCCCAGGATT (SEQ ID
NO:85349) (SEQ ID NO:85350) hCV2553030 C/T CCGGCTTGCACTTCAC
CCGGCTTGCAGTTCAT (SEQ ID NO:85352) (SEQ ID NO:85353) hCV25593221
C/T GGCAACTCCTAGTAGTACAAC GGCAACTCCTAGTAGTACAAT (SEQ ID NO:85355)
(SEQ ID NO:85356) hCV25598594 A/G ATATATTGACCGTTCTCCCAT
ATATATTGACCGTTCTCCCAC (SEQ ID NO:85358) (SEQ ID NO:85359)
hCV25607108 A/G CCCTGTACTTTCATAAGATGCT CCTGTACTTTCATAAGATGCC (SEQ
ID NO:85361) (SEQ ID NO:85362) hCV25610470 A/G CACAATCACCACGGTCT
ACAATCACCACGGTCC (SEQ ID NO:85364) (SEQ ID NO:85365) hCV25610774
C/T GGGTCGGTGCAAGAGG GGGTCGGTGCAAGAGA (SEQ ID NO:85367) (SEQ ID
NO:85368) hCV25610819 A/T GGACGTGGACATGGAGT GGACGTGGACATGGAGA (SEQ
ID NO:85370) (SEQ ID NO:85371) hCV25613493 C/T CGGCCCTCAGGACC
CCGGCCCTCAGGACT (SEQ ID NO:85373) (SEQ ID NO:85374) hCV25614474 A/G
CTGTTGTCCTGCTTCCAA CTGTTGTCCTGCTTCCAG (SEQ ID NO:85376) (SEQ ID
NO:85377) hCV25615376 G/A ATTTAACACCACTATACTCTCAG
ATTTAACACCACTATACTCTCAA (SEQ ID NO:85379) (SEQ ID NO:85380)
hCV25615626 A/G AATATACCATTCTGTTAGGACTTA ATATACCATTCTGTTAGGACTTG
(SEQ ID NO:85382) (SEQ ID NO:85383) hCV25617571 C/T CCAGCAGTATGGACG
TGCCAGCAGTATGGACA (SEQ ID NO:85385) (SEQ ID NO:85386) hCV25620145
A/G CACACCAGCAATGATGAAACT CACCAGCAATGATCAAACC (SEQ ID NO:85388)
(SEQ ID NO:85389) hCV25620774 C/T CACCCTGGCTGGAGAG CACCCTGGCTGGAGAA
(SEQ ID NO:85391) (SEQ ID NO:85392) hCV25623265 A/G
TGGAGGCTGATGGGTA GGAGGCTGATGGGTG (SEQ ID NO:85394) (SEQ ID
NO:85395) hCV25627634 C/G CACCCTGCAGATGGAAC CACCCTGCAGATGGAAG (SEQ
ID NO:85397) (SEQ ID NO:85398) hCV25629492 A/G CCCACAGCCTGCGAT
CCCACAGCCTGCGAC (SEQ ID NO:85400) (SEQ ID NO:85401) hCV25630499 C/T
CATTGCTGGTTTCCACG CATTGCTGGTTTCCACA (SEQ ID NO:85403) (SEQ ID
NO:85404) hCV25630686 C/T AGGTTGTACCTGTAGCACTAAGAC
TAGGTTGTACCTGTAGCACTAAGAT (SEQ ID NO:85406) (SEQ ID NO:85407)
hCV25631989 C/T AAGATAAGCCTGTCACTGGTC AAGATAAGCCTGTCACTGGTT (SEQ ID
NO:85409) (SEQ ID NO:85410) hCV25637308 A/G CAGAAGGAAGACTACCATTAT
CAGAAGGAAGACTACCATTAC (SEQ ID NO:85412) (SEQ ID NO:85413)
hCV25637309 A/T GGCCACTTTGCCTGAATA GGCCACTTTGCCTGAATT (SEQ ID
NO:85415) (SEQ ID NO:85416) hCV25640505 A/G GATCCCCAGATTCCTAA
GATGCCCAGATTCCTAG (SEQ ID NO:85418) (SEQ ID NO:85419) hCV25640926
A/G GCCCAGAGACAGGAAAAT GCCCAGAGACAGGAAAAC (SEQ ID NO:85421) (SEQ ID
NO:85422) hCV25644901 A/G CAGACCTGCAGCTTCA AGACCTGCAGCTTCG (SEQ ID
NO:85424) (SEQ ID NO:85425) hCV25651174 A/G CGCTGCAGGGTCAT
CGCTGCAGGGTCAC (SEQ ID NO:85427) (SEQ ID NO:85428) hCV25654217 C/G
CCAATAGTCGTTTTTTGTTGG CCAATAGTCGTTTTTTGTTGC (SEQ ID NO:85430) (SEQ
ID NO:85431) hCV25751017 C/A CTTATTTTCAGCGAAAGGC
CCTTATTTTCAGCGAAAGGA (SEQ ID NO:85433) (SEQ ID NO:85434)
hCV25761292 C/G GGGCAGCTCACCTCTCTAG GGGCAGCTCACCTCTCTAC (SEQ ID
NO:85436) (SEQ ID NO:85437) hCV25922320 A/G CTCGCAGCGGTCAGT
TCGCAGCGGTCAGC (SEQ ID NO:85439) (SEQ ID NO:85440) hCV25922816 A/G
TGGCACTCAGGGCAT TGGCACTCAGGGCAC (SEQ ID NO:85442) (SEQ ID NO:85443)
hCV25926178 C/G GCTTTATCAGAGACTCTGAAGC GCTTTATCAGAGACTCTGAAGG (SEQ
ID NO:85445) (SEQ ID NO:85446) hCV25926771 C/T GGCCTTGGTCTCGC
TGGCCTTGGTCTCGT (SEQ ID NO:85448) (SEQ ID NO:85449) hCV25930271 C/T
GAATCTCATGTTCAGGAAATG CGAATCTCATGTTCAGGAAATA (SEQ ID NO:85451) (SEQ
ID NO:85452) hCV25942539 G/A GGATCCGACCGTTGAG GGATCCGACCGTTGAA (SEQ
ID NO:85454) (SEQ ID NO:85455) hCV25943544 C/G
ATGTCCTGAAATACACGTATGAC ATGTCCTGAAATACACGTATGAG (SEQ ID NO:85457)
(SEQ ID NO:85458) hCV25956925 A/G GCTTCCCTGGGCTTCT CTTCCCTGGGCTTCC
(SEQ ID NO:85460) (SEQ ID NO:85461) hCV25990513 G/A
AGATAATCATAAGCTGGAGAACAC AGATAATCATAAGCTGGAGAACAT (SEQ ID NO:85463)
(SEQ ID NO:85464) hCV2715953 C/G CATTGGGGCCAATGAC ATTGGGGCCAATGAG
(SEQ ID NO:85466) (SEQ ID NO:85467) hCV2741051 C/T GCAGCCAGTTTCTCCC
TGCAGCCAGTTTCTCCT (SEQ ID NO:85469) (SEQ ID NO:85470) hCV2741083
C/T GTTCCAACCAGAAGAGAATG GGTTCCAACCAGAAGAGAATA (SEQ ID NO:85472)
(SEQ ID NO:85473) hCV2769554 A/G TCCGTTGTTCTCAGGGAT
TCCGTTGTTCTCAGGGAC (SEQ ID NO:85475) (SEQ ID NO:85476) hCV2782570
A/G CCAGCAAACTATGATGAATAAT CCAGCAAACTATGATGAATAAC (SEQ ID NO:85478)
(SEQ ID NO:85479) hCV2811372 A/G CAGCTGGACGACGAACA AGCTGGACGACGAACG
(SEQ ID NO:85481) (SEQ ID NO:85482) hCV2983035 A/G
TTGGACCCTCACATGAAA TTGGACCCTCACATGAAG (SEQ ID NO:85484) (SEQ ID
NO:85485) hCV2992252 T/C CCCTGTGATTGGCCAT CCCTGTGATTGGCCAC (SEQ ID
NO:85487) (SEQ ID NO:85488) hCV3020386 G/T AGAATTGTGTCCAAAGAAGTTG
AAGAATTGTGTCCAAAGAAGTTT (SEQ ID NO:85490) (SEQ ID NO:85491)
hCV3023236 A/G CAGTTGGTTTTGTGGT AGTTGGTTTTGTGGC (SEQ ID NO:85493)
(SEQ ID NO:85494) hCV3026206 C/G CCGTCTGGTAATTGTCCAC
CCGTCTGGTAATTGTCCAG (SEQ ID NO:85496) (SEQ ID NO:85497) hCV3084793
C/T CCCGGCTGGGCGCGGACATGGAGGACGTT- C CCCGGCTGGGCGCGGACATGGAGGACGTTT
(SEQ ID NO:85499) (SEQ ID NO:85500) hCV3112686 C/G
ACTTTGCTTCCCGAAGATAC ACTTTGCTTCCCGAAGATAG (SEQ ID NO:85502) (SEQ ID
NO:85503) hCV3135085 G/T CTGGAAATGGTTATGGGC TACTGGAAATGGTTATGGGA
(SEQ ID NO:85505) (SEQ ID NO:85506) hCV3187716 A/C
CCTTCAATTCTGAAAAGTAGCTAAT CCTTCAATTCTGAAAAGTAGCTAAG (SEQ ID
NO:85508) (SEQ ID NO:85509) hCV3210838 C/T CTGCATTATTTCTATGACGC
TTCTGCATTATTTCTATGACGT (SEQ ID NO:85511) (SEQ ID NO:85512)
hCV3212009 A/G GTTCTCCCCTTTCAGTGTCT TCTCCCCTTTCAGTGTCC (SEQ ID
NO:85514) (SEQ ID NO:85515) hCV3215409 A/G GTGGCTCATTACCAATCTCTT
GTGGCTCATTACCAATCTCTC (SEQ ID NO:85517) (SEQ ID NO:85518)
hCV3223182 C/T TCGCAACTCACATCACTG GTCGCAACTCACATCACTA (SEQ ID
NO:85520) (SEQ ID NO:85521) hCV3275199 A/G CCATGCAACCAAACCAT
CCATGCAACCAAACCAC (SEQ ID NO:85523) (SEQ ID NO:85524) hCV334226 A/G
GAGCCTGGGCCAAAT GAGCCTGGGCCAAAC (SEQ ID NO:85526) (SEQ ID NO:85527)
hCV517658 T/C AATGGCCTTGGACTTGAT AATGGCCTTGGACTTGAC (SEQ ID
NO:85529) (SEQ ID NO:85530) hCV529706 C/G GCGAGGACGAAGGGG
GCGAGGACGAAGGGC (SEQ ID NO:85532) (SEQ ID NO:85533) hCV529710 C/G
CCGACCCGAACTAAAGG CCGACCCGAACTAAAGC (SEQ ID NO:85535) (SEQ ID
NO:85536) hCV549926 C/T ACCATGGTCACCCTGG CACCATGGTCACCCTGA (SEQ ID
NO:85538) (SEQ ID NO:85539) hCV5687 A/G GCCCTCAGTGTGACTGAGAT
GCCCTCAGTGTGACTGAGAC (SEQ ID NO:85541) (SEQ ID NO:85542) hCV57888
A/G GCATAAAGCCAAGGTAGAAA GCATAAAGCCAAGGTAGAAG (SEQ ID NO:85544)
(SEQ ID NO:85545) hCV600632 A/C CGTCAATGCCCTCATCT GTCAATGCCCTCATCG
(SEQ ID NO:85547) (SEQ ID NO:85548) hCV7429784 A/G
GGGTCATGGTACTCAATGAA GGGTCATGGTACTCAATGAG (SEQ ID NO:85550) (SEQ ID
NO:85551) hCV7443062 T/C GGAGCAGGATGGTGAT GGAGCAGGATGGTGAC (SEQ ID
NO:85553) (SEQ ID NO:85554) hCV7449808 A/G GGCTTACCTGGCCCAGT
GCTTACCTGGCCCAGC (SEQ ID NO:85556) (SEQ ID NO:85557) hCV7481138 A/C
CGGATCTCTCGCAA CGGATCTCTCGCAC (SEQ ID NO:85559) (SEQ ID NO:85560)
hCV7490135 C/T GCAGTCCTGAACAAAGTAGATG CGCAGTCCTGAACAAAGTAGATA (SEQ
ID NO:85562) (SEQ ID NO:85563) hCV7492597 C/T TACCTGAGCCAGTTGCAC
TACCTGAGCCAGTTGCAT (SEQ ID NO:85565) (SEQ ID NO:85566) hCV7492601
T/A AAGGAGGTCTGCCTAAGGA AAGGAGGTCTGCCTAAGGT (SEQ ID NO:85568) (SEQ
ID NO:85569) hCV7494810 C/G CCCGAGCGGACAGTG CCCGAGCGGACAGTC (SEQ ID
NO:85571) (SEQ ID NO:85572) hCV7499900 T/C CACACCAGCAATGATGAAACT
CACCAGCAATGATGAAACC (SEQ ID NO:85574) (SEQ ID NO:85575) hCV7509650
C/T GCTCAGGACTATCTGCAGTG GGCTCAGGACTATCTGCAGTA (SEQ ID NO:85577)
(SEQ ID NO:85578) hCV7514692 A/C GCCCCAACACCAGAGAA
GCCCCAACACCAGAGAC (SEQ ID NO:85580) (SEQ ID NO:85581) hCV7514879
A/G GGCTGAACCCCGTCCT GCTGAACCCCGTCCC (SEQ ID NO:85583) (SEQ ID
NO:85584) hCV7580070 C/T TCCCATGCTTAAGGAAATG GATCCCATGCTTAAGGAAATA
(SEQ ID NO:85586) (SEQ ID NO:85587) hCV7582933 C/T
CCAAAGGGTGTCAAGGC TCCAAAGGGTGTCAAGGT (SEQ ID NO:85589) (SEQ ID
NO:85590) hCV761961 C/T CACAGTCAAAGAATCAAGCG TCACAGTCAAAGAATCAAGCA
(SEQ ID NO:85592) (SEQ ID NO:85593) hCV7686234 C/T
GAGCGCTCTTTCTTGAC GAGCGCTCTTTCTTGAT (SEQ ID NO:85595) (SEQ ID
NO:85596) hCV7798230 G/C GAGCGAGGGCTCAGG GAGCGAGGGCTCAGC (SEQ ID
NO:85598) (SEQ ID NO:85599) hCV783184 G/T TGCGAGTCAAATCTCAAGAC
TGCGAGTCAAATCTCAAGAA (SEQ ID NO:85601) (SEQ ID NO:85602) hCV7841642
A/G ACCAGCTCCAGGGTGTT ACCAGCTCCAGGGTGTC (SEQ ID NO:85604) (SEQ ID
NO: 85605) hCV7900503 C/T CGTCTCCAGGAAAATCATAAC
CGTCTCCAGGAAAATCATAAT (SEQ ID NO:85607) (SEQ ID NO:85608) hCV791476
C/T CAGAAAGTTCATGGTTTCG GCAGAAAGTTCATGGTTTCA (SEQ ID NO:85610) (SEQ
ID NO:85611) hCV795442 A/G CCATTCAATGCAATACGTCA CATTCAATGCAATACGTCG
(SEQ ID NO:85613) (SEQ ID NO:85614) hCV8022252 A/G
CACTGGTCTCAGATGTGATGT ACTGGTCTCAGATGTGATGC (SEQ ID NO:85616) (SEQ
ID NO:85817) hCV8339791 C/T TTCTACAACGTGGACATGG
ACTTCTACAACGTGGACATGA (SEQ ID NO:85619) (SEQ ID NO:85620)
hCV8400671 A/G TTGTTAACATATACTTACTGGAGA TGTTAACATATACTTACTGGAGG
(SEQ ID NO:85622) (SEQ ID NO:85623) hCV8705506 C/G CCACTTCGGGTTCCTC
CCACTTCGGGTTCCTG (SEQ ID NO:85625) (SEQ ID NO:85626) hCV8708473 A/G
GCAACAGGACACCTGAA GCAACAGGACACCTGAG (SEQ ID NO:85628) (SEQ ID
NO:85629) hCV8718197 A/G CCTCTGAGGCCTGAGAAA CCTCTGAGGCCTGAGAAG (SEQ
ID NO:85631) (SEQ ID NO:85632) hCV8722981 C/T GCGCTGGTTTGGAGG
GCGCTGGTTTGGAGA (SEQ ID NO:85634) (SEQ ID NO:85635) hCV8726331 A/G
TGGTCTGTTCCCTGGACA GGTCTGTTCCCTGGACG (SEQ ID NO:85637) (SEQ ID
NO:85838) hCV8726337 A/G CACATTCACGGTCACCTT CACATTCACGGTCACCTC (SEQ
ID NO:85640) (SEQ ID NO:85641) hCV8737990 C/T GTCCTTGCAAGTATCCG
GGTCCTTGCAAGTATCCA (SEQ ID NO:85643) (SEQ ID NO:85644) hCV8815434
G/T GGTGGTCCCTTTGG ACGGTGGTCCCTTTGT (SEQ ID NO:85646) (SEQ ID
NO:85647) hCV8827241 C/G TCAAGAGGACAGTGATGGTG TCAAGAGGACAGTGATGGTC
(SEQ ID NO:85649) (SEQ ID NO:85650) hCV8849004 A/G
AGAGAGTGCACAGTAGATGT GAGAGTGCACAGTAGATGC (SEQ ID NO:85652) (SEQ ID
NO:85653) hCV8851080 A/G GGCACTGCCCGCTT GGCACTGCCCGCTC (SEQ ID
NO:85655) (SEQ ID NO:85656) hCV8851084 A/G CAGTGCCGGACAGGA
CAGTGCCGGACAGGG (SEQ ID NO:85658) (SEQ ID NO:85659) hCV8851085 A/G
GCTCGTAGTTGTGTCTGCAT GCTCGTAGTTGTGTCTGCAC (SEQ ID NO:85661) (SEQ ID
NO:85662) hCV8895373 A/G AGGACTTCCGTGTCTT AGGACTTCCGTGTCTC (SEQ ID
NO:85664) (SEQ ID NO:85665) hCV8907537 C/G GCCTATCCATCCTGCC
GCCTATCCATCCTGCG (SEQ ID NO:85667) (SEQ ID NO:85668) hCV8921137 A/T
CAGAGCCTGCACATCAAT CAGAGCCTGCACATCAAA (SEQ ID NO:85670) (SEQ ID
NO:85671) hCV8921288 C/A CCGCAGAGGTGTGGG CCGCAGAGGTGTGGT (SEQ ID
NO:85673) (SEQ ID NO:85674) hCV8931357 A/G
TTATTGACACTTTCCAGTAAATAATT TTATTGACACTTTCCAGTAAATAATC (SEQ ID
NO:85676) (SEQ ID NO:85677) hCV8952817 C/G CGCATCCAGAACATTCTATG
CGCATCCAGAACATTCTATC (SEQ ID NO:85679) (SEQ ID NO:85680) hCV905013
G/T ACACCTCGCCCAGTAATC GACACCTCGCCCAGTAATA (SEQ ID NO:85682) (SEQ
ID NO:85683) hCV9077561 G/A AGAAGGTGGGATCCAAAC AGAAGGTGGGATCCAAAT
(SEQ ID NO:85685) (SEQ ID NO:85686) hCV9485713 T/C
GCCCAGAGACAGGAAAAT GCCCAGAGACAGGAAAAC (SEQ ID NO:85688) (SEQ ID
NO:85689) hCV9506149 A/T CTGCTGGCCGTCCT TGCTGGCCGTCCA (SEQ ID
NO:85691) (SEQ ID NO:85692) hCV9546471 A/C CTCAGGAAGCTAAAAGGTGA
TCAGGAAGCTAAAAGGTGC (SEQ ID NO:85694) (SEQ ID NO:85695) hCV9546517
G/A ACATTTCAGAACCTATCTTCTTC ACATTTCAGAACCTATCTTCTTT (SEQ ID
NO:85697) (SEQ ID NO:85698) hCV9698595 A/T GCTGGTCATCCTCATCCA
TGCTGGTCATCCTCATCCT (SEQ ID NO:85700) (SEQ ID NO:85701) Marker
Sequence C (commom primer) hCV1085600 GAAGTCAACAGTGAACATGTGA (SEQ
ID NO:85093) hCV1088055 CCTTCCAGGTGAAGGTCAC (SEQ ID NO:85096)
hCV11225994 TGACATTGCACTCTCAAATATTT (SEQ ID NO:85099) hCV11359098
GAGCTGTGTGTTTCTTTGTTCTA (SEQ ID NO:85102) hCV11482766
CCACGTTCTGGTCGATCTT (SEQ ID NO:85105) hCV11571465
CCTTGGCTGTGTGGTACAG (SEQ ID NO:85108) hCV11696920 CGGCTTTGGCCTACAAG
(SEQ ID NO:85111) hCV1180648 TCGCTATCCAAGTGAACATATC (SEQ ID
NO:85114) hCV11852251 TGTCATCAGATGAAGAAGAGAGAA (SEQ ID NO:85117)
hCV11889257 GGGCAGGGCTAGGAGTAG (SEQ ID NO:85120) hCV11942529
CCAGGGTTGGGCTACTG (SEQ ID NO:85123) hCV11951095 GGGCCAGCATGTGGAC
(SEQ ID NO:85126) hCV11975296 CTCCACCTGCATTTCAGAG (SEQ ID NO:85129)
hCV12020339 GGCCCCAACAGTTGACTG (SEQ ID NO:85132) hCV1202883
AGCCTCTCCTGACTGTCATC (SEQ ID NO:85135) hCV1207994
CATTTTGCTGATGTTTGTTTCTAG (SEQ ID NO:85138) hCV12102850
CTGATGGCCAAAAGAAGAGT (SEQ ID NO:85141) hCV12108245
GACGGATCTGACAGAATCTTTC (SEQ ID NO:85144) hCV12114319
CCTGTCCTTGAGGTCTGATC (SEQ ID NO:85147) hCV12120554
TTGCCAGCCATGACTAGA (SEQ ID NO:85150) hCV1253630 CCCCATCCCTTCTCA
(SEQ ID NO:85153) hCV1260328 GCCCAGGTATTTCATCAGC (SEQ ID NO:85156)
hCV1345898 TTATGAAATGGTACAGACAAGTGAT (SEQ ID NO:85159) hCV1345898
TTATGAAATGGTACAGACAAGTGAT (SEQ ID NO:85162) hCV1361979
TTGCAACCTGAAAAACATAACTA (SEQ ID NO:85165) hCV1366366
GACTCTTTTGCAGGAATGTGT (SEQ ID NO:85168) hCV1376137
CCAATTCCCCTGATGTTAAA (SEQ ID NO:85171) hCV1403468
AGGAGGGAACCAAACCTTA (SEQ ID NO:85174) hCV1466546
CGTAGCTGTTGACCATCATTTA (SEQ ID NO:85177) hCV15757745
TGCCGACTCAGAAACTCTCTA (SEQ ID NO:85180) hCV15760070
CTTTATGCAGCGGACCAT (SEQ ID NO:85183) hCV15852235
ATGAAATGGGTCAACAAAACT (SEQ ID NO:85186) hCV15871020
AACCTTCCGTGGAAAGAGA (SEQ ID NO:85189) hCV15876071 CCGAAAACGGAAGCATC
(SEQ ID NO:85192) hCV15882348 GCCCTCTGCGTACCTAAGG (SEQ ID NO:85195)
hCV15943710 GAGGCCAGCGAGGAGA (SEQ ID NO:85198) hCV15954277
GGTGGGTGGTCTGACTCTC (SEQ ID NO:85201) hCV15962586
GAAGGCAGGGACTTTTATCA (SEQ ID NO:85204) hCV1603856
GGGCACTGCCAATTCTTAG (SEQ ID NO:85207) hCV1603692 CCCCATTTGCACACAGAC
(SEQ ID NO:85210) hCV1603697 GCCCAGGGCGTGTTCT (SEQ ID NO:85213)
hCV16044337 TGGAGAGTGTTTGCTCATCTAC (SEQ ID NO:85216) hCV16047108
CAATTTTGGCTCCCTTAAAAG (SEQ ID NO:85219) hCV16053900
GGTTCACATTTTGGTTCACAA (SEQ ID NO:85222) hCV16165996
AGCTCTCCTTTGTTGCTACTG (SEQ ID NO:85225) hCV16166043
GGTTGTGCAGAGACATCTGA (SEQ ID NO:85228) hCV16170435
CAGGCTCCATCTCACAGATAC (SEQ ID NO:85231) hCV16170900
GCAACTACCTGGGCCACTATA (SEQ ID NO:85234) hCV16170911
GGGTACTGAATTTTTAAAAGGTTTTA (SEQ ID NO:85237) hCV16170982
GGCAAAAGCACTGTGAAGA (SEQ ID NO:85240) hCV16172087
GGAGGTCAGGTGGATGTTTA (SEQ ID NO:85243) hCV16172249
GGATGTATATCATCTATCTTCACAG- TATAT (SEQ ID NO:85246) hCV16172339
TGGCATCTGCCATACTCA (SEQ ID NO:85249) hCV16172571
AGGTTGGTTCTGGAGATGAC (SEQ ID NO:85252) hCV16179493 GGGCCCCTCAGTGAAG
(SEQ ID NO:85255) hCV16182835 GGCGTTCCTCTCACCTTAATA (SEQ ID
NO:85258) hCV16189421 GCTTATTTGCCAGAAAACATTT (SEQ ID NO:85261)
hCV16190893 GCCACCTTTATTTCTTTAGTGAA (SEQ ID NO:85264) hCV16192174
CTTGTCAAGGCACAGAATAATT (SEQ ID NO:85267) hCV16196014
CTCTCCCTGGCTGAGTTG (SEQ ID NO:85270) hCV16273460
AATGACATCCCCTATCTTTCTG (SEQ ID NO:85273) hCV16276495
TCACTTTCTGTTGATTACATGAGA (SEQ ID NO:85276) hCV1647371
CCTCACCTGCATTCACATTT (SEQ ID NO:85279) hCV1662671
CCCAAGACACGTTCAGAAAT (SEQ ID NO:85282) hCV1789791
TTTGTAGACCAGTGAAGAAGTGAT (SEQ ID NO:85285) hCV1819516
GTTCTGCCAGGGAATCTCTA (SEQ ID NO:85288) hCV1842400
AAACTTCTTAGGACAGAGTGATTAGA (SEQ ID NO:85291) hCV190754
CGTAAGTCTGTGATTTGTCAATACT (SEQ ID NO:85294) hCV2038
GGTGGAGCTTGGTTTCTCA (SEQ ID NO:85297) hCV2126249 GCTCAGCCAGCCAGAAA
(SEQ ID NO:85300) hCV2188895 TTCTCCTGGGTCAGATTCTC (SEQ ID NO:85303)
hCV2200985 TGTAATACATGATTTTCAGACAC- AC (SEQ ID NO:85306)
hCV22271841 TCAGCTCCAAGGAGATTCTTAG (SEQ ID NO:85309) hCV22272267
CCTCTAGAAACAAAATGGACTGTAT (SEQ ID NO:85312) hCV22272997
AGGCCCTCCTACCTTTTG (SEQ ID NO:85315) hCV22273204
GCTTTGATTTCCTACTCTGATTTTA (SEQ ID NO:85318) hCV22274624
CAGAGCCTCCCTTGTCAC (SEQ ID NO:85321) hCV22274632 GCAGCACGAAGCATTCAT
(SEQ ID NO:85324) hCV2351160 GGCAAGCAGGCTTGAGAA (SEQ ID NO:85327)
hCV2442143 TGGTACACCATAAATCTTGACTTAC (SEQ ID NO:85330) hCV2485037
GCGGCCTTGCACTCA (SEQ ID NO:85333) hCV2531086 CCAGTTCGTGGTATGTTCATCT
(SEQ ID NO:85336) hCV2531431 CCTGGACGACGGTTTCA (SEQ ID NO:85339)
hCV25472673 CCAATTCTTTTTCTTCTTTCAGTT (SEQ ID NO:85342) hCV25473653
GAGCTCTGGGTCAGAACTGT (SEQ ID NO:85345) hCV25474627
AGGTTGGTTCTGGAGATGAC (SEQ ID NO:85348) hCV2548962
GTTTTAATTGCAGTTTGAATGATAT (SEQ ID NO:85351) hCV2553030
CTTTGTGGCCGCAGTAGT (SEQ ID NO:85354) hCV25593221
GGAAGTTTCCATCCAAATTTAC (SEQ ID NO:85357) hCV25598594
GCCACCTCCAACCATATC (SEQ ID NO:85360) hCV25607108 ACGACGCCAAGGTGATA
(SEQ ID NO:85363) hCV25610470 CCTTCTGCATCAGCATCTTC (SEQ ID
NO:85366) hCV25610774 GCACCTTGGTGGGTTTGT (SEQ ID NO:85369)
hCV25610819 CGGCGCTCGTAGGTG (SEQ ID NO:85372) hCV25613493
GCGGAAGGTACCAAGTTTG (SEQ ID NO:85375) hCV25614474
GTTTCTGCATCAGTGAGATTTT (SEQ ID NO:85378) hCV25615376
GGATATGCCTTCTTTGGAAATA (SEQ ID NO:85381) hCV25615626
GTGGTGGTGGGTCAGTATG (SEQ ID NO:85384) hCV25617571
CCATCCAGCCTCAGGAAC (SEQ ID NO:85387) hCV25620145
GGGCTAACTCTTTGCATCTTC (SEQ ID NO:85390) hCV25620774
CTCCCTGTCCCAAAAAGAC (SEQ ID NO:85393) hCV25623265
CGCTTTGCAGCCATAACT (SEQ ID NO:85396) hCV25627634
CAAGACTCCTTCATCCTCAATAGT (SEQ ID NO:85399) hCV25629492
CCGCTTGAGGTCCACATA (SEQ ID NO:85402) hCV25630499 GGCAGTGGCACACAATCT
(SEQ ID NO:85405) hCV25630686 TGGGCTCCTCAGAGAAAATAT (SEQ ID
NO:85408) hCV25631989 CAAGCCAGCCTAATAAACATAA (SEQ ID NO:85411)
hCV25637308 CCTCCCCCTATTTATTTTTACAT (SEQ ID NO:85414) hCV25637309
CGAAATGTTCATTTTTAAAGTCAGA (SEQ ID NO:85417) hCV25640505
GCTCCATGCCTTGATTCT (SEQ ID NO:85420) hCV25640926 GCCTGCCCTCTGTTCA
(SEQ ID NO:85423) hCV25644901 TGTAACCCATCAACTCTGTTTATC (SEQ ID
NO:85426) hCV25651174 CCTCCCCGCAGAGAATTA (SEQ ID NO:85429)
hCV25654217 GCTGTGTGGGAAGTCAGAAC (SEQ ID NO:85432) hCV25751017
CCAATGGTCGTCATCTCC (SEQ ID NO:85435) hCV25761292
GAGTGACTGCCACAATTGTCT (SEQ ID NO:85438) hCV25922320
GCTGGCGGGAATTTCT (SEQ ID NO:85441) hCV25922816
CCAAAGAGGACTGACAACTGTA (SEQ ID NO:85444) hCV25926178
CCAAGGCCACGGATATC (SEQ ID NO:85447) hCV25926771
TGCAGATCAGCTTGAAGAACTA (SEQ ID NO:85450) hCV25930271
GCCATGGCCCATAAAAC (SEQ ID NO:85453) hCV25942539
TCATTTTGAACTCATTTTTTCTA- GA (SEQ ID NO:85456) hCV25943544
TCCCAACGTCAATTTCATATT (SEQ ID NO:85459) hCV25956925
TGCTCATCATGAGTTTGAAACT (SEQ ID NO:85462) hCV25990513
TGATTATGCATCTTCTGTCTTGTAG (SEQ ID NO:85465) hCV2715953
ATGCATTTCATGTGAAAACTCT (SEQ ID NO:85468) hCV2741051
CATGAAATGCTTCCAGGTATT (SEQ ID NO:85471) hCV2741083
CTTGCCCCCAACAGTTAG (SEQ ID NO:85474) hCV2769554 GGTTCCTGGAGGCATGTC
(SEQ ID NO:85477) hCV2782570 TGGGATGACTCTAGCCACTTAC (SEQ ID
NO:85480) hCV2811372 CGGCTCTCCTTGATGAG (SEQ ID NO:85483) hCV2983035
GCCATTTTCCACAATAAATATTT (SEQ ID NO:85486) hCV2992252
CCTGCTCGCTCTGTCAC (SEQ ID NO:85489) hCV3020386
AACTGGTATAATTTGAATCACATAAAT (SEQ ID NO:85492) hCV3023236
TGCTTCGTGGAGGTCAAT (SEQ ID NO:85495) hCV3026206 TCAAGCCCTTGGCTAAGA
(SEQ ID NO:85498) hCV3084793 CAGCTTGCGCAGGTG (SEQ ID NO:85501)
hCV3112686 TCACCGCTCCACAGACTT (SEQ ID NO:85504) hCV3135085
TTTATAGGCGTGAAACTAATTCTC (SEQ ID NO:85507) hCV3187716
TTTGAGGTTGAGTGACATGTTC (SEQ ID NO:85510) hCV3210838
CAAAAAATGCCAACAGTTTAGA (SEQ ID NO:85513) hCV3212009
TGTCGGTGACTGTTCTGTTAA (SEQ ID NO:85516) hCV3215409
GGGCTCCATCAACATCAC (SEQ ID NO:85519) hCV3223182
AGTTCTTGGAGGCATCTCAT (SEQ ID NO:85522) hCV3275199
CCTCTCATCCCTCTCATCTTT (SEQ ID NO:85525)
hCV334226 CCTAAGAGGCTGGAAAGATAGAG (SEQ ID NO:85528) hCV517658
CTCTGCCATGCAAAACAC (SEQ ID NO:85531) hCV529706
GGAGGATGAATGGACAGACAA (SEQ ID NO:85534) hCV529710 CGCGTTCCCCATGTC
(SEQ ID NO:85537) hCV549926 GGACTGAAAGCAATGTGAGAG (SEQ ID NO:85540)
hCV5687 CCAGGCATTTCCCATACAG (SEQ ID NO:85543) hCV57888
CCACTGGAACACTCACACAT (SEQ ID NO:85546) hCV600632
GAGACTGCGATGTCTGAATAGT (SEQ ID NO:85549) hCV7429784
TGTACAAAAATGTTGTCACATACAG (SEQ ID NO:85552) hCV7443062
GGAAATATCTCGTTCTTGTTCTCT (SEQ ID NO:85555) hCV7449808
CCTTCAGCCTCCAACATGA (SEQ ID NO:85558) hCV7481138 TGGAGGAGGTGATTCA
(SEQ ID NO:85561) hCV7490135 CGTGCATGTTTTGAAAAATGTA (SEQ ID
NO:85564) hCV7492597 GGCTTCAGCTGAAGAAAGAG (SEQ ID NO:85567)
hCV7492601 TACCTGCCTTTAAAGAACATTACT (SEQ ID NO:85570) hCV7494810
CAACTGCTGGCAGAATCTTC (SEQ ID NO:85573) hCV7499900 GGCGGGTTCCAGACAA
(SEQ ID NO:85576) hCV7509650 TCCAAGCATGACTTCAGATTC (SEQ ID
NO:85579) hCV7514692 CCACCACCACTCACCAGA (SEQ ID NO:85582)
hCV7514879 CTTTTTCCTGCATCCTGTCT (SEQ ID NO:85585) hCV7580070
TGAGTGTACAATTCTAATTCTCAGACT (SEQ ID NO:85588) hCV7582933
GCTGCTGGAATATGTTTGAGA (SEQ ID NO:85591) hCV761961
AAATTCTTACCCTGAGTTCAGTTC (SEQ ID NO:85594) hCV7686234
GCGGAGGCCCTCTGTA (SEQ ID NO:85597) hCV7798230 CCTCCCTGGAGAATACTGTG
(SEQ ID NO:85600) hCV783184 CCTATTCCCGGCACTTCT (SEQ ID NO:85803)
hCV7841642 TGAAGTTTTGGAATGAGACTGAT (SEQ ID NO:85606) hCV7900503
TGAGTTATTGCTACTTCAGAATCAT (SEQ ID NO:85609) hCV791476
CCGGGGAGGAAGAGTAG (SEQ ID NO:85612) hCV795442 CCTCTCCTTCCAGAACCAGT
(SEQ ID NO:85615) hCV8022252 GGGCTGGCAGGGTATAG (SEQ ID NO:85618)
hCV8339791 GCCTGCCACTCACATTACA (SEQ ID NO:85621) hCV8400671
TGCCTCTTCTTTATTTATGTC (SEQ ID NO:85624) hCV8705506
CCCTGGCTTCAACATGA (SEQ ID NO:85627) hCV8708473 GAGTGACAGGAGGCTGCTTA
(SEQ ID NO:85630) hCV8718197 GTCCTGATTCCTCATTTCTTTC (SEQ ID
NO:85633) hCV8722981 TGGCACAGGCAGTATTAAGTAG (SEQ ID NO:85636)
hCV8726331 TGCGGTCACACTGACTGAG (SEQ ID NO:85639) hCV8726337
CATTGCCCGAGCTCAA (SEQ ID NO:85842) hCV8737990
GCACTACAGCTGAGTCCTTTTC (SEQ ID NO:85645) hCV8815434
CCTCGCAGGCCTTCTC (SEQ ID NO:85648) hCV8827241
TGGTTAGAATCTGTGAAGGAACTA (SEQ ID NO:85651) hCV8849004
AAACCTGAGTTTTAACTTGGTGA (SEQ ID NO:85654) hCV8851080
CGCTTCCTGGAGAGATACATC (SEQ ID NO:85657) hCV8851084 CCGCCCGGCACTAAG
(SEQ ID NO:85660) hCV8851085 CGCTTCCTGGAGAGATACAT (SEQ ID NO:85663)
hCV8895373 ACAGATGCCAGCAATACAGA (SEQ ID NO:85666) hCV8907537
GGTAGGAGAGCACTGAGAATACT (SEQ ID NO:85669) hCV8921137
GGCAAGGTCTCTGATCTGTAA (SEQ ID NO:85672) hCV8921288
CATTTTGCGGTGGAAATG (SEQ ID NO:85675) hCV8931357 AGGCACAAGCTGCAGATAA
(SEQ ID NO:85678) hCV8952817 GCAGCTTCCCATCATACACT (SEQ ID NO:85681)
hCV905013 CCCCCTCTCCAGATTACATT (SEQ ID NO:85684) hCV9077561
AGAAACCATCATGCTGAGGT (SEQ ID NO:85687) hCV9485713 GCCTGCCCTCTGTTCA
(SEQ ID NO:85690) hCV9506149 ACTCACGCTTGCTTTGACT (SEQ ID NO:85693)
hCV9546471 CCTAATATCCCCTCCAGAACTAT (SEQ ID NO:85696) hCV9546517
AGTTCATATGGACCAGACATCA (SEQ ID NO:85699) hCV9698595
ACCGTCCTGGCTTTTAAAG (SEQ ID NO:85702)
[0484]
12TABLE 6 Significant Associations Between SNP Genotypes and
Qualitative Phenotypes Overall* SNP Effect** Chi-Square Test
Chi-Square Test Public Marker Stratum Phenotype statistic p-value
statistic p-value ACACB hCV16166043 All Patients Fatal Coronary
Heart Disease 7.5339 0.0231 6.6562 0.0099 ACACB hCV16166043 All
Patients Coronary Artery Bypass or Revascularization 10.3188 0.0057
9.2668 0.0023 ACACB hCV16166043 All Patients Hosp for Unstable
Angina 13.3305 0.0013 9.466 0.0021 ACACB hCV16166043 All Patients
Family History of CV Disease 8.0471 0.0179 6.7129 0.0096 ACE
hCV11942529 All Patients Fatal Coronary Heart Disease 14.0826
0.0009 5.2478 0.022 ACE hCV11942529 All Patients Cardiovascular
Mortality 12.0994 0.0024 4.8517 0.0276 ACE hCV11942529 All Patients
Fatal Atherosclerotic Cardiovascular Disease 12.0994 0.0024 4.8517
0.0276 ADAMTS1 hCV529706 All Patients Fatal CHD/Definite Non-fatal
MI 7.3723 0.0251 6.5765 0.0103 ADAMTS1 hCV529706 All Patients Fatal
Coronary Heart Disease 7.4845 0.0237 7.1633 0.0074 ADAMTS1
hCV529706 All Patients Total Mortality 12.4705 0.002 12.0029 0.0005
ADAMTS1 hCV529706 All Patients Cardiovascular Mortality 10.455
0.0054 9.947 0.0016 ADAMTS1 hCV529706 All Patients Fatal
Atherosclerotic Cardiovascular Disease 10.455 0.0054 9.947 0.0016
ANXA9 hCV8022252 All Patients Hosp. for Unstable Angina 8.1528
0.017 4.6114 0.0318 ANXA9 hCV8022252 All Patients CARE MI: Non
Q-Wave MI 10.3373 0.0057 9.0759 0.0026 APOA4 hCV11482766 All
Patients Fatal/Non-fatal Cerebrovascular Disease 7.0664 0.0292
6.169 0.013 APOA4 hCV11482766 All Patients Any Report of Stroke
During CARE 9.6951 0.0078 7.46 0.0063 APOA4 hCV11482766 All
Patients 1st Stroke Occurred During CARE 11.7036 0.0029 9.2108
0.0024 APOC3 hCV8907537 All Patients Fatal/Non-fatal
Cerebrovascular Disease 13.3844 0.0012 9.6921 0.0019 APOC3
hCV8907537 All Patients Fatal/Non-fatal Atherosclerotic CV Disease
7.2676 0.0264 4.0221 0.0449 APOC3 hCV8907537 All Patients History
of Percutaneous Transluminal Coronary Angioplasty 6.1599 0.046
5.9094 0.0151 APOC3 hCV8907537 All Patients Any Report of Stroke
Prior or During CARE 6.6883 0.0353 5.5134 0.0189 APOC3 hCV8907537
All Patients Any Report of Stroke During CARE 12.4845 0.0019 9.0194
0.0027 APOC3 hCV8907537 All Patients 1st Stroke Occurred During
CARE 15.0987 0.0005 10.5154 0.0012 APOE hCV3084793 All Patients
Fatal/Non-fatal Cerebrovascular Disease 6.5129 0.0385 5.792 0.0161
CASP1 hCV16276495 All Patients Fatal CHD/Definite Non-fatal MI
11.6894 0.0006 11.4335 0.0007 CASP1 hCV16276495 All Patients Fatal
Coronary Heart Disease 7.4141 0.0065 7.0957 0.0077 CASP1
hCV16276495 All Patients Non-fatal MI (def & prob) 7.3586
0.0067 7.2496 0.0071 CASP1 hCV16278495 All Patients Fatal/Non-fatal
MI (def & prob) 10.8754 0.001 10.672 0.0011 CASP1 hCV16276495
All Patients Cardiovascular Mortality 6.0571 0.0139 5.858 0.0155
CASP1 hCV16276495 All Patients Fatal Atherosclerotic Cardiovascular
Disease 6.0571 0.0139 5.858 0.0155 CCR5 hCV9698595 All Patients
Fatal CHD/Definite Non-fatal MI 9.0507 0.0108 4.5709 0.0325 CCR5
hCV9698595 All Patients Fatal Coronary Heart Disease 7.7729 0.0205
4.1219 0.0423 CCR5 hCV9698595 All Patients Fatal/Non-fatal MI (def
& prob) 7.255 0.0266 4.1925 0.0406 CCR5 hCV9698595 All Patients
More Than 1 Prior MI 7.4573 0.024 3.9966 0.0456 CCRL2 hCV25637308
All Patients Fatal CHD/Definite Non-fatal MI 9.2116 0.01 6.3488
0.0117 CCRL2 hCV25637309 All Patients Fatal CHD/Definite Non-fatal
MI 8.5218 0.0141 7.8587 0.0051 CCRL2 hCV25637309 All Patients
Fatal/Non-fatal MI (def & prob) 7.0061 0.0301 5.4247 0.0199
CD44 hCV25593221 All Patients Fatal/Non-fatal Cerebrovascular
Disease 6.5508 0.0105 5.9272 0.0149 CD44 hCV25593221 All Patients
Any Report of Stroke Prior to or During CARE 4.5325 0.0333 4.1751
0.041 CD44 hCV25593221 All Patients Any Report of Stroke During
CARE 5.5006 0.019 4.8895 0.027 CD44 hCV25593221 All Patients 1st
Stroke Occurred During CARE 6.9887 0.0082 6.0383 0.014 CHUK
hCV1345898 All Patients Hosp. for Unstable Angina 12.3061 0.0021
11.583 0.0007 CHUK hCV1345898 All Patients History of Coronary
Artery Bypass Graft 6.4389 0.04 5.8619 0.0155 CHUK hCV1345898 All
Patients Family History of CV Disease 6.7236 0.0347 6.0525 0.0139
COL6A2 hCV2811372 All Patients Non-fatal MI (def & prob) 7.6547
0.0218 6.8555 0.0088 COL6A2 hCV2811372 All Patients Fatal/Non-fatal
MI (def & prob) 7.0498 0.0295 6.1008 0.0135 COL6A2 hCV2811372
All Patients CARE MI: Non Q-Wave MI 6.441 0.0399 5.9297 0.0149 CTSB
hCV8339791 All Patients Fatal Coronary Heart Disease 7.8799 0.0194
6.4458 0.0111 CTSB hCV8339791 All Patients Cardiovascular Mortality
11.9462 0.0025 9.3211 0.0023 CTSB hCV8339791 All Patients Fatal
Atherosclerotic Cardiovascular Disease 11.9462 0.0025 9.3211 0.0023
CUBN hCV3135085 All Patients Congestive Heart Failure 6.8723 0.0322
6.4807 0.0109 CUBN hCV3135085 All Patients History of Diabetes
11.8699 0.0026 11.0773 0.0009 CUBN hCV3135085 All Patients Insulin
11.1304 0.0038 10.0331 0.0015 CX3CR1 hCV5687 All Patients Hosp. for
Cardiovascular Disease 15.5209 0.0004 13.3955 0.0003 CX3CR1 hCV5687
All Patients Hosp. for Unstable Angina 10.6459 0.0049 8.7005 0.0032
CX3CR1 hCV5687 All Patients Total Cardiovascular Disease Events
14.0718 0.0009 12.272 0.0005 CX3CR1 hCV5687 All Patients
Fatal/Non-fatal Atherosclerotic CV Disease 7.2089 0.0272 6.7757
0.0092 CX3CR1 hCV5687 All Patients CARE MI: Q-Wave MI 8.8335 0.0121
5.299 0.0213 CX3CR1 hCV7900503 All Patients Fatal CHD/Definite
Non-fatal MI 9.487 0.0087 8.1574 0.0043 CX3CR1 hCV7900503 All
Patients Non-fatal MI (def & prob) 11.6633 0.0029 7.2394 0.0071
CX3CR1 hCV7900503 All Patients Fata/Non-fatal MI (def & prob)
14.5731 0.0007 8.7401 0.0031 CX3CR1 hCV7900503 All Patients
Coronary Artery Bypass or Revascularization 6.8382 0.0327 4.3331
0.0374 CX3CR1 hCV7900503 All Patients Hosp. for Cardiovascular
Disease 12.0615 0.0024 9.2554 0.0023 CX3CR1 hCV7900503 All Patients
Hosp. for Unstable Angina 7.7014 0.0213 7.5098 0.0061 CX3CR1
hCV7900503 All Patients Total Coronary Heart Disease Events 11.1872
0.0037 6.8372 0.0089 CX3CR1 hCV7900503 All Patients Total
Cardiovascular Disease Events 11.9681 0.0025 8.402 0.0037 CX3CR1
hCV7900503 All Patients Fatal/Non.fatal Atherosclerotic CV Disease
11.1546 0.0038 6.4222 0.0113 DBH hCV12020339 All Patients Fatal
CHD/Definite Non-fatal MI 6.3707 0.0414 4.6865 0.0304 DBH
hCV12020339 All Patients Fatal Coronary Heart Disease 6.4202 0.0404
4.5927 0.0321 ELN hCV1253630 All Patients Fatal CHD/Definite
Non-fatal MI 7.0192 0.0299 5.8657 0.0154 ELN hCV1253630 All
Patients Non-fatal MI (def & prob) 6.4509 0.0397 6.2416 0.0125
F8 hCV11359098 All Patients CARE MI: Non Q-Wave MI 11.1257 0.0038
7.548 0.006 FGB hCV7429784 All Patients Cardiovascular Mortality
6.2697 0.0435 5.2663 0.0217 FGB hCV7429784 All Patients Fatal
Atherosclerotic Cardiovascular Disease 6.2697 0.0435 5.2663 0.0217
HDLBP hCV22274624 All Patients Hosp. for Unstable Angina 6.3052
0.0427 5.2308 0.0222 HFE hCV1085600 All Patients History of Angina
Pectoris 6.147 0.0463 5.3105 0.0212 HFE hCV1085600 All Patients
History of Diabetes 11.6431 0.003 6.3752 0.0116 HLA-DPA1
hCV15760070 All Patients Total Mortality 6.6793 0.0354 6.1772
0.0129 HLA-DPA1 hCV15760070 All Patients Coronary Artery Bypass or
Revascularization 9.3862 0.0092 7.003 0.0081 HLA-DPA1 hCV15760070
All Patients History of percutaneous Transluminal Coronary
Angioplasty 8.325 0.0156 7.753 0.0054 HLA-DPB1 hCV25651174 All
Patients Non-fatal MI (def & prob) 7.4596 0.024 6.8238 0.009
HLA-DPB1 hCV25651174 All Patients Coronary Artery Bypass or
Revascularization 9.7527 0.0076 6.5581 0.0104 HLA-DPB1 hCV25651174
All Patients Hosp. for Cardiovascular Disease 10.6608 0.0048 7.5713
0.0059 HLA-DPB1 hCV25651174 All Patients Total Coronary Heart
Disease Events 9.49 0.0087 9.0492 0.0026 HLA-DPB1 hCV25651174 All
Patients Total Cardiovascular Disease Events 7.7145 0.0211 6.0912
0.0136 HLA-DPB1 hCV25051174 All Patients Fatal/Non-fatal
Atherosclerotic CV Disease 9.2044 0.01 8.7506 0.0031 HLA-DPB1
hCV8851084 All Patients Total Coronary Heart Disease Events 8.5603
0.0138 7.9839 0.0047 HLA-DPB1 hCV8851084 All Patients
Fatal/Non-fatal Atherosclerotic CV Disease 7.3278 0.0256 6.5972
0.0102 HLA-DPB1 hCV8851085 All Patients Coronary Artery Bypass or
Revascularization 7.4082 0.0246 5.7094 0.0169 HLA-DPB1 hCV8851085
All Patients Hosp. for Cardiovascular Disease 7.6098 0.0223 7.2388
0.0071 HLA-DPB1 hCV8851085 All Patients Total Coronary Heart
Disease Events 8.0929 0.0175 7.7109 0.0055 HLA-DPB1 hCV8851085 All
Patients Total Cardiovascular Disease Events 6.441 0.0399 6.2467
0.0124 HLA-DPB1 hCV8851085 All Patients Fatal/Non-fatal
Atherosclerotic CV Disease 8.9261 0.0115 8.4377 0.0037 HSPG2
hCV1603656 All Patients Hosp. for Unstable Angina 7.3564 0.0253
5.9731 0.0145 HSPG2 hCV1603656 All Patients History of Angina
Pectoris 16.9406 0.0002 10.423 0.0012 HSPG2 hCV1603697 All Patients
Coronary Artery Bypass or Revascularization 6.4646 0.0395 4.1122
0.0426 HSPG2 hCV1603697 All Patients Hosp. for Unstable Angina
8.9933 0.0111 4.6813 0.0305 HSPG2 hCV1603697 All Patients History
of Angina Pectoris 11.8532 0.0027 6.1384 0.0132 HSPG2 hCV1603697
All Patients History of Stroke 6.362 0.0415 4.1405 0.0419 IGF1R
hCV8722981 All Patients Fatal CHD/Definite Non-fatal MI 12.0129
0.0025 8.8843 0.0029 IGF1R hCV8722981 All Patients Fatal Coronary
Heart Disease 11.536 0.0031 5.1641 0.0231 IGF1R hCV8722981 All
Patients Fatal/Non-fatal MI (def & prob) 7.2529 0.0266 4.8925
0.027 IGF1R hCV8722981 All Patients Cardiovascular Mortality
10.1906 0.0061 4.8293 0.028 IL1A hCV9546471 All Patients
Cardiovascular Mortality 6.9523 0.0309 5.6644 0.0173 IL1A
hCV9546471 All Patients Fatal Atherosclerotic Cardlovascular
Disease 6.9523 0.0309 5.6644 0.0173 IL1A hCV9546471 All Patients
History of Congestive Heart Failure (AE) 6.1271 0.0467 5.9334
0.0149 IL1B hCV9546517 All Patients Cardiovascular Mortality 6.6302
0.0363 6.0667 0.0138 IL1B hCV9546517 All Patients Fatal
Atherosclerotic Cardiovascular Disease 6.6302 0.0363 6.0667 0.0138
IL4R hCV2769554 All Patients Fatal CHD/Definite Non-fatal MI
10.0029 0.0067 6.8027 0.0091 IL4R hCV2769554 All Patients
Fatal/Non-fatal MI (def & prob) 8.0376 0.018 7.0306 0.008 ITGAE
hCV22273204 All Patients Coronary Artery Bypass or
Revascutarization 7.2966 0.026 6.6147 0.0101 ITGAE hCV22273204 All
Patients Family History of CV Disease 7.7796 0.0204 7.012 0.0081
ITGB2 hCV1088055 All Patients Fatal/Non-fatal Cerebrovascular
Disease 6.3122 0.0426 4.9703 0.0258 KL hCV2983035 All Patients
Total Mortality 9.639 0.0081 8.3919 0.0038 LAMA2 hCV25990513 All
Patients Congestive Heart Failure 7.5478 0.023 4.4464 0.035 LAMB2
hCV25630499 All Patients Congestive Heart Faiture 10.1403 0.0063
6.2037 0.0127 LBP hCV25617571 All Patients Fatal CHD/Definite
Non-fatal MI 6.4704 0.0394 4.2567 0.0391 LBP hCV25617571 All
Patients Fatal Coronary Heart Disease 13.1539 0.0014 6.9038 0.0086
LBP hCV25617571 All Patients Total Mortality 7.0693 0.0292 4.4586
0.0347 LBP hCV25617571 All Patients Cardiovascular Mortality 9.7674
0.0076 4.7106 0.03 LBP hCV25617571 All Patients Fatal
Atherosclerotic Cardiovascular Disease 9.7674 0.0076 4.7106 0.03
LPA hCV25930271 All Patients Fatal/Non-fatal Cerebrovascular
Disease 6.1113 0.0134 5.7793 0.0162 LPA hCV25930271 All Patients
History of Stroke 10.3748 0.0013 8.9305 0.0028 LPA hCV25930271 All
Patients Any Report of Stroke Prior to or During CARE 8.1023 0.0044
7.5172 0.0061 LRP8 hCV190754 All Patients Hosp. for Unstable Angina
6.2202 0.0446 5.3814 0.0204 LRP8 hCV190754 All Patients History of
Coronary Artery Bypass Graft 15.2786 0.0005 14.3188 0.0002 LTA
hCV16172087 All Patients Coronary Artery Bypass or
Revascularization 6.3807 0.0412 5.0148 0.0251 MARCO hCV2126249 All
Patients Hosp. for Cardiovascular Disease 9.4031 0.0091 4.6978
0.0302 MARCO hCV2126249 All Patients Total Cardiovascular Disease
Events 9.8232 0.0074 4.9202 0.0265 MC1R hCV11951095 All Patients
Hosp. for Unstable Angina 7.4068 0.0246 5.6448 0.0175 MMP27
hCV1366366 All Patients History of Percutaneous Transluminal
Coronary Angioplasty 7.9408 0.0189 7.7188 0.0055 MSR1 hCV16172249
All Patients Fatal CHD/Definite Non-fatal MI 6.6741 0.0355 4.5804
0.0323 MSR1 hCV16172249 All Patients Fatal Coronary Heart Disease
13.1069 0.0014 7.1248 0.0076 MSR1 hCV16172249 All Patients
Cardiovascular Mortality 10.3616 0.0056 6.5501 0.0105 MSR1
hCV16172249 All Patients Fatal Atherosclerotic Cardiovascular
Disease 10.3616 0.0056 6.5501 0.0105 MTHFD1 hCV1376137 All Patients
Hosp. for Peripheral Arterial Disease 7.6444 0.0219 6.96 0.0083
MTHFR hCV1202883 All Patients Congestive Heart Failure 6.0848
0.0477 5.4632 0.0194 MYH11 hCV334226 All Patients Fatal
CHD/Definite Non-fatal MI 6.8287 0.0329 4.0068 0.0453 MYH11
hCV334226 All Patients Non-fatal MI (def & prob) 9.5875 0.0083
7.7575 0.0053 MYH11 hCV334226 All Patients Fatal/Non-fatal MI (def
& prob) 7.4812 0.0237 5.5795 0.0182 MYH11 hCV334226 All
Patients CARE MI: Q-Wave MI 10.088 0.0064 7.3943 0.0065 NOS2A
hCV11889257 All Patients Total Coronary Heart Disease Events 8.4422
0.0147 6.5846 0.0103 NOS2A hCV11889257 All Patients Fatal/Non-fatal
Atherosclerotic CV Disease 6.5972 0.0369 5.927 0.0149 NPC1
hCV25472673 All Patients Hosp. for Cardiovascular Disease 14.1028
0.0009 13.6581 0.0002 NPC1 hCV25472673 All Patients Total Coronary
Heart Disease Events 6.9104 0.0316 6.8509 0.0089 NPC1 hCV25472673
All Patients Total Cardiovascular Disease Events 13.7798 0.001
13.0217 0.0003 NPC1 hCV25472673 All Patients Fatal/Non-fatal
Atherrosclerotic CV Disease 9.3597 0.0093 9.2405 0.0024 P2RY4
hCV8815434 All Patients Fatal CHD/Definite Non-fatal MI 6.9422
0.0311 5.1647 0.023 P2RY4 hCV8815434 All Patients Fatal Coronary
Heart Disease 6.7934 0.0335 5.0538 0.0246 P2RY4 hCV8815434 All
Patients Cardiovascular Mortality 7.1799 0.0276 4.5705 0.0325 P2RY4
hCV8815434 All Patients Fatal Atherosclerotic Cardiovascular
Disease 7.1799 0.0276 4.5705 0.0325 PDGFRA hCV22271841 All Patients
Fatal CHD/Definite Non-fatal MI 16.9486 0.0002 13.3442 0.0003
PDGFRA hCV22271841 All Patients Non-fatal MI (def & prob)
11.957 0.0025 9.9467 0.0016 PDGFRA hCV22271841 All Patients
Fatal/Non-fatal MI (def & prob) 10.0356 0.0066 8.4264 0.0037
PEMT hCV7443062 All Patients Fatal/Non-fatal Atherosclerotic CV
Disease 6.0125 0.0495 5.466 0.0194 PLA2G4C hCV16196014 All Patients
Congestive Heart Failure 9.2587 0.0098 4.6217 0.0316 PLA2G7
hCV7582933 All Patients Fatal/Non-fatal Cerebrovascular Disease
20.7612 <.0001 18.7233 <.0001 PLA2G7 hCV7582933 All Patients
Any Report of Stroke Prior to or During CARE 7.7866 0.0204 5.2256
0.0223 PLA2G7 hCV7582933 All Patients Any Report of Stroke During
CARE 13.9046 0.001 10.3804 0.0013 PLA2G7 hCV7582933 All Patients
1st Stroke Occurred During CARE 18.5501 <.0001 13.9535 0.0002
PLAT hCV3212009 All Patients Hosp. for Cardiovascular Disease
6.4904 0.039 6.3891 0.0115 PLAT hCV3212009 All Patients Hosp. for
Unstable Angina 6.0758 0.0479 5.9512 0.0147 PLAT hCV3212009 All
Patients Total Coronary Heart Disease Events 7.506 0.0234 7.4548
0.0063 PLAT hCV3212009 All Patients Total Cardiovascular Disease
Events 6.7267 0.0346 6.675 0.0098 PLAT hCV3212009 All Patients
Fatal/Non-fatal Atherosclerotic CV Disease 8.814 0.0122 8.5038
0.0035 PLAT hCV3212009 All Patients CARE MI: Q-Wave MI 6.2617
0.0437 4.8823 0.0271 PLAU hCV16273460 All Patients Hosp. for
Peripheral Arterial Disease 7.0124 0.03 6.2128 0.0127 PLG
hCV25614474 All Patients Hosp. for Peripheral Arterial Disease
6.5529 0.0378 5.2289 0.0222 PON1 hCV2548962 All Patients History of
Stroke 7.762 0.0206 6.2747 0.0122 PON1 hCV2548962 All Patients Any
Report of stroke During CARE 18.3981 0.0001 15.8161 <.0001 PON1
hCV2548962 All Patients 1st Stroke Occurred During CARE 15.5223
0.0004 13.6541 0.0002 PRKCQ hCV15954277 All Patients Fatal
CHD/Definite Non-fatal MI 7.6114 0.0222 6.3909 0.0115 PRKCQ
hCV15954277 All Patients History of Percutaneous Transluminal
Coronary Angioplasty 7.1755 0.0277 6.1643 0.013 PROCR hCV25620145
All Patients Congestive Heart Failure 8.8085 0.0122 7.09 0.0078
PROCR hCV25620145 All Patients Hosp. for Peripheral Arterial
Disease 18.4984 <.0001 12.2481 0.0005 PROCR hCV25620145 All
Patients History of Congestive Heart Failure (AE) 7.8606 0.0196
3.8993 0.0483 PROCR hCV25620145 All Patients History of Diabetes
10.7224 0.0047 7.0162 0.0081 PROCR hCV25620145 All Patients More
Than 1 Prior MI 9.2085 0.01 7.533 0.0061 PROCR
hCV7499900 All Patients Hosp. for Peripheral Arterial Disease 8.569
0.0138 6.1406 0.0132 PROCR hCV7499900 All Patients More Than 1
Prior MI 6.3048 0.0427 5.2347 0.0221 PSMB9 hCV8849004 All Patients
Hosp. for Unstable Angina 6.1961 0.0451 4.8294 0.028 SCARF1
hCV25613493 All Patients Congestive Heart Failure 7.751 0.0207
7.3777 0.0066 SCARF1 hCV25613493 All Patients History of Stroke
10.3312 0.0057 7.0201 0.0081 SELL hCV16172571 All Patients
Congestive Heart Failure 10.7046 0.0047 9.2061 0.0024 SELL
hCV16172571 All Patients History of Angina Pectoris 6.4757 0.0392
4.5067 0.0338 SELL hCV25474627 All Patients Congestive Heart
Failure 10.9187 0.0043 9.3741 0.0022 SELL hCV25474627 All Patients
History of Angina Pectoris 6.1573 0.046 4.1763 0.041 SELP
hCV11975296 All Patients Coronary Artery Bypass or
Revascularization 7.9917 0.0184 5.884 0.0153 SERPINA1 hCV1260328
All Patients Fatal/Non-fatal Cerebrovascular Disease 8.1188 0.0173
7.4562 0.0063 SERPINA10 hCV15943710 All Patients Hosp. for
Peripheral Arterial Disease 6.8119 0.0091 5.6794 0.0172 SERPINA3
hCV2188895 All Patients Fatal Coronary Heart Disease 9.6621 0.008
8.2548 0.0041 SERPINA3 hCV2188895 All Patients Cardiovascular
Mortality 13.1924 0.0014 10.5191 0.0012 SERPINA3 hCV2188895 All
Patients Fatal Atherosclerotic Cardiovascular Disease 13.1924
0.0014 10.5191 0.0012 SERPINA3 hCV2188895 All Patients History of
Diabetes 7.4219 0.0245 7.0093 0.0081 SERPINA3 hCV2188895 All
Patients More Than 1 Prior MI 8.7112 0.0128 8.6032 0.0034 SERPINB2
hCV8931357 All Patients Fatal Coronary Heart Disease 6.1008 0.0473
5.8986 0.0152 SERPINB2 hCV8931357 All Patients 1st Stroke Occurred
During CARE 6.4019 0.0407 5.3677 0.0205 SMTN hCV25627634 All
Patients Falal/Non-fatal MI (def & prob) 6.1622 0.0459 4.8023
0.0284 SREBF2 hCV16170982 All Patients Non-fatal MI (def &
