U.S. patent application number 13/657215 was filed with the patent office on 2013-08-15 for genetic polymorphisms associated with psoriasis, methods of detection and uses thereof.
This patent application is currently assigned to CELERA CORPORATION. The applicant listed for this patent is Celera Corporation. Invention is credited to Ann BEGOVICH, Michele CARGILL, Monica CHANG, Yonghong LI, Steven SCHRODI.
Application Number | 20130209486 13/657215 |
Document ID | / |
Family ID | 40718480 |
Filed Date | 2013-08-15 |
United States Patent
Application |
20130209486 |
Kind Code |
A1 |
LI; Yonghong ; et
al. |
August 15, 2013 |
GENETIC POLYMORPHISMS ASSOCIATED WITH PSORIASIS, METHODS OF
DETECTION AND USES THEREOF
Abstract
The present invention is based on the discovery of genetic
polymorphisms that are associated with psoriasis and related
pathologies. In particular, the present invention relates to
nucleic acid molecules containing the polymorphisms, including
groups of nucleic acid molecules that may be used as a signature
marker set, such as a haplotype, a diplotype, 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: |
LI; Yonghong; (Palo Alto,
CA) ; SCHRODI; Steven; (Madison, WI) ;
BEGOVICH; Ann; (El Cerrito, CA) ; CHANG; Monica;
(Oakland, CA) ; CARGILL; Michele; (Orinda,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Celera Corporation; |
|
|
US |
|
|
Assignee: |
CELERA CORPORATION
Alameda
CA
|
Family ID: |
40718480 |
Appl. No.: |
13/657215 |
Filed: |
October 22, 2012 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13080458 |
Apr 5, 2011 |
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13657215 |
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12325832 |
Dec 1, 2008 |
7947451 |
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13080458 |
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61005018 |
Nov 30, 2007 |
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Current U.S.
Class: |
424/158.1 ;
435/6.11; 514/18.6; 514/44A; 536/24.31 |
Current CPC
Class: |
C12Q 2600/172 20130101;
G01N 2800/50 20130101; G01N 33/6881 20130101; G01N 2800/065
20130101; A61P 37/00 20180101; G01N 2500/04 20130101; C12Q 2600/158
20130101; C12Q 2600/136 20130101; G01N 2800/205 20130101; C12Q
2600/156 20130101; G01N 33/6893 20130101; A61P 17/06 20180101; C12Q
2600/106 20130101; C12Q 1/6883 20130101 |
Class at
Publication: |
424/158.1 ;
435/6.11; 536/24.31; 514/44.A; 514/18.6 |
International
Class: |
C12Q 1/68 20060101
C12Q001/68 |
Claims
1. A method for determining whether a human has an altered risk for
psoriasis or Crohn's Disease, comprising testing nucleic acid from
said human for the presence or absence of a single nucleotide
polymorphism (SNP) as represented by position 101 of SEQ ID NOS:
5-9 and 19-110 or their complements, wherein the presence of the
SNP indicates said human has an altered risk for psoriasis or
Crohn's Disease.
2. The method of claim 1 in which the altered risk is an increased
risk.
3. The method of claim 1 in which the altered risk is a decreased
risk.
4. The method of claim 1, wherein the SNP is selected from the
group consisting of rs1800925, rs20541, and rs848.
5. 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.
6. The method of claim 1, wherein said nucleic acid is a nucleic
acid extract from a biological sample from said human.
7. The method of claim 1, wherein said biological sample is blood,
saliva, or buccal cells.
8. The method of claim 1, further comprising preparing said nucleic
acid extract from said biological sample prior to said testing
step.
9. The method of claim 8, further comprising obtaining said
biological sample from said human prior to said preparing step.
10. The method of claim 1, wherein said testing step comprises
nucleic acid amplification.
11. The method of claim 10, wherein said nucleic acid amplification
is carried out by polymerase chain reaction.
12. The method of claim 1, further comprising correlating the
presence or absence of said SNP with the altered risk for psoriasis
or Crohn's Disease.
13. The method of claim 1, wherein said correlating step is
performed by computer software.
14. A method for identifying an agent useful in therapeutically or
prophylactically treating psoriasis, the method comprising
contacting a polypeptide comprising an amino acid sequence selected
from the group consisting of SEQ ID NOS: 3-4 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.
15. The method of claim 1, wherein the SNP comprises a SNP
haplotype selected from the group consisting of: the risk haplotype
of rs1800925(C), rs20541(C), and rs848(G); and the protective
haplotype of rs1800925(T), rs20541(T), and rs848(T).
16. The method of claim 2, wherein the SNP comprises the risk
haplotype of rs1800925(C), rs20541(C), and rs848(G).
17. The method of claim 3, wherein the SNP comprises the protective
haplotype of rs1800925(T), rs20541(T), and rs848(T).
18. A method for determining a human's risk of developing
psoriasis, the method comprising detecting a SNP haplotype selected
from the group consisting of the risk haplotype of rs1800925(C),
rs20541(C), and rs848(G) and the protective haplotype of
rs1800925(T), rs20541(T), and rs848(T) in said human's nucleic
acids, wherein the presence of the SNP haplotype is indicative of
an altered risk of developing psoriasis in said human.
19. A method for determining whether a human will likely benefit
from a drug treatment targeting IL13, the method comprising testing
nucleic acid from said human for the presence or absence of a SNP
as represented by position 101 of SEQ ID NOS: 5-9 and 19-110 or
their complement, wherein the presence or absence of the SNP
indicates that said human is likely to benefit from the drug
treatment.
20. The method of claim 19, wherein the human is selected for
inclusion in a clinical trial of the drug treatment.
21. A method of treating a human who will likely benefit from a
drug treatment targeting IL13, the method comprising testing
nucleic acid from said human for the presence or absence of a SNP
as represented by position 101 of SEQ ID NOS: 5-9 and 19-110 or
their complement, wherein the presence or absence of the SNP
indicates that said human is likely to benefit from the drug
treatment, and administering said drug treatment to said human.
22. The method of any one of claim 4, 15, or 18, wherein the method
further comprises detecting at least one variant selected from the
group consisting of HLA-C, SNPs in IL12B, and SNPs in IL23R.
23. The method of claim 22, wherein the HLA-C variant is HLA-C
*0602.
24. The method of claim 22, wherein the SNPs in IL12 and IL23R are
selected from the group consisting of: SNPs rs321227, rs3212220,
rs7709212, and rs6887695; the psoriasis risk haplotype
rs3212227(A)/rs6887695(G); the psoriasis protective haplotype
rs3212227(C)/rs6887695(C); the psoriasis risk haplotype
rs11209026(G)/rs7530511(C); a SNP diplotype which is a combination
of two copies of the risk haplotype, rs3212227(A)/rs6887695(G); a
SNP diplotype which is a combination of two copies of the
protective haplotype, rs3212227(C)/rs6887695(C); a SNP diplotype
which is a combination of two copies of the risk haplotype
rs11209026(G)/rs 7530511(C); and a two-locus diplotype which is a
combination of
rs3212227(A)/rs6887695(G)/rs11209026(G)/rs7530511(C).
25. A kit for carrying out the method of claim 1, wherein the kit
comprises at least one polynucleotide detection reagent, and
wherein the polynucleotide detection reagent selectively hybridizes
to said nucleic acid in the presence of said polymorphism and does
not hybridize to said nucleic acid in the absence of said
polymorphism.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation application of U.S.
non-provisional application Ser. No. 13/080,458, filed on Apr. 5,
2011, which is a divisional application of U.S. non-provisional
application Ser. No. 12/325,832, filed on Dec. 1, 2008 (issued as
U.S. Pat. No. 7,947,451 on May 24, 2011), which claims priority to
U.S. provisional application Ser. No. 61/005,018, filed on Nov. 30,
2007, the contents of each of which are hereby incorporated by
reference in their entirety into this application.
FIELD OF THE INVENTION
[0002] The present invention is in the field of diagnosis and
therapy of psoriasis. In particular, the present invention relates
to specific single nucleotide polymorphisms (SNPs) in the human
genome, and their association with psoriasis and related
pathologies. Based on differences in allele frequencies in the
psoriasis patient population relative to normal 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 identifying an individual who is at an increased or
decreased risk of developing psoriasis and for early detection of
the disease, for providing clinically important information for the
prevention and/or treatment of psoriasis, 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
[0003] Psoriasis is a common, chronic, T-cell-mediated inflammatory
disease of the skin affecting .about.2-3% of whites of European
descent. Although this disease is found in all populations, its
prevalence is lower in Asians and African-Americans and also
declines at lower latitudes. The most common form, psoriasis
vulgaris, is characterized by varying numbers of red, raised, scaly
skin patches that can be present on any body surface, but most
often appear on the elbows, knees and scalp. The onset of disease
usually occurs early in life (15-30 years) and affects males and
females equally. Up to 30% of individuals with psoriasis will
develop an inflammatory arthritis, which can affect the peripheral
joints of the hands and feet, large joints, or the central
axial-skeleton. Pathologically, psoriasis is characterized by
vascular changes, hyperproliferation of keratinocytes, altered
epidermal differentiation and inflammation. In particular, the
reaction of cells in the epidermis to type 1 effector molecules
produced by T-cells results in the characteristic pathology of the
plaques.
[0004] The genetics of psoriasis are complex and highly heritable
as evidenced by an increased rate of concordance in monozygotic
twins over dizygotic twins (35%-72% vs. 12-23%) and a substantially
increased incidence in family members of affected individuals
(first-degree relatives 6%); however, it is clear that
environmental effects are also responsible for disease
susceptibility. Ten genome-wide linkage scans have resulted in
strong evidence for a susceptibility locus in the MHC region on
6p21 (PSORS1 [MIM 177900]), but have not yielded consistent
evidence for other regions.
[0005] Linkage and association in the MHC (6p21) are thought to be
due to HLA-C, in particular psoriasis susceptibility effects are
thought to be caused by the *0602 allele, although other candidate
genes in the area may also contribute to disease predisposition.
Association studies have identified three genes under linkage
peaks, with considerable evidence for linkage disequilibrium with
psoriasis, namely SLC9A3R1/NAT9 and RAPTOR (KIAA1303) in 17q25, and
SLC12A8 in 3q21. Several other genes including VDR, MMP2, IL10,
IL1RN, IL12B, and IRF2 (Genetic Association Database, OMIM) have
been associated with psoriasis in sample sets of varying sizes and
of different ethnicities; however, without more data from
additional independent studies, it is difficult to draw
statistically sound conclusions about whether these markers are
truly associated with disease. Thus, there remains a need for the
discovery of reliable markers that can associate themselves with
psoriasis, and in turn, would facilitate the diagnosis and
treatment of the disease.
[0006] The discovery of genetic markers which are useful in
identifying psoriasis individuals who are at increased risk for
developing psoriasis may lead to, for example, better therapeutic
strategies, economic models, and health care policy decisions.
[0007] SNPs
[0008] 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 members of the 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.
[0009] 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 1/100 or 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.
[0010] 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):855-82).
[0011] 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".
[0012] 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 Jul. 2001). As used herein, the term "haplotype" refers
to a set of two or more alleles on a single chromosome. The term
"diplotype" refers to a combination of two haplotypes that a
diploid individual carries. The term "double diplotype", also
called "two-locus diplotype", refers to a combination of diplotypes
at two distinct loci for an individual.
[0013] 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.
[0014] 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.
[0015] 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 psoriasis and related pathologies 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.
[0016] 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 pathological condition, such as
pathologies related to psoriasis, increased or decreased risk of
developing psoriasis. 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).
[0017] 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 (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
[0018] The present invention relates to the identification of novel
SNPs, unique combinations of such SNPs, haplotypes or diplotypes of
SNPs that are associated with psoriasis and in particular the
increased or decreased risk of developing psoriasis. 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
psoriasis and related pathologies.
[0019] Based on the identification of SNPs associated with
psoriasis, 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
psoriasis and related pathologies, 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 identifying individuals who have an altered (i.e.,
increased or decreased) risk of developing psoriasis 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 (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.
[0020] In Tables 1-2, the present invention provides gene
information, transcript sequences (SEQ ID NOS: 1-2), encoded amino
acid sequences (SEQ ID NOS:3-4), genomic sequences (SEQ ID
NOS:10-18), transcript-based context sequences (SEQ ID NOS:5-9) and
genomic-based context sequences (SEQ ID NOS:19-110) 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:1-2), amino acid
sequences (SEQ ID NOS:3-4), genomic sequences (SEQ ID NOS: 10-18),
transcript-based SNP context sequences (SEQ ID NOS: 5-9), and
genomic-based SNP context sequences (SEQ ID NOS:19-110) are also
provided in the Sequence Listing.
[0021] 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 psoriasis
and related pathologies. In particular the SNPs are associated with
either an increased or decreased risk of developing psoriasis. As
such, they can have a variety of uses in the diagnosis and/or
treatment of psoriasis and related pathologies. 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 that is propriatory to Applera, or Celera. 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 that is encoded by a
nucleic acid molecule containing a SNP disclosed herein.
[0022] 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.
[0023] In another embodiment of the invention, applicants teach a
method of determining whether a human has an altered risk (either
increased risk or decreased risk) of developing psoriasis or other
related diseases such as Crohn's Diseases, comprising testing
nucleic acid from said human for the presence of absence of a
polymorphism selected from the exon 4 LD block of IL13, wherein the
presence of said polymorphism indicates that said human has an
altered risk of developing psoriasis or other related diseases such
as Crohn's Diseases. Examples of such polymorphisms are disclosed
in Table 1 and Table 2.
[0024] In a further embodiment of the invention, applicants teach a
method of further correlating the presence or absence of the SNP
with the altered risk for psoriasis or Crohn's Disease for said
human.
[0025] 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 psoriasis by detecting the presence or absence of one or
more SNP alleles disclosed herein. Preferably, the SNP allele can
be an allele of a SNP selected from the group consisting of
rs1800925, rs20541, and rs848, or a combination of any number of
them.
[0026] In another embodiment, a method for diagnosis of psoriasis
and related pathologies by detecting the presence or absence of one
or more SNP alleles disclosed herein is provided. In another
embodiment, the invention provides for a method of identifying an
individual having an altered (either increased, or, decreased) risk
of developing psoriasis by detecting the presence or absence of one
or more SNP haplotypes disclosed herein.
[0027] The SNP haplotype herein can be, for example, a combination
of rs1800925(C), rs20541(C), and rs848(G), as a risk haplotype
(interchangeably referred to as a susceptible haplotype). The SNP
haplotype herein can also be, for example, a combination of
rs1800925(T), rs20541(T), and rs848(T), as a protective
haplotype.
[0028] Furthermore, an exemplary embodiment of the invention
provides for a method of identifying an individual having an
increased risk of developing psoriasis by detecting the presence or
absence of one or more SNP haplotypes. Preferably, the SNP
haplotype can be a combination of rs1800925(C), rs20541(C), and
rs848(G). An alternative exemplary embodiment of the invention
provides for a method of identifying an individual having a
decreased risk of developing psoriasis by detecting the presence or
absence of one or more SNP haplotypes. Preferably, the SNP
haplotype can be a combination of rs1800925(T), rs20541(T), and
rs848(T).
[0029] 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 psoriasis and related pathologies.
[0030] An aspect of this invention is a method for treating
psoriasis 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 counteracting the effects of the disease, such as by
inhibiting (or stimulating) the activity of the gene, transcript,
and/or encoded protein identified in Tables 1-2.
[0031] Another aspect of this invention is a method for identifying
an agent useful in therapeutically or prophylactically treating
psoriasis and related pathologies 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
under conditions suitable to allow formation of a binding complex
between the gene, transcript, or encoded protein and the candidate
agent and detecting the formation of the binding complex, wherein
the presence of the complex identifies said agent.
[0032] Another aspect of this invention is a method for treating
psoriasis and related pathologies in a human subject, which method
comprises:
[0033] (i) determining that said human subject harbors a SNP, gene,
transcript, and/or encoded protein identified in Tables 1-2,
and
[0034] (ii) administering to said subject a therapeutically or
prophylactically effective amount of one or more agents
counteracting the effects of the disease.
[0035] Yet another aspect of this invention is a method for
evaluating the suitability of a patient for psoriasis treatment
comprising determining the genotype of said patient with respect to
a particular set of SNP markers, said SNP markers comprising a
plurality of individual SNPs ranging from two to seven SNPs in
Table 1 or Table 2, and calculating a score using an appropriate
algorithm based on the genotype of said patient, the resulting
score being indicative of the suitability of said patient
undergoing psoriasis treatment.
[0036] Another aspect of the invention is a method of treating a
psoriasis patient comprising administering an appropriate drug in a
therapeutically effective amount to said psoriasis patient whose
genotype has been shown to contain a plurality of SNPs as described
in Table 1 or Table 2.
[0037] 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.
DESCRIPTION OF THE SEQUENCE LISTING
[0038] File CD000018ORD_SEQLIST.TXT provides the Sequence Listing
in text (ASCII) format. The Sequence Listing provides the
transcript sequences (SEQ ID NOS:1-2) and protein sequences (SEQ ID
NOS:3-4) as shown in Table 1, and genomic sequence (SEQ ID
NO:10-18) as shown in Table 2, for each liver fibrosis-associated
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:5-9) and genomic-based context
sequences as shown in Table 2 (SEQ ID NOS:19-110). 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.
[0039] File CD000018ORD_SEQLIST.TXT is 716 KB in size, and was
created on Nov. 25, 2008.
[0040] The Sequence Listing is hereby incorporated by reference
pursuant to 37 CFR 1.77(b)(4).
[0041] Description of Table 1 and Table 2
[0042] Table 1 and Table 2 disclose the SNP and associated
gene/transcript/protein information of the present invention. For
each gene, Table 1 provides a header containing gene, transcript
and protein information, followed by a transcript and protein
sequence identifier (SEQ ID NO), and then SNP information regarding
each SNP found in that gene/transcript including the transcript
context sequence. For each gene in Table 2, a header is provided
that contains gene and genomic information, followed by a genomic
sequence identifier (SEQ ID NO) and then SNP information regarding
each SNP found in that gene, including the genomic context
sequence.
[0043] Note that SNP markers 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. Additionally, in either Table 1 or 2 a
"Related Interrogated SNP" may be listed following a SNP which is
determined to be in LD with that interrogated SNP according to the
given Power value. SNPs can be readily cross-referenced between all
Tables based on their Celera hCV (or, in some instances, hDV)
identification numbers and/or public rs identification numbers, and
to the Sequence Listing based on their corresponding SEQ ID
NOs.
[0044] The gene/transcript/protein information includes: [0045] a
gene number (1 through n, where n=the total number of genes in the
Table), [0046] a gene symbol, along with an Entrez gene
identification number (Entrez Gene database, National Center for
Biotechnology Information (NCBI), National Library of Medicine,
National Institutes of Health) [0047] a gene name, [0048] an
accession number for the transcript (e.g., RefSeq NM number, or a
Celera hCT identification number if no RefSeq NM number is
available) (Table 1 only), [0049] an accession number for the
protein (e.g., RefSeq NP number, or a Celera hCP identification
number if no RefSeq NP number is available) (Table 1 only), [0050]
the chromosome number of the chromosome on which the gene is
located, [0051] an OMIM ("Online Mendelian Inheritance in Man"
database, Johns Hopkins University/NCBI) public reference number
for the gene, and OMIM information such as alternative gene/protein
name(s) and/or symbol(s) in the OMIM entry.
[0052] Note that, due to the presence of alternative splice forms,
multiple transcript/protein entries may 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.
[0053] Following the gene/transcript/protein information is a
transcript context sequence (Table 1), or a genomic context
sequence (Table 2), for each SNP within that gene.
[0054] 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 (such SNPs are identified as "INTERGENIC" for SNP
type).
[0055] Note that the transcript, protein, and transcript-based SNP
context sequences are all provided in the Sequence Listing. The
transcript-based SNP context sequences are provided in both Table 1
and also in the Sequence Listing. The genomic and genomic-based SNP
context sequences are provided in the Sequence Listing. The
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 the transcript-based context sequences (SEQ ID NOS:5-9); SEQ ID
NOs are indicated in Table 2 for the genomic-based context
sequences (SEQ ID NOS:19-110).
[0056] The SNP information includes: [0057] Context sequence (taken
from the transcript sequence in Table 1, 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:5-9; the
genomic-based SNP context sequences in Table 2 are provided in the
Sequence Listing as SEQ ID NOS:19-110). [0058] Celera hCV internal
identification number for the SNP (in some instances, an "hDV"
number is given instead of an "hCV" number). [0059] The
corresponding public identification number for the SNP, the rs
number. [0060] "SNP Chromosome Position" indicates the nucleotide
position of the SNP along the entire sequence of the chromosome as
provided in NCBI Genome Build 36. [0061] SNP position (nucleotide
position of the SNP within the given transcript sequence (Table 1)
or within the given genomic sequence (Table 2)). [0062] "Related
Interrogated SNP" is the interrogated SNP with which the listed SNP
is in LD at the given value of Power. [0063] 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 a disease, "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).
[0064] Note that 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.
[0065] Certain SNPs from Tables 1 and 2 are SNPs 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. 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).
These SNPs include: hCV25597248 (transcript-based context sequence
SEQ ID NO:39 in Table 1, genomic-based context sequence SEQ ID
NO:113 in Table 2) and hCV25635059 (transcript-based context
sequences SEQ ID NOS:42 and 45 in Table 1; genomic-based context
sequences SEQ ID NO:123 and 335 in Table 2). [0066]
Population/allele/allele count information in the format of
[population1(first_allele,count|second_allele,count)population2(first_all-
ele,count|second_allele,count) total (first_allele,total
count|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 "|"); "-" 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"=human individual 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
six 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_CA"=Caucasians-12 DNAs from Corielle cell repositories
that are from the CEPH/UTAH library, six male and six female.
[0067] Note that 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.
[0068] Note that 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. [0069] 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]. [0070] 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.
[0071] Note that SNPs can be cross-referenced between all tables
herein based on the hCV/hDV and/or rs identification number of each
SNP.
[0072] Description of Table 3
[0073] Table 3 provides sequences (SEQ ID NOS:111-164) of primers
that have been synthesized and used in the laboratory to assay
certain SNPs by allele-specific PCR during the course of
association studies to verify the association of these SNPs with
psoriasis (see Examples section).
[0074] Table 3 provides the following: [0075] the column labeled
"Marker" provides an hCV identification number for each SNP. [0076]
the column labeled "rs number" provides the public rs
identification number for each SNP. [0077] the column labeled
"Alleles" designates the two alternative alleles (i.e.,
nucleotides) at the SNP site. These alleles are targeted by the
allele-specific primers (the allele-specific primers are shown as
Primer 1 and Primer 2). Note that alleles may be presented in Table
3 based on a different orientation (i.e., the reverse complement)
relative to how the same alleles are presented in Tables 1-2.
[0078] the column labeled "Primer 1 (Allele-Specific Primer)"
provides an allele-specific primer that is specific for an allele
designated in the "Alleles" column. [0079] the column labeled
"Primer 2 (Allele-Specific Primer)" provides an allele-specific
primer that is specific for the other allele designated in the
"Alleles" column. [0080] the column labeled "Common Primer"
provides a common primer that is used in conjunction with each of
the allele-specific primers (i.e., Primer 1 and Primer 2) and which
hybridizes at a site away from the SNP position.
[0081] All primer sequences are given in the 5' to 3'
direction.
[0082] 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 (i.e., either Primer 1 or
Primer 2) that is specific for that allele.
[0083] Description of Table 4
[0084] Table 4 provides a list of LD SNPs that are related to and
derived from certain interrogated SNPs. The interrogated SNPs,
which are shown in column 1 (which indicates the hCV identification
numbers of each interrogated SNP) and column 2 (which indicates the
public rs identification numbers of each interrogated SNP) of Table
4, are statistically significantly associated with psoriasis as
shown in the tables. These LD SNPs are provided as an example of
SNPs which can also serve as markers for disease association based
on their being in LD with an interrogated SNP. The criteria and
process of selecting such LD SNPs, including the calculation of the
r.sup.2 value and the r.sup.2 threshold value, are described in
Example Two, below.
[0085] In Table 4, the column labeled "Interrogated SNP" presents
each marker as identified by its unique hCV identification number.
The column labeled "Interrogated rs" presents the publicly known
identifier rs number for the corresponding hCV number. The column
labeled "LD SNP" presents the hCV numbers of the LD SNPs that are
derived from their corresponding interrogated SNPs. The column
labeled "LD SNP rs" presents the publicly known rs number for the
corresponding hCV number. The column labeled "Power" presents the
level of power where the r.sup.2 threshold is set. For example,
when power is set at 0.51, the threshold r.sup.2 value calculated
therefrom is the minimum r.sup.2 that an LD SNP must have in
reference to an interrogated SNP, in order for the LD SNP to be
classified as a marker capable of being associated with a disease
phenotype at greater than 51% probability. The column labeled
"Threshold r.sup.2" presents the minimum value of r.sup.2 that an
LD SNP must meet in reference to an interrogated SNP in order to
qualify as an LD SNP. The column labeled "r.sup.2" presents the
actual r.sup.2 value of the LD SNP in reference to the interrogated
SNP to which it is related.
[0086] Descriptions of Tables 5-16
[0087] Table 5 provides statistical results for the association of
the IL13 SNPs rs1800925, rs20541, and rs848 with psoriasis. All
three SNPs were individually genotyped using allele-specific
real-time PCR as previously described.sup.9. Positions for each SNP
are given according to genomic contig NT.sub.--034772.5 (Entrez
Nucleotide). The minor allele is listed first, followed by the
position in National Center for Biotechnology Information Genome
Build 36.2 and then the major allele. All samples were white of
Northern European extraction and are described in detail
elsewhere.sup.9 (Sample set 1: 467 cases/460 controls; sample set
2: 498 cases/498 controls; sample set 3: 481 cases/424 controls).
Hardy-Weinberg exact P-values were calculated according to the
formula of Weir..sup.10 Fisher's exact P-values were calculated for
allelic data. Two-tailed P-values are presented for Sample Set 1;
one-tailed P-values are given for Sample Sets 2 and 3. Combined
P-values were calculated using a Fisher's combined P-value, or
omnibus method. Genotypic P-values for the individual sample sets
were calculated using the William's-corrected G test..sup.11 As
with the allelic analysis, Sample Set 1 P-values are two-tailed;
Sample Set 2 and 3 P-values are one-tailed. Odds ratios were
calculated for the minor allele. Combined or joint ORs were
calculated using a Mantel-Haenszel common OR.
[0088] Table 6 provides statistical results for the association of
three-marker IL13 haplotypes with psoriasis. The order of SNPs is
rs1800925-rs20541-rs848. The Haplo.Stats package.sup.12 was used to
estimate haplotype frequencies from unphased data, treating cases
and controls separately, and to test for association between
haplotypes and disease status. Global P-values were also calculated
and all P-values were adjusted for haplotype estimation error. Two
tailed P-values are presented for sample set 1; one-tailed P-values
are presented for Sample Sets 2 and 3. P-values were combined using
Fisher's combined probability method. Mantel-Haenszel joint odds
ratios (OR.sub.MH) were calculated for each haplotype.