prob) 6.5833 0.0372 4.1648 0.0413 SREBF2 hCV16170982 All Patients
CARE Ml: Q-Wave MI 6.4495 0.0398 3.9908 0.0457 TAP1 hCV25630686 All
Patients Congestive Heart Failure 15.1025 0.0005 6.8656 0.0088
TGFB1 hCV8708473 All Patients Cardiovascular Mortality 6.3933
0.0409 5.0113 0.0252 TGFB1 hCV8708473 All Patients Fatal
Atherosclerotic Cardiovascular Disease 6.3933 0.0409 5.0113 0.0252
TGFB1 hCV8708473 All Patients More Than 1 Prior MI 10.1295 0.0063
8.4288 0.0037 TGFB1 hCV8708473 All Patients Any Report of Stroke
During CARE 8.1211 0.0172 6.0819 0.0137 TGFB1 hCV8708473 All
Patients 1st Stroke Occurred During CARE 8.5461 0.0139 6.7848
0.0092 THBD hCV2531431 All Patients Fatal CHD/Definite Non-fatal MI
10.6922 0.0048 8.0919 0.0044 THBD hCV2531431 All Patients Coronary
Artery Bypass or Revascularization 7.5952 0.0224 7.1945 0.0073 THBD
hCV2531431 All Patients History of Percutaneous Transluminal
Coronary Angioplasty 12.6379 0.0018 10.8371 0.001 THBS1 hCV16170900
All Patients Coronary Artery Bypass or Revascularization 11.2439
0.0036 8.8265 0.003 THBS1 hCV16170900 All Patients History of
Angina Pectoris 10.3425 0.0057 8.823 0.003 TIMP2 hCV1466546 All
Patients Fatal CHD/Definite Non-fatal MI 9.2264 0.0099 6.5997
0.0102 TIMP2 hCV1466546 All Patients Family History of CV Disease
6.153 0.0461 6.1285 0.0133 TLR5 hCV15871020 All Patients Coronary
Artery Bypass or Revascularization 8.072 0.0177 7.2739 0.007 TLR5
hCV15871020 All Patients Total Coronary Heart Disease Events 8.5656
0.0138 7.3782 0.0066 TLR5 hCV15871020 All Patients Total
Cardiovascular Disease Events 6.1316 0.0466 4.8612 0.0275 TLR5
hCV15871020 All Patients Fatal/Non-fatal Atherosclerotic CV Disease
7.0226 0.0299 6.2028 0.0128 TNF hCV7514879 All Patients Total
Mortality 8.8535 0.012 6.0624 0.0138 TNF hCV7514879 All Patients
Hosp. for Cardiovascular Disease 8.6699 0.0131 7.5339 0.0061 TNF
hCV7514879 All Patients Total Cardiovascular Disease Events 7.8468
0.0198 6.789 0.0092 TNF hCV7514879 All Patients CARE MI: Q-Wave MI
7.9203 0.0191 5.6008 0.018 TNFRSF10A hCV12102850 All Patients Total
Mortality 7.7139 0.0211 6.2178 0.0126 TNFRSF10A hCV12102850 All
Patients More Than 1 Prior MI 6.6427 0.0361 4.852 0.0276 TNFRSF10A
hCV12102850 All Patients Any Report of Stroke During CARE 10.989
0.0041 9.6137 0.0019 TNFRSF10A hCV12102850 All Patients 1st Stroke
Occurred During CARE 15.4596 0.0004 12.4232 0.0004 VWF hCV8921137
All Patients Fatal Coronary Heart Disease 10.8514 0.0044 8.2057
0.0042 VWF hCV8921137 All Patients Fatal/Non-fatal Cerebrovascular
Disease 7.2772 0.0263 4.3481 0.0371 VWF hCV8921137 All Patients
Cardiovascular Mortality 8.1772 0.0168 6.1886 0.0129 VWF hCV8921137
All Patients Fatal Atherosclerotic Cardiovascular Disease 8.1772
0.0168 6.1886 0.0129 WWOX hCV25654217 All Patients Fatal/Non-fatal
Cerebrovascular Disease 9.8699 0.0072 5.7737 0.0163 WWOX
hCV25654217 All Patients Any Report of Stroke Prior to or During
CARE 10.3168 0.0058 6.5212 0.0107 WWOX hCV25654217 All Patients Any
Report of Stroke During CARE 17.6324 0.0001 9.1628 0.0025 WWOX
hCV25654217 All Patients 1st Stroke Occurred During CARE 21.4279
<.0001 9.8532 0.0017 WWOX hCV57888 All Patients Total Coronary
Heart Disease Events 6.3913 0.0409 6.2902 0.0121 WWOX hCV57888 All
Patients Fatal/Non-fatal Atherosclerotic CV Disease 7.3501 0.0253
7.2682 0.007 ABCC6 hCV25620774 All Patients Definite Nonfatal MI
6.4478 0.0111 6.0215 0.0141 ABCC6 hCV25620774 All Patients Fatal
CHD/Definite Nonfatal MI 4.3789 0.0364 4.1898 0.0407 ABCC6
hCV25620774 All Patients CARE MI: Q-Wave MI 6.0048 0.0143 5.7616
0.0164 ABO hCV25610774 All Patients MI (Fatal/Nonfatal) 6.5033
0.0387 5.5359 0.0186 ABO hCV25610774 All Patients Fatal
CHD/Definite Nonfatal MI 6.6893 0.0353 4.3471 0.0371 ABO
hCV25610819 All Patients Fatal CHD/Definite Nonfatal MI 6.7297
0.0346 4.7025 0.0301 ADAMTS1 hCV529710 All Patients Fatal
CHD/Definite Nonfatal MI 7.5605 0.0228 6.7732 0.0093 ADAMTS1
hCV529710 All Patients Fatal Coronary Heart Disease 7.3045 0.0259
6.9927 0.0082 ADAMTS1 hCV529710 All Patients Total Mortality
12.1574 0.0023 11.7126 0.0006 ADAMTS1 hCV529710 All Patients
Cardiovascular Mortality 10.2172 0.006 9.7327 0.0018 ADAMTS1
hCV529710 All Patients Fatal Atherosclerotic Cardiovascular Disease
10.2172 0.006 9.7327 0.0018 ADAMTS1 hCV529710 All Patients History
of Diabetes 6.9684 0.0307 6.9003 0.0086 APOBEC1 hCV15757745 All
Patients Stroke 17.213 0.0002 15.295 <.0001 APOBEC1 hCV15757745
All Patients Percutaneous Transluminal Coronary Angioplasty 6.9765
0.0306 5.2376 0.0221 APOBEC1 hCV15757745 All Patients Hosp. for
Cardiovascular Disease 6.3026 0.0428 4.6198 0.0316 APOBEC1
hCV15757745 All Patients Fatal/Nonfatal Cerebrovascular Disease
11.5495 0.0031 11.1298 0.0008 APOBEC1 hCV15757745 All Patients
Hosp. for Unstable Angina 7.827 0.02 5.8787 0.0153 APOBEC1
hCV15757745 All Patients Total Cardiovascular Disease Events 6.2745
0.0434 4.9393 0.0263 APOBEC1 hCV15757745 All Patients Any Report of
Stroke Prior to or During CARE 17.6174 0.0001 13.6085 0.0002
APOBEC1 hCV15757745 All Patients Any Report of Stroke During CARE
14.6273 0.0007 13.0337 0.0003 APOBEC1 hCV15757745 All Patients 1st
Stroke Occurred During CARE 15.5685 0.0004 13.4449 0.0002 ASAH1
hCV2442143 All Patients MI (Fatal/Nonfatal) 6.5487 0.0378 6.0662
0.0138 ASAH1 hCV2442143 All Patients Definite Nonfatal MI 7.1575
0.0279 6.9682 0.0083 ASAH1 hCV2442143 All Patients Fatal
CHD/Definite Nonfatal MI 7.3794 0.025 7.0385 0.008 ASAH1 hCV2442143
All Patients Fatal/Nonfatal MI (def & prob) 6.1285 0.0467 5.639
0.0176 BAT2 hCV7514692 All Patients Fatal Coronary Heart Disease
7.3974 0.0248 6.1273 0.0133 BAT2 hCV7514692 All Patients
Cardiovascular Mortality 8.2365 0.0163 6.0975 0.0135 BAT2
hCV7514692 All Patients Fatal Atherosclerotic Cardiovascular
Disease 8.2365 0.0163 6.0975 0.0135 BAT2 hCV7514692 All Patients
History of Congestive Heart Failure (AE) 9.0538 0.0108 8.3932
0.0038 BCL2A1 hCV7509650 All Patients Nonfatal MI
(Probable/Definite) 6.0311 0.049 5.7126 0.0168 BCL2A1 hCV7509650
All Patients Nonfatal MI (def & prob) 7.9668 0.0186 7.7732
0.0053 CCL4 hCV12120554 All Patients Fatal CHD/Definite Nonfatal MI
5.9309 0.0149 5.884 0.0153 CCL4 hCV12120554 All Patients Fatal
Coronary Heart Disease 13.1864 0.0003 12.3436 0.0004 CCL4
hCV12120554 All Patients Total Mortality 9.1271 0.0025 8.8684
0.0029 CCL4 hCV12120554 All Patients Cardiovascular Mortality
13.9315 0.0002 13.0944 0.0003 CCL4 hCV12120554 All Patients Fatal
Atherosclerotic Cardiovascular Disease 13.9315 0.0002 13.0944
0.0003 CCL4 hCV12120554 All Patients Fatal/Nonfatal Atherosclerotic
CV Disease 4.0079 0.0453 4.0002 0.0455 CD22 hCV2531086 All Patients
Coronary Artery Bypass Graft 10.9893 0.0041 10.0168 0.0016 CD22
hCV2531086 All Patients Coronary Artery Bypsss or Revascularization
7.0879 0.0289 6.6326 0.01 CD22 hCV2531086 All Patients Hosp. for
Unstable Angina 7.0207 0.0299 6.4786 0.0109 CD6 hCV2553030 All
Patients Congestive Heart Failure 7.2236 0.027 4.9062 0.0268 CD6
hCV2553030 All Patients Hosp. for Peripheral Arterial Disease
7.4666 0.0239 6.4999 0.0108 CD6 hCV2553030 All Patients History of
Coronary Artery Bypass Graft 10.2377 0.006 10.0806 0.0015 CD6
hCV2553030 All Patients CARE MI: Non Q-Wave MI 6.7337 0.0345 5.7915
0.0161 CTSH hCV15882348 All Patients Percutaneous Transluminal
Coronary Angioplasty 7.1211 0.0284 5.6616 0.0173 CTSS hCV1789791
All Patients Fatal MI 8.2495 0.0162 4.7645 0.0291 CTSS hCV1789791
All Patients History of Percutaneous Transluminal Coronary
Angioplasty 6.4861 0.039 5.2065 0.0225 CYP4F2 hCV16179493 All
Patients Fatal Coronary Heart Disease 9.3585 0.0093 8.497 0.0036
CYP4F2 hCV16179493 All Patients Total Mortality 9.4509 0.0089
6.6827 0.0097 CYP4F2 hCV16179493 All Patients Congestive Heart
Failure 7.5512 0.0229 4.7724 0.0289 CYP4F2 hCV16179493 All Patients
Hosp. for Unstable Angina 8.1794 0.0167 3.8637 0.0493 CYP4F2
hCV16179493 All Patients Cardiovascular Mortality 9.0692 0.0107
8.0291 0.0046 CYP4F2 hCV16179493 All Patients Fatal Atherosclerotic
Cardiovascular Disease 9.0692 0.0107 8.0291 0.0046 DDEF1 hCV7686234
All Patients Fatal Coronary Heart Disease 9.6484 0.008 9.0687
0.0026 DDEF1 hCV7686234 All Patients History of Percutaneous
Transluminal Coronary Angioplasty 7.0086 0.0301 6.9582 0.0083 EDN3
hCV3223182 All Patients Congestive Heart Failure 9.3292 0.0094
8.0301 0.0046 FCGR2A hCV9077561 All Patients Fatal Coronary Heart
Disease 9.2868 0.0096 7.4361 0.0064 FCGR2A hCV9077561 All Patients
Total Mortality 8.9741 0.0113 8.4427 0.0037 FCGR2A hCV9077561 All
Patients Cardiovascular Mortality 10.1866 0.0061 8.823 0.003 FCGR2A
hCV9077561 All Patients Fatal Atherosclerotic Cardiovascular
Disease 10.1866 0.0061 8.823 0.003 IL12A hCV1403468 All Patients
Coronary Artery Bypass Graft 9.5881 0.0083 9.4081 0.0022 IL12A
hCV16053900 All Patients Stroke 6.215 0.0447 5.596 0.018 IL12A
hCV16053900 All Patients Catheterization 9.2674 0.0097 7.7503
0.0054 IL12A hCV16053900 All Patients Coronary Artery Bypass or
Revascularization 9.1727 0.0102 7.8217 0.0052 IL12A hCV16053900 All
Patients Total Coronary Heart Disease Events 5.9977 0.0498 5.7793
0.0162 IL12A hCV16053900 All Patients Fatal/Nonfatal
Atherosclerotic CV Disease 9.1922 0.0101 8.9378 0.0028 IL12A
hCV16053900 All Patients Any Report of Stroke During CARE 8.2797
0.0159 6.9438 0.0084 IL12A hCV16053900 All Patients 1st Stroke
Occurred During CARE 6.7045 0.035 5.7565 0.0164 IL1RL1 hCV25607108
All Patients Definite Nonfatal MI 11.894 0.0026 5.7708 0.0163
IL1RL1 hCV25607108 All Patients Fatal MI 7.5954 0.0224 5.9238
0.0149 IL1RL1 hCV25607108 All Patients Fatal CHD/Definite Nonfatal
MI 8.5336 0.014 6.7904 0.0092 IL1RL1 hCV25607108 All Patients Fatal
Coronary Heart Disease 6.188 0.0453 5.8909 0.0152 IL1RL1
hCV25607108 All Patients Total Mortality 7.1672 0.0278 6.9439
0.0084 IL1RL1 hCV25607108 All Patients Hosp. for Unstable Angina
9.0023 0.0111 8.4372 0.0037 IL1RL1 hCV25607108 All Patients
Cardiovascular Mortality 7.0779 0.029 6.7239 0.0095 IL1RL1
hCV25607108 All Patients Fatal Atherosclerotic Cardiovascular
Disease 7.0779 0.029 6.7239 0.0095 KIAA0329 hCV1662671 All Patients
Stroke 6.2709 0.0435 3.9375 0.0472 KIAA0329 hCV1662671 All Patients
Any Report of Stroke During CARE 6.5108 0.0386 4.0999 0.0429
KIAA0329 hCV25751017 All Patients MI (Fatal/Nonfatal) 9.5857 0.002
9.1277 0.0025 KIAA0329 hCV25751017 All Patients Nonfatal MI
(Probable/Definite) 9.3425 0.0022 8.8902 0.0029 KIAA0329
hCV25751017 All Patients Fatal CHD/Definite Nonfatal MI 6.6912
0.0097 6.4342 0.0112 KIAA0329 hCV25751017 All Patients Nonfatal MI
(def & prob) 7.0931 0.0077 6.8051 0.0091 KIAA0329 hCV25751017
All Patients Fatal/Nonfatal MI (def & prob) 9.8958 0.0017
9.4086 0.0022 KIAA0329 hCV25751017 All Patients History of Angina
Pectoris 5.8485 0.0156 5.6948 0.017 KIAA0329 hCV25751017 All
Patients History of Congestive Heart Failure (AE) 14.6298 0.0001
13.1769 0.0003 KIAA0329 hCV25751017 All Patients More Than 1 Prior
MI 9.2578 0.0023 8.8444 0.0029 KLK1 hCV8705506 All Patients
Congestive Heart Failure 8.9138 0.0116 7.7742 0.0053 KLK1
hCV8705506 All Patients More Than 1 Prior MI 11.8625 0.0027 7.535
0.0061 KLK14 hCV16044337 All Patients MI (Fatal/Nonfatal) 11.9595
0.0025 11.623 0.0007 KLK14 hCV16044337 All Patients Nonfatal MI
(Probable/Definite) 10.3731 0.0056 9.8772 0.0017 KLK14 hCV16044337
All Patients Definite Nonfatal MI 8.8701 0.0119 8.2722 0.004 KLK14
hCV16044337 All Patients Fatal MI 11.2134 0.0037 8.3119 0.0039
KLK14 hCV16044337 All Patients Coronary Artery Bypass Graft 6.4727
0.0393 6.2691 0.0123 KLK14 hCV16044337 All Patients Fatal
CHD/Definite Nonfatal MI 11.2734 0.0036 10.8986 0.001 KLK14
hCV16044337 All Patients Nonfatal MI (def & prob) 11.0705
0.0039 10.1263 0.0015 KLK14 hCV16044337 All Patients Fatal/Nonfatal
MI (del & prob) 12.3831 0.002 12.0168 0.0005 KLK14 hCV16044337
All Patients History of Diabetes 7.2874 0.0262 7.1207 0.0076 KLK14
hCV16044337 All Patients Family History of CV Disease 7.7839 0.0204
7.6659 0.0056 LAMA2 hCV1819516 All Patients Hosp. for Unstable
Angina 6.7501 0.0342 5.5114 0.0189 MARK3 hCV25926178 All Patients
MI (Fatal/Nonfatal) 8.101 0.0174 7.1106 0.0077 MARK3 hCV25926178
All Patients Nonfatal MI (Probable/Definite) 8.8132 0.0122 7.3651
0.0067 MARK3 hCV25926178 All Patients Definite Nonfatal MI 6.5601
0.0376 6.4606 0.011 MARK3 hCV25926178 All Patients Nonfatal MI (def
& prob) 9.5045 0.0086 8.4948 0.0036 MARK3 hCV25926178 All
Patients Fatal/Nonfatal MI (def & prob) 8.3633 0.0153 7.2345
0.0072 MARK3 hCV25926771 All Patients MI (Fatal/Nonfatal) 10.7762
0.001 10.5972 0.0011 MARK3 hCV25926771 All Patients Nonfatal MI
(Probable/Definite) 12.7866 0.0003 12.5077 0.0004 MARK3 hCV25926771
All Patients Definite Nonfatal MI 9.3959 0.0022 9.1721 0.0025 MARK3
hCV25926771 All Patients Fatal CHD/Definite Nonfatal MI 5.8825
0.0153 5.8181 0.0159 MARK3 hCV25926771 All Patients Nonfatal MI
(def & prob) 12.688 0.0004 12.3884 0.0004 MARK3 hCV25926771 All
Patients Fatal/Nonfatal MI (def & prob) 11.0905 0.0009 10.8977
0.001 MARK3 hCV25926771 All Patients 1st Stroke Occurred During
CARE 4.1518 0.0416 4.0187 0.045 MMP27 hCV7492597 All Patients
Percutaneous Transluminal Coronary Angioptasty 6.0292 0.0491 5.8699
0.0154 MMP27 hCV7492601 All Patients Percutaneous Transluminal
Coronary Angioptasty 8.7778 0.0124 8.6086 0.0033 MMP27 hCV7492601
All Patients Catheterization 8.8894 0.0117 7.5393 0.006 MMP27
hCV7492601 All Patients Total Mortality 6.5936 0.037 5.9846 0.0144
NUDT6 hCV25956925 All Patients History of Hypertension 9.7172
0.0078 8.9124 0.0028 PLAT hCV12108245 All Patients Coronary Artery
Bypass or Revacsularization 4.9189 0.0266 4.5384 0.0331 PON2
hCV8952817 All Patients CARE MI: Q-Wave MI 6.1557 0.0461 4.9557
0.026 PPOX hCV25922816 All Patients percutaneous Transluminal
Coronary Angioplasty 9.1866 0.0101 4.8253 0.028 PPOX hCV25922816
All Patients Coronary Artery Bypass or Revascularization 12.759
0.0017 7.4351 0.0064 PPOX hCV25922816 All Patients Hosp. for
Cardiovascular Disease 7.7482 0.0208 5.5017 0.019 PPOX hCV25922816
All Patients Hosp. for Unstable Angina 7.8955 0.0193 7.7455 0.0054
PPOX hCV25922816 All Patients Total Coronary Heart Disease Events
9.8483 0.0073 8.3457 0.0039 PPOX hCV25922816 All Patients Total
Cardiovascular Disease Events 8.7618 0.0125 6.6786 0.0098 PPOX
hCV25922816 All Patients Fatal/Nonfatal Atherosclerotic CV Disease
10.5783 0.005 7.0358 0.008 PRG1 hCV1842400 All Patients Fatal MI
11.4732 0.0032 6.2891 0.0121 PRG1 hCV1842400 All Patients Fatal
Coronary Heart Disease 8.8239 0.0121 7.7888 0.0053 PRG1 hCV1842400
All Patients Fatal/Nonfatal MI (def & prob) 6.2693 0.0435
3.8612 0.0494
PRG1 hCV1642400 All Patients Cardiovascular Mortality 6.555 0.0377
5.9856 0.0144 PRG1 hCV1842400 All Patients Fatal Atherosclerotic
Cardiovascular Disease 6.555 0.0377 5.9856 0.0144 PTGIS hCV2782570
All Patients Fatal/Nonfatal Cerebrovascular Disease 7.804 0.0202
6.0104 0.0142 PTGIS hCV2782570 All Patients Any Report of Stroke
Prior to or During CARE 7.068 0.0292 6.1437 0.0132 PTPN21
hCV16182835 All Patients Stroke 12.2467 0.0022 11.1265 0.0009
PTPN21 hCV16182835 All Patients Fatat/Nonfatal Cerebrovascular
Disease 6.7201 0.0347 5.5243 0.0188 PTPN21 hCV16182835 All Patients
Any Report of Stroke Prior to or During CARE 11.8249 0.0027 10.3066
0.0013 PTPN21 hCV16182835 All Patients Any Report of Stroke During
CARE 12.2355 0.0022 11.1265 0.0009 PTPN21 hCV16182835 All Patients
1st Stroke Occurred During CARE 12.1541 0.0023 11.0615 0.0009
PTPN21 hCV25942539 All Patients Stroke 9.372 0.0092 8.6113 0.0033
PTPN21 hCV25942539 All Patients Any Report of Stroke Prior to or
During CARE 9.804 0.0074 8.5121 0.0035 PTPN21 hCV25942539 All
Patients Any Report of Stroke During CARE 9.3606 0.0093 8.6114
0.0033 PTPN21 hCV25942539 All Patients 1st Stroke Occurred During
CARE 9.0284 0.011 8.367 0.0038 PTPRJ hCV25943544 All Patients
Stroke 8.0699 0.0177 4.9043 0.0268 PTPRJ hCV25943544 All Patients
Any Report of Stroke During CARE 12.2226 0.0022 6.4092 0.0114
SCARF1 hCV12114319 All Patients Percutaneous Transluminal Coronary
Angloplasty 6.3674 0.0414 5.0636 0.0244 SERPINA1 hCV25640505 All
Patients Coronary Artery Bypass Graft 6.8645 0.0323 6.6037 0.0102
SERPINA1 hCV25640505 All Patients Any Report of Stroke Prior to or
During CARE 6.1297 0.0467 4.7864 0.0287 SERPINB6 hCV16190893 All
Patients Fatal/Nonfatal Cerebrovascular Disease 10.0396 0.0066
3.9528 0.0468 SERPINB6 hCV16190893 All Patients Fatal/Nonfatal
Atherosclerotic CV Disease 7.2903 0.0261 5.6856 0.0171 SERPINB8
hCV3023236 All Patients MI (Fatal/Nonfatal) 9.4616 0.0088 6.3892
0.0115 SERPINB8 hCV3023236 All Patients Nonfatal MI
(Probable/Definite) 8.0517 0.0178 5.6357 0.0176 SERPINB8 hCV3023236
All Patients Nonfatal MI (def & prob) 7.7449 0.0208 5.3563
0.0206 SERPINB8 hCV3023236 All Patients Fatal/Nonfatal MI (def
& prob) 8.3387 0.0155 5.772 0.0163 SERPINB8 hCV3023236 All
Patients Fatal/Nonfatal Atherosclerotic CV Disease 6.6908 0.0352
4.0053 0.0454 SN hCV25623265 All Patients Percutaneous Transluminal
Coronary Angioplasty 7.1386 0.0282 5.7749 0.0163 SN hCV25623265 All
Patients Catheterization 14.4805 0.0007 12.4057 0.0004 SN
hCV25623265 All Patients Coronary Artery Bypass or
Revascularization 11.6208 0.003 9.3889 0.0022 SN hCV25623265 All
Patients Hosp. for Cardiovascular Disease 6.7526 0.0342 5.2835
0.0215 SN hCV25623265 All Patients Hosp. for Unstable Angina 7.1878
0.0275 6.7216 0.0095 SN hCV25623265 All Patients History of Stroke
8.5497 0.0139 6.7929 0.0092 SN hCV2992252 All Patients Coronary
Artery Bypass Graft 6.3825 0.0411 5.345 0.0208 SN hCV2992252 All
Patients Catheterization 9.4523 0.0089 7.3988 0.0065 SN hCV2992252
All Patients Coronary Artery Bypass or Revascularization 9.8313
0.0073 7.0387 0.008 SN hCV2992252 All Patients Hosp. for Unstable
Angina 6.0158 0.0494 5.3573 0.0206 SOAT2 hCV15962586 All Patients
Coronary Artery Bypass Graft 6.397 0.0408 5.9871 0.0144 SOAT2
hCV15962586 All Patients Total Mortality 6.4718 0.0393 5.1538
0.0232 SPARCL1 hCV8827241 All Patients MI (Fatal/Nonfatal) 10.1729
0.0062 6.3913 0.0115 SPARCL1 hCV8827241 All Patients Nonfatal MI
(Probable/Definite) 7.4988 0.0235 5.4507 0.0196 SPARCL1 hCV8827241
All Patients Nonfatal MI (def & prob) 9.0581 0.0108 6.0662
0.0138 SPARCL1 hCV8827241 All Patients Fatal/Nonfatal Mi (def &
prob) 9.436 0.0089 5.6592 0.0174 SPARCL1 hCV8827241 All Patients
Total Coronary Heart Disease Events 8.9684 0.0113 8.2806 0.004
SPARCL1 hCV8827241 All Patients Total Cardiovascular Disease Events
5.9975 0.0498 4.5295 0.0333 SPARCL1 hCV8827241 All Patients More
Than 1 Prior MI 7.4735 0.0238 5.1023 0.0239 SPATA7 hCV2485037 All
Patients Fatal/Nonfatal Cerebrovascular Disease 7.2724 0.0264
5.2324 0.0222 SPATA7 hCV2485037 All Patients History of
Percutaneous Transtluminal Coronary Angioplasty 6.9271 0.0313
5.2953 0.0214 SPATA7 hCV2485037 All Patients Any Report of Stroke
Prior to or During CARE 9.9552 0.0069 7.3899 0.0066 SPATA7
hCV2485037 All Patients Any Report of Stroke During CARE 9.8656
0.0072 6.823 0.009 SPATA7 hCV2485037 All Patients 1st Stroke
Occurred During CARE 7.4687 0.0239 5.2807 0.0216 TGFB1 hCV22272997
All Patients Total Mortality 7.5472 0.023 6.5204 0.0107 TGFB1
hCV22272997 All Patients Cardiovascular Mortality 7.8062 0.0202
6.1764 0.0129 TGFB1 hCV22272997 All Patients Fatal Atherosclerotic
Cardiovascular Disease 7.8062 0.0202 6.1764 0.0129 TGFB1
hCV22272997 All Patients More Than 1 Prior MI 8.2241 0.0164 7.272
0.007 TGOLN2 hCV25615626 All Patients Percutaneous Transluminal
Coronary Angioplasty 12.3407 0.0021 10.0079 0.0016 TGOLN2
hCV25615626 All Patients Coronary Artery Bypass or
Revascularization 8.9099 0.0116 8.6407 0.0033 TGOLN2 hCV25615626
All Patients Hosp. for Unstable Angina 7.1053 0.0286 5.8082 0.016
TGOLN2 hCV25615626 All Patients History of Angina Pectoris 7.2218
0.027 6.5235 0.0106 TGOLN2 hCV25615626 All Patients History of
Stroke 9.4434 0.0089 5.15 0.0232 TGOLN2 hCV25615626 All Patients
Any Report of Stroke Prior to or During CARE 7.8803 0.0194 5.2621
0.0218 TLR6 hCV25615376 All Patients Catheterization 5.1613 0.0231
4.9743 0.0257 TLR6 hCV25615376 All Patients CARE M1: Q-Wave MI
5.1695 0.023 4.9974 0.0254 TNFRSF10A hCV11852251 All Patients Any
Report of Stroke During CARE 10.8967 0.0043 9.2159 0.0024 TNFRSF10A
hCV11852251 All Patients 1st Stroke Occurred During CARE 15.0864
0.0005 12.0652 0.0005 TNFRSF10A hCV15852235 All Patients
Percutaneous Transluminal Coronary Angioplasty 11.2081 0.0037
10.0042 0.0016 TNFRSF10A hCV15852235 All Patients Total Coronary
Heart Disease Events 6.479 0.0392 6.0116 0.0142 TNFRSF10A
hCV15852235 All Patients Cardiovascular Mortality 6.169 0.0458
5.3279 0.021 TNFRSF10A hCV15852235 All Patients Fatal
Atherosclerotic Cardiovascular Disease 6.169 0.0458 5.3279 0.021
TNFRSF10A hCV15852235 All Patients History of Angina Pectoris
8.8876 0.0118 8.7922 0.003 TNFRSF10A hCV15852235 All Patients
Family History of CV Disease 10.6888 0.0048 10.3253 0.0013 VEGF
hCV1647371 All Patients Fatal CHD/Definite Nonfatal MI 9.3214
0.0095 8.6915 0.0032 VEGF hCV1647371 All Patients Fatal Coronary
Heart Disease 8.2873 0.0159 7.3006 0.0069 VEGF hCV1647371 All
Patients Coronary Artery Bypass or Revascularization 10.0627 0.0065
8.2097 0.0042 VEGF hCV1647371 All Patients Total Coronary Heart
Disease Events 12.4873 0.0019 11.905 0.0006 VEGF hCV1647371 All
Patients Cardiovascular Mortality 6.3554 0.0417 5.2451 0.022 VEGF
hCV1647371 All Patients Fatal Atherosclerotic Cardiovascular
Disease 6.3554 0.0417 5.2451 0.022 VEGF hCV1647371 All Patients
Fatal/Nonfatal Atherosclerotic CV Disease 8.0612 0.0178 7.7403
0.0054 VEGF hCV791476 All Patients Fatal Coronary Heart Disease
7.3992 0.0247 6.9861 0.0082 VEGF hCV791476 All Patients
Fatal/Nonfatal Cerebrovascular Disease 6.5892 0.0371 5.9563 0.0147
VEGF hCV791476 All Patients Cardiovascular Mortality 9.5492 0.0084
9.008 0.0027 VEGF hCV791476 All Patients Fatal Atherosclerotic
Cardiovascular Disease 9.5492 0.0084 9.008 0.0027 VWF hCV7481138
All Patients MI (Fatal/Nonfatal) 4.2053 0.0403 4.1504 0.0416 VWF
hCV7481138 All Patients Nonfatal MI (Probable/Definite) 5.9933
0.0144 5.8657 0.0154 VWF hCV7481138 All Patients Definite Nonfatal
MI 4.4518 0.0349 4.3509 0.037 VWF hCV7481138 All Patients Nonfatal
MI (def & prob) 6.0747 0.0137 5.9319 0.0149 VWF hCV7481138 All
Patients Fatal/Nonfatal MI (def & prob) 3.9465 0.047 3.898
0.0483 VWF hCV7481138 All Patients History of Diabetes 4.3405
0.0372 4.3128 0.0378 VWF hCV7481138 All Patients CARE M1: Non
Q-Wave MI 4.14 0.0419 4.047 0.0443 Placebo Patients Odds Ratio (95%
CI) n/total (%) 2 Rare Alleles vs. 0 1 Rare Allele vs. 0
Significance Public 0 Rare Alleles 1 Rare Alleles 2 Rare Alleles
Rare Alleles Rare Alleles level ACACB 34/989 (3.4%) 17/432 (3.9%)
5/43 (11.6%) 1.15 (0.62 to 2.05) 3.70 (1.22 to 9.23) p < 0.05
ACACB 216/989 (21.8%) 64/432 (14.8%) 6/43 (14.0%) 0.62 (0.48 to
0.84) 0.58 (0.22 to 1.30) p < 0.005 ACACB 201/989 (20.3%) 58/432
(13.4%) 3/43 (7.0%) 0.61 (0.44 to 0.83) 0.29 (0.07 to 0.82) p <
0.005 ACACB 430/989 (43.5%) 156/432 (36.1%) 14/43 (32.6%) 0.74
(0.58 to 0.93) 0.63 (0.32 to 1.18) p < 0.05 ACE 54/1454 (3.7%)
2/18 (11.1%) 1/2 (50.0%) 3.24 (0.51 to 11.78) 25.93 (1.02 to
660.87) p < 0.05 ACE 61/1454 (4.2%) 2/18 (11.1%) 1/2 (50.0%)
2.86 (0.45 to 10.34) 22.84 (0.90 to 581.53) p < 0.05 ACE 61/1454
(4.2%) 2/18 (11.1%) 1/2 (50.0%) 2.86 (0.45 to 10.34) 22.84 (0.90 to
581.53) p < 0.05 ADAMTS1 92/872 (10.6%) 78/511 (15.3%) 14/90
(15.6%) 1.53 (1.10 to 2.11) 1.56 (0.82 to 2.79) p < 0.05 ADAMTS1
24/872 (2.8%) 29/511 (5.7%) 4/90 (4.4%) 2.13 (1.23 to 3.72) 1.64
(0.48 to 4.38) p < 0.05 ADAMTS1 40/872 (4.6%) 48/511 (9.4%) 6/90
(6.7%) 2.16 (1.40 to 3.34) 1.49 (0.56 to 3.36) p < 0.005 ADAMTS1
26/872 (3.0%) 34/511 (6.7%) 4/90 (4.4%) 2.32 (1.38 to 3.94) 1.51
(0.44 to 4.00) p < 0.005 ADAMTS1 20/872 (3.0%) 34/511 (6.7%)
4/90 (4.4%) 2.32 (1.38 to 3.94) 1.51 (0.44 to 4.00) p < 0.005
ANXA9 179/1069 (16.4%) 75/353 (21.2%) 10/32 (31.3%) 1.37 (1.01 to
1.85) 2.31 (1.03 to 4.84) p < 0.05 ANXA9 93/1089 (8.5%) 31/352
(8.8%) 8/32 (25.0%) 1.03 (0.67 to 1.57) 3.57 (1.47 to 7.85) p <
0.005 APOA4 72/1106 (6.5%) 23/347 (6.6%) 5/25 (20.0%) 1.02 (0.62 to
1.63) 3.59 (1.17 to 9.17) p < 0.05 APOA4 43/1106 (3.9%) 12/347
(3.5%) 4/25 (16.0%) 0.89 (0.44 to 1.65) 4.71 (1.33 to 13.04) p <
0.05 APOA4 36/1106 (3.3%) 12/347 (3.5%) 4/25 (16.0%) 1.07 (0.53 to
2.01) 5.66 (1.59 to 15.83) p < 0.005 APOC3 75/1211 (6.2%) 21/255
(8.2%) 4/13 (30.8%) 1.36 (0.80 to 2.21) 6.73 (1.79 to 21.19) p <
0.005 APOC3 486/1211 (40.1%) 89/255 (34.9%) 9/13 (69.2%) 0.80 (0.60
to 1.06) 3.36 (1.09 to 12.44) p < 0.05 APOC3 375/1211 (31.0%)
99/255 (38.8%) 5/13 (38.5%) 1.42 (1.07 to 1.87) 1.39 (0.42 to 4.20)
p < 0.05 APOC3 71/1211 (5.9%) 16/255 (6.3%) 3/13 (23.1%) 1.08
(0.59 to 1.83) 4.82 (1.06 to 16.16) p < 0.05 APOC3 46/1211
(3.8%) 10/255 (3.9%) 3/13 (23.1%) 1.03 (0.49 to 1.99) 7.60 (1.66 to
25.83) p < 0.005 APOC3 39/1211 (3.2%) 10/255 (3.9%) 3/13 (23.1%)
1.23 (0.57 to 2.40) 9.02 (1.97 to 30.85) p < 0.005 APOE 70/1074
(6.5%) 24/368 (6.5%) 6/34 (17.6%) 1.00 (0.61 to 1.59) 3.07 (1.12 to
7.20) p < 0.05 CASP1 132/1187 (11.1%) 53/285 (18.6%) 0/0 (0.0%)
1.83 (1.28 to 2.58) p < 0.005 CASP1 38/1187 (3.2%) 19/285 (6.7%)
0/0 (0.0%) 2.16 (1.20 to 3.76) p < 0.05 CASP1 134/1187 (11.3%)
49/285 (17.2%) 0/0 (0.0%) 1.63 (1.13 to 2.32) p < 0.05 CASP1
148/1187 (12.5%) 57/285 (20.0%) 0/0 (0.0%) 1.76 (1.25 to 2.45) p
< 0.005 CASP1 44/1187 (3.7%) 20/285 (7.0%) 0/0 (0.0%) 1.96 (1.12
to 3.34) p < 0.05 CASP1 44/1187 (3.7%) 20/285 (7.0%) 0/0 (0.0%)
1.96 (1.12 to 3.34) p < 0.05 CCR5 177/1398 (12.7%) 5/61 (8.2%)
2/3 (66.7%) 0.62 (0.21 to 1.42) 13.79 (1.32 to 297.56) p < 0.05
CCR5 55/1398 (3.9%) 1/61 (1.6%) 1/3 (33.3%) 0.41 (0.02 to 1.90)
12.21 (0.56 to 129.27) p < 0.05 CCR5 195/1398 (13.9%) 7/61
(11.5%) 2/3 (66.7%) 0.80 (0.33 to 1.67) 12.34 (1.18 to 266.05) p
< 0.05 CCR5 205/1398 (14.7%) 12/61 (19.7%) 2/3 (66.7%) 1.43
(0.71 to 2.64) 11.62 (1.11 to 250.94) p < 0.05 CCRL2 151/1278
(11.8%) 29/184 (15.8%) 5/14 (35.7%) 1.40 (0.89 to 2.12) 4.15 (1.26
to 12.17) p < 0.05 CCRL2 75/531 (14.1%) 92/689 (13.4%) 17/244
(7.0%) 0.94 (0.68 to 1.30) 0.46 (0.26 to 0.77) p < 0.05 CCRL2
78/531 (14.7%) 100/689 (15.2%) 21/244 (8.6%) 1.04 (0.76 to 1.44)
0.55 (0.32 to 0.89) p < 0.05 CD44 94/1446 (6.5%) 6/34 (17.6%)
0/0 (0.0%) 3.08 (1.13 to 7.15) p < 0.05 CD44 85/1446 (5.9%) 5/34
(14.7%) 0/0 (0.0%) 2.76 (0.92 to 6.74) p < 0.05 CD44 55/1446
(3.8%) 4/34 (11.8%) 0/0 (0.0%) 3.37 (0.98 to 8.92) p < 0.05 CD44
48/1446 (3.3%) 4/34 (11.8%) 0/0 (0.0%) 3.88 (1.12 to 10.33) p <
0.05 CHUK 51/407 (12.5%) 136/724 (18.8%) 73/331 (22.1%) 1.62 (1.15
to 2.30) 1.98 (1.34 to 2.94) p < 0.005 CHUK 120/407 (31.0%)
176/724 (24.3%) 82/331 (24.8%) 0.72 (0.55 to 0.94) 0.73 (0.53 to
1.02) p < 0.05 CHUK 179/407 (44.0%) 305/724 (42.1%) 116/331
(35.0%) 0.93 (0.73 to 1.19) 0.69 (0.51 to 0.93) p < 0.05 COL6A2
54/372 (14.5%) 100/755 (13.2%) 29/352 (8.2%) 0.90 (0.63 to 1.29)
0.53 (0.33 to 0.85) p < 0.05 COL6A2 59/372 (15.9%) 112/755
(14.8%) 34/352 (9.7%) 0.92 (0.66 to 1.31) 0.57 (0.36 to 0.88) p
< 0.05 COL6A2 40/372 (10.8%) 72/754 (9.5%) 20/352 (5.7%) 0.88
(0.59 to 1.33) 0.50 (0.28 to 0.86) p < 0.05 CTSB 41/1107 (3.7%)
12/340 (3.5%) 4/29 (13.8%) 0.95 (0.47 to 1.78) 4.16 (1.19 to 11.34)
p < 0.05 CTSB 46/1107 (4.2%) 13/340 (3.8%) 5/29 (17.2%) 0.92
(0.47 to 1.67) 4.81 (1.56 to 12.23) p < 0.005 CTSB 46/1107
(4.2%) 13/340 (3.8%) 5/29 (17.2%) 0.92 (0.47 to 1.67) 4.81 (1.56 to
12.23) p < 0.005 CUBN 38/636 (6.0%) 52/629 (8.3%) 22/191 (11.5%)
1.42 (0.92 to 2.20) 2.05 (1.16 to 3.53) p < 0.05 CUBN 75/636
(11.8%) 100/629 (15.9%) 41/191 (21.5%) 1.41 (1.03 to 1.96) 2.05
(1.33 to 3.10) p < 0.005 CUBN 9/636 (1.4%) 19/629 (3.0%) 11/191
(5.8%) 2.17 (1.00 to 5.07) 4.26 (1.74 to 10.71) p < 0.005 CX3CR1
458/1000 (45.8%) 200/427 (46.8%) 31/40 (77.5%) 1.04 (0.83 to 1.31)
4.08 (2.00 to 9.18) p < 0.0005 CX3CR1 164/1000 (16.4%) 85/427
(19.9%) 14/40 (35.0%) 1.27 (0.95 to 1.69) 2.75 (1.37 to 5.29) p
< 0.005 CX3CR1 473/1000 (47.3%) 205/427 (48.0%) 31/40 (77.5%)
1.03 (0.82 to 1.29) 3.84 (1.88 to 8.64) p < 0.005 CX3CR1
389/1000 (38.9%) 167/427 (39.1%) 24/40 (60.0%) 1.01 (0.80 to 1.27)
2.36 (1.25 to 4.57) p < 0.05 CX3CR1 614/1000 (61.4%) 286/427
(67.0%) 32/40 (80.0%) 1.28 (1.01 to 1.62) 2.52 (1.20 to 5.91) p
< 0.05 CX3CR1 110/756 (14.6%) 57/606 (9.4%) 17/105 (16.2%) 0.61
(0.43 to 0.85) 1.14 (0.63 to 1.94) p < 0.005 CX3CR1 106/756
(14.0%) 56/606 (9.2%) 20/105 (19.0%) 0.62 (0.44 to 0.88) 1.44 (0.83
to 2.41) p < 0.05 CX3CR1 119/756 (15.7%) 62/606 (10.2%) 23/105
(21.9%) 0.61 (0.44 to 0.84) 1.50 (0.89 to 2.45) p < 0.005 CX3CR1
149/756 (19.7%) 107/606 (17.7%) 30/105 (28.6%) 0.87 (0.66 to 1.15)
1.63 (1.02 to 2.56) p < 0.05 CX3CR1 354/756 (46.8%) 270/606
(44.6%) 66/105 (62.9%) 0.91 (0.74 to 1.13) 1.92 (1.27 to 2.95) p
< 0.005 CX3CR1 125/756 (16.5%) 109/606 (18.0%) 29/105 (27.6%)
1.11 (0.83 to 1.47) 1.93 (1.19 to 3.05) p < 0.05 CX3CR1 267/756
(35.3%) 193/606 (31.8%) 51/105 (48.6%) 0.86 (0.68 to 1.07) 1.73
(1.15 to 2.61) p < 0.05 CX3CR1 367/756 (48.5%) 276/606 (45.5%)
67/105 (63.8%) 0.89 (0.72 to 1.10) 1.87 (1.23 to 2.87) p < 0.005
CX3CR1 304/756 (40.2%) 220/606 (36.3%) 56/105 (53.3%) 0.85 (0.68 to
1.06) 1.70 (1.13 to 2.57) p < 0.05 DBH 160/1261 (12.7%) 21/198
(10.6%) 4/11 (36.4%) 0.82 (0.49 to 1.29) 3.93 (1.02 to 13.17) p
< 0.05 DBH 49/1261 (3.9%) 6/198 (3.0%) 2/11 (18.2%) 0.77 (0.29
to 1.69) 5.50 (0.82 to 22.04) p < 0.05 ELN 77/507 (15.2%) 84/721
(11.7%) 21/241 (8.7%) 0.74 (0.53 to 1.03) 0.53 (0.31 to 0.87) p
< 0.05 ELN 73/507 (14.4%) 88/721 (12.2%) 19/241 (7.9%) 0.83
(0.59 to 1.16) 0.51 (0.29 to 0.85) p < 0.05 F8 109/1200 (9.1%)
19/263 (7.2%) 4/11 (36.4%) 0.78 (0.46 to 1.26) 5.72 (1.48 to 19.25)
p < 0.05 FGB 35/1006 (3.5%) 26/418 (6.2%) 3/40 (7.5%) 1.84 (1.08
to 3.09) 2.25 (0.53 to 6.63) p < 0.05 FGB 35/1006 (3.5%) 26/418
(6.2%) 3/40 (7.5%) 1.84 (1.08 to 3.09) 2.25 (0.53 to 6.63) p <
0.05 HDLBP 157/802 (19.6%) 91/545 (16.7%) 12/114 (10.5%) 0.82 (0.62
to 1.09) 0.48 (0.25 to 0.87) p < 0.05 HFE 199/1086 (18.3%)
85/355 (23.9%) 10/39 (25.6%) 1.40 (1.05 to 1.87) 1.54 (0.70 to
3.10) p < 0.05 HFE 166/1086 (15.3%) 40/355 (11.3%) 12/39 (30.8%)
0.70 (0.48 to 1.01) 2.46 (1.18 to 4.85) p < 0.05 HLA-DPA1 57/994
(5.7%) 29/429 (6.8%) 8/56 (14.3%) 1.19 (0.74 to 1.88) 2.74 (1.16 to
5.78) p < 0.05 HLA-DPA1 200/994 (20.1%) 86/429 (20.0%) 2/56
(3.6%) 1.00 (0.75 to 1.32) 0.15 (0.02 to 0.48) p < 0.05 HLA-DPA1
315/994 (31.7%) 135/429 (31.5%) 28/56 (50.0%) 0.99 (0.78 to 1.26)
2.16 (1.25 to 3.71) p < 0.05 HLA-DPB1 98/708 (13.8%) 78/632
(12.3%) 7/132 (5.3%) 0.88 (0.64 to 1.20) 0.35 (0.14 to 0.72) p <
0.05 HLA-DPB1 137/708 (19.4%) 137/632 (21.7%) 13/132 (9.8%) 1.15
(0.88 to 1.51) 0.46 (0.24 to 0.80) p < 0.05 HLA-DPB1 334/708
(47.2%) 314/632 (49.7%) 45/132 (34.1%) 1.11 (0.89 to 1.37) 0.58
(0.39 to 0.85) p < 0.05 HLA-DPB1 258/708 (36.4%) 225/632 (35.6%)
30/132 (22.7%) 0.96 (0.77 to 1.21) 0.51 (0.33 to 0.78) p < 0.005
HLA-DPB1 346/708 (48.9%) 318/632 (50.3%) 49/132 (37.1%) 1.06 (0.86
to 1.31) 0.62 (0.42 to 0.90) p <
0.05 HLA-DPB1 291/708 (41.1%) 255/632 (40.3%) 36/132 (27.3%) 0.97
(0.78 to 1.21) 0.54 (0.35 to 0.80) p < 0.005 HLA-DPB1 342/950
(36.0%) 161/465 (34.6%) 11/62 (17.7%) 0.94 (0.75 to 1.19) 0.38
(0.19 to 0.72) p < 0.005 HLA-DPB1 390/950 (41.1%) 178/465
(38.3%) 15/62 (24.2%) 0.89 (0.71 to 1.12) 0.46 (0.25 to 0.81) p
< 0.05 HLA-DPB1 174/894 (19.5%) 107/506 (21.1%) 6/76 (7.9%) 1.11
(0.85 to 1.45) 0.36 (0.14 to 0.77) p < 0.05 HLA-DPB1 428/894
(47.9%) 241/506 (47.6%) 24/76 (31.6%) 0.99 (0.80 to 1.23) 0.50
(0.30 to 0.82) p < 0.05 HLA-DPB1 321/894 (35.9%) 177/506 (35.0%)
15/76 (19.7%) 0.96 (0.76 to 1.21) 0.44 (0.24 to 0.76) p < 0.05
HLA-DPB1 441/894 (49.3%) 246/506 (48.6%) 26/76 (34.2%) 0.97 (0.78
to 1.21) 0.53 (0.32 to 0.87) p < 0.05 HLA-DPB1 367/894 (41.1%)
197/506 (38.9%) 18/76 (23.7%) 0.92 (0.73 to 1.14) 0.45 (0.25 to
0.75) p < 0.005 HSPG2 217/1246 (17.4%) 42/223 (18.8%) 5/10
(50.0%) 1.10 (0.76 to 1.57) 4.74 (1.31 to 17.18) p < 0.05 HSPG2
248/1246 (19.9%) 38/223 (17.0%) 7/10 (70.0%) 0.83 (0.56 to 1.19)
9.39 (2.59 to 43.80) p < 0.005 HSPG2 249/1313 (19.0%) 36/159
(22.6%) 3/5 (60.0%) 1.25 (0.83 to 1.84) 6.40 (1.06 to 48.85) p <
0.05 HSPG2 225/1313 (17.1%) 36/159 (22.6%) 3/5 (60.0%) 1.42 (0.94
to 2.09) 7.25 (1.20 to 55.30) p < 0.05 HSPG2 262/1313 (20.0%)
28/159 (17.6%) 4/5 (80.0%) 0.86 (0.55 to 1.30) 16.03 (2.36 to
314.38) p < 0.05 HSPG2 32/1313 (2.4%) 5/159 (3.1%) 1/5 (20.0%)
1.30 (0.44 to 3.11) 10.01 (0.50 to 70.04) p < 0.05 IGF1R
169/1418 (11.9%) 15/59 (25.4%) 1/2 (50.0%) 2.52 (1.33 to 4.53) 7.39
(0.29 to 187.30) p < 0.005 IGF1R 54/1418 (3.8%) 2/59 (3.4%) 1/2
(50.0%) 0.89 (0.14 to 2.95) 25.26 (0.99 to 643.88) p < 0.05
IGF1R 190/1418 (13.4%) 14/59 (23.7%) 1/2 (50.0%) 2.01 (1.05 to
3.64) 6.46 (0.26 to 163.75) p < 0.05 IGF1R 60/1418 (4.2%) 3/59
(5.1%) 1/2 (50.0%) 1.21 (0.29 to 3.41) 22.68 (0.89 to 576.45) p
< 0.05 IL1A 22/739 (3.0%) 33/584 (5.7%) 9/144 (6.3%) 1.95 (1.13
to 3.43) 2.17 (0.93 to 4.68) p < 0.05 IL1A 22/739 (3.0%) 33/584
(5.7%) 9/144 (6.3%) 1.95 (1.13 to 3.43) 2.17 (0.93 to 4.68) p <
0.05 IL1A 41/739 (5.5%) 39/584 (6.7%) 16/144 (11.1%) 1.22 (0.77 to
1.92) 2.13 (1.13 to 3.84) p < 0.05 IL1B 28/886 (3.2%) 30/504
(6.0%) 5/87 (5.7%) 1.94 (1.14 to 3.30) 1.87 (0.62 to 4.58) p <
0.05 IL1B 28/886 (3.2%) 30/504 (6.0%) 5/87 (5.7%) 1.94 (1.14 to
3.30) 1.87 (0.62 to 4.56) p < 0.05 IL4R 63/471 (13.4%) 99/691
(14.3%) 23/313 (7.3%) 1.08 (0.77 to 1.53) 0.51 (0.31 to 0.84) p
< 0.05 IL4R 73/471 (15.5%) 103/691 (14.9%) 28/313 (8.9%) 0.96
(0.69 to 1.33) 0.54 (0.33 to 0.84) p < 0.05 ITGAE 165/869
(19.0%) 94/502 (18.7%) 29/96 (30.2%) 0.98 (0.74 to 1.30) 1.85 (1.14
to 2.92) p < 0.05 ITGAE 339/869 (39.0%) 214/502 (42.6%) 51/96
(53.1%) 1.16 (0.93 to 1.45) 1.77 (1.16 to 2.71) p < 0.05 ITGB2
40/648 (6.2%) 39/645 (6.0%) 20/180 (11.1%) 0.98 (0.62 to 1.54) 1.90
(1.06 to 3.30) p < 0.05 KL 62/1079 (5.7%) 24/364 (6.6%) 6/31
(19.4%) 1.16 (0.70 to 1.86) 3.94 (1.42 to 9.37) p < 0.005 LAMA2
70/1058 (6.6%) 37/379 (9.8%) 6/38 (15.8%) 1.53 (1.00 to 2.30) 2.65
(0.97 to 6.13) p < 0.05 LAMB2 102/1351 (7.5%) 9/117 (7.7%) 2/4
(50.0%) 1.02 (0.47 to 1.97) 12.23 (1.46 to 102.87) p < 0.05 LBP
148/1262 (11.7%) 33/194 (17.0%) 3/11 (27.3%) 1.54 (1.01 to 2.30)
2.82 (0.61 to 9.88) p < 0.05 LBP 41/1262 (3.2%) 14/194 (7.2%)
2/11 (18.2%) 2.32 (1.20 to 4.23) 6.62 (0.99 to 26.71) p < 0.05
LBP 73/1262 (5.8%) 19/194 (9.8%) 2/11 (18.2%) 1.77 (1.02 to 2.94)
3.62 (0.55 to 14.37) p < 0.05 LBP 48/1262 (3.8%) 14/194 (7.2%)
2/11 (18.2%) 1.97 (1.03 to 3.55) 5.62 (0.84 to 22.56) p < 0.05
LBP 48/1262 (3.8%) 14/194 (7.2%) 2/11 (18.2%) 1.97 (1.03 to 3.55)
5.62 (0.84 to 22.56) p < 0.05 LPA 89/1393 (6.4%) 10/72 (13.9%)
0/0 (0.0%) 2.36 (1.11 to 4.57) p < 0.05 LPA 31/1393 (2.2%) 6/72
(8.3%) 0/0 (0.0%) 4.00 (1.46 to 9.28) p < 0.005 LPA 79/1393
(5.7%) 10/72 (13.9%) 0/0 (0.0%) 2.68 (1.25 to 5.22) p < 0.05
LRP8 83/557 (14.9%) 130/687 (18.9%) 51/235 (21.7%) 1.33 (0.99 to
1.81) 1.58 (1.07 to 2.33) p < 0.05 LRP8 120/557 (21.5%) 214/687
(31.1%) 57/235 (24.3%) 1.65 (1.27 to 2.14) 1.17 (0.81 to 1.67) p
< 0.0005 LTA 243/1259 (19.3%) 38/199 (19.1%) 4/7 (57.1%) 0.99
(0.67 to 1.43) 5.57 (1.22 to 28.45) p < 0.05 MARCO 601/1286
(46.7%) 85/161 (52.8%) 1/12 (8.3%) 1.28 (0.92 to 1.77) 0.10 (0.01
to 0.54) p < 0.05 MARCO 618/1286 (48.1%) 87/161 (54.0%) 1/12
(8.3%) 1.27 (0.92 to 1.77) 0.10 (0.01 to 0.51) p < 0.05 MC1R
232/1310 (17.7%) 28/161 (17.4%) 4/7 (57.1%) 0.98 (0.62 to 1.49)
6.19 (1.36 to 31.62) p < 0.05 MMP27 314/1006 (31.2%) 125/381
(32.8%) 38/82 (46.3%) 1.08 (0.84 to 1.38) 1.90 (1.20 to 3.00) p
< 0.05 MSR1 165/1304 (12.7%) 16/157 (10.2%) 3/7 (42.9%) 0.78
(0.44 to 1.31) 5.18 (1.01 to 23.68) p < 0.05 MSR1 52/1304 (4.0%)
3/157 (1.9%) 2/7 (28.6%) 0.47 (0.11 to 1.29) 9.63 (1.36 to 45.84) p
< 0.05 MSR1 57/1304 (4.4%) 5/157 (3.2%) 2/7 (28.6%) 0.72 (0.25
to 1.66) 8.75 (1.24 to 41.56) p < 0.05 MSR1 57/1304 (4.4%) 5/157
(3.2%) 2/7 (28.6%) 0.72 (0.25 to 1.66) 8.75 (1.24 to 41.56) p <
0.05 MTHFD1 6/443 (1.4%) 22/732 (3.0%) 14/291 (4.8%) 2.26 (0.97 to
6.17) 3.68 (1.46 to 10.50) p < 0.05 MTHFR 56/650 (8.6%) 52/667
(7.8%) 4/149 (2.7%) 0.90 (0.60 to 1.33) 0.29 (0.09 to 0.73) p <
0.05 MYH11 103/938 (11.0%) 71/485 (14.6%) 11/55 (20.0%) 1.39 (1.00
to 1.92) 2.03 (0.97 to 3.91) p < 0.05 MYH11 102/938 (10.9%)
68/485 (14.0%) 13/55 (23.6%) 1.34 (0.96 to 1.85) 2.54 (1.27 to
4.76) p < 0.05 MYH11 116/938 (12.4%) 76/485 (15.7%) 13/55
(23.6%) 1.32 (0.96 to 1.80) 2.19 (1.10 to 4.10) p < 0.05 MYH11
616/938 (65.7%) 293/485 (60.4%) 26/55 (47.3%) 0.80 (0.64 to 1.00)
0.47 (0.27 to 0.81) p < 0.05 NOS2A 340/980 (34.7%) 165/445
(37.1%) 9/53 (17.0%) 1.11 (0.88 to 1.40) 0.39 (0.17 to 0.76) p <
0.05 NOS2A 390/980 (39.8%) 181/445 (40.7%) 12/53 (22.6%) 1.04 (0.83
to 1.30) 0.44 (0.22 to 0.83) p < 0.05 NPC1 244/560 (43.6%)
323/697 (46.3%) 122/208 (58.7%) 1.12 (0.89 to 1.40) 1.84 (1.33 to
2.54) p < 0.0005 NPC1 180/560 (32.1%) 242/697 (34.7%) 88/208
(42.3%) 1.12 (0.89 to 1.42) 1.55 (1.12 to 2.15) p < 0.05 NPC1
254/560 (45.4%) 330/697 (47.3%) 125/208 (60.1%) 1.08 (0.87 to 1.35)
1.81 (1.32 to 2.51) p < 0.0005 NPC1 204/560 (36.4%) 274/697
(39.3%) 101/208 (48.6%) 1.13 (0.90 to 1.42) 1.65 (1.19 to 2.27) p
< 0.005 P2RY4 147/1231 (11.9%) 34/234 (14.5%) 4/11 (36.4%) 1.25
(0.83 to 1.85) 4.21 (1.09 to 14.13) p < 0.05 P2RY4 44/1231
(3.6%) 11/234 (4.7%) 2/11 (18.2%) 1.33 (0.64 to 2.52) 6.00 (0.90 to
24.13) p < 0.05 P2RY4 48/1231 (3.9%) 14/234 (6.0%) 2/11 (18.2%)
1.57 (0.82 to 2.82) 5.48 (0.82 to 21.98) p < 0.05 P2RY4 48/1231
(3.9%) 14/234 (6.0%) 2/11 (18.2%) 1.57 (0.82 to 2.82) 5.48 (0.82 to
21.98) p < 0.05 PDGFRA 140/1161 (12.1%) 36/288 (12.5%) 8/18
(44.4%) 1.04 (0.70 to 1.53) 5.83 (2.19 to 15.04) p < 0.0005
PDGFRA 138/1161 (11.9%) 37/288 (12.8%) 7/18 (38.9%) 1.09 (0.73 to
1.60) 4.72 (1.71 to 12.18) p < 0.005 PDGFRA 154/1161 (13.3%)
43/288 (14.9%) 7/18 (38.9%) 1.15 (0.79 to 1.64) 4.16 (1.51 to
10.73) p < 0.005 PEMT 193/462 (41.8%) 299/739 (40.5%) 91/275
(33.1%) 0.95 (0.75 to 1.20) 0.69 (0.50 to 0.94) p < 0.05 PLA2G4C
95/1334 (7.1%) 15/127 (11.8%) 2/6 (33.3%) 1.75 (0.95 to 3.03) 6.53
(0.90 to 33.85) p < 0.05 PLA2G7 42/834 (5.0%) 41/534 (7.7%)
17/101 (16.8%) 1.57 (1.00 to 2.45) 3.82 (2.04 to 6.90) p <
0.0005 PLA2G7 39/834 (4.7%) 41/534 (7.7%) 10/101 (9.9%) 1.70 (1.08
to 2.67) 2.24 (1.03 to 4.47) p < 0.05 PLA2G7 21/834 (2.5%)
29/534 (5.4%) 9/101 (8.9%) 2.22 (1.26 to 3.99) 3.79 (1.61 to 8.28)
p < 0.005 PLA2G7 16/834 (1.9%) 27/534 (5.1%) 9/101 (8.9%) 2.72
(1.47 to 5.21) 5.00 (2.07 to 11.43) p < 0.0005 PLAT 548/1125
(48.7%) 132/324 (40.7%) 10/20 (50.0%) 0.72 (0.56 to 0.93) 1.05
(0.43 to 2.59) p < 0.05 PLAT 216/1125 (19.2%) 43/324 (13.3%)
4/20 (20.0%) 0.64 (0.45 to 0.91) 1.05 (0.30 to 2.90) p < 0.05
PLAT 412/1125 (36.6%) 92/324 (28.4%) 7/20 (35.0%) 0.69 (0.52 to
0.90) 0.93 (0.35 to 2.29) p < 0.05 PLAT 564/1125 (50.1%) 136/324
(42.0%) 10/20 (50.0%) 0.72 (0.56 to 0.92) 1.00 (0.41 to 2.44) p
< 0.05 PLAT 466/1125 (41.4%) 105/324 (32.4%) 9/20 (45.0%) 0.68
(0.52 to 0.88) 1.16 (0.46 to 2.82) p < 0.005 PLAT 712/1125
(63.3%) 202/324 (62.3%) 18/20 (90.0%) 0.96 (0.75 to 1.24) 5.22
(1.50 to 32.94) p < 0.05 PLAU 22/888 (2.5%) 14/499 (2.8%) 6/78
(7.7%) 1.14 (0.56 to 2.22) 3.28 (1.18 to 7.88) p < 0.05 PLG
14/738 (1.9%) 22/622 (3.5%) 6/105 (5.7%) 1.90 (0.97 to 3.82) 3.13
(1.09 to 8.01) p < 0.05 PON1 28/753 (3.7%) 8/579 (1.4%) 2/133
(1.5%) 0.36 (0.15 to 0.77) 0.40 (0.06 to 1.34) p < 0.05 PON1
16/753 (2.1%) 39/579 (6.7%) 4/133 (3.0%) 3.33 (1.88 to 6.18) 1.43
(0.40 to 3.97) p < 0.0005 PON1 14/753 (1.9%) 34/579 (5.9%) 4/133
(3.0%) 3.29 (1.79 to 6.40) 1.64 (0.46 to 4.65) p < 0.0005 PRKCQ
114/817 (14.0%) 65/546 (11.9%) 5/106 (4.7%) 0.83 (0.60 to 1.15)
0.31 (0.11 to 0.69) p < 0.05 PRKCQ 248/817 (30.4%) 201/546
(36.8%) 30/106 (28.3%) 1.34 (1.06 to 1.68) 0.91 (0.57 to 1.40) p
< 0.05 PROCR 90/1206 (7.5%) 18/248 (7.3%) 4/14 (28.6%) 0.97
(0.56 to 1.60) 4.96 (1.34 to 15.16) p < 0.05 PROCR 30/1206
(2.5%) 9/248 (3.6%) 3/14 (21.4%) 1.48 (0.65 to 3.03) 10.69 (2.33 to
36.38) p < 0.005 PROCR 83/1206 (6.9%) 10/248 (4.0%) 3/14 (21.4%)
0.57 (0.27 to 1.06) 3.69 (0.82 to 12.09) p < 0.05 PROCR 181/1206
(15.0%) 29/248 (11.7%) 6/14 (42.9%) 0.75 (0.49 to 1.12) 4.25 (1.38
to 12.35) p < 0.05 PROCR 173/1206 (14.3%) 40/248 (16.1%) 6/14
(42.9%) 1.15 (0.78 to 1.66) 4.48 (1.46 to 13.03) p < 0.05 PROCR
30/1200 (2.5%) 9/248 (3.6%) 2/13 (15.4%) 1.47 (0.65 to 3.01) 7.09
(1.07 to 27.93) p < 0.05 PROCR 172/1200 (14.3%) 40/248 (16.1%)
5/13 (38.5%) 1.15 (0.78 to 1.66) 3.74 (1.12 to 11.33) p < 0.05
PSMB9 153/773 (19.8%) 99/595 (16.6%) 12/110 (10.9%) 0.81 (0.61 to
1.07) 0.50 (0.25 to 0.89) p < 0.05 SCARF1 94/1070 (8.8%) 16/369
(4.3%) 2/30 (6.7%) 0.47 (0.26 to 0.79) 0.74 (0.12 to 2.52) p <
0.05 SCARF1 21/1070 (2.0%) 14/369 (3.8%) 3/30 (10.0%) 1.97 (0.97 to
3.88) 5.55 (1.26 to 17.38) p < 0.05 SELL 78/1074 (7.3%) 27/362
(7.5%) 7/30 (23.3%) 1.03 (0.64 to 1.60) 3.89 (1.50 to 8.91) p <
0.005 SELL 197/1074 (18.3%) 85/362 (23.5%) 9/30 (30.0%) 1.37 (1.02
to 1.82) 1.91 (0.82 to 4.11) p < 0.05 SELL 77/1073 (7.2%) 27/365
(7.4%) 7/30 (23.3%) 1.03 (0.65 to 1.61) 3.94 (1.52 to 9.03) p <
0.005 SELL 197/1073 (18.4%) 85/365 (23.3%) 9/30 (30.0%) 1.35 (1.01
to 1.80) 1.91 (0.82 to 4.10) p < 0.05 SELP 205/996 (20.6%)
78/422 (18.5%) 2/47 (4.3%) 0.88 (0.65 to 1.17) 0.17 (0.03 to 0.56)
p < 0.05 SERPINA1 53/915 (5.8%) 36/486 (7.4%) 11/79 (13.9%) 1.30
(0.83 to 2.01) 2.63 (1.25 to 5.10) p < 0.05 SERPINA10 39/1451
(2.7%) 3/27 (11.1%) 0/0 (0.0%) 4.53 (1.05 to 13.67) p < 0.05
SERPINA3 24/407 (5.9%) 28/724 (3.9%) 5/338 (1.5%) 0.64 (0.37 to
1.13) 0.24 (0.08 t0 0.59) p < 0.005 SERPINA3 28/407 (6.9%)
30/724 (4.1%) 5/338 (1.5%) 0.59 (0.34 to 1.00) 0.20 (0.07 to 0.49)
p < 0.005 SERPINA3 28/407 (6.9%) 30/724 (4.1%) 5/338 (1.5%) 0.59
(0.34 to 1.00) 0.20 (0.07 to 0.49) p < 0.005 SERPINA3 70/407
(17.2%) 112/724 (15.5%) 35/338 (10.4%) 0.88 (0.64 to 1.23) 0.56
(0.36 to 0.85) p < 0.05 SERPINA3 77/407 (18.9%) 90/724 (12.4%)
50/338 (14.8%) 0.61 (0.44 to 0.85) 0.74 (0.50 to 1.10) p < 0.005
SERPINB2 26/893 (2.9%) 28/503 (5.6%) 3/70 (4.3%) 1.97 (1.14 to
3.41) 1.49 (0.35 to 4.38) p < 0.05 SERPINB2 23/893 (2.6%) 25/503
(5.0%) 4/70 (5.7%) 1.98 (1.11 to 3.54) 2.29 (0.66 to 6.18) p <
0.05 SMTN 70/617 (11.3%) 104/669 (15.5%) 30/178 (16.9%) 1.44 (1.04
to 2.00) 1.58 (0.98 to 2.50) p < 0.05 SREBF2 149/1263 (11.8%)
30/196 (15.3%) 3/8 (37.5%) 1.35 (0.87 to 2.04) 4.49 (0.91 to 18.47)
p < 0.05 SREBF2 797/1263 (63.1%) 132/196 (67.3%) 2/8 (25.0%)
1.21 (0.88 to 1.67) 0.20 (0.03 to 0.85) p < 0.05 TAP1 102/1379
(7.4%) 7/92 (7.6%) 2/3 (66.7%) 1.03 (0.42 to 2.14) 25.04 (2.38 to
541.07) p < 0.05 TGFB1 20/686 (2.9%) 34/629 (5.4%) 10/162 (6.2%)
1.90 (1.09 to 3.40) 2.19 (0.97 to 4.67) p < 0.05 TGFB1 20/686
(2.9%) 34/629 (5.4%) 10/162 (6.2%) 1.90 (1.09 to 3.40) 2.19 (0.97
to 4.67) p < 0.05 TGFB1 81/686 (11.8%) 110/629 (17.5%) 30/162
(18.5%) 1.58 (1.16 to 2.16) 1.70 (1.06 to 2.66) p < 0.005 TGFB1
24/686 (3.5%) 21/629 (3.3%) 13/162 (8.0%) 0.95 (0.52 to 1.73) 2.41
(1.17 to 4.76) p < 0.05 TGFB1 20/686 (2.9%) 19/629 (3.0%) 12/162
(7.4%) 1.04 (0.55 to 1.97) 2.66 (1.24 to 5.50) p < 0.05 THBD
113/1025 (11.0%) 58/394 (14.7%) 12/48 (25.0%) 1.39 (0.99 to 1.95)
2.69 (1.31 to 5.18) p < 0.005 THBD 180/1025 (17.6%) 94/394
(23.9%) 11/48 (22.9%) 1.47 (1.11 to 1.95) 1.40 (0.67 to 2.70) p
< 0.05 THBD 315/1025 (30.7%) 137/394 (34.8%) 26/48 (54.2%) 1.20
(0.94 to 1.54) 2.66 (1.49 to 4.81) p < 0.005 THBS1 217/1194
(18.2%) 67/254 (26.4%) 1/18 (5.6%) 1.61 (1.17 to 2.20) 0.27 (0.02
to 1.30) p < 0.005 THBS1 233/1194 (19.5%) 50/254 (19.7%) 9/18
(50.0%) 1.01 (0.71 to 1.41) 4.12 (1.59 to 10.68) p < 0.005 TIMP2
45/451 (10.0%) 109/715 (15.2%) 30/300 (10.0%) 1.62 (1.13 to 2.37)
1.00 (0.61 to 1.62) p < 0.05 TIMP2 168/451 (37.3%) 294/715
(41.1%) 139/300 (46.3%) 1.18 (0.92 to 1.50) 1.45 (1.08 to 1.96) p
< 0.05 TLR5 199/1070 (18.6%) 76/371 (20.5%) 12/31 (38.7%) 1.13
(0.54 to 1.51) 2.76 (1.29 to 5.72) p < 0.05 TLR5 360/1070
(33.6%) 136/371 (36.7%) 18/31 (58.1%) 1.14 (0.89 to 1.46) 2.73
(1.33 to 5.75) p < 0.05 TLR5 504/1070 (47.1%) 188/371 (50.7%)
21/31 (67.7%) 1.15 (0.91 to 1.46) 2.36 (1.13 to 5.27) p < 0.05
TLR5 411/1070 (38.4%) 152/371 (41.0%) 19/31 (61.3%) 1.11 (0.87 to
1.42) 2.54 (1.23 to 5.43) p < 0.05 TNF 56/1036 (5.4%) 33/411
(8.0%) 5/30 (16.7%) 1.53 (0.97 to 2.37) 3.50 (1.15 to 8.79) p <
0.05 TNF 483/1036 (46.6%) 188/411 (45.7%) 22/30 (73.3%) 0.97 (0.77
to 1.21) 3.15 (1.44 to 7.60) p < 0.05 TNF 498/1036 (48.1%)
193/411 (47.0%) 22/30 (73.3%) 0.96 (0.76 to 1.20) 2.97 (1.36 to
7.17) p < 0.05 TNF 673/1036 (65.0%) 248/411 (60.3%) 13/30
(43.3%) 0.82 (0.65 to 1.04) 0.41 (0.19 to 0.86) p < 0.05
TNFRSF10A 19/448 (4.2%) 57/710 (8.0%) 16/317 (5.0%) 1.97 (1.18 to
3.44) 1.20 (0.66 to 2.37) p < 0.05 TNFRSF10A 56/448 (12.5%)
123/710 (17.3%) 40/317 (12.6%) 1.47 (1.05 to 2.08) 1.01 (0.65 to
1.56) p < 0.05 TNFRSF10A 7/448 (1.6%) 33/710 (4.6%) 19/317
(6.0%) 3.07 (1.43 to 7.62) 4.02 (1.74 to 10.39) p < 0.005
TNFRSF10A 4/448 (0.9%) 29/710 (4.1%) 19/317 (6.0%) 4.73 (1.85 to
16.02) 7.08 (2.63 to 24.59) p < 0.0005 VWF 46/1351 (3.4%) 10/110
(9.1%) 1/7 (14.3%) 2.84 (1.32 to 5.57) 4.73 (0.25 to 28.47) p <
0.005 VWF 87/1351 (6.4%) 11/110 (10.0%) 2/7 (28.6%) 1.61 (0.79 to
3.00) 5.81 (0.82 to 27.39) p < 0.05 VWF 53/1351 (3.9%) 10/110
(9.1%) 1/7 (14.3%) 2.45 (1.14 to 4.76) 4.08 (0.21 to 24.49) p <
0.05 VWF 53/1351 (3.9%) 10/110 (9.1%) 1/7 (14.3%) 2.45 (1.14 to
4.76) 4.08 (0.21 to 24.49) p < 0.05 WWOX 89/1305 (6.8%) 8/167
(4.8%) 2/5 (40.0%) 0.69 (0.30 to 1.36) 9.11 (1.19 to 55.63) p <
0.05 WWOX 78/1305 (6.0%) 9/167 (5.4%) 2/5 (40.0%) 0.90 (0.41 to
1.73) 10.49 (1.37 to 64.15) p < 0.05 WWOX 51/1305 (3.9%) 5/167
(3.0%) 2/5 (40.0%) 0.76 (0.26 to 1.76) 16.39 (2.13 to 100.97) p
< 0.005 WWOX 46/1305 (3.5%) 3/167 (1.8%) 2/5 (40.0%) 0.50 (0.12
to 1.39) 18.25 (2.36 to 112.63) p < 0.005 WWOX 149/479 (31.1%)
253/718 (35.2%) 113/282 (40.1%) 1.21 (0.94 to 1.54) 1.48 (1.09 to
2.01) p < 0.05 WWOX 170/479 (35.5%) 286/718 (39.8%) 128/282
(45.4%) 1.20 (0.95 to 1.53) 1.51 (1.12 to 2.04) p < 0.05 ABCC6
128/1408 (9.1%) 9/44 (20.5%) 2.57 (1.14 to 5.25) p < 0.05 ABCC6
171/1408 (12.1%) 10/44 (22.7%) 2.13 (0.98 to 4.23) p < 0.05
ABCC6 895/1408 (63.6%) 20/44 (45.5%) 0.48 (0.26 to 0.87) p <
0.05 ABO 136/856 (15.9%) 62/545 (11.4%) 8/77 (10.4%) 0.61 (0.27 to
1.23) 0.68 (0.49 to 0.93) p < 0.05 ABO 120/856 (14.0%) 60/545
(11.0%) 4/77 (5.2%) 0.34 (0.10 to 0.83) 0.76 (0.54 to 1.05) p <
0.05 ABO 119/847 (14.0%) 61/542 (11.3%) 4/80 (5.0%) 0.32 (0.10 to
0.79) 0.78 (0.56 to 1.07) p < 0.05 ADAMTS1 92/873 (10.5%) 79/516
(15.3%) 14/90 (15.6%) 1.56 (0.82 to 2.80) 1.53 (1.11 to 2.12) p
< 0.05 ADAMTS1 24/873 (2.7%) 29/516 (5.6%) 4/90 (4.4%) 1.65
(0.48 to 4.38) 2.11 (1.21 to 3.69) p < 0.05 ADAMTS1 40/873
(4.6%) 48/516 (9.3%) 6/90 (6.7%) 1.49 (0.55 to 3.36) 2.14 (1.38 to
3.31) p < 0.005 ADAMTS1 26/873 (3.0%) 34/516 (6.6%) 4/90 (4.4%)
1.52 (0.44 to 4.00) 2.30 (1.37 to 3.91) p < 0.005 ADAMTS1 26/873
(3.0%) 34/516 (6.6%) 4/90 (4.4%) 1.52 (0.44 to 4.00) 2.30 (1.37 to
3.91) p < 0.005 ADAMTS1 112/873 (12.8%) 93/516 (18.0%) 13/90
(14.4%) 1.15 (0.59 to 2.07) 1.49 (1.11 to 2.01) p < 0.05 APOBEC1
32/1131 (2.8%) 25/318 (7.9%) 2/27 (7.4%) 2.75 (0.43 to 9.79) 2.93
(1.70 to 5.01) p < 0.0005 APOBEC1 126/1132 (11.1%) 30/319 (9.4%)
7/27 (25.9%) 2.80 (1.08 to 6.45) 0.83 (0.54 to 1.24) p < 0.05
APOBEC1 512/1132 (45.2%) 166/319 (52.0%) 16/27 (59.3%) 1.76 (0.82
to 3.94) 1.31
(1.02 to 1.69) p < 0.05 APOBEC1 63/1132 (5.6%) 35/319 (11.0%)
2/27 (7.4%) 1.36 (0.22 to 4.70) 2.09 (1.34 to 3.21) p < 0.005
APOBEC1 204/1132 (18.0%) 50/319 (15.7%) 10/27 (37.0%) 2.68 (1.17 to
5.84) 0.85 (0.60 to 1.18) p < 0.05 APOBEC1 527/1132 (46.6%)
171/319 (53.6%) 16/27 (59.3%) 1.67 (0.77 to 3.73) 1.33 (1.03 to
1.70) p < 0.05 APOBEC1 53/1132 (4.7%) 33/319 (10.3%) 4/27
(14.8%) 3.54 (1.01 to 9.61) 2.35 (1.48 to 3.68) p < 0.0005
APOBEC1 33/1132 (2.9%) 24/319 (7.5%) 2/27 (7.4%) 2.66 (0.42 to
9.47) 2.71 (1.56 to 4.64) p < 0.0005 APOBEC1 28/1132 (2.5%)
22/319 (6.9%) 2/27 (7.4%) 3.15 (0.49 to 11.33) 2.92 (1.63 to 5.17)
p < 0.0005 ASAH1 64/397 (16.1%) 108/735 (14.7%) 34/343 (9.9%)
0.57 (0.36 to 0.89) 0.90 (0.64 to 1.26) p < 0.05 ASAH1 47/397
(11.8%) 72/735 (9.8%) 21/343 (6.1%) 0.49 (0.28 to 0.82) 0.81 (0.55
to 1.20) p < 0.05 ASAH1 59/397 (14.9%) 96/735 (13.1%) 29/343
(8.5%) 0.53 (0.33 to 0.84) 0.86 (0.61 to 1.23) p < 0.05 ASAH1
63/397 (15.9%) 107/735 (14.6%) 34/343 (9.9%) 0.58 (0.37 to 0.90)
0.90 (0.65 to 1.27) p < 0.05 BAT2 28/796 (3.5%) 20/575 (3.5%)
9/101 (8.9%) 2.68 (1.16 to 5.66) 0.99 (0.54 to 1.76) p < 0.05
BAT2 33/796 (4.1%) 21/575 (3.7%) 10/101 (9.9%) 2.54 (1.15 to 5.15)
0.88 (0.49 to 1.52) p < 0.05 BAT2 33/796 (4.1%) 21/575 (3.7%)
10/101 (9.9%) 2.54 (1.15 to 5.15) 0.88 (0.49 to 1.52) p < 0.05
BAT2 42/796 (5.3%) 41/575 (7.1%) 13/101 (12.9%) 2.65 (1.32 to 5.01)
1.38 (0.88 to 2.15) p < 0.005 BCL2A1 122/807 (15.1%) 61/572
(10.7%) 11/95 (11.6%) 0.74 (0.36 to 1.36) 0.67 (0.48 to 0.93) p
< 0.05 BCL2A1 117/807 (14.5%) 54/572 (9.4%) 11/95 (11.6%) 0.77
(0.38 to 1.43) 0.61 (0.43 to 0.86) p < 0.05 CCL4 118/1059
(11.1%) 65/411 (15.8%) 1.50 (1.08 to 2.07) p < 0.05 CCL4 29/1059
(2.7%) 28/411 (6.8%) 2.60 (1.52 to 4.43) p < 0.0005 CCL4 55/1059
(5.2%) 39/411 (9.5%) 1.91 (1.24 to 2.92) p < 0.005 CCL4 33/1059
(3.1%) 31/411 (7.5%) 2.54 (1.53 to 4.20) p < 0.0005 CCL4 33/1059
(3.1%) 31/411 (7.5%) 2.54 (1.53 to 4.20) p < 0.0005 CCL4
401/1059 (37.9%) 179/411 (43.6%) 1.27 (1.00 to 1.59) p < 0.05
CD22 88/930 (9.5%) 50/496 (10.1%) 12/50 (24.0%) 3.02 (1.47 to 5.84)
1.07 (0.74 to 1.54) p < 0.005 CD22 175/930 (18.8%) 94/496
(19.0%) 17/50 (34.0%) 2.22 (1.19 to 4.03) 1.01 (0.76 to 1.33) p
< 0.05 CD22 162/930 (17.4%) 868/496 (17.3%) 16/50 (32.0%) 2.23
(1.17 to 4.08) 0.99 (0.74 to 1.32) p < 0.05 CD6 56/888 (6.3%)
47/512 (9.2%) 10/76 (13.2%) 2.25 (1.04 to 4.44) 1.50 (1.00 to 2.25)
p < 0.05 CD6 22/888 (2.5%) 14/512 (2.7%) 6/76 (7.9%) 3.37 (1.21
to 8.12) 1.11 (0.55 to 2.16) p < 0.05 CD6 210/888 (23.6%)
161/512 (31.4%) 19/76 (25.0%) 1.08 (0.61 to 1.82) 1.48 (1.16 to
1.89) p < 0.005 CD6 69/888 (7.8%) 51/512 (10.0%) 12/75 (16.0%)
2.26 (1.12 to 4.26) 1.31 (0.90 to 1.92) p < 0.05 CTSH 131/1186
(11.0%) 26/270 (9.6%) 6/21 (28.6%) 3.22 (1.13 to 8.08) 0.86 (0.54
to 1.32) p < 0.05 CTSS 5/606 (0.8%) 5/673 (0.7%) 6/196 (3.1%)
3.80 (1.13 to 13.30) 0.90 (0.25 to 3.25) p < 0.05 CTSS 176/606
(29.0%) 229/973 (34.0%) 74/196 (37.8%) 1.48 (1.05 to 2.07) 1.26
(0.99 to 1.60) p < 0.05 CYP4F2 39/720 (5.4%) 14/629 (2.2%) 4/125
(3.2%) 0.58 (0.17 to 1.47) 0.40 (0.21 to 0.72) p < 0.005 CYP4F2
60/720 (8.3%) 30/629 (4.8%) 4/125 (3.2%) 0.36 (0.11 to 0.90) 0.55
(0.35 to 0.86) p < 0.05 CYP4F2 68/720 (9.4%) 39/629 (6.2%) 5/125
(4.0%) 0.40 (0.14 to 0.92) 0.63 (0.42 to 0.95) p < 0.05 CYP4F2
138/720 (19.2%) 95/629 (15.1%) 31/125 (24.8%) 1.39 (0.88 to 2.15)
0.75 (0.56 to 1.00) p < 0.05 CYP4F2 43/720 (6.0%) 17/629 (2.7%)
4/125 (3.2%) 0.52 (0.15 to 1.31) 0.44 (0.24 to 0.76) p < 0.005
CYP4F2 43/720 (6.0%) 17/629 (2.7%) 4/125 (3.2%) 0.52 (0.15 to 1.31)
0.44 (0.24 to 0.76) p < 0.005 DDEF1 28/464 (6.0%) 18/727 (2.5%)
11/283 (3.9%) 0.63 (0.30 to 1.25) 0.40 (0.21 to 0.72) p < 0.005
DDEF1 172/464 (37.1%) 216/727 (29.7%) 91/283 (32.2%) 0.80 (0.59 to
1.10) 0.72 (0.56 to 0.92) p < 0.05 EDN3 39/435 (9.0%) 63/744
(8.5%) 10/294 (3.4%) 0.36 (0.17 to 0.70) 0.94 (0.62 to 1.44) p <
0.005 FCGR2A 23/363 (6.3%) 26/737 (3.5%) 8/377 (2.1%) 0.32 (0.13 to
0.70) 0.54 (0.30 to 0.97) p < 0.05 FCGR2A 33/363 (9.1%) 47/737
(6.4%) 14/377 (3.7%) 0.39 (0.20 to 0.72) 0.68 (0.43 to 1.09) p <
0.005 FCGR2A 25/363 (6.9%) 31/737 (4.2%) 8/377 (2.1%) 0.29 (0.12 to
0.63) 0.59 (0.35 to 1.03) p < 0.005 FCGR2A 25/363 (6.9%) 31/737
(4.2%) 8/377 (2.1%) 0.29 (0.12 to 0.63) 0.59 (0.35 to 1.03) p <
0.005 IL12A 91/1035 (8.8%) 55/381 (14.4%) 4/38 (10.5%) 1.22 (0.36
to 3.15) 1.75 (1.22 to 2.49) p < 0.005 IL12A 24/458 (5.2%)
30/717 (4.2%) 4/267 (1.5%) 0.28 (0.08 to 0.72) 0.79 (0.46 to 1.38)
p < 0.05 IL12A 75/459 (16.3%) 77/718 (10.7%) 28/267 (10.5%) 0.60
(0.37 to 0.94) 0.62 (0.44 to 0.87) p < 0.05 IL12A 109/459
(23.7%) 133/718 (18.5%) 40/267 (15.0%) 0.57 (0.38 to 0.84) 0.73
(0.55 to 0.97) p < 0.05 IL12A 171/459 (37.3%) 253/718 (35.2%)
76/267 (28.5%) 0.67 (0.48 to 0.93) 0.92 (0.72 to 1.17) p < 0.05
IL12A 196/459 (42.7%) 286/718 (39.8%) 84/267 (31.5%) 0.62 (0.45 to
0.84) 0.89 (0.70 to 1.13) p < 0.005 IL12A 25/459 (5.4%) 30/718
(4.2%) 3/267 (1.1%) 0.20 (0.05 to 0.57) 0.76 (0.44 to 1.31) p <
0.05 IL12A 22/459 (4.8%) 26/718 (3.6%) 3/267 (1.1%) 0.23 (0.05 to
0.66) 0.75 (0.42 to 1.34) p < 0.05 IL1RL1 53/564 (9.4%) 52/679
(7.7%) 36/235 (15.3%) 1.74 (1.10 to 2.74) 0.80 (0.54 to 1.19) p
< 0.05 IL1RL1 2/564 (0.4%) 8/679 (1.2%) 6/235 (2.6%) 7.36 (1.68
to 50.49) 3.35 (0.84 to 22.26) p < 0.05 IL1RL1 64/564 (11.3%)
78/679 (11.5%) 43/235 (18.3%) 1.75 (1.14 to 2.66) 1.01 (0.71 to
1.44) p < 0.05 IL1RL1 13/564 (2.3%) 34/679 (5.0%) 10/235 (4.3%)
1.88 (0.79 to 4.34) 2.23 (1.20 to 4.43) p < 0.05 IL1RL1 24/564
(4.3%) 54/679 (8.0%) 16/235 (6.8%) 1.64 (0.84 to 3.13) 1.94 (1.20
to 3.24) p < 0.05 IL1RL1 111/564 (19.7%) 127/679 (18.7%) 26/235
(11.1%) 0.51 (0.32 to 0.79) 0.94 (0.71 to 1.25) p < 0.005 IL1RL1
15/564 (2.7%) 39/679 (5.7%) 10/235 (4.3%) 1.63 (0.70 to 3.64) 2.23
(1.24 to 4.21) p < 0.05 IL1RL1 15/564 (2.7%) 39/679 (5.7%)
10/235 (4.3%) 1.63 (0.70 to 3.64) 2.23 (1.24 to 4.21) p < 0.05
KIAA0329 35/669 (5.2%) 21/620 (3.4%) 2/157 (1.3%) 0.23 (0.04 to
0.78) 0.64 (0.36 to 1.09) p < 0.05 KIAA0329 36/670 (5.4%) 19/620
(3.1%) 3/158 (1.9%) 0.34 (0.08 to 0.96) 0.56 (0.31 to 0.97) p <
0.05 KIAA0329 180/1365 (13.2%) 20/78 (25.6%) 2.27 (1.30 to 3.80) p
< 0.005 KIAA0329 169/1365 (12.4%) 19/78 (24.4%) 2.28 (1.30 to
3.85) p < 0.005 KIAA0329 162/1365 (11.9%) 17/78 (21.8%) 2.07
(1.15 to 3.55) p < 0.05 KIAA0329 159/1365 (11.6%) 17/78 (21.8%)
2.11 (1.17 to 3.63) p < 0.05 KIAA0329 178/1365 (13.0%) 20/78
(25.6%) 2.30 (1.32 to 3.85) p < 0.005 KIAA0329 266/1365 (19.5%)
24/78 (30.8%) 1.84 (1.10 to 2.99) p < 0.05 KIAA0329 79/1365
(5.8%) 13/78 (16.7%) 3.26 (1.66 to 5.98) p < 0.0005 KIAA0329
195/1365 (14.3%) 21/78 (26.9%) 2.21 (1.28 t0 3.67) p < 0.005
KLK1 44/660 (6.7%) 47/664 (7.1%) 21/155 (13.5%) 2.19 (1.24 to 3.77)
1.07 (0.70 to 1.64) p < 0.05 KLK1 97/660 (14.7%) 86/664 (13.0%)
37/155 (23.9%) 1.82 (1.18 to 2.77) 0.86 (0.63 to 1.18) p < 0.05
KLK14 81/685 (11.8%) 89/629 (14.1%) 35/156 (22.4%) 2.16 (1.37 to
3.33) 1.23 (0.89 to 1.70) p < 0.005 KLK14 79/685 (11.5%) 81/629
(12.9%) 33/156 (21.2%) 2.06 (1.30 to 3.20) 1.13 (0.81 to 1.58) p
< 0.005 KLK14 57/685 (8.3%) 58/629 (9.2%) 25/156 (16.0%) 2.10
(1.25 to 3.45) 1.12 (0.76 to 1.64) p < 0.005 KLK14 2/685 (0.3%)
9/629 (1.4%) 5/156 (3.2%) 11.31 (2.41 to 79.44) 4.96 (1.27 to
32.60) p < 0.005 KLK14 57/685 (8.3%) 79/629 (12.6%) 15/156
(9.6%) 1.17 (0.62 to 2.08) 1.58 (1.11 to 2.27) p < 0.05 KLK14
73/685 (10.7%) 79/629 (12.6%) 32/156 (20.5%) 2.16 (1.35 to 3.40)
1.20 (0.86 to 1.69) p < 0.005 KLK14 75/685 (10.9%) 74/629
(11.8%) 32/156 (20.5%) 2.10 (1.32 to 3.29) 1.08 (0.77 to 1.53) p
< 0.005 KLK14 80/685 (11.7%) 88/629 (14.0%) 35/156 (22.4%) 2.19
(1.39 to 3.38) 1.23 (0.89 to 1.70) p < 0.005 KLK14 91/685
(13.3%) 93/629 (14.8%) 34/156 (21.8%) 1.82 (1.16 to 2.80) 1.13
(0.83 to 1.55) p < 0.05 KLK14 294/685 (42.9%) 258/629 (41.0%)
48/156 (30.8%) 0.59 (0.40 to 0.85) 0.92 (0.74 to 1.15) p < 0.05
LAMA2 134/769 (17.4%) 98/588 (16.7%) 32/121 (26.4%) 1.70 (1.08 to
2.64) 0.95 (0.71 to 1.26) p < 0.05 MARK3 62/573 (10.8%) 104/646
(16.1%) 37/228 (16.2%) 1.60 (1.02 to 2.47) 1.58 (1.13 to 2.22) p
< 0.05 MARK3 57/573 (9.9%) 98/646 (15.2%) 36/228 (15.8%) 1.70
(1.08 to 2.65) 1.62 (1.15 to 2.30) p < 0.05 MARK3 41/573 (7.2%)
74/646 (11.5%) 22/228 (9.6%) 1.39 (0.79 to 2.36) 1.68 (1.13 to
2.52) p < 0.05 MARK3 52/573 (9.1%) 94/646 (14.6%) 33/228 (14.5%)
1.70 (1.06 to 2.69) 1.71 (1.20 to 2.46) p < 0.005 MARK3 61/573
(10.6%) 103/646 (15.9%) 37/228 (16.2%) 1.63 (1.04 to 2.52) 1.59
(1.14 to 2.24) p < 0.05 MARK3 58/566 (10.2%) 144/879 (16.4%)
1.72 (1.25 to 2.39) p < 0.005 MARK3 52/566 (9.2%) 138/879
(15.7%) 1.84 (1.32 to 2.60) p < 0.0005 MARK3 37/566 (6.5%)
100/879 (11.4%) 1.84 (1.25 to 2.75) p < 0.005 MARK3 56/566
(9.9%) 125/879 (14.2%) 1.51 (1.09 to 2.12) p < 0.05 MARK3 48/566
(8.5%) 130/879 (14.8%) 1.87 (1.33 to 2.68) p < 0.0005 MARK3
57/566 (10.1%) 143/879 (16.3%) 1.74 (1.26 to 2.42) p < 0.005
MARK3 13/566 (2.3%) 38/879 (4.3%) 1.92 (1.04 to 3.78) p < 0.05
MMP27 59/668 (8.8%) 84/645 (13.0%) 19/160 (11.9%) 1.39 (0.79 to
2.37) 1.55 (1.09 to 2.21) p < 0.05 MMP27 36/449 (8.0%) 81/715
(11.3%) 46/310 (14.8%) 2.00 (1.26 to 3.19) 1.47 (0.98 to 2.23) p
< 0.005 MMP27 47/449 (10.5%) 84/715 (11.7%) 54/310 (17.4%) 1.80
(1.18 to 2.76) 1.14 (0.78 to 1.67) p < 0.05 MMP27 38/449 (8.5%)
44/715 (6.2%) 12/310 (3.9%) 0.44 (0.21 to 0.82) 0.71 (0.45 to 1.12)
p < 0.05 NUDT6 317/785 (40.4%) 254/571 (44.5%) 65/118 (55.1%)
1.81 (1.23 to 2.68) 1.18 (0.95 to 1.47) p < 0.005 PLAT 280/1407
(19.9%) 5/60 (8.3%) 0.37 (0.13 to 0.84) p < 0.05 PON2 570/872
(65.4%) 322/524 (61.5%) 44/83 (53.0%) 0.60 (0.38 to 0.94) 0.84
(0.67 to 1.06) p < 0.05 PPOX 129/1264 (10.2%) 28/178 (15.7%) 2/5
(40.0%) 5.87 (0.77 to 35.70) 1.64 (1.04 to 2.52) p < 0.05 PPOX
231/1264 (18.3%) 48/178 (27.0%) 3/5 (66.0%) 6.70 (1.11 to 51.14)
1.65 (1.14 to 2.35) p < 0.05 PPOX 577/1264 (45.6%) 98/178
(55.1%) 4/5 (80.0%) 4.76 (0.70 to 93.24) 1.46 (1.06 to 2.00) p <
0.05 PPOX 211/1264 (16.7%) 45/178 (25.3%) 1/5 (20.0%) 1.25 (0.06 to
8.48) 1.69 (1.16 to 2.43) p < 0.05 PPOX 421/1264 (33.3%) 79/178
(44.4%) 3/5 (60.0%) 3.00 (0.50 to 22.87) 1.60 (1.16 to 2.19) p <
0.005 PPOX 593/1264 (46.9%) 102/178 (57.3%) 4/5 (80.0%) 4.53 (0.67
to 88.61) 1.52 (1.11 to 2.09) p < 0.05 PPOX 479/1264 (37.9%)
86/178 (48.3%) 4/5 (80.0%) 6.56 (0.97 to 128.35) 1.53 (1.12 to
2.10) p < 0.05 PRG1 11/1007 (1.1%) 2/415 (0.5%) 3/54 (5.6%) 5.33
(1.18 to 17.69) 0.44 (0.07 to 1.64) p < 0.05 PRG1 33/1007 (3.3%)
18/415 (4.3%) 6/54 (11.1%) 3.69 (1.34 to 8.66) 1.34 (0.73 to 2.38)
p < 0.05 PRG1 143/1007 (14.2%) 49/415 (11.8%) 13/54 (24.1%) 1.92
(0.97 to 3.57) 0.81 (0.57 to 1.14) p < 0.05 PRG1 39/1007 (3.9%)
19/415 (4.6%) 6/54 (11.1%) 3.10 (1.14 to 7.19) 1.19 (0.67 to 2.06)
p < 0.05 PRG1 39/1007 (3.9%) 19/415 (4.6%) 6/54 (11.1%) 3.10
(1.14 to 7.19) 1.19 (0.67 to 2.06) p < 0.05 PTGIS 51/558 (9.1%)
37/674 (5.5%) 12/238 (5.0%) 0.53 (0.26 to 0.98) 0.58 (0.37 to 0.89)
p < 0.05 PTGIS 46/588 (8.2%) 32/674 (4.7%) 12/238 (5.0%) 0.59
(0.29 to 1.10) 0.55 (0.35 to 0.88) p < 0.05 PTPN21 14/615 (2.3%)
31/671 (4.6%) 13/162 (8.0%) 3.75 (1.70 to 8.18) 2.08 (1.12 to 4.07)
p < 0.005 PTPN21 30/615 (4.9%) 51/673 (7.6%) 16/162 (9.9%) 2.14
(1.11 to 3.97) 1.60 (1.01 to 2.57) p < 0.05 PTPN21 24/615 (3.9%)
48/673 (7.1%) 17/162 (10.5%) 2.89 (1.49 to 5.49) 1.89 (1.16 to
3.17) p < 0.005 PTPN21 14/615 (2.3%) 31/673 (4.6%) 13/162 (8.0%)
3.75 (1.70 to 8.18) 2.07 (1.11 to 4.05) p < 0.005 PTPN21 12/615
(2.0%) 27/673 (4.0%) 12/162 (7.4%) 4.02 (1.75 to 9.22) 2.10 (1.08
to 4.34) p < 0.005 PTPN21 16/620 (2.6%) 31/671 (4.6%) 12/155
(7.7%) 3.17 (1.44 to 6.81) 1.83 (1.00 to 3.46) p < 0.005 PTPN21
26/620 (4.2%) 48/673 (7.1%) 16/155 (10.3%) 2.63 (1.35 to 4.99) 1.75
(1.08 to 2.90) p < 0.005 PTPN21 16/620 (2.6%) 31/673 (4.6%)
12/155 (7.7%) 3.17 (1.44 to 6.81) 1.82 (1.00 to 3.45) p < 0.005
PTPN21 14/620 (2.3%) 27/673 (4.0%) 11/155 (7.1%) 3.31 (1.44 to
7.42) 1.81 (0.95 to 3.58) p < 0.005 PTPRJ 15/455 (3.3%) 23/709
(3.2%) 21/307 (6.8%) 2.15 (1.10 to 4.32) 0.98 (0.51 to 1.94) p <
0.05 PTPRJ 15/455 (3.3%) 21/710 (3.0%) 23/308 (7.5%) 2.37 (1.23 to
4.71) 0.89 (0.46 to 1.78) p < 0.05 SCARF1 51/520 (9.8%) 70/694
(10.1%) 40/261 (15.3%) 1.66 (1.06 to 2.59) 1.03 (0.71 to 1.51) p
< 0.05 SERPINA1 86/705 (12.2%) 43/413 (10.4%) 18/277 (6.5%) 0.50
(0.29 to 0.83) 0.84 (0.56 to 1.23) p < 0.05 SERPINA1 48/705
(6.8%) 15/413 (3.6%) 21/277 (7.6%) 1.12 (0.65 to 1.89) 0.52 (0.28
to 0.91) p < 0.05 SERPINB6 53/732 (7.2%) 30/603 (5.0%) 17/138
(12.3%) 1.80 (0.98 to 3.15) 0.67 (0.42 to 1.06) p < 0.05
SERPINB6 286/732 (39.1%) 227/603 (37.6%) 69/138 (50.0%) 1.56 (1.08
to 2.25) 0.94 (0.75 to 1.18) p < 0.05 SERPINB8 91/515 (17.7%)
85/683 (12.4%) 30/277 (10.8%) 0.57 (0.36 to 0.87) 0.66 (0.48 to
0.91) p < 0.05 SERPINB8 85/515 (16.5%) 80/683 (11.7%) 29/277
(10.5%) 0.59 (0.37 to 0.92) 0.67 (0.48 to 0.93) p < 0.05
SERPINB8 80/515 (15.5%) 75/683 (11.0%) 27/277 (9.7%) 0.59 (0.36 to
0.92) 0.67 (0.48 to 0.94) p < 0.05 SERPINB8 89/515 (17.3%)
85/683 (12.4%) 30/277 (10.8%) 0.58 (0.37 to 0.90) 0.68 (0.49 to
0.94) p < 0.05 SERPINB8 214/515 (41.6%) 245/683 (35.9%) 121/277
(43.7%) 1.09 (0.81 to 1.47) 0.79 (0.62 to 1.00) p < 0.05 SN
57/396 (14.4%) 76/745 (10.2%) 29/337 (8.6%) 0.56 (0.35 to 0.89)
0.68 (0.47 to 0.98) p < 0.05 SN 71/396 (17.9%) 78/745 (10.5%)
36/337 (10.7%) 0.55 (0.35 to 0.84) 0.54 (0.38 to 0.76) p <
0.0005 SN 99/896 (25.0%) 135/745 (18.1%) 53/337 (15.7%) 0.56 (0.38
to 0.81) 0.66 (0.50 to 0.89) p < 0.005 SN 201/396 (50.8%)
325/745 (43.6%) 168/337 (49.9%) 0.96 (0.72 to 1.29) 0.75 (0.59 to
0.96) p < 0.05 SN 86/396 (21.7%) 129/745 (17.3%) 48/337 (14.2%)
0.60 (0.40 to 0.88) 0.75 (0.56 to 1.03) p < 0.05 SN 3/396 (0.8%)
27/745 (3.6%) 8/337 (2.4%) 3.19 (0.91 to 14.63) 4.93 (1.73 to
20.71) p < 0.05 SN 69/539 (12.8%) 62/710 (8.7%) 19/224 (8.5%)
0.63 (0.36 to 1.06) 0.65 (0.45 to 0.94) p < 0.05 SN 86/539
(16.0%) 76/710 (10.7%) 22/224 (9.8%) 0.57 (0.34 to 0.93) 0.63 (0.45
to 0.88) p < 0.05 SN 126/539 (23.4%) 126/710 (17.7%) 33/224
(14.7%) 0.57 (0.37 to 0.85) 0.71 (0.54 to 0.93) p < 0.05 SN
111/539 (20.6%) 122/710 (17.2%) 30/224 (13.4%) 0.60 (0.38 to 0.91)
0.80 (0.60 to 1.07) p < 0.05 SOAT2 98/1007 (9.7%) 45/430 (10.5%)
9/41 (22.0%) 2.61 (1.14 to 5.41) 1.08 (0.74 to 1.56) p < 0.05
SOAT2 75/1007 (7.4%) 18/430 (4.2%) 1/41 (2.4%) 0.31 (0.02 to 1.46)
0.54 (0.31 to 0.90) p < 0.05 SPARCL1 77/577 (13.3%) 82/675
(12.1%) 45/218 (20.6%) 1.69 (1.12 to 2.53) 0.90 (0.64 to 1.25) p
< 0.05 SPARCL1 71/577 (12.3%) 80/675 (11.9%) 41/218 (18.8%) 1.65
(1.08 to 2.50) 0.96 (0.68 to 1.35) p < 0.05 SPARCL1 67/577
(11.6%) 73/675 (10.8%) 40/218 (18.3%) 1.71 (1.11 to 2.61) 0.92
(0.65 to 1.31) p < 0.05 SPARCL1 77/577 (13.3%) 81/675 (12.0%)
44/218 (20.2%) 1.64 (1.09 to 2.46) 0.89 (0.63 to 1.24) p < 0.05
SPARCL1 188/577 (32.6%) 228/675 (33.8%) 95/218 (43.6%) 1.60 (1.16
to 2.20) 1.06 (0.83 to 1.34) p < 0.005 SPARCL1 274/577 (47.5%)
315/675 (46.7%) 122/218 (56.0%) 1.41 (1.03 to 1.93) 0.97 (0.77 to
1.21) p < 0.05 SPARCL1 96/577 (16.6%) 82/675 (12.1%) 40/218
(18.3%) 1.13 (0.74 to 1.68) 0.69 (0.50 to 0.95) p < 0.05 SPATA7
43/465 (9.2%) 44/725 (6.1%) 11/250 (4.4%) 0.45 (0.22 to 0.86) 0.63
(0.41 to 0.98) p < 0.05 SPATA7 171/465 (38.8%) 220/725 (30.3%)
72/250 (28.8%) 0.70 (0.50 to 0.97) 0.75 (0.59 to 0.96) p < 0.05
SPATA7 41/465 (8.8%) 40/725 (5.5%) 8/250 (3.2%) 0.34 (0.15 to 0.70)
0.60 (0.38 to 0.95) p < 0.05 SPATA7 29/465 (6.2%) 26/725 (3.6%)
4/250 (1.6%) 0.24 (0.07 to 0.63) 0.56 (0.32 to 0.96) p < 0.05
SPATA7 25/465 (5.4%) 23/725 (3.2%) 4/250 (1.6%) 0.29 (0.08 to 0.75)
0.58 (0.32 to 1.03) p < 0.05 TGFB1 22/538 (4.1%) 52/678 (7.7%)
20/254 (7.9%) 2.00 (1.07 to 3.75) 1.95 (1.18 to 3.31) p < 0.05
TGFB1 13/538 (2.4%) 36/678 (5.3%) 15/254 (5.9%) 2.53 (1.19 to 5.49)
2.26 (1.22 to 4.47) p < 0.05 TGFB1 13/538 (2.4%) 36/678 (5.3%)
15/254 (5.9%) 2.53 (1.19 to 5.49) 2.26 (1.22 to 4.47) p < 0.05
TGFB1 63/538 (11.7%) 109/678 (16.1%) 48/254 (18.9%) 1.76 (1.16 to
2.64) 1.44 (1.04 to 2.02) p < 0.05 TGOLN2 52/548 (9.5%) 68/676
(10.1%) 43/246 (17.5%) 2.02 (1.30 to 3.12) 1.07 (0.73 to 1.57) p
< 0.05 TGOLN2 93/548 (17.0%) 130/676 (19.2%) 64/246 (26.0%) 1.72
(1.20 to 2.47) 1.16 (0.87 to 1.57) p < 0.005 TGOLN2 80/548
(14.6%) 130/676 (19.2%) 53/246 (21.5%) 1.61 (1.09 to 2.36) 1.39
(1.03 to
1.89) p < 0.005 TGOLN2 99/548 (18.1%) 129/676 (19.1%) 64/246
(26.0%) 1.60 (1.11 to 2.28) 1.07 (0.80 to 1.43) p < 0.05 TGOLN2
22/548 (4.0%) 15/676 (2.2%) 1/246 (0.4%) 0.10 (0.01 to 0.47) 0.54
(0.27 to 1.05) p < 0.05 TGOLN2 45/548 (8.2%) 35/676 (5.2%) 9/246
(3.7%) 0.42 (0.19 to 0.84) 0.61 (0.38 to 0.96) p < 0.05 TLR6
172/1407 (12.2%) 14/64 (21.9%) 2.01 (1.05 to 3.62) p < 0.05 TLR6
880/1407 (62.5%) 49/64 (76.6%) 1.96 (1.11 to 3.64) p < 0.05
TNFRSF10A 7/453 (1.5%) 34/712 (4.8%) 18/309 (5.8%) 3.94 (1.69 to
10.24) 3.20 (1.49 to 7.92) p < 0.05 TNFRSF10A 4/453 (0.9%)
30/712 (4.2%) 18/309 (5.8%) 6.94 (2.56 to 24.21) 4.94 (1.93 to
16.71) p < 0.05 TNFRSF10A 106/1055 (10.0%) 45/378 (11.9%) 11/42
(26.2%) 3.18 (1.49 to 6.33) 1.21 (0.83 to 1.74) p < 0.05
TNFRSF10A 355/1055 (33.6%) 135/378 (35.7%) 22/42 (52.4%) 2.17 (1.17
to 4.06) 1.10 (0.86 to 1.40) p < 0.05 TNFRSF10A 43/1055 (4.1%)
15/378 (4.0%) 5/42 (11.9%) 3.18 (1.05 to 7.84) 0.97 (0.52 to 1.73)
p < 0.05 TNFRSF10A 43/1055 (4.1%) 15/378 (4.0%) 5/42 (11.9%)
3.18 (1.05 to 7.84) 0.97 (0.52 to 1.73) p < 0.05 TNFRSF10A
190/1055 (18.0%) 95/378 (25.1%) 8/42 (19.0%) 1.07 (0.46 to 2.24)
1.53 (1.15 to 2.02) p < 0.005 TNFRSF10A 405/1055 (38.4%) 181/378
(47.9%) 19/42 (45.2%) 1.33 (0.71 to 2.46) 1.47 (1.16 to 1.87) p
< 0.005 VEGF 103/673 (15.3%) 60/613 (9.8%) 18/164 (11.0%) 0.68
(0.39 to 1.14) 0.60 (0.43 to 0.84) p < 0.005 VEGF 37/673 (5.5%)
15/613 (2.4%) 5/164 (3.0%) 0.54 (0.18 to 1.28) 0.43 (0.23 to 0.78)
p < 0.05 VEGF 136/673 (20.2%) 130/613 (21.2%) 17/164 (10.4%)
0.46 (0.26 to 0.76) 1.06 (0.81 to 1.39) p < 0.005 VEGF 249/673
(37.0%) 219/613 (35.7%) 37/164 (22.6%) 0.50 (0.33 to 0.73) 0.95
(0.75 to 1.19) p < 0.005 VEGF 39/673 (5.8%) 19/613 (3.1%) 5/164
(3.0%) 0.51 (0.17 to 1.20) 0.52 (0.29 to 0.90) p < 0.05 VEGF
39/673 (5.8%) 19/613 (3.1%) 5/164 (3.0%) 0.51 (0.17 to 1.20) 0.52
(0.29 to 0.90) p < 0.05 VEGF 277/673 (41.2%) 246/613 (40.1%)
48/164 (29.3%) 0.59 (0.41 to 0.85) 0.96 (0.77 to 1.20) p < 0.05
VEGF 32/1030 (3.1%) 24/384 (6.3%) 1/34 (2.9%) 0.95 (0.05 to 4.61)
2.08 (1.20 to 3.57) p < 0.05 VEGF 68/1030 (6.4%) 26/384 (6.8%)
6/34 (17.6%) 3.13 (1.14 to 7.35) 1.06 (0.65 to 1.68) p < 0.05
VEGF 34/1030 (3.3%) 27/384 (7.0%) 2/34 (5.9%) 1.83 (0.29 to 6.39)
2.22 (1.31 to 3.72) p < 0.005 VEGF 34/1030 (3.3%) 27/384 (7.0%)
2/34 (5.9%) 1.83 (0.29 to 6.39) 2.22 (1.31 to 3.72) p < 0.005
VWF 178/1199 (14.8%) 28/277 (10.1%) 0.65 (0.42 to 0.97) p < 0.05
VWF 170/1199 (14.2%) 24/277 (8.7%) 0.57 (0.36 to 0.88) p < 0.05
VWF 123/1199 (10.3%) 17/277 (6.1%) 0.57 (0.33 to 0.94) p < 0.05
VWF 160/1199 (13.3%) 22/277 (7.9%) 0.56 (0.34 to 0.87) p < 0.05
VWF 176/1199 (14.7%) 28/277 (10.1%) 0.65 (0.42 to 0.98) p < 0.05
VWF 166/1199 (13.8%) 52/277 (18.8%) 1.44 (1.01 to 2.02) p < 0.05
VWF 116/1199 (9.7%) 16/276 (5.8%) 0.57 (0.32 to 0.96) p < 0.05
*Results of the Overall Score Test (chi-square test) for the
logistic regression model in which the qualitative phenotype is a
function of SNP genotype (based on placebo patients only).
**Results of the chi-square test of the SNP effect (based on the
logistic regression model for placebo patients only).
[0485]
13TABLE 7 Significant Associations Between SNP Genotypes and
Quantitative Phenotypes Overall SNP Effect F-Test F-Test Public
Marker Stratum Phenotype (at Baseline) statistic p-value statistic
p-value HDLBP hCV22274624 All Patients Ln(Triglycerides) 5.55 0.004
5.5479 0.004 HDLBP hCV22274624 All Patients VLDL 8 0.0004 7.9953
0.0004 HFE hCV1085600 All Patients Bilirubin, Total 3.93 0.0198
3.9303 0.0198 HFE hCV1085600 All Patients Hemoglobin (gms %) 7.36
0.0007 7.3625 0.0007 HFE hCV1085600 All Patients Mean Cell
Hemoglobin 15.49 <.0001 15.4903 <.0001 LAMA2 hCV25990513 All
Patients Left Ventricular Ejection Fraction (%) 6.95 0.001 6.9481
0.001 PLG hCV25614474 All Patients Systolic Blood Pressure (mmHg)
6.21 0.0021 6.2083 0.0021 MARK3 hCV25926178 All Patients Change
from Baseline in Urinary Glucose (at LOCF) 4.43 0.0121 4.4318
0.0121 MARK3 hCV25926178 All Patients Change from Baseline in
Urinary Glucose (at 5 Years) 6.31 0.0019 6.3069 0.0019 MARK3
hCV25926771 All Patients Change from Baseline in Urinary Glucose
(at LOCF) 5.76 0.0165 5.7578 0.0165 PON2 hCV8952817 All Patients
Baseline HDL 4.65 0.0097 4.6545 0.0097 SN hCV2992252 All Patients
Baseline Lymphocytes, Absolute (k/cumm) 5.24 0.0054 5.242 0.0054
SOAT2 hCV15962586 All Patients Baseline HDL 3.41 0.0335 3.4055
0.0335 SOAT2 hCV15962586 All Patients Baseline Ln(Triglycerides)
3.9 0.0204 3.9027 0.0204 SOAT2 hCV15962586 All Patients Baseline
3.82 0.0222 3.8167 0.0222 SOAT2 hCV15962586 All Patients Baseline
VLDL-Triglycerides 4.05 0.0175 4.0544 0.0175 Placebo Patients mean
(se)# (N) Significance Public 0 Rare Alleles 1 Rare Allele 2 Rare
Alleles level HDLBP 4.955 (0.014) (N = 802) 4.998 (0.016) (N = 545)
5.073 (0.036) (N = 114) p < 0.005 HDLBP 25.969 (0.564) (N = 802)
27.873 (0.685) (N = 544) 32.000 (1.497) (N = 114) p < 0.0005 HFE
0.479 (0.007) (N = 1083) 0.509 (0.013) (N = 354) 0.561 (0.039) (N =
39) p < 0.05 HFE 14.808 (0.035) (N = 1071) 15.040 (0.060) (N =
353) 15.213 (0.181) (N = 39) p < 0.005 HFE 30.398 (0.054) (N =
1071) 30.956 (0.093) (N = 353) 31.113 (0.281) (N = 39) p <
0.0005 LAMA2 53.735 (0.376) (N = 1058) 52.591 (0.628) (N = 379)
46.632 (1.984) (N = 38) p < 0.005 PLG 130.051 (0.671) (N = 738)
128.934 (0.731) (N = 622) 123.371 (1.780) (N = 105) p < 0.005
MARK3 0.053 (0.026) (N = 561) 0.101 (0.024) (N = 637) 0.196 (0.041)
(N = 224) p < 0.05 MARK3 0.069 (0.035) (N = 334) 0.064 (0.034)
(N = 350) 0.277 (0.054) (N = 141) p < 0.005 MARK3 0.050 (0.026)
(N = 556) 0.130 (0.021) (N = 864) p < 0.05 PON2 38.486 (0.304)
(N = 872) 39.530 (0.393) (N = 524) 41.122 (0.986) (N = 83) p <
0.05 SN 2.334 (0.033) (N = 532) 2.282 (0.029) (N = 704) 2.135
(0.052) (N = 218) p < 0.05 SOAT2 38.723 (0.283) (N = 1007)
39.362 (0.434) (N = 430) 42.191 (1.405) (N = 41) p < 0.05 SOAT2
4.995 (0.012) (N = 1007) 4.957 (0.019) (N = 430) 4.847 (0.060) (N =
41) P < 0.05 SOAT2 27.787 (0.504) (N = 1006) 25.888 (0.771) (N =
430) 22.561 (2.497) (N = 41) p < 0.05 SOAT2 125.268 (2.044) (N =
1004) 117.305 (3.123) (N = 430) 103.537 (10.114) (N = 41) p <
0.05 *Results of the Overall F-Test for the analysis of variance
model in which the quantitative phenotype is a function of SNP
genotype (based on placebo patients only). **Results of the F-test
of the SNP effect (based on the analysis of variance model for
placebo patients only). #Least squares estimates of the mean and
its standard error based on the analysis of variance model.
[0486]
14TABLE 8 Significant Interactions Between SNP Genotypes and
Pravastatin Efficacy Overall* Interaction Chi-Square Effect** 0
Rare Alleles 1 Rare Allele Test Chi-Square n/total (%) n/total (%)
Public Marker Stratum Phenotype statistic p-value statistic inter
pv Prava Placebo Prava Placebo ABCA1 hCV2741051 All patients
Fatal/Non-fatal Cerebrovascular Disease 19.4858 0.0016 7.5666
0.0227 51/730 (7.0%) 53/746 (7.1%) 18/651 (2.8%) 38/615 (6.2%)
ABCA1 hCV2741051 All Patients Any Report of Storke During CARE
20.2702 0.0011 8.3498 0.0154 27/730 (3.7%) 30/746 (4.0%) 5/651
(0.8%) 22/615 (3.6%) ABCA1 hCV2741051 All Patients 1st Stroke
Occurred During CARE 19.1074 0.0018 7.1772 0.0276 26/730 (3.6%)
27/746 (3.6%) 5/651 (0.8%) 18/615 (2.9%) AGTR1 hCV3187716 All
Patients Fatal CHD/Definite Non-fatal MI 17.2109 0.0041 7.5975
0.0224 63/769 (8.2%) 91/735 (12.4%) 72/625 (11.5%) 71/568 (12.1%)
AGTR1 hCV3187716 All Patients Hosp. for Unstable Angina 11.9501
0.0355 7.5586 0.0228 120/769 (15.6%) 126/735 (17.1%) 103/625
(16.5%) 106/588 (18.0%) AGTR1 hCV3187716 All Patients Total
Coronary Heart Disease 20.7576 0.0009 6.1362 0.0465 227/769 (29.5%)
252/735 (34.3%) 194/625 (31.0%) 208/588 (35.4%) Events CCL11
hCV7449808 All Patients Hosp. for Cardiovascular Disease 31.6672
<.0001 11.562 0.0031 423/1025 (41.3%) 483/1006 (48.0%) 176/448
(39.3%) 171/412 (41.5%) CCL11 hCV7449808 All Patients Total
Coronary Heart Disease Events 19.3552 0.0017 6.9384 0.0311 310/1025
(30.2%) 355/1006 (35.3%) 127/448 (28.3%) 132/412 (32.0%) CCL11
hCV7449808 All Patients Total Cardiovascular Disease Events 32.1314
<.0001 12.1479 0.0023 436/1025 (42.5%) 494/1006 (49.1%) 181/448
(40.4%) 179/412 (43.4%) CCL11 hCV7449808 All Patients
Fatal/Non-fatal Atherosclerotic CV 24.1297 0.0002 6.6941 0.0352
359/1025 (35.0%) 405/1006 (40.3%) 139/448 (31.0%) 146/412 (35.4%)
Disease CHUK hCV1345898 All Patients Non-fatal MI (def & prob)
19.6476 0.0015 7.1993 0.0273 47/413 (11.4%) 53/407 (13.0%) 69/734
(9.4%) 86/724 (11.9%) CHUK hCV1345898 All Patients Hosp. for
Unstable Angina 17.1525 0.0042 9.4908 0.0087 68/413 (16.5%) 51/407
(12.5%) 110/734 (15.0%) 136/724 (18.8%) CR1 hCV25598594 All
Patients Fatal CHD/Definite 15.4324 0.0015 5.4753 0.0193 139/1445
(9.6%) 173/1413 (12.2%) 1/72 (1.4%) 12/66 (18.2%) Non-fatal MI CR1
hCV25598594 All Patients Non-fatal MI (def & prob) 16.765
0.0008 5.4291 0.0198 132/1445 (9.1%) 170/1413 (12.0%) 2/72 (2.8%)
13/66 (19.7%) CR1 hCV25598594 All Patients Coronary Artery Bypass
or 22.1947 <.0001 5.6728 0.0172 212/1445 (14.7%) 267/1413
(18.9%) 7/72 (9.7%) 21/66 (31.8%) Revascularization CR1 hCV25598594
All Patients Hosp. for Cardiovascular Disease 20.4621 0.0001 5.917
0.015 586/1445 (40.6%) 656/1413 (46.4%) 23/72 (31.9%) 39/66 (59.1%)
CR1 hCV25598594 All Patients Hosp. for Unstable Angina 10.6553
0.0137 4.7608 0.0291 223/1445 (15.4%) 245/1413 (17.3%) 8/72 (11.1%)
19/66 (28.8%) CR1 hCV25598594 All Patients Total Coronary Heart
Disease Events 21.4023 <.0001 10.0244 0.0015 431/1445 (29.8%)
485/1413 (34.3%) 11/72 (15.3%) 30/66 (45.5%) CR1 hCV25598594 All
Patients Total Cardiovascular Disease Events 21.0456 0.0001 5.8723
0.0154 603/1445 (41.7%) 675/1413 (47.8%) 24/72 (33.3%) 40/66
(60.6%) CR1 hCV25598594 All Patients Fatal/Non-fatal
Atherosclerotic CV Disease 21.601 <.0001 9.255 0.0023 491/1445
(34.0%) 550/1413 (38.9%) 15/72 (20.8%) 34/66 (51.5%) CXCL16
hCV8718197 All Patients Fata CHD/Definite 19.0205 0.0019 7.6339
0.022 36/468 (7.7%) 74/469 (15.8%) 68/742 (9.2%) 79/722 (10.9%)
Non-fatal MI CXCL16 hCV8718197 All Patients Fatal/Non-fatal MI (def
& Prob) 23.7086 0.0002 9.3715 0.0092 33/468 (7.1%) 78/469
(16.6%) 75/742 (10.1%) 89/722 (12.3%) CXCL16 hCV8718197 All
Patients Coronary Artery Bypass or 23.6046 0.0003 9.8539 0.0072
56/468 (12.0%) 108/469 (23.0%) 119/742 (16.0%) 123/722 (17.0%)
Revascularization CXCL16 hCV8718197 All Patients Hosp. for
Cardiovascular Disease 20.8072 0.0009 6.1046 0.0473 177/468 (37.8%)
239/469 (51.0%) 305/742 (41.1%) 318/722 (44.0%) CXCL16 hCV8718197
All Patients Total Coronary Heart Disease Events 20.8149 0.0009
6.8483 0.0326 125/468 (26.7%) 182/469 (38.8%) 220/742 (29.6%)
227/722 (31.4%) CXCL16 hCV8718197 All Patients Cardiovascular
Mortality 11.7405 0.0385 7.9558 0.0187 12/468 (2.6%) 26/469 (5.5%)
24/742 (3.2%) 29/722 (4.0%) CXCL16 hCV8718197 All Patients Total
Cardiovascular Disease Events 23.8178 0.0002 7.808 0.0202 180/468
(38.5%) 247/469 (52.7%) 314/742 (42.3%) 325/722 (45.0%) CXCL16
hCV8718197 All Patients Fatal Atherosclerotic Cardiovascular
12.2666 0.0313 8.0102 0.0182 12/468 (2.6%) 26/469 (5.5%) 23/742
(3.1%) 29/722 (4.0%) Disease ELN hCV1253630 All Patients Fatal
CHD/Definite Non-fatal MI 18.1317 0.0028 8.1533 0.017 45/543 (8.3%)
77/507 (15.2%) 65/724 (9.0%) 84/721 (11.7%) ELN hCV1253630 All
Patients Non-fatal MI (def & prob) 20.2262 0.0011 10.3191
0.0057 42/543 (7.7%) 73/507 (14.4%) 62/724 (8.6%) 88/721 (12.2%)
ELN hCV1253630 All Patients Fatal/Non-fatal MI (def & prob)
27.8399 <.0001 13.5967 0.0011 45/543 (8.3%) 86/507 (17.0%)
68/724 (9.4%) 95/721 (13.2%) ELN hCV1253630 All Patients Hosp. for
Cardiovascular Disease 21.4078 0.0007 7.3688 0.0251 204/543 (37.6%)
248/507 (48.9%) 291/724 (40.2%) 339/721 (47.0%) ELN hCV1253630 All
Patients Total Coronary Heart Disease Events 19.635 0.0015 8.2358
0.0163 146/543 (26.9%) 182/507 (35.9%) 206/724 (28.5%) 254/721
(35.2%) ELN hCV1253630 All Patients Total Cardiovascular Disease
Events 21.3232 0.0007 6.4222 0.0403 212/543 (39.0%) 255/507 (50.3%)
298/724 (41.2%) 348/721 (48.3%) HLA-DPA1 hCV15760070 All Patients
Coronary Artery Bypass or 24.365 0.0002 7.073 0.0291 143/1019
(14.0%) 200/994 (20.1%) 67/443 (15.1%) 86/429 (20.0%)
Revascularization HLA-DPA1 hCV15760070 All Patients Total Coronary
Heart Disease Events 20.3365 0.0011 9.1406 0.0104 285/1019 (28.0%)
357/994 (35.9%) 136/443 (30.7%) 146/429 (34.0%) HLA-DPB1
hCV25651174 All Patients Fatal CHD/Definite Non-fatal MI 15.7588
0.0076 6.9829 0.0305 58/733 (7.9%) 93/708 (13.1%) 62/632 (9.8%)
81/632 (12.8%) HLA-DPB1 hCV25651174 All Patients Non-fatal MI (def
& prob) 19.2761 0.0017 7.1578 0.0279 63/733 (8.6%) 98/708
(13.8%) 55/632 (8.7%) 78/632 (12.3%) HLA-DPB1 hCV25651174 All
Patients Fatal/Non-fatal MI (def & prob) 22.2281 0.0005 8.6158
0.0135 65/733 (8.9%) 108/708 (15.3%) 61/632 (9.7%) 87/632 (13.8%)
HLA-DPB1 hCV25651174 All Patients Coronary Artery Bypass or 26.9669
<.0001 10.9893 0.0041 103/733 (14.1%) 137/708 (19.4%) 87/632
(13.8%) 137/632 (21.7%) Revascularization HLA-DPB1 hCV25651174 All
Patients Hosp. for Cardiovascular Diesease 27.7297 <.0001 7.3005
0.026 282/733 (38.5%) 334/708 (47.2%) 259/632 (41.0%) 314/632
(49.7%) HLA-DPB1 hCV25651174 All Patients Total Coronary Heart
Disease Events 23.6497 0.0003 11.0762 0.0039 207/733 (28.2%)
258/708 (36.4%) 182/632 (28.8%) 225/632 (35.6%) HLA-DPB1
hCV25651174 All Patients Total Cardiovascular Disease Events
25.4895 0.0001 6.5985 0.0369 291/733 (39.7%) 346/708 (48.9%)
265/632 (41.9%) 318/632 (50.3%) HLA-DPB1 hCV25651174 All Patients
Fatal/Non-fatal Atherosclerotic CV Disease 24.828 0.0002 10.0154
0.0067 230/733 (31.4%) 291/708 (41.1%) 218/632 (34.5%) 255/632
(40.3%) HLA-DPB1 hCV8851085 All Patients Fatal/Non-fatal MI (def
& prob) 18.9046 0.002 6.0738 0.048 82/919 (8.9%) 132/894
(14.8%) 53/521 (10.2%) 66/506 (13.0%) HLA-DPB1 hCV8851085 All
Patients Coronary Artery Bypass or 26.0775 <.0001 11.1434 0.0038
129/919 (14.0%) 174/894 (19.5%) 72/521 (13.8%) 107/506 (21.1%)
Revascularization HLA-DPB1 hCV8851085 All Patients Hosp. for
Cardiovascular Disease 23.3669 0.0003 6.8274 0.0329 363/919 (39.5%)
428/894 (47.9%) 209/521 (40.1%) 241/506 (47.6%) HLA-DPB1 hCV8851085
All Patients Total Coronary Heart Disease Events 21.0571 0.0008
8.5864 0.0137 263/919 (28.6%) 321/894 (35.9%) 151/521 (29.0%)
177/506 (35.0%) HLA-DPB1 hCV8851085 All Patients Total
Cardiovascular Disease Events 23.3123 0.0003 6.9617 0.0308 374/919
(40.7%) 441/894 (49.3%) 214/521 (41.1%) 246/506 (48.6%) HLA-DPB1
hCV8851085 All Patients Fatal/Non-fatal Atherosclerotic CV Disease
22.7355 0.0004 8.8922 0.0117 301/919 (32.8%) 367/894 (41.1%)
174/521 (33.4%) 197/506 (38.9%) ICAM1 hCV8726337 All Patients
Non-fatal MI (def & prob) 18.3028 0.0026 8.2162 0.0164 28/495
(5.7%) 61/460 (13.3%) 76/736 (10.3%) 91/749 (12.1%) ICAM1
hCV8726337 All Patients Fatal/Non-fatal MI 21.403 0.0007 8.3848
0.0151 31/495 (6.3%) 68/460 (14.8%) 84/736 (11.4%) 99/749 (13.2%)
(def & prob) ICAM3 hCV25473653 All Patients Total
Cardiovascular Disease Events 23.2012 0.0003 6.7475 0.0343 376/924
(40.7%) 429/874 (49.1%) 230/511 (45.0%) 247/527 (46.9%) ICAM3
hCV25473653 All Patients Fatal/Non-fatal Atherosclerotic CV Disease
21.6115 0.0006 7.3182 0.0258 299/924 (32.4%) 352/874 (40.3%)
191/511 (37.4%) 201/527 (38.1%) IGF2R hCV2200985 All Patients Hosp.