[0089] Table 7 provides HLA-cytokine pathway psoriasis relative
risk estimates. HLA-C genotypes were partitioned into *0602
carriers and noncarriers. IL12B (rs3212227 and 6887695) and IL23R
(rs7530511 and rs11209026) diplotypes.sup.9 were combined with IL13
(rs1800925) genotypes and classified into risk groups (Very High to
Low) as outlined below Table 7. Psoriasis prevalence was set at
0.03. The probability of psoriasis conditioned on each multi-locus
genotype--P(MLG), was calculated using Bayes' theorem. The P(MLG)
was divided by the unconditioned psoriasis risk (disease
prevalence) to obtain the relative risk values. Confidence
intervals were calculated using 10,000 replicates of a Monte Carlo
simulation. The scaled relative risk (SRR) was calculated by
setting the lowest risk category equal to 1.
[0090] Throughout Tables 5-16, "OR" refers to the odds ratio, "95%
CI" refers to the 95% confidence interval for the odds ratio, "MAF"
refers to the minor allele frequency, and "HWE" refers to
Hardy-Weinberg equilibrium.
[0091] Odds ratios (OR) greater than one indicate that a given
allele (or combination of alleles such as a haplotype, diplotype,
or two-locus diplotype) is a risk allele, whereas odds ratios less
than one indicate that a given allele is a non-risk allele (which
may also be referred to as a protective allele). For a given risk
(i.e., susceptible) allele, the other alternative allele at the SNP
position (which can be derived from the information provided in
Tables 1-2, for example) may be considered a non-risk (i.e.,
protective) allele. For a given non-risk (i.e., protective) allele,
the other alternative allele at the SNP position may be considered
a risk allele.
[0092] Tables 8-16 are described in detail in the Examples section
below.
BRIEF DESCRIPTION OF THE FIGURES
[0093] FIG. 1 shows a HLA-cytokine pathway psoriasis relative risk
plot. The scaled relative risk of each multi-locus genotype
combination is graphed using the data from sample set 1. HLA-C
genotypes were determined as previously described.sup.9 and
aggregated into *0602 carriers and noncarriers.
Psoriasis-associated diplotypes at IL12B (rs3212227 and rs6887695)
and IL23R (rs753511 and rs11209026).sup.9 were combined with
genotypes at rs1800925 (5' of IL13) and partitioned into four
cytokine pathway categories: very high risk, high risk, moderate
risk and low risk (as described in the description of Table 7).
Psoriasis prevalence of 0.03 was assumed. Conditional independence
between the loci was also assumed [Three separate analyses-a
genotype-based squared correlation coefficient, the Multifactor
dimensionality reduction (MDR) program,.sup.17 and a Monte Carlo
simulation-substantiated this assumption and provided no evidence
for significant interaction effects between these markers.].
Expected frequencies of the multi-locus genotype combinations are
presented for both affected and unaffected populations and are
listed above each bar (affected/unaffected). The relative risk
estimates were scaled with respect to the lowest risk category,
which was set at 1.00.
[0094] FIG. 2 shows a schematic representation of (A) P-values of
SNPs tested in the three sample sets individually (SS1, SS2 and
SS3) and combined (meta). A total of 93 SNPs were tested in sample
set 1; 12 SNPs were tested in sample sets 2 and 3. rs1800925,
rs20541 and rs848, which were previously reported to be associated
with psoriasis (21), were tested in all three sample sets. A gene
map is shown at the bottom, based on the NCBI b36 genome assembly.
(B) Inter-marker LD of the 93 markers in sample set 1. D' values
are shown in the top right triangle, and r.sup.2 values are in the
bottom triangle. The D' and r.sup.2 values were calculated using
both cases and controls of sample set 1.
DETAILED DESCRIPTION OF THE INVENTION
[0095] The present invention provides SNPs associated with
psoriasis and related pathologies, nucleic acid molecules
containing 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 psoriasis-associated SNPs disclosed herein are useful for
diagnosing, screening for, and evaluating predisposition to
psoriasis, including an increased or decreased risk of developing
psoriasis, the rate of progression of psoriasis, and related
pathologies in humans. Furthermore, such SNPs and their encoded
products are useful targets for the development of therapeutic
agents.
[0096] 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.
[0097] Thus, the present invention provides individual SNPs
associated with psoriasis, as well as combinations of SNPs and
haplotypes in genetic regions associated with psoriasis,
polymorphic/variant transcript sequences (SEQ ID NOS:1-2) and
genomic sequences (SEQ ID NOS:10-18) containing SNPs, encoded amino
acid sequences (SEQ ID NOS: 3-4), and both transcript-based SNP
context sequences (SEQ ID NOS: 5-9) and genomic-based SNP context
sequences (SEQ ID NOS:19-110) (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 psoriasis, methods of screening for compounds
useful for treating disorders associated with a variant
gene/protein such as psoriasis, 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.
[0098] The present invention provides novel SNPs associated with
psoriasis and related pathologies, as well as SNPs that were
previously known in the art, but were not previously known to be
associated with psoriasis. 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
psoriasis (e.g., for diagnosing psoriasis, etc.). 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 the
tables.
[0099] Particular SNP alleles of the present invention can be
associated with either an increased risk of having or developing
psoriasis and related pathologies, or a decreased risk of having or
developing psoriasis. SNP alleles that are associated with a
decreased risk of having or developing psoriasis may be referred to
as "protective" alleles, and SNP alleles that are associated with
an increased risk of having or developing psoriasis may be referred
to as "susceptibility" alleles, "risk" alleles, or "risk factors".
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 risk of having or developing
psoriasis (i.e., a susceptibility allele), other SNPs (or their
encoded products) can be assayed to determine whether an individual
possesses a SNP allele that is indicative of a decreased risk of
having or developing psoriasis (i.e., a protective allele).
Similarly, particular SNP alleles of the present invention can be
associated with either an increased or decreased likelihood of
responding to a particular treatment or therapeutic compound, or an
increased or decreased likelihood of experiencing toxic effects
from a particular treatment or therapeutic compound. The term
"altered" may be used herein to encompass either of these two
possibilities (e.g., an increased or a decreased
risk/likelihood).
[0100] 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.
[0101] 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.
[0102] IL12B, IL23R, and HLA-C
[0103] The SNPs provided herein, particularly rs1800925, rs20541,
and rs848 [including the risk haplotype of rs1800925(C),
rs20541(C), and rs848(G); and the protective haplotype of
rs1800925(T), rs20541(T), and rs848(T)], can be combined with other
genetic variants, such as to increase the power to determine
psoriasis risk. In certain preferred embodiments, SNPs rs1800925,
rs20541, and rs848 are combined with any or all of HLA-C (e.g.,
HLA-C variant *0602), IL12B SNPs, and IL23 SNPs.
[0104] Exemplary IL12B and IL23R variants which can be used in
conjunction with rs1800925, rs20541, and/or rs848 include any of
the following SNPs, haplotypes, diplotypes, and two-locus
diplotypes, and any combination of these:
[0105] SNPs rs321227, rs3212220, rs7709212, and rs6887695.
[0106] The psoriasis risk haplotype rs3212227(A) and
rs6887695(G).
[0107] The psoriasis protective haplotype rs3212227(C) and
rs6887695(C).
[0108] The psoriasis risk haplotype rs11209026(G) and
rs7530511(C).
[0109] A SNP diplotype which is a combination of two copies of the
risk haplotype, rs3212227(A)/rs6887695(G).
[0110] A SNP diplotype which is a combination of two copies of the
protective haplotype, rs3212227(C)/rs6887695(C).
[0111] A SNP diplotype which is a combination of two copies of the
risk haplotype rs11209026(G)/rs 7530511(C).
[0112] A two-locus diplotype which is a combination of
rs3212227(A)/rs6887695(G)/rs11209026(G)/rs7530511(C).
[0113] Further information regarding the above IL12B and IL23R
SNPs, haplotypes, and diplotypes, including allele information and
exemplary nucleotide sequences, is disclosed in Cargill et al., "A
large-scale genetic association study confirms IL12B and leads to
the identification of IL23R as psoriasis risk genes", Am J Hum
Genet. 2007 February; 80(2):273-90, which is incorporated herein by
reference.
[0114] IL13 Therapeutics/Pharmacogenomics in Inflammatory and
Autoimmune Disorders
[0115] Exemplary embodiments of the invention provide SNPs in IL13
that are associated with psoriasis (as shown in the tables). These
SNPs have a variety of therapeutic and pharmacogenomic uses related
to the treatment of psoriasis, as well as other inflammatory and
automimmune disorders such as Crohn's disease and bronchial
hyperresponsiveness/atopy/asthma. The psoriasis-associated SNPs
provided herein may be used, for example, to determine variability
between different individuals in their response to an inflammatory
or autoimmune disease therapy (e.g., a psoriasis therapy or a
therapy for Crohn's disease, bronchial
hyperresponsiveness/atopy/asthma, or other inflammatory or
autoimmune disorder) such as to predict whether an individual will
respond positively to a particular therapy, to determine the most
effective therapeutic agent (e.g., antibody, small molecule
compound, nucleic acid agent, etc.) to use to treat an individual,
to determine whether a particular therapeutic agent should or
should not be administered to an individual (e.g., by predicting
whether the individual is likely to positively respond to the
therapy or by predicting whether the individual will experience
toxic or other undesirable side effects or is unlikely to respond
to the therapy), or to determine the therapeutic regimen to use for
an individual such as the dosage or frequency of dosing of a
therapeutic agent for a particular individual. Therapeutic agents
that directly modulate IL13 may be used to treat psoriasis or other
inflammatory/autimmune disorders and, furthermore, therapeutic
agents that target proteins that interact with IL13 or are
otherwise in IL13 pathways may be used to indirectly modulate IL13
to thereby treat psoriasis or other inflammatory/autimmune
disorders. Any therapeutic agents such as these may be used in
conjunction with the SNPs provided herein.
[0116] For example, the IL13 psoriasis-associated SNPs provided
herein may be used to predict whether an individual will respond
positively to anti-IL13 antibody therapy and/or to determine the
most effective dosage of this therapy. This facilitates decision
making by medical practitioners, such as in deciding whether to
administer this therapy to a particular individual or select
another therapy that may be better suited to the individual, or to
use a particular dosage, dosing schedule, or to modify other
aspects of a therapeutic regimen to effectively treat the
individual, for example.
[0117] In addition to medical treatment, these uses may also be
applied, for example, in the context of clinical trials of a
therapeutic agent (e.g., a therapeutic agent that targets IL13 for
the treatment of psoriasis, Crohn's disease, bronchial
hyperresponsiveness/atopy/asthma, or other inflammatory or
autoimmune disorder), such as to include particular individuals in
a clinical trial who are predicted to positively respond to the
therapeutic agent based on the SNPs provided herein and/or to
exclude particular individuals from a clinical trial who are
predicted to not positively respond to the therapeutic agent based
on the SNPs provided herein. By using the SNPs provided herein to
target a therapeutic agent to individuals who are more likely to
positively respond to the agent, the therapeutic agent is more
likely to succeed in clinical trials by showing positive efficacy
and to therefore satisfy the FDA requirements for approval.
Additionally, individuals who are more likely to experience toxic
or other undesirable side effects may be excluded from being
administered the therapeutic agent. Furthermore, by using the SNPs
provided herein to determine an effective dosage or dosing
frequency, for example, the therapeutic agent may be less likely to
exhibit toxicity or other undesirable side effects, as well as more
likely to achieve positive efficacy.
Isolated Nucleic Acid Molecules and SNP Detection Reagents &
Kits
[0118] Tables 1 and 2 provide a variety of information about each
SNP of the present invention that is associated with psoriasis,
including the transcript sequences (SEQ ID NOS:1-2), genomic
sequences (SEQ ID NOS:10-18), and protein sequences (SEQ ID
NOS:3-4) 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:5-9) correspond to transcript-based
SNP context sequences disclosed in Table 1, and SEQ ID NOS:19-110
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.
[0119] Isolated Nucleic Acid Molecules
[0120] 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 as Applera or Celera proprietary. Isolated
nucleic acid molecules containing one or more SNPs disclosed in at
least one of Tables 1-2 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.
[0121] 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.
[0122] 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.
[0123] 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.
[0124] 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:1-2), and polymorphic genomic
sequences are provided in Table 2 and in the Sequence Listing (SEQ
ID NOS:10-18). 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.
[0125] 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:1-2, genomic
sequences are provided in Table 2 as SEQ ID NOS:10-18,
transcript-based SNP context sequences are provided in Table 1 as
SEQ ID NO:5-9, and genomic-based SNP context sequences are provided
in Table 2 as SEQ ID NO:19-110) 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.
[0126] 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.
[0127] 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.
[0128] 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.
[0129] 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).
[0130] 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.
[0131] 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:1-2, genomic sequences are provided in Table 2 as
SEQ ID NOS:10-18, transcript-based SNP context sequences are
provided in Table 1 as SEQ ID NO:5-9, and genomic-based SNP context
sequences are provided in Table 2 as SEQ ID NO:19-110), or any
nucleic acid molecule that encodes any of the variant proteins
provided in Table 1 (SEQ ID NOS:3-4). A nucleic acid molecule
consists of a nucleotide sequence when the nucleotide sequence is
the complete nucleotide sequence of the nucleic acid molecule.
[0132] 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:1-2, genomic sequences are
provided in Table 2 as SEQ ID NOS:10-18, transcript-based SNP
context sequences are provided in Table 1 as SEQ ID NO:5-9, and
genomic-based SNP context sequences are provided in Table 2 as SEQ
ID NO:19-110), or any nucleic acid molecule that encodes any of the
variant proteins provided in Table 1 (SEQ ID NOS:3-4). 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.
[0133] 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:1-2,
genomic sequences are provided in Table 2 as SEQ ID NOS:10-18,
transcript-based SNP context sequences are provided in Table 1 as
SEQ ID NO:5-9, and genomic-based SNP context sequences are provided
in Table 2 as SEQ ID NO:19-110), or any nucleic acid molecule that
encodes any of the variant proteins provided in Table 1 (SEQ ID
NOS:3-4). 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).
[0134] 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.
[0135] 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.
[0136] 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.
[0137] 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.
[0138] 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).
[0139] 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.
[0140] 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.
[0141] 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 amino acid 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.
[0142] 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.
[0143] 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.
[0144] 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.
[0145] 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.
[0146] SNP Detection Reagents
[0147] 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:1-2),
genomic sequences (provided in Table 2 as SEQ ID NOS:10-18), and
context sequences (transcript-based context sequences are provided
in Table 1 as SEQ ID NOS:5-9; genomic-based context sequences are
provided in Table 2 as SEQ ID NOS:19-110), 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:5-9; genomic-based context sequences are provided in Table 2
as SEQ ID NOS:19-110). 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.
[0148] 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.
[0149] 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.
[0150] Other preferred primer and probe sequences can readily be
determined using the transcript sequences (SEQ ID NOS:1-2), genomic
sequences (SEQ ID NOS:10-18), and SNP context sequences
(transcript-based context sequences are provided in Table 1 as SEQ
ID NOS:5-9; genomic-based context sequences are provided in Table 2
as SEQ ID NOS:19-110) 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.
[0151] 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.
[0152] 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").
[0153] 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.
[0154] 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
are 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.
[0155] 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.
[0156] 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.
[0157] 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 which 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.
[0158] 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.
[0159] 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.
[0160] 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.
[0161] 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.
[0162] 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.
[0163] 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).
[0164] 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.
[0165] 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 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.
[0166] SNP Detection Kits and Systems
[0167] 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 kits and systems,
including but not limited 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.
[0168] 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.
[0169] 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; 100; 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.
[0170] 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.
[0171] 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.
[0172] 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.
[0173] 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 6-60 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.
[0174] 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.
[0175] 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, 5994073,
5981768, 5871938, 5843681, 5800999, and 5773628 describe methods
and compositions of dioxetane for performing chemiluminescent
detection; and U.S. published application US2002/0110828 discloses
methods and compositions for microarray controls.
[0176] 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.
[0177] 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.
[0178] 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.
[0179] 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.TM. 6700 sample preparation system, and Roche
Molecular Systems' COBAS AmpliPrep System.
[0180] 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".
[0181] 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. Nos.
6,153,073, Dubrow et al., and 6,156,181, Parce et al.
[0182] 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.
[0183] Uses of Nucleic Acid Molecules
[0184] The nucleic acid molecules of the present invention have a
variety of uses, especially in the diagnosis and treatment of
psoriasis and related pathologies. 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.
[0185] 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).
[0186] 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.).
[0187] 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.
[0188] 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
at risk for psoriasis and related pathologies or has developed
early stage psoriasis. Detection of a SNP associated with a disease
phenotype provides a diagnostic tool for an active disease and/or
genetic predisposition to the disease.
[0189] 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.
[0190] 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.
[0191] 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.
[0192] 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.
[0193] 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.
[0194] 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.
[0195] 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.
[0196] 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.
[0197] 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.
[0198] 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.
[0199] SNP Genotyping Methods
[0200] 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 screening
for psoriasis or related pathologies, or determining predisposition
thereto, or determining responsiveness to a form of treatment, or
in genome mapping or SNP association analysis, etc.
[0201] 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.
[0202] 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.
[0203] 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.
[0204] 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.
[0205] 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 programs, 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
diagnostic assays for psoriasis and related pathologies, and 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).
[0206] 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.
[0207] 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, 5494810, 5830711, and 6054564
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 Ser. No. 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. applications 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.
[0208] 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.
[0209] 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.
[0210] 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.
[0211] 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 Mass ARRAY 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.
[0212] 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 3730.times.1 DNA Analyzers
(Foster City, Calif.), is commonly used in the art for automated
sequencing.
[0213] 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).
[0214] 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
[0215] 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.
[0216] 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.
[0217] Analysis of Genetic Association Between SNPs and Phenotypic
Traits
[0218] 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.
[0219] 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.
[0220] 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.
[0221] 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.
[0222] 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)).
[0223] 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%.
[0224] 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.
[0225] 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.
[0226] 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.
[0227] 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<0.2 (a significance level on the
lenient side), for example, 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.
[0228] 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.
[0229] 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.
[0230] 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 be used 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).
[0231] 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).
[0232] Once individual risk factors, genetic or non-genetic, have
been found for the 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)).
[0233] Disease Diagnosis and Predisposition Screening
[0234] 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).
[0235] The SNPs of the invention may contribute to psoriasis and
related pathologies in an individual 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.
[0236] As used herein, the terms "diagnose", "diagnosis", and
"diagnostics" include, but are not limited to any of the following:
detection of psoriasis that an individual may presently have,
predisposition/susceptibility screening (i.e., determining the
increased risk of an individual in developing psoriasis in the
future, or determining whether an individual has a decreased risk
of developing psoriasis in the future, determining a particular
type or subclass of psoriasis in an individual known to have
psoriasis, confirming or reinforcing a previously made diagnosis of
psoriasis, 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, 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 psoriasis. Such diagnostic uses are based on the
SNPs individually or in a unique combination or SNP haplotypes of
the present invention.
[0237] 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.
[0238] 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 SNP 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.
[0239] 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.
[0240] For diagnostic purposes and similar uses, if a particular
SNP site is found to be useful for diagnosing psoriasis and related
pathologies (e.g., has a significant statistical association with
the condition and/or is recognized as a causative polymorphism for
the condition), then the skilled artisan would recognize that other
SNP sites which are in LD with this SNP site would also be useful
for diagnosing the condition. 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.,
psoriasis) 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.
[0241] 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
1-4, for example.
[0242] Linkage disequilibrium in the human genome is reviewed in
the following references: Wall et al. et al., "Haplotype blocks and
linkage disequilibrium in the human genome,", Nat Rev Genet. 2003
August; 4(8):587-97 (August 2003); Garner et al. et al., "On
selecting markers for association studies: patterns of linkage
disequilibrium between two and three diallelic loci,", Genet
Epidemiol. 2003 January; 24(1):57-67 (January 2003); Ardlie et al.
et al., "Patterns of linkage disequilibrium in the human genome,",
Nat Rev Genet. 2002 April; 3(4):299-309 (April 2002); (erratum in
Nat Rev Genet. 2002 July; 3(7):566 (July 2002); and Remm et al. 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 (February 2002); J. B. S. Haldane,
"JBS (1919) The combination of linkage values, and the calculation
of distances between the loci of linked factors,". J Genet.
8:299-309 (1919); G. Mendel, G. (1866) Versuche uber
Pflanzen-Hybriden. Verhandlungen des naturforschenden Vereines in
Brunn [(Proceedings of the Natural History Society of Brunn)]
(1866); Lewin B (1990) Genes IV, B. Lewin, ed., Oxford University
Press, New York, USA (1990); D. L. Hartl D L and A. G. Clark A G
(1989) Principles of Population Genetics 2.sup.nd ed., Sinauer
Associates, Inc., Ma Sunderland, Mass., USA (1989); J. H. Gillespie
J H (2004) Population Genetics: A Concise Guide.2.sup.nd ed., Johns
Hopkins University Press. (2004) USA; R. C. Lewontin, "RC (1964)
The interaction of selection and linkage. I. General
considerations; heterotic models,". Genetics 49:49-67 (1964); P. G.
Hoel, P G (1954) Introduction to Mathematical Statistics 2.sup.nd
ed., John Wiley & Sons, Inc., N.Y. New York, USA (1954); R. R.
Hudson, R R "(2001) Two-locus sampling distributions and their
application,". Genetics 159:1805-1817 (2001); A. P. Dempster A P,
N. M. Laird, D. B. NM, Rubin, "DB (1977) Maximum likelihood from
incomplete data via the EM algorithm,". J R Stat Soc 39:1-48
(1977); L. Excoffier L, M. Slatkin, M "(1995) Maximum-likelihood
estimation of molecular haplotype frequencies in a diploid
population,". Mol Biol Evol 12(5):921-927 (1995); D. A. Tregouet D
A, S. Escolano S, L. Tiret L, A. Mallet A, J. L. Golmard, J L
"(2004) A new algorithm for haplotype-based association analysis:
the Stochastic-EM algorithm,". Ann Hum Genet. 68(Pt 2):165-177
(2004); A. D. Long A D and C. H. Langley C H, "(1999) The power of
association studies to detect the contribution of candidate genetic
loci to variation in complex traits,". Genome Research 9:720-731
(1999); A. Agresti, A (1990) Categorical Data Analysis, John Wiley
& Sons, Inc., N.Y. New York, USA (1990); K. Lange, K (1997)
Mathematical and Statistical Methods for Genetic Analysis.
Springer-Verlag New York, Inc., N.Y. New York, USA (1997); The
International HapMap Consortium, "(2003) The International HapMap
Project,". Nature 426:789-796 (2003); The International HapMap
Consortium, "(2005) A haplotype map of the human genome,". Nature
437:1299-1320 (2005); G. A. Thorisson G A, A. V. Smith A V, L.
Krishnan L, L. D. Stein L D (2005), "The International HapMap
Project Web Site,". Genome Research 15:1591-1593 (2005); G. McVean,
C. C. A. G, Spencer C C A, R. Chaix R (2005), "Perspectives on
human genetic variation from the HapMap project,". PLoS Genetics
1(4):413-418 (2005); J. N. Hirschhorn J N, M. J. Daly, M J "(2005)
Genome-wide association studies for common diseases and complex
traits,". Nat Genet. 6:95-108 (2005); S. J. Schrodi, "SJ (2005) A
probabilistic approach to large-scale association scans: a
semi-Bayesian method to detect disease-predisposing alleles,".
SAGMB 4(1):31 (2005); W. Y. S. Wang W Y S, B. J. Barratt B J, D. G.
Clayton D G, J. A. Todd, "J A (2005) Genome-wide association
studies: theoretical and practical concerns,". Nat Rev Genet.
6:109-118 (2005); J. K. Pritchard J K, M. Przeworski, "M (2001)
Linkage disequilibrium in humans: models and data,". Am J Hum
Genet. 69:1-14 (2001).
[0243] As discussed above, one aspect of the present invention is
the discovery that SNPs which are in certain LD distance with the
interrogated SNP can also be used as valid markers for identifying
an increased or decreased risks of having or developing psoriasis.
As used herein, the term "interrogated SNP" refers to SNPs that
have been found to be associated with an increased or decreased
risk of disease using genotyping results and analysis, or other
appropriate experimental method as exemplified in the working
examples described in this application. As used herein, the term
"LD SNP" refers to a SNP that has been characterized as a SNP
associating with an increased or decreased risk of diseases due to
their being in LD with the "interrogated SNP" under the methods of
calculation described in the application. Below, applicants
describe the methods of calculation with which one of ordinary
skilled in the art may determine if a particular SNP is in LD with
an interrogated SNP. The parameter r.sup.2 is commonly used in the
genetics art to characterize the extent of linkage disequilibrium
between markers (Hudson, 2001). As used herein, the term "in LD
with" refers to a particular SNP that is measured at above the
threshold of a parameter such as r.sup.2 with an interrogated
SNP.
[0244] It is now common place to directly observe genetic variants
in a sample of chromosomes obtained from a population. Suppose one
has genotype data at two genetic markers located on the same
chromosome, for the markers A and B. Further suppose that two
alleles segregate at each of these two markers such that alleles
A.sub.1 and A.sub.2 can be found at marker A and alleles B.sub.1
and B.sub.2 at marker B. Also assume that these two markers are on
a human autosome. If one is to examine a specific individual and
find that they are heterozygous at both markers, such that their
two-marker genotype is A.sub.1A.sub.2B.sub.1B.sub.2, then there are
two possible configurations: the individual in question could have
the alleles A.sub.1B.sub.1 on one chromosome and A.sub.2B.sub.2 on
the remaining chromosome; alternatively, the individual could have
alleles A.sub.1B.sub.2 on one chromosome and A.sub.2B.sub.1 on the
other. The arrangement of alleles on a chromosome is called a
haplotype. In this illustration, the individual could have
haplotypes A.sub.1B.sub.1/A.sub.2B.sub.2 or
A.sub.1B.sub.2/A.sub.2B.sub.1 (see Hartl and Clark (1989) for a
more complete description). The concept of linkage equilibrium
relates the frequency of haplotypes to the allele frequencies.
[0245] Assume that a sample of individuals is selected from a
larger population. Considering the two markers described above,
each having two alleles, there are four possible haplotypes:
A.sub.1B.sub.1, A.sub.1B.sub.2, A.sub.2B.sub.1 and A.sub.2B.sub.2.
Denote the frequencies of these four haplotypes with the following
notation.
P.sub.11=freq(A.sub.1B.sub.1) (1)
P.sub.12=freq(A.sub.1B.sub.2) (2)
P.sub.21=freq(A.sub.2B.sub.1) (3)
P.sub.22=freq(A.sub.2B.sub.2) (4)
The allele frequencies at the two markers are then the sum of
different haplotype frequencies, it is straightforward to write
down a similar set of equations relating single-marker allele
frequencies to two-marker haplotype frequencies:
P.sub.1=freq(A.sub.1)=P.sub.11+P.sub.12 (5)
P.sub.2=freq(A.sub.2)=P.sub.21+P.sub.22 (6)
q.sub.1=freq(B.sub.1)=P.sub.11+P.sub.21 (7)
q.sub.2=freq(B.sub.2)=P.sub.12+P.sub.22 (8)
Note that the four haplotype frequencies and the allele frequencies
at each marker must sum to a frequency of 1.
P.sub.11+P.sub.12+P.sub.21+P.sub.22=1 (9)
p.sub.1+p.sub.2=1 (10)
q.sub.1+q.sub.2=1 (11)
If there is no correlation between the alleles at the two markers,
one would expect that the frequency of the haplotypes would be
approximately the product of the composite alleles. Therefore,
P.sub.11.apprxeq.p.sub.1q.sub.1 (12)
P.sub.12.apprxeq.p.sub.1q.sub.2 (13)
P.sub.21.apprxeq.p.sub.2q.sub.1 (14)
P.sub.22.apprxeq.p.sub.2q.sub.2 (15)
These approximating equations (12)-(15) represent the concept of
linkage equilibrium where there is independent assortment between
the two markers--the alleles at the two markers occur together at
random. These are represented as approximations because linkage
equilibrium and linkage disequilibrium are concepts typically
thought of as properties of a sample of chromosomes; and as such
they are susceptible to stochastic fluctuations due to the sampling
process. Empirically, many pairs of genetic markers will be in
linkage equilibrium, but certainly not all pairs.
[0246] Having established the concept of linkage equilibrium above,
applicants can now describe the concept of linkage disequilibrium
(LD), which is the deviation from linkage equilibrium. Since the
frequency of the A.sub.1 B.sub.1 haplotype is approximately the
product of the allele frequencies for A.sub.1 and B.sub.1 under the
assumption of linkage equilibrium as stated mathematically in (12),
a simple measure for the amount of departure from linkage
equilibrium is the difference in these two quantities, D,
D=P.sub.11-p.sub.1q.sub.1 (16)
D=0 indicates perfect linkage equilibrium. Substantial departures
from D=0 indicates LD in the sample of chromosomes examined. Many
properties of D are discussed in Lewontin (1964) including the
maximum and minimum values that D can take. Mathematically, using
basic algebra, it can be shown that D can also be written solely in
terms of haplotypes:
D=P.sub.11P.sub.22-P.sub.12P.sub.21 (17)
If one transforms D by squaring it and subsequently dividing by the
product of the allele frequencies of A.sub.1, A.sub.2, B.sub.1 and
B.sub.2, the resulting quantity, called r.sup.2, is equivalent to
the square of the Pearson's correlation coefficient commonly used
in statistics (e.g. Hoel, 1954).
r 2 = D 2 p 1 p 2 q 1 q 2 ( 18 ) ##EQU00001##
[0247] As with D, values of r.sup.2 close to 0 indicate linkage
equilibrium between the two markers examined in the sample set. As
values of r.sup.2 increase, the two markers are said to be in
linkage disequilibrium. The range of values that r.sup.2 can take
are from 0 to 1. r.sup.2=1 when there is a perfect correlation
between the alleles at the two markers.
[0248] In addition, the quantities discussed above are
sample-specific. And as such, it is necessary to formulate notation
specific to the samples studied. In the approach discussed here,
three types of samples are of primary interest: (i) a sample of
chromosomes from individuals affected by a disease-related
phenotype (cases), (ii) a sample of chromosomes obtained from
individuals not affected by the disease-related phenotype
(controls), and (iii) a standard sample set used for the
construction of haplotypes and calculation pairwise linkage
disequilibrium. For the allele frequencies used in the development
of the method described below, an additional subscript will be
added to denote either the case or control sample sets.
P.sub.1,cs=freq(A.sub.1 in cases) (19)
P.sub.2,cs=freq(A.sub.2 in cases) (20)
q.sub.1,cs=freq(B.sub.1 in cases) (21)
q.sub.2,cs=freq(B.sub.2 in cases) (22)
Similarly,
p.sub.1,ct=freq(A.sub.1 in controls) (23)
P.sub.2,ct=freq(A.sub.2 in controls) (24)
q.sub.1,ct=freq(B.sub.1 in controls) (25)
q.sub.2,ct=freq(B.sub.2 in controls) (26)
[0249] As a well-accepted sample set is necessary for robust
linkage disequilibrium calculations, data obtained from the
International HapMap project (The International HapMap Consortium
2003, 2005; Thorisson et al, 2005; McVean et al, 2005) can be used
for the calculation of pairwise r.sup.2 values. Indeed, the samples
genotyped for the International HapMap Project were selected to be
representative examples from various human sub-populations with
sufficient numbers of chromosomes examined to draw meaningful and
robust conclusions from the patterns of genetic variation observed.
The International HapMap project website (hapmap.org) contains a
description of the project, methods utilized and samples examined.
It is useful to examine empirical data to get a sense of the
patterns present in such data.
[0250] Haplotype frequencies were explicit arguments in equation
(18) above. However, knowing the 2-marker haplotype frequencies
requires that phase to be determined for doubly heterozygous
samples. When phase is unknown in the data examined, various
algorithms can be used to infer phase from the genotype data. This
issue was discussed earlier where the doubly heterozygous
individual with a 2-SNP genotype of A.sub.1A.sub.2B.sub.1B.sub.2
could have one of two different sets of chromosomes:
A.sub.1/B.sub.1/A.sub.2B.sub.2 or A.sub.1B.sub.2/A.sub.2B.sub.1.
One such algorithm to estimate haplotype frequencies is the
expectation-maximization (EM) algorithm first formalized by
Dempster et al et al. (1977). This algorithm is often used in
genetics to infer haplotype frequencies from genotype data (e.g.
e.g. Excoffier and Slatkin (1995); Tregouet et al et al., (2004)).
It should be noted that for the two-SNP case explored here, EM
algorithms have very little error provided that the allele
frequencies and sample sizes are not too small. The impact on
r.sup.2 values is typically negligible.
[0251] As correlated genetic markers share information,
interrogation of SNP markers in LD with a disease-associated SNP
marker can also have sufficient power to detect disease association
(Long and Langley (1999)). The relationship between the power to
directly find disease-associated alleles and the power to
indirectly detect disease-association was investigated by Pritchard
and Przeworski (2001). In a straight-forward derivation, it can be
shown that the power to detect disease association indirectly at a
marker locus in linkage disequilibrium with a disease-association
locus is approximately the same as the power to detect
disease-association directly at the disease-association locus if
the sample size is increased by a factor of
1 r 2 ##EQU00002##
(the reciprocal of equation 18) at the marker in comparison with
the disease-association locus.
[0252] Therefore, if one calculated the power to detect
disease-association indirectly with an experiment having N samples,
then equivalent power to directly detect disease-association (at
the actual disease-susceptibility locus) would necessitate an
experiment using approximately r.sup.2 N samples. This elementary
relationship between power, sample size and linkage disequilibrium
can be used to derive an r.sup.2 threshold value useful in
determining whether or not genotyping markers in linkage
disequilibrium with a SNP marker directly associated with disease
status has enough power to indirectly detect
disease-association.
[0253] To commence a derivation of the power to detect
disease-associated markers through an indirect process, define the
effective chromosomal sample size as
n = 4 N cs N ct N cs + N ct ; ( 27 ) ##EQU00003##
where N.sub.cs and N.sub.ct are the numbers of diploid cases and
controls, respectively. This is necessary to handle situations
where the numbers of cases and controls are not equivalent. For
equal case and control sample sizes, N.sub.cs=N.sub.ct=N, the value
of the effective number of chromosomes is simply n=2N-as expected.
Let power be calculated for a significance level a (such that
traditional P-values below .alpha. will be deemed statistically
significant). Define the standard Gaussian distribution function as
.PHI.(.cndot.). Mathematically,
.PHI. ( x ) = 1 2 .pi. .intg. - .infin. x - .theta. 2 2 .theta. (
28 ) ##EQU00004##
Alternatively, the following error function notation (Erf) may also
be used,
.PHI. ( x ) = 1 2 [ 1 + Erf ( x 2 ) ] ( 29 ) ##EQU00005##
[0254] For example, .PHI.(1.644854)=0.95. The value of r.sup.2 may
be derived to yield a pre-specified minimum amount of power to
detect disease association though indirect interrogation. Noting
that the LD SNP marker could be the one that is carrying the
disease-association allele, therefore that this approach
constitutes a lower-bound model where all indirect power results
are expected to be at least as large as those interrogated.
[0255] Denote by .beta. the error rate for not detecting truly
disease-associated markers. Therefore, 1-.beta. is the classical
definition of statistical power. Substituting the
Pritchard-Pzreworski result into the sample size, the power to
detect disease association at a significance level of .alpha. is
given by the approximation
1 - .beta. .apprxeq. .PHI. [ q 1 , cs - q 1 , ct q 1 , cs ( 1 - q 1
, cs ) + q 1 , ct ( 1 - q 1 , ct ) r 2 n - Z 1 - .alpha. / 2 ] ; (
30 ) ##EQU00006##
where Z.sub.u is the inverse of the standard normal cumulative
distribution evaluated at u (u.epsilon.(0,1)).
Z.sub.u=.PHI..sup.-1(u), where
.PHI.(.PHI..sup.-1(u))=.PHI..sup.-1(.PHI.(u))=u. For example,
setting a=0.05, and therefore 1-.alpha./2=0.975,
Z.sub.0.975=1.95996 is obtained. Next, setting power equal to a
threshold of a minimum power of T,
T = .PHI. [ q 1 , cs - q 1 , ct q 1 , cs ( 1 - q 1 , cs ) + q 1 ,
ct ( 1 - q 1 , ct ) r 2 n - Z 1 - .alpha. / 2 ] ( 31 )
##EQU00007##
and solving for r.sup.2, the following threshold r.sup.2 is
obtained:
r T 2 = [ q 1 , cs ( 1 - q 1 , cs ) + q 1 , ct ( 1 - q 1 , ct ) ] n
( q 1 , cs - q 1 , ct ) 2 [ .PHI. - 1 ( T ) + Z 1 - .alpha. / 2 ] 2
Or , ( 32 ) r T 2 = ( Z T + Z 1 - .alpha. / 2 ) 2 n [ q 1 , cs - (
q 1 , cs ) 2 + q 1 , ct - ( q 1 , ct ) 2 ( q 1 , cs - q 1 , ct ) 2
] ( 33 ) ##EQU00008##
[0256] Suppose that r.sup.2 is calculated between an interrogated
SNP and a number of other SNPs with varying levels of LD with the
interrogated SNP. The threshold value r.sub.T.sup.2 is the minimum
value of linkage disequilibrium between the interrogated SNP and
the potential LD SNPs such that the LD SNP still retains a power
greater or equal to T for detecting disease-association. For
example, suppose that SNP rs200 is genotyped in a case-control
disease-association study and it is found to be associated with a
disease phenotype. Further suppose that the minor allele frequency
in 1,000 case chromosomes was found to be 16% in contrast with a
minor allele frequency of 10% in 1,000 control chromosomes. Given
those measurements one could have predicted, prior to the
experiment, that the power to detect disease association at a
significance level of 0.05 was quite high--approximately 98% using
a test of allelic association. Applying equation (32) one can
calculate a minimum value of r.sup.2 to indirectly assess disease
association assuming that the minor allele at SNP rs200 is truly
disease-predisposing for a threshold level of power. If one sets
the threshold level of power to be 80%, then r.sub.T.sup.2=0.489
given the same significance level and chromosome numbers as above.
Hence, any SNP with a pairwise r.sup.2 value with rs200 greater
than 0.489 is expected to have greater than 80% power to detect the
disease association. Further, this is assuming the conservative
model where the LD SNP is disease-associated only through linkage
disequilibrium with the interrogated SNP rs200.
[0257] The contribution or association of particular SNPs and/or
SNP haplotypes with disease phenotypes, such as psoriasis, 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 psoriasis, 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 psoriasis might indicate a probability of 20% that
an individual has or is at risk of developing psoriasis, whereas
detection of five SNPs, each of which correlates with psoriasis,
might indicate a probability of 80% that an individual has or is at
risk of developing psoriasis. 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 of psoriasis, such as disease symptoms,
pathological characteristics, family history, diet, environmental
factors or lifestyle factors.
[0258] It will, of course, be understood by practitioners skilled
in the treatment or diagnosis of psoriasis that the present
invention generally does not intend to provide an absolute
identification of individuals who are at risk (or less at risk) of
developing psoriasis, and/or pathologies related to psoriasis, but
rather to indicate a certain increased (or decreased) degree or
likelihood of developing the disease based on statistically
significant association results. However, this information is
extremely valuable as it can be used to, for example, 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, or to have regularly scheduled
physical exams to monitor for appearance of a condition in order to
identify and begin treatment of the condition at an early stage.
Particularly with diseases that are extremely debilitating or fatal
if not treated on time, the knowledge of a potential
predisposition, even if this predisposition is not absolute, would
likely contribute in a very significant manner to treatment
efficacy.
[0259] 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
pathologies and disorders related to psoriasis.
[0260] 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 as a result of possessing a particular trait-causing or
trait-influencing allele.
[0261] 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.
[0262] Pharmacogenomics and Therapeutics/Drug Development
[0263] The present invention provides methods for assessing the
pharmacogenomics of a subject harboring particular SNP alleles or
haplotypes or diplotypes 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.
[0264] 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.
[0265] 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.
[0266] Pharmacogenomic uses of the SNPs of the present invention
provide several significant advantages for patient care,
particularly in treating psoriasis. 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.
[0267] Attempts have been made to develop drugs that can be used to
treat psoriasis. Several drug candidates have been introduced into
clinical trials to test their efficacy in treating psoriasis. Among
them are ABT-874, STA-5326, and CNTO-1275. For references
discussing these drugs, please see Burakoff, et al., A phase 1/2A
trial of STA 5326, an oral interleukin-12/23 inhibitor, in patients
with active moderate to severe Crohn's disease. Inflamm Bowel Dis.
2006 July; 12(7):558-65, and Borchardt J K, Focus on small molecule
inhibitors for treatment of inflammatory and autoimmune diseases.
Drug News Perspect. 2004 November; 17(9):607-14 (for STA-5326);
Sandborn W J, How future tumor necrosis factor antagonists and
other compounds will meet the remaining challenges in Crohn's
disease. Rev Gastroenterol Disord. 2004; 4 Suppl 3:S25-33 (for
ABT-874); Papp K A. Potential future therapies for psoriasis. Semin
Cutan Med. Surg. 2005 March; 24(1):58-63 (for CNTO-1275). These
drug candidates target the metabolic pathway involving IL-12 and
IL-23 genes.
[0268] It is also well known in the art that markers that are
diagnostically useful in distinguishing patients at higher risk of
developing a disease, such as psoriasis from those who are at a
decreased risk of developing psoriasis can be useful in identifying
those patients that are more likely to respond to drug treatments
targeting at those pathways involving genes where the diagnostic
SNPs reside. See references Gerdes, et al., Circulation, 2000;
101:1366-1371, Kuivenhoven, et al., N Engl J Med 1998; 338:86-93,
Stolarz, et al., Hypertension 2004; 44:156-162, Chartier-Harlin, et
al., Hum. Mol. Genet. 1994 April; 3(4):569-74, Roses, et al., The
Pharmacogenomics Journal 2006, 1-19.
[0269] In that regard, embodiments of the present invention can be
very useful in assisting clinicians select patients who are more
likely to develop psoriasis, and are in turn good candidates for
drug responses targeting psoriasis, thus warrant the application of
the above-mentioned drug treatments on such patients. In the mean
time, patients who are deemed to have low risk of developing
psoriasis, using SNP markers discovered herein, can be spared of
the aggravation and wastefulness of the drug due to the reduced
benefit of such treatment in view of its cost and side effect.
[0270] 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, Mukherjee 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.
[0271] The SNPs of the present invention also can be used to
identify novel therapeutic targets for psoriasis. 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.
[0272] 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).
[0273] Antisense technology is further reviewed in: Layery 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; 75:621-46; 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.
[0274] 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).
[0275] 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 psoriasis, 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.
[0276] 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).
[0277] 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; Layery 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):1040-1046;
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).
[0278] A subject suffering from a pathological condition, such as
psoriasis, 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.
[0279] 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.
[0280] The invention further provides a method for identifying a
compound or agent that can be used to treat psoriasis. 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.
[0281] Variant gene expression in a psoriasis patient 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).
[0282] 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.
[0283] 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 psoriasis 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.
[0284] 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.
[0285] 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.
[0286] 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.
[0287] 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.
[0288] 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 indicate
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 psoriasis patient population that can
benefit from it.
[0289] 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).
[0290] 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.
[0291] 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).
[0292] 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.
[0293] 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.
[0294] Pharmaceutical Compositions and Administration Thereof
[0295] Any of the psoriasis-associated proteins, and encoding
nucleic acid molecules, disclosed herein can be used as therapeutic
targets (or directly used themselves as therapeutic compounds) for
treating psoriasis 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.
[0296] 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.
[0297] 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.
[0298] 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.
[0299] 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.
[0300] 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.
[0301] Solid pharmaceutical excipients include starch, cellulose,
talc, glucose, lactose, sucrose, gelatin, malt, rice, flour, chalk,
silica gel, magnesium stearate, sodium stearate, 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.
[0302] 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.
[0303] Other suitable pharmaceutical excipients and their
formulations are described in Remington's Pharmaceutical Sciences,
edited by E. W. Martin (Mack Publishing Company, 18.sup.th ed.,
1990).
[0304] 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 %.
[0305] 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 psoriasis-associated protein can be administered
in combination with another agent that inhibits or stimulates the
activity of the same or a different psoriasis-associated protein to
thereby counteract the affects of psoriasis.
[0306] For further information regarding pharmacology, see Current
Protocols in Pharmacology, John Wiley & Sons, Inc., N.Y.
[0307] Human Identification Applications
[0308] In addition to their diagnostic and therapeutic uses in
psoriasis and related pathologies, 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.
[0309] 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.
[0310] 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.
[0311] 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.
[0312] 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.
[0313] 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.
[0314] 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.
[0315] 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.
[0316] 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").
[0317] 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.
[0318] 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.
[0319] 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).
[0320] 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.
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.
Variant Proteins, Antibodies, Vectors & Host Cells, & Uses
Thereof
[0321] Variant Proteins Encoded by SNP-Containing Nucleic Acid
Molecules 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:3-4 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.
[0322] 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.
[0323] 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.
[0324] 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.
[0325] 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.
[0326] 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.).
[0327] 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.
[0328] 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.
[0329] 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.
[0330] 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 acid
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.
[0331] 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.
[0332] 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.
[0333] 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.
[0334] 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.
[0335] 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.
[0336] 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.
[0337] 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).
[0338] 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.
[0339] 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)).
[0340] 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.
[0341] 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.
[0342] 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 (1990); and Rattan et al., Ann. N.Y. Acad.
Sci. 663:48-62 (1992).
[0343] 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 or 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.
[0344] 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)).
[0345] Uses of Variant Proteins
[0346] 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).
[0347] 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:3-4. 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.
[0348] In another specific aspect of the invention, the variant
proteins of the present invention are used as targets for
diagnosing psoriasis or for determining predisposition to psoriasis
in a human. 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.
[0349] 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.
[0350] In vitro methods for detection of the variant proteins
associated with psoriasis 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.
[0351] 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.
[0352] 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.
[0353] 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.
[0354] 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.
[0355] 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).
[0356] 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.
[0357] 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.
[0358] 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.
[0359] 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).
[0360] 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 competes for ligand, for
example with a higher affinity, or a fragment that binds ligand but
does not allow release, is encompassed by the invention.
[0361] 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.
[0362] 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.
[0363] 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, September 10(9), 973-80).
[0364] 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.125I 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.
[0365] 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.
[0366] 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 psoriasis.
These methods of treatment typically include the steps of
administering the modulators of protein activity in a
pharmaceutical composition to a subject in need of such
treatment.
[0367] 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.
[0368] 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.
[0369] 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.
[0370] Antibodies Directed to Variant Proteins
[0371] 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).
[0372] 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.
[0373] 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. 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.
[0374] 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).
[0375] 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.
[0376] 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.
[0377] 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.
[0378] Uses of Antibodies
[0379] 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 psoriasis. Additionally, antibody
detection of circulating fragments of the full-length variant
protein can be used to identify turnover.
[0380] 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.
[0381] 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, particularly psoriasis.
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 screen for predisposition to psoriasis as indicated by the
presence of the variant protein.
[0382] 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.
[0383] 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.
[0384] 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.
[0385] 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).
[0386] 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.
[0387] Vectors and Host Cells
[0388] 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.
[0389] 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.
[0390] 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).
[0391] 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.
[0392] 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 .lamda., 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.
[0393] 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.
[0394] 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.).
[0395] 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, N.Y.
[0396] 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.
[0397] 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.
[0398] 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.
[0399] 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 67:31-40 (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 69:301-415 (1988)) and pET
11d (Studier et al., Gene Expression Technology: Methods in
Enzymology 185:60-89 (1990)).
[0400] 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)).
[0401] 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.).
[0402] 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., Sf 9 cells) include the
pAc series (Smith et al., Mol. Cell. Biol. 3:2156-2165 (1983)) and
the pVL series (Lucklow et al., Virology 170:31-49 (1989)).
[0403] 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)).
[0404] 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).
[0405] 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.
[0406] 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.).
[0407] 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.
[0408] 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.
[0409] 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.
[0410] 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.
[0411] 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.
[0412] 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.
[0413] 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.
[0414] For further information regarding vectors and host cells,
see Current Protocols in Molecular Biology, John Wiley & Sons,
N.Y.
[0415] Uses of Vectors and Host Cells, and Transgenic Animals
[0416] 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.
[0417] 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.
[0418] 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.
[0419] 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.
[0420] 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.
[0421] 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.
[0422] 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.
[0423] 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 G.sub.o
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.
[0424] 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).
[0425] 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.
EXAMPLES
[0426] The following examples are offered to illustrate, but not to
limit, the claimed invention.
Example One
Statistical Analysis of SNPs Associated with Psoriasis
[0427] Overview
[0428] A multi-tiered genetic association study of 25,215 SNPs in
three case-control sample sets (1,446 patients and 1,432 controls)
identified three IL13-linked SNPs (rs1800925, rs20541, rs848)
associated with psoriasis. These SNPs had psoriasis susceptibility
effects (joint allelic ORs: 0.76.fwdarw.0.78; P.sub.comb:
1.3E-03.fwdarw.2.50E-04), and the association patterns were
consistent across the sample sets, with the minor alleles being
protective. Haplotype analyses identified one common, susceptible
haplotype CCG (joint allelic OR=1.27; P.sub.comb=1.88E-04) and a
less common, protective haplotype TTT (joint allelic OR=0.74;
P.sub.comb=7.05E-04). In combination with the other known genetic
risk factors, HLA-C, IL12B and IL23R, the variants reported here
generate an 11-fold psoriasis-risk differential. Residing in the
5q31 cytokine gene cluster, IL13 encodes an important T-cell
derived cytokine that regulates cell-mediated immunity.
[0429] Results and Discussion
[0430] Three SNPs within 4 kb of one another in the IL13-region in
5q31 met our significance criteria in the pooled-genotyping phase
of our study: rs1800925 (located 1 kb 5' of the IL13 coding
region), rs20541 (an IL13 exon 4 missense SNP, Q144R), and rs848
(located within the 3' UTR region of IL13).
[0431] Individual genotyping of these three markers in all three
sample sets showed each of the markers was consistent with
Hardy-Weinberg equilibrium in both cases and controls of each
sample set (Table 5). Minor allele frequencies for all three SNPs
were nearly the same: approximately 18-20% in controls and
decreasing to 14-17% in cases. For all three SNPs, combining
P-values across the three sample sets using Fisher's combined
probability method generated significant values for both allelic
and genotypic tests (allelic: P.sub.rs1800925=2.50E-04,
P.sub.rs20541=0.0013, P.sub.rs848=0.0017; genotypic
P.sub.rs1800925=0.0029, P.sub.rs20541=0.0022, P.sub.rs848=0.0027).
Notably, the 5' SNP, rs1800925, and the 3' UTR SNP, rs848, were
significant (P.sub.allelic<0.05) in all three sample sets.
[0432] Pairwise LD values between these three associated SNPs were
calculated, using the r.sup.2 measure applied to all individuals in
sample set 1. Two of the SNPs, rs20541 and rs848, were in very high
LD (r.sup.2=0.98). The remaining SNP, rs1800925 was not as highly
correlated with the other two SNPs (r.sup.2=0.24 for both
comparisons).
[0433] Haplotype analyses can often reveal important cis-acting
effects among alleles at closely-linked sites. We used the program
Haplo.Stats (Schaid D J, Rowland C M, Tines D E, Jacobson R M,
Poland G A. Score tests for association between traits and
haplotypes when linkage phase is ambiguous. Am J Hum Genet. 2002;
70: 425-434) to estimate haplotypes for these three SNPs and to
perform a test of psoriasis association. This program calculates
P-values for each haplotype and also a global P-value. Results for
the three SNPs (rs1800925, rs20541 and rs848) showed four common
haplotypes in each sample set (as expected from the LD patterns),
but only the CCG haplotype (carrying the major allele at each site)
was significant in all three studies (SS1 P=0.0288, SS2 P=0.0177,
and SS3 P=0.0037) (Table 6). A combined analysis showed association
for this haplotype (P.sub.comb=1.84E-04) and also revealed a second
associated haplotype, TTT (P.sub.comb=7.05E-04) which carries the
minor allele at each site and exhibited protective effects.
Overall, the susceptible haplotype, CCG, had a frequency of 72.1%
in controls increasing to 76.5% in cases while the protective
haplotype, TTT, had a frequency of 11.5% in controls decreasing to
8.8% in cases. The risk CCG haplotype had a joint OR=1.27 and the
protective haplotype had a joint OR=0.74.
[0434] IL-13 is an immuno-regulatory cytokine produced primarily by
activated Th2 cells that exerts its effect by binding to its
receptor and activating the STATE-mediated signal transduction
pathway. IL-13 has been most prominently implicated as a critical
mediator of an allergic inflammatory response, and genetic variants
of IL13 are known to be associated with susceptibility to asthma in
humans (Heinzmann A, Mao X Q, Akaiwa M, Kreomer R T, Gao P S,
Ohshima K et al. Genetic variants of IL-13 signalling and human
asthma and atopy. Hum Mol Genet. 2000; 9: 549-559). Genetic
variation in IL13 has also been associated with the risk of atopic
dermatitis in a Japanese study (Tsunemi Y, Saeki H, Nakamura K,
Sekiya T, Hirai K, Kakinuma T et al. Interleukin-13 gene
polymorphism G4257A is associated with atopic dermatitis in
Japanese patients. J Dermatol Sci 2002; 30: 100-107) and although
there has been no prior report for a role of IL-13 in psoriasis,
altered expression of the two IL-13 receptor chains, IL4-Roc and
IL-13.alpha.1, has been observed in the skin of psoriasis patients
(Cancino-Diaz J C, Reyes-Maldonado E, Banuelos-Panuco C A,
Jimenez-Zamudio L, Garcia-Latorre E, Leon-Dorantes G et al.
Interleukin-13 receptor in psoriatic keratinocytes: overexpression
of the mRNA and underexpression of the protein. J Invest Dermatol
2002; 119: 1114-1120). Thus IL13 represents a reasonable biological
candidate gene for the development of psoriasis.
[0435] However, as the initial single marker results were derived
from a screen of a large number of SNPs, false positive results due
to selection bias from multiple testing must be considered. Given
the extremely limited number of loci tested in the third sample set
(N=three loci--IL12B, IL23R and IL13), our results argue against a
false positive error. Using the Dunn-Sidak method of calculating an
experimentwise P-value (Sokal R R, Rohlf F J. Biometry 3.sup.rd ed.