for Cardiovascular Disease 23.7283 0.0002 8.0478 0.0179 465/1175
(39.6%) 510/1093 (46.7%) 137/316 (43.4%) 167/358 (46.6%) IL1A
hCV9546471 All Patients Total Mortality 12.1611 0.0326 10.3678
0.0058 52/759 (6.9%) 37/739 (5.0%) 28/617 (4.5%) 43/584 (7.4%)
IL1RN hCV8737990 All Patients Fatal CHD/Definite Non-fatal MI
16.7149 0.0051 7.1816 0.0276 80/809 (9.9%) 100/786 (12.7%) 44/585
(7.5%) 77/568 (13.6%) IL1RN hCV8737990 All Patients Non-fatal MI
(def & prob) 20.9801 0.0008 7.2412 0.0268 68/809 (8.4%) 93/786
(11.8%) 45/585 (7.7%) 78/568 (13.7%) IL1RN hCV8737990 All Patients
Fatal/Non-fatal MI (def & prob) 22.5713 0.0004 7.6202 0.0221
76/809 (9.4%) 107/786 (13.6%) 49/585 (8.4%) 86/568 (15.1%) IL1RN
hCV8737990 All Patients Hosp. for Cardiovascular Disease 25.4952
0.0001 7.1653 0.0278 315/809 (38.9%) 357/786 (45.4%) 232/585
(39.7%) 288/568 (50.7%) IL1RN hCV8737990 All Patients Total
Coronary Heart Disease Events 23.5824 0.0003 10.6112 0.005 228/809
(28.2%) 272/786 (34.6%) 167/585 (28.5%) 213/568 (37.5%) IL1RN
hCV8737990 All Patients Total Cardiovascular Disease Events 24.6658
0.0002 6.7849 0.0336 325/809 (40.2%) 370/786 (47.1%) 239/585
(40.9%) 293/568 (51.6%) IL1RN hCV8737990 All Patients
Fatal/Non-fatal Atherosclerotic CV Disease 24.3476 0.0002 9.5892
0.0083 260/809 (32.1%) 303/786 (38.5%) 193/585 (33.0%) 243/568
(42.8%) IL6ST hCV16170435 All Patients Hosp. for Cardiovascular
Disease 20.5539 0.001 6.1238 0.0468 450/1131 (39.8%) 506/1080
(46.9%) 139/340 (40.9%) 173/352 (49.1%) IL6ST hCV16170435 All
Patients Total Cardiovascular Disease Events 21.8497 0.0006 6.4073
0.0406 465/1131 (41.1%) 519/1080 (48.1%) 142/340 (41.8%) 180/352
(51.1%) LRP8 hCV190754 All Patients Hosp. for Unstable Angina
14.1312 0.0148 9.6697 0.0079 98/560 (17.5%) 83/557 (14.9%) 100/712
(14.0%) 130/687 (18.9%) MTRR hCV7580070 All Patients Hosp. for
Cardiovascular Disease 25.4655 0.0001 7.7684 0.0206 466/1201
(38.8%) 544/1157 (47.0%) 135/284 (47.5%) 127/273 (46.5%) MTRR
hCV7580070 All Patients Total Coronary Heart Disease Events 22.029
0.0005 7.6985 0.0213 338/1201 (28.1%) 403/1157 (34.8%) 98/284
(34.5%) 94/273 (34.4%) MTRR hCV7580070 All Patients Tolal
Cardiovascular Disease Events 25.947 <.0001 7.2212 0.027
480/1201 (40.0%) 560/1157 (48.4%) 137/284 (48.2%) 131/273 (48.0%)
MTRR hCV7580070 All Patients Fatal/Non-fatal Atherosclerotic CV
Disease 25.0449 0.0001 8.5401 0.014 390/1201 (32.5%) 455/1157
(39.3%) 110/284 (38.7%) 109/273 (39.9%) NPC1 hCV25472673 All
Patients Fatal CHD/Definite Non-fatal MI 16.7713 0.005 6.9147
0.0315 65/596 (10.9%) 61/560 (10.9%) 56/664 (8.4%) 86/697 (12.3%)
NPC1 hCV25472673 All Patients Hosp. for Cardiovascular Disease
33.7727 <.0001 16.8966 0.0002 262/596 (44.0%) 244/560 (43.6%)
255/664 (38.4%) 323/697 (46.3%) NPC1 hCV25472673 All Patients Total
Coronary Heart Disease Events 23.8979 0.0002 12.324 0.0021 193/596
(32.4%) 180/560 (32.1%) 186/664 (28.0%) 242/697 (34.7%) NPC1
hCV25472673 All Patients Total Cardiovascular Disease Events
36.5639 <.0001 18.2781 0.0001 274/596 (46.0%) 254/560 (45.4%)
259/664 (39.0%) 330/697 (47.3%) NPC1 hCV25472673 All Patients
Fatal/Non-fatal Atherosclerotic CV Disease 28.4984 <.0001
15.5441 0.0004 221/596 (37.1%) 204/560 (36.4%) 213/664 (32.1%)
274/697 (39.3%) NPC1 hCV7490135 All Patients Hosp. for
Cardiovascular Disease 23.7333 0.0002 9.7365 0.0077 194/437 (44.4%)
181/410 (44.1%) 295/742 (39.8%) 333/718 (46.4%) NPC1 hCV7490135 All
Patients Total Coronary Heart Disease 19.1385 0.0018 7.9824 0.0185
146/437 (33.4%) 131/410 (32.0%) 213/742 (28.7%) 257/718 (35.8%)
Events NPC1 hCV7490135 All Patients Cardiovascular Mortality
13.4221 0.0197 7.0589 0.0293 26/437 (5.9%) 19/410 (4.6%) 26/742
(3.5%) 30/718 (4.2%) NPC1 hCV7490135 All Patients Total
Cardiovascular Disease Events 25.0799 0.0001 10.2093 0.0061 202/437
(46.2%) 188/410 (45.9%) 303/742 (40.8%) 343/718 (47.8%) NPC1
hCV7490135 All Patients Fatal Atherosclerotic Cardiovascular
Disease 12.5678 0.0278 6.6963 0.0351 25/437 (5.7%) 19/410 (4.6%)
26/742 (3.5%) 30/718 (4.2%) NPC1 hCV7490135 All Patients
Fatal/Non-fatal Atherosclerotic CV Disease 21.1468 0.0008 9.3367
0.0094 165/437 (37.8%) 148/410 (36.1%) 246/742 (33.2%) 290/718
(40.4%) PEMT hCV7443062 All Patients Fatal CHD/Definite Non-fatal
MI 17.658 0.0034 8.5923 0.0136 34/478 (7.1%) 71/462 (15.4%) 72/735
(9.8%) 82/739 (11.1%) PLAU hCV16273460 All Patients Fatal/Non-fatal
Atherosclerotic CV Disease 18.1127 0.0028 6.1227 0.0468 301/903
(33.3%) 350/888 (39.4%) 185/527 (35.1%) 192/499 (38.5%) PON1
hCV2548962 All Patients Total Coronary Heart Disease Events 16.8056
0.0049 6.2165 0.0447 217/736 (29.5%) 266/753 (35.3%) 190/625
(30.4%) 189/579 (32.6%) PON1 hCV2548962 All Patients Any Report of
Stroke During CARE 34.8995 <.0001 7.1404 0.0281 13/736 (1.8%)
16/753 (2.1%) 14/625 (2.2%) 39/579 (6.7%) PON1 hCV2548962 All
Patients 1st Stroke Occurred During CARE 28.2289 <.0001 6.8104
0.0332 13/736 (1.8%) 14/753 (1.9%) 13/625 (2.1%) 34/579 (5.9%) SELP
hCV11975296 All Patients Coronary Artery Bypass or 24.9318 0.0001
7.3821 0.0249 146/969 (15.1%) 205/996 (20.6%) 60/478 (12.6%) 78/422
(18.5%) Revascularization SELP hCV11975296 All Patients Hosp. for
Cardiovascular Disease 27.7519 <0.0001 6.7453 0.0343 415/969
(42.8%) 479/996 (48.1%) 164/478 (34.3%) 193/422 (45.7%) SELP
hCV11975296 All Patients Hosp. for Unstable Angina 15.1132 0.0099
8.9591 0.0113 150/969 (15.5%) 181/996 (18.2%) 65/478 (13.6%) 78/422
(18.5%) SERPINA1 hCV1260328 All Patients Fatal/Non-fatal
Cerebrovascular Disease 21.6532 0.0006 11.1964 0.0037 56/942 (5.9%)
53/915 (5.8%) 14/502 (2.8%) 36/486 (7.4%) SERPINA1 hCV1260328 All
Patients Any Report of Stroke During CARE 15.254 0.0093 7.0558
0.0294 27/942 (2.9%) 30/915 (3.3%) 6/502 (1.2%) 24/486 (4.9%) TAP1
hCV549926 All Patients Fatal CHD/Definite Non-fatal MI 16.2424
0.0062 6.4831 0.0391 104/1042 (10.0%) 117/1013 (11.5%) 34/414
(8.2%) 58/407 (14.3%) TGFB1 hCV8708473 All Patients Fatal Coronary
Heart Disease 19.8613 0.0013 16.4965 0.0003 36/704 (5.1%) 20/686
(2.9%) 8/652 (1.2%) 29/629 (4.6%) TGFB1 hCV8708473 All Patients
Total Mortality 12.6344 0.0271 11.4639 0.0032 51/704 (7.2%) 34/686
(5.0%) 25/652 (3.8%) 48/629 (7.6%) TGFB1 hCV8708473 All Patients
Total Coronary Heart Disease Events 27.3046 <.0001 8.436 0.0147
226/704 (32.1%) 234/686 (34.1%) 156/652 (23.9%) 220/629 (35.0%)
TGFB1 hCV8708473 All Patients Cardiovascular Mortality 21.2405
0.0007 18.5606 <.0001 39/704 (5.5%) 20/686 (2.9%) 11/652 (1.7%)
34/629 (5.4%) TGFB1 hCV8708473 All Patients Fatal Atherosclerotic
Cardiovascular Disease 20.614 0.001 17.9247 0.0001 38/704 (5.4%)
20/686 (2.9%) 11/652 (1.7%) 34/629 (5.4%) TGFB1 hCV8708473 All
Patients Fatal/Non-fatal Atherosclerotic CV Disease 27.9483
<.0001 8.0319 0.018 262/704 (37.2%) 265/686 (38.6%) 182/652
(27.9%) 248/629 (39.4%) TGFB1 hCV8708473 All Patients More Than 1
Prior MI 14.8325 0.0111 12.9873 0.0015 122/704 (17.3%) 81/686
(11.8%) 86/652 (13.2%) 110/629 (17.5%) TGFB1 hCV8708473 All
Patients History of Stroke 22.4625 0.0004 7.6883 0.0214 38/704
(5.4%) 19/686 (2.8%) 8/652 (1.2%) 16/629 (2.5%) TGFB1 hCV8708473
All Patients Any Report of Stroke Prior to or During 13.4403 0.0196
7.6397 0.0219 53/704 (7.5%) 39/686 (5.7%) 25/652 (3.8%) 35/629
(5.6%) CARE TLR5 hCV15871020 All Patients Hosp. for Cardiovascular
Disease 28.2057 <.0001 12.2152 0.0022 444/1087 (40.8%) 492/1070
(46.0%) 159/390 (40.8%) 181/371 (48.8%) TLR5 hCV15871020 All
Patients Total Coronary Heart Disease Events 26.4624 <.0001
13.2013 0.0014 331/1087 (30.5%) 360/1070 (33.6%) 106/390 (27.2%)
136/371 (36.7%) TLR5 hCV15871020 All Patients Total Cardiovascular
Disease Events 28.9522 <.0001 12.4869 0.0019 457/1087 (42.0%)
504/1070 (47.1%) 163/390 (41.8%) 188/371 (50.7%) TLR5 hCV15871020
All Patients Fatal/non-fatal Atherosclerotic CV Disease 23.7163
0.0002 10.5837 0.005 374/1087 (34.4%) 411/1070 (38.4%) 125/390
(32.1%) 152/371 (41.0%) TNF hCV7514879 All Patients Total Mortality
11.4977 0.0424 6.8371 0.0328 63/1057 (6.0%) 56/1036 (5.4%)
19/401 (4.7%) 33/411 (8.0%) TNF hCV7514879 All Patients
Fatal/Non-fatal Ml (def & prob) 21.2263 0.0007 7.2562 0.0266
111/1057 (10.5%) 132/1036 (12.7%) 31/401 (7.7%) 66/411 (16.1%) TNF
hCV7514879 All Patients Hosp. for Cardiovascular Disease 23.6158
0.0003 7.276 0.0263 432/1057 (40.9%) 483/1036 (46.6%) 156/401
(38.9%) 188/411 (45.7%) TNF hCV7514879 All Patients Total
Cardiovascular Disease Events 24.2211 0.0002 7.3706 0.0251 448/1057
(42.4%) 498/1036 (48.1%) 158/401 (39.4%) 193/411 (47.0%) ABCC8
hCV600632 All Patients Catheterization 13.9418 0.016 9.5561 0.0084
74/615 (12.0%) 61/599 (10.2%) 61/696 (8.8%) 100/677 (14.8%)
ADAMTS13 hCV11571465 All Patients Nonfatal Ml (Probable/Definite)
17.5811 0.0035 6.1707 0.0457 46/508 (9.1%) 76/548 (13.9%) 75/726
(10.3%) 77/667 (11.5%) ADAMTS13 hCV11571465 All Patients Nonfatal
MI (def & prob) 17.3392 0.0039 6.5756 0.0373 46/508 (9.1%)
73/548 (13.3%) 70/726 (9.6%) 70/667 (10.5%) ADAMTS13 hCV11571465
All Patients Family History of CV Disease 14.4524 0.013 11.1981
0.0037 191/508 (37.6%) 235/548 (42.9%) 263/726 (36.2%) 277/667
(41.5%) APOE hCV905013 All Patients Nonfatal MI (Probable/Definite)
18.7262 0.0022 6.2618 0.0437 33/395 (8.4%) 57/375 (15.2%) 78/749
(10.4%) 81/712 (11.4%) BCL2A1 hCV7509650 All Patients MI
(Fatal/Nonfatal) 20.7271 0.0009 7.0892 0.0289 75/828 (9.1%) 127/807
(15.7%) 68/579 (11.4%) 66/572 (11.5%) BCL2A1 hCV7509650 All
Patients Definite Nonfatal MI 15.791 0.0075 7.0986 0.0287 52/828
(6.3%) 88/807 (10.9%) 46/579 (7.9%) 42/572 (7.3%) BCL2A1 hCV7509650
All Patients Nonfatal MI (def & prob) 21.0159 0.0008 8.5271
0.0141 67/828 (8.1%) 117/807 (14.5%) 59/579 (10.2%) 54/572 (9.4%)
BCL2A1 hCV7509650 All Patients Fatal/Nonfatal MI (def & prob)
21.9831 0.0005 8.1075 0.0174 72/828 (8.7%) 126/807 (15.6%) 66/579
(11.4%) 65/572 (11.4%) CCL4 hCV12120554 All Patients Fatal Coronary
Heart Disease 17.031 0.0007 9.227 0.0024 38/1093 (3.5%) 29/1059
(2.7%) 9/402 (2.2%) 28/411 (6.8%) CCL4 hCV12120554 All Patients
Total Mortality 13.1127 0.0044 9.1894 0.0024 66/1093 (6.0%) 55/1059
(5.2%) 16/402 (4.0%) 39/411 (9.5%) CCL4 hCV12120554 All Patients
Total Coronary Heart Disease Events 17.7584 0.0005 6.5889 0.0103
333/1093 (30.5%) 355/1059 (33.5%) 101/402 (25.1%) 156/411 (38.0%)
CCL4 hCV12120554 All Patients Cardiovascular Mortality 18.0677
0.0004 10.6031 0.0011 44/1093 (4.0%) 33/1059 (3.1%) 10/402 (2.5%)
31/411 (7.5%) CCL4 hCV12120554 All Patients Fatal Atherosclerotic
Cardiovascular Disease 19.0598 0.0003 11.5967 0.0007 44/1093 (4.0%)
33/1059 (3.1%) 9/402 (2.2%) 31/411 (7.5%) CCL4 hCV12120554 All
Patients Fatal/Nonfatal Atherosclerotic CV Disease 19.4099 0.0002
6.6292 0.01 376/1093 (34.4%) 401/1059 (37.9%) 120/402 (29.9%)
179/411 (43.6%) CD6 hCV2553030 All Patients Hosp. for
Cardiovascular Disease 20.6003 0.001 6.0367 0.0489 351/845 (41.5%)
415/888 (46.7%) 220/551 (39.9%) 236/512 (46.1%) CD6 hCV2553030 All
Patients Total Cardiovascular Disease Events 21.3941 0.0007 6.0879
0.0476 365/845 (43.2%) 425/888 (47.9%) 222/551 (40.3%) 245/512
(47.9%) CD6 hCV2553030 All Patients History of Angina Pectoris
12.5002 0.0285 11.4198 0.0033 180/845 (21.3%) 181/888 (20.4%)
125/551 (22.7%) 91/512 (17.8%) CD6 hCV25922320 All Patients
Definite Nonfatal MI 15.6195 0.008 6.8415 0.0327 57/995 (5.7%)
97/935 (10.4%) 42/457 (9.2%) 39/471 (8.3%) CD6 hCV25922320 All
Patients Fatal CHD/Definite Nonfatal MI 17.6754 0.0034 8.5308 0.014
77/995 (7.7%) 126/935 (13.5%) 56/457 (12.3%) 52/471 (11.0%) COL11A1
hCV8400671 All Patients MI (Fatal/Nonfatal) 18.8839 0.002 6.1759
0.0456 108/1007 (10.7%) 122/966 (12.6%) 36/417 (8.6%) 70/426
(16.4%) COL11A1 hCV8400671 All Patients Nonfatal MI (def &
prob) 19.0171 0.0019 7.4511 0.0241 97/1007 (9.6%) 103/966 (10.7%)
32/417 (7.7%) 66/426 (15.5%) COL11A1 hCV8400671 All Patients
Fatal/Nonfatal MI (def & prob) 20.2734 0.0011 7.2186 0.0271
107/1007 (10.6%) 120/966 (12.4%) 34/417 (8.2%) 70/426 (16.4%)
CYP4F2 hCV16179493 All Patients Catheterization 16.4595 0.0056
9.206 0.01 76/724 (10.5%) 100/720 (13.9%) 55/639 (8.6%) 77/629
(12.2%) CYP4F2 hCV16179493 All Patients Fatal Coronary Heart
Disease 14.8471 0.011 11.1566 0.0038 18/724 (2.5%) 39/720 (5.4%)
27/639 (4.2%) 14/629 (2.2%) CYP4F2 hCV16179493 All Patients Total
Mortality 13.9492 0.0159 8.7397 0.0127 34/724 (4.7%) 60/720 (8.3%)
42/639 (6.6%) 30/629 (4.8%) CYP4F2 hCV16179493 All Patients
Cardiovascular Mortality 12.7875 0.0255 7.6593 0.0217 24/724 (3.3%)
43/720 (6.0%) 28/639 (4.4%) 17/629 (2.7%) CYP4F2 hCV16179493 All
Patients Fatal Atherosclerotic Cardiovascular Disease 13.275 0.0209
8.1604 0.0169 23/724 (3.2%) 43/720 (6.0%) 28/639 (4.4%) 17/629
(2.7%) FCGR2A hCV9077561 All Patients Catheterization 17.7696
0.0032 12.6158 0.0018 43/372 (11.6%) 45/363 (12.4%) 88/783 (11.2%)
79/737 (10.7%) FCGR2A hCV9077561 All Patients Coronary Artery
Bypass or 21.2433 0.0007 7.357 0.0253 60/372 (16.1%) 64/363 (17.6%)
116/783 (14.8%) 134/737 (18.2%) Revascularization GAPD hCV8921288
All Patients MI (Fatal/Nonfatal) 19.0929 0.0018 7.4744 0.0238
106/975 (10.9%) 114/932 (12.2%) 39/447 (8.7%) 75/451 (16.6%) GAPD
hCV8921288 All Patients Nonfatal MI (Probable/Definite) 17.0899
0.0043 6.5106 0.0386 100/975 (10.3%) 108/932 (11.6%) 36/447 (8.1%)
71/451 (15.7%) GAPD hCV8921288 All Patients Fatal CHD/Definite
Nonfatal MI 18.5634 0.0023 10.4472 0.0054 102/975 (10.5%) 98/932
(10.5%) 33/447 (7.4%) 70/451 (15.5%) GAPD hCV8921288 All Patients
Nonfatal MI (def & prob) 14.4084 0.0132 6.4562 0.0396 97/975
(9.9%) 103/932 (11.1%) 34/447 (7.6%) 64/451 (14.2%) GAPD hCV8921288
All Patients Fatal/Nonfatal MI (def & prob) 19.0127 0.0019
6.6952 0.0352 103/975 (10.6%) 113/932 (12.1%) 39/447 (8.7%) 74/451
(16.4%) IL12A hCV16053900 All Patients Coronary Artery Bypass Graft
18.6383 0.0022 8.9976 0.0111 22/453 (4.9%) 56/459 (12.2%) 68/761
(8.9%) 72/718 (10.0%) IL12A hCV16053900 All Patients Cornary Artery
Bypass or 29.621 <.0001 13.1691 0.0014 50/453 (11.0%) 109/459
(23.7%) 123/761 (16.2%) 133/718 (18.5%) Revascularization IL9
hCV3275199 All Patients MI (Fatal/Nonfatal) 22.6018 0.0004 10.1051
0.0064 125/1129 (11.1%) 153/1151 (13.3%) 21/348 (6.0%) 49/302
(16.2%) IL9 hCV3275199 All patients Nonfatal MI (Probable/Definite)
23.2912 0.0003 11.1902 0.0037 117/1129 (10.4%) 141/1151 (12.3%)
20/348 (5.7%) 49/302 (16.2%) IL9 hCV3275199 All patients Nonfatal
MI (def & prob) 19.7567 0.0014 9.2262 0.0099 111/1129 (9.8%)
133/1151 (11.6%) 20/348 (5.7%) 45/302 (14.9%) IL9 hCV3275199 All
Patients Fatal/Nonfatal MI (def & prob) 22.278 0.0005 9.1717
0.0102 122/1129 (10.8%) 152/1151 (13.2%) 21/348 (6.0%) 48/302
(15.9%) KLK14 hCV16044337 All Patients MI (Fatal/Nonfatal) 27.4658
<.0001 8.606 0.0135 70/693 (10.1%) 81/685 (11.8%) 67/657 (10.2%)
89/629 (14.1%) KLK14 hCV16044337 All Patients Nonfatal MI
(Probable/Definite) 25.1331 0.0001 8.1765 0.0168 67/693 (9.7%)
79/685 (11.5%) 62/657 (9.4%) 81/629 (12.9%) KLK14 hCV16044337 All
Patients Definite Nonfatal MI 18.9026 0.002 6.7602 0.034 49/693
(7.1%) 57/685 (8.3%) 47/657 (7.2%) 58/629 (9.2%) KLK14 hCV16044337
All Patients Coronary Artery Bypass Graft 18.8672 0.002 8.7354
0.0127 60/693 (8.7%) 57/685 (8.3%) 41/657 (6.2%) 79/629 (12.6%)
KLK14 hCV16044337 All Patients Fatal CHD/Definite Nonfatal MI
23.3389 0.0003 9.6221 0.0081 68/693 (9.5%) 73/685 (10.7%) 65/657
(9.9%) 79/629 (12.6%) KLK14 hCV16064337 All Patients Nonfatal MI
(def & prob) 23.6296 0.0003 7.6653 0.0217 63/693 (9.1%) 75/685
(10.9%) 60/657 (9.1%) 74/629 (11.8%) KLK14 hCV16044337 All Patients
Fatal/Nonfatal MI (def & prob) 28.3799 <.0001 8.3321 0.0155
68/693 (9.8%) 80/685 (11.7%) 66/657 (10.0%) 88/629 (14.0%) LAMA5
hCV25629492 All Patients Definite Nonfatal MI 17.052 0.0044 8.4868
0.0144 55/622 (8.8%) 53/616 (8.6%) 36/664 (5.4%) 64/639 (10.0%)
LAMA5 hCV25629492 All Patients Nonfatal MI (def & prob) 19.6962
0.0014 8.0144 0.0182 70/622 (11.3%) 71/616 (11.5%) 49/664 (7.4%)
84/639 (13.1%) LAMA5 hCV25629492 All Patients Fatal/Nonfatal MI
(def & prob) 21.1343 0.0008 6.1961 0.0451 75/622 (12.1%) 82/616
(13.3%) 51/664 (7.7%) 90/639 (14.1%) MARK3 hCV25926771 All Patients
Definite Nonfatal MI 17.5176 0.0015 3.8996 0.0483 39/578 (6.7%)
37/566 (6.5%) 63/906 (7.0%) 100/879 (11.4%) MARK3 hCV25926771 All
Patients Fatal CHD/Definite Nonfatal MI 14.4978 0.0059 4.1405
0.0419 57/578 (9.9%) 56/566 (9.9%) 82/906 (9.1%) 125/879 (14.2%)
MJD hCV16189421 All Patients MI (Fatal/Nonfatal) 16.398 0.0058
6.2348 0.0443 73/845 (8.6%) 123/828 (14.9%) 68/547 (12.1%) 61/506
(12.1%) MJD hCV16189421 All Patients Nonfatal MI
(Probable/Definite) 16.5163 0.0055 7.157 0.0279 68/845 (8.0%)
118/828 (14.3%) 62/547 (11.3%) 56/506 (11.1%) MJD hCV16189421 All
Patients Nonfatal MI (def & prob) 17.6259 0.0035 9.9522 0.0069
63/845 (7.5%) 113/828 (13.6%) 61/547 (11.2%) 50/506 (9.9%) MJD
hCV16189421 All Patients Fatal/Nonfatal MI (def & prob) 16.788
0.0049 6.31 0.0426 71/845 (8.4%) 122/828 (14.7%) 65/547 (11.9%)
61/506 (12.1%) MJD hCV16189421 All Patients Hosp. for Unstable
Angina 11.229 0.047 6.7739 0.0338 122/845 (14.4%) 161/828 (19.4%)
96/547 (17.6%) 79/506 (15.6%) MMP27 hCV7492601 All Patients
Percutaneous Transluminal Coronary 13.2841 0.0209 6.4349 0.0401
42/432 (9.7%) 36/449 (6.0%) 68/746 (9.1%) 81/715 (11.3%) Angiopla:
NiD2 hCV15876071 All Patients Fatal/Nonfatal Cerebrovascular
Disease 13.2979 0.0207 7.6501 0.0218 47/830 (5.7%) 47/838 (5.6%)
23/561 (4.1%) 44/549 (8.0%) PECAM1 hCV16170911 All Patients Stroke
16.5925 0.0053 7.4654 0.0239 7/476 (1.5%) 17/443 (3.8%) 22/716
(3.1%) 22/679 (3.2%) PLAB hCV7494810 All Patients MI
(Fatal/Nonfatal) 21.5216 0.0006 6.8687 0.0322 99/876 (11.3%)
109/836 (13.0%) 44/551 (8.0%) 87/542 (16.1%) PLAB hCV7494810 All
Patients Nonfatal MI (Probable/Definite) 19.4685 0.0016 6.2388
0.0442 93/876 (10.6%) 103/836 (12.3%) 41/551 (7.4%) 81/542 (14.9%)
PLAB hCV7494810 All Patients Definite Nonfatal MI 19.0196 0.0019
8.9516 0.0114 69/876 (7.9%) 70/836 (8.4%) 28/551 (5.1%) 65/542
(12.0%) PLAB hCV7494810 All Patients Fatal CHD/Definite Nonfatal MI
18.025 0.0029 6.5222 0.0383 91/876 (10.4%) 96/836 (11.5%) 42/551
(7.6%) 81/542 (14.9%) PLAB hCV7494810 All Patients Nonfatal MI (def
& prob) 18.3495 0.0025 6.8182 0.0331 89/876 (10.2%) 95/836
(11.4%) 39/551 (7.1%) 78/542 (14.4%) PLAB hCV7494810 All Patients
Fatal/Nonfatal MI (def & prob) 21.1333 0.0008 6.0322 0.049
96/876 (11.0%) 108/836 (12.9%) 44/551 (8.0%) 86/542 (15.9%) PTPN21
hCV16182835 All Patients Fatal/Nonfatal Cerebrovascular Disease
15.5999 0.0081 8.6004 0.0136 38/661 (5.7%) 30/615 (4.9%) 26/646
(4.0%) 51/673 (7.6%) PTPN21 hCV25942539 All patients Fatal/Nonfatal
Cerebrovascular Disease 14.0688 0.0152 7.0712 0.0291 38/672 (5.7%)
32/620 (5.2%) 26/642 (4.0%) 51/673 (7.6%) QSCN6 hCV25761292 All
Patients Coronary Artery Bypass Graft 19.4949 0.0016 7.7834 0.0204
63/1085 (5.8%) 107/1024 (10.4%) 41/376 (10.9%) 39/405 (9.6%)
SERPINA1 hCV25640505 All Patients Coronary Artery Bypass Graft
20.6685 0.0009 7.2873 0.0262 44/724 (6.1%) 86/705 (12.2%) 38/420
(9.0%) 43/413 (10.4%) SERPINB6 hCV16190893 All Patients
Fatal/Nonfatal Atherosclerotic CV Disease 21.4112 0.0007 6.2956
0.0429 266/762 (34.9%) 286/732 (39.1%) 198/612 (32.4%) 227/603
(37.6%) SN hCV25623265 All Patients Definite Nonfatal MI 17.7417
0.0033 8.3114 0.0157 33/401 (8.2%) 41/369 (10.4%) 60/786 (7.6%)
66/745 (8.9%) SN hCV25623265 All Patients Percutaneous Transluminal
Coronary 12.2825 0.0311 7.1894 0.0275 30/401 (7.5%) 57/396 (14.4%)
75/786 (9.5%) 76/745 (10.2%) Angiopla: SN hCV25623265 All Patients
Fatal CHD/Definite Nonfatal MI 18.5351 0.0023 8.1295 0.0172 39/401
(9.7%) 53/396 (13.4%) 85/786 (10.8%) 89/745 (11.9%) SN hCV25623265
All Patients Coronary Artery Bypass or 27.1389 <.0001 8.407
0.0149 52/401 (13.0%) 99/396 (25.0%) 117/786 (14.9%) 135/745
(18.1%) Revascularization SN hCV25623265 All Patients Total
Coronary Heart Disease Events 18.4965 0.0024 6.233 0.0443 109/401
(27.2%) 157/396 (39.6%) 240/786 (30.5%) 243/745 (32.6%) TGFB1
hCV22272997 All Patients Fatal Coronary Heart Disease Events
17.2829 0.004 14.9183 0.0006 29/554 (5.2%) 13/538 (2.4%) 14/712
(2.0%) 32/678 (4.7%) TGFB1 hCV22272997 All Patients Total Mortality
15.1303 0.0098 13.5508 0.0011 41/554 (7.4%) 22/538 (4.1%) 33/712
(4.6%) 52/678 (7.7%) TGFB1 hCV22272997 All Patients Total Coronary
Heart Disease Events 22.2798 0.0005 8.4079 0.0149 180/554 (32.5%)
183/538 (34.0%) 178/712 (25.0%) 243/678 (35.8%) TGFB1 hCV22272997
All Patients Cardiovacular Mortality 18.1724 0.0027 16.0606 0.0003
31/554 (5.6%) 13/538 (2.4%) 18/712 (2.5%) 36/678 (5.3%) TGFB1
hCV22272997 All Patients Fatal Atherosclerotic Cardiovascular
Disease 19.1187 0.0018 16.6988 0.0002 31/554 (5.6%) 13/538 (2.4%)
17/712 (2.4%) 36/678 (5.3%) TLR6 hCV1180648 All Patients Fatal
Coronary Heart Disease 17.8186 0.0032 9.4953 0.0087 18/548 (3.3%)
28/532 (5.3%) 13/692 (1.9%) 24/689 (3.5%) TLR6 hCV1180648 All
Patients Cardiovascular Mortality 17.2547 0.004 10.936 0.0042
19/548 (3.5%) 30/532 (5.6%) 17/692 (2.5%) 29/689 (4.2%) TLR6
hCV1180648 All Patients Fatal Atherosclerotic Cardiovascular
Disease 15.9494 0.007 10.159 0.0062 19/548 (3.5%) 30/532 (5.6%)
17/692 (2.5%) 29/689 (4.2%) VEGF hCV791476 All Patients
Cardiovascular Mortality 13.8606 0.0165 9.7311 0.0077 45/1067
(4.2%) 34/1030 (3.3%) 9/372 (2.4%) 27/384 (7.0%) VEGF hCV791476 All
Patients Fatal Atherosclerotic Cardiovascular Disease 13.8845
0.0164 9.3771 0.0092 44/1067 (4.1%) 34/1030 (3.3%) 9/372 (2.4%)
27/384 (7.0%) 2 Rare Alleles Prava vs. Placebo n/total (%) Odds
Ratio (95% CI) Significance Public Prava Placebo 0 Rare Alleles 1
Rare Alleles 2 Rare Alleles Level ABCA1 3/127 (2.4%) 9/107 (8.4%)
0.98 (0.66 to 1.46) 0.43 (0.18 to 1.01) 0.26 (0.06 to 1.15) P <
0.05 ABCA1 2/127 (1.6%) 7/107 (6.5%) 0.92 (0.54 to 1.56) 0.21 (0.06
to 0.75) 0.23 (0.04 to 1.38) P < 0.05 ABCA1 2/127 (1.6%) 7/107
(6.5%) 9.88 (0.57 to 1.70) 0.26 (0.07 to 0.96) 0.23 (0.04 to 1.40)
p < 0.05 AGTR1 5/120 (4.2%) 23/150 (15.3%) 0.63 (0.45 to 0.89)
0.95 (0.50 to 1.78) 0.24 (0.08 to 0.74) p < 0.05 AGTR1 8/120
(6.7%) 31/150 (20.7%) 0.89 (0.68 to 1.17) 0.90 (0.53 to 1.52) 0.27
(0.11 to 0.69) p < 0.05 AGTR1 20/120 (16.7%) 52/150 (34.7%) 0.80
(0.65 to 1.00) 0.82 (0.54 to 1.29) 0.38 (0.19 to 0.74) p < 0.05
CCL11 9/34 (26.5%) 34/49 (69.4%) 0.76 (0.64 to 0.91) 0.91 (0.62 to
1.35) 0.16 (0.06 to 0.44) p < 0.005 CCL11 4/34 (118%) 22/49
(44.9%) 0.80 (0.66 to 096) 0.84 (0.56 to 1.27) 0.16 (0.05 to 0.56)
p < 0.05 CCL11 9/34 (26.5%) 35/49 (71.4%) 0.77 (0.64 to 0.91)
0.88 (0.60 to 1.30) 0.14 (0.05 to 0.40) P < 0.005 CCL11 7/34
(20.6%) 27/49 (55.1%) 0.80 (0.67 to 0.96) 0.82 (0.55 to 1.22) 0.21
(0.07 to 0.60) p < 0.05 CHUK 17/354 (4.8%) 43/331 (13.0%) 0.86
(0.56 to 1.30) 0.77 (0.37 to 1.61) 0.34 (0.14 to 0.81) p < 0.05
CHUK 51/354 (14.4%) 73/331 (22.1%) 1.38 (0.93 to 2.04) 0.76 (0.38
to 1.51) 0.59 (0.28 to 1.25) p < 0.05 CR1 0/0 (0.0%) 0/0 (0.0%)
0.76 (0.60 to 0.97) 0.06 (0.01 to 0.52) p < 0.05 CR1 0/0 (0.0%)
0/0 (0.0%) 0.74 (0.58 to 0.93) 0.12 (0.02 to 0.56) p < 0.05 CR1
0/0 (0.0%) 0/0 (0.0%) 0.74 (0.61 to 0.90) 0.23 (0.09 to 0.62) p
< 0.05 CR1 0/0 (0.0%) 0/0 (0.0%) 0.79 (0.68 to 0.91) 0.33 (0.16
to 0.68) p < 0.05 CR1 0/0 (0.0%) 0/0 (0.0%) 0.87 (0.71 to 1.06)
0.31 (0.12 to 0.81) p < 0.05 CR1 0/0 (0.0%) 0/0 (0.0%) 0.81
(0.69 to 0.95) 0.22 (0.09 to 0.50) p < 0.005 CR1 0/0 (0.0%) 0/0
(0.0%) 0.78 (0.68 to 0.91) 0.33 (0.16 to 0.68) p < 0.05 CR1 0/0
(0.0%) 0/0 (0.0%) 0.81 (0.69 to 0.94) 0.25 (0.11 to 0.54) p <
0.005 CXCL16 34/292 (11.6%) 31/278 (11.2%) 0.44 (0.29 to 0.68) 0.82
(0.40 to 1.70) 1.05 (0.46 to 2.40) p < 0.05 CXCL16 36/292
(12.3%) 37/278 (13.3%) 0.38 (0.25 to 0.58) 0.80 (0.39 to 1.66) 0.92
(0.40 to 2.06) p < 0.05 CXCL16 43/292 (14.7%) 55/278 (19.8%)
0.45 (0.32 to 0.65) 0.93 (0.51 to 1.71) 0.70 (0.35 to 1.41) p <
0.05 CXCL16 124/292 (42.5%) 133/278 (47.8%) 0.59 (0.45 to 0.76)
0.89 (0.56 to 1.40) 0.80 (0.48 to 1.36) p < 0.05 CXCL16 94/262
(32.2%) 102/278 (36.7%) 0.57 (0.44 to 0.76) 0.92 (0.56 to 1.50)
0.82 (0.47 to 1.43) p < 0.05 CXCL16 19/292 (6.5%) 9/278 (3.2%)
0.45 (0.22 to 0.90) 0.80 (0.24 to 2.64) 2.08 (0.55 to 7.91) p <
0.05 CXCL16 130/292 (44.5%) 138/278 (49.6%) 0.56 (0.43 to 0.73)
0.90 (0.57 to 1.42) 0.81 (0.48 to 1.38) p < 0.05 CXCL16 19/292
(6.5%) 9/278 (3.2%) 0.45 (0.22 to 0.90) 0.76 (0.23 to 2.53) 2.08
(0.55 to 7.91) p < 0.05 ELN 29/245 (11.8%) 21/241 (8.7%) 0.50
(0.34 to 0.75) 0.75 (0.37 to 1.49) 1.41 (0.60 to 3.27) p < 0.05
ELN 30/245 (12.2%) 19/241 (7.9%) 0.50 (0.33 to 0.74) 0.67 (0.33 to
1.37) 1.63 (0.69 to 3.87) p < 0.05 ELN 33/245 (13.5%) 21/241
(8.7%) 0.44 (0.30 to 0.65) 0.68 (0.35 to 1.34) 1.63 (0.71 to 3.72)
p < 0.005 ELN 113/245 (46.1%) 103/241 (42.7%) 0.63 (0.49 to
0.80) 0.76 (0.49 to 1.18) 1.15 (0.68 to 1.95) p < 0.05 ELN
88/245 (35.9%) 74/241 (30.7%) 0.66 (0.51 to 0.85) 0.73 (0.46 to
1.17) 1.26 (0.72 to 2.21) p < 0.05
ELN 115/245 (46.9%) 107/241 (44.4%) 0.63 (0.50 to 0.81) 0.75 (0.48
to 1.16) 1.11 (0.65 to 1.88) p < 0.05 HLA-DPA1 9/52 (17.3%) 2/56
(3.6%) 0.65 (0.51 to 0.82) 0.71 (0.43 to 1.18) 5.65 (1.1 to 28.71)
p < 0.05 HLA-DPA1 21/52 (40.4%) 12/56 (21.4%) 0.69 (0.57 to
0.84) 0.86 (0.57 to 1.29) 2.48 (1.01 to 6.08) p < 0.05 HLA-DPB1
20/144 (13.9%) 11/132 (8.3%) 0.57 (0.40 to 0.80) 0.74 (0.39 to
1.40) 1.77 (0.69 to 4.58) p < 0.05 HLA-DPB1 16/144 (11.1%) 7/132
(5.3%) 0.59 (0.42 to 0.82) 0.68 (0.36 to 1.28) 2.23 (0.77 to 6.43)
p < 0.05 HLA-DPB1 20/144 (13.9%) 10/132 (7.6%) 0.54 (0.39 to
0.75) 0.67 (0.36 to 1.24) 1.97 (0.76 to 5.07) p < 0.05 HLA-DPB1
27/144 (18.8%) 13/132 (9.8%) 0.68 (0.62 to 0.90) 0.58 (0.34 to
0.98) 2.11 (0.92 to 4.86) p < 0.005 HLA-DPB1 61/144 (42.4%)
45/132 (34.1%) 0.70 (0.57 to 0.86) 0.70 (0.47 to 1.05) 1.42 (0.79
to 2.56) p < 0.05 HLA-DPB1 50/144 (34.7%) 30/132 (22.7%) 0.69
(0.55 to 0.86) 0.73 (0.48 to 1.12) 1.81 (0.96 to 3.42) p < 0.005
HLA-DPB1 64/144 (44.4%) 49/132 (37.1%) 0.69 (0.56 to 0.85) 0.71
(0.48 to 1.06) 1.35 (0.76 to 2.43) p < 0.05 HLA-DPB1 54/144
(37.5%) 36/132 (27.3%) 0.66 (0.53 to 0.81) 0.78 (0.52 to 1.17) 1.60
(0.87 to 2.95) p < 0.05 HLA-DPB1 11/73 (15.1%) 6/76 (7.9%) 0.57
(0.42 to 0.76) 0.75 (0.42 to 1.37) 2.07 (0.66 to 6.51) p < 0.05
HLA-DPB1 17/73 (23.3%) 6/76 (7.9%) 0.68 (0.53 to 0.87) 0.60 (0.36
to 0.99) 3.54 (1.22 to 10.31) p < 0.005 HLA-DPB1 33/73 (45.2%)
24/76 (31.6%) 0.71 (0.59 to 0.86) 0.74 (0.50 to 1.08) 1.79 (0.86 to
3.71) p < 0.05 HLA-DPB1 26/73 (35.6%) 15/76 (19.7%) 0.72 (0.59
to 0.87) 0.76 (0.50 to 1.14) 2.25 (1.01 to 5.02) p < 0.05
HLA-DPB1 35/73 (47.9%) 26/76 (34.2%) 0.70 (0.59 to 0.85) 0.74 (0.50
to 1.08) 1.77 (0.86 to 3.65) p < 0.05 HLA-DPB1 29/73 (39.7%)
18/76 (3.7%) 0.70 (0.58 to 0.85) 0.79 (0.53 to 1.17) 2.12 (0.98 to
4.57) p < 0.05 ICAM1 30/282 (10.6%) 30/268 (11.2%) 0.39 (0.25 to
0.63) 0.83 (0.38 to 1.82) 0.94 (0.39 to 2.31) p < 0.05 ICAM1
31/282 (11.0%) 37/268 (13.8%) 0.39 (0.25 to 0.60) 0.85 (0.40 to 0
1.79) 0.77 (0.33 to 1.80) p < 0.05 ICAM3 19/70 (27.1%) 31/62
(50.0%) 0.71 (0.59 to 0.86) 0.93 (0.63 to 1.36) 0.37 (0.17 to 0.82)
p < 0.05 ICAM3 14/70 (20.0%) 25/62 (40.3%) 0.71 (0.58 to 0.86)
0.97 (0.65 to 1.44) 0.37 (0.16 to 0.85) p < 0.05 IGF2R 5/24
(20.8%) 15/22 (68.2%) 0.75 (0.63 to 0.88) 0.88 (0.59 to 1.31) 0.12
(0.03 to 0.48) p < 0.05 IL1A 4/132 (3.0%) 14/144 (9.7%) 1.40
(0.90 to 2.15) 0.60 (0.25 to 1.40) 0.29 (0.08 to 1.10) p < 0.05
IL1RN 15/121 (12.4%) 8/115 (7.0%) 0.75 (0.55 to 1.03) 0.52 (0.28 to
0.97) 1.89 (0.68 to 5.27) p < 0.05 IL1RN 20/121 (16.5%) 12/115
(10.4%) 0.68 (0.49 to 0.95) 0.52 (0.28 to 1.00) 1.70 (0.68 to 4.28)
p < 0.05 IL1RN 20/121 (16.5%) 12/115 (10.4%) 0.66 (0.48 to 0.90)
0.51 (0.28 to 0.94) 1.70 (0.69 to 4.21) p < 0.05 IL1RN 60/121
(49.6%) 48/115 (41.7%) 0.77 (0.63 to 0.94) 0.64 (0.43 to 0.95) 1.37
(0.75 to 2.51) p < 0.05 IL1RN 45/121 (37.2%) 28/115 (24.3%) 0.74
(0.60 to 0.92) 0.67 (0.44 to 1.01) 1.84 (0.96 to 3.54) p < 0.05
IL1RN 61/121 (50.4%) 49/115 (42.6%) 0.75 (0.62 to 0.92) 0.65 (0.44
to 0.96) 1.37 (0.75 to 2.50) p < 0.05 IL1RN 51/121 (42.1%)
35/115 (30.4%) 0.75 (0.61 to 0.93) 0.66 (0.44 to 0.99) 1.67 (0.89
to 3.12) p < 0.05 IL6ST 19/37 (51.4%) 11/37 (29.7%) 0.75 (0.63
to 0.89) 0.72 (0.48 to 1.07) 2.49 (0.93 to 6.72) p < 0.05 IL6ST
19/37 (51.4%) 11/37 (29.7%) 0.75 (0.64 to 0.89) 0.69 (0.46 to 1.02)
2.49 (0.93 to 6.72) p < 0.05 LRP8 32/244 (13.1%) 51/235 (21.7%)
1.21 (0.88 to 1.67) 0.70 (0.39 to 1.25) 0.54 (0.27 to 1.10) p <
0.05 MTRR 5/22 (22.7%) 16/28 (57.1%) 0.71 (0.61 to 0.84) 1.04 (0.68
to 1.59) 0.22 (0.06 to 0.79) p < 0.05 MTRR 2/22 (9.1%) 13/28
(46.4%) 0.73 (0.62 to 0.87) 1.00 (0.64 to 1.56) 0.12 (0.02 to 0.60)
p < 0.05 MTRR 5/22 (22.7%) 16/28 (57.1%) 0.71 (0.60 to 0.84)
1.01 (0.66 to 1.54) 0.22 (0.06 to 0.79) p < 0.05 MTRR 2/22
(9.1%) 15/28 (53.6%) 0.74 (0.63 to 0.88) 0.95 (0.62 to 1.46) 0.09
(0.02 to 0.45) p < 0.05 NPC1 19/242 (7.9%) 36/208 (17.3%) 1.00
(0.69 to 1.45) 0.65 (0.33 to 1.30) 0.41 (0.18 to 0.94) p < 0.05
NPC1 88/242 (36.4%) 122/208 (58.7%) 1.02 (0.81 to 1.28) 0.72 (0.47
to 1.11) 0.40 (0.24 to 0.68) p < 0.0005 NPC1 59/242 (24.4%)
88/208 (42.3%) 1.01 (0.79 to 1.29) 0.73 (0.46 to 1.15) 0.44 (0.25
to 0.77) p < 0.005 NPC1 90/242 (37.2%) 125/208 (60.1%) 1.03
(0.81 to 1.29) 0.71 (0.46 to 1.09) 0.39 (0.23 to 0.67) p <
0.0005 NPC1 68/242 (28.1%) 101/208 (48.6%) 1.03 (0.81 to 1.31) 0.73
(0.47 to 1.13) 0.41 (0.24 to 0.71) p < 0.0005 NPC1 117/324
(36.1%) 174/335 (51.9%) 1.01 (0.77 to 1.32) 0.76 (0.47 to 1.23)
0.52 (0.31 to 0.69) p < 0.05 NPC1 81/324 (25.0%) 122/335 (36.4%)
1.07 (0.80 to 1.42) 0.72 (0.44 to 1.20) 0.58 (0.33 to 1.03) p <
0.05 NPC1 3/324 (0.9%) 15/335 (4.5%) 1.30 (0.71 to 2.39) 0.83 (0.27
to 2.53) 0.20 (0.04 to 0.97) p < 0.05 NPC1 119/324 (36.7%)
177/335 (52.8%) 1.02 (0.77 to 1.33) 0.75 (0.47 to 1.21) 0.52 (0.30
to 0.88) p < 0.05 NPC1 3/324 (0.9%) 15/335 (4.5%) 1.25 (0.68 to
2.30) 0.83 (0.27 to 2.55) 0.20 (0.04 to 0.98) p < 0.05 NPC1
93/324 (28.7%) 140/335 (41.8%) 1.07 (0.81 to 1.42) 0.73 (0.45 to
1.20) 0.56 (0.32 to 0.97) p < 0.05 PEMT 34/305 (11.1%) 31/275
(11.3%) 0.42 (0.27 to 0.65) 0.87 (0.42 to 1.82) 0.99 (0.43 to 2.28)
p < 0.05 PLAU 19/77 (24.7%) 38/78 (48.7%) 0.77 (0.63 to 0.93)
0.86 (0.58 to 1.29) 0.35 (0.16 to 0.73) p < 0.05 PON1 33/144
(22.9%) 54/133 (40.6%) 0.77 (0.62 to 0.95) 0.90 (0.59 to 1.37) 0.44
(0.23 to 0.81) p < 0.05 PON1 7/144 (4.9%) 4/133 (3.0%) 0.83
(0.40 to 1.73) 0.32 (0.09 to 1.18) 1.65 (0.30 to 9.06) p < 0.05
PON1 7/144 (4.9%) 4/133 (3.0%) 0.95 (0.44 to 2.03) 0.34 (0.09 to
1.33) 1.65 (0.29 to 9.33) p < 0.05 SELP 12/59 (20.3%) 2/47
(4.3%) 0.68 (0.54 to 0.86) 0.63 (0.38 to 1.06) 5.74 (1.17 to 28.28)
p < 0.05 SELP 29/59 (49.2%) 17/47 (36.2%) 0.81 (0.68 to 0.97)
0.62 (0.42 to 0.91) 1.71 (0.74 to 3.92) p < 0.05 SELP 16/59
(27.1%) 3/47 (6.4%) 0.82 (0.65 to 1.05) 0.69 (0.41 to 1.16) 5.45
(1.41 to 21.13) p < 0.05 SERPINA1 2/73 (2.7%) 11/79 (13.9%) 1.03
(0.70 to 1.51) 0.38 (0.15 to 0.86) 0.17 (0.03 to 0.92) p < 0.005
SERPINA1 1/73 (1.4%) 5/79 (6.3%) 0.87 (0.51 to 1.48) 0.23 (0.07 to
0.79) 0.21 (0.02 to 2.10) p < 0.05 TAP1 2/49 (4.1%) 9/42 (21.4%)
0.85 (0.64 to 1.12) 0.54 (0.29 to 1.01) 0.16 (0.03 to 0.82) p <
0.05 TGFB1 4/162 (2.5%) 8/162 (4.9%) 1.79 (1.03 to 3.13) 0.26 (0.08
to 0.85) 0.49 (0.11 to 2.23) p < 0.0005 TGFB1 8/162 (4.9%)
12/162 (7.4%) 1.50 (0.96 to 2.34) 0.48 (0.20 to 1.16) 0.65 (0.20 to
2.09) p < 0.005 TGFB1 60/162 (37.0%) 60/162 (37.0%) 0.91 (0.73
to 1.14) 0.58 (0.38 to 0.90) 1.00 (0.56 to 1.77) p < 0.05 TGFB1
5/162 (3.1%) 10/162 (6.2%) 1.95 (1.13 to 3.38) 0.30 (0.10 to 0.93)
0.48 (0.12 to 1.99) p < 0.0005 TGFB1 5/162 (3.1%) 10/162 (6.2%)
1.90 (1.09 to 3.30) 0.30 (0.10 to 0.93) 0.48 (0.12 to 2.00) p <
0.0005 TGFB1 62/162 (38.3%) 70/162 (43.2%) 0.94 (0.76 to 1.17) 0.59
(0.39 to 0.90) 0.81 (0.47 to 1.43) p < 0.05 TGFB1 27/162 (16.7%)
30/162 (18.5%) 1.57 (1.16 to 2.12) 0.72 (0.40 to 1.27) 0.88 (0.41
to 1.87) p < 0.005 TGFB1 5/162 (3.1%) 3/162 (1.9%) 2.00 (1.14 to
3.51) 0.48 (0.14 to 1.67) 1.69 (0.30 to 9.36) p < 0.05 TGFB1
6/162 (3.7%) 15/162 (9.3%) 1.35 (0.88 to 2.07) 0.68 (0.29 to 1.61)
0.38 (0.11 to 1.24) p < 0.05 TLR5 5/34 (14.7%) 20/31 (64.5%)
0.81 (0.68 to 0.96) 0.72 (0.49 to 1.07) 0.09 (0.03 to 0.32) p <
0.005 TLR5 4/34 (11.8%) 18/31 (58.1%) 0.86 (0.72 to 1.03) 0.64
(0.42 to 0.98) 0.10 (0.03 to 0.35) p < 0.005 TLR5 6/34 (17.6%)
21/31 (67.7%) 0.81 (0.69 to 0.97) 0.70 (0.47 to 1.04) 0.10 (0.03 to
0.34) p < 0.005 TLR5 6/34 (17.6%) 19/31 (61.3%) 0.84 (0.71 to
1.00) 0.68 (0.45 to 1.02) 0.14 (0.04 to 0.44) p < 0.05 TNF 2/56
(3.6%) 5/30 (16.7%) 1.11 (0.77 to 1.61) 0.57 (0.25 to 1.30) 0.19
(0.03 to 1.13) p < 0.05 TNF 4/56 (7.1%) 7/30 (23.3%) 0.80 (0.61
to 1.05) 0.44 (0.24 to 0.81) 0.25 (0.06 to 1.01) p < 0.05 TNF
20/56 (35.7%) 22/30 (73.3%) 0.79 (0.67 to 0.94) 0.76 (0.51 to 1.12)
0.20 (0.07 to 0.56) p < 0.05 TNF 20/56 (35.7%) 22/30 (73.3%)
0.79 (0.67 to 0.94) 0.73 (0.50 to 1.08) 0.20 (0.07 to 0.56) p <
0.05 ABCC8 20/197 (10.2%) 24/197 (12.2%) 1.21 (0.84 to 1.73) 0.55
(0.28 to 1.08) 0.81 (0.35 to 1.91) p < 0.05 ADAMTS13 18/274
(6.6%) 40/259 (15.4%) 0.62 (0.42 to 0.91) 0.88 (0.44 to 1.76) 0.38
(0.17 to 0.89) p < 0.05 ADAMTS13 17/274 (6.2%) 39/259 (15.1%)
0.65 (0.44 to 0.96) 0.91 (0.45 to 1.83) 0.37 (0.16 to 0.87) p <
0.05 ADAMTS13 127/274 (46.4%) 93/259 (35.9%) 0.80 (0.63 to 1.03)
0.80 (0.51 to 1.25) 1.54 (0.92 to 2.60) p < 0.005 APOE 29/373
(7.8%) 57/390 (14.6%) 0.51 (0.32 to 0.80) 0.91 (0.42 to 1.97) 0.49
(0.21 to 1.15) p < 0.05 BCL2A1 7/102 (6.9%) 13/95 (13.7%) 0.53
(0.39 to 0.72) 0.99 (0.55 to 1.78) 0.46 (0.16 to 1.36) p < 0.05
BCL2A1 4/102 (3.9%) 10/95 (10.5%) 0.55 (0.38 to 0.78) 1.09 (0.54 to
2.20) 0.35 (0.09 to 1.29) p < 0.05 BCL2A1 7/102 (6.9%) 11/95
(11.6%) 0.52 (0.38 to 0.71) 1.09 (0.58 to 2.03) 0.56 (0.19 to 1.70)
p < 0.05 BCL2A1 7/102 (6.9%) 13/95 (13.7%) 0.51 (0.38 to 0.70)
1.00 (0.55 to 1.82) 0.46 (0.16 to 1.36) p < 0.05 CCL4 1.28 (0.78
to 2.09) 0.31 (0.10 to 0.94) p < 0.005 CCL4 1.17 (0.81 to 1.70)
0.40 (0.17 to 0.91) p < 0.005 CCL4 0.87 (0.72 to 1.04) 0.55
(0.36 to 0.83) p < 0.05 CCL4 1.30 (0.82 to 2.06) 0.31 (0.11 to
0.88) p < 0.005 CCL4 1.30 (0.82 to 2.06) 0.28 (0.10 to 0.81) p
< 0.005 CCL4 0.86 (0.72 to 1.03) 0.55 (0.37 to 0.82) p < 0.05
CD6 36/115 (31.3%) 42/76 (55.3%) 0.81 (0.67 to 0.98) 0.78 (0.53 to
1.14) 0.37 (0.19 to 0.72) p < 0.05 CD6 38/115 (33.0%) 43/76
(56.6%) 0.83 (0.69 to 1.00) 0.74 (0.50 to 1.08) 0.38 (0.19 to 0.74)
p < 0.05 CD6 14/115 (12.2%) 22/76 (28.9%) 1.06 (0.84 to 1.33)
1.36 (0.84 to 2.18) 0.34 (0.15 to 0.78) p < 0.005 CD6 3/62
(4.8%) 5/67 (7.5%) 0.52 (0.37 to 0.74) 1.12 (0.56 to 2.25) 0.63
(0.13 to 3.02) p < 0.05 CD6 6/62 (9.7%) 7/67 (10.4%) 0.54 (0.40
to 0.73) 1.13 (0.61 to 2.08) 0.92 (0.27 to 3.17) p < 0.05
COL11A1 3/73 (4.1%) 8/60 (13.3%) 0.83 (0.63 to 1.09) 0.48 (0.26 to
0.88) 0.28 (0.07 to 1.18) p < 0.05 COL11A1 3/73 (4.1%) 7/60
(11.7%) 0.89 (0.67 to 1.20) 0.45 (0.24 to 0.86) 0.32 (0.07 to 1.42)
p < 0.05 COL11A1 3/73 (4.1%) 8/60 (13.3%) 0.84 (0.64 to 1.11)
0.45 (0.24 to 0.84) 0.28 (0.07 to 1.18) p < 0.05 CYP4F2 24/144
(16.7%) 9/125 (7.2%) 0.73 (0.53 to 1.00) 0.68 (0.36 to 1.25) 2.58
(1.00 to 6.65) p < 0.05 CYP4F2 3/144 (2.1%) 4/125 (3.2%) 0.45
(0.25 to 0.79) 1.94 (0.65 to 5.74) 0.64 (0.11 to 3.69) p < 0.005
CYP4F2 6/144 (4.2%) 4/125 (3.2%) 0.54 (0.35 to 0.84) 1.40 (0.62 to
3.20) 1.32 (0.31 to 5.62) p < 0.05 CYP4F2 3/144 (2.1%) 4/125
(3.2%) 0.54 (0.32 to 0.90) 1.65 (0.61 to 4.47) 0.64 (0.12 to 3.55)
p < 0.05 CYP4F2 3/144 (2.1%) 4/125 (3.2%) 0.52 (0.31 to 0.87)
1.65 (0.61 to 4.50) 0.64 (0.12 to 3.56) p < 0.05 FCGR2A 24/355
(6.8%) 62/377 (16.4%) 0.92 (0.59 to 1.44) 1.05 (0.49 to 2.29) 0.37
(0.16 to 0.87) p < 0.005 FCGR2A 42/355 (11.8%) 88/377 (23.3%)
0.90 (0.61 to 1.32) 0.78 (0.40 to 1.53) 0.44 (0.21 to 0.91) p <
0.05 GAPD 4/62 (6.5%) 11/60 (18.3%) 0.88 (0.66 to 1.16) 0.48 (0.26
to 0.88) 0.31 (0.09 to 1.11) p < 0.05 GAPD 4/62 (6.5%) 9/60
(15.0%) 0.87 (0.65 to 1.16) 0.47 (0.25 to 0.87) 0.39 (0.10 to 1.46)
p < 0.05 GAPD 5/62 (8.1%) 10/60 (16.7%) 0.99 (0.74 to 1.33) 0.43
(0.23 to 0.82) 0.44 (0.13 to 1.50) p < 0.05 GAPD 3/62 (4.8%)
9/60 (15.0%) 0.89 (0.66 to 1.19) 0.50 (0.26 to 0.94) 0.29 (0.07 to
1.21) p < 0.05 GAPD 4/62 (6.5%) 11/60 (18.3%) 0.86 (0.64 to
1.14) 0.49 (0.27 to 0.89) 0.31 (0.08 to 1.11) p < 0.05 IL12A
20/277 (7.2%) 19/267 (7.1%) 0.37 (0.22 to 0.61) 0.88 (0.38 to 2.06)
1.02 (0.37 to 2.80) p < 0.05 IL12A 41/277 (14.8%) 40/267 (15.0%)
0.40 (0.28 to 0.57) 0.85 (0.46 to 1.58) 0.99 (0.47 to 2.05) p <
0.005 IL9 2/23 (6.1%) 5/24 (20.8%) 0.81 (0.63 to 1.04) 0.33 (0.17
to 0.65) 0.25 (0.04 to 1.45) p < 0.05 IL9 2/33 (6.1%) 5/24
(20.8%) 0.83 (0.64 to 1.07) 0.31 (0.16 to 0.62) 0.25 (0.04 to 1.46)
p < 0.005 IL9 2/33 (6.1%) 5/24 (20.8%) 0.83 (0.64 to 1.07) 0.35
(0.17 to 0.70) 0.25 (0.04 to 1.46) p < 0.05 IL9 2/33 (6.1%) 5/24
(20.8%) 0.80 (0.62 to 1.03) 0.34 (0.17 to 0.66) 0.25 (0.04 to 1.46)
p < 0.05 KLK14 11/160 (6.9%) 35/156 (22.4%) 0.84 (0.60 to 1.18)
0.69 (0.37 to 1.29) 0.26 (0.10 to 0.62) p < 0.05 KLK14 10/160
(6.3%) 33/156 (21.2%) 0.82 (0.58 to 1.16) 0.70 (0.37 to 1.34) 0.25
(0.10 to 0.62) p < 0.05 KLK14 7/160 (4.4%) 25/156 (16.0%) 0.84
(0.58 to 1.25) 0.76 (0.36 to 1.59) 0.24 (0.08 to 0.70) p < 0.05
KLK14 9/160 (5.6%) 15/156 (9.6%) 1.04 (0.71 to 1.53) 0.46 (0.23 to
0.95) 0.56 (0.20 to 1.60) p < 0.05 KLK14 9/160 (5.6%) 32/156
(20.5%) 0.88 (0.62 to 1.25) 0.76 (0.40 to 1.47) 0.23 (0.09 to 0.60)
p < 0.05 KLK14 10/160 (6.3%) 32/156 (20.5%) 0.81 (0.57 to 1.16)
0.75 (0.39 to 1.46) 0.26 (0.10 to 0.66) p < 0.05 KLK14 11/160
(6.9%) 35/156 (22.4%) 0.82 (0.58 to 1.16) 0.69 (0.36 to 1.30) 0.26
(0.10 to 0.63) p < 0.05 LAMA5 9/221 (4.1%) 23/215 (10.7%) 1.03
(0.69 to 1.53) 0.52 (0.24 to 1.10) 0.26 (0.13 to 0.97) p < 0.05
LAMA5 12/221 (5.4%) 27/215 (12.6%) 0.97 (0.69 to 1.38) 0.53 (027 to
1.03) 0.40 (0.16 to 0.98) p < 0.05 LAMA5 17/221 (7.7%) 32/215
(14.9%) 0.89 (0.64 to 1.25) 0.51 (0.27 to 0.96) 0.48 (0.21 to 1.08)
p < 0.05 MARK3 1.03 (0.65 to 1.65) 0.58 (0.26 to 1.31) p <
0.05 MARK3 1.00 (0.68 to 1.47) 0.60 (0.30 to 1.19) p < 0.05 MJD
10/89 (11.2%) 15/100 (15.0%) 0.54 (0.40 to 0.74) 1.00 (0.55 to
1.83) 0.72 (0.27 to 1.91) p < 0.05 MJD 10/89 (11.2%) 13/100
(13.0%) 0.53 (0.38 to 0.72) 1.03 (0.56 to 1.91) 0.85 (0.31 to 2.31)
p < 0.05 MJD 10/89 (11.2%) 12/100 (12.0%) 0.51 (0.37 to 0.71)
1.14 (0.61 to 2.16) 0.93 (0.33 to 2.58) p < 0.05 MJD 10/89
(11.2%) 14/100 (14.0%) 0.53 (0.39 to 0.72) 0.98 (0.54 to 1.80) 0.78
(0.29 to 2.09) p < 0.05 MJD 9/89 (10.1%) 18/100 (18.0%) 0.70
(0.54 to 0.90) 1.15 (0.69 to 1.93) 0.51 (0.20 to 1.32) p < 0.05
MMP27 27/331 (8.2%) 46/310 (14.8%) 1.24 (0.78 to 1.97) 0.79 (0.35
to 1.78) 0.51 (0.21 to 1.25) p < 0.05 NiD2 2/115 (1.7%) 8/88
(9.1%) 1.01 (0.66 to 1.53) 0.49 (0.21 to 1.13) 0.18 (0.03 to 0.98)
p < 0.05 PECAM1 3/318 (0.9%) 19/351 (5.4%) 0.37 (0.15 to 0.91)
0.95 (0.22 to 4.14) 0.17 (0.03 to 1.03) p < 0.05 PLAB 5/87
(5.7%) 11/98 (11.2%) 0.85 (0.64 to 1.14) 0.45 (0.25 to 0.82) 0.48
(0.15 to 1.59) p < 0.05 PLAB 5/87 (5.7%) 11/98 (11.2%) 0.85
(0.63 to 1.14) 0.46 (0.25 to 0.85) 0.48 (0.15 to 1.59) p < 0.05
PLAB 5/87 (5.7%) 6/98 (6.1%) 0.94 (0.66 to 1.32) 0.39 (0.19 to
0.80) 0.93 (0.24 to 3.57) p < 0.05 PLAB 6/87 (6.9%) 8/98 (8.2%)
0.89 (0.66 to 1.21) 0.47 (0.25 to 0.87) 0.83 (0.25 to 2.77) p <
0.05 PLAB 5/87 (5.7%) 10/98 (10.2%) 0.88 (0.65 to 1.20) 0.45 (0.24
to 0.85) 0.54 (0.16 to 1.81) p < 0.05 PLAB 5/87 (5.7%) 11/98
(11.2%) 0.83 (0.62 to 1.11) 0.46 (0.25 to 0.84) 0.48 (0.15 to 1.59)
p < 0.05 PTPN21 6/177 (3.4%) 16/162 (9.9%) 1.19 (0.73 to 1.95)
0.51 (0.20 to 1.29) 0.32 (0.09 to 1.11) p < 0.05 PTPN21 6/172
(3.5%) 15/155 (9.7%) 1.10 (0.68 to 1.79) 0.51 (0.21 to 1.28) 0.34
(0.10 to 1.17) p < 0.05 QSCN6 5/38 (13.2%) 5/42 (11.9%) 0.53
(0.38 to 0.73) 1.15 (0.58 to 2.27) 1.12 (0.27 to 4.62) p < 0.05
SERPINA1 22/298 (7.4%) 18/277 (6.5%) 0.47 (0.32 to 0.68) 0.86 (0.41
to 1.80) 1.15 (0.48 to 2.74) p < 0.05 SERPINB6 41/138 (29.7%)
69/138 (50.0%) 0.84 (0.68 to 1.03) 0.79 (0.53 to 1.19) 0.42 (0.23
to 0.77) p < 0.05 SN 9/326 (2.8%) 34/337 (10.1%) 0.78 (0.48 to
1.26) 0.85 (0.37 to 1.96) 0.25 (0.09 to 0.73) p < 00.5 SN 32/326
(9.8%) 29/337 (8.6%) 0.48 (0.30 to 0.77) 0.93 (0.42 to 2.05) 1.16
(0.47 to 2.81) p < 0.05 SN 15/326 (4.6%) 43/337 (12.8%) 0.70
(0.45 to 1.08) 0.89 (0.42 to 1.90) 0.33 (0.13 to 0.82) p < 0.05
SN 49/326 (15.0%) 53/337 (15.7%) 0.45 (0.31 to 0.65) 0.79 (0.42 to
1.49) 0.95 (0.47 to 1.93) p < 0.05 SN 92/326 (28.2%) 114/337
(33.8%) 0.57 (0.42 to 0.77) 0.91 (0.54 to 1.52) 0.77 (0.43 to 1.36)
p < 0.05 TGFB1 5/244 (2.0%) 12/254 (4.7%) 2.23 (1.15 to 4.34)
0.40 (0.11 to 1.43) 0.42 (0.09 to 1.93) p < 0.005 TGFB1 9/244
(3.7%) 20/254 (7.9%) 1.87 (1.10 to 3.19) 0.59 (0.22 to 1.55) 0.45
(0.14 to 1.46) p < 0.005 TGFB1 81/244 (33.2%) 86/254 (33.9%)
0.93 (0.73 to 1.20) 0.60 (0.38 to 0.95) 0.97 (0.56 to 1.67) p <
0.05 TGFB1 61/244 (2.5%) 15/254 (5.9%) 2.39 (1.24 to 4.63) 0.46
(0.14 to 1.58) 0.40 (0.09 to 1.71) p < 0.0005 TGFB1 6/244 (2.5%)
15/254 (5.9%) 2.39 (1.24 to 4.63) 0.44 (0.13 to 1.49) 0.40 (0.09 to
1.71) p < 0.0005 TLR6 17/276 (6.2%) 5/253 (2.0%) 0.61 (0.33 to
1.12) 0.53 (0.17 to 1.69) 3.26 (0.82 to 12.92) p < 0.05 TLR6
19/276 (6.9%) 5/253 (2.0%) 0.60 (0.33 to 1.08) 0.57 (0.19 to 1.71)
3.67 (0.95 to 14.17) p < 0.005 TLR6 18/276 (6.5%) 5/253 (2.0%)
0.60 (0.33 to 1.08) 0.57 (0.19 to 1.71) 3.46 (0.89 to 13.42) p <
0.05 VEGF 1/51 (2.0%) 2/34 (5.9%) 1.29 (0.82 to 2.03) 0.33 (0.11
to
0.94) 0.32 (0.03 to 4.09) p < 0.05 VEGF 1/51 (2.0%) 2/34 (5.9%)
1.26 (0.80 to 1.99) 0.33 (0.11 to 0.95) 0.32 (0.03 to 4.09) p <
0.05 *Results of the Overall Score Test (chi-square test) for the
logistic regression model in which the qualitative phenotype is a
function of SNP genotype, treatment group, and the interaction
between SNP genotype and treatment group. **Results of the
chi-square test of the interaction between SNP genotype and
treatment group (based on the logistic regression model).