W.H. Freeman and Company, New York, 1995) for the third sample set,
analysis of data at the 5' marker, rs1800925, shows it retains
statistical significance after adjusting for multiple testing
(P.sub.adj=0.0199). In addition, although simulation results (not
shown) indicate that these results could have been generated by a
truly associated marker, there is still a reasonable chance that
the observed results arose from a null model. Finally, previous
analyses of population stratification in these sample sets
suggested that the confounding impact on the genetic association
results was marginal (Cargill M, Schrodi S J, Chang M, Garcia V E,
Brandon R, Callis K P et al. A large-scale genetic association
study confirms IL12B and leads to the identification of IL23R as
psoriasis-risk genes. Am J Hum Genet. 2007; 80:273-290).
[0436] Three other gene regions with substantial and replicated
association evidence--HLA-C, IL12B, and IL23R--have been shown to
affect the risk of psoriasis. Given the modest effect sizes of
these and other gene variants associated with common diseases,
multi-locus estimates of differential risk are informative measures
(Janssens A C, Moonesinghe R, Yang Q, Steyerberg E W, van Duijn C
M, Khoury M J. The impact of genotype frequencies on the clinical
validity of genomic profiling for predicting common chronic
diseases. Genet Med 2007; 9: 528-535). In an effort to better
elucidate the strength of the psoriasis-predisposing effects from
all four loci, we estimated the probability of psoriasis given
genotypes at HLA-C and the cytokine-pathway genes IL12B, IL23R and
IL13. Conditional independence between loci was assumed (three
independent methods substantiated this assumption, see the Brief
Description of the Figure section) and we employed Bayes' theorem
for the calculation. Assuming a psoriasis-prevalence of 3%, these
calculations show that the differential risk between the Very High
and Low risk multi-locus genotype groups is over 11-fold (FIG. 1;
Table 7). Greater than 10% of the general North American white
population carry gene combinations which increase their risk of
psoriasis to over 0.08; whereas 33% of the North American white
population are at less than half the risk of disease compared to
the general population.
The 5q31 region harboring IL13 has been identified as a
susceptibility locus for psoriasis in a previous family-based
linkage study of psoriasis (Friberg C, Bjorck K, Nilsson S, Inerot
A, Wahlstrom J, Samuelsson, L. Analysis of chromosome 5q31-42 and
psoriasis: confirmation of a susceptibility locus but no
association with SNPs within SLC22A4 and SLC22A5. J Invest Dermatol
2006; 126: 998-1002), as well as for other inflammatory conditions
including Crohn's disease (Rioux J D, Silverberg M S, Daly M J,
Steinhart A H, McLeod R S, Griffiths A M et al. Genomewide search
in Canadian families with inflammatory bowel disease reveals two
novel susceptibility loci. Am J Hum Genet. 2000; 66: 1863-1870;
Rioux J D, Daly M J, Silverberg M S, Lindblad K, Steinhart H, Cohen
Z et al. Genetic variation in the 5q31 cytokine gene cluster
confers susceptibility to Crohn disease. Nat Genet. 2001; 29:
223-228; Mirza M M, Fisher S A, King K, Cuthbert A P, Hampe J,
Sanderson J et al. Genetic evidence for interaction of the 5q31
cytokine locus and the CARD15 gene in Crohn disease. Am J Hum
Genet. 2003; 72: 1018-1022; Wellcome Trust Case Control Consortium.
Genome-wide association study of 14,000 cases of seven common
diseases and 3,000 shared controls. Nature 2007; 447: 661-678) and
bronchial hyperresponsiveness/atopy/asthma phenotypes (Heinzmann A,
Mao X Q, Akaiwa M, Kreomer R T, Gao P S, Ohshima K et al. Genetic
variants of IL-13 signalling and human asthma and atopy. Hum Mol
Genet. 2000; 9: 549-559; Postma D S, Bleecker E R, Amelung P J,
Holroyd K J, Xu J, Panhuysen C I M et al. Genetic susceptibility to
asthma: bronchial hyperresponsiveness coinherited with a major gene
for atopy. New Eng J Med 1995; 333: 894-900; Howard T D, Whittaker
P A, Zaiman A L, Koppelman G H, Xu J, Hanley M T et al.
Identification and association of polymorphisms in the
interleukin-13 gene with asthma and atopy in a Dutch population. Am
J Respir Cell Mol Biol 2001; 25: 377-384). The link between
psoriasis and Crohn's disease appears to be particularly strong, as
evidenced by (i) a similar aberrant response in T-helper cells
(Neimann A L, Porter S B, Gelfand J M. The epidemiology of
psoriasis. Expert Rev Dermatol 2006; 1: 63-75), (ii) familial
clustering of the two diseases (Neimann A L, Porter S B, Gelfand J
M. The epidemiology of psoriasis. Expert Rev Dermatol 2006; 1:
63-75), and (iii) the observation that the same allele in the IL23R
SNP, rs 11209026, is associated with risk for both diseases
(Cargill M, Schrodi S J, Chang M, Garcia V E, Brandon R, Callis K P
et al. A large-scale genetic association study confirms IL12B and
leads to the identification of IL23R as psoriasis-risk genes. Am J
Hum Genet. 2007; 80:273-290; Duerr R H, Taylor K D, Brant S R,
Rioux J D, Silverberg M S, Daly M J et al. A genome-wide
association study identifies IL23R as an inflammatory bowel disease
gene. Science 2006; 314: 1461-1463). Genes contributing to asthma
and psoriasis risk, such as ADAM33, also appear to overlap (Lesueur
F, Oudot T, Heath S, Foglio M, Lathrop M, Prud'homme J F et al.
ADAM33, a new candidate for psoriasis susceptibility. PLoS ONE
2007; 2:e906).
[0437] In conclusion, we have presented results of three IL13 SNPs
associated with psoriasis. A common susceptibility haplotype, CCG,
carried by 92% of controls produced a consistent effect (joint
OR=1.27) that achieved statistical significance
(P.sub.comb=1.88E-04). Conversely, a less-frequent haplotype, TTT,
generates protective effects in our study (joint OR=0.74) with
fairly similar significance (P.sub.comb=7.05E-04). Further,
combining the genotypic effects at the SNP directly 5' of IL13
(rs1800925) with previously-reported susceptibility variants at
HLA-C, IL12B and IL23R demonstrates a range of psoriasis relative
risk from 0.34, increasing 11-fold to 3.83.
Example Two
Statistical Analysis of Additional SNPs Associated with
Psoriasis
[0438] As disclosed above in Example One, we described that three
SNPs (rs1800925, rs20541 and rs848) in the IL13-region at the 3'
end of the 5q31 cytokine gene cluster were associated with
psoriasis in a large, multi-tiered, genetic association study
(Chang, M., Li, Y., Yan, C., Callis-Duffin, K. P., Matsunami, N.,
Garcia, V. E., Cargill, M., Civello, D., Bui, N., Catanese, J. J.,
Leppert, M. F. et al. (2008) Variants in the 5q31 cytokine gene
cluster are associated with psoriasis. Genes Immun,
doi:10.1038/sj.gene.6364451). The 5q31 genomic region contains a
cluster of cytokine and immune-related genes, including interleukin
(IL) genes IL3, IL4, IL5, and IL13, interferon regulatory factor-1
(IRF-1), colony-stimulating factor-2 (CSF2) and T-cell
transcription factor-7 (TCF7), all excellent biological candidate
genes. This region shows extended marker-marker correlation; for
example, examination of the CEU HapMap dataset (www.hapmap.org)
reveals that a number of markers within the 100 kb interval
immediately upstream of IL13 are in relatively strong LD
(r.sup.2>0.5) with one of the significant IL13 SNPs, rs20541.
Numerous other markers extending as far as 1 Mb upstream of IL13
also show moderate LD with rs20541 (r.sup.2>0.2). Therefore, to
more precisely define the causal variants in the 5q31 region, we
carried out a comprehensive analysis of the genetic variation in
this region using three large, independent sample sets, totaling
1,448 cases and 1,385 controls, and report findings from
association tests of the markers with psoriasis risk.
Results
[0439] Single Marker Association Test Identifies Multiple SNPs
Associated with Psoriasis
[0440] Examination of the 5q31 LD structure in the CEU HapMap Phase
II dataset, led us to focus our fine-mapping to a 725 kb region
that delimits the entire cytokine cluster, extending from .about.50
kb upstream of IL3 to .about.50 kb downstream of IL4 (FIG. 2). This
region was targeted with 90 finemapping SNPs, primarily selected as
tagging markers (see Materials and Methods). Allelic association
tests of the 90 SNPs with psoriasis identified nine significant
ones (P<0.05, FIG. 2 and Table 12) in a 370 kb region extending
from SLC22A4 to KIF3A and including IRF1, IL5, IL13 and IL4; these
nine SNPs were then genotyped in two other case control sample
sets. Although the significance of these nine markers varied in the
two follow-up sample sets (FIG. 2 and Table 13), all nine were
significant in a combined analysis of the three sample sets
(Mantel-Haenszel P.sub.combined<0.05, Table 8 & Table 13).
Breslow-Day tests provided no evidence for heterogeneity of effect
across sample sets except for one marker, rs11568506 (odds ratio
(OR) homogeneity: P.sub.rs11568506=0.032; P>0.05 for all other
markers). Based on the P.sub.comb-values, none of the nine markers
were more significant than rs1800925 (Mantel-Haenszel
P.sub.combined=0.00015), one of the three IL13 markers in our
original report (Chang, M., Li, Y., Yan, C., Callis-Duffin, K. P.,
Matsunami, N., Garcia, V. E., Cargill, M., Civello, D., Bui, N.,
Catanese, J. J., Leppert, M. F. et al. (2008) Variants in the 5q31
cytokine gene cluster are associated with psoriasis. Genes Immun,
doi:10.1038/sj.gene.6364451), although some were comparable (e.g.
P=0.00022 for the IL4 marker rs2227282). Odds ratios conferred by
these variants were all modest (Table 8 & Table 13).
Conditional Analysis Reveals Two Independent SNPs
[0441] To tease apart association signals from patterns of LD and
determine which of these nine SNPs were independently associated
with psoriasis risk, we performed pairwise tests of association for
each SNP, using the combined datasets, conditioning on the
genotypes at the other SNPs and evaluated the significance of these
results using a permutation test (10,000 permutations) (Table 9).
This approach is similar to the haplotype method (Valdes, A. M. and
Thomson, G. (1997) Detecting disease-predisposing variants: the
haplotype method. Am J Hum Genet, 60, 703-716) and has been
previously described (Cargill, M., Schrodi, S. J., Chang, M.,
Garcia, V. E., Brandon, R., Callis, K. P., Matsunami, N., Ardlie,
K. G., Civello, D., Catanese, J. J. et al. (2007) A large-scale
genetic association study confirms IL12B and leads to the
identification of IL23R as psoriasis-risk genes. Am J Hum Genet,
80, 273-390). Not surprisingly, the significant association of
various SNPs with psoriasis disappeared upon conditioning on other
markers. Most notably, the significance of all other markers except
rs11568506 (in SLC22A4; P=0.0105) was abolished upon conditioning
on rs1800925. Conversely, association of rs1800925 remained strong
(P=0.0002) upon conditioning on rs11568506. Together these
observations suggest that rs11568506 and rs1800925 make independent
contributions to psoriasis risk. The genotype correlation between
rs11568506 and rs1800925 is very low (r.sup.2=0.006), while that
between rs1800925 and the other 10 SNPs varied from 0.016 to 0.801
(Table 14).
[0442] Next we assessed whether SNPs in high LD with rs1800925
could be more significantly associated with disease. Genotype data
were retrieved from the HapMap CEU dataset (release #22, phase II
April 07), covering 1 Mb on each side of the IL13 gene, and the
correlation (as determined by r.sup.2 values) between rs1800925 and
all other 1559 SNPs was calculated. A total of 32 markers were
highly correlated with rs1800925 (r.sup.2>0.8) (Table 15), 30 of
which were in absolute LD (r.sup.2=1) with one another. One of
these 30 markers, rs2897443 (r.sup.2 with rs1800925=0.897), which
was genotyped in all three psoriasis sample sets (Table 13), was
nearly 10-fold less significant than rs1800925
(P.sub.rs2897443=0.001 vs P.sub.rs1800925=0.00015). In addition,
rs2897443 was no longer significant after conditioning on rs1800925
(P=0.2168) while, rs1800925 remained significant after conditioning
on rs2897443 (P=0.042). The other two markers (rs2706370 and
rs12187537) were not genotyped; however, they were highly
correlated with rs2897443 (r.sup.2=0.94) and less so with rs1800925
(r.sup.2=0.829 and 0.817, respectively) making it unlikely that
they were more significantly associated with disease than
rs1800925.
[0443] Given that two markers, rs11568506 and rs1800925, show
independent association with psoriasis, we carried out haplotype
analyses using both markers in each of the three individual sample
sets and in a combined analysis of all three sample sets. Although
it's difficult to determine whether the two independent markers
reside in the same LD block (FIG. 2B), the number of double
heterozygotes was small (7 cases and 16 controls out of 2,800
samples; see Table 16); therefore phase could be unambiguously
established in 99.2% of all individuals. Three haplotypes were
observed, with the fourth being relatively rare (<0.001 in cases
or controls) due to the low frequency of rs11568506. The two common
haplotypes were significantly associated with psoriasis in two of
the three sample sets; they were not significant in sample set 2
although the odds ratios were in the same direction as in the other
two sample sets (Table 10). In a meta-analysis, both common
haplotypes were significantly associated with psoriasis, and
significance of the most common haplotype, GC, was markedly higher
than any single SNP(P=5.67.times.10.sup.-6 for the haplotype vs.
1.5.times.10.sup.-4 for rs1800925). The observed effect sizes in
the combined analysis of all sample sets were 1.37 for the
predisposing haplotype GC (rs11568506-rs1800925) (frequency: 0.827
in cases vs 0.777 in controls) and 0.75 for the protective
haplotype GT (frequency: 0.156 in cases vs 0.198 in controls).
Distinct SNPs are Associated with Psoriasis and Crohn's Disease
[0444] Previous studies have identified linkage of the 5q31 locus
and/or association of specific variants in this region with several
other diseases, including CD and asthma/allergic disorders
(Heinzmann, A., Mao, X. Q., Akaiwa, M., Kreomer, R. T., Gao, P. S.,
Ohshima, K., Umeshita, R., Abe, Y., Braun, S., Yamashita, T. et al.
(2000) Genetic variants of IL-13 signalling and human asthma and
atopy. Hum Mol Genet, 9, 549-559; Howard, T. D., Whittaker, P. A.,
Zaiman, A. L., Koppelman, G. H., Xu, J., Hanley, M. T., Meyers, D.
A., Postma, D. S. and Bleecker, E. R. (2001) Identification and
association of polymorphisms in the interleukin-13 gene with asthma
and atopy in a Dutch population. Am J Respir Cell Mol Biol, 25,
377-384; Postma, D. S., Bleecker, E. R., Amelung, P. J., Holroyd,
K. J., Xu, J., Panhuysen, C. I., Meyers, D. A. and Levitt, R. C.
(1995) Genetic susceptibility to asthma--bronchial
hyperresponsiveness coinherited with a major gene for atopy. N Engl
J Med, 333, 894-900). Because psoriasis and CD may share common
genetic etiology (psoriasis is approximately five times more common
in Crohn's disease patients than in controls (Lee, F. I., Bellary,
S. V. and Francis, C. (1990) Increased occurrence of psoriasis in
patients with Crohn's disease and their relatives. Am J
Gastroenterol, 85, 962-963) and the same missense SNP in IL23R is
associated with both diseases (Duerr, R. H., Taylor, K. D., Brant,
S. R., Rioux, J. D., Silverberg, M. S., Daly, M. J., Steinhart, A.
H., Abraham, C., Regueiro, M., Griffiths, A. et al. (2006) A
genome-wide association study identifies IL23R as an inflammatory
bowel disease gene. Science, 314, 1461-1463; Cargill, M., Schrodi,
S. J., Chang, M., Garcia, V. E., Brandon, R., Callis, K. P.,
Matsunami, N., Ardlie, K. G., Civello, D., Catanese, J. J. et al.
(2007) A large-scale genetic association study confirms IL12B and
leads to the identification of IL23R as psoriasis-risk genes. Am J
Hum Genet, 80, 273-390; Capon, F., Di Meglio, P., Szaub, J.,
Prescott, N. J., Dunster, C., Baumber, L., Timms, K., Gutin, A.,
Abkevic, V., Burden, A. D. et al. (2007) Sequence variants in the
genes for the interleukin-23 receptor (IL23R) and its ligand
(IL12B) confer protection against psoriasis. Hum Genet, 122,
201-206; Smith, R. L., Warren, R. B., Eyre, S., Ho, P., Ke, X.,
Young, H. S., Griffiths, C. E. and Worthington, J. (2007)
Polymorphisms in the IL-12 beta and IL-23R Genes Are Associated
with Psoriasis of Early Onset in a UK Cohort. J Invest Dermatol.
doi:10.1038/sj.jid.5701140; Nair, R. P., Ruether, A., Stuart, P.
E., Jenisch, S., Tejasvi, T., Hiremagalore, R., Schreiber, S.,
Kabelitz, D., Lim, H. W., Voorhees, J. J. et al. (2008)
Polymorphisms of the IL12B and IL23R Genes Are Associated with
Psoriasis. J Invest Dermatol. doi:10.1038/sj.jid.5701255), we were
also interested in testing our psoriasis sample sets for 5q31 SNPs
showing strong association with CD. The WTCCC reported several
highly significant SNPs in this region in their CD dataset
(Wellcome Trust Case Control Consortium. (2007) Genome-wide
association study of 14,000 cases of seven common diseases and
3,000 shared controls. Nature, 447, 661-678). When selecting our
set of 103 tagging SNPs, we specifically selected those SNPs, in
groups of highly correlated markers, with evidence of association
with CD in the WTCCC sample set. Of the 90 fine-mapping markers
described above, five were identical to those showing strong
association with CD (rs2285673, rs4540166, rs2522057, rs6596075 and
rs10077785, all with P<5.times.10.sup.-5 in .about.2,000 cases
and .about.3,000 controls (Wellcome Trust Case Control Consortium.
(2007) Genome-wide association study of 14,000 cases of seven
common diseases and 3,000 shared controls. Nature, 447, 661-678)
and genotyped in all three of our psoriasis sample sets. None were
significant in sample set 1 (all P>0.05), but one SNP,
rs2522057, was significantly associated with psoriasis in a
meta-analyses of the three sample sets combined (P=0.022) (Table
11). The pairwise conditional association test, however, showed
that this significant association could be accounted for by the
IL13 marker, rs1800925 (P=0.60 for rs2522057 conditioned upon
rs1800925, whereas rs1800925 remained significant when conditioned
upon rs2522057, P=0.017). Assuming a type I error rate of 0.05 and
the population allele frequency observed in the WTCCC study, our
combined analysis had 90% power to detect an allelic effect equal
to an OR of 1.25, similar to the reported OR of 1.37 for rs6596075,
which tags the 5q31 CD risk haplotype (Wellcome Trust Case Control
Consortium. (2007) Genome-wide association study of 14,000 cases of
seven common diseases and 3,000 shared controls. Nature, 447,
661-678). Thus variants contributing to CD risk in this genomic
region, which map 5' of the psoriasis-associated SNPs near the
LOC441108-region, do not make an independent contribution to the
etiology of psoriasis in our sample sets. In addition, although
neither of the two independent psoriasis markers, rs1800925 and
rs11568506, was tested in the WTCCC's CD sample set, four other
markers in high LD with rs1800925 (r.sup.2=0.9 for all) were tested
but were not significant in their study. Therefore, association
with CD and psoriasis in this region appears to be explained by
different variants.
Discussion
[0445] Our analysis of the 5q31 cytokine cluster reveals that
multiple SNPs are significantly associated with psoriasis risk;
however, incorporating LD into our analysis identified two SNPs
independently associated with psoriasis: rs1800925 in IL13 and
rs11568506 in SLC22A4, also known as organic cation transporter 1
(OCTN1). The observed significance was only marginal for the
SLC22A4 marker (Mantel-Haenszel P.sub.combined=0.043). However,
combining the genotype information for this marker with the more
frequent IL13 marker, which is also more significant
(Mantel-Haenszel P.sub.combined=0.00015), resulted in two common
psoriasis-associated haplotypes that were both highly significant.
In particular, the major risk haplotype, with a control allele
frequency of 0.777 increasing to 0.827 in cases, showed more
pronounced association with psoriasis
(P.sub.combined=5.67.times.10.sup.-6, OR=1.37).
[0446] The biological interpretation of this observation (i.e.,
variants in two linked genes) is not straight-forward; however,
both SLC22A4 and IL13 are putative genetic risk factors for other
autoimmune or autoinflammatory disorders. Specifically, two-locus
functional polymorphisms (haplotypes) in SLC22A4 and the adjacent
SLC22A5 genes have been reported to be associated with CD
(Peltekova, V. D., Wintle, R. F., Rubin, L. A., Amos, C. I., Huang,
Q., Gu, X., Newman, B., Van Oene, M., Cescon, D., Greenberg, G. et
al. (2004) Functional variants of OCTN cation transporter genes are
associated with Crohn disease. Nat Genet, 36, 471-475), although
definitive causal variants remain to be determined (Silverberg, M.
S. (2006) OCTNs: will the real IBD5 gene please stand up? World J
Gastroenterol, 12, 3678-3681; Silverberg, M. S., Duerr, R. H.,
Brant, S. R., Bromfield, G., Datta, L. W., Jani, N., Kane, S. V.,
Rotter, J. I., Philip Schumm, L., Hillary Steinhart, A., et al.
(2007) Refined genomic localization and ethnic differences observed
for the IBD5 association with Crohn's disease. Eur J Hum Genet, 15,
328-335). Variation in IL13, an immunoregulatory cytokine produced
by activated T helper 2-type (Th2) cells, has been most prominently
associated with asthma (Heinzmann, A., Mao, X. Q., Akaiwa, M.,
Kreomer, R. T., Gao, P. S., Ohshima, K., Umeshita, R., Abe, Y.,
Braun, S., Yamashita, T. et al. (2000) Genetic variants of IL-13
signalling and human asthma and atopy. Hum Mol Genet, 9, 549-559,
as well as atopic dermatitis (Tsunemi, Y., Saeki, H., Nakamura, K.,
Sekiya, T., Hirai, K., Kakinuma, T., Fujita, H., Asano, N., Tanida,
Y., Wakugawa, M. et al. (2002) Interleukin-13 gene polymorphism
G4257A is associated with atopic dermatitis in Japanese patients. J
Dermatol Sci, 30, 100-107). Thus both genes have strong a priori
plausibility as risk factors of psoriasis, particularly as multiple
autoimmune disorders have been associated with the same genetic
variant (Gregersen, P. K., Lee, H. S., Batliwalla, F. and Begovich,
A. B. (2006) PTPN22: setting thresholds for autoimmunity. Semin
Immunol, 18, 214-223; Yamada, R. and Ymamoto, K. (2005) Recent
findings on genes associated with inflammatory disease. Mutat Res,
573, 136-151). Strong biological evidence for the involvement of
SLC22A4 or IL13 in the pathogenesis of psoriasis has, however, not
yet been reported. Further experimentation should help determine
whether these genes play a role in the disease process.
[0447] The two identified SNPs are located in an intron of SLC22A4
and near the 5' end of IL13, respectively, with no predictive
functional significance based on the current SNP annotation,
although rs11568506 is 43 bp from a POU2F1 transcription factor
binding site, which exhibits a high degree of conservation across
multiple placental mammals. In the absence of a validated role in
gene regulation for these SNPs, and the presence of several other
excellent biological candidate genes within this region as well as
critical regulatory elements (Mohrs, M., Blankespoor, C. M., Wang,
Z., Loots, G. G., Afzal V., Hadeiba, H., Shinkai, K., Rubin, E. M.,
and Locksley, R. M. (2001) Deletion of a coordinate regulator of
type 2 cytokine expression in mice. Nat. Immunol. 2, 842-847), it
is tempting to speculate that untested, causal genetic variant(s)
lie on the particular haplotype defined by the two independent SNPs
identified here. Although our comprehensive, HapMap-based analysis
of the variation in this region provided no evidence for such a
marker, we were unable to develop assays for tagging SNPS covering
13.6% of the variation. In addition, SNPs not available in the
HapMap, such as for the most significant marker, rs1800925, may
explain these results. Similarly, other genetic variants
(insertions, deletions, etc) which have been implicated in the
etiology of various complex diseases, including psoriasis (see, for
example, Hollox, E. J., Huffineier, U., Zeeuwen, P. L., Palla, R.,
Lascorz, J., Rodijk-Olthuis, D., van de Kerkhof, P. C., Traupe, H.,
de Jongh, G., den Heijer, M. et al. (2008) Psoriasis is associated
with increased beta-defensin genomic copy number. Nat Genet, 40,
23-25, and Fanciulli, M., Norsworthy, P. J., Petretto, E., Dong,
R., Harper, L., Kamesh, L., Heward, J. M., Gough, S. C., de Smith,
A., Blakemore, A. I. et al. (2007) FCGR3B copy number variation is
associated with susceptibility to systemic, but not organ-specific,
autoimmunity. Nat Genet, 39, 721-723), may be responsible for
modulating disease susceptibility.
[0448] Although the recent identification of IL23R variants
associated with psoriasis and CD solidifies the notion that genetic
etiology may overlap between these two diseases (Duerr, R. H.,
Taylor, K. D., Brant, S. R., Rioux, J. D., Silverberg, M. S., Daly,
M. J., Steinhart, A. H., Abraham, C., Regueiro, M., Griffiths, A.
et al. (2006) A genome-wide association study identifies IL23R as
an inflammatory bowel disease gene. Science, 314, 1461-1463;
Cargill, M., Schrodi, S. J., Chang, M., Garcia, V. E., Brandon, R.,
Callis, K. P., Matsunami, N., Ardlie, K. G., Civello, D., Catanese,
J. J. et al. (2007) A large-scale genetic association study
confirms IL12B and leads to the identification of IL23R as
psoriasis-risk genes. Am J Hum Genet, 80, 273-390), our data
suggest that this is unlikely to be the case for the 5q31 locus,
where linkage signals have been detected for both diseases (Rioux,
J. D., Silverberg, M. S., Daly, M. J., Steinhart, A. H., McLeod, R.
S., Griffiths, A. M., Green, T., Brettin, T. S., Stone, V., Bull,
S. B. et al. (2000) Genomewide search in Canadian families with
inflammatory bowel disease reveals two novel susceptibility loci.
Am J Hum Genet, 66, 1863-1870; Rioux, J. D., Daly, M. J.,
Silverberg, M. S., Lindblad, K., Steinhart, H., Cohen, Z.,
Delmonte, T., Kocher, K., Miller, K., Guschwan, S. et al. (2001)
Genetic variation in the 5q31 cytokine gene cluster confers
susceptibility to Crohn disease. Nat Genet, 29, 223-228;
Samuelsson, L., Enlund, F., Torinsson, A., Yhr, M., Inerot, A.,
Enerback, C., Wahlstrom, J., Swanbeck, G. and Martinsson, T. (1999)
A genome-wide search for genes predisposing to familial psoriasis
by using a stratification approach. Hum Genet, 105, 523-529).
Several previously reported CD-associated markers in the 5q31
region, including one that tags a risk haplotype (rs6596075), were
not significant in our psoriasis sample sets and rs2522057, which
showed modest association the combined analysis, could be explained
by LD with the most significant marker, rs1800925. This is despite
the fact that our sample sets had sufficient power to detect an
effect size similar to that of the same markers observed in CD or
the majority of the SNPs recently identified for other complex
diseases (Wellcome Trust Case Control Consortium. (2007)
Genome-wide association study of 14,000 cases of seven common
diseases and 3,000 shared controls. Nature, 447, 661-678). This
observation is consistent with a recent report that failed to
detect a significant association between psoriasis and three other
CD-associated SNPs in SLC22A4 and SLC22A5 (Friberg, C., Bjorck, K.,
Nilsson, S., Inerot, A., Wahlstrom, J. and Samuelsson, L. (2006)
Analysis of chromosome 5q31-32 and psoriasis: confirmation of a
susceptibility locus but no association with SNPs within SLC22A4
and SLC22A5. J Invest Dermatol, 126, 998-1002). It is possible that
the lack of association may be partly confounded by the fact that
the actual causal CD variants have not been tested. However,
judging from the significance level observed in the WTCCC study
(Wellcome Trust Case Control Consortium. (2007) Genome-wide
association study of 14,000 cases of seven common diseases and
3,000 shared controls. Nature, 447, 661-678), and unless there are
significant differences in the LD structure between their sample
sets and ours (which is unlikely), we favor the interpretation that
susceptibility to psoriasis and CD are affected by distinct genetic
variants at this locus or the same variants but with different
effect sizes.
[0449] Finally, it is possible that we may not have the power to
detect conditional association effects in our sample sets. Thus,
although the significance of all other markers except rs11568506
can be accounted for by rs1800925, we cannot exclude the
possibility that these other markers, particularly the stronger
ones in IL13 and IL4, make additional, independent contributions to
disease risk. In addition, the possibility that our current finding
is false positive cannot be completely discounted, since the
observed significance will not survive multiple testing corrections
if all markers tested in our previous genome-wide scan and in this
study are considered--which is generally deemed conservative.
However, in an unpublished GWA study of .about.1400 Caucasian cases
and .about.1400 Caucasian controls, two of our original
IL13-associated SNPs, rs20541 and rs848, exhibit very strong
evidence for association. These data suggest markers in the 5q31
region are true psoriasis risk markers and suggest that variants in
both the IL13 and SLC22A4 regions independently contribute to
psoriasis risk. Validation in other sample sets of similar
characteristics is warranted to bring further definition to the
causal variant(s).
Materials and Methods
Clinical Samples
[0450] Three sample sets of psoriasis cases and unaffected controls
were assembled in this study. Detailed demographics and
diagnostic/enrollment criteria have been described in a previous
publication (Cargill, M., Schrodi, S. J., Chang, M., Garcia, V. E.,
Brandon, R., Callis, K. P., Matsunami, N., Ardlie, K. G., Civello,
D., Catanese, J. J. et al. (2007) A large-scale genetic association
study confirms IL12B and leads to the identification of IL23R as
psoriasis-risk genes. Am J Hum Genet, 80, 273-390). Briefly, all
individuals are North American whites of European descent and were
18 years or older when they contributed their samples (sample set
1: 467 cases/460 controls; sample set 2: 498 cases/498 controls;
sample set 3: 483 cases/427 controls. Informed written consent was
obtained from all participants, and all protocols were approved by
national and/or local institutional review board.
Selection of Tagging SNPs and Overall Study Design
[0451] To comprehensively yet efficiently investigate the 5q31
region, we ran the MIT tagger program
(http://www.broad.mit.edu/mpg/tagger/server.html) (de Bakker, P.
I., Yelensky, R., Pe'er, I., Gabriel, S. B., Daly, M. J. and
Altshuler, D. (2005) Efficiency and power in genetic association
studies. Nat Genet, 37, 1217-1223) with the CEU HapMap phase II
dataset (The landmarks were set at chr5:131373131.132097638 [NCBI
Build 36]; minimal allele frequency was set at 0.02; r.sup.2
threshold was set at 0.8; and tagging mode was set at pair wise). A
total of 103 tagging SNPs (including the previously tested IL13
marker rs20541) are required to capture the SNP diversity (610
polymorphic sites) within this 725 kbp region. Assay designs were
attempted on the default tagging markers, and when not feasible, on
an alternative marker within the tagging group. We also referenced
the WTCCC study to preferentially select markers that were
significantly associated with CD as tagging markers. We were able
to develop assays for 90 of these tagging SNPs (excluding the assay
already available for rs20541). In addition, assays for two SNPs in
predicted transcription factor binding sites (rs381870 and
rs4540166) were developed.
[0452] The above 92 SNPs were genotyped in one of the three
psoriasis case-control sample sets (sample set 1; 467 cases/460
controls). Genotyping data for 90 markers, including 88 tagging
markers (equivalent to 86.4% coverage for all tagging markers),
passed quality control and were subjected to further analysis.
Hardy-Weinberg equilibrium tests identified six markers in controls
and two others in cases with P<0.05 (Table 12). However,
analysis of the data showed no apparent error in genotype
assignment for these markers, thus they were included in the
association tests. As predicted, inter-marker LD between the
genotyped markers was low in our samples (FIG. 2). Significant SNPs
(P<0.05) were then genotyped in two other case control sample
sets (sample set 2 (498 cases/498 controls) and sample set 3 (481
cases/424 controls)).
Genotyping
[0453] Genotyping was carried out by the method of real-time,
allele-specific PCR with primers designed and validated in-house
(Germer, S., Holland, M. J. and Higuchi, R. (2000) High-throughput
SNP allele-frequency determination in pooled DNA samples by kinetic
PCR. Genome Res, 10, 258-266). Genotype calls of cases and
controls, randomly arrayed onto genotyping plates, were made using
an automated algorithm and were subjected to manual examination
without knowledge of case-control status, prior to statistical
analysis. Our genotyping accuracy has been consistently better than
99% (Cargill, M., Schrodi, S. J., Chang, M., Garcia, V. E.,
Brandon, R., Callis, K. P., Matsunami, N., Ardlie, K. G., Civello,
D., Catanese, J. J. et al. (2007) A large-scale genetic association
study confirms IL12B and leads to the identification of IL23R as
psoriasis-risk genes. Am J Hum Genet, 80, 273-390; Li, Y., Rowland,
C., Catanese, J., Morris, J. C., Lovestone, S., O'Donovan M, C.,
Goate, A., Owen, M., Williams, J. and Grupe, A. (2008) SORL1
variants and risk of late-onset Alzheimer's disease. Neurobiol Dis,
29, 293-296).
Statistical Analysis
[0454] Hardy-Weinberg equilibrium was examined by an exact test.
Allelic association of SNPs with psoriasis risk was determined by
the .chi..sup.2 test in individual sample sets and by meta-analysis
using fixed effects of Mantel-Haenszel methods to combine odds
ratios across the sample sets. Marker conditional association tests
were done using an approach similar to the haplotype method (22) as
previously described (Cargill, M., Schrodi, S. J., Chang, M.,
Garcia, V. E., Brandon, R., Callis, K. P., Matsunami, N., Ardlie,
K. G., Civello, D., Catanese, J. J. et al. (2007) A large-scale
genetic association study confirms IL12B and leads to the
identification of IL23R as psoriasis-risk genes. Am J Hum Genet,
80, 273-390). In brief, cases and controls were partitioned on the
basis of genotypes at one SNP, and counts at an interrogated SNP
were subjected to analysis where statistical significance was
assessed by a permutation method (10,000 permutations). For
marker-marker LD measurements, D' and r.sup.2 were calculated using
LDMax (www.sph.umich.edu/csg/abecasis/GOLD/docs/ldmax.html).
Haplotypes were estimated and tested for association with disease
status using a score test with haplotypes coded in an additive
fashion (Schaid, D. J., Rowland, C. M., Tines, D. E., Jacobson, R.
M. and Poland, G. A. (2002) Score tests for association between
traits and haplotypes when linkage phase is ambiguous. Am J Hum
Genet, 70, 425-434). Power calculations were done using the
PS:Power and Sample Size Calculation Program, obtained from the
Department of Biostatistics, Vanderbilt University website
(http://biostat.mc.vanderbiltedu/twiki/bin/view/Main/PowerSampleSize).
Example Three
Additional LD SNPs Associated with Psoriasis
[0455] Additional investigation was conducted to identify SNPs in
linkage disequilibrium (LD) with certain "interrogated SNPs" which
have been found to be associated with psoriasis, as shown in the
tables. The interrogated SNPs, which are shown in column 1 (which
indicates the hCV identification numbers of each interrogated SNP)
and column 2 (which indicates the public rs identification numbers
of each interrogated SNP) of Table 4. The methodology is described
earlier in the instant application. To summarize briefly, the power
threshold (T) was set at an appropriate level, such as 51%, for
detecting disease association using LD markers. This power
threshold is based on equation (31) above, which incorporates
allele frequency data from previous disease association studies,
the predicted error rate for not detecting truly disease-associated
markers, and a significance level of 0.05. Using this power
calculation and the sample size, for each interrogated SNP a
threshold level of LD, or r.sup.2 value, was derived (, equations
(32) and (33) above). The threshold value r.sub.T.sup.2 is the
minimum value of linkage disequilibrium between the interrogated
SNP and its LD SNPs possible such that the non-interrogated SNP
still retains a power greater or equal to T for detecting
disease-association.
[0456] Based on the above methodology, LD SNPs were found for the
interrogated SNPs. Several exemplary LD SNPs for the interrogated
SNPs are listed in Table 4; each LD SNP is associated with its
respective interrogated SNP. Also shown are the public SNP IDs (rs
numbers) for the interrogated and LD SNPs, when available, and the
threshold r.sup.2 value and the power used to determine this, and
the r.sup.2 value of linkage disequilibrium between the
interrogated SNP and its matching LD SNP. As an example in Table 4,
the interrogated, psoriasis-associated SNP rs20541 (hCV2259921) was
calculated to be in LD with rs847 (hCV8932046) at an r.sup.2 value
of 0.9061, based on a 51% power calculation, thus establishing the
latter as a marker associated with psoriasis as well.
[0457] 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.
TABLE-US-00001 TABLE 1 Transcript SNP info and associated
gene/protein information Gene Number: 1 Gene Symbol IL13-3596 Gene
Name: interleukin 13 Transcript Accession: NM_002188 Protein
Accession: NP_002179 Chromosome: 5 OMIM NUMBER: 147683 OMIM
Information: {Asthma, susceptibility to}, 600807 (3); {Allergic
rhinitis, /susceptibility to}, 607154 (3) Transcript Sequence (SEQ
ID NO: 1): Protein Sequence (SEQ ID NO: 3): SNP Information Context
(SEQ ID NO: 5):
GGCAGTTTTCCAGCTTGCATGTCCGAGACACCAAAATCGAGGTGGCCCAGTTTGTAAAG
GACCTGCTCTTACATTTAAAGAAACTTTTTCGCGAGGGACAR
TTCAACTGAAACTTCGAAAGCATCATTATTTGCAGAGACAGGACCTGACTATTGAAGTT
GCAGATTCATTTTTCTTTCTGATGTCAAAAATGTCTTGGGT Celera SNP ID: hCV2259921
Public SNP ID: rs20541 SNP Chromosome Position: 132023863 SNP in
Transcript Sequence SEQ ID NO: 1 SNP Position Transcript: 446 SNP
Source: Applera Population (Allele, Count): Caucasian (A, 6|G, 34)
African American (A, 7|G, 29) total (A, 13|G, 63) SNP Type:
Missense Mutation Protein Coding: SEQ ID NO: 3, at position 144,
(Q, CAG) (R, CGG) SNP Source: HGMD; dbSNP; HapMap; HGBASE
Population (Allele, Count): Caucasian (A, 28|G, 92) SNP Type:
Missense Mutation Protein Coding: SEQ ID NO: 3, at position 144,
(Q, CAG) (R, CGG) Context (SEQ ID NO: 6):
GAGTGTGTTTGTCACCGTTGGGGATTGGGGAAGACTGTGGCTGCTAGCACTTGGAGCCA
AGGGTTCAGAGACTCAGGGCCCCAGCACTAAAGCAGTGGACM
CCAGGAGTCCCTGGTAATAAGTACTGTGTACAGAATTCTGCTACCTCACTGGGGTCCTG
GGGCCTCGGAGCCTCATCCGAGGCAGGGTCAGGAGAGGGGC Celera SNP ID: hCV8932051
Public SNP ID: rs848 SNP Chromosome Position: 132024399 SNP in
Transcript Sequence SEQ ID NO: 1 SNP Position Transcript: 981 SNP
Source: dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):
Caucasian (A, 29|C, 91) SNP Type: UTR3 Context (SEQ ID NO: 7):
AGCCTCATCCGAGGCAGGGTCAGGAGAGGGGCAGAACAGCCGCTCCTGTCTGCCAGCC
AGCAGCCAGCTCTCAGCCAACGAGTAATTTATTGTTTTTCCTY
GTATTTAAATATTAAATATGTTAGCAAAGAGTTAATATATAGAAGGGTACCTTGAACAC
TGGGGGAGGGGACATTGAACAAGTTGTTTCATTGACTATCA Celera SNP ID: hCV8932046
Public SNP ID: rs847 SNP Chromosome Position: 132024568 SNP in
Transcript Sequence SEQ ID NO: 1 SNP Position Transcript: 1150
Related Interrogated SNP: hCV2259921 (Power = .51) Related
Interrogated SNP: hCV8932051 (Power = .51) SNP Source: dbSNP;
Celera; HapMap; HGBASE Population (Allele, Count): Caucasian (T,
27|C, 91) SNP Type: UTR3 Context (SEQ ID NO: 8):
AGCAGCTCAGGCACACTTCTTCTTGGTCTTATTTATTATTGTGTGTTATTTAAATGAGTG
TGTTTGTCACCGTTGGGGATTGGGGAAGACTGTGGCTGCTR
GCACTTGGAGCCAAGGGTTCAGAGACTCAGGGCCCCAGCACTAAAGCAGTGGACACCA
GGAGTCCCTGGTAATAAGTACTGTGTACAGAATTCTGCTACC Celera SNP ID:
hCV8932052 Public SNP ID: rs1295685 SNP Chromosome Position:
132024344 SNP in Transcript Sequence SEQ ID NO: 1 SNP Position
Transcript: 926 Related Interrogated SNP: hCV2259921 (Power = .51)
Related Interrogated SNP: hCV8932051 (Power = .51) SNP Source:
dbSNP; Celera; HapMap; HGBASE Population (Allele, Count): Caucasian
(A, 29|G, 91) SNP Type: UTR3 Gene Number: 2 Gene Symbol KIF3A-11127
Gene Name: kinesin family member 3A Transcript Accession: NM_007054
Protein Accession: NP_008985 Chromosome: 5 OMIM NUMBER: 604683 OMIM
Information: Transcript Sequence (SEQ ID NO: 2): Protein Sequence
(SEQ ID NO: 4): SNP Information Context (SEQ ID NO: 9):
TTGAGACTTTATAAGTTAGTATTTATTAAATTAATATTATTTTAATAAGTTTTGTTAAATC
CTAGTTTAAATGACAAAGCTGTGTATAGAGTAGGGGTGAS
TGAAGGTGGAGTACTCTTGAGGTGGCGATAAAAATGTACCCATAAATTTAAAGTCCATT
CTGTAATTGGAATACTGAATGTCCTGTGTGTGGTGAACATT Celera SNP ID:
hCV11818506 Public SNP ID: rs17690965 SNP Chromosome Position:
132058566 SNP in Transcript Sequence SEQ ID NO: 2 SNP Position
Transcript: 3913 Related Interrogated SNP: hCV16176374 (Power = .6)
SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):
Gaucasian (G, 31|C, 69) SNP Type: UTR3
TABLE-US-00002 TABLE 2 Genomic SNP info and associated gene
information Gene Number: 1 Gene Symbol: IL13-3596 Gene Name:
interleukin 13 Chromosome: 5 OMIM NUMBER: 147683 OMIM Information:
{Asthma, susceptibility to}, 600807 (3); {Allergic rhinitis,
/susceptibility to}, 607154 (3) Genomic Sequence (SEQ ID NO: 10):
SNP Information Context (SEQ ID NO: 19):
CAGCAGTTTTCCAGCTTGCATGTCCGAGACACCAAAATCGAGGTGGCCCAGTTTGTAAA
GGACCTGCTCTTACATTTAAAGAAACTTTTTCGCGAGGGACR
GTTCAACTGAAACTTCGAAAGCATCATTATTTGCAGAGACAGGACCTGACTATTGAAGT
TGCAGATTCATTTTTCTTTCTGATGTCAAAAATGTCTTGGG Celera SNP ID: hCV2259921
Public SNP ID: rs20541 SNP Chromosome Position: 132023863 SNP in
Genomic Sequence: SEQ ID NO: 10 SNP Position Genomic: 12099 SNP
Source: Applera Population (Allele, Count): Caucasian (A, 6|G, 34)
African American (A, 7|G, 29) total (A, 13|G, 63) SNP Type:
MISSENSE MUTATION; ESE; UTR3; SILENT RARE CODON; SILENT MUTATION
SNP Source: HGMD; dbSNP; HapMap; HGBASE Population (Allele, Count):
Caucasian (A, 28|G, 92) SNP Type: MISSENSE MUTATION; ESE; UTR3;
SILENT RARE CODON; SILENT MUTATION Context (SEQ ID NO: 20):
TATTCTAAATACTTGAAAACTTTAAATGTATTCATTCCTCAGAGCAACTTCATGAGACAG
GGACAGCTATGACCCCTATTTCACAGATGAGGCTGAGTAGM
GTGCCCAAGGTCACACAGCCAGGAGGCACAGCAGCCAGGCCTGACAGACCACCTGGGC
CCAGCGTCCGCTCTCTTAGCCACCGTGTACTATAGCAGCCTC Celera SNP ID:
hCV2259917 Public SNP ID: rs762534 SNP Chromosome Position:
132032655 SNP in Genomic Sequence: SEQ ID NO: 10 SNP Position
Genomic: 20891 SNP Source: dbSNP; Celera; HapMap; ABI_Val; HGBASE
Population (Allele, Count): Caucasian (C, 111|A, 9) SNP Type:
INTERGENIC; UNKNOWN Context (SEQ ID NO: 21):
GAGTGTGTTTGTCACCGTTGGGGATTGGGGAAGACTGTGGCTGCTAGCACTTGGAGCCA
AGGGTTCAGAGACTCAGGGCCCCAGCACTAAAGCAGTGGACM
CCAGGAGTCCCTGGTAATAAGTACTGTGTACAGAATTCTGCTACCTCACTGGGGTCCTG
GGGCCTCGGAGCCTCATCCGAGGCAGGGTCAGGAGAGGGGC Celera SNP ID: hCV8932051
Public SNP ID: rs848 SNP Chromosome Position: 132024399 SNP in
Genomic Sequence: SEQ ID NO: 10 SNP Position Genomic: 12635 SNP
Source: dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):
Caucasian (A, 29|C, 91) SNP Type: UTR3 Context (SEQ ID NO: 22):
TCGGGGAGGAAGTGGGTAGGGGAGAAATCTTGACATCAACACCCAACAGGCAAATGCC
GTGGCCTCTGCTGTGGGGGTTTCTGGAGGACTTCTAGGAAAAY
GAGGGAAGAGCAGGAAAAGGCGACATGGCTGCAGGGGCCAAGCCCAGGAGCCGCCCT
CCACAGCACTCATTCTGCAGAAGGGAAATTTGAGGCCCCCAGA Celera SNP ID:
hCV50000065 Public SNP ID: rs1800925 SNP Chromosome Position:
132020708 SNP in Genomic Sequence: SEQ ID NO: 10 SNP Position
Genomic: 8944 SNP Source: dbSNP; HGBASE Population (Allele, Count):
Caucasian (C, 97|T, 23) SNP Type: MISSENSE MUTATION; UTR5; INTRON
Context (SEQ ID NO: 23):
CACAGCAGGGAGAGTGCTGTGTTATGCGAGGAGGTTGGAGAAATCCTCCCCATGAGAT
AAGATGGGAACAGAGATCGGGACGAAACAAGGGGAGGGGACAM
CCATGCACAGATCGGGGCAAAGTCATCAAGGGAAAGGGAACTGCAGGTGCTAAGGTCT
TGAGCAAGAGCGAGCTGGGGATGCCCTTCCCAGCACTCACGG Celera SNP ID:
hCV16176063 Public SNP ID: rs2243211 SNP Chromosome Position:
132029321 SNP in Genomic Sequence: SEQ ID NO: 10 SNP Position
Genomic: 17557 SNP Source: dbSNP; HapMap; HGBASE Population
(Allele, Count): Caucasian (C, 108|A, 12) SNP Type: TFBS
SYNONYMOUS; INTERGENIC; UNKNOWN Context (SEQ ID NO: 24):
CAGTACCCACCTCATGGGGACTTCCGTGAGGACTGAATGAGACAGTCCCTGGAAAGCC
CCTGGTTTGTGCGAGTCGTCCCGGCCTCTGGCGTTCTACTCAY
GTGCTGACCTCTTTGTCCTGCAGCAGTTTTCCAGCTTGCATGTCCGAGACACCAAAATCG
AGGTGGCCCAGTTTGTAAAGGACCTGCTCTTACATTTAAA Celera SNP ID: hCV8932053
Public SNP ID: rs1295686 SNP Chromosome Position: 132023742 SNP in
Genomic Sequence: SEQ ID NO: 10 SNP Position Genomic: 11978 Related
Interrogated SNP: hCV2259921 (Power = .51) Related Interrogated
SNP: hCV8932051 (Power = .51) SNP Source: Applera Population
(Allele, Count): Caucasian (C, 33|T, 7) African American (C, 13|T,
23) total (C, 46|T, 30) SNP Type: TRANSCRIPTION FACTOR BINDING
SITE; INTRON SNP Source: dbSNP; HapMap; ABI_Val; HGBASE Population
(Allele, Count): Caucasian (T, 28|C, 92) SNP Type: TRANSCRIPTION
FACTOR BINDING SITE; INTRON Context (SEQ ID NO: 25):
AGCCTCATCCGAGGCAGGGTCAGGAGAGGGGCAGAACAGCCGCTCCTGTCTGCCAGCC
AGCAGCCAGCTCTCAGCCAACGAGTAATTTATTGTTTTTCCTY
GTATTTAAATATTAAATATGTTAGCAAAGAGTTAATATATAGAAGGGTACCTTGAACAC