[0487]
15TABLE 9 RMI_Logistic Regression Endpoint Public Marker
Genotype/mode Strata Confounder Prisk est.sup.a RMI(fatal MI,
confirmed non-fatal MI) A2M hCV517658 Het(CT) All statin, hx_smoke*
0.026 RMI(fatal MI, confirmed non-fatal MI) ENPP1 hCV1207994
Het(CA) All statin 0.0706 RMI(fatal MI, confirmed non-fatal MI)
IGF1R hCV8722981 Het(TC) All statin 0.0039 RMI(fatal MI, confirmed
non-fatal MI) IRF3 hCV7798230 Rec(GG) All statin 0.0071 RMI(fatal
MI, confirmed non-fatal MI) LRP2 hCV16165996 Rec(TT) All statin
0.0324 RMI(fatal MI, confirmed non-fatal MI) MC3R hCV22274632
Het(CA) All statin, hx_smoke* 0.0565 RMI(fatal MI, confirmed
non-fatal MI) MC3R hCV25640926 Het(GA) All statin, hx_smoke* 0.0264
RMI(fatal MI, confirmed non-fatal MI) MC3R hCV9485713 Het(CT) All
statin, hx_smoke* 0.0225 Case Endpoint RR.sup.b 95% CI.sup.c
case.sup.d AF(%).sup.e control.sup.f Control AF(%).sup.g RMI(fatal
MI, confirmed non-fatal MI) 1.34 1.04-1.71 130 51.8 1137 44.8
RMI(fatal MI, confirmed non-fatal MI) 1.28 0.98-1.65 73 28.9 616
24.2 RMI(fatal MI, confirmed non-fatal MI) 2.01 1.26-3.06 17 6.7 80
3.1 RMI(fatal MI, confirmed non-fatal MI) 1.61 1.14-2.23 42 16.5
257 10.1 RMI(fatal MI, confirmed non-fatal MI) 0.45 0.21-0.93 7 2.8
160 6.3 RMI(fatal MI, confirmed non-fatal MI) 1.34 0.99-1.78 50
19.7 397 15.6 RMI(fatal MI, confirmed non-fatal MI) 1.4 1.04-1.85
51 20.1 389 15.2 RMI(fatal MI, confirmed non-fatal MI) 1.41
1.05-1.87 51 20.2 388 15.2 *History of smoking .sup.aSignificance
of risk estimated by Wald test .sup.bRelative risk .sup.c95%
confidence interval for relative risk .sup.dNumber of patients
(with the corresponding genotype or mode) developed recurrent MI
during 5 years of follow up .sup.eThe allele frequency of patients
(with the corresponding genotype or mode) developed recurrent MI
during 6 years of follow up .sup.fNumber of patients (with the
corresponding genotype or mode) had MI .sup.gThe allele frequency
of patients (with the corresponding genotype or mode) had MI RMI
Replication Between CAREand PreCARE Sample Sets Analysis 1 of CARE
samples Genotype/ Case Endpoint Public Marker mode Strata P risk
est.sup.a OR.sup.b 95% CI.sup.c case.sup.d AF(%).sup.e RMI(fatal
MI, confirmed non-fatal MI) FABP2 hCV761961 Dom(TC + AGE_T1 0.01
0.50 0.3-0.9 19 40.8 TT) RMI(fatal MI, confirmed non-fatal MI)
HLA-DPB1 hCV8851080 Rec(GG) AGE_T3 0.037 2.70 1.1-6.7 10 11.1
RMI(fatal MI, confirmed non-fatal MI) IL12RB1 hCV795442 Allelic(G)
BMI > 30.5 0.06 0.60 0.4-1.0 29 25.0 RMI(fatal MI, confirmed
non-fatal MI) KDR hCV16192174 Allelic(A) HYP_Y 0.03 1.80 1.1-3.3 28
23.5 RMI(fatal MI, confirmed non-fatal MI) KLKB1 hCV22272267 Dom(GA
+ HYP_Y 0.025 1.80 1.1-3.1 96 82.1 AA) RMI(fatal MI, confirmed
non-fatal MI) MMP7 hCV3210838 Allelic(T) AGE_T1 0.029 0.60 0.3-1.0
21 13.8 RMI(fatal MI, confirmed non-fatal MI) WRN hCV3020386
Rec(TT) AGE_T1 0.06 1.8 1.0-3.4 20 26.3 RMI(fatal MI, confirmed
non-fatal MI) LRP2 hCV16165996 Rec(TT) All 0.015 0.30 0.1-0.9 7 2.8
RMI(fatal MI, confirmed non-fatal MI) LRP8 hCV190754 Het(TC)/ APOE4
allele 0.1 1.80 0.9-3.6 28 Dom(TC + TT) RMI(fatal MI, confirmed
non-fatal MI) LRP8 hCV190754 Het(TC)/ APOE4 not 1.00 0.7-1.4 75
Dom(TC + TT) RMI(fatal MI, confirmed non-fatal MI) KDR hCV16192174
Dom(AA + APOE4 allele 0.0011 2.80 1.4-5.4 18 AG) RMI(fatal MI,
confirmed non-fatal MI) KDR hCV16192174 Dom(AA + APOE4 not 0.70
0.4-1.2 25 AG) RMI(fatal MI, confirmed non-fatal MI) KDR
hCV16192174 Dom(AA + AG) RMI(fatal MI, confirmed non-fatal MI) KDR
hCV16192174 Dom(AA + AG) RMI Replication Between CAREand PreCARE
Sample Sets Analysis 1 of CARE samples Analysis 2 of CARE Samples
Control Case Control Endpoint control.sup.f AF(%).sup.g Strata P
risk est.sup.a OR.sup.b 95% CI.sup.c case.sup.d AF(%).sup.e
control.sup.f AF(%).sup.g RMI(fatal MI, confirmed non-fatal MI) 110
25.2 AGE_T1 0.01 0.5 0.3-0.9 21 26.6 187 41.7 RMI(fatal MI,
confirmed non-fatal MI) 11 4.4 AGE_T3 0.039 1.9 1.0-3.6 19 10.7 25
5.8 RMI(fatal MI, confirmed non-fatal MI) 104 34.7 BMI > 30.5
0.006 0.5 0.4-0.8 33 23.2 182 35.7 RMI(fatal MI, confirmed
non-fatal MI) 45 14.4 HYP_Y 0.03 1.7 1.0-2.7 4 2.4 2 0.4 RMI(fatal
MI, confirmed non-fatal MI) 223 71.3 HYP_Y 0.034 1.3 1.0-1.7 180
53.6 500 46.9 RMI(fatal MI, confirmed non-fatal MI) 117 21.8 AGE_T1
0.033 0.6 0.4-1.0 23 14.6 197 22.0 RMI(fatal MI, confirmed
non-fatal MI) 43 16.3 AGE_T1 0.018 1.9 1.1-3.1 30 38.0 110 24.7
RMI(fatal MI, confirmed non-fatal MI) 65 6.2 All 0.002 0.3 0.1-0.7
11 2.8 92 7.0 RMI(fatal MI, confirmed non-fatal MI) 124 APOE4
allele 0.1 1.5 0.9-2.3 60 128 RMI(fatal MI, confirmed non-fatal MI)
389 APOE4 not 0.98 0.7-1.4 154 391 RMI(fatal MI, confirmed
non-fatal MI) 51 APOE4 allele 0.2 1.5 0.9-2.6 26 43 RMI(fatal MI,
confirmed non-fatal MI) 167 APOE4 not 1.0 0.7-1.37 RMI(fatal MI,
confirmed non-fatal MI) APOE4/2 0.0048 16.6 1.28-158 RMI(fatal MI,
confirmed non-fatal MI) APOE4 not 1.0 0.8-1.42 .sup.aSignificance
of risk estimated by Wald test .sup.bOdds ratio .sup.c95%
confidence interval for odds ratio .sup.dNumber of patients (With
the corresponding genotype or mode) developed recurrent MI during 5
years of follow up .sup.eThe allele frequency of patients (with the
corresponding genotype or mode) developed recurrent MI during 6
years of follow up .sup.fNumber of patients (with the corresponding
genotype or mode) had MI .sup.gThe allele frequency of patients
(with the corresponding genotype or mode) had MI AGE_T1 indicate
that Age < 55 AGE_T13 indicate that Age >= 64 .vertline.HYP_Y
Indicate that patients had history of hypertension Stroke
Replication Between CAREand PreCARE Sample Sets Analysis 1 of CARE
samples Endpoint Public Marker Genotype/mode Strata P risk
est.sup.a OR.sup.b 95% CI.sup.c case.sup.d Stroke ACAT2 hCV1361979
Dom(AA + GA)/Allelic(G) male 0.015 1.7 1.1-2.7 89 Stroke APOA4
hCV11482766 Rec(CC) all 0.016 3.5 1.4-9.1 6 Stroke HTR2A
hCV11696920 Rec(AA) all 0.06 5.8 1.9-18.1 5 Stroke ICAM1 hCV8726331
Rec(AA) all 0.1 3 1.2-9.3 5 Stroke ICAM1 hCV8726331 Rec(AA) male
0.01 4.8 1.6-14.3 5 Stroke KCNMB1 hCV3028206 Het(GC) male 0.019 1.7
1.1-2.7 29 Stroke Replication Between CAREand PreCARE Sample Sets
Analysis 1 of CARE samples Analysis 2 of CARE samples Case Control
Case Control Endpoint AF(%).sup.e control.sup.f AF(%).sup.g Strata
P risk est.sup.a OR.sup.b 95% CI.sup.c case.sup.d AF(%).sup.e
control.sup.f AF(%).sup.g Stroke 75.42 715 64.18 male 0.013 1.5
1.1-2.2 73 53.68 926 42.71 Stroke 4.23 16 1.24 all 0.05 3.3 1.1-9.8
4 5 20 1.59 Stroke 3.52 8 0.62 all 0.038 4.9 1.3-18.0 3 3.75 10
0.79 Stroke 3.52 14 1.09 all 0.04 2.6 0.9-10.6 3 3.75 16 1.27
Stroke 4.17 10 0.9 male 0.06 3.8 1.1-13.8 3 4.41 13 1.19 Stroke
24.58 176 15.81 male 0.074 1.7 1.0-2.9 18 26.47 193 17.69
.sup.aSignificance of risk estimated by Wald test .sup.bOdds ratio
.sup.c95% confidence interval for odds ratio .sup.dNumber of
patients (with the corresponding genotype or mode) developed
recurrent MI during 5 years of follow up .sup.eThe allele frequency
of patients (with the corresponding genotype or mode) developed
recurrent MI during 6 years of follow up .sup.fNumber of patients
(with the corresponding genotype or mode) had MI .sup.gThe allele
frequency of patients (with the corresponding genotype or mode) had
MI
[0488]
16TABLE 10 Risk of cardiovascular disease events associated with
Pravastatin by genotypes Case Y Control Y PRIMER PRIMER ALLELE
ALLELE Gene Nucleotide Nucleotide symbol hCV Freq* Freq** Stratum
Group ptrend.sup.a N aff.sup.b N unaf.sup.fc RR.sup.d RR 95%
Cl.sup.e P.sub.risk est.sup.f P.sub.int.sup.g Covars.sup.h ATF6
hCV25631989 0.04 0.08 Placebo hom(TT) vs. ref (CC) 1 5 1.49
(0.25-9.00) 0.6624 0.0069 none het(TC) vs. ref (CC) 9 185 0.42
(0.22-0.80) 0.0089 ref (CC) 128 1018 1.00 Statin hom(TT) vs. ref
(CC) 0 11 NA het(TC) vs. ref (CC) 24 189 1.53 (0.99-2.34) 0.0535
ref (CC) 85 1066 1.00 Maj Hom (CC) Statin 85 1066 0.66 (0.51-0.86)
0.0019 Placebo 128 1018 1.00 Het (TC) Statin 24 189 2.43 (1.165.10)
0.0189 Placebo 9 185 1.00 Min Hom (TT) Statin 0 11 NA Placebo 1 5
1.00 LAMA2 hCV16047108 0.06 0.07 Placebo hom(GG) vs. ref (AA) 0 7
NA 0.0057 none het(GA) vs. ref (AA) 17 147 0.98 (0.61-1.58) 0.9257
ref (AA) 128 1079 1.00 Statin hom(GG) vs. ref (AA) 2 4 4.97
(1.57-15.70) 0.0063 het(GA) vs. ref (AA) 22 140 2.02 (1.30-3.14)
0.0017 ref (AA) 84 1168 1.00 Maj Hom (AA) Statin 84 1168 0.63
(0.49-0.82) 0.0007 Placebo 128 1079 1.00 Het (GA) Statin 22 140
1.31 (0.72-2.37) 0.3732 Placebo 17 147 1.00 Min Hom (GG) Statin 2 4
NA Placebo 0 7 1.00 ITGA9 hCV25644901 0.08 0.04 Placebo dom(GA +
GG) vs. 24 105 1.92 (1.29-2.86) 0.0013 0.0093 none ref(AA) ref (AA)
121 1129 1.00 Statin dom(GA + GG) vs. 6 123 0.58 (0.26-1.31) 0.1904
ref(AA) ref (AA) 103 1192 1.00 Maj Hom (AA) Statin 103 1192 0.82
(0.64-1.06) 0.1251 Placebo 121 1129 1.00 Dom (GA + GG) Statin 6 123
0.25 (0.11-0.59) 0.0016 Placebo 24 105 1.00 LAMA5 hCV25629492 0.38
0.36 Placebo hom (GG) vs. ref (AA) 0.3885 25 172 1.26 (0.81-1.95)
0.3086 0.0173 none het(GA) vs. ref(AA) 61 532 1.02 (0.73-1.43)
0.9170 ref(AA) 59 525 1.00 Statin hom (GG) vs. 0.0193 13 193 0.64
(0.36-1.14) 0.1306 ref (AA) het(GA) vs. 36 595 0.58 (0.39-0.86)
0.0074 ref(AA) ref(AA) 57 520 1.00 Maj Hom (AA) Statin 57 520 0.98
(0.69-1.38) 0.8972 Placebo 59 525 1.00 Het(GA) Statin 36 595 0.55
(0.37-0.82) 0.0036 Placebo 61 532 1.00 Min Hom(GG) Statin 13 193
0.50 (0.26-0.94) 0.0327 Placebo 25 172 1.00 KLK14 hCV16044337 0.62
0.69 Placebo hom(AA) vs. 0.0096 23 117 1.87 (1.19-2.92) 0.0063
0.0188 none ref(GG) het(GA) vs. 64 521 1.24 (0.89-1.75) 0.2073
ref(GG) ref(GG) 57 591 1.00 Statin hom(AA) vs. ref(GG) 0.3371 6 128
0.56 (0.25-1.28) 0.1678 het(GA) vs. ref(GG) 50 570 1.01 (0.69-1.46)
0.9629 ref(GG) 53 610 1.00 Maj Hom(GG) Statin 53 610 0.91
(0.64-1.30) 0.6005 Placebo 57 591 1.00 Het(GA) Statin 50 570 0.74
(0.52-1.05) 0.0897 Placebo 64 521 1.00 Min Hom(AA) Statin 6 128
0.27 (0.11-0.65) 0.0033 Placebo 23 117 1.00 GAPD hCV8921288 0.75
0.81 Placebo hom(CC) vs. ref(AA) 0.0239 7 51 1.38 (0.67-2.86)
0.3819 0.0209 none het(AC) vs. ref(AA) 55 363 1.51 (1.09-2.09)
0.0138 ref(AA) 76 795 1.00 Statin hom(CC) vs. ref(AA) 0.1309 4 54
0.81 (0.31-2.13) 0.6634 het(AC) vs. ref(AA) 27 391 0.76 (0.50-1.15)
0.1924 ref(AA) 78 834 1.00 Maj Hom(AA) Statin 78 834 0.98
(0.72-1.33) 0.8966 Placebo 76 795 1.00 Het(AC) Statin 27 391 0.49
(0.32-0.76) 0.0015 Placebo 55 363 1.00 Min Hom(CC) Statin 4 54 0.57
(0.18-1.85) 0.3499 Placebo 7 51 1.00 CD6 hCV25922320 0.82 0.78
Placebo hom(AA) vs. ref(GG) 0.0815 4 60 0.53 (0.20-1.38) 0.1911
0.0140 HX_SMOKE_1 het(GA) vs. ref(GG) 43 415 0.80 (0.57-1.12)
0.1872 ref(GG) 98 756 1.00 Statin hom(AA) vs. ref(GG) 0.0860 3 57
0.79 (0.25-2.43) 0.6753 het(GA) vs. ref(GG) 46 395 1.65 (1.14-2.38)
0.0077 ref(GG) 59 861 1.00 Maj Hom(GG) Statin 59 861 0.55
(0.40-0.74) 0.0001 Placebo 98 756 1.00 Het(GA) Statin 46 395 1.13
(0.76-1.68) 0.5393 Placebo 43 415 1.00 Min Hom(AA) Statin 3 57 0.82
(0.19-3.49) 0.7846 Placebo 4 60 1.00 SLC18A1 hCV2715953 0.88 0.92
Placebo hom(CC) vs. ref(GG) 0.0714 4 17 1.92 (0.78-4.71) 0.1560
0.0274 none het(GC) vs. ref (GG) 26 175 1.30 (0.87-1.94) 0.1950
ref(GG) 115 1042 1.00 Statin hom(CC) vs. ref(GG) 0.1356 0 12 0.9995
het(GC) vs. ref (GG) 14 229 0.72 (0.42-1.23) 0.2295 ref(GG) 93 1063
1.00 Maj Hom(GG) Statin 93 1063 0.81 (0.62-1.05) 0.1121 Placebo 115
1042 1.00 Het(GC) Statin 14 229 0.45 (0.24-0.83) 0.0109 Placebo 26
175 1.00 Min Hom(CC) Statin 0 12 Placebo 4 17 1.00 PTPRJ hCV8895373
0.86 0.82 Placebo hom(AA)vs. ref(GG) 0.1002 2 40 0.42 (0.11-1.65)
0.2156 het(GA) vs. ref(GG) 36 360 0.81 (0.56-1.15) 0.2400 0.0209
none ref(GG) 106 834 1.00 Statin hom(AA)vs. ref(GG) 0.1045 3 36
1.14 (0.37-3.46) 0.8192 het(GA) vs. ref (GG) 41 382 1.43
(0.99-2.08) 0.0585 ref(GG) 65 897 1.00 Maj Hom(GG) Statin 65 897
0.60 (0.45-0.81) 0.0007 Placebo 106 834 1.00 Het(GA) Statin 41 382
1.07 (0.70-1.63) 0.7862 Placebo 36 360 1.00 Min Hom(AA) Statin 3 36
1.62 (0.28-9.16) 0.5881 Placebo 2 40 1.00 IL4R hCV2769554 0.38 0.46
Placebo hom(GG) vs. ref (AA) 0.0207 16 279 0.47 (0.27-0.81) 0.0067
0.0297 none het(GA) vs. ref(AA) 79 569 1.06 (0.76-1.48) 0.7287 ref
(AA) 50 385 1.00 Statin hom(GG) vs. ref(AA) 0.3773 27 292 1.26
(0.75-2.10) 0.3819 het(GA) vs. ref(AA) 55 646 1.17 (0.75-1.82)
0.4995 ref (AA) 27 374 1.00 Maj Hom(AA) Statin 27 374 0.59
(0.37-0.92) 0.0193 Placebo 50 385 1.00 Het(GA) Statin 55 646 0.64
(0.46-0.89) 0.0083 Placebo 79 569 1.00 Min Hom(GG) Statin 27 292
1.56 (0.86-2.84) 0.1445 Placebo 16 279 1.00 F7 hCV783184 0.09 0.12
Placebo hom(TT) vs. ref(GG) 0.1044 1 21 0.41 (0.06-2.79) 0.3616
0.0373 none het (TG) vs. ref(GG) 23 255 0.74 (0.49-1.14) 0.1737
ref(GG) 120 959 1.00 Statin hom(TT) vs. ref(GG) 0.1895 2 15 1.65
(0.44-6.17) 0.4568 het (TG) vs. ref(GG) 27 270 1.28 (0.84-1.94)
0.2543 ref(GG) 79 1029 1.00 Maj Hom(GG) Statin 79 1029 0.64
(0.49-0.84) 0.0013 Placebo 120 959 1.00 Het(TG) Statin 27 270 1.10
(0.65-1.87) 0.7282 Placebo 23 255 1.00 Min Hom(TT) Statin 2 15 2.59
(0.26-26.22) 0.4208 Placebo 1 21 1.00 EDG3 hCV25610470 0.95 0.96
Placebo hom(AA) vs. ref(GG) 0.5799 0 4 0.0645 HX_SMOKE het(GA) vs.
ref(GG) 13 83 1.27 (0.75-2.15) 0.3834 ref(GG) 131 1148 1.00 Statin
hom(AA) vs. ref(GG) 0.0745 0 3 het(GA) vs. ref(GG) 3 101 0.37
(0.12-1.13) 0.0818 ref(GG) 105 1205 1.00 Maj Hom(GG) Statin 105
1205 0.77 (0.61-0.98) 0.0390 Placebo 131 1148 1.00 Het(GA) Statin 3
101 0.22 (0.07-0.76) 0.0165 Placebo 13 83 1.00 Min Hom(AA) Statin 0
3 1.10 Placebo 0 4 1.00 FCAR hCV7841642 0.90 0.93 Placebo hom
(AA)vs. ref(GG) 0.0687 1 11 0.85 (0.13-5.59) 0.8656 0463 none
het(GA) vs. ref(GG) 28 159 1.53 (1.05-2.24) 0.0302 ref(GG) 116 1067
1.00 Statin hom (AA)vs. ref(GG) 0.2107 1 8 1.38 (0.22-8.83) 0.7350
het(GA) vs. ref(GG) 9 178 0.60 (0.31-1.16) 0.1283 ref(GG) 99 1129
1.00 Maj Hom(GG) Statin 99 1129 0.82 (0.64-1.06) 0.1339 Placebo 116
1067 1.00 Het(GA) Statin 9 178 0.32 (0.16-0.66) 0.0021 Placebo 28
159 1.00 Min Hom(AA) Statin 1 8 1.33 (0.10-18.57) 0.8305 Placebo 1
11 1.00 PLAB hCV7494810 0.27 0.25 Placebo hom(GG) vs. ref(CC)
0.2988 7 83 0.85 (0.41-1.80) 0.6778 0.0326 HX_SMOKE het(GC) vs.
ref(CC) 65 442 1.39 (1.01-1.90) 0.0408 ref(CC) 73 709 1.00 Statin
hom(GG) vs. ref(CC) 0.0605 5 78 0.68 (0.28-1.63) 0.3889 het(GC) vs.
ref(CC) 31 491 0.67 (0.45-1.01) 0.0534 ref(CC) 72 744 1.00 Maj
Hom(CC) Statin 72 744 0.94 (0.69-1.29) 0.7177 Placebo 73 709 1.00
Het(GC) Statin 31 491 0.46 (0.30-0.69) 0.0002 Placebo 65 442 1.00
Min Hom(GG) Statin 5 78 0.75 (0.25-2.27) 0.6137 Placebo 7 83 1.00
LPA hCV11225994 0.90 0.86 Placebo hom (AA)vs. ref(GG) 0.1018 3 21
1.09 (0.37-3.20) 0.8695 0.0412 none het(GA) vs. ref (GG) 24 300
0.65 (0.43-0.99) 0.0437 ref (GG) 117 907 1.00 Statin hom (AA)vs.
ref(GG) 0.2142 5 25 2.34 (1.02-5.35) 0.0449 het(GA) vs. ref (GG) 24
294 1.06 (0.68-1.64) 0.8037 ref (GG) 76 989 1.00 Maj Hom(GG) Statin
76 989 0.62 (0.47-0.82) 0.0008 Placebo 117 907 1.00 Het(GA) Statin
24 294 1.02 (0.59-1.76) 0.9463 Placebo 24 300 1.00 Min Hom(AA)
Statin 5 25 1.33 (0.35-5.03) 0.6709 Placebo 3 21 1.00 FN1
hCV9506149 0.24 0.28 Placebo hom(TT) vs. ref(AA) 0.2100 11 91 0.92
(0.51-1.66) 0.7735 0.0395 none het(TA) vs. ref(AA) 48 500 0.74
(0.53-1.04) 0.0846 ref(AA) 86 645 1.00 Statin hom(TT) vs. ref(AA)
0.0985 13 97 1.72 (0.97-3.06) 0.0647 het(TA) vs. ref(AA) 45 525
1.15 (0.78-1.69) 0.4814 ref(AA) 51 691 1.00 Maj Hom(AA) Statin 51
691 0.58 (0.42-0.81) 0.0015 Placebo 86 645 1.00 Het(TA) Statin 45
525 0.90 (0.61-1.33) 0.6010 Placebo 48 500 1.00 Min Hom(TT) Statin
13 97 1.10 (0.51-2.33) 0.8125 Placebo 11 91 1.00 PPOX hCV25922816
0.92 0.94 Placebo hom(AA) vs. ref(GG) 0.2414 1 4 1.98 (0.34-11.53)
0.4467 het(GA) vs. ref(GG) 21 146 1.25 (0.81-1.92) 0.3216) ref(GG)
21 146 1.00 Statin hom(AA) vs. ref(GG) 0 9 het(GA) vs. ref(GG) 10
179 0.64 0.34-1.20) 0.1636 ref(GG) 99 1095 1.00 0.0463 none Maj
Hom(GG) Statin 0.1064 99 1095 0.82 (0.64-1.06) 0.1294 Placebo 21
146 1.00 Het(GA) Statin 10 179 0.42 (0.20-0.87) 0.0191 Placebo 21
146 1.00 Min Hom(AA) Statin 0 9 Placebo 1 4 1.00 ITGA9 hCV3215409
0.48 0.42 Placebo hom(GG) vs. ref(AA) 0.0768 34 225 1.48
(0.96-2.28) 0.0745 0.0435 none het (GA)vs. ref(AA) 71 600 1.19
(0.83-1.72) 0.3480 ref(AA) 40 411 1.00 Statin hom(GG) vs. ref(AA)
0.2483 10 240 0.54 (0.27-1.06) 0.0744 het (GA)vs. ref(AA) 63 629
1.22 (0.82-1.91) 0.3180 ref(AA) 36 447 1.00 Maj Hom(AA) Statin 36
447 0.84 (0.55-1.29) 0.4297 Placebo 40 411 1.00 Het(GA) Statin 63
629 0.86 (0.62-1.19) 0.3603 Placebo 71 600 1.00 Min Hom(GG) Statin
10 240 0.30 (0.15-0.60) 0.0007 Placebo 34 225 1.00 MACF1 hCV3112686
0.46 0.42 Placebo hom(GG) vs. ref(CC) 0.1260 29 217 1.38
(0.88-2.17) 0.1603 0.0427 HX_SMOKE het(GC) vs. ref(CC) 76 592 1.32
(0.92-1.90) 0.1351 ref(CC) 40 424 1.00 Statin hom(GG) vs. ref(CC)
0.1717 12 228 0.60 (0.32-1.12) 0.1110 het(GC) vs. ref(CC) 55 620
0.98 (0.67-1.44) 0.9179 ref(CC) 42 466 1.00 Maj Hom(CC) Statin 42
466 0.96 (0.63-1.45) 0.8310 Placebo 40 424 1.00 Het(GC) Statin 55
620 0.71 (0.51-0.99) 0.0417 Placebo 76 592 1.00 Min Hom(GG) Statin
12 228 0.42 (0.22-0.80) 0.0082 Placebo 29 217 1.00 IL4R hCV2351160
0.23 0.20 Placebo hom (GG)vs. ref(AA) 0.0514 8 46 1.46 (0.75-2.85)
0.2677 0.0570 HX_SMOKE het(GA) vs. ref(AA) 50 393 1.13 (0.82-1.57)
0.4552 ref(AA) 86 789 1.00 Statin hom (GG)vs. ref(AA) 0.1343 3 56
0.61 (0.20-1.88) 0.3887 het(GA) vs. ref(AA) 31 447 0.76 (0.51-1.14)
0.1889 ref(AA) 75 811 1.00 Maj Hom(AA) Statin 75 811 0.85
(0.63-1.14) 0.2842 Placebo 86 789 1.00 Het(GA) Statin 31 447 0.57
(0.37-0.88) 0.0109 Placebo 50 393 1.00 Min Hom(GG) Statin 3 56 0.36
(0.10-1.27) 0.1118 Placebo 8 46 1.00 ABCA1 hCV2741051 0.21 0.28
Placebo hom(TT) vs. ref(CC) 0.0149 6 84 0.54 (0.24-1.16) 0.1188
0.0369 none het(TC) vs. ref(CC) 49 516 0.70 (0.50-0.97) 0.0338
ref(CC) 90 637 1.00 Statin hom(TT) vs. ref(CC) 0.5954 9 99 1.14
(0.57-2.19) 0.6981 het(TC) vs. ref(CC) 48 555 1.09 (0.75-1.58)
0.6440 ref(CC) 52 662 1.00 Maj Hom(CC) Statin 52 662 0.59
(0.42-0.82) 0.0013 Placebo 90 637 1.00 Het(TC) Statin 48 555 0.92
(0.62-1.34) 0.6594 Placebo 49 516 1.00 Min Hom(TT) Statin 9 99 1.25
(0.45-3.15) 0.6596 Placebo 6 84 1.00 ABCA1 hCV2741083 0.93 0.87
Placebo hom (CC)vs. ref(TT) 0.0054 1 18 0.15 (0.06-2.51) 0.395
0.0051 none het(TC)vs. ref(TT) 18 275 0.52 (0.32-0.84) 0.0063
ref(TT) 126 943 1.00 Statin hom (CC)vs. ref(TT) 0.3109 2 26 1.00
(0.25-3.46) 0.9946 het(TC)vs. ref(TT) 30 294 1.29 (0.86-1.91)
0.2178 ref(TT) 77 996 1.00 Maj Hom(TT) Statin 77 996 0.61
(0.46-0.80) 0.0003 Placebo 126 943 1.00 Het(TC) Statin 30 294 1.51
(0.86-2.57) 0.1517 Placebo 18 275 1.00 Min Hom(CC) Statin 2 26 1.36
(0.12-9.07) 0.7966 Placebo 1 18 1.00 CYBA hCV2038 0.33 0.34 Placebo
hom(AA) vs. ref(GG) 0.6072 14 149 0.81 (0.46-1.40) 0.4414 0.0260
$$x_smoke het(AG) vs. ref(GG) 68 555 1.05 (0.76-1.44) 0.7862
ref(GG) 63 533 1.00 Statin hom(AA) vs. ref(GG) 0.0086 18 132 2.02
(1.18-3.44) 0.0102 het(AG) vs. ref(GG) 55 612 1.40 (0.94-2.10)
0.1009 ref(GG) 36 571 1.00 Maj Hom(GG) Statin 36 571 0.55
(0.37-0.82) 0.0031 Placebo 63 533 1.00 Het(AG) Statin 55 612 0.74
(0.53-1.04) 0.0821 Placebo 68 555 1.00 Min Hom(AA) Statin 18 132
1.38 (0.72-2.68) 0.3354 Placebo 14 149 1.00 HLA-DPB1 hCV8851085
0.81 0.77 Placebo hom(AA) vs. ref(GG) 0.2553 4 66 0.53 (0.19-1.34)
0.6898 0.0154 $$x_smoke het (GA)vs. ref(GG) 48 424 0.93 (0.66-1.29)
0.6823 ref(GG) 92 745 1.00 Statin hom(AA) vs. ref(GG) 0.021 8 53
1.97 (0.96-3.77) 0.0645 het (GA)vs. ref(GG) 43 445 1.40 (0.95-2.02)
0.085 ref(GG) 58 814 1.00 Maj Hom(GG) Statin 58 814 0.58
(0.42-0.80) 0.0009 Placebo 92 745 1.00 Het(GA) Statin 43 445 0.87
(0.58-1.29) 0.0501 Placebo 48 424 1.00 Min Hom(AA) Statin 8 53 2.19
(0.68-5.87) 0.1805 Placebo 4 66 1.00 HSPG2 hCV1603656 0.10 0.08
Placebo hom(TT) vs. ref(CC) 0.1704 2 6 2.46 (0.60-6.24) 0.1954
0.0334 $$x_smoke het (TC)vs. ref(CC) 25 177 1.23 (0.81-1.83) 0.3189
ref(CC) 118 1054 1.00 Statin hom(TT) vs. ref(CC) 0.1033 0 11 N/A
0.9771 het (TC)vs. ref(CC) 11 196 0.65 (0.35-1.18) 0.1607 ref(CC)
98 1105 1.00 Maj Hom (CC) Statin 98 1105 0.80 (0.62-1.04) 0.0908
Placebo 118 1054 1.00 Het(TC) Statin 11 196 0.42 (0.21-0.84) 0.013
Placebo 25 177 1.00 Min Hom(TT) Statin 0 11 N/A 0.9745 Placebo 2 6
1.00 HSPG2 hCV1603692 0.08 0.06 Placebo hom(TT) vs. ref(CC) 0.1106
1 4 1.98 (0.27-6.86) 0.4769 0.0427 none het (TC)vs. ref(CC) 21 130
1.37 (0.88-2.07) 0.1542 ref(CC) 123 1093 1.00 Statin hom(TT) vs.
ref(CC) 0.1801 0 6 N/A 0.9829 het (TC)vs. ref(CC) 8 146 0.65
(0.22-1.28) 0.2175 ref(CC) 101 1157 1.00 Maj Hom (CC) Statin 101
1157 0.79 (0.61-1.02) 0.0712 Placebo 123 1093 1.00 Het(TC) Statin 8
146 0.37 (0.17-0.82) 0.0125 Placebo 21 130 1.00 Min Hom(TT) Statin
0 6 N/A 0.9814 Placebo 1 4 1.00 HSPG2 hCV1603697 0.08 0.06 Placebo
hom(TT) vs. ref(CC) 0.0951 1 4 1.99 (0.34-11.59) 0.4431 0.0447 none
het (TC)vs. ref(CC) 21 129 1.39 (0.91-2.14) 0.1303 ref(CC) 123 1102
1.00 Statin hom(TT) vs. ref(CC) 0.1749 0 6 N/A 0.9994 het (TC)vs.
ref(CC) 8 145 0.65 (0.32-1.32) 0.2342 ref(CC) 101 1162 1.00 Maj Hom
(CC) Statin 101 1162 0.80 (0.62-1.02) 0.0757 Placebo 123 1102 1.00
Het(TC) Statin 8 145 0.37 (0.17-0.82) 0.0136 Placebo 21 129 1.00
Min Hom(TT) Statin 0 6 N/A 0.9994 Placebo 1 4 1.00 HSPG2
hCV16172339 0.08 0.06 Placebo hom(TT) vs. ref(CC) 0.0927 1 4 2.00
(0.27-6.94) 0.4689 0.0927 none het (TC)vs. ref(CC) 21 128 1.41
(0.91-2.13) 0.1233 ref(CC) 122 1100 1.00
Statin hom(TT) vs. ref(CC) 0.1728 0 6 N/A 0.983 het (TC)vs. ref(CC)
8 144 0.66 (0.32-1.30) 0.2343 ref(CC) 101 1160 1.00 Maj Hom (CC)
Statin 101 1160 0.80 (0.62-1.03) 0.086 Placebo 122 1100 1.00
Het(TC) Statin 8 144 0.37 (0.16-0.82) 0.0124 Placebo 21 128 1.00
Min Hom(TT) Statin 0 6 N/A 0.9815 Placebo 1 4 1.00 NPC1 hCV25472673
0.53 0.62 Placebo hom(CC) vs. ref(TT) 0.0037 33 173 1.96
(1.28-2.91) 0.0023 0.0093 none het(TC) vs. ref(TT) 70 602 1.28
(0.88-1.82) 0.1935 ref(TT) 41 461 1.00 Statin hom(CC) vs. ref(TT)
0.4107 18 215 0.87 (0.51-1.45) 0.6102 het(TC) vs. ref(TT) 43 601
0.76 (0.50-1.12) 0.1642 ref(TT) 48 495 1.00 Maj Hom(TT) Statin 48
495 1.08 (0.72-1.60) 0.6973 Placebo 41 461 1.00 Het(TC) Statin 43
601 0.61 (0.44-0.92) 0.013 Placebo 70 602 1.00 Min Hom(CC) Statin
18 215 0.48 (0.27-0.83) 0.008 Placebo 33 173 1.00 NPC1 hCV7490135
0.48 0.53 Placebo hom(CC) vs. ref(TT) 0.0754 41 273 1.47
(0.96-2.27) 0.0763 0.0347 none het(TC) vs. ref(TT) 70 608 1.17
(0.79-1.72) 0.4402 ref(TT) 34 350 1.00 Statin hom(CC) vs. ref(TT)
0.2055 23 283 0.77 (0.47-1.26) 0.3024 het(TC) vs. ref(TT) 46 657
0.67 (0.45-1.01) 0.0552 ref(TT) 40 371 1.00 Maj Hom(TT) Statin 40
371 1.10 (0.71-1.70) 0.6704 Placebo 34 350 1.00 Het(TC) Statin 46
657 0.63 (0.44-0.91) 0.0122 Placebo 70 608 1.00 Min Hom(CC) Statin
23 283 0.58 (0.35-0.94) 0.0258 Placebo 41 273 1.00 .sup.aP value
for trend .sup.bNumber of patients developed recurrent MI during 5
years of follow up .sup.cNumber of patients had MI .sup.dRelative
risk for RMI .sup.e95% confidence interval for relative risk
.sup.fSignificance of risk estimated by Wald test .sup.gP vale for
interaction .sup.hConfounders *Y primer nucleotide frequency for
cases* *Y primer nucleotide frequency for controls**
[0489]
17TABLE 11 Risk of cardiovascular disease events associated with
Pravastatin, by CD6 genotype, CARE and WOSCOPS N Endpoint Gene
Marker Study CD6 genotype RMI.sup.a MI.sup.b RR.sup.e 95% CI
p-value.sup.g BP p value.sup.h RMI CD6 hCV2553030 CARE Minor hom
(TT) 2 108 0.13 0.03-0.60 0.0016 0.0342 28 159 Het (TC) 41 489 0.76
0.51-1.12 0.1735 50 442 Major hom (CC) 65 713 0.8 0.59-1.09 0.1518
85 728 recessive (TT) 2 108 0.13 0.03-0.60 0.0016 0.009 10 64
recessive (TT + CC)ref* 106 1202 0.78 0.61-1.00 0.0478 135 1170
CS.sup.c Cn.sup.d OR.sup.f 95% CI p-value.sup.g BP p value.sup.h MI
WOSCOPS Minor hom (TT) 7 38 0.23 0.09-0.64 0.0033 0.1126 19 24 Het
(TC) 62 198 0.71 0.49-1.04 0.0789 88 200 Major hom (CC) 120 305
0.66 0.50-0.87 0.0036 179 300 recessive (TT) 7 38 0.23 0.09-0.64
0.0033 0.0388 19 24 recessive TC + CC)ref* 182 503 0.68 0.54-0.85
0.0007 267 500 *Heterozygote and major homozygote was used as
reference .sup.aPatients developed recurrent MI during 5years
follow up .sup.bPatients had MI before entry but didn't developed
current MI during 5 years follow up .sup.cPatients had MI
.sup.dPatients had no MI .sup.erelative risk .sup.fOdds ratio
.sup.gWald test .sup.hBreslow's Day p value
[0490]
18TABLE 12 Risk of cardiovascular disease events associated with
FCAR genotype in untreated arms, CARE and WOSCOPS Adjusted for Age,
Smoking status, Gender, hypertension, BMI, Adjusted for Age,
Smoking diabetes, baseline LDLD End- Unadjusted status, Gender* and
HDL*,.dagger. point Gene Marker FCARgenotype N
OR.vertline..vertline. 95% CI P.dagger-dbl. OR.vertline..vertline.
95% CI P.dagger-dbl. OR.vertline..vertline. 95% CI P.dagger-dbl.
CARE RMI.sup.a MI.sup.b RMI FCAR hCV7841642 AA 1 11 0.84
(0.11-6.54) 0.87 0.74 (0.09-5.89) 0.78 0.86 (0.11-6.71) 0.88 AG 28
159 1.62 (1.04-2.53) 0.034 1.58 (1.01-2.48) 0.063 1.58 (1.02-2.46)
0.041 AA + AG 29 170 1.57 (1.01-2.43) 0.044 1.52 (0.98-2.37) 0.063
1.58 (1.02-2.46) 0.041 GG.vertline..vertline. 116 1067 1 (ref) 1
(ref) 1 (ref) WOSCOPS.sctn. Cs.sup.c Cn.sup.d MI AA 1 3 0.67
(0.07-6.52) 0.73 0.68 (0.07-6.75) 0.75 AG 54 70 1.5 (1.01-2.22)
0.043 1.49 (1.00-2.22) 0.05 AA + AG 55 73 1.47 (1.00-2.16) 0.053
1.46 (0.98-2.16) 0.061 GG.vertline..vertline. 233 456 1 (ref) 1
(ref) CARE indicates Cholesterol and Recurrent Events trial;
WOSCOPS, West of Scotland Coronary Prevention Study; RMI; BMI,
body-mass index (kg/m2); LDL, low-density lipoprotein; HDL,
high-density lipoprotein; OR, odds ratio; CI, confidence interval
*Adjusted for age (continuous for CARE, 5-year age groups for
WOSCOPS), smoking (never, former, current) and gender (all male in
WOSCOPS) .dagger.Further adjusted for history of hypertension, BMI
(continuous), history of diabetes, baseline LDL level (continuous),
and baseline HDL level (continuous) .dagger-dbl.Wald test
.sctn.Conditional logistic regression used to account for matching
of WOSCOPS cases and controls (all male) on smoking and age
.vertline..vertline.Major homozygote (AspAsp) was used as reference
.sup.aPatients developed recurrent MI during 5 years follow up
.sup.bPatients had MI before entry but didn't developed current MI
during 6 years follow up .sup.cPatients had MI .sup.dPatients had
no MI Risk of cardiovascular disease events associated with
Pravastatin, by FCAR genotype, CARE and WOSCOPS Adjusted for Age,
Smoking status, Gender, hypertension, BMI, Adjusted for Age,
Smoking diabetes, baseline LDLD End- FCAR Unadjusted status,
Gender* and HDL*,.dagger. point Gene Marker Study genotype **OR 95%
CI P.dagger-dbl. **OR 95% CI P.dagger-dbl. **OR 95% CI
P.dagger-dbl. RMI FCAR hCV7841642 CARE AA + AG 0.32 (0.15-0.67)
0.0016 0.31 (0.15-0.65) 0.0021 0.31 (0.15-0.67) 0.0026 GG 0.81
(0.61-1.07) 0.13 0.79 (0.60-1.06) 0.12 0.79 (0.60-1.05) 0.11 p
interaction: 0.0163.sctn. p interaction: 0.0151.sctn. p
interaction: 0.0193.sctn. MI WOSCOPS.vertline..vertline. AA + AG
0.57 (0.34-0.95) 0.031 0.55 (0.32-0.93) 0.025 GG 0.66 (0.52-0.84)
0.0008 0.65 (0.51-0.83) 0.0006 p interaction: 0.5851.sctn. p
interaction: 0.5480.sctn. CARE indicates Cholesterol and Recurrent
Events trial; WOSCOPS, West of Scotland Coronary Prevention Study;
RMI, recurrent myocardial infarction; LDL, low-density lipoprotein;
HDL, high-density lipoprotein; OR, odds ratio; CI, confidence
interval; BMI, body-mass index (kg/m2) *Adjusted for age
(continuous in CARE, 5-year age groups in WOSCOPS), smoking (never,
former, current) and gender (all male in WOSCOPS) .dagger.Further
adjusted for history of hypertension, BMI (continuous), history of
diabetes, baseline LDL level (continuous), and baseline HDL level
(continuous) .dagger-dbl.Wald test .sctn.Likelihood ratio test of
interaction between treatment and FCAR genotype
.vertline..vertline.Conditional logistic regression used to account
for matching of WOSCOPS cases and controls on smoking and age
**Placebo group was used as reference
[0491]
19TABLE 13 Statistically Significant Interactions Between SNP
Genotypes and Pravastatin Efficacy for Two CVD Case Defintions:
Fatal MI/Sudden Death/Definite Non-fatal MI and Fatal/Non-fatal MI
Overall** Interaction 0 Rare Alleles n/total Chi-Square Effect**
Chi (%) Study Control Group Test Square Test Pravastatin Public
Marker Study Design Case Definition Definition*** Stratum Statistic
p-value Statistic p-value Patients Placebo Patients ABCA1
hCV2741083 CARE Prospective Fatal MySudden Depth/Definite Nonfatal
MI Cleaner White Males 15.1 0.0099 7.68 0.0215 80/630 (12.7%)
113/575 (19.7%) ABCA1 hCV2741083 CARE Case/Control Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 12.96 0.0237 6.55
0.0377 50/622 (12.9%) 113/572 (19.6%) ADAMTS1 hCV529706 CARE
Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner
White Males 12.70 0.0254 6.44 0.0399 65/470 (13.8%) 57/434 (15.4%)
ADAMTS1 hCV529710 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 13.42 0.0197 6.54 0.038 65/471
(13.6%) 67/435 (15.4%) AGTR1 hCV3187716 CARE Prospective Fatal
MI/Sudden Death/Definite Nonfatal MI All Possibles White Males
12.22 0.032 8.25 0.0162 50/612 (8.2%) 65/579 (11.2%) AGTR1
hCV3187716 CARE Prospective Fatal MI/Sudden Death/Definite Nonfatal
MI Cleaner White Males 14.41 0.0132 7.65 0.0218 50/405 (12.3%)
65/364 (17.0%) AGTR1 hCV3187716 CARE Case/Control Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 11.97 0.352 6.93
0.0313 50/400 (12.5%) 65/361 (18.0%) ASAH1 hCV2442143 CARE
Prospective Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner
White Males 15.62 0.008 6.23 0.0445 21/201 (10.4%) 43/196 (21.9%)
CAPG hCV15851292 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 12.24 0.0317 7.67 0.0227 92/642
(14.3%) 97/559 (17.4%) CAPN10 hCV25614016 CARE Prospective Fatal
MI/Sudden Death/Definite Nonfatal MI All Possibles White Males
11.48 0.0427 8.63 0.0121 70/867 (5.1%) 103/839 (12.3%) CAPN10
hCV25614016 CARE Prospective Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 14.29 0.0138 6.28 0.016 70/581
(12.0%) 103/524 (19.7%) CAPN10 hCV25614016 CARE Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI All Possibles White Males 11.5
0.0424 9.06 0.0108 70/857 (8.2%) 103/828 (12.4%) CAPN10 hCV25614016
CARE Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI
Cleaner White Males 13.12 0.0222 .11 0.0173 70/574 (12.2%) 103/519
(19.5%) CAPN2 hCV781558 WOSCOPS Case/Control Fatal MI/Sudden
Death/Definite Nonfatal MI All Possibles White Males 27.51
<.0001 10.58 0.0048 67/434 (15.4%) 124/442 (28.1%) CAPN2
hCV781558 WOSCOPS Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 29.73 <.0001 10.14 0.003 67/386
(17.4%) 124/396 (31.3%) CCL11 hCV7449608 WOSCOPS Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI All Possibles White Males
22.55 0.0004 9.09 0.0105 95/507 (18.7%) 145/554 (26.2%) CCL11
hCV7449608 WOSCOPS Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 25.38 0.0001 10.38 0.0058 95/452
(21.0%) 145/491 (29.5%) CD163 hCV25591528 CARE Prospective Fatal
MI/Sudden Death/Definite Nonfatal MI All Possibles White Males
12.05 0.0341 9.01 0.0111 99/954 (10.3%) 99/936 (10.6%) CD163
hCV25591528 CARE Prospective Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 14.40 0.0129 7.65 0.0218 99/649
(15.3%) 99/573 (17.3%) CD163 hCV25591528 CARE Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI All Possible White Males 12.07
0.0247 10.44 0.0054 99/649 (10.4%) 90/917 (10.8%) CD163 hCV25591528
CARE Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI
Cleaner White Males 15.08 0.01 0.01 0.011 99/640 (15.5%) 99/585
(17.6%) CD6 hCV2553030 CARE Prospective Fatal MI/Sudden
Death/Definite Nonfatal MI All Possible White Males 11.51 0.0422
6.64 0.0323 68/449 (10.2%) 73/697 (10.5%) CD6 hCV2553030 CARE
Prospective Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner
White Males 15.69 0.072 7.6 0.0202 68/449 (15.1%) 73/434 (16.6%)
CD6 hCV2553030 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI All White Males 12.22 0.0318 12.46 0.002 66/656 (10.4%)
73/683 (10.7%) Possible CD6 hCV25922320 CARE Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI Cleaner White Males 16.02
0.0068 13.78 0.001 68/442 (15.4%) 73/427 (17.1%) CD6 hCV25922320
CARE Prospective Fatal MI/Sudden Death/Definite Nonfatal MI All
White Males 12.15 0.0327 0.27 0.0097 59/792 (7.4%) 89/730 (12.2%)
Possible CD6 hCV25922320 CARE Prospective Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 16.27 0.0061 9.94
0.0089 59/549 (10.7%) 89/463 (19.2%) CD6 hCV25922320 CARE
Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI All White
Males 12.46 0.029 0.34 0.0094 59/705 (7.5%) 89/721 (12.3%) Possible
CD6 hCV25922320 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 17.95 0.003 12.05 0.0024 59/545
(10.8%) 89/461 (19.3%) COL6A2 hCV2611372 WOSCOPS Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI All White Males 21.94 0.0005
6.17 0.0168 29/194 (14.9%) 65/217 (30.0%) Possibles COL6A2
hCV2611372 WOSCOPS Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 22.35 0.0004 7.28 0.0262 29/174
(16.7%) 65/199 (32.7%) CR1 hCV25698594 CARE Prospective Fatal
MI/Sudden Death/Definite Nonfatal MI All White Males 5.5 0.0367
4.66 0.0305 111/1177 (9.4%) 122/1143 (10.7%) Possibles CR1
hCV25598594 CARE Prospective Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 12.80 0.0049 5.2 0.0225 111/302
(13.8)% 122/715 (17.1%) CR1 hCV25598594 CARE Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI All White Males 6.11 0.0437
7.14 0.0076 111/1159 (9.6%) 122/122 (10.9%) Possibles CR1
hCV25598594 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 11.67 0.0079 7.52 0.0052 111/791
(14.0%) 122/708 (17.3%) CXCL16 hCV6718197 CARE Prospective Fatal
MI/Sudden Death/Definite Nonfatal MI Cleaner White Males 15.8
0.0075 6.68 0.0118 25/260 (10.0%) 52/231 (22.6%) CXCL16 hCV8718197
CARE Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI
Cleaner White Males 15.14 0.0078 9.25 0.0098 25/256 (10.2%) 52/229
(22.7%) ELN hCV1253630 CARE Prospective Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 12.02 0.0345 6.79
0.0336 32/294 (10.9%) 40/552 (19.0%) ELN hCV1253630 CARE
Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner
White Males 11.34 0.045 6.77 0.0338 32/291 (11.0%) 48/248 (19.4%)
FCAR hCV7841642 CARE Prospective Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 13.17 0.0218 6.22 0.0445 103/734
(14.0%) 104/637 (16.3%) FGB hCV7429784 WOSCOPS Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI All White Males 24.00 0.0002
6.19 0.0463 95/512 (1.5%) 147/566 (26.0%) Possible GALC hCV25922440
CARE Prospective Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner
White Males 11.27 0.0463 7.21 0.0273 67/581 (15.0%) 84/532 (15.0%)
GAPO hCV8921258 WOSCOPS Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI All White Males 23.92 0.0002 6.94 0.0312 75/454 (16.5%)
148/534 (27.7%) Possible GAPO hCV8921288 WOSCOPS Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI Cleaner White Males 27.62
<.0001 10.62 0.0075 75/415 (18.1%) 148/468 (31.8%) HLA-DPB1
hCV25651174 CARE Prospective Fatal MI/Sudden Death/Definite
Nonfatal MI All White Males 15.04 0.0102 10.82 0.0045 45/505 (7.6%)
71/585 (12.1%) Possible HLA-DPB1 hCV25651174 CARE Prospective Fatal
MI/Sudden Death/Definite Nonfatal MI Cleaner White Males 20.44
0.001 12.43 0.002 46/416 (11.1%) 71/370 (19.2%) HLA-DPB1
hCV25651174 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI All White Males 15.47 0.0085 13.5 0.0012 46/598 (7.7%)
71/578 (12.3%) Possible HLA-DPB1 hCV25651174 CARE Case/Control
Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner White Males
20.65 0.0000 16.15 0.0003 48/410 (11.2%) 71/388 (19.3%) HLA-DPB1
hCV51065 CARE Prospective Fatal MI/Sudden Death/Definite Nonfatal
MI All White Males 13.92 0.0161 0.18 0.0102 48/843 (7.5%) 72/629
(11.4%) Possible HLA-DPB1 hCV8851065 CARE Prospective Fatal
MI/Sudden Death/Definite Nonfatal MI Cleaner White Males 18.12
0.0022 10.22 0.006 45/438 (11.0%) 72/391 (18.4%) HLA-DPB1
hCV8851065 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI All Possible White Males 14.95 0.0105 12.1 0.0024
40/538 (7.5%) 72/620 (11.6%) HLA-DPB1 hCV8851065 CARE Case/Control
Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner White Males
19.13 0.0016 14.05 0.0009 48/432 (11.1%) 72/389 (18.5%) HLA-DPB1
hCV8851084 CARE Prospective Fatal MI/Sudden Death/Definite Nonfatal
MI Cleaner White Males 12.61 0.0274 6.21 0.0448 68/544 (12.5%)
90/474 (19.0%) HLA-DPB1 hCV8851084 CARE Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI Cleaner White Males 13.34
0.0204 6.64 0.0139 68/538 (12.7%) 90/472 (19.1%) HLA-DPB1
hCV8851085 CARE Prospective Fatal MI/Sudden Death/Definite Nonfatal
MI Cleaner White Males 13.65 0.0168 7.67 0.0198 61/510 (12.0%)
86/452 (19.0%) HLA-DPB1 hCV8851085 CARE Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI Cleaner White Males 14.28
0.0139 9.61 0.0082 61/502 (12.2%) 86/450 (19.1%) HLA-DOB1
hCV9494470 CARE Prospective Fatal MI/Sudden Death/Definite Nonfatal
MI All Possible White Males 11.15 0.0484 8.63 0.0134 85/840 (10.1%)
86/840 (10.2%) HLA-DOB1 hCV9494470 CARE Prospective Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 14.11 0.0149 5.51
0.0142 85/576 (14.5%) 88/520 (16.5%) HLA-DOB1 hCV9494470 CARE
Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI All White
Males 11.7 0.0391 9.42 0.009 85/627 (10.3%) 86/825 (10.4%) Possible
HLA-DOB1 hCV9494470 CARE Case/Control Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 14.73 0.0116 9.71
0.0078 85/588 (15.0%) 88/513 (16.8%) HRC hCV11506744 WOSCOPS
Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI All White
Males 23.6 0.0002 10.36 0.0058 54/253 (21.3%) 80/247 (24.3%)
Possible HRC hCV11506744 WOSCOPS Case/Control Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 25.89 <.0001
10.62 0.0049 54/229 (23.6%) 50/216 (27.5%) L1A hCV9546471 WOSCOPS
Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI All White
Males 22.89 0.0004 7.84 0.022 62/370 (16.6%) 121/400 (30.3%)
Possible L1A hCV9546471 WOSCOPS Case/Control Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 24.89 0.0002 6.79
0.0335 62/324 (19.1%) 121/354 (34.2%) L1RN hCV8737990 CARE
Prospective Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner
White Males 14.44 0.0131 7.62 0.0222 67/454 (14.8%) 70/393 (17.8%)
L1RN hCV8737990 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 13 0.0234 5.62 0.0384 67/448
(15.0%) 70/387 (18.1%) L4R hCV2769554 CARE Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI All White Males 14.49 0.0128
8.76 0.0341 25/346 (7.2%) 42/361 (11.6%) Possible L4R hCV2769554
CARE Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI
Cleaner White Males 14.68 0.0123 6.12 0.0469 25/218 (11.5%) 42/230
(18.3%) ITGAE hCV1243283 CARE Case/Control Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 13.01 0.0233 6.66
0.0357 57/381 (15.0%) 57/313 (18.2%) KDR hCV16192174 CARE
Prospective Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner
White Males 14.39 0.0133 6.44 0.04 78/688 (11.7%) 107/587 (17.9%)
KDR hCV16192174 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI All White Males 13.72 0.0175 8.04 0.0179 78/975 (11.0%)
107/591 (18.1%) Possible KDR hCV16192174 CARE Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI Cleaner White Males 16.55
0.0054 9.34 0.0094 78/000 (11.0%) 107/591 (18.1%) KDR hCV22271999
CARE Prospective Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner
White Males 14.38 0.0133 6.45 0.0397 75/885 (11.7%) 106/594 (17.8%)
KDR hCV22271999 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI All White Males 13.75 0.0171 8.11 0.0174 78/973 (8.0%)
106/943 (11.2%) Possible KDR hCV22271999 CARE Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI Cleaner White Males 15.66
0.0052 9.48 0.0087 78/659 (11.8%) 106/588 (18.0%) KLK14 hCV18044337
CARE Prospective Fatal MI/Sudden Death/Definite Nonfatal MI All
White Males 17.43 0.0037 8.78 0.0124 52/560 (9.3%) 50/560 (8.9%)
Possible KLK14 hCV18044337 CARE Prospective Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 18.02 0.0029 7.27
0.0264 52/366 (14.2%) 50/342 (14.5%) KLK14 hCV18044337 CARE
Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI All White
Males 17.16 0.0042 9.22 0.01 62/550 (9.5%) 50/549 (9.1%) Possible
KLK14 hCV18044337 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 18.67 0.0022 7.63 0.022 52/359
(14.5%) 50/339 (14.7%) LRP3 hCV25594515 WOSCOPS Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI All White Males 24 0.0002
11.17 0.0038 115/552 (20.8%) 158/621 (25.4%) Possible LRP3
hCV25594815 WOSCOPS Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 26.51 <.0001 11.9 0.0026 115/191
(23.4%) 158/550 (28.7%) MICA hCV25174101 CARE Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI Cleaner White Males 14.22
0.0143 6.69 0.0353 79/608 (13.0%) 99/549 (18.0%) MYH7 hCV25629396
CARE Prospective Fatal MI/Sudden Death/Definite Nonfatal MI All
White Males 13.00 0.0044 6.8 0.0091 105/200 (8.8%) 130/144 (11.4%)
Possible MYH7 hCV25629396 CARE Prospective Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 17 0.007 7.26 0.007
105/816 (12.9%) 130/715 (15.2%) MYH7 hCV25629396 CARE Case/Control
Fatal MI/Sudden Death/Definite Nonfatal MI All White Males 12.06
0.0047 9.81 0.0017 105/1182 (8.9%) 130/1124 (11.6%) Possible MYH7
hCV25629396 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 14.74 0.0021 9.47 0.0021 105/805
(13.0%) 130/707 (18.4%) NOS3 hCV3219460 CARE Prospective Fatal
MI/Sudden Death/Definite Nonfatal MI All White Males 11.76 0.0382
6.75 0.0342 46/539 (8.5%) 58/528 (10.8%) Possible NOS3 hCV3219460
CARE Prospective Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner
White Males 14.69 0.0118 7.47 0.0239 46/381 (12.7%) 58/325 (17.2%)
NOS3 hCV3219460 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI All White Males 12.02 0.0346 7.45 0.0242 45/532 (8.6%)
56/516 (10.9%) Possible NOS3 hCV3219460 CARE Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI Cleaner White Males 14.78
0.0114 7.96 0.0185 46/355 (13.0%) 56/318 (17.6%) NPC1 hCV25472673
CARE Prospective Fatal MI/Sudden Death/Definite Nonfatal MI All
White Males 11.68 0.0394 6.39 0.0409 48/462 (10.4%) 37/436 (8.6%)
Possible NPC1 hCV25472673 CARE Prospective Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 21.0 0.008 11.02
0.004 48/302 (15.9%) 37/282 (13.1%) NPC1 hCV25472673 CARE
Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner
White Males 19.06 0.0019 9.81 0.0074 48/299 (16.1%) 37/279 (13.3%)
PLAB hCV7494810 CARE Prospective Fatal MI/Sudden Death/Definite
Nonfatal MI All White Males 11.47 0.0429 6.87 0.0322 72/706 (10.2%)
87/675 (9.9%) Possible PLAB hCV7494810 CARE Prospective Fatal
MI/Sudden Death/Definite Nonfatal MI Cleaner White Males 14.7
0.0117 6.06 0.0483 72/478 (15.1%) 67/417 (18.1%) PLAB hCV7494810
CARE Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI All
White Males 11.35 0.0449 7.37 0.0251 72/694 (10.4%) 67/660 (10.2%)
Possible PLAB hCV7494810 CARE Case/Control Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 14.94 0.0111 7.43
0.0244 72/471 (15.3%) 67/411 (18.2%) PRKCO hCV15954277 CARE
Prospective Fatal MI/Sudden Death/Definite Nonfatal MI All White
Males 13.47 0.0194 9.75 0.0077 50/655 (7.0%) 83/667 (12.8%)
Possible PRKCO hCV15954277 CARE Prospective Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 11.96 0.0354 6.08
0.0479 50/425 (11.0%) 83/434 (19.1%) PRKCO hCV15954277 CARE
Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI All White
Males 12.34 0.0304 9.38 0.0092 60/645 (7.8%) 83/434 (19.1%)
Possible SERPINAS hCV9596963 CARE Case/Control Fatal MI/Sudden
Death/Definite Nonfatal MI All White Males 12.27 0.0313 6.41 0.0405
60/557 (9.0%) 56/545 (10.2%) Possible SN hCV25623265 CARE
Prospective Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner
White Males 14.96 0.0105 8.54 0.014 33/220 (15.0%) 38/194 (19.0%)
SN hCV25623265 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 15.1 0.01
9.75 0.0076 33/214 (15.4%) 38/193 (19.7%) TAP1 hCV549926 CARE
Prospective Fatal MI/Sudden Death/Definite Nonfatal MI All White
Males 13.9 0.0163 7.13 0.0283 63/848 (9.0%) 81/829 (9.0%) Possible
TAP1 hCV549926 CARE Prospective Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 14.3 0.0138 6.22 0.0447 83/576
(14.4%) 81/505 (14.4%) TAP1 hCV549926 CARE Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI All White Males 13.04 0.023
9.44 0.0089 83/832 (10.0%) 81/817 (9.9%) Possible TAP1 hCV549926
CARE Case/Control Fatal MI/Sudden Death/Definite Nonfatal MI
Cleaner White Males 12.88 0.0245 8.15 0.017 83/666 (14.7%) 81/501
(16.2%) TMP2 hCV25629888 CARE Case/Control Fatal MI/Sudden
Death/Definite Nonfatal MI Cleaner White Males 14.43 0.0131 5.59
0.0352 75/561 (13.4%) 65/513 (16.6%) TNF hCV7514879 CARE
Prospective Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner
White Males 14.05 0.0153 7.17 0.0278 85/579 (14.7%) 88/524 (14.7%)
TNF hCV7514879 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI Cleaner White Males 12.72 0.0261 6.07 0.0481 85/573
(14.5%) 85/517 (16.) VTN hCV2536595 CARE Prospective Fatal
MI/Sudden Death/Definite Nonfatal MI All White Males 12.97 0.0237
7.6 0.0224 65/340 (10.3%) 25/361 (6.9%) Possible VTN hCV2536595
CARE Prospective Fatal MI/Sudden Death/Definite Nonfatal MI Cleaner
White Males 14.43 0.0131 6.14 0.0453 35/238 (14.8%) 25/213 (11.7%)
VTN hCV2536595 CARE Case/Control Fatal MI/Sudden Death/Definite
Nonfatal MI All White Males 13 0.0234 7.42 0.0244 35/337 (10.4%)
25/352 (7.1%) Possible VTN hCV2536595 CARE Case/Control Fatal
MI/Sudden Death/Definite Nonfatal MI Cleaner White Males 14.88
0.0109 6.93 0.0313 35/235 (14.9%) 25/210 (11.9%) A2M hCV517658 CARE
Case/Control Fatal & Nonfatal MI All Possible White Males 15.24
0.0094 6.84 0.0327 42/525 (8.0%) 54/479 (13.4%) A2M hCV517658 CARE
Case/Control Fatal & Nonfatal MI Cleaner White Males 17.54
0.0038 6.16 0.046 42/355 (11.8%) 64/318 (20.1%) ABCA1 hCV2741051
CARE Prospective Fatal & Nonfatal MI All Possible White Males
13.87 0.0165 7.96 0.0157 56/625 (9.0%) 95/628 (15.3%) ABCA1
hCV2741051 CARE Prospective Fatal & Nonfatal MI Cleaner White
Males 16.34 0.0059 6.38 0.0411 56/414 (13.5%) 95/414 (23.2%) ABCA1
hCV2741051 CARE Case/Control Fatal & Nonfatal MI All Possible
White Males 13.37 0.0202 7.64 0.0219 56/612 (9.2%) 96/616 (15.6%)
ABCA1 hCV2741051 CARE Case/Control Fatal & Nonfatal MI Cleaner
White Males 15.31 0.0091 6.25 0.044 56/405 (13.8%) 95/410 (23.4%)
ABCA1 hCV2741063 CARE Prospective Fatal & Nonfatal MI All
Possible White Males 16.94 0.0048 7.99 0.0184 92/931 (9.9%) 137/927
(14.8%) ABCA1 hCV2741063 CARE Prospective Fatal & Nonfatal MI
Cleaner White Males 21.26 0.0007 5 0.0183 92/642 (14.3%) 137/599
(22.9%) ABCA1 hCV2741063 CARE Case/Control Fatal & Nonfatal MI
All Possible White Males 16.64 0.0052 7.83 0.02 92/913 (10.1%)
137/915 (15.0%) ABCA1 hCV2741063 CARE Case/Control Fatal &
Nonfatal MI Cleaner White Males 18.67 0.0022 8.53 0.0382 92/631
(14.6%) 137/595 (23.0%) ADAM12 hCV25928135 CARE Case/Control Fatal
& Nonfatal MI All Possible White Males 17.71 0.0033 8.92 0.0315
95/141 (12.8%) 97/728 (13.3%) ADAM12 hCV25928135 CARE Case/Control
Fatal & Nonfatal MI Cleaner White Males 19.51 0.0016 7.5 0.0235
95/525 (18.1%) 97/478 (20.3%) ALOX12 hCV1552894 CARE Prospective
Fatal & Nonfatal MI All Possible White Males 13.01 0.0233 6.5
0.0389 48/421 (11.4%) 47/411 (11.4%) ALOX12 hCV1552900 CARE
Prospective Fatal & Nonfatal MI All Possible White Males 13.22
0.00214 6.49 0.039 48/418 (11.5%) 47/410 (11.5%) C14orf159
hCV25472345 CARE Prospective Fatal & Nonfatal MI All Possible
White Males 11.44 0.0433 6.05 0.0485 63/560 (11.3%) 74/517 (14.3%)
C14orf159 hCV25472345 CARE Case/Control Fatal & Nonfatal MI All
Possible White Males 11.83 0.0372 5.4 0.0408 63/551 (11.4%) 74/511
(14.5%) CAPN2 hCV781558 WOSCOPS Case/Control Fatal & Nonfatal
MI All Possible White Males 23.75 0.0002 8.92 0.0115 80/434 (18.4%)
132/442 (29.9%) CAPN2 hCV781558 WOSCOPS Case/Control Fatal &
Nonfatal MI Cleaner White Males 26.05 <.0001 8.68 0.0118 80/399
(20.1%) 132/404 (32.7%) CCL11 hCV7449808 WOSCOPS Case/Control Fatal
& Nonfatal MI All Possible White Males 21.25 0.0007 10.28
0.0059 107/507 (21.1%) 155/554 (28.0%) CCL11 hCV7449808 WOSCOPS
Case/Control Fatal & Nonfatal MI Cleaner White Males 23.44
0.0003 1.88 0.0043 107/464 (23.1%) 155/501 (30.9%) CD163
hCV25591528 CARE Prospective Fatal & Nonfatal MI All Possible
White Males 15.1 0.01 9.22 0.01 111/964 (11.5%) 119/938 (12.7%)
CD163 hCV25591528 CARE Prospective Fatal & Nonfatal MI Cleaner
White Males 16.28 0.0028 7.62 0.0201 111/661 (16.5%)
119/593.20.14%) CD163 hCV25591528 CARE Case/Control Fatal &
Nonfatal MI All Possible White Males 15.62 0.008 10.5 0.0052
111/945 (11.7%) 119/915 (13.0%) CD163 hCV25591528 CARE Case/Control
Fatal & Nonfatal MI Cleaner White Males 18.72 0.0022 9.13
0.0104 111/650 (17.1%) 119/583 (20.4%) CD6 hCV2553030 CARE
Prospective Fatal & Nonfatal MI All Possible White Males 12.37
0.0301 4.35 0.0418 77/688 (11.5%) 89/697 (12.6%) CD6 hCV2553030
CARE Prospective Fatal & Nonfatal MI Cleaner White Males 17.24
0.0041 7.6 0.0224 77/458 (16.8%) 89/450 (19.8%) CD6 hCV2553030 CARE
Case/Control Fatal & Nonfatal MI All Possible White Males 12.41
0.0295 8.44 0.0147 77/654 (11.8%) 89/682 (13.0%) CD6 hCV2553030
CARE Case/Control Fatal & Nonfatal MI Cleaner White Males 17.04
0.0044 10.19 0.0061 77/449 (17.1%) 89/442 (20.1%) COL11A1
hCV8400671 CARE Case/Control Fatal & Nonfatal MI All Possible
White Males 11.4 0.044 7.45 0.0241 95/815 (11.7%) 95%768 (12.5%)
COL2A1 hCV3276198 CARE Case/Control Fatal & Nonfatal MI Cleaner
White Males 17.65 0.0031 6.29 0.0431 92/583 (15.8%) 114/528 (21.7%)
CR1 hCV25598594 CARE Prospective Fatal & Nonfatal MI All
Possible White Males 11.12 0.0111 4.95 0.0256 125/1177 (10.6%)
147/1143 (12.9%) CR1 hCV25598594 CARE Prospective Fatal &
Nonfatal MI Cleaner White Males 16.21 0.001 5.53 0.0157 125/818
(15.3%) 147/740 (19.9%) CR1 hCV25598594 CARE Case/Control Fatal
& Nonfatal MI All Possible White Males 11.01 0.0117 6.69 0.0097
125/1155 (10.8%) 147/112013.1%) CR1 hCV25598594 CARE Case/Control
Fatal & Nonfatal MI Cleaner White Males 15.25 0.0016 5.94
0.0084 125/802 (15.6%) 147/729 (20.2%) CXCL16 hCV8718197 CARE
Prospective Fatal & Nonfatal MI All Possible White Males 14.38
0.0134 8.02 0.011 26/376 (6.9%) 68/380 (15.3%) CXCL16 hCV8718197
CARE Prospective Fatal & Nonfatal MI Cleaner White Males 19.81
0.0014 10.87 0.0044 26/260 (10.0%) 58/237 (24.5%) CXCL16 hCV8718197
CARE Case/Control Fatal & Nonfatal MI All Possible White Males
14.45 0.0128 9.07 0.0107 26/369 (7.0%) 58 (373 (15.5%) CXCL16
hCV8718197 CARE Case/Control Fatal & Nonfatal MI Cleaner White
Males 19.69 0.0014 11.26 0.0036 26/255 (10.2%) 58/234 (25.8%) CYBA
hCV2038 CARE Case/Control Fatal & Nonfatal MI All Possible
White Males 12.79 0.0254 5.61 0.0367 48/510 (9.0%) 75/515 (14.6%)
DDEF1 hCV7686234 WOSCOPS Case/Control Fatal & Nonfatal MI All
Possible White Males 18.21 0.0027 6.17 0.0458 35/208 (16.8%) 80.262
(60.5%) ELN hCV1253830 CARE Prospective Fatal & Nonfatal MI All
Possible White Males 15.02 0.0103 9.3 0.0095 39/425 (9.2%) 64/406
(15.0%) ELN hCV1253830 CARE Prospective Fatal & Nonfatal MI
Cleaner White Males 19.02 0.0019 10.25 0.006 39/301 (13.0%)
64/26823.9%) ELN hCV1253830 CARE Case/Control Fatal & Nonfatal
MI All Possible White Males 18.96 0.0048 11.05 0.004 39/417 (9.4%)
64/394 (16.2%) ELN hCV1253830 CARE Case/Control Fatal &
Nonfatal MI Cleaner White Males 19.18 0.0018 11.09 0.0039 39/297
(13.1%) 64/263 (24.3%) F13A1 hCV11972326 CARE Case/Control Fatal
& Nonfatal MI All Possible White Males 12.42 0.0294 6.28 0.0433
56/694 (9.4%) 92/688 (13.8%) F7 hCV783138 CARE Prospective Fatal
& Nonfatal MI All Possible White Males 13.5 0.0183 8.4 0.015
91/978 (9.3%) 138/957 (13.9%) F7 hCV783138 CARE Prospective Fatal
& Nonfatal MI Cleaner White Males 15.55 0.0062 7.11 0.0287
91/587 (13.5%) 133/622 (21.4%) F7 hCV783138 CARE Case/Control Fatal
& Nonfatal MI All Possible White Males 12.8 0.0254 7.75 0.0208
91/959 (9.5%) 133/937 (14.2%) F7 hCV783138 CARE Case/Control Fatal
& Nonfatal MI Cleaner White Males 14.16 0.0146 6.31 0.0425
91/655 (13.9%) 133/613 (21.7%) F7 hCV783184 CARE Prospective Fatal
& Nonfatal MI All Possible White Males 11.84 0.037 6.54 0.0362
90/950 (9.4%) 131/937 (14.0%) F7 hCV783184 CARE Case/Control Fatal
& Nonfatal MI All Possible White Males 11.65 0.0396 6.42 0.0403
90/941 (9.5%) 131/917 (14.3%) FABP1 hCV16173091 CARE Prospective
Fatal & Nonfatal MI All Possible White Males 11.41 0.0439 6.21
0.0449 55/599 (9.2%) (79/556 (14.2%) FABP1 hCV16173091 CARE
Prospective Fatal & Nonfatal MI Cleaner White Males 15.3 0.0091
6.42 0.0404 55/410 (13.4%) 79/680 (21.9%) FABP1 hCV16173091 CARE
Case/Control Fatal & Nonfatal MI Cleaner White Males 14.49
0.0128 6.02 0.0492 55/402 (13.7%) 79/355 (22.3%) FCAR hCV7841842
CARE Case/Control Fatal & Nonfatal MI All Possible White Males
11.76 0.038 6.15 0.0461 115/1045 (11.0%) 127/987 (12.7%) FN1
hCV9506149 CARE Case/Control Fatal & Nonfatal MI All Possible
White Males 13.4 0.0199 6.05 0.0485 60/642 (9.3%) 94/615 (15.3%)
GALC hCV25922440 CARE Prospective Fatal & Nonfatal MI Cleaner
White Males 13.79 0.017 6.1 0.0473 99/593 (16.7%) 108/556 (19.4%)
GAPD hCV8921288 CARE Prospective Fatal & Nonfatal MI Cleaner
hite Males 15.4 0.0088 6.93 0.0313 88/540 (16.3%) 84/484 (17.4%)
GAPD hCV8921288 CARE Case/Control Fatal & Nonfatal MI All
Possible White Males 11.36 0.0447 5.14 0.0485 88/778 (11.3%) 84/737
(11.4%) GAPD hCV8921288 WOSCOPS Case/Control Fatal & Nonfatal
MI All Possible White Males 19.53 0.0015 7.65 0.0219 89/454 (19.6%)
154/534 (30.7%) GAPD hCV8921288 CARE Case/Control Fatal &
Nonfatal MI Cleaner White Males 14.21 0.0144 8.66 0.0358 88/532
(16.5%) 84/79 (17.5%) GAPD hCV8921288 WOSCOPS Case/Control Fatal
& Nonfatal MI Cleaner White Males 23.91 0.0002 10.29 0.0058
69/429 (20.7%) 154/482 (34.0%) HLA (DPB1 hCV25651174 CARE
Prospective Fatal & Nonfatal MI All Possible White Males 13.57
0.0186 7.75 0.0207 59/429 (13.8%) 83/382 (282 (21.7%) HLA (DPB1
hCV25651174 CARE Prospective Fatal & Nonfatal MI Cleaner White
Males 20.31 0.0011 9.88 0.0072 59/429 (13.8%) 83/382 (21.7%) HLA
(DPB1 hCV25651174 CARE Case/Control Fatal & Nonfatal MI All
Possible White Males 13.9 0.0183 9 0.0111 59/595 (8.9%) 83/577
(14.4%) HLA (DPB1 hCV25651174 CARE Case/Control Fatal &
Nonfatal MI Cleaner White Males 20.01 0.0012 11.53 0.0031 69/421
(14.0%) 83/379 (21.9 (21.9%) HLA (DPB1 hCV8851065 CARE Prospective
Fatal & Nonfatal MI All Possible White Males 14.29 0.0138 5.35
0.0154 63/543 (9.5%) 85/629 (13.5%) HLA (DPB1 hCV8851065 CARE
Prospective Fatal & Nonfatal MI Cleaner White Males 19.31
0.0017 9.3 0.0095 63/453 (13.9%) 85/404 (21.0%) HLA (DPB1
hCV8851065 CARE Case/Control Fatal & Nonfatal MI All Possible
White Males 14.94 0.0106 10.01 0.0067 63/633 (10.0%) 65/619 (13.7%)
HLA (DPB1 hCV8851065 CARE Case/Control Fatal & Nonfatal MI
Cleaner White Males 19.39 0.0016 11.48 0.0032 83/445 (14.2%) 85/401
(21.2%) HLA (DPB1 hCV8851084 CARE Prospective Fatal & Nonfatal
MI Cleaner White Males 17.32 0.0339 8.89 0.032 80/558 (14.4%)
108/492 (22.0%) HLA (DPB1 hCV8851084 CARE Case/Control Fatal &
Nonfatal MI All Possible White Males 12.93 0.0241 7.81 0.0202
80/785 (10.2%) 106/757 (14.3%) HLA (DPB1 hCV8851084 CARE
Case/Control Fatal & Nonfatal MI Cleaner White Males 17.99
0.003 9.78 0.0075 80/548 (14.7%) 108/489 (22.1%) HLA (DPB1
hCV8851085 CARE Prospective Fatal & Nonfatal MI All Possible
White Males 11.72 0.0388 6.08 0.048 74/747 (8.9%) 102/14.0%) HLA
(DPB1 hCV8851085 CARE Prospective Fatal & Nonfatal MI Cleaner
White Males 17.88 0.0031 5.02 0.0182 74/523 (14.1%) 102/485 (21.8%)
HLA (DPB1 hCV8851085 CARE Case/Control Fatal & Nonfatal MI All
Possible White Males 12.2 0.0322 7.44 0.0242 74/733 (10.1%) 102/17
(14.2%) HLA (DPB1 hCV8851085 CARE Case/Control Fatal & Nonfatal
MI Cleaner White Males 18.1 0.0028 10.1 0.0064 74/513 (14.4%)
102/485 (21.9%) HLA (DQB1 hCV9494470 CARE Prospective Fatal &
Nonfatal MI All Possible White Males 12.37 0.0301 5.1 0.0474 82/840
(11.0%) 111/840 (13.2%) HLA (DQB1 hCV9494470 CARE Prospective Fatal
& Nonfatal MI Cleaner White Males 16.24 0.0062 6.35 0.0417
92/683 (15.8%) 111/545 (20.4%) HLA (DQB1 hCV9494470 CARE
Case/Control Fatal & Nonfatal MI All Possible White Males 12.01
0.0347 5.05 0.0485 92/828 (11.1%) 111/823 (13.5%) HLA (DQB1
hCV9494470 CARE Case/Control Fatal & Nonfatal MI Cleaner White
Males 18.35 0.0059 6.72 0.0347 92/572 (16.1%) 111/538 (20.7%) HRC
hCV11506744 WOSCOPS Case/Control Fatal & Nonfatal MI All
Possible White Males 18.27 0.0026 7.55 0.023 59/253 (23.3%) 65/247
(26.3%) HRC hCV11506744 WOSCOPS Case/Control Fatal & Nonfatal
MI Cleaner White Males 20.75 0.0009 6.06 0.0177 59/234 (25.2%)
65/221 (29.4%) IL1A hCV9546471 WOSCOPS Case/Control Fatal &
Nonfatal MI All Possible White Males 20.88 0.0009 6.2 0.0451 77/370
(20.8%) 134/440 (33.8%) IL1RN hCV8737990 CARE Prospective Fatal
& Nonfatal MI All Possible White Males 13.25 0.0209 6.11 0.047
86/642 (10.3%) 61/623 (13.0%) IL1RN hCV8737990 CARE Prospective
Fatal & Nonfatal MI Cleaner White Males 19.22 0.0017 5.15 0.017
86/453 (14.6%) 81/404 (20.0%) IL1RN hCV8737990 CARE Case/Control
Fatal & Nonfatal MI Cleaner White Males 17.24 0.0041 7.18
0.00278 66/444 (14.9%) 81/398 (20.5%) IL9 hCV3275199 CARE
Prospective Fatal & Nonfatal MI All Possible White Males 18.13
0.0026 12.38 0.0021 111/911 (12.2%) 115/919 (12.5%) IL9 hCV3275199
CARE Prospective Fatal & Nonfatal MI Cleaner White Males 19.78
0.0014 10.69 0.0048 111/844 (17.2%) 116/591 (18.5%) IL9 hCV3275199
CARE Case/Control Fatal & Nonfatal MI All Possible White Males
17.77 0.0032 13.04 0.0015 111/896 (12.4%) 116/901%) IL9 hCV3275199
CARE Case/Control Fatal & Nonfatal MI Cleaner White Males 18.5
0.0024 10.68 0.0048 111/833 (17.5%) 116/583 (19.9%) ITGA4
hCV7628858 CARE Prospective Fatal & Nonfatal MI All Possible
White Males 10.26 0.0165 4 0.0455 120/1204 (10.0%) 155/%1182
(13.2%) ITGA4 hCV7628858 CARE Case/Control Fatal & Nonfatal MI
All Possible White Males 11.67 0.0086 5.77 0.0163 120/817 (14.7%)
15/740 (20.9%) ITGA4 hCV7628858 CARE Case/Control Fatal &
Nonfatal MI Cleaner White Males 13.44 0.0038 4.75 0.292 120/817
(14.7%) 155/740 (20.8%) KDR hCV16192174 CARE Prospective Fatal
& Nonfatal MI All Possible White Males 16.78 0.0049 5.22 0.0164
87/985 (8.8%) 130/951 (13.5%) KDR hCV16192174 CARE Prospective
Fatal & Nonfatal MI Cleaner White Males 19.35 0.0017 8.21
0.0165 87/675 (12.9%) 130/620 (21.0%) KDR hCV16192174 CARE
Case/Control Fatal & Nonfatal MI All Possible White Males 19.22
0.0017 10.15 0.0062 87/971 (9.0%) 130/946 (13.7%) KDR hCV16192174
CARE Case/Control Fatal & Nonfatal MI Cleaner White Males 21.49
0.0007 10.88 0.0044 87/666 (13.1%) 130/614 (21.2%) KDR hCV22271999
CARE Prospective Fatal & Nonfatal MI All Possible White Males
16.69 0.0051 0.1 0.0174 129/958 (13.5%) KDR hCV22271999 CARE
Prospective Fatal & Nonfatal MI Cleaner White Males 19.38
0.0016 8.15 0.017 87/874 (12.9%) 129/617 (20.9%) KDR hCV22271999
CARE Case/Control Fatal & Nonfatal MI All Possible White Males
19.26 0.0017 10.18 0.0062 129/943 (13.7%) KDR hCV22271999 CARE
Case/Control Fatal & Nonfatal MI Cleaner White Males 21.51
0.0006 10.95 0.0042 129/811 (21.1%) KLK14 hCV16044337 CARE
Prospective Fatal & Nonfatal MI All Possible White Males 20.37
0.0011 7.7 0.0212 60/560 (10.7%) KLK14 hCV16044337 CARE Prospective
Fatal & Nonfatal MI Cleaner White Males 21.38 0.0007 6.24
0.0442 60/374 (16.0%) 61/353 (17.3%) KLK14 hCV16044337 CARE
Case/Control Fatal & Nonfatal MI All Possible White Males 20.43
0.001 7.95 0.0186 60/548 (10.9%) 61/548 (11.1%) KLK14 hCV16044337
CARE Case/Control Fatal & Nonfatal MI Cleaner White Males 22.34
0.0005 6.75 0.0343 60/385 (16.4%) 81/349 (17.5%) LPA hCV11225004
CARE Case/Control Fatal & Nonfatal MI Cleaner White Males 23.9
0.0002 5.86 0.0325 68/627 (14.0%) 128/585 (22.7%) LRP3 hCV25594815
WOSCOPS Case/Control Fatal & Nonfatal MI All Possible White
Males 19.58 0.0014 9.94 0.0063 133/552 (24.1%) 17/621 (27.5%) LRP3
hCV25594815 WOSCOPS Case/Control Fatal & Nonfatal MI Cleaner
White Males 21.90 0.0005 10.2 0.0081 133/508 (26.1%) 171/563
(30.4%) MYH7 hCV25629396 CARE Prospective Fatal & Nonfatal MI
All Possible White Males 19.04 0.0003 9.53 0.002 118/1200 (9.8%)
154/144 (13.6%) MYH7 hCV25629396 CARE Prospective Fatal &
Nonfatal MI Cleaner White Males 22.27 <.0001 9.49 0.0021 118/829
(14.2%) 154/739 (20.8%) MYH7 hCV25629396 CARE Case/Control Fatal
& Nonfatal MI All Possible White Males 19.29 0.0002 11.83
0.0006 118/1178 (10.0%) 154/1122 (13.7%) MYH7 hCV25629396 CARE
Case/Control Fatal & Nonfatal MI Cleaner White Males 20.59
0.0001 10.99 0.0009 118/815 (14.5%) 154/729 (21.1%) NOS3 hCV3219460
CARE Prospective Fatal & Nonfatal MI All Possible White Males
11.33 0.0452 6.1 0.0474 53/539 (9.8%) 66/526 (12.5%) NOS3
hCV3219460 CARE
Prospective Fatal & Nonfatal MI Cleaner White Males 15.17 0.097
6.72 0.0347 53/368 (14.4%) 68/335 (19.7%) NOS3 hCV3219460 CARE
Case/Control Fatal % NonFatal MI All Possible White Males 11.36
0.0447 6.52 0.0384 53/529 (10.0%) NOS3 hCV3219460 CARE Case/Control
Fatal & Nonfatal MI Cleaner White Males 14.68 0.0124 6.79
0.0335 53/359 (14.8%) NPC1 hCV25472673 CARE Prospective Fatal &
Nonfatal MI Cleaner White Males 24.23 0.0002 10.08 0.0065 53/307
(17.3%) 45/290 (15.5%) NPC1 hCV25472673 CARE Case/Control Fatal
& Nonfatal MI Cleaner White Males 21.33 0.0007 8.55 0.0139
53/304 (17.4%) 45/287 (15.7%) NPC1 hCV7490135 CARE Prospective
Fatal & Nonfatal MI Cleaner White Males 15.4 0.0088 6.22 0.0446
44/240 (18.3%) 36/217 (16.5%) PLAB hCV7494810 CARE Prospective
Fatal & Nonfatal MI All Possible White Males 12.41 0.0296 6.11
0.0047 38/706 (11.9%) 82/675 (12.1%) PLAB hCV7494810 CARE
Case/Control Fatal NonFatal MI All Possible White Males 12.67
0.0267 6.61 0.0368 84/591 (12.4%) 38/448 (8.6%) PLAB hCV7494810
CARE Case/Control Fatal NonFatal MI Cleaner White Males 16.31 0.006
6.33 0.0421 84/481 (17.5%) 82/426 (19.2%) PPOX hCV25922816 CARE
Prospective Fatal & Nonfatal MI All Possible White Males 11.43
0.0435 6.78 0.0338 118/1036 (11.2%) 128/1019 (12.6%) PPOX
hCV25922816 CARE Prospective Fatal & Nonfatal MI Cleaner White
Males 18.35 0.0025 8.32 0.0156 118/721 (16.1%) 128/1019 (12.8%)
PPOX hCV25922816 CARE Case/Control Fatal & Nonfatal MI All
Possible White Males 11.43 0.044 6.78 0.0338 118/1036 (11.2%)
128/1018 (12.6%) PPOX hCV25922816 CARE Case/Control Fatal &
Nonfatal MI Cleaner White Males 15.05 0.0102 7.03 0.0297 99/915
(10.8%) 104/7882 (11.8%) SELL hCV16172571 CARE Prospective Fatal
& Nonfatal MI All Possible White Males 15.39 0.0068 7.03 0.0297
99/930 (10.5%) 105/803 (11.9%) SELL hCV16172571 CARE Case/Control
Fatal & Nonfatal MI All Possible White Males 15.17 0.0097 7.24
0.0256 99/915 (10.8%) 105/870 (12.1%) SELL hCV25474827 CARE
Prospective Fatal & Nonfatal MI All Possible White Males 14.9
0.0108 7.4 0.0256 100/930 (10.8%) 104/882 (11.8%) SELL hCV25474827
CARE Case/Control Fatal & Nonfatal MI All Possible White Males
14.83 0.0111 7.58 0.0215 100/915 (10.9%) 104/569 (12.0%) SERPINA1
hCV25640504 CARE Prospective Fatal & Nonfatal MI Cleaner White
Males 14.83 0.0109 6.03 0.0491 80/489 (16.4%) 65/427 (20.1%)
SERPINA1 hCV25640504 CARE Case/Control Fatal & Nonfatal MI
Cleaner White Males 14.68 0.0118 7.06 0.0293 80/481 (16.5%) 85/418
(20.6%) SERPINA5 hCV9596963 CARE Prospective Fatal & Nonfatal
MI All Possible White Males 15.57 0.0072 9.13 0.0104 60/560 (10.7%)
65/553 (11.8%) SERPINA5 hCV9596963 CARE Prospective Fatal &
Nonfatal MI Cleaner White Males 20.59 0.001 8.37 0.0152 60/407
(14.7%) 65 (545 (11.9%) SERPINA5 hCV9596963 CARE Case/Control Fatal
& Nonfatal MI All Possible White Males 15.98 0.0045 9.24 0.0099
50/554 (10.6%) 65/545 (11.9%) SERPINA5 hCV9596963 CARE Case/Control
Fatal & Nonfatal MI Cleaner White Males 19.95 0.0013 7.74 0.0
60/402 (14.9%) 55/359 (18.1%) SERPINB6 hCV16190893 CARE Prospective
Fatal & Nonfatal MI All Possible White Males 14. 0.0122 8.96
0.0119 74/409 (12.2%) 65/574 (11.5%) SERPINB6 hCV16190893 CARE
Prospective Fatal & Nonfatal MI Cleaner White Males 16.56
0.0054 7.42 0.0245 74/433 (17.1%) 66/360 (18.3%) SERPINB6
hCV16190893 CARE Case/Control Fatal & Nonfatal MI All Possible
White Males 14.41 0.0132 9.19 0.0101 74/598 (12.4%) 65/564 (11.7%)
SERPINB6 hCV16190893 CARE Case/Control Fatal & Nonfatal MI
Cleaner White Males 16.73 0.005 8.96 0.0133 74/425 (17.4%) 65/356
(18.5%) SERPIN12 hCV370782 CARE Prospective Fatal & Nonfatal MI
All Possible White Males 17.89 0.0031 9.54 0.0081 54/483 (11.2%)
51/470 (10.9%) SERPIN12 hCV370782 CARE Prospective Fatal &
Nonfatal MI Cleaner White Males 21.19 0.0007 8.65 0.0132 54/332
(16.3%) 51/229 (17.1%) SERPIN12 hCV370782 CARE Case/Control Fatal
& Nonfatal MI All Possible White Males 15.78 0.0049 0.0118
54/477 (11.3%) 51/480 (11.1%) SERPIN12 hCV370782 CARE Case/Control
Fatal & Nonfatal MI Cleaner White Males 18.6 0.0023 7.91 0.0191
54/326 (16.6%) 51/450 (11.1%) TNF hCV7514879 CARE Prospective Fatal
& Nonfatal MI Cleaner White Males 19.06 0.0019 8.55 0.0138
96/590 (16.3%) 103/541 (19.0%) TNF hCV7514879 CARE Case/control
Fatal & Nonfatal MI Cleaner White Males 17.78 0.0032 7.77
0.0206 96/581 (16.5%) 103/532 (19.4%) VTN hCV2538595 CARE
Prospective Fatal & Nonfatal MI All Possible White Males 18.78
0.0026 7.52 0.0232 39/340 (11.5%) 32/381 (8.9%) VTN hCV2538595 CARE
Prospective Fatal & Nonfatal MI Cleaner White Males 19.68
0.0014 6.07 0.0451 39/240 (16.3%) 32/220 (14.5%) VTN hCV2538595
CARE Case/Control Fatal & Nonfatal MI All Possible White Males
15.11 0.0028 7.48 0.0237 39/334 (11.7%) 32/351 (9.1%) VTN
hCV2538595 CARE Case/Control Fatal & Nonfatal MI Cleaner White
Males 20.02 0.0012 6.98 0.0305 39/236 (16.5%) 32/215 (14.8%) 1 Rare
Allele 2 Rare Alleles n/total (%) n/total (%) Pravastatin vs.
Placebo Odds Ratio (95% CI) Pravastatin Pravastatin Placebo
Patients with 0 Rare Patients with 1 Rare Patients with 2 Rare
Significance Public Patients Placebo Patients Patients Patients
Alleles Allele Alleles Level ABCA1 30/192 (15.6%) 17/165 (10.3%)
2/17 (11.8%) 1/5 (20.0%) 0.69 (0.44 to 0.1) 1.61 (0.71 to 3.8) 0.53
(0.04 to 7.89) P <= 0.05 ABCA1 30/190 (15.6%) 17/159 (10.7%)
2/16 (12.5%) 1/5 (20.0%) 0.60 (0.44 to 0.83) 1.53 (0.80 to 2.91)
0.71 (0.05 to 10.15) P <= 0.05 ADAMTS1 42/305 (13.6%) 51/258
(19.8%) 4/50 (8.0%) 12/42 (28.6%) 0.91 (0.62 to 1.32) 0.64 (0.40 to
1.01) 0.20 (0.06 to 0.68) P <= 0.05 ADAMTS1 43/307 (14.0%)
52/258 (20.2%) 4/50 (8.0%) 12/42 (28.6%) 0.91 (0.63 to 1.33) 0.63
(0.40 to 0.89) 0.20 (0.06 to 0.69) P <= 0.05 AGTR1 57/521
(10.9%) 48/488 (9.4%) 5/100 (5.0%) 20/122 (16.4%) 0.70 (0.48 to
1.04) 1.18 (0.54 to 2.58) 0.27 (0.08 to 0.90) P <= 0.05 AGTR1
57/363 (15.7%) 46/299 (15.4%) 5/89 (7.2%) 20/76 (25.6%) 0.65 (0.43
to 0.97) 1.02 (0.46 to 2.28) 0.23 (0.07 to 0.79) P <= 0.05 AGTR1
57/359 (15.9%) 46/294 (15.6%) 5/67 (7.5%) 20/78 (25.0%) 0.65 (0.43
to 0.97) 1.03 (0.66 to 1.58) 0.26 (0.09 to 0.74) P <= 0.05 ASAH1
62/414 (15.0%) 67/364 (18.4%) 29/220 (13.2%) 21/181 (11.6%) 0.42
(0.24 to 0.73) 0.78 (0.29 to 2.13) 1.16 (0.38 to 3.60) P <= 0.05
CAPG 16/169 (9.5%) 33/160 (20.6%) 3/14 (21.4%) 1/16 (6.3%) 0.81
(0.59 to 1.20) 0.37 (0.19 to 0.71) 6.35 (0.44 to 64.57) P <=
0.05 CAPN10 39/333 (11.7%) 25/326 (7.7%) 3/33 (9.1%) 3/30 (10.0%)
0.63 (0.46 to 0.05) 1.60 (0.75 to 3.39) 0.90 (0.15 to 5.27) P <=
0.05 CAPN10 39/230 (17.0%) 25/199 (12.6%) 3/26 (11.5%) 3/21 (14.3%)
0.58 (0.40 to 0.76) 1.42 (0.65 to 3.09) 0.78 (0.13 to 4.75) P <=
0.05 CAPN10 29/326 (12.0%) 25/316 (7.9%) 3/32 (9.4%) 3/30 (10.0%)
0.62 (0.45 to 0.85) 1.58 (0.93 to 2.70) 1.07 (0.19 to 5.86) P <=
0.05 CAPN10 39/227 (17.2%) 25/196 (12.6%) 3/25 (12.0%) 3/21 (14.3%)
0.56 (0.40 to 0.79) 1.43 (0.82 to 2.49) 0.90 (0.18 to 5.11) P <=
0.05 CAPN2 60/268 (22.4%) 67/320 (20.9%) 10/41 (24.4%) 10/50
(36.0%) 0.48 (0.33 to 0.64) 1.08 (0.73 to 1.60) 0.56 (0.22 to 1.42)
P <= 0.05 CAPN2 60/243 (24.7%) 67/281 (23.6%) 10/39 (25.8%)
18/41 (43.9%) 0.45 (0.32 to 0.63) 1.03 (0.69 to 1.54) 0.43 (0.17 to
1.11) P <= 0.05 CCL11 33/209 (15.8%) 65/738 (27.3%) 7/24 (29.2%)
1/21 (4.8%) 0.63 (0.47 to 0.85) 0.60 (0.31 to 0.80) 8.67 (0.95 to
77.17) P <= 0.05 CCL11 33/192 (17.2%) 65/209 (31.1%) 7/19
(36.0%) 1/18 (5.0%) 0.62 (0.48 to 0.83) 0.48 (0.29 to 0.76) 0.95
(1.07 to 92.24) P <= 0.05 CD163 10/245 (4.1%) 31/248 (12.6%)
3/25 (12.0%) 1/14 (7.1%) 0.97 (0.72 to 1.30) 0.30 (0.12 to 0.72)
1.77 (0.to 19.92) P <= 0.05 CD163 10/168 (6.0%) 31/1(18.7%) 3/20
(15.0%) 1/6 (16.7%) 0.86 (0.64 to 1.17) 0.28 (0.11 to 0.69) 0.86
(0.07 to 11.07) P <= 0.05 CD163 10/243 (4.1%) 31/243 (12.8%)
3/24 (12.5%) 1/14 (7.1%) 0.96 (0.72 to 1.30) 0.29 (0.14 to 0.60)
1.97 (0.18 to 21.69) P <= 0.05 CD163 10/188 (8.0%) 31/185
(18.8%) 3/20 (15.0%) 1/8 (16.7%) 0.88 (0.84 to 1.20) 0.27 (0.13 to
0.57) 0.00 (0.06 to 12.46) P <= 0.05 CD6 43/470 (9.1%) 48/432
(11.1%) 1/92 (1.1%) 10/64 (15.0%) 0.97 (0.68 to 1.37) 0.81 (0.38 to
1.69) 0.06 (0.01 to 0.52) P <= 0.05 CD6 43/323 (13.3%) 48/272
(17.6%) 1/63 (1.6%) 10/37 (27.0%) 0.(0.62 to 1.27) 0.72 (0.33 to
1.54) 0.04 (0.00 to 0.39) P <= 0.05 CD6 43/465 (9.2%) 48/426
(11.3%) 1/91 (1.1%) 10/62 (16.1%) 0.97 (0.64 to 1.38) 0.80 (0.51 to
1.23) 0.06 (0.01 to 0.44) P <= 0.05 CD6 43/320 (13.4%) 48/270
(17.8%) 1/62 (1.6%) 10/37 (27.0%) 0.92 (0.64 to 1.32) 0.68 (0.43 to
1.08) 0.04 (0.01 to 0.36) P <= 0.05 CD6 48/392 (12.2%) 37/406
(9.1%) 5/49 (10.2%) 5/53 (9.4%) 0.58 (0.41 to 0.82) 1.39 (0.67 to
2.91) 1.00 (0.26 to 4.65) P <= 0.05 CD6 48/261 (18.4%) 37/246
(15.0%) 5/28 (17.9%) 5/32 (15.6%) 0.51 (0.35 to 0.72) 1.27 (0.50 to
2.73) 1.17 (0.27 to 5.16) P <= 0.05 CD6 48/381 (12.5%) 37/394
(9.4%) 5/49 (10.2%) 5/52 (9.6%) 0.57 (0.41 to 0.81) 1.39 (0.68 to
2.21) 1.09 (0.29 to 4.06) P <= 0.05 CD6 48/254 (18.9%) 37/240
(15.4%) 5/28 (17.9%) 5/31 (16.1%) 0.49 (0.34 to 0.70) 1.36 (0.84 to
2.20) 1.44 (0.36 to 5.77) P <= 0.05 COL6A2 69/382 (18.1%)
102/395 (25.8%) 38/165 (23.0%) 43/201 (21.4%) 0.39 (0.24 to 0.65)
0.62 (0.44 to 0.88) 1.00 (0.66 to 1.79) P <= 0.05 COL6A2 69/343
(20.1%) 102/345 (29.6%) 38/148 (25.7%) 43/175 (24.6%) 0.39 (0.24 to
0.65) 0.59 (0.42 to 0.84) 1.04 (0.63 to 1.73) P <= 0.05 CR1 1/58
(1.7%) 9/52 (17.3%) 0/0 (0.0%) 0/0 (0.0%) 0.87 (0.66 to 1.14) 0.08
(0.01 to 0.72) P <= 0.05 CR1 1/36 (2.8%) 8/29 (31.0%) 0/0 (0.0%)
0/0 (0.0%) 0.78 (0.59 to 1.03) 0.08 (0.01 to 0.57) P <= 0.05 CR1
1/58 (1.7%) 9/51 (17.6%) 0/0 (0.0%) 0/0 (0.0%) 0.88 (0.65 to 1.13)
0.09 (0.01 to 0.71) P <= 0.05 CR1 1/36 (2.8%) 0/29 (31.0%) 0/0
(0.0%) 0/0 (0.0%) 0.78 (0.69 to 1.04) 0.07 (0.01 to 0.57) P <=
0.05 CXCL16 58/411 (14.1%) 58/389 (15.2%) 27/157 (17.2%) 23/140
(16.4%) 0.38 (0.23 to 0.64) 0.92 (0.36 to 2.33) 1.06 (0.37 to 2.99)
P <= 0.05 CXCL16 58/408 (14.3%) 56/384 (15.4%) 27/155 (17.4%)
23/138 (16.7%) 0.38 (0.23 to 0.64) 0.91 (0.61 to 1.37) 1.12 (0.60
to 2.06) P <= 0.05 ELN 55/409 (13.4%) 65/362 (18.0%) 24/132
(18.2%) 15/123 (12.2%) 0.52 (0.32 to 0.84) 0.71 (0.29 to 1.75) 1.80
(0.55 to 4.88) P <= 0.05 ELN 55/402 (13.7%) 65/359 (18.1%)
24/131 (18.2%) 15/121 (12.4%) 0.53 (0.32 to 0.57) 0.70 (0.47 to
1.05) 1.64 (0.80 to 3.32) P <= 0.05 FCAR 8/96 (8.3%) 28/103
(25.2%) 1/8 (12.5%) 1/4 (25.0%) 0.84 (0.62 to 1.12) 0.27 (0.10 to
0.73) 0.43 (0.02 to 0.77) P <= 0.05 FGB 33/209 (15.6%) 57/219
(26.0%) 8/16 (50.0%) 6/24 (25.0%) 0.63 (0.47 to 0.65) 0.52 (0.32 to
0.84) 3.14 (0.81 to 12.11) P <= 0.05 GALC 20/207 (9.7%) 39/178
(21.9%) 5/34 (14.7%) 2/15 (13.3%) 0.04 (0.68 to 1.30) 0.38 (0.17 to
0.66) 1.12 (0.18 to 7.18) P <= 0.05 GAPO 52/260 (20.0%) 54/244
(22.1%) 10/26 (38.5%) 9/32 (28.1%) 0.50 (0.37 to 0.69) 0.88 (0.57
to 1.35) 1.58 (0.52 to 4.69) P <= 0.05 GAPO 52/227 (22.9%)
54/217 (24.9%) 10/23 (43.6%) 9/32 (28.1%) 0.46 (0.34 to 0.64) 0.89
(0.57 to 1.37) 1.92 (0.62 to 5.03) P <= 0.05 HLA-DPB1 49/514
(0.5%) 58/505 (11.1%) 17/10 (15.5%) 4/98 (4.1%) 0.59 (0.40 to 0.88)
0.84 (0.39 to 1.62) 4.29 (1.17 to 15.78) P <= 0.05 HLA-DPB1
49/345 (14.2%) 58/300 (18.7%) 17/77 (22.1%) 4/69 (5.8%) 0.52 (0.35
to 0.78) 0.72 (0.33 to 1.60) 4.60 (1.22 to 17.36) P <= 0.05
HLA-DPB1 49/504 (9.7%) 58/492 (11.4%) 17/110 (15.5%) 4/96 (4.2%)
0.59 (0.39 to 0.87) 0.84 (0.68 to 1.27) 4.39 (1.42 to 13.62) P
<= 0.05 HLA-DPB1 49/340 (14.4%) 58/295 (19.0%) 17/77 (22.1%)
4/67 (6.0%) 0.51 (0.34 to 0.76) 0.75 (0.49 to 1.15) 4.91 (1.54 to
15.64) P <= 0.05 HLA-DPB1 51/502 (10.2%) 56/480 (11.7%) 13/88
(14.6%) 3/87 (3.4%) 0.62 (0.43 to 0.92) 0.88 (0.40 to 1.63) 4.85
(1.14 to 20.58) P <= 0.05 HLA-DPB1 51/338 (15.2%) 58/294 (19.0%)
13/63 (20.6%) 3/60 (5.0%) 0.65 (0.37 to 0.01) 0.76 (0.35 to 1.67)
4.94 (1.14 to 21.49) P <= 0.05 HLA-DPB1 51/491 (10.4%) 66/489
(11.9%) 13/88 (14.5%) 3/85 (3.5%) 0.60 (0.41 to 0.89) 0.87 (0.68 to
1.31) 5.02 (1.37 to 18.44) P <= 0.05 HLA-DPB1 51/331 (15.4%)
58/289 (19.4%) 13/63 (20.8%) 3/58 (5.2%) 0.52 (0.35 to 0.78) 0.80
(0.52 to 1.23) 5.41 (1.43 to 20.46) P <= 0.05 HLA-DPB1 37/263
(14.1%) 39/234 (16.7%) 7/31 (22.0%) 2/35 (5.7%) 0.61 (0.43 to 0.86)
0.82 (0.38 to 1.75) 4.81 (0.83 to 27.84) P <= 0.05 HLA-DPB1
37/260 (14.2%) 39/228 (17.1%) 7/31 (22.6%) 2/34 (5.9%) 0.80 (0.42
to 0.85) 0.84 (0.51 to 1.38) 6.83 (1.08 to 231.55) P <= 0.05
HLA-DPB1 43/294 (14.0%) 41/245 (16.7%) 8/35 (22.9%) 3/45 (6.7%)
0.58 (0.41 to 0.63) 0.85 (0.40 to 1.63) 4.15 (0.89 to 19.26) P
<= 0.05 HLA-DPB1 43/291 (14.5%) 41/240 (17.1%) 8/35 (22.9%) 3/43
(7.0%) 0.57 (0.40 to 0.62) 0.87 (0.54 to 1.14) 4.59 (1.11 to 19.90)
P <= 0.05 HLA-DOB1 22/361 (8.1%) 42/314 (13.4%) 5/35 (14.3%)
3/40 (7.5%) 0.99 (0.72 to 1.35) 0.42 (0.19 to 0.91) 2.08 (0.41 to
10.25) P <= 0.05 HLA-DOB1 22/241 (9.1%) 42/199 (21.1%) 6/22
(22.7%) 3/25 (12.0%) 0.87 (0.63 to 1.21) 0.38 (0.17 to 0.83) 2.16
(0.41 to 11.39) P <= 0.05 HLA-DOB1 22/356 (6.2%) 42/308 (13.8%)
5/35 (14.3%) 3/40 (7.5%) 0.99 (0.72 to 1.37) 0.40 (0.23 to 0.70)
2.00 (0.44 to 9.18) P <= 0.05 HLA-DOB1 22/240 (9.2%) 42/198
(21.2%) 5/22 (22.7%) 3/25 (12.0%) 0.90 (0.64 to 1.25) 0.36 (0.20 to
0.63) 2.22 (0.45 to 10.85) P <= 0.05 HRC 51/361 (14.1%) 113/402
(28.1%) 30/127 (23.6%) 37/164 (22.6%) 0.85 (0.56 to 1.29) 0.41
(0.28 to 0.69) 1.04 (0.60 to 1.81) P <= 0.05 HRC 51/324 (15.7%)
113/357 (31.7%) 30/113 (26.5%) 37/146 (25.3%) 0.80 (0.52 to 1.23)
0.39 (0.27 to 0.57) 1.05 (0.80 to 1.84) P <= 0.05 L1A 64/306
(20.9%) 78/351 (22.2%) 11/80 (18.3%) 11/61 (18.0%) 0.48 (0.32 to
0.65) 0.81 (0.63 to 1.33) 0.94 (0.37 to 2.38) P <= 0.05 L1A
64/281 (22.8%) 78/307 (25.4%) 11/54 (20.4%) 11/56 (19.5%) 0.45
(0.31 to 0.64) 0.85 (0.58 (0.58 to 1.25) 0.98 (0.38 to 2.51) P
<= 0.05 L1RN 32/325 (9.0%) 53/277 (19.1%) 12/58 (20.7%) 8/87
(11.9%) 0.80 (0.55 to 1.15) 0.46 (0.21 to 1.02 1.92 (0.00 to 6.15)
P <= 0.05 L1RN 32/323 (9.9%) 53/276 (19.2%) 12/57 (21.1%) 8/66
(12.1%) 0.77 (0.53 to 1.12) 0.50 (0.31 to 0.80) 1.97 (0.73 to 5.31)
P <= 0.05 L4R 60/589 (10.2%) 73/557 (13.1%) 27/280 (9.6%) 16/252
(6.3%) 0.58 (0.34 to 0.97) 0.74 (0.51 to 1.07) 1.85 (0.87 to 3.18)
P <= 0.05 L4R 80/415 (14.5%) 73/354 (20.6%) 27/193 (14.0%)
16/149 (10.7%) 0.57 (0.33 to 0.97) 0.64 (0.43 to 0.93) 1.62 (0.78
to 2.96) P <= 0.05 ITGAE 48/360 (13.3%) 55/349 (15.8%) 7/87
(8.0%) 19/72 (26.4%) 0.79 (0.53 to 1.20) 0.64 (0.55 to 1.28) 0.24
(0.09 to 0.61) P <= 0.05 KDR 33/182 (20.4%) 21/137 (15.3%) 1/10
(10.0%) 19/72 (26.4%) 0.79 (0.53 to 1.20) 0.64 (0.55 to 1.28) 0.24
(0.09 to 0.61) P <= 0.05 KDR 33/157 (21.0%) 21/134 (15.7%) 1/10
(10.0%) 3/11 (27.3%) 0.58 (0.42 to 0.81) 1.68 (0.91 to 3.11) 0.35
(0.03 to 4.21) P <= 0.05 KDR 33/157 (21.0%) 21/134 (15.7%) 1/10
(10.0%) 3/11 (27.3%) 0.58 (0.42 to 0.81) 1.68 (0.91 to 3.11) 0.35
(0.03 to 4.21) P <= 0.05 KDR 33/161 (20.5%) 21/136 (15.4%) 1/11
(9.1%) 3/11 (27.3%) 0.61 (0.45 to 0.54) 1.41 (0.63 to 3.16) 0.27
(0.02 to 3.25) P <= 0.05 KDR 33/228 (14.5%) 21/208 (10.1%) 1/18
(6.3%) 3/18 (16.7%) 0.67 (0.49 to 0.91) 1.69 (0.94 to 3.06) 0.38
(0.03 to 4.17) P <= 0.05 KDR 33/158 (21.2%) 21/134 (15.7%) 1/11
(9.1%) 3/11 (27.3%) 0.59 (0.42 to 0.81) 1.69 (0.91 to 3.13) 0.31
(0.03 to 3.71) P <= 0.05 KLK14 54/558 (9.7%) 57/511 (11.2%) 6/14
(5.3%) 23/115 (20.0%) 1.04 (0.69 to 1.57) 0.88 (0.38 to 1.92) 0.22
(0.07 to 0.72) P <= 0.05 KLK14 54/401 (13.5%) 57/323 (17.8%)
6/67 (9.0%) 23/78 (30.3%) 0.97 (0.64 to 1.47) 0.73 (0.32 to 1.67)
0.23 (0.07 to 0.76) P <= 0.05 KLK14 64/549 (9.0%) 57/502 (11.4%)
6/113 (5.3%) 23/113 (20.4%) 1.02 (0.68 to 1.54) 0.85 (0.57 to 1.27)
0.23 (0.09 to 0.00) P <= 0.05 KLK14 54/397 (13.6%) 57/318
(17.9%) 6/67 (9.0%) 23/75 (30.7%) 0.96 (0.64 to 1.50) 0.74 (0.49 to
1.2) 0.23 (0.09 to 0.62) P <= 0.05 LRP3 19/172 (11.0%) 52/176
(29.5%) 3/11 (27.3%) 2/15 (13.3%) 0.76 (0.58 to 1.00) 0.29 (0.16 to
0.51) 2.40 (0.32 to 17.85) P <= 0.05 LRP3 19/158 (12.0%) 62/156
(33.3%) 3/11 (27.3%) 2/12 (16.7%) 0.75 (0.57 to 0.99) 0.26 (0.15 to
0.47) 1.80 (0.24 to 13.73) P <= 0.05 MICA 27/204 (13.2%) 30/168
(17.9%) 6/16 (37.5%) 2/18 (11.1%) 0.67 (0.48 to 0.93) 0.72 (0.40 to
1.27) 6.64 (1.06 to 41.69) P <= 0.05 MYH7 7/31 (22.6%) 1/47
(2.1%) 0/0 (0.0%) 0/0 (0.0%) 0.75 (0.57 to 0.96) 13.41 (1.48 to
121.25) P <= 0.05 MYH7 7/20 (35.0%) 1/27 (3.7%) 0/0 (0.0%) 0/0
(0.0%) 0.68 (0.50 to 0.68) 14.00 (1.48 to 132.80) P <= 0.05 MYH7
7/31 (22.0%) 1/45 (2.2%) 0/0 (0.0%) 0/0 (0.0%) 0.75 (0.57 to 0.96)
12.05 (1.39 to 104.59) P <= 0.05 MYH7 7/20 (35.0%) 1/28 (3.8%)
0/0 (0.0%) 0/0 (0.0%) 0.67 (0.51 to 0.90) 11.70 (1.28 to 107.21) P
<= 0.05 NOS3 60/527 (11.4%) 58/526 (11.0%) 6/169 (3.6%) 17/140
(12.1%) 0.79 (0.52 to 1.18) 1.04 (0.47 to 2.30) 0.27 (0.08 to 0.37
P <= 0.05 NOS3 80/362 (16.6%) 68/335 (17.3%) 6/115 (5.2%) 17/85
(20.0%) 0.70 (0.45 to 1.07) 0.05 (0.42 to 2.16) 0.22 (0.07 to 0.74)
P <= 0.05 NOS3 60/521 (11.5%) 58/521 (11.1%) 6/164 (3.7%)
17/135
(12.6%) 0.78 (0.50 to 1.16) 1.04 (0.71 to 1.54) 0.27 (0.10 to 0.70)
P <= 0.05 NOS3 60/359 (15.7%) 58/333 (17.4%) 6/113 (5.3%) 17/85
(20.0%) 0.57 (0.44 to 1.04) 0.96 (0.86 to 1.47) 0.23 (0.09 to 0.63)
P <= 0.05 NPC1 46/552 (8.3%) 85/575 (11.3%) 18/208 (8.7%) 28/173
(16.2%) 1.25 (0.80 to 1.96) 0.71 (0.29 to 1.74) 0.49 (0.18 to 1.35)
P <= 0.05 NPC1 45/381 (12.1%) 65/380 (18.1%) 18/143 (12.6%)
28/93 (30.1%) 1.21 (0.76 to 1.94) 0.85 (0.43 to 0.06) 0.34 (0.17 to
0.67) P <= 0.05 NPC1 48/378 (12.2%) 65/358 (18.3%) 18/143
(12.6%) 28/93 (30.1%) 1.21 (0.76 to 1.94) 0.85 (0.43 to 0.96) 0.34
(0.17 to 0.87) P <= 0.05 PLAB 34/455 (7.6%) 80/443 (13.6%) 6/72
(8.3%) 4/75 (5.3%) 1.03 (0.73 to 1.46) 0.52 (0.24 to 1.10) 1.61
(0.17 to 0.67) P <= 0.05 PLAB 34/455 (7.6%) 80/443 (13.5%) 6/72
(8.3%) 4/75 (5.3%) 1.03 (0.73 to 1.46) 0.52 (0.24 to 1.10) 1.61
(0.28 to 6.84) P <= 0.05 PLAB 34/449 (7.6%) 60/439 (13.7%) 6/72
(8.3%) 4/73 (5.5%) 1.03 (0.73 to 1.47) 0.50 (0.32 to 0.79) 1.62
(0.43 to 6.05) P <= 0.05 PLAB 34/299 (11.4%) 60/278 (21.6%) 6/57
(10.5%) 4/48 (8.7%) 0.65 (0.66 to 1.37) 0.44 (0.28 to 0.71) 1.45
(0.38 to 5.57) P <= 0.05 PRKCO 51/471 (10.88%) 45/449 (10.1%)
11/100 (11.0%) 3/85 (3.5%) 0.57 (0.40 to 0.83) 1.08 (0.51 to 2.28)
3.38 (0.79 to 14.38) P <= 0.05 PRKCO 51/343 (14.6%) 45/284
(17.0%) 11/62 (17.7%) 3/42 (7.1%) 0.58 (0.39 to 0.82) 0.085 (0.39
to 1.84) 2.80 (0.63 to 12.38) P <= 0.05 PRKCO 51/343 (14.6%)
45/284 (17.0%) 11/62 (17.7%) 342 (7.1%) 0.58 (0.39 to 0.82) 0.85
(0.39 to 1.84) 2.60 (0.63 to 12.38) P <= 0.05 SERPINAS 41/515
(8.0%) 65/515 (12.8%) 21/139 (15.1%) 10/11 (9.0%) 0.89 (0.59 to
1.33) 0.57 (0.38 to 0.87) 1.72 (0.77 to 3.00) P <= 0.05 SN
66/443 (14.6%) 58/382 (15.2%) 13/174 (7.5%) 35/168 (20.0%) 0.72
(0.43 to 1.33) 0.57 (0.37 to 2.66) 0.31 (0.10 to 0.93) P <= 0.05
SN 66/439 (15.0%) 58/378 (15.3%) 13/173 (7.5%) 25/184 (21.3%) 0.71
(0.42 to 1.19) 1.02 (0.69 to 1.51) 0.30 (0.15 to 0.00) P <= 0.05
TAP1 28/349 (8.0%) 42/329 (12.8%) 1/36 (2.8%) 8/33 (24.2%) 1.00
(0.73 to 1.38) 0.60 (0.28 to 1.27) 0.09 (0.01 to 0.82) P <= 0.05
TAP1 26/237 (11.8%) 42/214 (19.6%) 1/25 (4.0%) 8/24 (33.3%) 0.65
(0.63 to 1.23) 0.55 (0.25 to 1.19) 0.06 (0.01 to 0.79) P <= 0.05
TAP1 26/347 (8.1%) 42/319 (13.2%) 1/36 (2.8%) 6/33 (24.2%) 0.98
(0.71 to 1.36) 0.61 (0.37 to 1.01) 0.06 (0.01 to 0.70) P <= 0.05
TAP1 28/236 (11.0%) 42/209 (20.1) 1/25 (4.0%) 8/24 (33.3%) 0.69
(0.63 to 1.25) 0.66 (0.33 to 0.94) 0.05 (0.01 to 0.72) P <= 0.05
TMP2 30/234 (12.8%) 44/200 (22.0%) 7/24 (29.2%) 1/17 (5.9%) 0.76
(0.54 to 1.08) 0.56 (0.33 to 0.93) 6.81 (0.74 to 62.68) P <=
0.05 TNF 24/223 (10.8%) 41/211 (19.4%) 3/35 (8.8%) 4/9 (44.4%) 0.88
(0.83 to 1.21 0.88 (0.60 to 1.21 0.12 (0.02 to 0.75) P <= 0.05
TNF 24/219 (11.0%) 41/209 (19.6%) 3/34 (8.8%) 4/9 (44.4%) 0.87
(0.62 to 1.22) 0.62 (0.30 to 0.90) 0.14 (0.02 to 0.81) P <= 0.05
VTN 56/629 (8.9%) 74/567 (13.1%) 21/265 (7.9%) 32/238 (11.9%) 1.54
(0.90 to 2.54) 0.65 (0.23 to 1.81) 0.63 (0.21 to 1.93) P <= 0.05
VTN 56/428 (13.1%) 74 (65 (20.7%) 21/12.1%) 32/175 (18.3%) 1.31
(0.76 to 2.27) 0.58 (0.20 to 1.64) 0.61 (0.20 to 1.93) P <= 0.05
VTN 56/620 (9.0%) 74/559 (13.2%) 21/260 (8.1%) 32/263 (12.2%) 1.51
(0.58 to 2.69) 0.63 (0.43 to 0.91) 0.66 (0.37 to 1.19) P <= 0.05
VTN 56/424 (13.2%) 74/352 (21.0%) 21/165 (12.5%) 32/174 (18.4%)
1.37 (0.78 to 2.42) 0.68 (0.38 to 0.82) 0.84 (0.35 to 1.16) P <=
0.05 A2M 72/540 (13.3%) 72/544 (13.2%) 11/144 (7.6%) 20/138 (14.5%)
0.55 (0.38 to 0.83) 1.04 (0.73 to 1.48) 0.47 (0.21 to 1.02) P <=
0.05 A2M 72/380 (18.9%) 72/351 (20.5%) 11/101 (10.9%) 20/(23.3%)
0.53 (0.34 to 0.61) 0.93 (0.65 to 1.25) 0.38 (0.17 to 0.5) P <=
0.05 ABCA1 59/517 (11.4%) 58/487 (11.5%) 12/94 (12.8%) 6/0 (7.5%)
0.55 (0.38 to 0.77) 0.99 (0.49 to 2.00) 1.80 (0.56 to 5.89) P <=
0.05 ABCA1 59/375 (15.7%) 58/304 (18.4%) 12/65 (18.5%) 6/54 (11.1%)
0.52 (0.35 to 0.74) 0.83 (0.40 to 1.71) 1.81 (0.54 to 0.11) P <=
0.05 ABCA1 59/509 (11.6%) 56/478 (11.7%) 12/93 (12.9%) 6/77 (7.8%)
0.55 (0.38 to 0.78) 0.98 (0.66 to 1.46) 1.71 (0.61 to 4.83) P <=
0.05 ABCA1 59/371 (15.9%) 56/298 (18.8%) 12/64 (18.8%) 6/53 (11.3%)
0.62 (0.36 to 0.76) 0.82 (0.54 to 1.34) 1.81 (0.62 to 5.28) P <=
0.05 ABCA1 31/282 (11.0%) 19/253 (7.5%) 4/23 (17.4%) 1/14 (7.1%)
0.83 (0.48 to 0.84) 1.52 (0.71 to 3.25) 2.74 (0.28 to 28.71) P
<= 0.05 ABCA1 31/193 (16.1%) 19/167 (11.4%) 4/19 (21.1%) 1/5
(20.0%) 0.58 (0.42 to 0.76) 1.49 (0.68 to 3.27) 1.07 (0.08 to
13.02) P <= 0.05 ABCA1 31/279 (11.1%) 19/242 (7.9%) 4/22 (18.2%)
1/13 (7.7%) 0.63 (0.48 to 0.84) 1.48 (0.80 to 2.87) 2.99 (0.29 to
30.35) P <= 0.05 ABCA1 31/191 (16.2%) 19/160 (11.9%) 4/18
(22.2%) 1/5 (20.0%) 0.57 (0.43 to 0.77) 1.37 (0.73 to 2.65) 1.30
(0.12 to 16.54) P <= 0.05 ADAM12 25/393 (6.4%) 44/357 (12.3%)
7/58 (12.1%) 11/54 (20.4%) 0.98 (0.72 to 1.33) 0.47 (0.28 to 0.79)
0.47 (0.17 to 1.33) P <= 0.05 ADAM12 25/260 (9.6%) 44/224
(19.6%) 7/41 (17.1%) 11/38 (30.8%) 0.91 (0.66 to 1.25) 0.42 (0.25
to 0.72) 0.37 (0.12 to 1.10) P <= 0.05 ALOX12 64/611 (10.5%)
68/544 (12.5%) 15/198 (7.6%) 42/236 (17.8%) 1.00 (0.85 to 1.53)
0.82 (0.36 to 1.87) 0.38 (0.14 to 1.00) P <= 0.05 ALOX12 64/16
(10.4%) 69/545 (12.%) 15/18 (7.8%) 42/236 (17.8%) 1.00 (0.65 to
1.54) 0.80 (0.35 to 1.83) 0.38 (0.14 to 1.00) P <= 0.05
C14orf159 57/511 (11.2%) 65/488 (11.3%) 7/140 (5.0%) 24/160
(18.0%9) 0.78 (0.53 to 1.08) 0.98 (0.48 to 2.05) 0.30 (0.10 to
0.87) P <= 0.05 C14orf159 67/499 (11.4%) 65/476 (11.6%) (7/140
(5.0%) 24/158% (15.4%) 0.74 (0.52 to 1.07) 0.99 (0.66 to 1.47) 0.30
(0.12 to 0.73) P <= 0.05 CAPN2 70.268 (26.1%) 78/320 (24.4%)
10/41 (24.4%) 21/50 (42.0%) 0.52 (0.38 to 0.72) 1.07 (0.73 to 1.55)
0.48 (0.18%1.13) P <= 0.05 CAPN2 70/253 (27.7%) 78/282 (26.7%)
10.39 (25.6%) 21/44 (47.7%) 0.51 (0.37 to 0.70) 1.02 (0.70 to 1.60)
0.38 (0.15 to 0.38) P <= 0.05 CCL11 43/209 (20.6%) 75/238
(31.5%) 1024 (41.7%) 2/21 (9.5%) 0.67 (0.50 to 0.89) 0.57 (0.37 to
0.55) 5.95 (1.31 to 37.07) P <= 0.05 CCL11 43/202 (21.3%) 75/219
(34.2%) 10/22 (45.5%) 2/19 (10.5%) 0.65 (0.49 to 0.87) 0.53 (0.34
to 0.82) 7.20 (1.32 to 39.14) P <= 0.05 CD163 12/245 (4.9%)
37/248 (15.0%) 4/25 (16.0%) 2/14 (14.3%) 0.89 (0.68 to 1.18) 0.29
(0.13 to 0.67) 1.14 (0.17 to 7.64) P <= 0.05 CD163 12/170 (7.1%)
37/172 (21.5%) 4/21 (19.0%) 2/7 (20.6%) 0.80 (0.60 to 1.07) 0.28
(0.12 to 0.65) 0.59 (0.08 to 4.48) P <= 0.05 CD163 12/242 (5.0%)
37/243 (15.2%) 4/24 (16.7%) 2/14 (14.3%) 0.09 (0.67 to 1.18) 0.28
(0.14 to 0.56) 1.23 (0.19 to 7.95) P <= 0.05 CD163 12/167 (7.2%)
37/171 (21.6%) 4/21 (19.0%) 2/7 (28.6%) 0.82 (0.81 to 1.09) 0.27
(0.13 to 0.54) 0.64 (0.00 to 4.75) P <= 0.05 CD6 48/470 (10.2%)
59/432 (13.7%) 2/92 (2.2%) 10/64 (15.6%) 0.89 (0.84 to 1.23) 0.72
(0.36 to 1.43) 0.12 (0.02 to 0.63) P <= 0.05 CD6 48/328 (14.6%)
59/283 (20.8%) 2/64 (3.1%) 10/37 (27.0%) 0.62 (0.59 to 1.15) 0.56
(0.32 to 1.33) 0.09 (0.02%0.47) P <= 0.05 CD6 48/483 (10.4%)
59/425 (13.9%) 2/91 (2.2%) 10/62 (16.1%) 0.89 (0.56 to 1.230) 0.71
(0.47 to 1.07) 0.12 (0.02 to 0.55) P <= 0.05 CD6 48/324 (14.8%)
69/280 (21.1%) 2/63 (3.2%) 10/37 (27.0%) 0.84 (0.59 to 1.16) 0.63
(0.41 to 0.97) 0.09 (0.02 to 0.42) P <= 0.05 COL11A1 30/332
(9.0%) 49/332 (14.8%) 1/52 (1.9%) 7/51 (12.7%) 0.92 (0.68 to 1.25)
0.67 (0.35 to 0.93) 0.11 (0.01 to 0.95) P <= 0.05 COL2A1 27/233
(11.6%) 40/215 (18.6%) 7/20 (35.0%) 1/14 (7.1%) 0.68 (0.49 to 0.91)
0.60 (0.35 to 1.02) 7.20 (0.77 to 67.69) P <= 0.05 CR1 2/58
(3.4%) 11/52 (21.2%) 0/0 (0.0%) 0/0 (0.0%) 0.81 (0.62 to 1.04) 0.13
(0.03 to 0.67) P <= 0.05 CR1 2/37 (5.4%) 11/31 (35.5%) 0/0
(0.0%) 0/00.0%) 0.73 (0.56 to 0.95) 0.100.02 to 0.56) P <= 0.05
CR1 2/58 (3.4%) 11/51 (21.6%) 0/0 (0.0%) 0/0 (0.0%) 0.80 (0.62 to
1.03) 0.13 (0.03 to 0.62) P <= 0.05 CR1 2/37 (5.4%) 11.31
(35.5%) 0/0 (0.0%) 0/0 (0.0%) 0.73 (0.58 to 0.95) 0.11 (.02 to
0.53) P <= 0.05 CXCL16 60/611 (11.1%) 74/584 (12.7%) 32/237
(13.5%) 26/223 (11.7%) 0.41 (0.25 to 0.67) 0.96 (0.36 to 2.06) 1.18
(0.48 to 3.11) P <= 0.05 CXCL16 68/421 (16.2%) 74/387 (19.1%)
32/162 (19.8%) 26/143 (18.2%) 0.34 (0.21 to 0.57) 0.81 (0.33 (0.33
to 2.00) 1.11 (0.41 to 3.03) P <= 0.05 CXCL16 68/600 (11.3%)
74573 (12.9%) 32/233 (13.7%) 26/217 (12.0%) 0.41 (0.25 to 0.87)
0.85 (0.60 to 1.22) 1.17 (0.67 to 2.04) P <= 0.05 CXCL16 68/414
(14.4%) 74/382 (19.4%) 32/160 (20.0%) 26/140 (15.6%) 0.34 (0.21 to
0.57) 0.81 (0.58 to 1.17) 1.14 (0.94 to 2.05) P <= 0.05 CYBA
58/587 (10.2%) 68/525 (16.0%) 23/135 (16.9%) 15/132 (11.4%) 0.57