TGGGGGAGGGGACATTGAACAAGTTGTTTCATTGACTATCA Celera SNP ID: hCV8932046
Public SNP ID: rs847 SNP Chromosome Position: 132024568 SNP in
Genomic Sequence: SEQ ID NO: 10 SNP Position Genomic: 12804 Related
Interrogated SNP: hCV2259921 (Power = .51) Related Interrogated
SNP: hCV8932051 (Power = .51) SNP Source: dbSNP; Celera; HapMap;
HGBASE Population (Allele, Count): Caucasian (T, 27|C, 91) SNP
Type: MICRORNA; UTR3 Context (SEQ ID NO: 26):
AGCAGCTCAGGCACACTTCTTCTTGGTCTTATTTATTATTGTGTGTTATTTAAATGAGTG
TGTTTGTCACCGTTGGGGATTGGGGAAGACTGTGGCTGCTR
GCACTTGGAGCCAAGGGTTCAGAGACTCAGGGCCCCAGCACTAAAGCAGTGGACACCA
GGAGTCCCTGGTAATAAGTACTGTGTACAGAATTCTGCTACC Celera SNP ID:
hCV8932052 Public SNP ID: rs1295685 SNP Chromosome Position:
132024344 SNP in Genomic Sequence: SEQ ID NO: 10 SNP Position
Genomic: 12580 Related Interrogated SNP: hCV2259921 (Power = .51)
Related Interrogated SNP: hCV8932051 (Power = .51) SNP Source:
dbSNP; Celera; HapMap; HGBASE Population (Allele, Count): Caucasian
(A, 29|G, 91) SNP Type: MICRORNA; UTR3 Context (SEQ ID NO: 27):
GAGGTGTTATAGTGCCAGGGAAAAGGGGTGCAAGACTAGTGTTTGCCTCTTATTTCTTG
TCTTGTTTATAAATTCTCTACATTAAAAATATAAATTCCAAR
TGAAAACAATGGAATAAACACAAACTCCCACTTTATAACCAACTAAAATGACAGTAAC
TGAATTTTCTAAAGTTTTAAACCCACCAAAATGGGAGAAATG Celera SNP ID:
hCV27452177 Public SNP ID: rs3091307 SNP Chromosome Position:
132017035 SNP in Genomic Sequence: SEQ ID NO: 10 SNP Position
Genomic: 5271 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: dbSNP; HapMap; ABI_Val; HGBASE Population (Allele,
Count): Caucasian (A, 94|G, 26) SNP Type: INTRON Gene Number: 2
Gene Symbol: KIF3A-11127 Gene Name: kinesin family member 3A
Chromosome: 5 OMIM NUMBER: 604683 OMIM Information: Genomic
Sequence (SEQ ID NO: 11): SNP Information Context (SEQ ID NO: 28):
AATAGGCTTTAACTCTTTATGACAAAATTATGTAAAAAACTCTAGGGTTTAAAATACAT
TATTTGTATAGAACTGTAAGTCCAGAGCAAACCTAAGACACR
AGACAAATGAAATAAAAGAGTAAATAAAAGCACTGATCCAAATTCATGCTTTGGTGTG
GTGTGATTCATTGCATTCCAAAAGTCAGGATGTAGACTGATT Celera SNP ID:
hCV29575948 Public SNP ID: rs10069772 SNP Chromosome Position:
132068587 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 22365 SNP Source: dbSNP; HapMap Population (Allele,
Count): Caucasian (A, 16|G, 104) SNP Type: INTRON Context (SEQ ID
NO: 29):
ACAGTTGCTGAGCTGTCAAGATATATCATCATACACTAAAGGAACAACTAAAATAGCTT
GTTATTATGTCAAACTCAGGACCCGAAGGCTCCCTAAGTCAR
AGTAAACATGCCAAGTGTCAAATATAAGTAGAAATACTACCAAATAATAAAGCTGGAA
TATGGCTTCCAATTGATTATTTTTGCTAATAATGTCTAATAA Celera SNP ID:
hCV31237680 Public SNP ID: rs12186803 SNP Chromosome Position:
132067968 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 21746 SNP Source: dbSNP; HapMap Population (Allele,
Count): Caucasian (G, 101|A, 19) SNP Type: TRANSCRIPTION FACTOR
BINDING SITE; INTRON Context (SEQ ID NO: 30):
TCACCCTCTTCATCATCATCTTCCTCTGACCCACTGATATCAGAGCCTGATATTTCTTCTC
CTTGGACAGAAATTTAATACAATGTTTTTTATCCTGTACS
AAGTCATTAGCTATTTAGGAAATACCTATATCAGCTTTCTTCCTCAGATTTTTGTTACTG
CAAACAACAAATTTAAATACTATTTAAATGCTCCTAGAAA Celera SNP ID: hCV11818501
Public SNP ID: rs41564665 SNP Chromosome Position: 132074688 SNP in
Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 28466 Related
Interrogated SNP: hCV16176374 (Power = .6) SNP Source: Applera
Population (Allele, Count): Caucasian (C, 30|G, 10) African
American (C, 14|G, 20) total (C, 44|G, 30) SNP Type: INTRON SNP
Source: dbSNP; Celera; HapMap Population (Allele, Count): Caucasian
(G, 34|C, 86) SNP Type: INTRON Context (SEQ ID NO: 31):
AAGGGTGTTCTAAAGCTGGATTGTGATGATGGTTTCACAACTGTATATATTTACTACACT
CATCAAACTGCACAGCTGCAATATGTGAATTTATGGCACAK
TAATTATGTCTCAATAAGGGAGTTTTTTAAAAAGTAAAGATTCACTTACCATTGTAGCCT
TCAAGTACAGAATCAATAATAGGTCTTGCAGTTAAGTTAT Celera SNP ID: hCV2558119
Public SNP ID: rs9784600 SNP Chromosome Position: 132097746 SNP in
Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 51524 Related
Interrogated SNP: hCV16176374 (Power = .51) SNP Source: dbSNP;
Celera Population (Allele, Count): Caucasian (G, 95|T, 21) SNP
Type: INTRON Context (SEQ ID NO: 32):
ATTAATGGAAGAGAGTTCTGAAATAAATATTTATGGTAAAAAGGTTTGAAATGTAGGCC
ATTATAATATGTCCATTTCATTTGCATATTATCTATATTCTK
ATCATAATAAACAGTCTTAATTCACACGTGGCAACAAATCCCCCACAACAGAGTGAGA
ATGAGAATACATTTTATAAAGAAAAAGAACTAAATTTAAAAA Celera SNP ID:
hCV2558124 Public SNP ID: rs10036532 SNP Chromosome Position:
132073714 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 27492 Related Interrogated SNP: hCV16176374 (Power = .6)
SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):
Caucasian (G, 33|T, 81) SNP Type: TRANSCRIPTION FACTOR BINDING
SITE; INTRON Context (SEQ ID NO: 33):
TTTCCTTTTAAAAGGGTGAAAGATAGCCTATTTTTAATATTTAATAACATCTAAAATATT
GAAGTCATAAAACTAAAATCTTAATAACATTGAGTAATAAW
AGTCTCAAAACATTATATACTGATATAACCTTTTTATAAATTCTAAAATACATATTTCTT
AGGAATGCATGCAGATGAAATAAAACTAAATGAAAATGAA Celera SNP ID: hCV8932022
Public SNP ID: rs1468215
SNP Chromosome Position: 132064388 SNP in Genomic Sequence: SEQ ID
NO: 11 SNP Position Genomic: 18166 Related Interrogated SNP:
hCV16176374 (Power = .6) SNP Source: dbSNP; HapMap; HGBASE
Population (Allele, Count): Caucasian (T, 34|A, 86) SNP Type:
TRANSCRIPTION FACTOR BINDING SITE; INTRON Context (SEQ ID NO: 34):
TCTGAGGTACTCAAAAGGTGCAAGTGGATTCAGAGGAAATCAGAAACAAATCATCTCA
GGCAATACCTGATGCATATGTAGGGACTTATGGAAATGCTACR
TTAATGTATTATATTTATTGCAATTTTGCCTAGCCCATCTAACTATGTGTTTCTAACAAG
GAACATCACATTGAACATATCATATAATGTAACATAGCAT Celera SNP ID: hCV11740439
Public SNP ID: rs2023823 SNP Chromosome Position: 132060705 SNP in
Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 14483 Related
Interrogated SNP: hCV16176374 (Power = .6) SNP Source: dbSNP;
HapMap; HGBASE Population (Allele, Count): Caucasian (A, 34|G, 82)
SNP Type: INTRON Context (SEQ ID NO: 35):
TTAAAAATTATTATTTTAATGCTATTGCCTACTTTTTTATTGTTGATATGATCAACTCCAT
TAACTAGATTATAAAAAGAAATGTCATAAGAGCAAAAATR
AACTGAAATGTATTAACAACAGTATTATCATAGAATCCAGCAATTCCATTGCTGGGTAC
ATACCCCAAAAATGGTAAAACAAGAATTCAAACAGGTATTA Celera SNP ID:
hCV11818497 Public SNP ID: rs4266392 SNP Chromosome Position:
132077154 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 30932 Related Interrogated SNP: hCV16176374 (Power = .6)
SNP Source: dbSNP; Celera; HapMap; HGBASE Population (Allele,
Count): Caucasian (G, 35|A, 85) SNP Type: TRANSCRIPTION FACTOR
BINDING SITE; INTRON Context (SEQ ID NO: 36):
AAGGAAAACTGGCCAAATTTGAATAAAGTCCACAGATTAGTTAATAAGACTATATCAAT
GTAAATCTCCTGGTTTCAATAACTGTTGTATGCTTATAAAAR
ATGTTAACATGAGGTGAAGCTGGGTGAAGGGTAGATAGGAACTCTCCATATCATGTTTG
CAAGTTGCATATAGCCTACAATAATTTTTAAGTTTAAAAAT Celera SNP ID:
hCV11818498 Public SNP ID: rs4425499 SNP Chromosome Position:
132076961 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 30739 Related Interrogated SNP: hCV16176374 (Power = .6)
SNP Source: dbSNP; Celera; HapMap; HGBASE Population (Allele,
Count): Caucasian (A, 34|G, 86) SNP Type: INTRON Context (SEQ ID
NO: 37): GGATTGTATCCTGGACCAGGAAAAAGAGGCACTGGAAGGAAAACTGGCCAAATTTGAA
TAAAGTCCACAGATTAGTTAATAAGACTATATCAATGTAAATY
TCCTGGTTTCAATAACTGTTGTATGCTTATAAAAAATGTTAACATGAGGTGAAGCTGGG
TGAAGGGTAGATAGGAACTCTCCATATCATGTTTGCAAGTT Celera SNP ID:
hCV11818499 Public SNP ID: rs2897442 SNP Chromosome Position:
132076926 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 30704 Related Interrogated SNP: hCV16176374 (Power = .6)
SNP Source: dbSNP; Celera; HapMap; HGBASE Population (Allele,
Count): Caucasian (C, 35|T, 85) SNP Type: INTRON Context (SEQ ID
NO: 38):
AATGTTCACCACACACAGGACATTCAGTATTCCAATTACAGAATGGACTTTAAATTTAT
GGGTACATTTTTATCGCCACCTCAAGAGTACTCCACCTTCAS
TCACCCCTACTCTATACACAGCTTTGTCATTTAAACTAGGATTTAACAAAACTTATTAAA
ATAATATTAATTTAATAAATACTAACTTATAAAGTCTCAA Celera SNP ID: hCV11818506
Public SNP ID: rs17690965 SNP Chromosome Position: 132058566 SNP in
Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 12344 Related
Interrogated SNP: hCV16176374 (Power = .6) SNP Source: dbSNP;
Celera; HapMap Population (Allele, Count): Caucasian (C, 31|G, 69)
SNP Type: MICRORNA; UTR3; INTRON Context (SEQ ID NO: 39):
TAGATTACAGTAATTTCCACTGATTATTTGATTAACAGAAAGGTCTAATGAAGAATTTTT
AAAGACACAAGTTCTCCCAATACATCCGATTTCCCAACCGK
ATTAAGGGCTTTTTTTTTTTTCCAGAAAATAAAATTATTACATAAAATGAAGTATACCTG
TACAGTAACAAACTTACATTCCTTCTATTAGTAGATTTTT Celera SNP ID: hCV15751509
Public SNP ID: rs2299009 SNP Chromosome Position: 132070712 SNP in
Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 24490 Related
Interrogated SNP: hCV16176374 (Power = .6) SNP Source: dbSNP;
HapMap; HGBASE Population (Allele, Count): Caucasian (G, 35|T, 85)
SNP Type: INTRON Context (SEQ ID NO: 40):
GGCCAGGATGGTCTCAATCTCTTGACCTCGTGATCCACCTGCCTCAACCTCCCAAAGTG
CTGGGATTACAGGGGTGAGCCACCACACCCGGCCCAGCAGTW
GTTTTTCTAAAACACAAATAGGCCAGGTGCAGTGGCTCACGCCTGTAATCCCGGCACTT
TGGGAGACTGAGATGGGAGCTTCGCTTGAACCCAAAAGTTC Celera SNP ID:
hCV15793498 Public SNP ID: rs2406539 SNP Chromosome Position:
132051175 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 4953 Related Interrogated SNP: hCV16176374 (Power = .7)
SNP Source: dbSNP; HapMap; HGBASE Population (Allele, Count):
Caucasian (A, 29|T, 77) SNP Type: TRANSCRIPTION FACTOR BINDING
SITE; INTERGENIC; UNKNOWN Context (SEQ ID NO: 41):
AGAGAATAGCAGCCACTCACTTTAGACAGGACTGCTCACCACTGCCAATTTTTCTCCTA
CGCTGGGGACAAATGTCTTACCATTTATCATCACACTTGCAY
TGTCATTTTATTAAAAATGGAAAAAAAGATACATCTAAAGGGACTCATGTTTCTTAGAA
CTGATTTGCTTCACTACAATATGCTTGGCATGTGTTGGTAT Celera SNP ID:
hCV15955623 Public SNP ID: rs2237059 SNP Chromosome Position:
132061511 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 15289 Related Interrogated SNP: hCV16176374 (Power = .51)
SNP Source: dbSNP; HapMap; ABI_Val; HGBASE Population (Allele,
Count): Caucasian (C, 96|T, 20) SNP Type: INTRON Context (SEQ ID
NO: 42): ACCAAGAGACAGCCGTATGAGAGTTGCATAGATTGGCGCTACTAAAAAGAAACAAAAT
TTTGCTCGGCATGGAAAATGATTTGTGGTATCTTTCATTCATM
TATGCTCTCTACATGGTAAATAATCAAAGTGGAATGGTTTTCAAGAAACCTAAAAAATC
CAGTCTCTACAGGGTAAAGTGCCATACCAAATTTGCTTCTA Celera SNP ID:
hCV16164369 Public SNP ID: rs41564561 SNP Chromosome Position:
132084046 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 37824 Related Interrogated SNP: hCV16176374 (Power = .6)
SNP Source: dbSNP; HapMap; ABI_Val; HGBASE Population (Allele,
Count): Caucasian (C, 35|A, 85) SNP Type: INTRON Context (SEQ ID
NO: 43):
AAAATAGCTACACTGGAGACAAAAATCCAAGCTTTTAATTACTATTCAATTTTCCTATTT
TATATATCCTAGGAAAAAACAGAAATTTAAATCATGAATTM
ATCTCAATTCAATAATACTCACTGGGCTTTAAGAAGATCTTTTTCCCGTTTCTCTAATTC
AGCTCTAGCCTTGTTTCTTTCTTCTTCTTCCATGTCGAGC Celera SNP ID: hCV16177653
Public SNP ID: rs2285700 SNP Chromosome Position: 132067031 SNP in
Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 20809 Related
Interrogated SNP: hCV16176374 (Power = .6) SNP Source: dbSNP;
HapMap; ABI_Val; HGBASE Population (Allele, Count): Caucasian (C,
34|A, 86) SNP Type: TRANSCRIPTION FACTOR BINDING SITE; INTRON
Context (SEQ ID NO: 44):
ACTGGGTTTCTAAATACCATTCTCCTACAGAAGGGACCAGAGAGAAGTGAATGATTCTA
AGATTGGGCAAGGAAGACACAAGATAAACCTAAAACCTTTTR
TAGTGCCAAAAAGTAATCAAATGCTCAAAAAAACTGATGAGCACATGCTGAAAGAATA
CAGGAACTACTCTGAAGGATCTCATAATAGCCAAAGCTGGAA Celera SNP ID:
hCV26478846 Public SNP ID: rs6864565 SNP Chromosome Position:
132075870 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 29648 Related Interrogated SNP: hCV16176374 (Power = .6)
SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):
Caucasian (G, 34|A, 86) SNP Type: TRANSCRIPTION FACTOR BINDING
SITE; INTRON Context (SEQ ID NO: 45):
CAGAGTCTTGGGAGAAGAAATTTCTGAAAAATATTTTTTTCTTCGGGCTTAGAAACAAT
GACATCTTGGTAGTAATGAGCACAGCTAGTGCCCAAAACTGS
GTTTCTAAATACCATTCTCCTACAGAAGGGACCAGAGAGAAGTGAATGATTCTAAGATT
GGGCAAGGAAGACACAAGATAAACCTAAAACCTTTTGTAGT Celera SNP ID:
hCV26478847 Public SNP ID: rs6864396 SNP Chromosome Position:
132075774 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 29552 Related Interrogated SNP: hCV16176374 (Power = .6)
SNP Source: dbSNP; Celera; HapMap Population (Allele, Count):
Caucasian (G, 34|C, 86) SNP Type: INTRON Context (SEQ ID NO: 46):
TCTTCCTAGTCCAACTTTAAGTCTCTAAGCTGTCTGTTCCTTCTAGTTTCTGATTAGCCAG
AGTTCAGCCAAACGAAAATATGTTTTGATGTTTTGTATGS
TCACTGCACACCTGGGTACTTACTAGGCAACGTGAATAAGAGGACACACATTTGCTCCC
TCAGTTTATACCAATCACGAGTGCAAGCAAAACAGCTGAGA Celera SNP ID:
hCV26478954 Public SNP ID: rs4426908 SNP Chromosome Position:
132050617 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 4395 Related Interrogated SNP: hCV16176374 (Power = .7)
SNP Source: dbSNP; Celera; HGBASE Population (Allele, Count):
Caucasian (C, 32|G, 88) SNP Type: TRANSCRIPTION FACTOR BINDING
SITE; INTERGENIC; UNKNOWN Context (SEQ ID NO: 47):
AATAGATAAAATTAAAAATTGCACATAAAGAAATATTTTATTTCTTTTAAATTATAAGC
TCACATTATGATTATTTATAAATTCTTAATCAAAGAACTCCY
TTTTAAAAAATCCAGAACTGCATTAGTAGGTAATTTCTAAGAGAACCAACCTCTGACTT
TGCAGCCATCAGCATAGTCCAAACTTTCTTTAACTTCTTGG Celera SNP ID:
hCV27472356 Public SNP ID: rs3213639 SNP Chromosome Position:
132066098 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 19876 Related Interrogated SNP: hCV16176374 (Power = .6)
SNP Source: dbSNP; HapMap; HGBASE Population (Allele, Count):
Caucasian (C, 34|T, 86) SNP Type: INTRON Context (SEQ ID NO: 48):
TGGTGATGAAACTGAATCAAAGACAATTCATTTCTGGTCATACAGTTTCTTAGAAACAT
ACATTCCTTCAGAAAACCAATAACACTTTTCACAGAATTGGW
CTGAGGCTCTCCTAGAACCTTTCCGTCATTCTTAACTTCCTTCCCAAAGAACTACAGAAG
AAGAGTGTAAATCATAAGAGTGTATAAATTGTTAATGTCT Celera SNP ID: hCV30585769
Public SNP ID: rs10062446 SNP Chromosome Position: 132068273 SNP in
Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 22051 Related
Interrogated SNP: hCV16176374 (Power = .6) SNP Source: dbSNP;
HapMap Population (Allele, Count): Caucasian (T, 34|A, 86) SNP
Type: INTRON Context (SEQ ID NO: 49):
TCTAAAAAGGGATGGGGGAGGGGAGCAGGTGGAGAGGAATATCTGATCTGTCATATTC
TTTAGTCAGAGCCATAAACGTGTTTGGGTGAGACAATCTGATS
TTCTGATAACGTTGATAAAAGTCACTTGAAGATTGGGTCACAGGAAGCCCAAGATAAAT
GCTGAGAGGAAACAGGTTCTTTTTGAAGTAGCCTCTTCGTA Celera SNP ID:
hCV31237737 Public SNP ID: rs11242122 SNP Chromosome Position:
132052607 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 6385 Related Interrogated SNP: hCV16176374 (Power = .7)
SNP Source: dbSNP; HapMap; ABI_Val Population (Allele, Count):
Caucasian (C, 31|G, 89) SNP Type: INTERGENIC; UNKNOWN Context (SEQ
ID NO: 50):
AAACAAGTGATCCACCCACCTCAGCCTCCCAAAGTGCTGGGATTACAGGTGTGAGCCAC
CGCGACCAGACTTTTCACCTCTAATTTCTAATTGCTATTAGY
TGCATCACCAGTACTAGGTTTGAGGCATCTGTATAATATCGCTGAAGCTTCCTACTCTTT
AGACTAAAAATGTGACACAATTACTAAAAAGAATACAATT Celera SNP ID: hCV31237618
Public SNP ID: rs11242127 SNP Chromosome Position: 132083403 SNP in
Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 37181 Related
Interrogated SNP: hCV16176374 (Power = .6) SNP Source: dbSNP
Population (Allele, Count): Caucasian (C, 35|T, 85) SNP Type:
INTRON Context (SEQ ID NO: 51):
TACACTTAAAACAGGGCACATGCTGGGCACAGTGGCTCACGCCTGTAACCTCAGCACTT
TGGGAGCCCAAGGCGGGAGGACTGCTTGAAGCCAGGAGTTCY
AAACCAACCTGGGCAACTTAGCAAGCTCCTATCTCTACAAAAAATTAAAAAATTAGCCA
AGTGTAGTGGCAGACACCTGTGGTCCCAGCTACTTGGGAGG Celera SNP ID:
hCV31237741 Public SNP ID: rs11747814 SNP Chromosome Position:
132052065 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 5843 Related Interrogated SNP: hCV16176374 (Power = .7)
SNP Source: dbSNP; HapMap Population (Allele, Count): Caucasian (C,
31|T, 89) SNP Type: INTERGENIC; UNKNOWN Context (SEQ ID NO: 52):
TGTGGGGAAACAGAGGGCTGGAGTAGTTGGTCAGGACACAGTGTAGTAAGAAAAGATA
GCCTTGGATGTGATGGCATATATGAAAACGGTTCCTCAACTAW
TACTACTCTATTCAGTTAACCTCAACTTTTCTCAGACTTTTTTTTGTGAAAATAATCATAA
CACACTTTTCAGACTTTTCCGTGAAAATAAATGAATCAT Celera SNP ID: hCV31237596
Public SNP ID: rs3798129 SNP Chromosome Position: 132091459 SNP in
Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 45237 Related
Interrogated SNP: hCV16176374 (Power = .51) SNP Source: dbSNP;
HapMap; ABI_Val; HGBASE Population (Allele, Count): Caucasian (T,
99|A, 21) SNP Type: INTRON Context (SEQ ID NO: 53):
TTCTATTAAGATTTGGTCTTTTTCTATTAATTGGTTCATAAGAATGTAATTGATTTTTGAA
GTTTTGTTGTTTGATTTCCTTGGGTTTGATATATCTATCR
TCAAGTCACAGAAACTTATAAAAATTTTTCATTTCCTATTTCTCATCTTTTACCTCTAATC
CCTCTTTTTTTCTTTTTTTTTTGGTTGCTGTGTTGCCCA Celera SNP ID: hCV31237619
Public SNP ID: rs4705965 SNP Chromosome Position: 132083026 SNP in
Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 36804 Related
Interrogated SNP: hCV16176374 (Power = .6) SNP Source: dbSNP;
HGBASE Population (Allele, Count): Caucasian (G, 85|A, 35) SNP
Type: INTRON Context (SEQ ID NO: 54):
ATTTATATGACATTTCAAGAAAAGGCAAAATTATAGTGACAGAAAGCAGATCAATAGTT
GCTTGGGGGTGGGTCTGCAAATGGGCATAAAGGAAATTTTGR
GGATGACAAGGGTGTTCTAAAGCTGGATTGTGATGATGGTTTCACAACTGTATATATTT
ACTACACTCATCAAACTGCACAGCTGCAATATGTGAATTTA Celera SNP ID:
hCV30117349 Public SNP ID: rs9784675 SNP Chromosome Position:
132097638 SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position
Genomic: 51416 Related Interrogated SNP: hCV16176374 (Power = .51)
SNP Source: dbSNP; HapMap; ABI_Val Population (Allele, Count):
Caucasian (A, 99|G, 21) SNP Type: INTRON Gene Number: 3 Gene
Symbol: IL4-3565 Gene Name: interleukin 4 Chromosome: 5 OMIM
NUMBER: 147780 OMIM Information: Genomic Sequence (SEQ ID NO: 12):
SNP Information Context (SEQ ID NO: 55):
TATTCTAAATACTTGAAAACTTTAAATGTATTCATTCCTCAGAGCAACTTCATGAGACAG
GGACAGCTATGACCCCTATTTCACAGATGAGGCTGAGTAGM
GTGCCCAAGGTCACACAGCCAGGAGGCACAGCAGCCAGGCCTGACAGACCACCTGGGC
CCAGCGTCCGCTCTCTTAGCCACCGTGTACTATAGCAGCCTC Celera SNP ID:
hCV2259917 Public SNP ID: rs762534 SNP Chromosome Position:
132032655 SNP in Genomic Sequence: SEQ ID NO: 12 SNP Position
Genomic: 5383 SNP Source: dbSNP; Celera; HapMap; ABI_Val; HGBASE
Population (Allele, Count): Caucasian (C, 111|A, 9) SNP Type:
INTERGENIC; UNKNOWN Context (SEQ ID NO: 56):
CACAGCAGGGAGAGTGCTGTGTTATGCGAGGAGGTTGGAGAAATCCTCCCCATGAGAT
AAGATGGGAACAGAGATCGGGACGAAACAAGGGGAGGGGACAM
CCATGCACAGATCGGGGCAAAGTCATCAAGGGAAAGGGAACTGCAGGTGCTAAGGTCT
TGAGCAAGAGCGAGCTGGGGATGCCCTTCCCAGCACTCACGG Celera SNP ID:
hCV16176063 Public SNP ID: rs2243211 SNP Chromosome Position:
132029321 SNP in Genomic Sequence: SEQ ID NO: 12 SNP Position
Genomic: 2049 SNP Source: dbSNP; HapMap; HGBASE Population (Allele,
Count): Caucasian (C, 108|A, 12) SNP Type: TFBS SYNONYMOUS;
INTERGENIC; UNKNOWN Context (SEQ ID NO: 57):
GGCAGACACACTCAGCAGCCAGAGCTAGACAGGCAGGTGGTAGGAGTCCAGGGCCACG
GCAGGGATGGAGTGTCGCCCCCTCGCTGCGATACCAGAGCAAS
TAAAACGTTAAGGCCTTGCACTAAAGCTGCCCTTAGGATGCATTCTTTTAAAGTTTTTCC
ATTTAATGCAGACTCTTTTCAATTCTTATTTTATCCTTGT Celera SNP ID: hCV16176374
Public SNP ID: rs2227282 SNP Chromosome Position: 132041078 SNP in
Genomic Sequence: SEQ ID NO: 12 SNP Position Genomic: 13806 SNP
Source: dbSNP; HapMap; HGBASE Population (Allele, Count): Caucasian
(G, 32|C, 86) SNP Type: INTRON Context (SEQ ID NO: 58):
GGGTGTCTATGAAGTCAAGGCTGTCTGAGGAACAGCAAAGTGGGAAGAAGCAAGCTGG
CTGGCTGATGAAGGGTTTCTTGGGTGGACAAGTAGTTGGAGCK
ATTTCCTATTTACCAAAGAGAGCTAAAGTTCATAATTCTACAGAGAGTTCCATAATGAA
CCTCAAATACCTCTGTTTTTTGAAGGAGTTTCTCATATACA Celera SNP ID:
hCV11818513 Public SNP ID: rs2227284 SNP Chromosome Position:
132040624 SNP in Genomic Sequence: SEQ ID NO: 12 SNP Position
Genomic: 13352 Related Interrogated SNP: hCV16176374 (Power = .7)
SNP Source: dbSNP; Celera; HapMap; HGBASE Population (Allele,
Count): Caucasian (T, 32|G, 86) SNP Type: INTRON Context (SEQ ID
NO: 59):
GGCCAGGATGGTCTCAATCTCTTGACCTCGTGATCCACCTGCCTCAACCTCCCAAAGTG
CTGGGATTACAGGGGTGAGCCACCACACCCGGCCCAGCAGTW
GTTTTTCTAAAACACAAATAGGCCAGGTGCAGTGGCTCACGCCTGTAATCCCGGCACTT