(0.39 to 0.85) 0.77 (0.53 to 1.12) 1.64 (0.81 to 3.33) P <= 0.05
DDEF1 83/368 (22.6%) 117/392%29.5%) 42/197 (25.1%) 36/152 (23.7%)
0.45 (0.29 to 0.71) 0.68 (0.49 to 0.95) 1.06 (0.64 to 1.77) P <=
0.05 ELN 60/599 (10.0%) 75/579 (13.0%) 28/208 (13.5%) 16/201 (8.0%)
0.54 (0.35 to 0.02) 0.75 (0.34 to 0.68) 1.80 (0.69 to 4.70) P <=
0.05 ELN 60/414 (14.5%) 76/372 (20.2%) 28/136 (20.6%) 16/124
(12.8%) 0.47 (0.31 to 0.74) 0.67 (0.29 to 1.53) 1.75 (0.65 to 4.73)
P <= 0.05 ELN 60/589 (10.2%) 75/571 (13.1%) 28/204 (13.7%)
18/197 (8.1%) 0.52 (0.34 to 0.80) 0.74 (0.52 to 1.07) 1.90 (0.99 to
3.65) P <= 0.05 ELN 60/407 (14.7%) 75/389 (20.3%) 28/133 (21.1%)
16/121 (13.2%) 0.48 (0.30 to 0.70) 0.68 (0.45 to 0.97) 1.84 (0.93
to 3.64) P <= 0.05 F13A1 48/422 (10.8%) 59/428 (13.8%) 14/72
(19.4%) 7/73 (9.6%) 0.63 (0.45 to 0.59) 0.76 (0.52 to 1.17) 2.29
(0.58 to 6.12) P <= 0.05 F7 35/238 (14.8%) 20.208 (9.8%) 1/13
(7.7%) 3/18 (18.7%) 0.64 (0.48 to 0.84) 1.64 (0.77 to 3.48) 0.42
(0.04 to 4.75) P <= 0.05 F7 35/170 (20.6%) 20/130 (15.4%) 1/9
(11.1%) 3/12 (25.0%) 0.58 (0.43 to 0.78) 1.43 (0.85 to 3.11) 0.38
(0.03 to 4.59) P <= 0.05 F7 35/233 (15.0%) 20/204 (9.8%) 1/13
(7.7%) 3/16 (16.7%) 0.63 (0.46 to 0.84) 1.58 (0.87 to 2.84) 0.51
(0.05 to 5.64) P <= 0.05 F7 35/168 (20.5%) 20/128 (15.6%) 1/9
(11.1%) 3/12 (25.0%) 0.59 (0.44 to 0.79) (1.37 (0.74 to 2.54) 0.38
(0.03 to 4.63) P <= 0.05 F7 34/259 (13.1%) 24/234 (10.3%)
2/14.3%) 1/21 (4.6%) 0.64 (0.45 to 0.85) 1.32 (0.63 to 2.76) 3.33
(0.26 to 42.67) P <= 0.05 F7 34/258 (13.3%) 24/231 (10.4%) 2/14
(14.3%) 1/21 (4.8%) 0.64 (0.46 to 0.85) 1.27 (0.73 to 2.23) 3.73
(0.30 to 46.57) P <= 0.05 FABP1 53/508 (10.4%) 68/513 (13.5%)
19/127 (15.0%) 11/128 (8.7%) 0.61 (0.42 to 0.88) 0.76 (0.37 to
1.57) 1.54 (0.58 to 5.00) P <= 0.05 FABP1 (53/352 (15.1%) 58/328
(20.7%) 19/19 (20.9%) 11/64 (13.1%) 0.65 (0.38 to 0.80) (0.68 (0.32
to 1.44) 1.76 (0.52 to 4.92) P <= 0.05 FABP1 53/348 (15.3%)
68/324 (21.0%) 19/19 (20.9%) 11/82 (13.4%) 058 (0.38 to 0.83) 0.65
(0.44 to 0.99) 1.73 (0.76 to 3.96) P <= 0.05 FCAR 11/160 (6.9%)
30/162 (18.5%) 1/8 (12.5%) 1/12 (8.3%) 0.84 (0.74 to 1.10) 0.33
(0.16 to 0.69) 1.78 (0.09 to 33.90) P <= 0.05 FN1 65/482 (11.4%)
60/463 (10.8%) 12.87 (13.8%) 14/91 (15.4%) 0.58 (0.40 to 0.79) 1.08
(0.72 to 1.63) 0.92 (0.39 to 2.14) P <= 0.05 GALC 22/209 (10.5%)
43/182 (23.6%) 8/34 (14.7%) (2/15 (13.3%) 0.83 (0.62 to 1.12) 0.38
(0.18 to 0.82) 1.12 (0.18 to 7.06) P <= 0.05 GAPD 35/256 (13.7%)
57/232 (24.8%) 4/38 (10.5%) 10/35 (28.8%) 0.93 (0.67 to 1.29) 0.49
(0.23) 0.29 (0.07 to 1.18) P <= 0.05 GAPD 35/358 (9.8%) 67/651
(16.2%) 4/53 (7.6%) 10/52 (19.2%) 0.86 (0.71 to 1.35) 0.57 (0.36 to
0.90) 0.310.09 to 1.07) P <= 0.05 GAPD 63/260 (24.2%) 59/244
(24.2%) (10.26 (38.5%) 9/32 (28.1%) 0.54 (0.40 to 0.73 0.99 (0.68
to 1.49) 1.51 (0.50 to 4.55) P <= 0.05 GAPD 35/251 (13.9%)
57/227 (25.1%) 4/38 (10.5%) 10/35 (28.8%) 0.92 (0.68 to 1.28) 0.62
(0.32 to 0.83) 0.25 (0.07 to 0.93) P <= 0.05 GAPD 63//238
(2835%) 59/222 (26.8%) 10/23 (43.5%) 9/32 (28.1%) 0.50 (0.37 to
0.67) 0.98 (0.85 to 1.49) 1.90 (5.62 to 5.63) P <= 0.05 HLA
(DPB1 51 (514 (9.9%) 69/505 (13.7%) 17/110 (15.5%) 6/98 (6.1%) 0.65
(0.46 to 0.93) 0.70 (0.34 to 1.42) 2.00 (0.89 to 8.80) P <= 0.05
HLA (DPB1 51/347 (14.7%) 69/313 (22.0%) 17/77 (22.1%) 6/71 (8.5%)
0.67 (0.40 to 0.83) 0.81 (0.29 to 1.26) 3.07 (0.95 to (9.92) P
<= 0.05 HLA (DPB1 51/504 (10.1%) 69/492 (14.0%) 17/109 (15.6%)
6/95 (6.3%) 0.65 (0.46 to 0.83) 0.58 (0.46 to 1.01) 2.88 (1.08 to
7.67) P <= 0.05 HLA (DPB1 51/342 (14.6%) 69/308 (22.4%) 17/76
(22.4%) 8.68 (8.8%) 0.65 (0.39 to 0.82) 0.62 (0.41 to 0.93) 3.24
(1.18 to 8.91) P <= 0.05 HLA (DPB1 49/502 (9.8%) 55/480 (14.2%)
15/88 (17.0%) 5/87 (5.7%) 0.70 (0.49 to 0.98) 0.66 (0.32 to 1.33)
3.37 (1.00 to 11.32) P <= 0.05 HLA (DPB1 49/334 (14.7%) 68/308
(22.2%) 15/65 (23.1%) 5/62 (8.1%) 0.61 (0.42 to 0.87) 0.60 (0.29 to
1.25) 3.42 (0.99 to 11.62) P <= 0.05 HLA (DPB1 49/491 (10.0%)
68/469 (14.5%) 15/87 (17.2%) 6/84 (8.0%) 0.68 (0.48 to 0.97) 0.68
(0.44 to 0.97) 3.52 (1.21 to 10.24) P <= 0.05 HLA (DPB1 49/329
(14.9%) 68/301 (22.6%) 15/64 (23.4%) 5/59 (8.5%) 0.69 (0.41 to
0.05) 0.62 (0.41 to 0.93) 3.77 (1.25 to 11.38) P <= 0.05 HLA
(DPB1 39/265 (14.7%) 48/243 (19.8%) 5/32 (25.0%) 2/35 (5.7%) 0.60
(0.43 to 0.82) 0.70 (0.34 to 1.43) 6.50 (0.98 to 30.84) P <=
0.05 HLA (DPB1 39/385 (10.1%) 48/368 (13.0%) 8/42 (19.0%) 2/44
(4.5%) 0.60 (0.50 to 0.93) 0.74 (0.47 to 1.17) 5.69 (1.10 to 25.50)
P <= 0.05 HLA (DPB1 39/262 (14.9%) 48 (237 (20.3%) 8/31 (25.8%)
2/33 (6.1%) 0.59 (0.43 to 0.82) 0.70 (0.73 to 1.3) 6.70 (1.26 to
35.51) P <= 0.05 HLA (DPB1 44/443 (10.2%) 52/407 (12.6%) 9/52
(17.3%) 3/59 (5.1%) 0.67 (0.49 to 0.92) 0.77 (0.39 to 1.54) 3.91
(0.90 to 16.95) P <= 0.05 HLA (DPB1 44/295%14.9%) 52/258 (20.3)
9/25.0%) 3/45 (6.7%) 0.56 (0.43 to 0.82) 0.69 (0.34 to 1.40) 4.66
(1.04 to 20.92) P <= 0.05 HLA (DPB1 44/428 (10.3%) 52/395
(13.2%) 9/17.5%) 3/56 (5.4%) 0.58 (0.49 to 0.94) 0.74 (0.46 to
0.14) 4.24 (1.07 to 16.85) P <= 0.05 HLA (DPB1 44/292 (15.1%)
52/251 (20.7%) 9/35 (25.7%) 3/42 (7.1%) 0.59 (0.42 to 0.63) 0.69
(0.44 to 1.08) 5.34 (1.29 to 22.12) P <= 0.05 HLA (DQB1 28/361
(7.8%) 44/314 (14.0%) 7/35 (20.0%) 3/40 (7.5%) 0.81 (0.60 to 1.08)
0.52 (0.25 to 1.05) 3.08 (0.67 to 14.16) P <= 0.05 HLA (DQB1
28/247 (11.3%) 44/201 (21.9%) 7/24 (29.2%) 3/25 (12.0%) 073 (0.54
to 0.99) 0.46 (0.22 to 0.95) 3.02 to 14.69) P <= 0.05 HLA (DQB1
28/353 (7.9%) 44/308 (14.3%) 7/35 (20.0%) 3/40 (7.5%) 0.01 (0.60 to
1.09) 0.51 (0.31 to 0.85) 2.83 (0.66 to 12.06) P <= 0.05 HLA
(DQB1 28/244 (11.5%) 44/200%) 7/24 (29.2%) 3/25 (12.0%) 0.74 (0.55
to 1.023) 0.45 (0.27 to 0.76) 2.93 (0.64 to 13.37) P <= 0.05 HRC
65/361 (18.0%) 124/402 (30.8%) 35/127 (27.8%) 42 (%164 (25.6%) 0.84
(0.58 to 1.26) 0.49 (0.35 to 0.69) 1.08 to 1.82) P <= 0.05 HRC
65/33819.2%) 124/368 (33.7%) 35/118 (29.7%) 42/151 (27.8%) 0.80
(0.53 to 1.21) 0.46 (0.33 to 0.66) 1.08 (0.63 to 1.53) P <= 0.05
IL1A 74/306 (24.2%) 86/351 (24.5%) 11/60 (16.3%) 11/61 (18.0%) 0.62
(0.36 to 0.73) 0.95 (0.68 to 1.36) 0.95 (0.38 to 2.40) P <= 0.05
IL1RN 43/496 (6.7%) 66/451 (14.3%) 17/95 (17.9%) 11.101 (10.9%)
0.77 (0.54 to 1.08) 0.57 (0.28 to 1.06) 1.78 (0.65 to 4.88) P <=
0.05 IL1RN 43/338 (12.8%) 65/290 (22.8%) 17/63 (27.0%) 11/7015.7%)
0.68 (0.48 to 0.97) 0.50 (0.24 to 1.05) 1.98 (0.70 to 6.65) P <=
0.05 IL1RN 43/332 (13.0%) 66/689 (22.6%) 17.62 (27.4%) 11.69
(15.9%) 0.65 (0.45 to 0.94) 0.63 (0.35 to 0.62) 0.96 (0.82 to 4.65)
P <= 0.05 IL9 15.290 (5.2%) 39/253 (15.4%) 1/28 (3.6%) 3/21
(14.3%) 0.98 (0.73 to 1.27) 0.30 (0.14 to 0.66) 0.22 (0.02 to 2.42)
P <= 0.05 IL9 15/187 (8.0%) 39/168 (23.1%) 1/19 (5.3%) 3/11
(27.3%) 0.85 (0.64 to 1.14) 0.29 (0.13 to 0.65) 0.15%0.01 to 1.74)
P <= 0.05 IL9 15/283 (5.3%) 39/247 (15.8%) 1/28 (3.6%) 3/21
(14.3%) 0.95 (0.72 to 1.26) 0.30 (0.16 to 0.56) 0.21 (0.02 to 2.18)
P <= 0.05 IL9 15%184 (8.2%) 39 (166 (23.5%) 1/19 (5.3%) 3/11
(27.3%) 0.05 (0.83 to 1.14) 0.30 (0.15 to 0.57) 0.16 (0.01 to 1.77)
P <= 0.05 ITGA4 5/21 (23.8%) 2/30 (6.7%) 0/0 (0.0%) 0/0 (0.0%)
0.72 (0.56 to 0.93) 4.36 (0.72 to 26.56) P <= 0.05 ITGA4 5/16
(31.3%) 2/18 (11.1%) 0/0 (0.0%) 0/00.0%) 0.65 (0.50 to 0.85) 4.64
(0.74 to 29.19) P <= 0.05 ITGA4 5/18 (31.3%) 2/18 (11.1%) 0/0
(0.0%) 0/0 (0.0%) 0.65 (0.50 to 0.85) 4.64%0.74 to 29.19) P <=
0.05 KDR 39/235 (16.6%) 25/215 (11.6%) 1/15 (6.7%) 2/16 (11.1%)
0.62 (0.46 to 0.83) 1.51 (0.73 to 3.12) 0.57 (0.04 to 7.33) P <=
0.05 KDR 39/168 (23.2%) 25/141 (17.1%) 1/10 (10.0%) 2/10 (20.0%)
0.58 (0.41 to 0.75) 1.40 (0.56 to 2.85) 0.44 (0.03 to 6.17) P <=
0.05 KDR 39/17.2%) 25/206 (12.1%) 1/15 (%6.7%) 2/18 (11.1%) 0.50
(0.45 to 0.81) 1.63 (0.94 to 2.82) 0.57 (0.05 to 8.25) P <= 0.05
KDR 39/163 (21.9) 25/136 (18.4%) 1/10 (10.0%) 2/10 (20.0%) 0.54
(0.40 to 0.73) 1.59 (0.90 to 2.82) 0.52 (0.04 to 6.89) P <= 0.05
KDR 39/234 (16.7%) 25/214 (11.7%) 1.16 (6.3%) 2/18 (11.1%) 0.62
(0.47 to 0.83) 1.51 (0.73 to 3.12) 0.53 (0.04 to 6.82) P <= 0.05
KDR 39/167 (23.4%) 25/140 (17.9%) 1/11 (9.1%) 2/10 (20.0%) 0.56
(0.42 to 0.75) 1.40 (0.66 to 2.98) 0.40 (0.03 to 5.51) P <= 0.05
KDR 39/228 (17.3%) 25/206 (12.1%) 1/16 (8.3%) 2/18 (11.1%) 0.61
(0.45 to 0.61) 1.64 (0.95 to 2.83) 0.62 (0.05 to 7.57) P <= 0.05
KDR 39/162 (24.1%) 25/138 (16.4%) 1/11 (9.1%) 2/10
(20.0%) 0.54 (0.40 to 0.74) 1.80 (0.90 to 2.84) 0.45 (0.03 to 6.08)
P <= 0.005 KLK14 57/556 (10.3%) 68/511 (13.3%) 9/114 (7.9%)
27/115 (23.5%) 0.98 (0.67 to 1.43) 0.74 (0.35 to 1.58) 0.28 (0.10
to 0.79) P <= 0.05 KLK14 57/404 (14.1%) 68/334 (20.4%) 9/70
(12.9%) 27/80 (33.8%) 0.91 (0.62 to 1.25) 0.84 (0.29 to 1.40) 0.29
(0.10 to 0.85) P <= 0.05 KLK14 57/547 (10.4%) 68/501 (13.8%)
9/113 (8.0%) 27/113 (23.9%) 0.96 (0.68 to 1.41) 0.75 (0.51 to 1.09)
0.28 (0.12 to 0.83) (P <= 0.05 KLK14 57/399 (14.3%) 68/328
(20.7%) 9/70 (12.9%) 27/79 (34.2%) 0.92 (0.62 to 1.37) 0.65 (0.44
to 0.97) 0.28 (0.12 to 0.85) P <= 0.05 LPA 29/188 (15.4%) 25/178
(14.0%) 7/17 (41.2%) 3/11 (27.3%) 0.58 (0.41 to 0.76) 1.13 (0.83 to
2.03) 2.42 (0.46 to 12.85) P <= 0.05 LRP3 25/172 (14.5%) 59/178
(33.6%) 7/17 (27.3%) 3/15 (20.0%) 0.82 (0.63 to 1.07) 0.33 (0.20 to
0.57) 1.46 (0.23 to 9.19) P <= 0.05 LRP3 25/164 (15.2%) 59/163
(38.2%) 3/11 (27.3%) 3/13 (23.1%) 0.80 (0.61 to 1.04) 0.31 (0.19 to
0.54) 1.21 (0.19 to 7.76) P <= 0.05 MYH7 9/31 (29.0%) 2/47
(4.3%) 0/0 (0.0%) 0/0 (0.0%) 0.70 (0.54 to 0.90) 9.19 (1.73 to
48.90) P <= 0.005 MYH7 9/22 (40.9%) 2/28 (7.1%) 0/0 (0.0%) 0/0
(0.0%) 0.83 (0.48 to 0.82) 9.00 (1.60 to 50.73) P <= 0.005 MYH7
9/31 (29.0%) 2/45 (4.4%) 0/0 (0.0%) 0/0 (0.0%) 0.70 (0.54 to 0.90)
8.60 (1.70 to 43.64) P <= 0.005 MYH7 9/22 (40.9%) 2/27 (7.4%)
0/0 (0.0%) 0/0 (0.0%) 0.63 (0.48 to 0.83) 8.16 (1.51 to 44.20) P
<= 0.005 NOS3 64/527 (12.1%) 67/528 (12.7%) 10/169 (5.9%) 23/140
(18.4%) 0.76 (0.52 to 1.12) 0.95 (0.45 to 2.00) 0.32 (0.12 to 0.88)
P <= 0.05 NOS3 64/366 (17.5%) 67/344 (19.5%) 10/119 (8.4%) 23/91
(25.3%) 0.69 (0.48 to 1.12) 0.88 (0.42 to 1.90) 0.27 (0.09 to 0.78)
P <= 0.05 NOS3 64/520 (12.3%) 67/521 (12.9%) 10/164 (6.1%)
23/134 (17.2%) 0.75 (0.51 to 1.10) 0.32 (0.15 to 0.70) P <= 0.05
NOS3 64/383 (17.6%) 67/342 (19.8%) 10/117 (8.5%) 23/90 (25.6%) 0.90
(0.51 to 1.32) 0.29 (0.13 to 0.64) P <= 0.05 NPC1 51/386 (13.2%)
81/376 (21.5%) 22/150 (14.7%) 31/98 (31.6%) 1.14 (0.74 to 1.75)
0.55 (0.24 to 1.30) 0.37 (0.14 to 0.99) P <= 0.05 NPC1 51/378
(13.5%) 81/370 (21.9%) 22/147 (15.0%) 31/96 (32.3%) 0.58 (0.39 to
0.65) 0.37 (0.20 tp 0.70) P <= 0.05 NPC1 58/408 (13.7%) 81/387
(20.9%) 27/196 (13.8%) 40/160 (25.0%) 1.13 (0.70 to 1.83) 0.48
(0.17 to 1.31) P <= 0.05 PLAB 38/455 (8.4%) 68/443 (15.3%) 5/72
(6.9%) 8/75 (10.7%) 098 (0.71 to 1.35) 0.50 (0.25 to 1.02) 0.83
(0.17 to 2.28) P <= 0.05 PLAB 68/437 (6.9%) 8/73 (11.0%) 0.96
(0.71 to 1.36) 049 (0.32 to 0.76) 0.62 (0.19 to 2.02) P <= 0.05
PLAB 38/302 (12.8%) 68/264 (23.9%) 5/58 (18.9%) 8/50 (16.0%) 0.90
(0.64 to 1.25) 0.44 (0.23 to 0.69) 0.57 (0.17 to 1.89) P <= 0.05
PPOX 10/169 5.9%) 25/143 (17.5%) 1/5 (20.0%) P <= 0.05 PPOX
10/169 (5.9%) 25/143 (17.5%) 1/6 (16.7%) 1/5 (20.0%) 0.58 (0.67 to
1.15) 0.30 (0.12 to 0.73) P <= 0.05 PPOX 10/169 (5.9%) 25/143
(17.5%) 1/6 (16.7%) 1/5 (20.0%) 0.58 (0.61 to 1.06) 0.23 (0.09 to
0.59) 0.50 (0.01 to 20.18) P <= 0.05 PPOX 23/278 (8.3%) 62/283
(18.4%) 4/27 (14.8%) 1/19 (5.3%) 0.90 (0.67 to 1.21) 0.42 (0.20 to
0.87) 2.77 (0.27 to 28.37) P <= 0.05 SELL 23/173 (8.4%) 52/291
(17.9%) 4/31 (12.9%) 1/9 (5.3%) 0.88 (0.65 to 1.16) 0.42 (0.20 to
0.87) 2.57 (0.26 to 27.29) P <= 0.05 SELL 23/269 (3.6%) 62/280
(18.5%) 4/28 (14.3%) 1/19 (5.3%) 0.58 (0.65 to 1.18) 0.42 (0.25 to
0.71) 2.47 (0.25 to 24.40) P <= 0.05 SELL 23/278 (8.3%) 52/294
(17.7%) 4/30 (13.3%) 1/19 (5.3%) 0.90 (0.57 to 1.21) 0.42 (0.20 to
0.87) 2.77 (0.27 to 28.37) P <= 0.05 SELL 23/272 (8.5%) 52/283
(18.4%) 4/27 (14.8%) 1/19 (5.3%) 0.90 (0.57 to 1.20) 0.42 (0.25 to
0.71) 2.49 (0.25 to 24.61) P <= 0.05 SERPINA1 29/199 (14.6%)
32/181 (17.7%) 10/119 (3.4%) 29/117 (24.8%) 0.78 (0.55 to 1.09)
0.79 (0.36 to 1.77) 0.280.11 to 0.73) P <= 0.05 SERPINA1 29/195
(14.6%) 32/150 (17.6%) 10/116 (8.5%) 29/117 (24.5%) 0.78 (0.55 to
1.10) 0.51 (0.45 to 1.42) 0.27 (0.12 to 0.58) P <= 0.05 SERPINA5
44/526 (8.4%) 81/527 (15.4%) 23/142 (16.2%) 12/113 (10.5%) 0.90
(0.52 to 1.31) 0.50 (0.24 to 1.05) 1.53 (0.51 to 4.35) P <= 0.05
SERPINA5 44/347 (12.7%) 81/337 (24.0%) 23/95 (24.2%) 12/69 (17.4%)
0.80 (0.54 to 1.17) 0.46 (0.21 to 1.00) 1.52 (0.55 to 4.22) P <=
0.05 SERPINA5 44/515 (8.5%) 81/514 (15.8%) 23/138 (16.7%) 12/110
(40.9%) 0.91 (0.52 to 1.32) 0.49 (0.33 to 0.73) 1.52 (0.55 to 4.22)
P <= 0.05 SERPINA5 44/339 (13.0%) 81/333 (24.3%) 23/24.5%) 12/67
(17.9%) 0.80 (0.54 to 1.18) 0.46 (0.31 to 0.70) 1.48 (0.58 to 3.25)
P <= 0.05 SERPINB6 45/505 (8.9%) 70/504 (13.9%) 5/118 (6.5%)
21/111 (18.9%) 1.06 (0.75 to 1.52) 0.61 (0.28 to 1.25) 0.31 (0.11
to 0.90) P <= 0.05 SERPINB6 45/334 (13.5%) 70/333 (21.0%) 8/84
(9.5%) 21/74 (28.4%) 0.92 (0.54 to 1.32) 0.59 (0.27 to 1.25) 0.27
(0.09 to 0.79) P <= 0.05 SERPINB6 45/498 (9.0%) 70/493 (14.2%)
8/114 (7.0%) 21/108 (19.4%) 1.05 (0.74 to 1.51) 0.61 (0.41 to 0.91)
0.30 (0.13 to 0.71) P <= 0.05 SERPINB6 45/328 (13.7%) 70/327
(21.4%) 8/34 (9.5%) 21/73 (28.8%) 0.92 (0.63 to 1.34) 0.50 (0.40 to
0.91) 0.24 (0.10 to 0.58) P <= 0.05 SERPIN12 51/565 (9.0%)
90/541 (16.5%) 22/187 (11.8%) 17/179 (9.5%) 1.03 (0.69 to 1.55)
0.60 (0.22 to 1.10) 1.27 (0.48 to 3.36) P <= 0.05 SERPIN12
51/382 (13.4%) 90/687 (25.4%) 22/139 (15.8%) 17/116 (14.7%) 0.94
(0.62 to 1.44) 0.45 (0.20 to 1.03) 1.10 (0.40 to 2.95) P <= 0.05
SERPIN12 51/554 (9.2%) 90/531 (16.9%) 22/182 (12.1%) 17/175 (9.7%)
1.02 (0.68 to 1.54) 0.50 (0.35 to 0.73) 1.24 (0.83 to 2.43) P <=
0.05 SERPIN12 51/377 (13.5%) 90/351 (25.6%) 22/136 (16.2%) 17/113
(15.0%) 0.95 (0.52 to 1.45) 0.46 (0.31 to 0.68) 1.08 (0.43 to 2.12)
P <= 0.05 TNF 28/227 (12.3%) 50/220 (22.7%) 3/35 (8.6%) 5/10
(50.0%) 0.83 (0.61 to 1.12) 0.48 (0.23 to 0.89) 0.09 (0.02 to 0.56)
P <= 0.05 TNF 25/223 (12.6%) 50/218 (22.9%) 3/34 (5.8%) 5/10
(50.0%) 0.83 (0.60 to 1.13) 0.45 (0.29 to 0.81) 0.11 (0.02 to 0.56)
P <= 0.05 VTN 64/629 (10.2%) 93/587 (16.4%) 24/288 (9.0%) 33/258
(12.3%) 1.33 (0.81 to 1.18) 0.58 (0.23 to 1.46) 0.71 (0.25 to 1.98)
P <= 0.05 VTN 54/436 (14.7%) 93/376 (24.7%) 24/177 (13.5%)
33/176 (18.8%) 1.14 (0.69 to 1.69) 0.52 (0.20 to 1.37) 0.68 (0.24
to 1.96) P <= 0.05 VTN 64/620 (10.3%) 93/559 (16.6%) 24/259
(9.3%) 33/362 (12.6%) 1.31 (0.80 to 2.15) 0.56 (0.40 to 0.80) 0.73
(0.41 to 1.28) P <= 0.05 VTN 64/432 (14.8%) 93/371 (25.1%)
24/171 (14.0%) 33/174 (19.0%) 1.19 (0.71 to 2.01) 0.51 (0.39 to
0.73) 0.70 (0.39 to 1.25) P <= 0.05 *For the CARE prospective
study: results of the Overall Score Test (chi-square test) for the
logistic regression model in which the phenotype (case definition)
is a function of the SNP genotype treament group, and the
interaction between SNP genotype and treatment group. For
case/control studies: results of the Overall Score Test (chi-square
test) for the conditional logistic regression model in which the
phenotype (case definition) is a function of the SNP genotype,
treatment group and the interaction between SNP genotype and
treatment group, and cases and controls have been matched on age
and smoking status. **For the CARE prospective studies: results of
the Chi-square test of the interection between SNP genotype &
treatment group (based on the logistic regression model). For the
case/control study: results of the Chi-square test of the
interaction between SNP genotype and treatment group (based on the
conditional logistic regression model). ***All Possible Controls
include all controls with genotype data. Cleaner controls include
controls with genotype data but with no other CVD-related events
during the trial.
[0492]
20TABLE 14 Statistically Significant Associations Between SNP
Genotypes and Two CVD Case Definitions: Fatal MI/ Sudden
Death/Definite Non-fatal MI and Fatal/Non-fatal MI Overall* Placebo
Pattents Control Group Chi-Source Test SNP Effect n/total (%)
Public Marker Study Study Desion Case Definition Definition***
Stratum Statistic p-value Statistic p-value Rare Alleles 1 Rare
Allele ABCA1 hCV2741083 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI All White Males 6.3 0.0428 6.11 0.047
113/927 (12.2%) 17/253 (6.7%) Possible ABCA1 hCV2741083 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 7.75 0.0207 7.47 0.0239 113/575 (19.7%) 17/165 (10.3%)
ABCA1 hCV2741083 CARE Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI All White Males 7.81 0.0201 11.08 0.0256 113/916
(12.3%) 17/243 (7.0%) Possible ABCA1 hCV2741083 WOSCOPS
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All White
Males 7.56 0.0229 12.38 0.0148 143/604 (23.7%) 60/195 (30.8%)
Possible ABCA1 hCV2741083 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 7.97 0.0186 10.53
0.0324 113/572 (19.8%) 17/159 (10.7%) ABCA1 hCV2741083 WOSCOPS
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 6.4 0.0408 11.04 0.0261 143/531 (25.9%) 60/173 (34.7%)
ABO hCV25610774 CARE Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI Cleaner White Males 6.53 0.0382 9.54 0.049 86/436
(19.7%) 43/262 (16.4%) ABO hCV25610819 CARE Case/Control Fatal
MI/Sudden Death/Definite Non-fatal MI All White Males 6.21 0.0449
9.97 0.041 86/675 (12.7%) 43/431 (10.0%) Possible ABO hCV25610819
CARE Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI
Cleaner White Males 7.34 0.0255 10.21 0.0371 86/430 (20.0%) 43/260
(16.5%) ABO hCV8784787 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 6.84 0.0327 9.94
0.0414 86/434 (19.8%) 43/263 (16.3%) ADAMTS1 hCV529706 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All White
Males 5.5 0.0388 12.25 0.0156 67/695 (9.6%) 51/406 (12.6%) Possible
ADAMTS1 hCV529706 CARE Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI Cleaner White Males 6.41 0.0405 11.88 0.0183 67/434
(15.4%) 51/258 (19.6%) ADAMTS1 hCV529710 CARE Prospective Fatal
MI/Sudden Death/Definite Non-fatal MI Cleaner White Males 5.99
0.0499 5.85 0.0536 67/439 (15.3%) 52/263 (19.8%) ADAMTS1 hCV529710
CARE Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All
White Males 6.95 0.031 12.91 0.0117 67/696 (9.6%) 52/410 (12.7%)
Possible ADAMTS1 hCV529710 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 7.01 0.0301 12.83
0.0121 67/435 (15.4%) 52/258 (20.2%) APOB hCV25990803 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All White
Males 10.07 0.0015 6.22 0.0126 129/1169 (11.0%) 2/4 (50.0%)
Possible APOB hCV3216558 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 6.15 0.0462 9.56
0.0486 91/455 (20.0%) 35/246 (14.2%) APOB hCV7615376 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 6.19 0.0452 9.51 0.0496 91/455 (20.0%) 35/247 (14.2%)
ASAH1 hCV2442143 CARE Prospective Fatal MI/Sudden Death/Definite
Non-fatal MI Cleaner White Males 7.17 0.0278 7 0.0302 43/196
(21.9%) 67/384 (18.4%) ASAH1 hCV2442143 CARE Case/Control Fatal
MI/Sudden Death/Definite Non-fatal MI All White Males 7.98 0.0185
11.92 0.018 43/314 (13.7%) 67/577 (11.6%) Possible ASAH1 hCV2442143
CARE Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI
Cleaner White Males 10.34 0.0057 12.44 0.0144 43/195 (22.1%) 67/357
(18.8%) ATF6 hCV25831989 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 7.08 0.0291 6.66
0.0376 113/606 (18.6%) 11/115 (9.6%) ATF6 hCV25831989 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 7.71 0.0212 10.59 0.0316 113/599 (18.9%) 11/113 (9.7%)
BAIAP3 hCV2503034 CARE Prospective Fatal MI/Sudden Death/Definite
Non-fatal MI All White Males 8.74 0.0126 7.03 0.0296 98/956 (10.3%)
29/223 (13.0%) Possible BAIAP3 hCV2503034 CARE Prospective Fatal
MI/Sudden Death/Definite Non-fatal MI Cleaner White Males 10.16
0.0062 8.48 0.0144 98/609 (16.1%) 29/123 (23.6%) BAIAP3 hCV2503034
CARE Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All
White Males 7.89 0.0193 10.09 0.0389 98/936 (10.5%) 29/221 (13.1%)
Possible BAIAP3 hCV2503034 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 8.23 0.0164 11.74
0.0194 98/601 (16.3%) 29/122 (23.8%) BAT2 hCV7514722 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All White
Males 6.4 0.0409 6.3 0.0426 51/838 (9.7%) 47/319 (14.7%) Possible
BAT2 hCV7514722 CARE Prospective Fatal MI/Sudden Death/Definite
Non-fatal MI Cleaner White Males 7.47 0.0239 7.36 0.0253 81/530
(15.3%) 47/196 (24.0%) BAT2 hCV7514722 CARE Case/Control Fatal
MI/Sudden Death/Definite Non-fatal MI All White Males 6.34 0.042
5.97 0.0618 81/824 (9.8%) 47/312 (15.1%) Possible BAT2 hCV7514722
CARE Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI
Cleaner White Males 7.11 0.0286 9.59 0.0479 81/525 (15.4%) 47/192
(24.5%) BDKRB2 hCV25933600 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI All White Males 6.04 0.0487 5.93 0.0515
59/609 (9.7%) 65/481 (13.5%) Possible BDKRB2 hCV25933600 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 6.29 0.043 6.21 0.0448 59/386 (15.3%) 65/299 (21.7%)
CAPN2 hCV781558 WOSCOPS Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI All White Males 7.68 0.0215 9.99 0.0405 124/442
(28.1%) 67/320 (20.9%) Possible CAPN2 hCV781558 WOSCOPS
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 9.12 0.0104 11.45 0.022 124/396 (31.3%) 67/281 (23.8%)
CASP1 hCV16276495 CARE Prospective Fatal MI/Sudden Death/Definite
Non-fatal MI All White Males 12.26 0.0005 11.88 0.0006 91/961
(9.5%) 40/228 (17.5%) Possible CASP1 hCV16276495 CARE Prospective
Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner White Males
10.7 0.0011 10.43 0.0012 91/591 (15.4%) 40/149 (26.8%) CASP1
hCV16276495 CARE Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI All White Males 9.14 0.0025 8.94 0.0028 91/945 (9.6%)
40/223 (17.9%) Possible CASP1 hCV16276495 CARE Case/Control Fatal
MI/Sudden Death/Definite Non-fatal MI Cleaner White Males 8.34
0.0039 8.16 0.0043 91/585 (15.6%) 40/147 (27.2%) CCKBR hCV9604851
CARE Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All
White Males 13.75 0.001 10.68 0.0048 121/1058 (11.4%) 7/130 (5.4%)
Possible CCKBR hCV9604851 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 12.61 0.0018 8.61
0.0135 121/666 (18.2%) 7/74 (9.5%) CCKBR hCV9604851 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All White
Males 11.64 0.0027 14.34 0.0063 121/1038 (11.7%) 7/128 (5.5%)
Possible CCKBR hCV9604851 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 9.26 0.0098 11.17
0.0248 121/657 (18.4%) 7/74 (9.5%) CCL22 hCV3268420 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All White
Males 11.27 0.0036 6.88 0.032 121/1079 (11.2%) 8/112 (7.1%)
Possible CCL22 hCV3268420 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI All White Males 12.96 0.0015 11.27
0.0236 121/1059 (11.4%) 8/110 (7.3%) Possible CCRL2 hCV25637308
CARE Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All
White Males 12.07 0.0024 10.08 0.0055 105/1029 (10.2%) 21/150
(14.0%) Possible CCRL2 hCV25637308 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 8.98 0.0112 7.69
0.0214 105/637 (16.5%) 21/96 (21.9%) CCRL2 hCV25637308 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All White
Males 13.52 0.0012 15.11 0.0045 105/1011 (10.4%) 21/146 (14.4%)
Possible CCRL2 hCV25637308 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 7.02 0.0299 9.24
0.0555 105/629 (16.7%) 21/95 (21.1%) CCRL2 hCV25637309 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 6.17 0.0456 5.85 0.0505 60/258 (19.4%) 67/349 (19.2%)
CCL2A1 hCV25606528 CARE Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI All White Males 6.1 0.0474 7.59 0.1079 113/1042
(10.8%) 16/126 (12.7%) Possible CPT1A hCV15851335 CARE Prospective
Fatal MI/Sudden Death/Definite Non-fatal MI All White Males 9.05
0.0108 7.1 0.0288 116/1019 (11.4%) 12/169 (7.1%) Possible CR1
hCV25598589 CARE Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI All White Males 5.25 0.022 5.01 0.0253 119/1105
(10.8%) 11/62 (17.7%) Possible CR1 hCV25598589 CARE Case/Control
Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner White Males
6.01 0.0142 5.66 0.0173 119/693 (17.2%) 11/38 (28.9%) CX3CR1
hCV7900503 CARE Prospective Fatal MI/Sudden Death/Definite
Non-fatal MI All White Males 7.89 0.0193 7.75 0.0208 78/587 (13.3%)
41/507 (5.1%) Possible CX3CR1 hCV7900503 CARE Prospective Fatal
MI/Sudden Death/Definite Non-fatal MI Cleaner White Males 8.19
0.0167 8.04 0.018 78/380 (20.5%) 41/311 (13.2%) CX3CR1 hCV7900503
CARE Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All
White Males 7.39 0.0249 9.56 0.484 78/577 (13.5%) 41/497 (8.2%)
Possible CX3CR1 hCV7900503 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 6.9 0.317 9.06
0.0597 78/376 (20.7%) 41/306 (13.4%) DBH hCV12020339 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 9.48 0.0087 11.92 0.018 118/634 (18.6%) 10/93 (10.8%)
F7 hCV783184 WOSCOPS Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI All White Males 6.41 0.0406 9.66 0.0466 178/259
(27.0%) 28/146 (19.2%) Possible F7 hCV783184 WOSCOPS Case/Control
Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner White Males
6.68 0.0354 9.86 0.0428 178/579 (30.7%) 28/132 (21.2%) GBA
hCV2276802 CARE Prospective Fatal MI/Sudden Death/Definite
Non-fatal MI Cleaner White Males 7.05 0.0079 6.95 0.0084 45/189
(23.8%) 85/555 (15.3%) HLA-A hCV11689916 CARE Prospective Fatal
MI/Sudden Death/Definite Non-fatal MI All Possible White Males 6.49
0.039 6.38 0.0412 33/404 (8.2%) 42/381 (11.0%) HLA-A hCV11689916
CARE Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 6.08 0.0478 9.44 0.0511 33/399 (8.3%) 42/371
(11.3%) HLA-DPB1 hCV11916894 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI All Possible White Males 6.68 0.0354
6.56 0.0377 92/932 (9.9%) 38/245 (15.5%) HLA-DPB1 hCV11916894 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 10.56 0.0051 10.26 0.0059 92/591 (15.6%) 38/141 (27.0%)
HLA-DPB1 hCV11916894 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 8.93 0.0115 11.82
0.0187 92/584 (15.8%) 38/139 (27.3%) HLA-DPB1 hCV25651174 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 7.46 0.024 6.51 0.0388 71/370 (19.2%) 56/300 (18.7%)
HLA-DPB1 hCV25651174 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 7.05 0.0295 6.92
0.0531 71/368 (19.3%) 56/295 (19.0%) HLA-DPB1 hCV8851065 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 7.18 0.0276 6.07 0.048 72/391 (18.4%) 56/294 (19.0%)
HSPG2 hCV1603656 WOSCOPS Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI All Possible White Males 6.4 0.0408
7.98 0.0924 174/665 (26.2%) 31/133 (23.3%) HSPG2 hCV1603656 WOSCOPS
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 7.43 0.0243 7.85 0.0974 174/589 (29.5%) 31/117 (26.5%)
IL1A hCV9546471 WOSCOPS Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI All Possible White Males 7.56 0.0228 13.48 0.0092
121/400 (30.3%) 78/351 (22.2%) IL1A hCV9546471 WOSCOPS Case/Control
Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner White Males
7.87 0.0195 14.02 0.0072 121/354 (34.2%) 78/307 (25.4%) IL1B
hCV9546517 CARE Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI Cleaner White Males 6.1 0.0474 11.13 0.0252 65/427
(15.2%) 56/257 (21.8%) IL1RL1 hCV25607108 CARE Prospective Fatal
MI/Sudden Death/Definite Non-fatal MI All Possible White Males 9.45
0.0089 9.2 0.0101 49/451 (10.9%) 56/556 (9.0%) IL1RL1 hCV25607108
CARE Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 10.51 0.0052 10 0.0404 49/443 (11.1%) 50/545
(9.2%) IL1RL1 hCV25607108 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 7.32 0.0257 7.99
0.0919 49/281 (17.4%) 50/326 (15.3%) IL4R hCV2769554 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 8.2 0.0165 7.89 0.0194 42/371 (11.3%) 73/564
(12.9%) IL4R hCV2769554 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 7.04 0.0296 6.82
0.0331 42/233 (18.0%) 73/564 (20.4%) IL4R hCV2769554 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 10.46 0.0053 10.12 0.0384 42/361 (11.6%)
73/557 (13.1%) IL4R hCV2769554 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 8.54 0.014 8.68
0.0732 42/230 (18.3%) 73/354 (20.8%) ITGA9 hCV25644901 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 11.24 0.0008 10.71 0.0011 107/665 (16.1%) 24/76 (31.6%)
KIAA0329 hCV25751017 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI All Possible White Males 6.96 0.0082
6.62 0.0101 113/1102 (10.3%) 13/62 (21.0%) KIAA0329 hCV25751017
CARE Prospective Fatal MI/Sudden Death/Definite Non-fatal MI
Cleaner White Males 6.8 0.0091 6.42 0.0113 113/687 (16.4%) 13/40
(32.65%) KLK14 hCV16044337 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI All Possible White Males 12.02 0.0025
11.5 0.0032 50/560 (8.9%) 57/511 (11.2%) KLK14 hCV16044337 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 10.52 0.0052 10.11 0.0064 50/342 (14.6%) 57/323 (17.6%)
KLK14 hCV16044337 CARE Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI All Possible White Males 13 0.0015 18.35 0.0011 50/549
(9.1%) 57/502 (11.4%) KLK14 hCV16044337 CARE Case/Control Fatal
MI/Sudden Death/Definite Non-fatal MI Cleaner White Males 12.07
0.0024 17.46 0.0016 50/339 (14.7%) 57/318 (17.9%) KLKB1 hCV22272267
CARE Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 6.55 0.0379 6.44 0.0399 27/311 (8.7%) 61/592
(10.3%) KLKB1 hCV22272267 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI All Possible White Males 7.61 0.0223
10.02 0.04 27/308 (8.8%) 61/578 (10.6%) KLKB1 hCV22272267 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 6.3 0.0428 10.73 0.0296 27/197 (13.7%) 61/349 (17.6%)
LAPTM5 hCV25632652 CARE Prospective Fatal MI/Sudden Death/Definite
Non-fatal MI All Possible White Males 7.22 0.0271 7.11 0.0286
67/694 (8.9%) 59/418 (14.1%) LAPTM5 hCV25632652 CARE Case/Control
Fatal MI/Sudden Death/Definite Non-fatal MI All Possible White
Males 7.4 0.0247 11.11 0.0254 62/681 (9.1%) 59/409 (14.4%) LRP2
hCV16165996 WOSCOPS Prospective Fatal MI/Sudden Death/Definite
Non-fatal MI Cleaner White Males 6.37 0.0414 5.2 0.0743 82/431
(19.0%) 47/265 (17.7%) LRP2 hCV16165996 CARE Case/Control Fatal
MI/Sudden Death/Definite Non-fatal MI All Possible White Males 7.7
0.0213 9.65 0.0468 121/469 (25.8%) 64/283 (22.6%) LRP2 hCV16165996
WOSCOPS Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI
Cleaner White Males 6.12 0.047 7.77 0.1003 82/427 (19.2%) 47/260
(18.1%) LRP2 hCV16165996 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 9.52 0.0086 11.4
0.0224 121/426 (28.4%) 64/241 (26.6%) LTA hCV7514870 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 6.37 0.0415 6.27 0.0434 45/532 (8.5%) 69/536
(12.9%) LTA hCV7514870 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 7.34 0.0255 7.24
0.0268 45/334 (13.5%) 69/330 (20.9%) LTA hCV7514870 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 7.11 0.0286 14.18 0.0068 45/521 (8.6%) 69/527
(13.1%) LTA hCV7514870 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 6.17 0.0458 12.7
0.0129 45/329 (136.7%) 69/328 (21.0%) MARK3 hCV25926771 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 3.98 0.0461 3.93 0.0473 39/453 (8.6%) 68/713
(12.3%) MARK3 hCV25926771 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 3.93 0.0474 3.89
0.0485
39/279 (14.0%) 68/446 (19.7%) MC1R hCV11951095 CARE Prospective
Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner White Males
6.79 0.0092 6.29 0.121 124/655 (18.9%) 7/90 (7.8%) MMP7 hCV3210838
CARE Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 8.2 0.0166 6.66 0.0358 93/739 (12.6%) 37/398
(9.3%) MMP7 hCV3210838 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 7.01 0.0301 5.63
0.0599 93/472 (19.7%) 37/239 (15.5%) MMP7 hCV3210838 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 7.4 0.0248 10.52 0.0325 93/728 (12.8%) 37/389
(9.5%) MMP7 hCV3210838 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 7.68 0.0217 10.49
0.0329 93/467 (19.9%) 37/236 (15.7%) MMP8 hCV11484594 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 6.33 0.0422 6.2 0.045 25/206 (12.1%) 72/353 (20.4%) MTR
hCV16172188 CARE Prospective Fatal MI/Sudden Death/Definite
Non-fatal MI All Possible White Males 4.82 0.0282 4.63 0.0314
118/1131 (10.4%) 12/62 (19.4%) MTR hCV16172188 CARE Prospective
Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner White Males
4.17 0.0413 4.01 0.0451 118/702 (16.8%) 12/41 (29.3%) NDUFS2
hCV25653285 CARE Prospective Fatal MI/Sudden Death/Definite
Non-fatal MI All Possible White Males 4.65 0.0311 3.96 0.0467
128/1186 (10.8%) 3/9 (33.3%) NDUFS2 hCV25653285 CARE Case/Control
Fatal MI/Sudden Death/Definite Non-fatal MI All Possible White
Males 6.66 0.0099 5.38 0.0204 128/1164 (11.0%) 3/9 (33.3%) NDUFS2
hCV25653285 CARE Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI Cleaner White Males 5.09 0.024 4.11 0.0426 128/729
(17.6%) 3/6 (50.0%) NOS2A hCV11889257 CARE Prospective Fatal
MI/Sudden Death/Definite Non-fatal MI All Possible White Males 6.53
0.0383 6.29 0.043 77/785 (9.6%) 51/364 (14.0%) NOS2A hCV11889257
CARE Prospective Fatal MI/Sudden Death/Definite Non-fatal MI
Cleaner White Males 6.93 0.0313 6.64 0.0361 77/486 (15.8%) 61/228
(22.4%) NOS2A hCV11889257 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI All Possible White Males 7.19 0.0274
10.14 0.0381 77/774 (9.9%) 61/355 (14.4%) NOS2A hCV11889257 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 6.82 0.0331 9.62 0.0474 77/482 (16.0%) 61/223 (22.9%)
NPC1 hCV25472673 CARE Prospective Fatal MI/Sudden Death/Definite
Non-fatal MI All Possible White Males 7.63 0.022 7.47 0.0239 37/436
(8.6%) 65/575 (11.3%) NPC1 hCV25472673 CARE Prospective Fatal
MI/Sudden Death/Definite Non-fatal MI Cleaner White Males 13.16
0.0014 12.68 0.0018 37/282 (13.1%) 65/360 (18.1%) NPC1 hCV25472673
CARE Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 6.45 0.0397 11.68 0.02 37/428 (8.6%) 65/567
(11.5%) NPC1 hCV25472673 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 10.66 0.0048 16.12
0.0029 37/279 (13.3%) 65/356 (18.3%) PDGFRA hCV22271841 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 15.64 0.0004 11.07 0.004 100/944 (10.6%)
26/231 (11.3%) PDGFRA hCV22271841 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 13.98 0.0009 8.72
0.0128 100/580 (17.2%) 26/152 (17.1%) PDGFRA hCV22271841 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 13.11 0.0014 13.93 0.0075 100/925 (10.8%)
26/228 (11.4%) PDGFRA hCV22271841 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 11.59 0.003 11.42
0.0222 100/573 (17.5%) 26/150 (17.3%) PEMT hCV7443062 WOSPCOPS
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 6.76 0.034 12.19 0.016 74/235 (31.5%) 64/386
(21.8%) PLAB hCV7494810 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 7.12 0.0284 9.73
0.0452 67/411 (16.3%) 60/278 (21.6%) PNN hCV2092598 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 6.41 0.0405 5.35 0.0691 110/1043 (10.5%)
18/141 (12.8%) PNN hCV2092598 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 10.31 0.0058 6.48
0.0392 110/655 (16.8%) 18/83 (21.7%) PNN hCV2092598 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 6.28 0.0433 9.09 0.0589 110/1023 (10.8%)
18/139 (12.9%) PNN hCV2092598 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 7.25 0.0267 8.69
0.0694 110/647 (17.0%) 18/82 (22.0%) PRKCQ hCV15954277 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 6.97 0.0306 6.29 0.043 83/657 (12.6%) 45/445
(10.1%) PRKCQ hCV15954277 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI All Possible White Males 6.96 0.0308
10.69 0.0302 83/645 (12.9%) 45/437 (10.3%) PRKCQ hCV15954277
WOSPCOPS Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI
All Possible White Males 6.73 0.0345 10.97 0.027 132/442 (29.9%)
66/317 (20.8%) PRKCQ hCV15954277 WOSPCOPS Case/Control Fatal
MI/Sudden Death/Definite Non-fatal MI Cleaner White Males 6.87
0.0323 11.06 0.0259 132/391 (33.8%) 66/280 (23.6%) SERPINA10
hCV1260411 CARE Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI Cleaner White Males 7.97 0.0185 11.07 0.0258 89/536
(16.6%) 41/178 (23.0%) SERPINA10 hCV7586197 CARE Prospective Fatal
MI/Sudden Death/Definite Non-fatal MI Cleaner White Males 7.44
0.0242 6.8 0.0335 86/537 (16.0%) 41/179 (22.9%) SERPINA10
hCV7586197 CARE Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI Cleaner White Males 9.39 0.0092 12.51 0.0139 86/532
(16.2%) 41/176 (23.3%) SERPINB8 hCV3023236 WOSPCOPS Case/Control
Fatal MI/Sudden Death/Definite Non-fatal MI All Possible White
Males 7.05 0.0294 13.94 0.0075 56/277 (20.2%) 118/405 (29.1%)
SERPINB8 hCV3023236 WOSPCOPS Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 7.62 0.0221 15.35
0.004 56/246 (22.6%) 118/360 (32.8%) SERPINI2 hCV370782 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 7.6 0.0223 7.46 0.024 45/293 (15.4%) 73/337 (21.7%)
TAP1 hCV549926 CARE Prospective Fatal MI/Sudden Death/Definite
Non-fatal MI All Possible White Males 8.24 0.0163 7.77 0.0206
81/829 (9.8%) 42/329 (12.8%) TAP1 hCV549926 CARE Case/Control Fatal
MI/Sudden Death/Definite Non-fatal MI All Possible White Males 7.02
0.0299 11.77 0.0191 81/817 (9.9%) 42/319 (13.2%) TAP2 hCV16171128
CARE Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 5.82 0.0121 7.02 0.0298 106/1001 (10.6%)
21/183 (11.5%) TAP2 hCV16171128 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 6.24 0.0441 5.22
0.0735 106/627 (16.9%) 21/108 (19.4%) TAP2 hCV16171128 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 10.07 0.0065 12.08 0.0168 106/995 (10.7%)
21/176 (11.9%) TAP2 hCV16171128 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 7.13 0.0282 9.82
0.0435 106/622 (17.0%) 21/105 (20.0%) THBD hCV2531431 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 7.8 0.0202 7.47 0.0239 79/819 (9.6%) 42/325
(12.9%) THBD hCV2531431 CARE Case/Control Fatal MI/Sudden
Death/Definite Non-fatal MI All Possible White Males 7.13 0.0283
11.84 0.0185 79/809 (9.8%) 42/314 (13.4%) TLR6 hCV25615380 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 5.81 0.0169 4.74 0.0294 128/1187 (10.8%) 3/8
(37.5%) TLR6 hCV25615380 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI Cleaner White Males 6.24 0.0125 4.6
0.032 128/739 (17.3%) 3/5 (60.0%) TLR6 hCV25615380 CARE
Case/Control Fatal MI/Sudden Death/Definite Non-fatal MI All
Possible White Males 4.88 0.0272 4.1 0.0043 128/1165 (11.0%) 3/8
(37.5%) VTN hCV2536595 CARE Prospective Fatal MI/Sudden
Death/Definite Non-fatal MI All Possible White Males 8.83 0.0121
8.57 0.0138 25/351 (6.9%) 74/567 (13.1%) VTN hCV2536595 CARE
Prospective Fatal MI/Sudden Death/Definite Non-fatal MI Cleaner
White Males 7.52 0.0233 7.35 0.0254 25/213 (11.7%) 74/357 (20.7%)
VTN hCV2536595 CARE Case/Control Fatal MI/Sudden Death/Definite
Non-fatal MI All Possible White Males 9.52 0.0086 18.58 0.001
25/352 (7.1%) 74/559 (13.2%) VTN hCV2536595 CARE Case/Control Fatal
MI/Sudden Death/Definite Non-fatal MI Cleaner White Males 7.01
0.0301 13.75 0.0081 25/210 (11.9%) 74/352 (21.0%) ABCA1 hCV2741083
CARE Prospective Fatal & Non-fatal MI All Possible White Males
9.64 0.0081 9.26 0.0097 137/927 (14.8%) 19/253 (7.5%) ABCA1
hCV2741083 CARE Prospective Fatal & Non-fatal MI Cleaner White
Males 10.64 0.0049 10.15 0.0062 137/599 (22.9%) 19/167 (11.4%)
ABCA1 hCV2741083 CARE Case/Control Fatal & Non-fatal MI All
Possible White Males 10.01 0.0067 13.65 0.0085 137/915 (15.0%)
19/242 (7.9%) ABCA1 hCV2741083 CARE Case/Control Fatal &
Non-fatal MI Cleaner White Males 9.66 0.008 12.5 0.014 137/595
(23.0%) 19/160 (11.9%) ADAM12 hCV25926318 CARE Prospective Fatal
& Non-fatal MI All Possible White Males 6.32 0.0424 6.21 0.0449
64/578 (11.1%) 68/482 (14.1%) ADAM12 hCV25926933 CARE Prospective
Fatal & Non-fatal MI All Possible White Males 6.53 0.0383 6.41
0.0405 64/578 (11.1%) 70/487 (14.4%) ADAM12 hCV25926933 CARE
Case/Control Fatal & Non-fatal MI All Possible White Males 6.12
0.0469 12.23 0.0157 64/563 (11.4%) 70/481 (14.6%) APOB hCV3216558
CARE Prospective Fatal & Non-fatal MI All Possible White Males
6.09 0.0477 5.96 0.0504 111/732 (15.2%) 43/402 (10.7%) APOB
hCV3216558 CARE Case/Control Fatal & Non-fatal MI All Possible
White Males 7.23 0.0269 12.04 0.0171 111/721 (15.4%) 43/389 (11.1%)
APOB hCV3216558 CARE Case/Control Fatal & Non-fatal MI Cleaner
White Males 7.05 0.0295 11.71 0.0196 111/475 (23.4%) 43/252 (17.1%)
APOB hCV7615376 CARE Prospective Fatal & Non-fatal MI All
Possible White Males 6.04 0.0489 5.93 0.0515 111/732 (15.2%) 43/403
(10.7%) APOB hCV7615376 CARE Case/Control Fatal & Non-fatal MI
All Possible White Males 7.21 0.0272 11.99 0.0174 111/721 (15.4%)
43/390 (11.0%) APOB hCV7615376 CARE Case/Control Fatal &
Non-fatal MI Cleaner White Males 7.02 0.0299 11.63 0.0203 111/475
(23.4%) 43/253 (17.0%) ASAH1 hCV2442143 CARE Prospective Fatal
& Non-fatal MI All Possible White Males 8.56 0.0138 8.37 0.0152
54/320 (16.9%) 79/588 (13.4%) ASAH1 hCV2442143 CARE Prospective
Fatal & Non-fatal MI Cleaner White Males 9.54 0.0085 9.31
0.0095 54/207 (26.1%) 79/376 (21.0%) ASAH1 hCV2442143 CARE
Case/Control Fatal & Non-fatal MI All Possible White Males
10.55 0.0051 15.78 0.0033 54/314 (17.2%) 79/576 (13.7%) ASAH1
hCV2442143 CARE Case/Control Fatal & Non-fatal MI Cleaner White
Males 11.9 0.0026 15.13 0.0044 54/206 (26.2%) 79/368 (21.5%) ATF6
hCV25631989 CARE Prospective Fatal & Non-fatal MI All Possible
White Males 10.47 0.0053 9.02 0.011 137/982 (14.0%) 13/176 (7.4%)
ATF6 hCV25631989 CARE Prospective Fatal & Non-fatal MI Cleaner
White Males 10.92 0.0043 9.45 0.0089 137/630 (21.7%) 13/117 (11.1%)
ATF6 hCV25631989 CARE Case/Control Fatal & Non-fatal MI All
Possible White Males 9.23 0.0099 12.16 0.0162 137/963 (14.2%)
13/171 (7.6%) ATF6 hCV25631989 CARE Case/Control Fatal &
Non-fatal MI Cleaner White Males 10.79 0.0045 13.63 0.0089 137/622
(22.0%) 13/114 (11.4%) BAIAP3 hCV2503034 CARE Prospective Fatal
& Non-fatal MI All Possible White Males 6.1 0.0473 5.1 0.0782
121/956 (12.7%) 33/223 (14.8%) BAIAP3 hCV2503034 CARE Prospective
Fatal & Non-fatal MI Cleaner White Males 7.83 0.02 6.74 0.0344
121/632 (19.1%) 33/127 (26.0%) BCL2A1 hCV25992796 CARE Prospective
Fatal & Non-fatal MI All Possible White Males 6.14 0.0465 6.06
0.0482 102/665 (15.3%) 47/459 (10.2%) BCL2A1 hCV7509650 CARE
Prospective Fatal & Non-fatal MI All Possible White Males 7.14
0.0281 7.04 0.0296 102/662 (15.4%) 46/463 (9.9%) BCL2A1 hCV7509650
CARE Prospective Fatal & Non-fatal MI Cleaner White Males 6.17
0.0458 6.1 0.0475 102/434 (23.5%) 46/289 (15.9%) BCL2A1 hCV7509654
CARE Prospective Fatal & Non-fatal MI All Possible White Males
6.87 0.0322 6.79 0.0336 101/645 (15.7%) 48/468 (10.3%) BHMT
hCV11646506 CARE Case/Control Fatal & Non-fatal MI Cleaner
White Males 6.43 0.0402 8.37 0.0789 72/390 (18.5%) 74/294 (25.2%)
CASP1 hCV16276495 CARE Prospective Fatal & Non-fatal MI All
Possible White Males 11.61 0.0007 11.32 0.0008 112/961 (11.7%)
46/228 (20.2%) CASP1 hCV16276495 CARE Prospective Fatal &
Non-fatal MI Cleaner White Males 9.79 0.0018 9.59 0.002 112/612
(18.3%) 46/155 (29.7%) CASP1 hCV16276495 CARE Case/Control Fatal
& Non-fatal MI All Possible White Males 6.04 0.0046 7.91 0.0049
112/945 (11.9%) 46/221 (20.8%) CASP1 hCV16276495 CARE Case/Control
Fatal & Non-fatal MI Cleaner White Males 7.41 0.0065 7.29
0.0069 112/608 (18.5%) 46/151 (30.5%) CCKBR hCV9604851 CARE
Prospective Fatal & Non-fatal MI All Possible White Males 8.95
0.0114 7.15 0.028 143/1058 (13.5%) 12/130 (9.2%) CCKBR hCV9604851
CARE Prospective Fatal & Non-fatal MI Cleaner White Males 8.69
0.0129 5.9 0.0523 143/688 (20.8%) 12/79 (15.2%) CCKBR hCV9604851
CARE Case/Control Fatal & Non-fatal MI All Possible White Males
7.77 0.0206 10.61 0.0314 143/1037 (13.6%) 12/127 (9.4%) CCL22
hCV3268420 CARE Prospective Fatal & Non-fatal MI All Possible
White Males 8.64 0.0133 5.55 0.0615 145/1079 (13.4%) 11/112 (9.8%)
CCL22 hCV3268420 CARE Case/Control Fatal & Non-fatal MI All
Possible White Males 8.57 0.0138 8.8 0.0662 145/1057 (13.7%) 11/110
(10.0%) CCRL2 hCV25637309 CARE Prospective Fatal & Non-fatal MI
Cleaner White Males 6.63 0.0362 6.48 0.0396 55/263 (20.9%) 85/367
(23.2%) CD2 hCV2820518 CARE Prospective Fatal & Non-fatal MI
All Possible White Males 6.04 0.0487 5.82 0.0546 144/1018 (14.1%)
13/172 (7.6%) CD6 hCV2553030 WOSCOPS Case/Control Fatal &
Non-fatal MI All Possible White Males 7.21 0.0272 9.82 0.0435
145/479 (30.9%) 67/288 (23.3%) CD6 hCV2553030 WOSCOPS Case/Control
Fatal & Non-fatal MI Cleaner White Males 7.94 0.0189 10.57
0.0319 145/433 (34.2%) 67/263 (25.5%) CD66 hCV22271672 CARE
Case/Control Fatal & Non-fatal MI All Possible White Males 6.69
0.0353 9.04 0.0601 144/996 (14.6%) 11/151 (7.3%) CD66 hCV22271672
CARE Case/Control Fatal & Non-fatal MI Cleaner White Males 6.67
0.0356 9.27 0.0546 144/646 (22.3%) 11/95 (11.6%) CEL hCV2603661
CARE Prospective Fatal & Non-fatal MI Cleaner White Males 8.65
0.0132 8.47 0.0145 97/401 (24.2%) 52/307 (16.9%) CEL hCV2603661
CARE Case/Control Fatal & Non-fatal MI Cleaner White Males 6.84
0.0327 12.35 0.0149 97/392 (24.7%) 52/305 (17.0%) COL6A2 hCV2811372
CARE Prospective Fatal & Non-fatal MI All Possible White Males
7.59 0.0225 7.44 0.0242 47/276 (16.9%) 84/622 (13.5%) COL6A2
hCV2811372 CARE Prospective Fatal & Non-fatal MI Cleaner White
Males 7.01 0.0301 6.89 0.0319 47/184 (25.5%) 84/401 (20.9%) COL6A2
hCV2811372 CARE Case/Control Fatal & Non-fatal MI All Possible
White Males 6.77 0.0339 12.53 0.0138 47/271 (17.3%) 84/610 (13.8%)
CR1 hCV25598594 CARE Prospective Fatal & Non-fatal MI Cleaner
White Males 4.45 0.0348 4.25 0.0392 147/740 (19.9%) 11/31 (35.5%)
CTSB hCV8339791 CARE Prospective Fatal & Non-fatal MI All
Possible White Males 6.14 0.0465 5.61 0.0604 113/888 (12.7%) 38/281
(13.5%) CTSB hCV8339791 CARE Case/Control Fatal & Non-fatal MI
All Possible White Males 7.14 0.0282 10.08 0.0392 113/870 (13.0%)
38/275 (13.8%) CX3CR1 hCV7900503 CARE Prospective Fatal &
Non-fatal MI All Possible White Males 9.79 0.0075 9.61 0.0082
91/587 (15.5%) 50/507 (9.9%) CX3CR1 hCV7900503 CARE Prospective
Fatal & Non-fatal MI Cleaner White Males 10.67 0.0048 10.42
0.0055 91/393 (23.2%) 60/320 (15.6%) CX3CR1 hCV7900503 CARE
Case/Control Fatal & Non-fatal MI All Possible White Males
10.06 0.0065 11.89 0.0182 91/575 (15.8%) 50/497 (10.1%) ELN
hCV1253630 CARE Prospective Fatal & Non-fatal MI All Possible
White Males 7.22 0.0271 7.03 0.0298 64/406 (15.8%) 75/579 (13.0%)
ELN hCV1253830 CARE Prospective Fatal & Non-fatal MI Cleaner
White Males 6.32 0.0423 6.18 0.0456 64/268 (23.9%) 75/372 (20.2%)
ELN hCV1253630 CARE Case/Control Fatal & Non-fatal MI All
Possible White Males 9.48 0.0065 15.4 0.0039 64/394 (16.2%) 75/571
(13.1%) ELN hCV1253630 CARE Case/Control Fatal & Non-fatal MI
Cleaner White Males 7.07 0.0291 12.37 0.0148 64/263 (24.3%) 75/369
(20.3%) F7 hCV783184 WOSCOPS Case/Control Fatal & Non-fatal MI
Cleaner White Males 6.3 0.0427 9.26 0.055 197/598 (32.9%) 31/135
(23.0%) GAPD hCV8921288 CARE Prospective Fatal & Non-fatal MI
All Possible White Males 6.53 0.0381 6.45 0.0398 84/751 (11.2%)
57/360 (15.8%) GAPD hCV8921288 CARE Prospective Fatal &
Non-fatal MI Cleaner White Males 6.72 0.0348 6.64 0.0362 84/484
(17.4%) 57/232 (24.6%) GBA hCV2276802 CARE Prospective Fatal &
Non-fatal MI Cleaner White Males 5.62 0.0178 5.56 0.0183 51/195
(26.2%) 105/575 (18.3%) HLA-A hCV11689916 CARE Prospective Fatal
& Non-fatal MI All Possible White Males 6.56 0.0376
6.47 0.0394 40/404 (9.9%) 61/381 (15.0%) HLA-DPB1 hCV11916894 CARE
Prospective Fatal & Non-fatal MI All Possible White Males 8.22
0.0164 8.07 0.0177 110/932 (11.8%) 46/245 (18.8%) HLA-DPB1
hCV11916894 CARE Prospective Fatal & Non-fatal MI Cleaner White
Males 12.07 0.0024 11.77 0.0028 110/609 (18.1%) 46/149 (30.9%)
HLA-DPB1 hCV11916894 CARE Case/Control Fatal & Non-fatal MI
Cleaner White Males 10.06 0.0066 13.15 0.0105 110/600 (18.3%)
46/147 (31.3%) HLA-DPB1 hCV25651174 CARE Prospective Fatal &
Non-fatal MI Cleaner White Males 7.1 0.0288 6.47 0.0394 83/382
(21.7%) 69/313 (22.0%) HLA-DPB1 hCV25651174 CARE Case/Control Fatal
& Non-fatal MI Cleaner White Males 6.54 0.0379 8.38 0.0787
83/379 (21.9%) 69/308 (22.4%) HLA-DPB1 hCV8851065 CARE Prospective
Fatal & Non-fatal MI Cleaner White Males 6.52 0.0384 5.91 0.052
85/404 (21.0%) 68/306 (22.2%) HMMR hCV990335 CARE Prospective Fatal
& Non-fatal MI All Possible White Males 6.09 0.0476 5.55 0.0625
116/921 (12.6%) 36/254 (14.2%) HMOX1 hCV15869716 CARE Prospective
Fatal & Non-fatal MI Cleaner White Males 4.64 0.0312 4.47
0.0346 148/686 (21.6%) 10/86 (11.6%) HSPG2 hCV1603656 WOSCOPS
Case/Control Fatal & Non-fatal MI All Possible White Males
10.29 0.0058 9.7 0.0458 191/655 (28.7%) 33/133 (24.6%) HSPG2
hCV1603656 WOSCOPS Case/Control Fatal & Non-fatal MI Cleaner
White Males 9.02 0.011 8.99 0.0613 191/606 (31.5%) 33/119 (27.7%)
HSPG2 hCV16172339 CARE Case/Control Fatal & Non-fatal MI All
Possible White Males 6.07 0.0482 9.55 0.0488 132/1045 (12.6%)
24/117 (20.5%) ICAM1 hCV8726331 CARE Prospective Fatal &
Non-fatal MI All Possible White Males 7.01 0.03 6.18 0.0456 117/941
(12.4%) 34/236 (14.4%) IL1A hCV9545471 WOSCOPS Case/Control Fatal
& Non-fatal MI All Possible White Males 9.27 0.0097 15.82
0.0033 134/400 (33.5%) 88/351 (24.5%) IL1A hCV9545471 WOSCOPS
Case/Control Fatal & Non-fatal MI Cleaner White Males 8.88
0.0118 15.34 0.004 134/367 (36.5%) 86/315 (27.3%) IL1B hCV9546517
WOSCOPS Case/Control Fatal & Non-fatal MI All Possible White
Males 7.43 0.0243 12.67 0.13 159/496 (32.1%) 64/274 (23.4%) IL1B
hCV9546517 WOSCOPS Case/Control Fatal & Non-fatal MI Cleaner
White Males 6.85 0.0326 12.03 0.0172 159/456 (34.9%) 64/243 (26.3%)
IL4R hCV2769554 CARE Prospective Fatal & Non-fatal MI All
Possible White Males 7.2 0.0273 6.99 0.0303 53/371 (14.3%) 83/506
(14.7%) IL4R hCV2769554 CARE Case/Control Fatal & Non-fatal MI
All Possible White Males 8.7 0.0129 9.16 0.0573 53/360 (14.3%)
83/556 (14.9%) IL4R hCV2769554 CARE Case/Control Fatal &
Non-fatal MI Cleaner White Males 6.46 0.0395 7.06 0.1318 53/240
(22.1%) 83/363 (22.9%) ITGA9 hCV25644901 CARE Prospective Fatal
& Non-fatal MI Cleaner White Males 6.25 0.0124 6.08 0.0136
134/692 (19.4%) 24/76 (31.6%) ITPR3 hCV1923359 CARE Prospective
Fatal & Non-fatal MI All Possible White Males 9.56 0.0084 9.31
0.0096 29/338 (8.6%) 83/576 (14.4%) ITPR3 hCV1923359 CARE
Prospective Fatal & Non-fatal MI Cleaner White Males 7.18
0.0276 7.04 0.0295 29/204 (14.2%) 83/377 (22.0%) ITPR3 hCV1923359
CARE Case/Control Fatal & Non-fatal MI All Possible White Males
8.95 0.0114 18.96 0.0005 29/237 (8.9%) 83/568 (14.7%) ITPR3
hCV1923359 CARE Case/Control Fatal & Non-fatal MI Cleaner White
Males 7.28 0.0252 16.2 0.0028 29/201 (14.4%) 83/370 (22.4%)
KIAA0329 hCV25751017 CARE Prospective Fatal & Non-fatal MI All
Possible White Males 7.15 0.0075 6.82 0.009 137/1102 (12.4%) 15/62
(24.2%) KIAA0329 hCV25751017 CARE Prospective Fatal & Non-fatal
MI Cleaner White Males 6.66 0.0099 6.33 0.0119 137/711 (19.3%)
15/42 (35.7%) KLK14 hCV16044337 CARE Prospective Fatal &
Non-fatal MI All Possible White Males 13.25 0.0013 12.7 0.0017
61/560 (10.9%) 68/511 (13.3%) KLK14 hCV16044337 CARE Prospective
Fatal & Non-fatal MI Cleaner White Males 10.92 0.0043 10.52
0.0052 61/353 (17.3%) 68/334 (20.4%) KLK14 hCV16044337 CARE
Case/Control Fatal & Non-fatal MI All Possible White Males
15.27 0.0005 21.26 0.0003 61/548 (11.1%) 68/501 (13.6%) KLK14
hCV16044337 CARE Case/Control Fatal & Non-fatal MI Cleaner
White Males 13.84 0.001 19.63 0.0006 61/349 (17.5%) 68/328 (20.7%)
LPA hCV11225994 CARE Prospective Fatal & Non-fatal MI Cleaner
White Males 6.11 0.0471 5.99 0.05 128/575 (22.3%) 25/179 (14.0%)
LPA hCV11225994 CARE Case/Control Fatal & Non-fatal MI All
Possible White Males 7.16 0.0279 9.6 0.0478 128/867 (14.8%) 25/276
(91%) LPA hCV11225994 CARE Case/Control Fatal & Non-fatal MI
Cleaner White Males 7.07 0.0291 9.7 0.045 128/565 (22.7%) 25/179
(14.0%) LRP2 hCV16165996 WOSCOPS Case/Control Fatal & Non-fatal
MI All Possible White Males 7.52 0.0233 11.3 0.0234 124/469 (26.4%)
80/283 (28.3%) LRP2 hCV16165996 WOSCOPS Case/Control Fatal &
Non-fatal MI Cleaner White Males 9.39 0.0091 13.54 0.0089 124/429
(28.9%) 80/257 (31.1%) LRP2 hCV25646316 CARE Prospective Fatal
& Non-fatal MI All Possible White Males 8.21 0.0165 7.52 0.0233
128/1036 (12.4%) 29/148 (19.6%) LRP2 hCV25646316 CARE Case/Control
Fatal & Non-fatal MI All Possible White Males 13.74 0.001 15.94
0.0031 128/1015 (12.6%) 29/145 (20.0%) LRP2 hCV25646316 CARE
Case/Control Fatal & Non-fatal MI Cleaner White Males 7.76
0.0207 10.68 0.0304 128/649 (19.7%) 29/105 (27.6%) LTA hCV7514870
CARE Prospective Fatal & Non-fatal MI Cleaner White Males 6.1
0.0474 6.04 0.0458 57/345 (16.5%) 81/342 (23.7%) MARK3 hCV25926771
CARE Prospective Fatal & Non-fatal MI All Possible White Males
4.41 0.0358 4.37 0.0367 48/453 (10.6%) 106/733 (14.9%) MARK3
hCV25926771 CARE Prospective Fatal & Non-fatal MI Cleaner White
Males 4.17 0.0413 4.13 0.0421 48/255 (16.7%) 106/464 (22.8%) MC1R
hCV11951095 CARE Prospective Fatal & Non-fatal MI Cleaner White
Males 6.02 0.141 5.73 0.0167 147/678 (21.7%) 10/93 (10.8%) MMPB
hCV11482679 CARE Case/Control Fatal & Non-fatal MI Cleaner
White Males 6.47 0.0394 6.67 0.1543 130/623 (20.9%) 26/134 (19.4%)
NO62A hCV11889257 CARE Prospective Fatal & Non-fatal MI All
Possible White Males 6.97 0.0306 6.82 0.0331 93/785 (11.6%) 61/364
(16.8%) NOS2A hCV11889257 CARE Prospective Fatal & Non-fatal MI
Cleaner White Males 7.1 0.0288 6.91 0.0315 93/502 (18.5%) 61/238
(25.6%) NOS2A hCV11889257 CARE Case/Control Fatal & Non-fatal
MI All Possible White Males 7.06 0.0294 10.03 0.0399 93/773 (12.0%)
61/354 (17.2%) NOS2A hCV11889257 CARE Case/Control Fatal &
Non-fatal MI Cleaner White Males 6.77 0.0339 9.65 0.0468 93/497
(18.7%) 61/232 (26.3%) NPC1 hCV25475673 CARE Prospective Fatal
& Non-fatal MI All Possible White Males 6.88 0.032 6.78 0.0377
45/436 (10.3%) 81/575 (14.1%) NPC1 hCV25475673 CARE Prospective
Fatal & Non-fatal MI Cleaner White Males 12.1 0.0024 11.77
0.0026 45/290 (15.5%) 81/376 (21.5%) NPC1 hCV25475673 CARE
Case/Control Fatal & Non-fatal MI Cleaner White Males 9.57
0.0084 18.12 0.0029 45/287 (15.7%) 81/370 (21.9%) PDGFRA hCV2271841
CARE Prospective Fatal & Non-fatal MI All Possible White Males
11.91 0.0026 9.02 0.011 121/944 (12.8%) 32/231 (13.9%) PDGFRA
hCV2271841 CARE Prospective Fatal & Non-fatal MI Cleaner White
Males 11.14 0.0035 7.42 0.0244 121/601 (20.1%) 32.158 (20.3%) PGFRA
hCV2271841 CARE Case/Control Fatal & Non-fatal MI All Possible
White Males 10.59 0.005 12.08 0.0168 121/924 (13.1%) 32/227 (14.1%)
PDGFRA hCV2271841 CARE Case/Control Fatal & Non-fatal MI
Cleaner White Males 9.52 0.0061 9.92 0.0419 121/593 (20.4%) 32/155
(20.6%) PLA2G4C hCV25472687 CARE Prospective Fatal & Non-fatal
MI All Possible White Males 7.04 0.0296 6.34 0.042 120/956 (12.4%)
34/213 (16.0%) PLA2G4C hCV25472687 CARE Prospective Fatal &
Non-fatal MI Cleaner White Males 7.72 0.0211 6.57 0.0375 120/624
(19.2% 34/139 (24.5%) PLA2G4C hCV25472687 CARE Case/Control Fatal
& Non-fatal MI All Possible White Males 7.71 0.0212 11.65
0.0201 120/947 (12.7%) 34/208 (16.3%) PLA2G4C hCV25472687 CARE
Case/Control Fatal & Non-fatal MI Cleaner White Males 9.59
0.0083 12.64 0.0121 120/615 (19.5%) 34/137 (24.8%) PLA2G4C
hCV25472687 CARE Case/Control Fatal & Non-fatal MI Cleaner
White Males 9.59 0.0083 12.64 0.0121 120/615 (19.5%) 34/137 (24.8%)
PLAB hCV7494817 CARE Case/Control Fatal & Non-fatal MI All
Possible White Males 6.68 0.0354 9.11 0.0583 104/712 (14.6%) 41/397
(10.3%) PLAT hCV3212009 CARE Prospective Fatal & Non-fatal MI
Cleaner White Males 6.49 0.039 6.32 0.0424 131/577 (22.7%) 26/179
(14.5) PNN hCV2092598 CARE Prospective Fatal & Non-fatal MI
Cleaner White Males 9.41 0.0091 6.63 0.0363 132/677 (19.5%) 23/88
(26.1%) PNN hCV2092598 CARE Case/Control Fatal & Non-fatal MI
Cleaner White Males 7.58 0.0226 9.62 0.0473 132/657 (19.5%) 23/87
(26.4%) PPOX hCV25652722 CARE Prospective Fatal & Non-fatal MI
All Possible White Males 4.35 0.0369 4.08 0.0434 147/1139 (12.9%)
7/26 (26.9%) SELL hCV16172571 CARE Prospective Fatal &
Non-fatal MI All Possible White Males 7.88 0.0195 7.68 0.0215
105/883 (11.9%) 52/291 (17.9%) SELL hCV25474627 CARE Prospective
Fatal & Non-fatal MI All Possible White Males 7.77 0.0206 7.57
0.0227 104/882 (11.8%) 52/294 (17.7%) SERPINA10 hCV1260411 CARE
Case/Control Fatal & Non-fatal MI Cleaner White Males 7.34
0.0255 10.33 0.0352 110/557 (19.7%) 47/182 (25.8%) SERPINA10
hCV7586197 CARE Prospective Fatal & Non-fatal MI Cleaner White
Males 7.92 0.019 6.96 0.0309 106/557 (19.0%) 48/186 (25.8%)
SERPINA10 hCV7586197 CARE Case/Control Fatal & Non-fatal MI
Cleaner White Males 9.49 0.0087 12.56 0.0136 106/552 (19.2%) 48/181
(26.5%) SERPINB8 hCV3023236 CARE Case/Control Fatal & Non-fatal
MI All Possible White Males 6.02 0.0494 12.24 0.0156 65/397 (16.4%)
70/550 (12.7%) SERPINB8 hCV3023236 WOSCOPS Case/Control Fatal &
Non-fatal MI All Possible White Males 8.74 0.0126 17.73 0.0014
60/277 (21.7%) 128/405 (31.6%) SERPINB8 hCV3023236 WOSCOPS
Case/Control Fatal & Non-fatal MI Cleaner White Males 9.25
0.0098 18.62 0.001 60.250 (24.0%) 128/370 (34.6%) SERPINI2
hCV370782 CARE Prospective Fatal & Non-fatal MI All Possible
White Males 9.92 0.007 9.76 0.0076 51/470 (10.9%) 90/541 (16.6%)
SERPINI2 hCV370782 CARE Prospective Fatal & Non-fatal MI
Cleaner White Males 9.85 0.0072 9.71 0.0076 51/299 (17.1%) 90/354
(25.4%) SERPINI2 hCV370782 CARE Case/Control Fatal & Non-fatal
MI All Possible White Males 8.97 0.0113 9.89 0.0424 51/460 (11.1%)
90/531 (16.9%) SERPINI2 hCV370782 CARE Case/Control Fatal &
Non-fatal MI Cleaner White Males 7.53 0.0231 8.6 0.0719 51/294
(17.3%) 90/351 (25.6%) SPARCL1 hCV8827241 CARE Prospective Fatal
& Non-fatal MI Cleaner White Males 7.97 0.0186 7.77 0.0206
55/308 (17.9%) 72/364 (19.8%) SPARCL1 hCV8827241 CARE Case/Control
Fatal & Non-fatal MI All Possible White Males 6.39 0.0409 10.38
0.0346 55/472 (11.7%) 72/540 (13.3%) SPARCL1 hCV8827241 CARE
Case/Control Fatal & Non-fatal MI Cleaner White Males 9.31
0.0095 11.49 0.0216 55/301 (18.3%) 72/361 (19.9%) SPON2 hCV22275550
CARE Prospective Fatal & Non-fatal MI All Possible White Males
6.24 0.0442 6.15 0.0462 111/920 (12.1%) 45/251 (17.9) SPON2
hCV22275550 CARE Case/Control Fatal & Non-fatal MI All Possible
White Males 7.02 0.0299 9.5 0.0498 111/901 (12.3%) 45/246 (18.3%)
SREBF2 hCV16170982 CARE Case/Control Fatal & Non-fatal MI All
Possible White Males 7.05 0.0295 10.55 0.0322 128/996 (12.9%)
27/158 (17.1%) TAP2 hCV16171128 CARE Prospective Fatal &
Non-fatal MI All Possible White Males 6.3 0.043 5.27 0.0717
130/1001 (13.0%) 24/183 (13.1%) TAP2 hCV16171128 CARE Case/Control
Fatal & Non-fatal MI All Possible White Males 9.16 0.0103 10.44
0.0336 130/987 (13.2%) 24/176 (13.6%) TNF hCV7514879 CARE
Prospective Fatal & Non-fatal MI Cleaner White Males 6.72
0.0347 5.96 0.0507 103/541 (19.0%) 50/220 (22.7%) TNF hCV7514879
CARE Case/Control Fatal & Non-fatal MI Cleaner White Males 6.42
0.0404 10.35 0.0349 103/532 (19.4%) 50/218 (22.9%) TRPC6 hCV288790
CARE Prospective Fatal & Non-fatal MI All Possible White Males
7.86 0.0196 7.68 0.0215 104/888 (11.7%) 50/281 (17.8%) TRPC6
hCV288790 CARE Prospective Fatal & Non-fatal MI Cleaner White
Males 6.13 0.0465 6.06 0.0482 104/571 (18.2%) 50/189 (26.5%) TRPC6
hCV288790 CARE Case/Control Fatal & Non-fatal MI All Possible
White Males 8.04 0.018 11.02 0.0263 104/868 (12.0%) 50/278 (18.0%)
VTN hCV2536595 CARE Prospective Fatal & Non-fatal MI All
Possible White Males 11.17 0.0037 10.91 0.0043 32/361 (8.9%) 93/567
(16.4%) VTN hCV2536595 CARE Prospective Fatal & Non-fatal MI
Cleaner White Males 9.26 0.0097 9.11 0.0105 32/220 (14.5%) 93/376
(24.7%) VTN hCV2536595 CARE Case/Control Fatal & Non-fatal MI
All Possible White Males 10.93 0.0042 15.92 0.0031 32/351 (9.1%)
93/559 (16.6%) VTN hCV2536595 CARE Case/Control Fatal &
Non-fatal MI Cleaner White Males 8.34 0.0154 12.29 0.0153 32/216
(14.8%) 93/371 (25.1%) Placebo Pattents n/total (%) Odds Ratio (95%
CI) Public 2 Rare Alleles 2 Rare Alleles vs. 0 Rare Alleles 1 Rare
Allele vs. 0 Rare Alleles Significance Level ABCA1 1/14 (7.1%) 0.55
(0.03 to 2.82) 0.52 (0.30 to 0.86) P <= 0.05 ABCA1 1/5 (20.0%)
1.02 (0.05 to 6.99) 0.47 (0.26 to 0.79) P <= 0.05 ABCA1 1/3
(7.7%) 0.54 (0.07 to 4.27) 0.46 (0.26 to 0.61) P <= 0.05 ABCA1
7/15 (46.7%) 2.97 (1.05 to 8.44) 1.44 (1.00 to 2.06) P <= 0.05
ABCA1 1/5 (20.0%) 0.58 (0.10 to 8.16) 0.44 (0.24 to 0.79) P <=
0.05 ABCA1 7/15 (46.7%) 2.49 (0.87 to 7.10) 1.46 (1.01 to 2.12) P
<= 0.05 ABO 2/37 (5.4%) 0.19 (0.04 to 0.81) 0.81 (0.53 to 1.24)
P <= 0.05 ABO 2/59 (3.4%) 0.23 (0.05 to 0.97) 0.75 (0.50 to
1.11) P <= 0.05 ABO 2/39 (5.1%) 0.17 (0.04 to 0.74) 0.81 (0.53
to 1.24) P <= 0.05 ABO 2/38 (5.3%) 0.18 (0.04 to 0.80) 0.80
(0.52 to 1.22) P <= 0.05 ADAMTS1 12/67 (17.9%) 2.08 (1.04 to
4.15) 1.47 (0.99 to 2.19) P <= 0.05 ADAMTS1 12/42 (28.6%) 2.30
(1.08 to 4.57) 1.44 (0.95 to 2.17) P <= 0.05 ADAMTS1 12/42
(28.6%) 2.22 (1.05 to 4.46) 1.37 (0.91 to 2.04) P <= 0.05
ADAMTS1 12/67 (17.9%) 2.08 (1.04 to 4.17) 1.51 (1.02 to 2.24) P
<= 0.05 ADAMTS1 12/42 (28.6%) 2.30 (1.09 to 4.87) 1.50 (0.99 to
2.27) P <= 0.05 APOB 0/0 (0.0%) 13.40 (1.74 to 102.88) P <=
0.05 APOB 5/30 (16.7%) 0.76 (0.28 to 2.09) 0.57 (0.37 to 0.89) P
<= 0.05 APOB 5/29 (17.2%) 0.78 (0.28 to 2.15) 0.57 (0.36 to
0.89) P <= 0.05 ASAH1 21/181 (11.6%) 0.47 (0.25 to 0.81) 0.80
(0.52 to 1.24) P <= 0.05 ASAH1 21/279 (7.5%) 0.45 (0.26 to 0.80)
0.84 (0.56 to 1.28) P <= 0.05 ASAH1 21/180 (11.7%) 0.40 (0.22 to
0.73) 0.92 (0.59 to 1.43) P <= 0.05 ATF6 1/2 (50.0%) 4.36 (0.17
to 110.78) 0.46 (0.23 to 0.85) P <= 0.05 ATF6 1/2 (50.0%) 7.21
(0.44 to 119.14) 0.47 (0.24 to 0.93) P <= 0.05 BAIAP3 3/7
(42.9%) 6.57 (1.28 to 30.19) 1.31 (0.83 to 2.01) P <= 0.05
BAIAP3 3/5 (60.0%) 7.82 (1.28 to 59.95) 1.61 (0.99 to 2.55) P <=
0.05 BAIAP3 3/7 (42.9%) 6.53 (1.41 to 30.18) 1.22 (0.77 to 1.91) P
<= 0.05 BAIAP3 3/5 (60.0%) 7.03 (1.13 to 43.86) 1.55 (0.95 to
2.52) P <= 0.05 BAT2 3/37 (8.1%) 0.82 (0.20 to 2.36) 1.61 (1.09
to 2.36) P <= 0.05 BAT2 3/15 (16.7%) 1.11 (0.25 to 3.45) 1.75
(1.15 to 2.61) P <= 0.05 BAT2 3/36 (8.3%) 0.81 (0.24 to 2.73)
1.63 (1.10 to 2.42) P <= 0.05 BAT2 3/18 (16.7%) 0.92 (0.26 to
3.33) 1.75 (1.15 to 2.68) P <= 0.05 BDKRB2 7/103 (8.8%) 0.68
(0.28 to 1.44) 1.46 (1.00 to 2.12) P <= 0.05 BDKRB2 7/59 (11.9%)
0.75 (0.30 to 1.62) 1.54 (1.04 to 2.25) P <= 0.05 CAPN2 18/50
(36.0%) 1.38 (0.73 to 2.59) 0.67 (0.47 to 0.94) P <= 0.05 CAPN2
18/41 (43.9%) 1.68 (0.86 to 3.29) 0.67 (0.47 to 0.95) P <= 0.05
CASP1 0/0 (0.0%) 2.03 (1.35 to 3.03) P <= 0.005 CASP1 0/0 (0.0%)
2.02 (1.31 to 3.07) P <= 0.005 CASP1 0/0 (0.0%) 1.90 (1.25 to
2.90) P <= 0.005 CASP1 0/0 (0.0%) 1.92 (1.23 to 3.01) P <=
0.005 CCKBR 3/6 (50.0%) 7.74 (1.42 to 42.24) 0.44 (0.16 to 0.90) P
<= 0.05 CCKBR 3/4 (75.0%) 13.49 (1.71 to 274.34) 0.47 (0.19 to
0.98) P <= 0.05 CCKBR 3/6 (50.0%) 6.32 (1.22 to 32.70) 0.41
(0.19 to 0.91) P <= 0.05 CCKBR 3/4 (75.0%) 10.11 (1.03 to 99.58)
0.48 (0.21 to 1.09) P <= 0.05 CCL22 2/3 (68.7%) 15.83 (1.51 to
341.97) 0.61 (0.27 to 1.21) P <= 0.05 CCL22 2/3 (66.7%) 19.59
(1.72 to 222.53) 0.62 (0.29 to 1.32) P <= 0.05 CCRL2 5/13
(38.5%) 5.50 (1.64 to 16.79) 1.43 (0.85 to 2.33) P <= 0.005
CCRL2 5/10 (50.0%) 5.07 (1.39 to 18.51) 1.42 (0.82 to 2.37) P <=
0.05 CCRL2 5/13 (38.5%) 6.60 (2.07 to 21.11) 1.28 (0.78 to 2.16) P
<= 0.005 CCRL2 5/10 (50.0%) 4.81 (1.34 to 17.26) 1.15 (0.66 to
2.00) P <= 0.05 CCRL2 14/136 (10.3%) 0.48 (0.25 to 0.88) 0.99
(0.66 to 1.49) P <= 0.05 CCL2A1 2/5 (40.0%) 8.26 (1.11 to 61.51)
1.18 (0.67 to 2.09) P <= 0.05 CPT1A 2/4 (50.0%) 7.78 (0.93 to
65.35) 0.59 (0.31 to 1.06) P <= 0.05 CR1 0/0 (0.0%) 2.25 (1.11
to 4.57) P <= 0.05 CR1 0/0 (0.0%) 2.56 (1.18 to 5.57) P <=
0.05 CX3CR1 12/92 (13.0%) 0.98 (0.49 to 1.82) 0.57 (0.38 to 0.85) P
<= 0.05 CX3CR1 12/48 (25.0%) 1.29 (0.62 to 2.53) 0.59 (0.39 to
0.88) P <= 0.05 CX3CR1 12/90 (13.3%) 1.11 (0.57 to 2.16) 0.59
(0.39 to
0.89) P <= 0.05 CX3CR1 12/48 (25.0%) 1.53 (0.75 to 3.13) 0.65
(0.42 to 0.99) P <= 0.05 DBH 3/6 (50.0%) 6.23 (1.19 to 32.65)
0.53 (0.26 to 1.09) P <= 0.05 F7 6/14 (42.9%) 1.99 (0.67 to
5.88) 0.62 (0.40 to 0.97) P <= 0.05 F7 6/13 (46.2%) 1.54 (0.60
to 5.61) 0.59 (0.37 to 0.94) P <= 0.05 GBA 0/0 (0.0%) 0.58 (0.39
to 0.87) P <= 0.05 HLA-A 49/351 (14.0%) 1.82 (1.15 to 2.93) 1.39
(0.86 to 2.26) P <= 0.05 HLA-A 49/345 (14.2%) 1.76 (1.10 to
2.62) 1.20 (0.73 to 1.97) P <= 0.05 HLA-DPB1 1/16 (6.3%) 0.61
(0.03 to 3.06) 1.68 (1.10 to 2.50) P <= 0.05 HLA-DPB1 1/10
(10.0%) 0.60 (0.03 to 3.26) 2.00 (1.29 to 3.07) P <= 0.05
HLA-DPB1 1/10 (10.0%) 0.74 (0.09 to 6.02) 1.97 (1.25 to 3.10) P
<= 0.05 HLA-DPB1 4/69 (5.8%) 0.26 (0.08 to 0.65) 0.97 (0.65 to
1.42) P <= 0.05 HLA-DPB1 4/67 (6.0%) 0.26 (0.09 to 0.76) 0.97
(0.65 to 1.45) P <= 0.05 HLA-DPB1 3/60 (5.0%) 0.23 (0.06 to
0.65) 1.04 (0.71 to 1.63) P <= 0.05 HSPG2 5/7 (71.4%) 6.06 (1.16
to 31.62) 0.88 (0.56 to 1.37) P <= 0.05 HSPG2 5/6 (83.3%) 10.41
(1.21 to 89.65) 0.89 (0.56 to 1.39) P <= 0.05 IL1A 11/61 (18.0%)
0.52 (0.26 to 1.04) 0.67 (0.48 to 0.93) P <= 0.05 IL1A 11/56
(19.6%) 0.49 (0.24 to 0.96) 0.67 (0.47 to 0.94) P <= 0.05 IL1B
10/50 (20.0%) 1.64 (0.76 to 3.53) 1.64 (1.09 to 2.47) P <= 0.05
IL1RL1 32/187 (17.1%) 1.69 (1.04 to 2.73) 0.81 (0.53 to 1.23) P
<= 0.05 IL1RL1 32/184 (17.4%) 1.86 (1.13 to 3.08) 0.84 (0.55 to
1.29) P <= 0.05 IL1RL1 32/127 (25.2%) 1.85 (1.09 to 3.14) 0.94
(0.60 to 1.46) P <= 0.05 IL4R 16/257 (6.2%) 0.52 (0.28 to 0.93)
1.16 (0.78 to 1.76) P <= 0.05 IL4R 16/151 (10.6%) 0.64 (0.28 to
0.98) 1.16 (0.77 to 1.79) P <= 0.05 IL4R 16/252 (6.3%) 0.46
(0.25 to 0.84) 1.14 (0.75 to 1.73) P <= 0.05 IL4R 16/149 (10.7%)
0.49 (0.26 to 0.92) 1.16 (0.75 to 1.00) P <= 0.05 ITGA9 0/0
(0.0%) 2.41 (1.40 to 4.03) P <= 0.005 KIAA0329 0/0 (0.0%) 2.32
(1.18 to 4.29) P <= 0.05 KIAA0329 0/0 (0.0%) 2.45 (1.19 to 4.80)
P <= 0.05 KLK14 23/115 (20.0%) 2.55 (1.46 to 4.34) 1.28 (0.86 to
1.92) P <= 0.005 KLK14 23/76 (30.3%) 2.53 (1.41 to 4.47) 1.25
(0.83 to 1.90) P <= 0.05 KLK14 23/113 (20.4%) 2.79 (1.57 to
4.94) 1.29 (0.85 to 1.96) P <= 0.005 KLK14 23/75 (30.7%) 2.86
(1.56 to 5.26) 1.30 (0.85 to 2.01) P <= 0.005 KLKB1 43/288
(14.9%) 1.05 (1.11 to 3.11) 1.21 (0.76 to 1.97) P <= 0.05 KLKB1
43/283 (15.2%) 1.94 (1.15 to 3.26) 1.19 (0.73 to 1.93) P <= 0.05
KLKB1 43/188 (22.9%) 1.97 (1.13 to 3.40) 1.32 (0.79 to 2.21) P
<= 0.05 LAPTM5 7/64 (10.9%) 1.25 (0.60 to 2.69) 1.68 (1.15 to
2.45) P <= 0.05 LAPTM5 7/64 (10.9%) 1.29 (0.55 to 3.01) 1.71
(1.16 to 2.53) P <= 0.05 LRP2 2/47 (4.3%) 0.19 (0.03 to 0.63)
0.92 (0.61 to 1.36) P <= 0.05 LRP2 25/63 (39.7%) 1.95 (1.12 to
3.38) 0.87 (0.61 to 1.24) P <= 0.05 LRP2 2/47 (4.3%) 0.19 (0.04
to 0.61) 0.95 (0.63 to 1.44) P <= 0.05 LRP2 25/54 (46.3%) 2.35
(1.30 to 4.22) 0.95 (0.66 to 1.36) P <= 0.05 LTA 17/124 (13.7%)
1.72 (0.93 to 3.07) 1.60 (1.08 to 2.39) P <= 0.05 LTA 1.7/78
(21.8%) 1.79 (0.94 to 3.29) 1.70 (1.13 to 2.57) P <= 0.05 LTA
17/122 (13.9%) 1.87 (1.02 to 3.45) 1.62 (1.08 to 2.42) P <= 0.05
LTA 17/76 (22.4%) 1.90 (0.99 to 3.64) 1.58 (1.04 to 2.42) P <=
0.05 MARK3 0/0 (0.0%) 1.49 (1.01 to 2.24) P <= 0.05 MARK3 0/0
(0.0%) 1.5 (1.01 to 2.30) P <= 0.05 MC1R 0/0 (0.0%) 0.36 (0.15
to 0.75) P <= 0.05 MMP7 1/58 (1.7%) 0.12 (0.01 to 0.56) 0.71
(0.47 to 1.06) P <= 0.05 MMP7 1/33 (3.0%) 0.13 (0.01 to 0.60)
0.75 (0.49 to 1.12) P <= 0.05 MMP7 1/57 (1.8%) 0.13 (0.02 to
0.98) 0.71 (0.47 to 1.08) P <= 0.05 MMP7 1/33 (3.0%) 0.12 (0.02
to 0.88) 0.72 (0.47 to 1.11) P <= 0.05 MMP8 34/179 (19.0%) 1.70
(0.97 to 3.00) 1.86 (1.15 to 3.08) P <= 0.05 MTR 0/0 (0.0%) 2.05
(1.02 to 3.66) P <= 0.05 MTR 0/0 (0.0%) 2.05 (0.98 to 4.04) P
<= 0.05 NDUFS2 0/0 (0.0%) 4.13 (0.86 to 15.66) P <= 0.05
NDUFS2 0/0 (0.0%) 5.40 (1.30 to 22.49) P <= 0.05 NDUFS2 0/0
(0.0%) 5.41 (1.06 to 27.68) P <= 0.05 NOS2A 2/45 (4.4%) 0.43
(0.07 to 1.43) 1.50 (1.02 to 2.15) P <= 0.05 NOS2A 2/29 (6.9%)
0.39 (0.06 to 1.35) 1.53 (1.03 to 2.27) P <= 0.05 NOS2A 2/43
(4.7%) 0.41 (0.10 to 1.75) 1.55 (1.05 to 2.26) P <= 0.05 NOS2A
2/29 (6.9%) 0.35 (0.08 to 1.53) 1.51 (1.00 to 2.29) P <= 0.05
NPC1 28/173 (16.2%) 2.08 (1.22 to 3.52) 1.37 (0.90 to 2.12) P <=
0.05 NPC1 28/95 (29.5%) 2.77 (1.67 to 4.84) 1.46 (0.95 to 2.28) P
<= 0.005 NPC1 28/167 (16.5%) 2.02 (1.17 to 3.45) 1.29 (0.84 to
1.96) P <= 0.05 NPC1 28/93 (30.1%) 2.60 (1.45 to 4.69) 1.32
(0.84 to 2.05) P <= 0.005 PDGFRA 5/10 (50.0%) 5.44 (2.31 to
30.83) 1.07 (0.67 to 1.67) P <= 0.005 PDGFRA 5/7 (71.4%) 11.99
(2.55 to 84.58) 0.99 (0.61 to 1.57) P <= 0.005 PDGFRA 5/10
(50.0%) 7.67 (2.13 to 27.62) 1.17 (0.73 to 1.86) P <= 0.005
PDGFRA 5/7 (71.4%) 11.06 (2.05 to 59.73) 1.13 (0.69 to 1.84) P
<= 0.05 PEMT 44/174 (25.3%) 0.76 (0.49 to 1.19) 0.61 (0.42 to
0.69) P <= 0.05 PLAB 4/46 (6.7%) 0.48 (0.17 to 1.42) 1.51 (1.02
to 2.25) P <= 0.05 PNN 3/8 (37.5%) 5.09 (1.03 to 21.02) 1.24
(0.71 to 2.07) P <= 0.05 PNN 3/4 (75.0%) 14.84 (1.58 to 301.89)
1.37 (0.76 to 2.36) P <= 0.05 PNN 3/8 (37.5%) 5.16 (1.17 to
22.86) 1.30 (0.75 to 2.24) P <= 0.05 PNN 3/4 (75.0%) 11.89 (1.16
to 121.79) 1.32 (0.74 to 2.35) P <= 0.05 PRKCQ 3/85 (3.5%) 0.25
(0.06 to 0.70) 0.78 (0.53 to 1.14) P <= 0.05 PRKCQ 3/83 (3.6%)
0.24 (0.07 to 0.80) 0.79 (0.53 to 1.17) P <= 0.05 PRKCQ 12/53
(22.6%) 0.74 (0.37 to 1.46) 0.64 (0.45 to 0.90) P <= 0.05 PRKCQ
12/47 (25.5%) 0.74 (0.37 to 1.49) 0.63 (0.44 to 0.69) P <= 0.05
SERPINA10 1/21 (4.8%) 0.28 (0.04 to 2.16) 1.69 (1.10 to 2.60) P
<= 0.05 SERPINA10 1/24 (4.2%) 0.23 (0.01 to 1.10) 1.56 (1.02 to
2.35) P <= 0.05 SERPINA10 1/23 (4.3%) 0.29 (0.04 to 2.20) 1.60
(1.16 to 2.78) P <= 0.05 SERPINB8 36/131 (27.5%) 1.50 (0.92 to
2.43) 1.63 (1.13 to 2.35) P <= 0.05 SERPINB8 36/113 (31.9%) 1.62
(0.98 to 2.66) 1.66 (1.14 to 2.42) P <= 0.05 SERPINI2 13/112
(11.6%) 0.72 (0.36 to 1.36) 1.52 (1.02 to 2.31) P <= 0.05 TAP1
6/33 (24.2%) 2.96 (1.21 to 6.50) 1.35 (0.90 to 2.00) P <= 0.05
TAP1 8/33 (24.2%) 2.73 (1.17 to 6.39) 1.36 (0.91 to 2.05) P <=
0.05 TAP2 4/10 (40.0%) 5.63 (1.42 to 20.02) 1.09 (0.65 to 1.77) P
<= 0.05 TAP2 4/8 (50.0%) 4.92 (1.15 to 21.08) 1.19 (0.69 to
1.96) P <= 0.05 TAP2 4/9 (44.4%) 7.90 (1.80 to 34.62) 1.25 (0.75
to 2.08) P <= 0.05 TAP2 4/8 (50.0%) 6.41 (1.32 to 31.22) 1.29
(0.76 to 2.21) P <= 0.05 THBD 9/41 (22.0%) 2.63 (1.15 to 5.51)
1.39 (0.93 to 2.06) P <= 0.05 THBD 9/40 (22.5%) 2.77 (1.21 to
6.36) 1.34 (0.89 to 2.02) P <= 0.05 TLR6 0/0 (0.0%) 4.97 (1.01
to 20.47) P <= 0.05 TLR6 0/0 (0.0%) 7.16 (1.18 to 54.77) P <=
0.05 TLR6 0/0 (0.0%) 4.51 (1.05 to 19.38) P <= 0.05 VTN 32/268
(11.9%) 1.62 (1.06 to 3.18) 2.02 (1.27 to 3.30) P <= 0.05 VTN
32/175 (18.3%) 1.68 (0.96 to (2.99) 1.97 (1.22 to 3.26) P <=
0.05 VTN 32/263 (12.2%) 1.83 (1.03 to 3.25%) 2.16 (1.31 to 3.64) P
<= 0.05 VTN 32/174 (18.4%) 1.61 (0.89 to 2.91) 1.99 (1.19 to
3.33) P <= 0.05 ABCA1 1/14 (7.1%) 0.44 (0.02 to 2.25) 0.47 (0.28
to 0.76) P <= 0.05 ABCA1 1/5 (20.0%) 0.84 (0.04 to 5.76) 0.43
(0.25 to 0.71) P <= 0.005 ABCA1 1/13 (7.7%) 0.43 (0.05 to 3.35)
0.45 (0.26 to 0.75) P <= 0.05 ABCA1 1/5 (20.0%) 0.77 (0.08 to
7.06) 0.43 (0.24 to 0.74) P <= 0.05 ADAM12 20/102 (19.6%) 1.96
(1.10 to 3.36) 1.32 (0.92 to 1.90) P <= 0.05 ADAM12 20/102
(19.6%) 1.96 (1.10 to 3.36) 1.35 (0.94 to 1.94) P <= 0.05 ADAM12
20/100 (20.0%) 1.94 (1.09 to 3.46) 1.38 (0.95 to 1.99) P <= 0.05
APOB 4/53 (7.5%) 0.46 (0.14 to 1.15) 0.67 (0.46 to 0.97) P <=
0.05 APOB 4/53 (7.5%) 0.43 (0.15 to 1.22) 0.64 (0.44 to 0.94) P
<= 0.05 APOB 4/29 (13.8%) 0.48 (0.16 to 1.44) 0.60 (0.40 to
0.91) P <= 0.05 APOB 4/52 (7.7%) 0.47 (0.14 to 1.17) 0.67 (0.46
to 0.97) P <= 0.05 APOB 4/52 (7.7%) 0.43 (0.15 to 1.23) 0.64
(0.43 to 0.94) P <= 0.05 APOB 4/28 (14.3%) 0.49 (0.16 to 1.48)
0.60 (0.40 to 0.90) P <= 0.05 ASAH1 25/284 (8.8%) 0.48 (0.28 to
0.78) 0.76 (0.53 to 1.12) P <= 0.05 ASAH1 25/185 (13.5%) 0.44
(0.26 to 0.74) 0.75 (0.51 to 1.12) P <= 0.05 ASAH1 25/278 (9.0%)
0.43 (0.25 to 0.72) 0.80 (0.55 to 1.17) P <= 0.05 ASAH1 25/183
(13.7%) 0.40 (0.23 to 0.69) 0.87 (0.58 to 1.31) P <= 0.005 ATF6
2/4 (50.0%) 6.17 (0.74 to 51.73) 0.49 (0.26 to 0.66) P <= 0.05
ATF6 2/3 (66.7%) 7.20 (0.68 to 155.43) 0.45 (0.23 to 0.80) P <=
0.05 ATF6 2/4 (50.0%) 5.84 (0.81 to 42.04) 0.61 (0.28 to 0.93) P
<= 0.05 ATF6 2/3 (66.7%) 8.24 (0.72 to 94.43) 0.45 (0.24 to
0.84) P <= 0.05 BAIAP3 3/7 (42.9%) 5.18 (1.01 to 23.74) 1.20
(0.78 to 1.80) P <= 0.05 BAIAP3 3/5 (60.0%) 6.33 (1.04 to 48.48)
1.48 (0.94 to 2.29) P <= 0.05 BCL2A1 9/67 (13.4%) 0.86 (0.39 to
1.70) 0.63 (0.43 to 0.90) P <= 0.05 BCL2A1 9/66 (13.6%) 0.87
(0.39 to 1.72) 0.61 (0.42 to 0.87) P <= 0.05 BCL2A1 9/46 (19.6%)
0.79 (0.35 to 1.63) 0.62 (0.42 to 0.90) P <= 0.05 BCL2A1 9/71
(12.7%) 0.78 (0.35 to 1.55) 0.62 (0.42 to 0.88) P <= 0.05 BHMT
12/75 (16.0%) 0.66 (0.44 to 1.71) 1.66 (1.06 to 2.28) P <= 0.05
CASP1 0/0 (0.0%) 1.92 (1.30 to 2.78) P <= 0.05 CASP1 0/0 (0.0%)
1.88 (1.25 to 2.80) P <= 0.05 CASP1 0/0 (0.0%) 1.76 (1.19 to
2.61) P <= 0.05 CASP1 0/0 (0.0%) 1.79 (1.17 to 2.72) P <=
0.05 CCKBR 3/6 (50.0%) 5.40 (1.17 to 34.85) 0.65 (0.33 to 1.16) P
<= 0.05 CCKBR 3/4 (75.0%) 11.43 (1.45 to 231.99) 0.68 (0.34 to
1.25) P <= 0.05 CCKBR 3/6 (50.0%) 6.25 (1.03 to 26.81) 0.60
(0.32 to 1.12) P <= 0.05 CCL22 2/3 (66.7%) 12.68 (1.23 to
278.04) 0.70 (0.35 to 1.28) P <= 0.05 CCL22 2/3 (66.7%) 13.69
(1.21 to 152.35) 0.74 (0.38 to 1.42) P <= 0.05 CCRL2 18/140
(12.9%) 0.66 (0.31 to 0.98) 1.14 (0.78 to 1.68) P <= 0.05 CD2
1/4 (25.0%) 2.02 (0.10 to 15.92) 0.05 (0.26 to 0.87) P <= 0.05
CD6 17/43 (39.5%) 1.43 (0.74 to 2.75) 0.68 (0.48 to 0.95) P <=
0.05 CD6 17/41 (41.5%) 1.35 (0.70 to 2.62) 0.65 (0.46 to 0.91) P
<= 0.05 CD66 1/6 (12.5%) 0.90 (0.11 to 7.42) 0.42 (0.22 to 0.83)
P <= 0.05 CD66 1/6 (16.7%) 0.76 (0.09 to 5.62) 0.41 (0.21 to
0.82) P <= 0.05 CEL 7/60 (11.7%) 0.41 (0.17 to 0.88) 0.64 (0.44
to 0.93) P <= 0.05 CEL 7/60 (11.7%) 0.42 (0.18 to 0.98) 0.67
(0.45 to 0.99) P <= 0.05 COL6A2 27/295 (9.2%) 0.50 (0.30 to
0.81) 0.77 (0.52 to 1.14) P <= 0.05 COL6A2 27/156 (14.5%) 0.49
(0.29 to 0.83) 0.77 (0.51 to 1.17) P <= 0.05 COL6A2 27/290
(9.3%) 0.51 (0.30 to 0.85) 0.77 (0.51 to 1.14) P <= 0.05 CR1 0/0
(0.0%) 2.22 (1.01 to 4.65) P <= 0.05 CTSB 7/23 (30.4%) 3.00
(1.13 to 7.20) 1.07 (0.72 to 1.58) P <= 0.05 CTSB 7/23 (30.4%)
3.35 (1.31 to 8.58) 1.13 (0.75 to 1.69) P <= 0.05 CX3CR1 17/92
(18.5%) 1.24 (0.63 to 2.14) 0.60 (0.41 to 0.86) P <= 0.05 CX3CR1
17/53 (32.1%) 1.57 (0.82 to 2.88) 0.61 (0.42 to 0.90) P <= 0.05
CX3CR1 17/90 (18.9%) 1.42 (0.79 to 2.55) 0.61 (0.42 to 0.89) P
<= 0.05 ELN 16/201 (8.0%) 0.46 (0.25 to 0.80) 0.80 (0.55 to
1.14) P <= 0.05 ELN 16/124 (12.9%) 0.47 (0.25 to 0.84) 0.80
(0.55 to 1.18) P <= 0.05 ELN 16/197 (8.1%) 0.41 (0.23 to 0.73)
0.77 (0.53 to 1.12) P <= 0.05 ELN 16/121 (13.2%) 0.44 (0.24 to
0.82) 0.78 (0.53 to 1.16) P <= 0.05 F7 5/12 (41.7%) 1.41 (0.43
to 4.58) 0.59 (0.38 to 0.91) P <= 0.05 GAPD 10/52 (19.2%) 1.89
(0.87 to 3.77) 1.49 (1.04 to 2.14) P <= 0.05 GAPD 10/35 (28.6%)
1.90 (0.84 to 4.01) 1.55 (1.06 to 2.26) P <= 0.05 GBA 0/0 (0.0%)
0.63 (0.43 to 0.93) P <= 0.05 HLA-A 48/351 (13.7%) 1.44 (0.92 to
2.28) 1.73 (1.14 to 2.67) P <= 0.05 HLA-DPB1 2/16 (12.5%) 1.07
(0.17 to 3.89) 1.73 (1.18 to 2.51) P <= 0.05 HLA-DPB1 2/11
(18.2%) 1.01 (0.15 to 3.96) 2.03 (1.35 to 3.02) P <= 0.05
HLA-DPB1 2/11 (18.2%) 1.20 (0.25 to 5.75) 1.97 (1.29 to 3.00) P
<= 0.05 HLA-DPB1 6/71 (8.5%) 0.33 (0.13 to 0.74) 1.02 (0.71 to
1.46) P <= 0.05 HLA-DPB1 6/58 (8.8%) 0.34 (0.14 to 0.83) 1.03
(0.71 to 1.50) P <= 0.05 HLA-DPB1 5/62 (8.1%) 0.33 (0.11 to
0.77) 1.07 (0.75 to 1.54) P <= 0.05 HMMR 6/19 (31.6%) 3.20 (1.11
to 8.28) 1.15 (0.76 to 1.70) P <= 0.05 HMOX1 0/0 (0.0%) 0.48
(0.23 to 0.91) P <= 0.05 HSPG2 6/7 (85.7%) 13.24 (1.58 to
111.11) 0.85 (0.55 to 1.31) P <= 0.05 HSPG2 6/7 (85.7%) 11.85
(1.41 to 99.39) 0.86 (0.55 to 1.33) P <= 0.05 HSPG2 1/4 (25.0%)
2.93 (0.26 to 32.61) 1.79 (1.09 to 2.95) P <= 0.05 ICAM1 5/14
(35.7%) 3.91 (1.19 to 11.53) 1.19 (0.78 to 1.77) P <= 0.05 IL1A
11/61 (18.0%) 0.46 (0.23 to 0.92) 0.66 (0.48 to 0.92) P <= 0.05
IL1A 11/58 (19.6%) 0.45 (0.22 to 0.90) 0.67 (0.49 to 0.94) P <=
0.05 IL1B 9/47 (19.1%) 0.52 (0.25 to 1.11) 0.67 (0.48 to 0.94) P
<= 0.05 IL1B 9/44 (20.5%) 0.49 (0.23 to 1.05) 0.69 (0.49 to
0.98) P <= 0.05 IL4R 21/257 (8.2%) 0.53 (0.31 to 0.90) 1.04
(0.72 to 1.51) P <= 0.05 IL4R 21/252 (8.3%) 0.50 (0.29 to 0.87)
1.05 (0.72 to 1.54) P <= 0.05 IL4R 21/154 (13.6%) 0.56 (0.32 to
0.99) 1.11 (0.74 to 1.66) P <= 0.05 ITGA9 0/0 (0.0%) 1.82 (1.13
to 3.20) P <= 0.05 ITPR3 46/280 (16.4%) 2.09 (1.28 to 3.47) 1.79
(1.16 to 2.84) P <= 0.05 ITPR3 46/109 (24.3%) 1.94 (1.17 to
3.28) 1.70 (1.08 to 2.74) P <= 0.05 ITPR3 46/277 (16.6%) 2.11
(1.27 to 3.49) 1.71 (1.09 to 2.59) P <= 0.05 ITPR3 46/188
(24.5%) 2.02 (1.19 to 3.44) 1.67 (1.04 to 2.69) P <= 0.05
KIAA0329 0/0 (0.0%) 2.25 (1.19 to 4.04) P <= 0.05 KIAA0329 0/0
(0.0%) 2.33 (1.18 to 4.44) P <= 0.05 KLK14 27/155 (23.5%) 2.51
(1.50 to 4.13) 1.26 (0.87 to 1.82) P <= 0.05 KLK14 27/80 (33.8%)
2.44 (1.41 to 4.16) 1.22 (0.83 to 1.80) P <= 0.05 KLK14 27/113
(23.9%) 2.62 (1.65 to 4.81) 1.30 (0.89 to 1.91) P <= 0.05 KLK14
27/79 (34.2%) 2.90 (1.63 to 5.14) 1.31 (0.88 to 1.96) P <= 0.05
LPA 3/11 (27.3%) 1.31 (0.28 to 4.60) 0.57 (0.35 to 0.89) P <=
0.05 LPA 3/19 (15.8%) 1.01 (0.28 to 3.62) 0.54 (0.34 to 0.85) P
<= 0.05 LPA 3/11 (27.3%) 0.91 (0.23 to 3.63) 0.52 (0.32 to 0.85)
P <= 0.05 LRP2 27/63 (42.9%) 2.12 (1.23 to 3.65) 1.12 (0.80 to
1.57) P <= 0.05 LRP2 27/56 (48.2%) 2.40 (1.35 to 4.42) 1.15
(0.82 to 1.62) P <= 0.05 LRP2 1/2 (50.0%) 7.09 (0.28 to 179.96)
1.73 (1.09 to 2.67) P <= 0.05 LRP2 1/2 (50.0%) 18.26 (0.99 to
336.63) 1.90 (1.19 to 3.01) P <= 0.05 LRP2 1/2 (50.0%) 11.23
(0.64 to 198.02) 1.63 (1.00 to 2.65) P <= 0.05 LTA 19/80 (23.8%)
1.58 (0.85 to 2.81) 1.57 (1.08 to 2.30) P <= 0.05 MARK3 0/0
(0.0%) 1.47 (1.03 to 2.13) P <= 0.05 MARK3 0/0 (0.0%) 1.48 (1.02
to 2.17) P <= 0.05 MC1R 0/0 (0.0%) 0.44 (0.21 to 0.82) P <=
0.05 MMPB 2/3 (68.7%) 11.89 (1.05 to 134.77) 0.93 (0.58 to 1.50) P
<= 0.05 NO62A 3/45 (6.7%) 0.53 (0.13 to 1.50) 1.50 (1.05 to
2.12) P <= 0.05 NOS2A 3/30 (10.0%) 0.49 (0.12 to 1.42) 1.52
(1.05 to 2.19) P <= 0.05 NOS2A 3/43 (7.0%) 0.51 (0.15 to 1.71)
1.51 (1.06 to 2.16) P <= 0.05 NOS2A 3/30 (10.0%) 0.45 (0.13 to
1.52) 1.50 1.02 to 2.20) P <= 0.05 NPC1 31/173 (17.9%) 1.90
(1.15 to 3.10) 1.42 (0.97 to 2.11) P <= 0.05 NPC1 31/98 (31.6%)
2.52 (1.47 to 4.28) 1.49 (1.00 to 2.25) P <= 0.05 NPC1 31/96
(32.3%) 2.37 (1.36 to 4.11) 1.36 (0.90 to 2.05) P <= 0.05 PDGFRA
5/10 (50.0%) 6.80 (1.87 to 24.78) 1.09 (0.71 to 1.64) P <= 0.05
PDGFRA 5/7 (71.4%) 9.92 (2.11 to 69.80) 1.01 (0.64 to 1.54) P <=
0.05 PGFRA 5/10 (50.0%) 6.37 (1.79 to 22.70) 1.14 (0.74 to 1.74) P
<= 0.05 PDGFRA 5/7 (71.4%) 9.10 (1.72 to 48.10) 1.08 (0.69 to
1.59) P <= 0.05 PLA2G4C 4/11 (36.4%) 4.03 (1.04 to 13.54) 1.34
(0.87 to 2.00) P <= 0.05 PLA2G4C 4/7 (57.1%) 5.60 (1.22 to
28.73) 1.38 (0.87 to 2.08) P <= 0.05 PLA2G4C 4/11 (36.4%) 4.02
(1.14 to 14.17) 1.44 (0.94 to 2.21) P <= 0.05 PLA2G4C 4/7
(57.1%) 6.83 (1.42 to 32.80) 1.47 (0.93 to 2.32) p <= 0.05
PLA2G4C 4/7 (57.1%) 6.83 (1.42 to 32.80) 1.47 (0.93 to 2.32) p
<= 0.05 PLAB 12/60 (20.0%) 1.35 (0.68 to 2.67) 0.64 (0.43 to
0.95) p <= 0.05 PLAT 1/11 (9.1%) 0.34 (0.02 to 1.80) 0.58 (0.36
to 0.90) p <= 0.05 PNN 3/4 (75.0%) 12.38 (1.57 to 251.39) 1.46
(0.86 to 2.41) p <= 0.05 PNN 3/4 (75.0%) 10.96 (1.09 to 110.69)
1.42 (0.64 to 2.41) p <= 0.05 PPOX 0/0 (0.0%) 2.49 (0.96 to
5.77) p <= 0.05 SELL 1/19 (5.3%) 0.41 (0.02 to 2.03) 1.61 (1.12
to 2.31) p <= 0.05 SELL 1/19 (5.3%) 0.42 (0.02 to 2.05) 1.61
(1.11 to 2.30) p <= 0.05 SERPINA10 1/21 (4.8%) 0.24 (0.03 to
1.79) 1.55 (1.03 to 2.32) p <= 0.05 SERPINA10 1/24 (4.2%) 0.19
(0.01 to 0.89) 1.48 (1.00 to 2.18) p <=
0.05 SERPINA10 1/23 (4.3%) 0.23 (0.03 to 1.78) 1.69 (1.12 to 2.54)
p <= 0.05 SERPINB8 22/220 (10.0%) 0.54 (0.32 to 0.91) 0.73 (0.50
to 1.06) p <= 0.05 SERPINB8 43/131 (32.8%) 1.71 (1.07 to 2.73)
1.65 (1.15 to 2.36) p <= 0.05 SERPINB8 43/120 (35.8%) 1.75 (1.09
to 2.82) 1.69 (1.18 to 2.44) p <= 0.05 SERPINI2 17/179 (9.5%)
0.56 (0.47 to 1.51) 1.64 (1.14 to 2.38) p <= 0.05 SERPINI2
17/116 (14.7%) 0.54 (0.45 to 1.49) 1.68 (1.13 to 2.45) p <= 0.05
SERPINI2 17/175 (9.7%) 0.90 (0.50 to 1.61) 1.64 (1.13 to 2.40) p
<= 0.05 SERPINI2 17/113 (15.0%) 0.85 (0.46 to 1.56) 1.59 (1.07
to 2.36) p <= 0.05 SPARCL1 29/93 (31.2%) 2.06 (1.22 to 3.52)
1.13 (0.77 to 1.68) p <= 0.05 SPARCL1 29/152 (19.1%) 1.91 (1.15
to 3.18) 1.17 (0.80 to 1.71) p <= 0.05 SPARCL1 29/92 (31.5%)
2.22 (1.28 to 3.83) 1.07 (0.72 to 1.60) p <= 0.05 SPON2 2/22
(9.1%) 0.73 (0.12 to 2.54) 1.59 (1.08 to 2.31) p <= 0.05 SPON2
2/22 (9.1%) 1.00 (0.23 to 4.48) 1.69 (1.14 to 2.49) p <= 0.05
SREBF2 3/8 (37.5%) 4.76 (1.11 to 20.60) 1.41 (0.59 to 2.25) p <=
0.05 TAP2 4/10 (40.0%) 4.47 (1.13 to 15.84) 1.01 (0.62 to 1.59) p
<= 0.05 TAP2 4/8 (50.0%) 7.07 (1.66 to 30.19) 1.12 (0.69 to
1.80) p <= 0.05 TNF 5/10 (50.0%) 4.25 (1.16 to 15.55) 1.25 (0.85
to 1.82) p <= 0.05 TNF 5/10 (50.0%) 4.12 (1.13 to 15.06) 1.31
(0.89 to 1.94) p <= 0.05 TRPC6 1/18 (5.6%) 0.44 (0.02 to 2.19)
1.63 (1.12 to 2.35) p <= 0.05 TRPC6 1/7 (14.3%) 0.75 (0.04 to
4.45) 1.62 (1.09 to 2.37) p <= 0.05 TRPC6 1/17 (5.9%) 0.63 (0.08
to 4.88) 1.70 (1.16 to 2.48) p <= 0.05 VTN 33/268 (12.3%) 1.44
(0.86 to 2.42) 2.02 (1.33 to 3.13) p <= 0.005 VTN 33/176 (18.8%)
1.36 (0.79 to 2.32) 1.93 (1.25 to 3.04) p <= 0.05 VTN 33/262
(12.6%) 1.40 (0.82 to 2.38) 2.03 (1.31 to 3.16) p <= 0.005 VTN
33/174 (19.0%) 1.31 (0.75 to 2.26) 1.91 (1.20 to 3.03) p <= 0.05
*For the CARE prospective study design: results of the Overall
Score Test (chi-square test) for the logistic regression model in
which the phenotype (case definition) is a function of SNP genotype
(based on placebo patients only). For the case/control study
design: results of the Overall Score Test (chi-square test) for the
conditional logistic regression model in which the phenotype (case
definition) is a function of SNP genotype (based on placebo
patients only) and cases and controls were matched on age and
current smoking status. **Results of the chi-square test of the SNP
affect based on the logistic regression model in which the
phenotype (case definition) is a function of SNP genotype (based on
placebo patients only). Results of the chi-square test of the SNP
effect based on the conditional logistic regression model in which
the phenotype (case definition) is a function of SNP genotype
(based on placebo patients only) and cases and controls were
matched on age and current smoking status. ***All Possible Controls
include all control with genotype data. Cleaner controls include
controls with genotype data but with no other CVD-related events
during the trial.
[0493]
21TABLE 15 PON1 hCV2548962: Consistant interaction between PON1
Genotype and Efficiency within Both CARE & WOSCOPS Overall*
Chi-Square Study Control Test Public Marker Study Design Case
Definition Group Definition*** Staturm Statistic p-value PON1
hCV2548962 CARE Prospective Total CHD Events All Possible White
Moles 21.82 0.0005 PON1 hCV2548962 CARE Prospective Fatal &
NonFatal MI Cleaner White Moles 13.00 0.0234 PON1 hCV2548962 CARE
Case/Control Fatal & NonFatal MI Cleaner White Moles 13.79
0.0170 PON1 hCV2548962 WOSCOPS Case/Control Fatal & NonFatal MI
Cleaner White Moles 15.68 0.0079 Interraction 0 Rare Alleles 1 Rare
Allele 2 Rare Allele Effect** Chi n/total (%) n/total (%) n/total
(%) Square Test Pravestatin Pravestatin Pravestatin Placabo Public
Statistic p-value Patients Placabo Patients Patients Placabo
Patients Patients Patients PON1 11.51 0.0030 183/613 (29.9%)
223/627 (35.6%) 151/504 (30.0%) 143/458 (31.2%) 18/107 (16.5%)
42/100 (42.0%) PON1 3.69 0.1583 57/1423 (15.8%) 75/386 (18.8%)
50/340 (14.7%) 54/303 (21.1%) 9/80 (11.3%) 18/54 (25.1%) PON1 5.15
0.0763 67/1415 (16.1%) 75/394 (19.0%) 50/335 (14.9%) 64/297 (21.6%)
9/79 (11.4%) 18/64 (28.1%) PON1 4.89 0.258 88/344 (25.6%) 112/355
(29.0%) 65/282 (23.1%) 96/293 (33.5%) 9/53 (17.0%) 22/59 (37.3%)
CARE & WOSCOPS vs. Placabo Odds Ratio (95% CI) Combined#
Signifigance Public Patients with 0 Rare Alleles Patients with 1
Rare Allele Patients with 2 Rare Alleles Statistic p-value Level
PON1 0.77 (0.61 to 0.96) 0.94 (0.58 to 1.54) 0.28 (0.13 to 0.50) NA
PON1 0.81 (0.56 to 1.15) 0.64 (0.31 to 1.36) 0.32 (0.11 to 0.95) NA
PON1 0.84 (0.58 to 1.22) 0.53 (0.42 to 0.95) 0.29 (0.12 to 0.71)
9.34 0.0432 p < 0.05 PON1 0.84 (0.60 to 1.16) 0.58 (0.40 to
0.84) 0.34 (0.14 to 0.82) *For the CARE prospective study: results
of the Overall Score Test (chi-square test) for the logistic
regression model in which the phenotype (case definition) is a
function of the SNP genotype treatment group, and the interaction
between SNP genotype and treatment group. *For case/control
studies: results of the Overall Score Test (chi-square test) for
the conditional logistical regression modal in which the phenotype
(case definition) is a function of the SNP genotype treatment
group, and the interaction between SNP genotype and treatment group
and cases and controls have been matched on age and smoking status.
**For the CARE prospective study: results of the chi-square test of
the interaction between SNP genotype and treatment group (bassed on
the logistic regression model). **For the case/control studies:
results of the chi-square test of the interaction between SNP
genotype and treatment group (based on the conditional logistic
regression model). ***All possible Controls include all controls
with genotype data. Cleaner controls include controls with genotype
data but with no other CVD-related events during the trial.
#hood-ratio and Chi-square tests were used to determine whether
affcts (either of SNP genotype or of the interaction between SNP
genotype and treatment) were statistically significant.p-values for
CARE and WOSCOPS were compined using the method of Fisher (1954).
Results for # CARE and WOSCOPS were determined to be consistant
when (1) the combined p-value for the 2 studies is <=0.05. (2)
the odds ratios are concontdant, and (3) study-specific p-values
for the affect (interaction or association) are both <=0.10. Odd
ratios are defined to be concontdant if both of the 95% confidence
intervals (for both odds ratios) are below 1.0 or if both of the
95% confidence intervals are entirely above 1.0. NA = Not
Applicable.
[0494]
Sequence CWU 0
0
* * * * *