TGGGAGACTGAGATGGGAGCTTCGCTTGAACCCAAAAGTTC Celera SNP ID:
hCV15793498 Public SNP ID: rs2406539 SNP Chromosome Position:
132051175 SNP in Genomic Sequence: SEQ ID NO: 12 SNP Position
Genomic: 23903 Related Interrogated SNP: hCV16176374 (Power = .7)
SNP Source: dbSNP; HapMap; HGBASE Population (Allele, Count):
Caucasian (A, 29|T, 77) SNP Type: TRANSCRIPTION FACTOR BINDING
SITE; INTERGENIC; UNKNOWN Context (SEQ ID NO: 60):
TCTTCCTAGTCCAACTTTAAGTCTCTAAGCTGTCTGTTCCTTCTAGTTTCTGATTAGCCAG
AGTTCAGCCAAACGAAAATATGTTTTGATGTTTTGTATGS
TCACTGCACACCTGGGTACTTACTAGGCAACGTGAATAAGAGGACACACATTTGCTCCC
TCAGTTTATACCAATCACGAGTGCAAGCAAAACAGCTGAGA Celera SNP ID:
hCV26478954 Public SNP ID: rs4426908 SNP Chromosome Position:
132050617 SNP in Genomic Sequence: SEQ ID NO: 12 SNP Position
Genomic: 23345 Related Interrogated SNP: hCV16176374 (Power = .7)
SNP Source: dbSNP; Celera; HGBASE Population (Allele, Count):
Caucasian (C, 32|G, 88) SNP Type: TRANSCRIPTION FACTOR BINDING
SITE; INTERGENIC; UNKNOWN Context (SEQ ID NO: 61):
TCTAAAAAGGGATGGGGGAGGGGAGCAGGTGGAGAGGAATATCTGATCTGTCATATTC
TTTAGTCAGAGCCATAAACGTGTTTGGGTGAGACAATCTGATS
TTCTGATAACGTTGATAAAAGTCACTTGAAGATTGGGTCACAGGAAGCCCAAGATAAAT
GCTGAGAGGAAACAGGTTCTTTTTGAAGTAGCCTCTTCGTA Celera SNP ID:
hCV31237737 Public SNP ID: rs11242122 SNP Chromosome Position:
132052607 SNP in Genomic Sequence: SEQ ID NO: 12 SNP Position
Genomic: 25335 Related Interrogated SNP: hCV16176374 (Power = .7)
SNP Source: dbSNP; HapMap; ABI_Val Population (Allele, Count):
Caucasian (C, 31|G, 89) SNP Type: INTERGENIC; UNKNOWN Context (SEQ
ID NO: 62):
TACACTTAAAACAGGGCACATGCTGGGCACAGTGGCTCACGCCTGTAACCTCAGCACTT
TGGGAGCCCAAGGCGGGAGGACTGCTTGAAGCCAGGAGTTCY
AAACCAACCTGGGCAACTTAGCAAGCTCCTATCTCTACAAAAAATTAAAAAATTAGCCA
AGTGTAGTGGCAGACACCTGTGGTCCCAGCTACTTGGGAGG Celera SNP ID:
hCV31237741 Public SNP ID: rs11747814 SNP Chromosome Position:
132052065 SNP in Genomic Sequence: SEQ ID NO: 12 SNP Position
Genomic: 24793 Related Interrogated SNP: hCV16176374 (Power = .7)
SNP Source: dbSNP; HapMap Population (Allele, Count): Caucasian (C,
31|T, 89) SNP Type: INTERGENIC; UNKNOWN Gene Number: 4 Gene Symbol:
IL5-3567 Gene Name: interleukin 5 (colony-stimulating factor,
eosinophil) Chromosome: 5 OMIM NUMBER: 147850 OMIM Information:
Genomic Sequence (SEQ ID NO: 13): SNP Information Context (SEQ ID
NO: 63):
TCTGCCACAGGCAGATCCGGGTGATGGTCAGCTTGGCTGTGTGAATGGGACTCAGTGGA
AAGGACTGCCTTCTGTGGGGTGCAGAACAGGGGCATTACTTK
TTGAATGTCCTGATGAGCCACACACAGATCTAACCATGCTGTATCAGGAGAGAGTCAGT
GCTAGTCATGCACAGTCATGCACAAGGGAACTTGCAAACAC Celera SNP ID:
hCV28028637 Public SNP ID: rs4143832 SNP Chromosome Position:
131890876 SNP in Genomic Sequence: SEQ ID NO: 13 SNP Position
Genomic: 20000 SNP Source: dbSNP; HapMap; HGBASE Population
(Allele, Count): Caucasian (T, 17|G, 103) SNP Type: INTRON Context
(SEQ ID NO: 64):
AGTTCAGCTACAGAGACGGAGGCAATGTGAACTACCATTTAGATTTTTTAAAATCCACG
TTATTTTAGGGAAATAGAAAGAAATAAACAATTAGTACTTTS
ATTTTTAAATAATTACTGGTTGGTAATTTTATAATTTAAAAAAAGCACTTTGATTAATAT
TGAAAAGTTACATTGGTGGGTAACATCCATCCTTTTGCCC Celera SNP ID: hCV11818554
Public SNP ID: rs12652920 SNP Chromosome Position: 131913139 SNP in
Genomic Sequence: SEQ ID NO: 13 SNP Position Genomic: 42263 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
Celera; HapMap; ABI_Val Population (Allele, Count): Caucasian (G,
93|C, 25) SNP Type: TFBS SYNONYMOUS; INTRON Gene Number: 5 Gene
Symbol: LOC441108-441108 Gene Name: hypothetical gene supported by
AK128882 Chromosome: 5 OMIM NUMBER: OMIM Information: Genomic
Sequence (SEQ ID NO: 14): SNP Information Context (SEQ ID NO: 65):
TCTGCCACAGGCAGATCCGGGTGATGGTCAGCTTGGCTGTGTGAATGGGACTCAGTGGA
AAGGACTGCCTTCTGTGGGGTGCAGAACAGGGGCATTACTTK
TTGAATGTCCTGATGAGCCACACACAGATCTAACCATGCTGTATCAGGAGAGAGTCAGT
GCTAGTCATGCACAGTCATGCACAAGGGAACTTGCAAACAC Celera SNP ID:
hCV28028637 Public SNP ID: rs4143832 SNP Chromosome Position:
131890876 SNP in Genomic Sequence: SEQ ID NO: 14
SNP Position Genomic: 126304 SNP Source: dbSNP; HapMap; HGBASE
Population (Allele, Count): Caucasian (T, 17|G, 103) SNP Type:
INTRON Context (SEQ ID NO: 66):
ATCTGACTTCCCCCTAGCCGACTTAACCCTCAGGTGGGCCCCCTTCTCATCATTATCAGG
CTCTGAATCCCCACACTATTCCCTGGCGTGGACACTCTGCK
TCTGAGCTGGATCCCCCCTATTTGTGGATTCCTCTTTCATCCTGCTGGAACTCTGATACC
ATTGGACTCTTGAAACTCTGTCTATGCCAAGCTGTTTCCC Celera SNP ID: hCV2549985
Public SNP ID: rs2299015 SNP Chromosome Position: 131929396 SNP in
Genomic Sequence: SEQ ID NO: 14 SNP Position Genomic: 164824
Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:
dbSNP; Celera; HapMap; HGBASE Population (Allele, Count): Caucasian
(T, 89|G, 21) SNP Type: INTRON Context (SEQ ID NO: 67):
CATTAACAGAATAAAAAAGAAATATCATATGAACACCAATAGATACAGAAAACGCATT
TCAATTTAATAGTCTTTCGTGGTAAAAACCCTCAGCATAACTR
ATGGAGGAATATTAATTCCTGAATAATTCAGTCCAAAATCCGTTAGGTGTGGCTGAGTG
AGGAAGGCATCCACAAAAACAAGCTGTGACAGCCTGGTGGG Celera SNP ID:
hCV11818538 Public SNP ID: rs2706348 SNP Chromosome Position:
131933709 SNP in Genomic Sequence: SEQ ID NO: 14 SNP Position
Genomic: 169137 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: dbSNP; Celera; HapMap; ABI_Val; HGBASE Population
(Allele, Count): Caucasian (G, 94|A, 26) SNP Type: INTRON Context
(SEQ ID NO: 68):
AGTTCAGCTACAGAGACGGAGGCAATGTGAACTACCATTTAGATTTTTTAAAATCCACG
TTATTTTAGGGAAATAGAAAGAAATAAACAATTAGTACTTTS
ATTTTTAAATAATTACTGGTTGGTAATTTTATAATTTAAAAAAAGCACTTTGATTAATAT
TGAAAAGTTACATTGGTGGGTAACATCCATCCTTTTGCCC Celera SNP ID: hCV11818554
Public SNP ID: rs12652920 SNP Chromosome Position: 131913139 SNP in
Genomic Sequence: SEQ ID NO: 14 SNP Position Genomic: 148567
Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:
dbSNP; Celera; HapMap; ABI_Val Population (Allele, Count):
Caucasian (G, 93|C, 25) SNP Type: TFBS SYNONYMOUS; INTRON Context
(SEQ ID NO: 69):
AAAATATACTGTGCCAGCTAATGAAAAGAAAGCTGAAGTGACCATATTAATACCAGAC
AGAAGACATCAGAACTAGGGAAAATGAAACATTTTATGATGAK
AAGAGGTCAATTTAATGCAAGGACACAAAAATTCTAAATGTAAAACTTCCAAATATATG
AGGCAGAAACCTATGGAACAGAATGGAGAAATACACAAATC Celera SNP ID:
hCV16274080 Public SNP ID: rs2706347 SNP Chromosome Position:
131933016 SNP in Genomic Sequence: SEQ ID NO: 14 SNP Position
Genomic: 168444 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: dbSNP; HGBASE Population (Allele, Count): Caucasian (G,
92|T, 26) SNP Type: TRANSCRIPTION FACTOR BINDING SITE; INTRON
Context (SEQ ID NO: 70):
GTATGCCAGTCTTCCTTATCCTGCGTAGGCTCTTGACTCTTCATTCTGACTCCCTCATGG
GATGCTTTTCCATTCTGTATACACTTTGACTTCTGGTGCTR
GATCATGTCCTCATTCCCCGCCCTTCTCTGATACCAGGTGGCCTCTTGCAGGGATGCCCA
CTGTACTCTGACCTGAATCTCCCCAGATCTGTGTCACTGA Celera SNP ID: hCV16274083
Public SNP ID: rs2244012 SNP Chromosome Position: 131929124 SNP in
Genomic Sequence: SEQ ID NO: 14 SNP Position Genomic: 164552
Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:
dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):
Caucasian (A, 94|G, 26) SNP Type: INTRON Context (SEQ ID NO: 71):
CACACACACACACACACACACATATATATATAGTTTATTCGTTTTTAGTGGGGTCATGTG
CCTCTCTAGCCGCTCCCTGACCCCAGTTCCACTATGTTTTY
GTTACGTATTCTTCCAAGCTTTTTTCTGCTTATAAAACCATGTCTACGTGAGCACATAAA
TGCATTCACACATACATATTTTAGCACATTAATATAATTT Celera SNP ID: hCV16274086
Public SNP ID: rs2706338 SNP Chromosome Position: 131923748 SNP in
Genomic Sequence: SEQ ID NO: 14 SNP Position Genomic: 159176
Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:
dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):
Caucasian (C, 94|T, 26) SNP Type: INTRON Gene Number: 6 Gene
Symbol: P4HA2-8974 Gene Name: procollagen-proline, 2-oxoglutarate
4-dioxygenase (proline 4-hydroxylase), alpha polypeptide II
Chromosome: 5 OMIM NUMBER: 600608 OMIM Information: Genomic
Sequence (SEQ ID NO: 15): SNP Information Context (SEQ ID NO: 72):
TCCTACACACAGCTACTTCTCAGGGACTGCTGGTCCTAGAGCCTTAGGTGGGGCCTTTTC
CAACACTGTGTGCACTTCAAGCCCAGATCCGCCATTTTCTS
TTCATCTTCCCTGGGATGAGACAGCTTCTTGTTTAACTCTCCACACATAGAAGTTCTCAT
TATACATTCTCTTAGAGCTCCTGGTTTCTCCTGCAGGAGA Celera SNP ID: hCV559494
Public SNP ID: rs334902 SNP Chromosome Position: 131614458 SNP in
Genomic Sequence: SEQ ID NO: 15 SNP Position Genomic: 68256 SNP
Source: dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):
Caucasian (G, 44|C, 70) SNP Type: MICRORNA; UTR3; INTRON Context
(SEQ ID NO: 73):
GAGCACTCACAGCCGGGCTCCTCCCCTGGCACATGGCCAGCTGCCAATATGAAGCAGC
AATCTCAGAGTACGAGCTACCCACAGGCAAGAATAGTGCCTCS
GCCACCTCCTCTCTCTCGTCCCTCATTCTAGCCCCAGGCACGCTCCAGTCAGAAGCCAA
ACAGGCAGAAGGCACTCAAGGGATGAACTGAGATCAGCTGG Celera SNP ID: hCV2346958
Public SNP ID: rs157578 SNP Chromosome Position: 131589221 SNP in
Genomic Sequence: SEQ ID NO: 15 SNP Position Genomic: 43019 SNP
Source: dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):
Caucasian (G, 110|C, 8) SNP Type: INTRON Context (SEQ ID NO: 74):
AGCCTTAGGTGGGGCCTTTTCCAACACTGTGTGCACTTCAAGCCCAGATCCGCCATTTTC
TCTTCATCTTCCCTGGGATGAGACAGCTTCTTGTTTAACTM
TCCACACATAGAAGTTCTCATTATACATTCTCTTAGAGCTCCTGGTTTCTCCTGCAGGAG
AGGCACAGACTCCGTTGTTCCTAAGCAAGCCTATCTTCCC Celera SNP ID: hCV26479272
Public SNP ID: rs4594848 SNP Chromosome Position: 131614497 SNP in
Genomic Sequence: SEQ ID NO: 15 SNP Position Genomic: 68295 SNP
Source: dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):
Caucasian (C, 62|A, 58) SNP Type: MICRORNA; UTR3; INTRON Context
(SEQ ID NO: 75):
CCTAGTACCTCAAGCCAAAGCTGTTCCAAGATGAGGTCCAGGGGCCAGGATAGGAACC
TATTTCAGGTCTCTCCATGAGTGTCGGGCCTCCTGGTCACCTY
GGCCCCTACAATTCTATTAGGAGCAGAGCAATAGAGAATCGAGCTAAATCCTCCCTCCC
AATCATCAGTGATGGGATATGGCAGCAAATAGGTCTCTTTG Celera SNP ID:
hDV70977429 Public SNP ID: rs17618604 SNP Chromosome Position:
131570083 SNP in Genomic Sequence: SEQ ID NO: 15 SNP Position
Genomic: 23881 SNP Source: dbSNP; HapMap Population (Allele,
Count): Caucasian (C, 104|T, 14) SNP Type: INTRON Gene Number: 7
Gene Symbol: RAD50-10111 Gene Name: RAD50 homolog (S. cerevisiae)
Chromosome: 5 OMIM NUMBER: 604040 OMIM Information: Genomic
Sequence (SEQ ID NO: 16): SNP Information Context (SEQ ID NO: 76):
TTACAATTAGATTCCTGGGAAGCACAAACATTTAAAATGTTAGCAGGCAAAGGAAAAG
GAGCAAGTGAAGGAAACTGGGATGTGCCCAGGGAACCAGGGTK
AGAGCCAGATAGCTGTGGTGTCTAGGTGCCTTGGGAAAATAGTCTTCAAGGAGAAGGT
CAACAGTGTTTGGTGCTACGTAGAGGTAGAGTAAGATGAAGA Celera SNP ID:
hCV16154343 Public SNP ID: rs2897443 SNP Chromosome Position:
131957493 SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position
Genomic: 46964 SNP Source: dbSNP; Celera; HapMap; ABI_Val; HGBASE
Population (Allele, Count): Caucasian (G, 94|T, 26) SNP Type:
INTRON Context (SEQ ID NO: 77):
ACCACAGTAATAATTATTGCAAGCAAGATCTGTCAGTGGATACTAAAATCAGTAGGCAG
AAAGTTGAGAAGCAAGATATTTACATAGTCTCAACATTTCTY
TCCTAAGATACTTGTTAATTACAAAGACTAAAACAGTAACTTTACAGTGGAGAAACCTG
GCCAACACCATCTAAGCCAAGTGAATAAGGATTAACATCAT Celera SNP ID:
hCV29134417 Public SNP ID: rs6884762 SNP Chromosome Position:
131966629 SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position
Genomic: 56100 SNP Source: dbSNP; HapMap Population (Allele,
Count): Caucasian (C, 112|T, 6) SNP Type: INTRON Context (SEQ ID
NO: 78):
TTTTAAAAGAATTTTAGCCTCAGCCTGGTATCCTTTGAGAGTTACTAGAAGGTGAACAG
TGTTTTGATACAATTATATTTCATGGCCTTAAGAACTTTATY
ACTGAAGAAGTGATATAGAATTGGTAATCACACTGTAGTGATGGGCCTTAGTTATTCAG
TATTGAACATGCTTAGCCCCCATACATCTGCTAGCCTGCTG Celera SNP ID:
hCV15756644 Public SNP ID: rs2301713 SNP Chromosome Position:
131979895 SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position
Genomic: 69366 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: dbSNP; HapMap; ABI_Val; HGBASE Population (Allele,
Count): Caucasian (T, 91|C, 25) SNP Type: INTRON Context (SEQ ID
NO: 79):
GGCTGAGGAACTGGGGCATCTGGGTTGCTTCTGGCCAGACCACCAGGCTCTTGAATCCT
CCCAGCCAGAGAAAGAGTTTCCACACCAGCCATTGTTTTCCY
CTGGTAATGTCAGCCTCATCTGTTGTTCCTAGGCTTACTTGATATGTTTGTAAATGACAA
AAGGCTACAGAGCATAGGTTCCTCTAAAATATTCTTCTTC Celera SNP ID: hCV16164126
Public SNP ID: rs2074369 SNP Chromosome Position: 132001562 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 91033 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
HapMap; HGBASE Population (Allele, Count): Caucasian (T, 91|C, 25)
SNP Type: INTRON Context (SEQ ID NO: 80):
AAGAGCGTGAACTCTGGAGCTGGACTGGGTTAAAATCTTGGCTGCTTCATTTACTGGCT
GTTGTGACCCTGGACAAATCATTCTCTGTGTCTGTTTGCTCR
TTTGAAATATAGGACTGAAAATGATGGTACTGTCCTCATAGGGTCATTGAAAGGAGCAA
ATGAGTTGACTTTTAGAGCCTGGCACATAGAAAGTGCTTTT Celera SNP ID:
hCV25471631 Public SNP ID: rs2522394 SNP Chromosome Position:
131972028 SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position
Genomic: 61499 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: Applera Population (Allele, Count): Caucasian (A, 6|G,
34) African American (A, 26|G, 12) total (A, 32|G, 46) SNP Type:
INTRON SNP Source: dbSNP; HapMap; ABI_Val; HGBASE Population
(Allele, Count): Caucasian (G, 94|A, 26) SNP Type: INTRON Context
(SEQ ID NO: 81):
GTTCAAGACTCTTCTGAGCAGTGATACCAGCAATTTAGTTCAGTCCTAAAGAACTGAGG
GTCCTGGGAATTTAACCATGTCAGTGTAGTCTTTTTTACATY
GCTAGCATAAAAATGGGTGCCCTTTAAAGATTTTTTTAAGATTAAGAAACTAGAAGACA
GGAGGAGCCAAATCAGGACTGTAAGGTGGATGCCTAATGAT Celera SNP ID:
hCV2549970
Public SNP ID: rs10463893 SNP Chromosome Position: 131955938 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 45409 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
Celera; HapMap Population (Allele, Count): Caucasian (T, 93|C, 25)
SNP Type: INTRON Context (SEQ ID NO: 82):
AATGGAAGTAAGTCGCCTCACATCCTCACATCCTTTGTATGATGATCGCAGTAATGTTTG
CCTTTTTACCACTGGTGCAACATTTATTAGTTCATAAACCY
GCTTCCAAAGAACCTAAGGGCTTTTTGATGAAAGGTGACTGTGGTGGGAACAATGTTAG
GTTTTGACAGGCTACTTTTGCTTTTACAAACATTTCTCCTC Celera SNP ID: hCV2549979
Public SNP ID: rs12653750 SNP Chromosome Position: 131999801 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 89272 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
Celera; HapMap Population (Allele, Count): Caucasian (C, 94|T, 26)
SNP Type: INTRON Context (SEQ ID NO: 83):
GTAAAATAAAATTTTGATGTCAGTTCAGCTTAAGCTTCTAAATCATTCTCGCTGAACCAA
AGCTTCCAGTTGGTAAAAATCTAAGATCTGAGGAATAAAAS
CAACATAAGAAGCTGACTTTTGGTAAGCCTTAACAGTGATAGAAGAGGGACAAGGTGG
CAGTTCGATTCTCCTATTTTCCCCATAGACTGCAGGCCCCTT Celera SNP ID:
hCV2549980 Public SNP ID: rs2040703 SNP Chromosome Position:
132000157 SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position
Genomic: 89628 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: dbSNP; Celera; HapMap; HGBASE Population (Allele,
Count): Caucasian (C, 92|G, 26) SNP Type: INTRON Context (SEQ ID
NO: 84):
CAAGGTTGTCAAGCAGCTCTTGCATAAGGACTATGCTGGCAGAGAAAAAGGCAGTTTCC
CTGAGGTCAAAGGAGGTGTTTCAGGCACTCCTGGCTCCAGAY
AGTCCCTTTCTGGCAGAGAGGGCCAGAAGGAGAGCTCAGCAGCGCAGGGCCACCTTTC
TGCAGCCATCATCACAAGTAAGGGCGAGTGCTTTTGAAACCT Celera SNP ID:
hCV2549981 Public SNP ID: rs2240032 SNP Chromosome Position:
132005026 SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position
Genomic: 94497 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: dbSNP; Celera; HapMap; ABI_Val; HGBASE Population
(Allele, Count): Caucasian (C, 92|T, 24) SNP Type: INTRON Context
(SEQ ID NO: 85):
ATCTGACTTCCCCCTAGCCGACTTAACCCTCAGGTGGGCCCCCTTCTCATCATTATCAGG
CTCTGAATCCCCACACTATTCCCTGGCGTGGACACTCTGCK
TCTGAGCTGGATCCCCCCTATTTGTGGATTCCTCTTTCATCCTGCTGGAACTCTGATACC
ATTGGACTCTTGAAACTCTGTCTATGCCAAGCTGTTTCCC Celera SNP ID: hCV2549985
Public SNP ID: rs2299015 SNP Chromosome Position: 131929396 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 18867 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
Celera; HapMap; HGBASE Population (Allele, Count): Caucasian (T,
89|G, 21) SNP Type: INTRON Context (SEQ ID NO: 86):
GAGCCTAACAGGACTTACATATTTGACTGCAGTAGGCATTATATTTAGCTGATGACATA
ATAGGTTCTGTCATAGTGTAGATAGGGATAAGCCAAAATGCR
ATAAGAAAAACCATCCAGAGGAAACTCTTTTTTTTTTCTTTTTCTTTTTTTTTTTTCCAGA
TGGAGTCTCGCACTTCTCTGTCACCCGGGCTGGAGCGCA Celera SNP ID: hCV11740472
Public SNP ID: rs2040704 SNP Chromosome Position: 132001076 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 90547 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
Celera; HapMap; HGBASE Population (Allele, Count): Caucasian (A,
94|G, 26) SNP Type: TRANSCRIPTION FACTOR BINDING SITE; INTRON
Context (SEQ ID NO: 87):
CATTAACAGAATAAAAAAGAAATATCATATGAACACCAATAGATACAGAAAACGCATT
TCAATTTAATAGTCTTTCGTGGTAAAAACCCTCAGCATAACTR
ATGGAGGAATATTAATTCCTGAATAATTCAGTCCAAAATCCGTTAGGTGTGGCTGAGTG
AGGAAGGCATCCACAAAAACAAGCTGTGACAGCCTGGTGGG Celera SNP ID:
hCV11818538 Public SNP ID: rs2706348 SNP Chromosome Position:
131933709 SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position
Genomic: 23180 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: dbSNP; Celera; HapMap; ABI_Val; HGBASE Population
(Allele, Count): Caucasian (G, 94|A, 26) SNP Type: INTRON Context
(SEQ ID NO: 88):
AGTTCAGCTACAGAGACGGAGGCAATGTGAACTACCATTTAGATTTTTTAAAATCCACG
TTATTTTAGGGAAATAGAAAGAAATAAACAATTAGTACTTTS
ATTTTTAAATAATTACTGGTTGGTAATTTTATAATTTAAAAAAAGCACTTTGATTAATAT
TGAAAAGTTACATTGGTGGGTAACATCCATCCTTTTGCCC Celera SNP ID: hCV11818554
Public SNP ID: rs12652920 SNP Chromosome Position: 131913139 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 2610 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
Celera; HapMap; ABI_Val Population (Allele, Count): Caucasian (G,
93|C, 25) SNP Type: TFBS SYNONYMOUS; INTRON Context (SEQ ID NO:
89): AAATGGGAATTGCTAGAGGAATATGTTTCTAACTTTTTTTTTCTGCACACAAGTTCATGG
TCCTTCTATACTTGATAGCCCAGCTGCTCTATTTTTTTTAK
CTCATTTCACACTGGCACCTAAGCTTTAAACCCTTGGCTGTTTTTGTTATTGTTGTCTGCC
TGCTTGTCCTAGCTCCTTTTACTAGGTGTGTACTCTGGG Celera SNP ID: hCV15793510
Public SNP ID: rs2252775 SNP Chromosome Position: 131946343 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 35814 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
HapMap; HGBASE Population (Allele, Count): Caucasian (T, 94|G, 26)
SNP Type: INTRON Context (SEQ ID NO: 90):
AACTTTTTTTAACTGCATATATACAATACATATGTATATACAAACATTCACTTGTATGTA
TGTGCATATTTACCTTTACAAGCTTAATCAGAACAGGATTR
TGAGAGGAAGAGTCTGGGTTAAGTAAATCAATATAAAAGGAGTAAATGACCAATATGA
ATCGGGGTCAGATTATAGAAAGCTAATGGATTTCAGACTTAG Celera SNP ID:
hCV15892310 Public SNP ID: rs2246176 SNP Chromosome Position:
131945249 SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position
Genomic: 34720 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: dbSNP; HapMap; ABI_Val; HGBASE Population (Allele,
Count): Caucasian (A, 93|G, 25) SNP Type: INTRON Context (SEQ ID
NO: 91):
TTGTAGTCCATTAAGTTATTGAACTGTGTTTGCAATTTGGATGCTTCTTTTTAACAGAAA
AAATTTAAAAAGCAGAAAGGTCATCAGTTACTACCTCTCAY
CCAGCAGCAACCATTGGGCATATTTTCTTTCACTTGTCTTTCTGTGCGTATATTTATTTAC
CTGATTGACAGTATAAATGTAATTTTTTTCACTTACCAT Celera SNP ID: hCV15892315
Public SNP ID: rs2522403 SNP Chromosome Position: 131943216 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 32687 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
HapMap; HGBASE Population (Allele, Count): Caucasian (T, 94|C, 26)
SNP Type: INTRON Context (SEQ ID NO: 92):
TTGGTACATAACAGTACTTTTTACATTCATTCACATTACTAAGTACAACTATTTTTCAAA
CGTTTCTTCAACCAGGACATAACAGAAATGCCAACAAGACW
TGTAATCCAGTCGACTCTGTAAGGATGCCCATAAGCTTGAGAGTAGTGCCTGACACATA
AGAGGATGCTTAATAAGTGATAATAAATAAATGAAGATTTT Celera SNP ID:
hCV16098376 Public SNP ID: rs2106984 SNP Chromosome Position:
131980965 SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position
Genomic: 70436 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: dbSNP; Celera; HapMap; HGBASE Population (Allele,
Count): Caucasian (T, 94|A, 26) SNP Type: INTRON Context (SEQ ID
NO: 93): AAAATATACTGTGCCAGCTAATGAAAAGAAAGCTGAAGTGACCATATTAATACCAGAC
AGAAGACATCAGAACTAGGGAAAATGAAACATTTTATGATGAK
AAGAGGTCAATTTAATGCAAGGACACAAAAATTCTAAATGTAAAACTTCCAAATATATG
AGGCAGAAACCTATGGAACAGAATGGAGAAATACACAAATC Celera SNP ID:
hCV16274080 Public SNP ID: rs2706347 SNP Chromosome Position:
131933016 SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position
Genomic: 22487 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: dbSNP; HGBASE Population (Allele, Count): Caucasian (G,
92|T, 26) SNP Type: TRANSCRIPTION FACTOR BINDING SITE; INTRON
Context (SEQ ID NO: 94):
GTATGCCAGTCTTCCTTATCCTGCGTAGGCTCTTGACTCTTCATTCTGACTCCCTCATGG
GATGCTTTTCCATTCTGTATACACTTTGACTTCTGGTGCTR
GATCATGTCCTCATTCCCCGCCCTTCTCTGATACCAGGTGGCCTCTTGCAGGGATGCCCA
CTGTACTCTGACCTGAATCTCCCCAGATCTGTGTCACTGA Celera SNP ID: hCV16274083
Public SNP ID: rs2244012 SNP Chromosome Position: 131929124 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 18595 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
HapMap; ABI_Val; HGBASE Population (Allele, Count): Caucasian (A,
94|G, 26) SNP Type: INTRON Context (SEQ ID NO: 95):
CACACACACACACACACACACATATATATATAGTTTATTCGTTTTTAGTGGGGTCATGTG
CCTCTCTAGCCGCTCCCTGACCCCAGTTCCACTATGTTTTY
GTTACGTATTCTTCCAAGCTTTTTTCTGCTTATAAAACCATGTCTACGTGAGCACATAAA
TGCATTCACACATACATATTTTAGCACATTAATATAATTT Celera SNP ID: hCV16274086
Public SNP ID: rs2706338 SNP Chromosome Position: 131923748 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 13219 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
HapMap; ABI_Val; HGBASE Population (Allele, Count): Caucasian (C,
94|T, 26) SNP Type: INTRON Context (SEQ ID NO: 96):
AGTGCTAGGATTACAGGCATAAGCCACCATGCCCAACCAAGAGGACTTTTTTTTTTTTTA
AATATGGGAAAGCAATTGCCTAAGAGTGCAGTCAGGTTGAY
TTCAAATTCCAACTCTGCTGGGTGACCTTAGGGATGTTACTTAACCCATTTGGGCCTTCG
TATCCCCCACGTAAAGTGAGGGGATTGATTTACATGATCA Celera SNP ID: hCV16274088
Public SNP ID: rs2706372 SNP Chromosome Position: 131963376 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 52847 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
HapMap; HGBASE Population (Allele, Count): Caucasian (C, 94|T, 24)
SNP Type: INTRON Context (SEQ ID NO: 97):
GAGAAAGAAAGGCCTAAGAAGATGTGGTTTGTGGCAGCCAACTTCTAAGATGGTCCCT
AGTAATCTCGGCCTCTTGGTATTTATACTCTTGTATAGTCCCM
TCTCATGCTGTTGCATGATTGGTCTATATAACTGATAAAACAGGCAGAAGTGATAGCAT
GGCCTTTCCAACATTAGGTTATTTAAGGTACTATGGCTTCT Celera SNP ID:
hCV16274090 Public SNP ID: rs2706370 SNP Chromosome Position:
131960915 SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position
Genomic: 50386 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: dbSNP; HapMap; HGBASE Population (Allele, Count):
Caucasian (A, 91|C, 25) SNP Type: INTRON Context (SEQ ID NO: 98):
GAGGTGTTATAGTGCCAGGGAAAAGGGGTGCAAGACTAGTGTTTGCCTCTTATTTCTTG
TCTTGTTTATAAATTCTCTACATTAAAAATATAAATTCCAAR
TGAAAACAATGGAATAAACACAAACTCCCACTTTATAACCAACTAAAATGACAGTAAC
TGAATTTTCTAAAGTTTTAAACCCACCAAAATGGGAGAAATG Celera SNP ID:
hCV27452177 Public SNP ID: rs3091307 SNP Chromosome Position:
132017035 SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position
Genomic: 106506 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: dbSNP; HapMap; ABI_Val; HGBASE Population (Allele,
Count): Caucasian (A, 94|G, 26) SNP Type: INTRON Context (SEQ ID
NO: 99):
CTCCATAGTCTGTTTTTGACCTGGGCCTGGGATAAGAAGGAAGGGCTTTTCAGCAGAGA
AAAGTGCCTCAGTCACAGAGGCATGCTGAGCAGAATGAGGAY
CTATGAGGGAGCTTGGTGGAGCCTGGCGGGGTGGAGAGGTACAGGAGTGCTTTCTAGC
AATTTAGGCTTGTTAAGGAACAAAGCCAGGCTGTTTACTGAG Celera SNP ID:
hCV27484753 Public SNP ID: rs3798135 SNP Chromosome Position:
131993008 SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position
Genomic: 82479 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: dbSNP; HapMap; HGBASE Population (Allele, Count):
Caucasian (C, 94|T, 26) SNP Type: INTRON Context (SEQ ID NO: 100):
GTCACAGAGGCATGCTGAGCAGAATGAGGACCTATGAGGGAGCTTGGTGGAGCCTGGC
GGGGTGGAGAGGTACAGGAGTGCTTTCTAGCAATTTAGGCTTR
TTAAGGAACAAAGCCAGGCTGTTTACTGAGTTCTCTTACCTGGTACTCAGATGGATTCTT
CTAAATGAAAAGAGGTGATACAAATTTCCCCAAAATTGAG Celera SNP ID: hCV25812184
Public SNP ID: rs3798134 SNP Chromosome Position: 131993078 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 82549 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
HapMap; ABI_Val; HGBASE Population (Allele, Count): Caucasian (G,
93|A, 25) SNP Type: INTRON Context (SEQ ID NO: 101):
AGAGAGAAACAAACATCAGTGCAGTGGAAGCACCCAAGGCTACACCTGAATGGTGGGA
AGCTCTTTGCTGCTATATAAAATGAATCAGGCTCAGCTACTAW
TATTACACTCTCCTGAAGCTAACCAACATTTCCTGCAACATTATGTAGACTTTTAAAAGA
AGGGCCTGAAGCATTCTCACAGGATAGGCTAAATGTAGAA Celera SNP ID: hCV29134412
Public SNP ID: rs7737470 SNP Chromosome Position: 132001962 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 91433 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
HapMap Population (Allele, Count): Caucasian (T, 94|A, 26) SNP
Type: INTRON; PSEUDOGENE Context (SEQ ID NO: 102):
ATATGATTTAATTCGTATTGTGCCTTTGACATGAGCAAAATGATGATGAAGCCTGTTATC
CATAACTTCTTAGTGTTGATAATTGTGCATTCTCAGTTCAY
AATCAGAAGATTGTGAATTTGTAATATTAATCACCAGAGTGCTTTACTTAGCGTCTAAA
GGCCAGGAACTTTATCAGTGATCACATGCTATGAGGGTTCT Celera SNP ID:
hCV29134413 Public SNP ID: rs7449456 SNP Chromosome Position:
131981326 SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position
Genomic: 70797 Related Interrogated SNP: hCV50000065 (Power = .51)
SNP Source: dbSNP; HapMap Population (Allele, Count): Caucasian (C,
91|T, 23) SNP Type: INTRON Context (SEQ ID NO: 103):
AGAATATGGAGCTGTGGACCTTGTCTGGGTCAGAGCTTGTACAGTCTATAATATTGTCA
ATGGAGTTGTTGCCAGAGTGATTTATCCACAGAGATTCATTY
TAGATTTTCTCATTTGTAATTATGTGTCCACCAGAGCATTTCTTTTGAAAGATGAGCCTC
ATTCTTCCTTTATCTGGTCTTATTGTTACTTATTGTAGTT Celera SNP ID: hCV29134415
Public SNP ID: rs6596086 SNP Chromosome Position: 131980121 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 69592 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
HapMap Population (Allele, Count): Caucasian (T, 94|C, 26) SNP
Type: INTRON Context (SEQ ID NO: 104):
CTAATTTTTATGTTTCCATAGGTGACCAGCTGCATGCATTAACTGTCATCTGAGTTGGAT
GATTGGGGTTAATATTTAAGAGCTGAGGAGCCTAACAGTCR
CTTATTTACGTACTGATTTAAGCCCTGCTAAATTTAGTCCACAGAATAAAATAATTTGGA
AACTTAACTGCCTTTCTCAGTTTTCAGCTGAAGGAATATA Celera SNP ID: hCV30171484
Public SNP ID: rs10520114 SNP Chromosome Position: 131976790 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 66261 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
HapMap Population (Allele, Count): Caucasian (A, 94|G, 26) SNP
Type: INTRON Context (SEQ ID NO: 105):
GGATTTTGTTACTGACATTTTATTGGCTGCACAAAAAAAGCTTGCACTTTAATTTACATT
TCCCTCTTTACTAGTGAAGTTAAATGTCTTTTTGTATGTTR
TCTATTTGTATTTCTTCTCCAAGAATTACCTATTCATATCTCTTTGCCAGTTTTTCTACTA
GGTTGTCTGTTTCTTGATTTGTCACATTTTAATAGATTC Celera SNP ID: hCV31237845
Public SNP ID: rs6596087 SNP Chromosome Position: 131996508 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 85979 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
HapMap Population (Allele, Count): Caucasian (G, 93|A, 25) SNP
Type: INTRON Context (SEQ ID NO: 106):
CTTATGGATTCTGTTAAGCATTTTTTAATTTTATTGGGGTTTCTGTTTGGATTGCATTTAA
TTTATGGATTATTTGAGGAGAACGGACATCTTTGTAATAY
CACATCTACCATTCTGGACTCCTTAGTATGCATCTCCTGCTCAATCATTTCCTTTTATCCT
ATTGTAAAGTTTTACAGCTTTTTCCTCTAGCTCCTATAC Celera SNP ID: hCV30081308
Public SNP ID: rs6871536 SNP Chromosome Position: 131997773 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 87244 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
HapMap Population (Allele, Count): Caucasian (T, 94|C, 26) SNP
Type: INTRON Context (SEQ ID NO: 107):
GAGGTAGTAACTGATGACCTTTCTGCTTTTTAAATTTTTTCTGTTAAAAAGAAGCATCCA
AATTGCAAACACAGTTCAATAACTTAATGGACTACAAAGTY
TATTTAAGGGTTACAAACCTTGTTGCTGAAAAAATCTCATCAAACTTTTGCTTCAAAGCC
TTTCCTTCACTTAAAGGCCAATTAGAATCTTCTTGATGAC Celera SNP ID: hDV70911845
Public SNP ID: rs17166050 SNP Chromosome Position: 131943112 SNP in
Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 32583 Related
Interrogated SNP: hCV50000065 (Power = .51) SNP Source: dbSNP;
HapMap Population (Allele, Count): Caucasian (C, 94|T, 26) SNP
Type: TRANSCRIPTION FACTOR BINDING SITE; INTRON Gene Number: 8 Gene
Symbol: SLC22A4-6583 Gene Name: solute carrier family 22 (organic
cation transporter), member 4 Chromosome: 5 OMIM NUMBER: 604190
OMIM Information: {Rheumatoid arthritis, susceptibility to}, 180300
(3) Genomic Sequence (SEQ ID NO: 17): SNP Information Context (SEQ
ID NO: 108):
ATTAGGACATTTGAAGAGAAAATGCTATTTTGGGAATATATTTATGTTAATAAAAGTAC
TCCCACTGAAGCAAAAAGGACAATAAAAATAACTGATATAAR
AAAGTATCACTTCTAAAAGCACCATTGTTTATACCGGGTCTCTTTTCCAGATTATTACTT
CTTATCCATTGGTCTGGTCATGCTGGGAAAATTTGGGATC Celera SNP ID: hCV25603190
Public SNP ID: rs41542912 SNP Chromosome Position: 131699359 SNP in
Genomic Sequence: SEQ ID NO: 17 SNP Position Genomic: 51315 SNP
Source: Applera Population (Allele, Count): Caucasian (A, 2|G, 38)
African American (A, 0|G, 34) total (A, 2|G, 72) SNP Type:
TRANSCRIPTION FACTOR BINDING SITE; INTRON SNP Source: dbSNP; HapMap
Population (Allele, Count): Caucasian (G, 114|A, 6) SNP Type:
TRANSCRIPTION FACTOR BINDING SITE; INTRON Gene Number: 9 Gene
Symbol: SLC22A5-6584 Gene Name: solute carrier family 22 (organic
cation transporter), member 5 Chromosome: 5 OMIM NUMBER: 603377
OMIM Information: Carnitine deficiency, systemic primary, 212140
(3) Genomic Sequence (SEQ ID NO: 18): SNP Information Context (SEQ
ID NO: 109):
TTGTTTCTTATACCTAAGGTGGCTTGTCACCTTACAAAGCTAACCCCAAACGTAAAATGT
AAAGCACAAATAGATTTGGAGTTAGAAGTATTTCATCTCTW
GAGTATTAGCAATTATTCATTAAAAAGAAAAAAAAAGTGTTTAGTCTCTTTCTGCCCTC
CAATGGTTAATTATTGCATATCATCTTGGAGTCAGGTCCTT Celera SNP ID:
hCV15949533 Public SNP ID: rs35306350 SNP Chromosome Position:
131751188 SNP in Genomic Sequence: SEQ ID NO: 18 SNP Position
Genomic: 27845 SNP Source: HGBASE; dbSNP Population (Allele,
Count): no_pop (A, --|T, --) SNP Type: INTRON Context (SEQ ID NO:
110): AGGGCTAATATAGTGTTTTTCAAACCTTTCTAAACATTTTGGCCACAGAACTTTCATTAA
AGTAGGATAATTTAAGTCTAGTAAATGAAATACACCCTAAR
TGGCTAAAAGTATGGCTGTTCTGCCTGCAGCCCCTGCCTTCAATTCCCAATGCCCTGCCT
CAAGCCTGTCTGTGCCCCCTTGGAAGGCCCAGGGCCCTGT Celera SNP ID: hDV70978086
Public SNP ID: rs17622208 SNP Chromosome Position: 131744949 SNP in
Genomic Sequence: SEQ ID NO: 18 SNP Position Genomic: 21606 SNP
Source: dbSNP; HapMap Population (Allele, Count): Caucasian (G,
57|A, 61) SNP Type: UTR5; INTRON
TABLE-US-00003 TABLE 3 Primers Primer 1 Primer 2 (Allele-specific
(Allele-specific Marker Rs number Alleles Primer) Primer) Common
Primer hCV15949533 rs2073644 C/T TTGGAGTTAGAAGTATT
GATTTGGAGTTAGAAGTA GGGGGAAGAGGTGGACATCA rs35306350 TCATCTCC (SEQ ID
TTTCATCTCT (SEQ ID (SEQ ID NO: 113) NO: 111) NO: 112) hCV16154343
rs2897443 G/T CCACAGCTATCTGGCT CCACAGCTATCTGGCTCT
AGAGTTATGCAAAGGGAAGG CTC (SEQ ID NO: 114) A (SEQ ID NO: 115)
AGTTACA (SEQ ID NO: 116) hCV16176063 rs2243211 A/C CCGATCTGTGCATGGT
CCGATCTGTGCATGGG CCGCTACCGTGGGAAATAGA (SEQ ID NO: 117) (SEQ ID NO:
118) AC (SEQ ID NO: 119) hCV16176374 rs2227282 C/G GCAAGGCCTTAACGTT
GCAAGGCCTTAACGTTTT CTCAGCAGCCAGAGCTAGAC TTAG (SEQ ID NO: 120) AC
(SEQ ID NO: 121) A (SEQ ID NO: 122) hCV2259917 rs762534 A/C
CACAGATGAGGCTGAG ACAGATGAGGCTGAGTAG GGTCTGTTAACAGAGGCTGCT TAGA (SEQ
ID NO: 123) C (SEQ ID NO: 124) ATAG (SEQ ID NO: 125) hCV2259921
rs20541 A/G CTTTCGAAGTTTCAGTT TTCGAAGTTTCAGTTGAA
GTTTTCCAGCTTGCATGTC GAACT (SEQ ID NO: 126) CC (SEQ ID NO: 127) (SEQ
ID NO: 128) hCV2346958 rs157578 C/G GGCAAGAATAGTGCCT
GGCAAGAATAGTGCCTCG TGGCCCCAGCTGATCTCA CC (SEQ ID NO: 129) (SEQ ID
NO: 130) (SEQ ID NO: 131) hCV25603190 rs11568506 A/G
TGGTGCTTTTAGAAGTG TGGTGCTTTTAGAAGTGA CTCCATCTTTGTCCATGCCCA
rs41542912 ATACTTTT (SEQ ID TACTTTC (SEQ ID NO: 133) AATA (SEQ ID
NO: 134) NO: 132) hCV26479272 rs4594848 A/C GATGAGACAGCTTCTT
TGAGACAGCTTCTTGTTTA GCCCCCTGTGAAATCACCATA GTTTAACTA (SEQ ID ACTC
(SEQ ID NO: 136) TTA (SEQ ID NO: 137) NO: 135) hCV28028637
rs4143832 G/T CAGAACAGGGGCATTA CAGAACAGGGGCATTACT
AGCTTTTGCCAGGGTGTTTG CTTG (SEQ ID NO: 138) TT (SEQ ID NO: 139) (SEQ
ID NO: 140) hCV29134417 rs6884762 C/T GTCTTTGTAATTAACAA
GTCTTTGTAATTAACAAGT CAAGCAAGATCTGTCAGTGGA GTATCTTAGGAG (SEQ
ATCTTAGGAA (SEQ ID TACT (SEQ ID NO: 143) ID NO: 141) NO: 142)
hCV29575948 rs10069772 A/G CAGAGCAAACCTAAGA CAGAGCAAACCTAAGACA
GCCAAACAAGCCAGTAAATAG CACA (SEQ ID NO: 144) CG (SEQ ID NO: 145)
AATCAGT (SEQ ID NO: 146) hCV31237680 rs12186803 A/G
TGACACTTGGCATGTTT TGACACTTGGCATGTTTA CACAGTTGCTGAGCTGTCAAG ACTT
(SEQ ID NO: 147) CTC (SEQ ID NO: 148) ATAT (SEQ ID NO: 149)
hCV50000065 rs1800925 C/T TCTGGAGGACTTCTAG TCTGGAGGACTTCTAGGA
TTCCCTTCTGCAGAATGAGT GAAAAC (SEQ ID AAAT (SEQ ID NO: 151) (SEQ ID
NO: 152) NO: 150) hCV559494 rs334902 C/G CATCCCAGGGAAGATG
CATCCCAGGGAAGATGAA TCTCCGCAGTCAGCTTGTCTT AAG (SEQ ID NO: 153) C
(SEQ ID NO: 154) A (SEQ ID NO: 155) hCV8932051 rs848 C/A
AGCACTAAAGCAGTGG CAGCACTAAAGCAGTGGA TGTTCTGCCCCTCTCCTGAC ACC (SEQ
ID NO: 156) CA (SEQ ID NO: 157) (SEQ ID NO: 158) hDV70977429
rs17618604 C/T GCCTCCTGGTCACCTC GCCTCCTGGTCACCTT
GCTGCCATATCCCATCACTGA (SEQ ID NO: 159) (SEQ ID NO: 160) T (SEQ ID
NO: 161) hDV70978086 rs17622208 A/G GAACAGCCATACTTTTA
ACAGCCATACTTTTAGCC GTGAGTGTGTTTAGGACCACT GCCAT (SEQ ID NO: 162) AC
(SEQ ID NO: 163) TTAGTC (SEQ ID NO: 164)
TABLE-US-00004 TABLE 4 Linkage Disequilibrium (LD) SNPs
Interrogated SNP Interrogated rs LD SNP LD SNP rs Power Threshold
r.sup.2 r.sup.2 hCV16176374 rs2227282 hCV11740439 rs2023823 0.51
0.574147858 0.8788 hCV16176374 rs2227282 hCV11818497 rs4266392 0.51
0.574147858 0.8824 hCV16176374 rs2227282 hCV11818498 rs4425499 0.51
0.574147858 0.84 hCV16176374 rs2227282 hCV11818499 rs2897442 0.51
0.574147858 0.8824 hCV16176374 rs2227282 hCV11818501 rs11740584
0.51 0.574147858 0.84 hCV16176374 rs2227282 hCV11818506 rs17690965
0.51 0.574147858 0.8645 hCV16176374 rs2227282 hCV11818513 rs2227284
0.51 0.574147858 1 hCV16176374 rs2227282 hCV15751509 rs2299009 0.51
0.574147858 0.8824 hCV16176374 rs2227282 hCV15793498 rs2406539 0.51
0.574147858 0.9538 hCV16176374 rs2227282 hCV15955623 rs2237059 0.51
0.574147858 0.5957 hCV16176374 rs2227282 hCV16164369 rs2074529 0.51
0.574147858 0.8824 hCV16176374 rs2227282 hCV16177653 rs2285700 0.51
0.574147858 0.84 hCV16176374 rs2227282 hCV2558119 rs9784600 0.51
0.574147858 0.6046 hCV16176374 rs2227282 hCV2558124 rs10036532 0.51
0.574147858 0.8336 hCV16176374 rs2227282 hCV26478846 rs6864565 0.51
0.574147858 0.84 hCV16176374 rs2227282 hCV26478847 rs6864396 0.51
0.574147858 0.84 hCV16176374 rs2227282 hCV26478954 rs4426908 0.51
0.574147858 1 hCV16176374 rs2227282 hCV27472356 rs3213639 0.51
0.574147858 0.84 hCV16176374 rs2227282 hCV30117349 rs9784675 0.51
0.574147858 0.5818 hCV16176374 rs2227282 hCV30585769 rs10062446
0.51 0.574147858 0.84 hCV16176374 rs2227282 hCV31237596 rs3798129
0.51 0.574147858 0.5818 hCV16176374 rs2227282 hCV31237618
rs11242127 0.51 0.574147858 0.8824 hCV16176374 rs2227282
hCV31237619 rs4705965 0.51 0.574147858 0.8824 hCV16176374 rs2227282
hCV31237737 rs11242122 0.51 0.574147858 0.9576 hCV16176374
rs2227282 hCV31237741 rs11747814 0.51 0.574147858 0.9576
hCV16176374 rs2227282 hCV8932022 rs1468215 0.51 0.574147858 0.84
hCV2259921 rs20541 hCV8932046 rs847 0.51 0.893902117 0.9061
hCV2259921 rs20541 hCV8932051 rs848 0.51 0.893902117 0.955
hCV2259921 rs20541 hCV8932052 rs1295685 0.51 0.893902117 0.955
hCV2259921 rs20541 hCV8932053 rs1295686 0.51 0.893902117 1
hCV50000065 rs1800925 hCV11740472 rs2040704 0.51 0.783364112 0.8573
hCV50000065 rs1800925 hCV11818538 rs2706348 0.51 0.783364112 0.8573
hCV50000065 rs1800925 hCV11818554 rs12652920 0.51 0.783364112
0.8525 hCV50000065 rs1800925 hCV15756644 rs2301713 0.51 0.783364112
0.8519 hCV50000065 rs1800925 hCV15793510 rs2252775 0.51 0.783364112
0.8573 hCV50000065 rs1800925 hCV15892310 rs2246176 0.51 0.783364112
0.8525 hCV50000065 rs1800925 hCV15892315 rs2522403 0.51 0.783364112
0.8573 hCV50000065 rs1800925 hCV16098376 rs2106984 0.51 0.783364112
0.8573 hCV50000065 rs1800925 hCV16154343 rs2897443 0.51 0.783364112
0.8573 hCV50000065 rs1800925 hCV16164126 rs2074369 0.51 0.783364112
0.8519 hCV50000065 rs1800925 hCV16274080 rs2706347 0.51 0.783364112
0.8567 hCV50000065 rs1800925 hCV16274083 rs2244012 0.51 0.783364112
0.8573 hCV50000065 rs1800925 hCV16274086 rs2706338 0.51 0.783364112
0.8573 hCV50000065 rs1800925 hCV16274088 rs2706372 0.51 0.783364112
0.8479 hCV50000065 rs1800925 hCV16274090 rs2706370 0.51 0.783364112
0.8046 hCV50000065 rs1800925 hCV25471631 rs2522394 0.51 0.783364112
0.8573 hCV50000065 rs1800925 hCV2549970 rs10463893 0.51 0.783364112
0.8525 hCV50000065 rs1800925 hCV2549979 rs12653750 0.51 0.783364112
0.8573 hCV50000065 rs1800925 hCV2549980 rs2040703 0.51 0.783364112
0.8567 hCV50000065 rs1800925 hCV2549981 rs2240032 0.51 0.783364112
0.8474 hCV50000065 rs1800925 hCV2549985 rs2299015 0.51 0.783364112
0.8292 hCV50000065 rs1800925 hCV25812184 rs3798134 0.51 0.783364112
0.8525 hCV50000065 rs1800925 hCV27452177 rs3091307 0.51 0.783364112
0.8573 hCV50000065 rs1800925 hCV27484753 rs3798135 0.51 0.783364112
0.8573 hCV50000065 rs1800925 hCV29134412 rs7737470 0.51 0.783364112
0.8573 hCV50000065 rs1800925 hCV29134413 rs7449456 0.51 0.783364112
0.8418 hCV50000065 rs1800925 hCV29134415 rs6596086 0.51 0.783364112
0.8573 hCV50000065 rs1800925 hCV30081308 rs6871536 0.51 0.783364112
0.8573 hCV50000065 rs1800925 hCV30171484 rs10520114 0.51
0.783364112 0.8573 hCV50000065 rs1800925 hCV31237845 rs6596087 0.51
0.783364112 0.8525 hCV50000065 rs1800925 hDV70911845 rs17166050
0.51 0.783364112 0.8573 hCV8932051 rs848 hCV2259921 rs20541 0.51
0.85292942 0.955 hCV8932051 rs848 hCV8932046 rs847 0.51 0.85292942
0.9537 hCV8932051 rs848 hCV8932052 rs1295685 0.51 0.85292942 1
hCV8932051 rs848 hCV8932053 rs1295686 0.51 0.85292942 0.955
TABLE-US-00005 TABLE 5 Association of IL13 SNPs with psoriasis
Marker Genotypes Allelic Genotypic (Alleles & Position) Sample
Set Status 11 12 22 MAF HWE OR (95% CI) P P rs1800925 1 case 338
112 11 0.145 0.577 (T132020708C) control 303 139 14 0.183 0.756
0.76 (0.59-0.97) 0.0320 0.0781 2 case 335 150 9 0.170 0.111 control
316 158 21 0.202 0.782 0.75 (0.60-0.94) 0.0162 0.0297 3 case 345
119 16 0.157 0.166 control 272 131 21 0.204 0.373 0.73 (0.57-0.93)
0.0050 0.0205 Combined 0.76 (0.67-0.88) 2.50E-04 0.0029 rs20541 1
case 326 131 6 0.154 0.106 (T132023863C) control 298 140 20 0.197
0.462 0.75 (0.59-0.95) 0.0198 0.0092 2 case 339 143 12 0.169 0.630
control 312 170 12 0.196 0.047 0.83 (0.66-1.05) 0.0650 0.0907 3
case 341 131 8 0.153 0.376 control 272 138 12 0.192 0.347 0.76
(0.60-0.97) 0.0166 0.0416 Combined 0.78 (0.68-0.90) 0.0013 0.0022
rs848 1 case 323 132 6 0.156 0.076 (T132024399G) control 294 145 19
0.200 0.884 0.74 (0.58-0.94) 0.0148 0.0113 2 case 338 144 12 0.170
0.527 control 308 171 13 0.200 0.067 0.82 (0.65-1.03) 0.0463 0.0784
3 case 334 138 8 0.160 0.175 control 269 141 13 0.197 0.358 0.78
(0.61-0.99) 0.0210 0.0503 Combined 0.78 (0.68-0.89) 0.0017
0.0027
TABLE-US-00006 TABLE 6 Three-marker IL13 haplotypes (the order of
SNPs is rs1800925-rs20541-rs848) Sample Set 1 Sample Set 2 Sample
Set 3 467 cases/460 controls 498 cases/498 controls 481 cases/424
controls Combined Hap- Global P = 0.093 Global P = 0.151 Global P =
0.025 Global lo- No. (Frequency) in No. (Frequency) in No.
(Frequency) in P.sub.comb = 0.014 type Case Control P OR Case
Control P OR Case Control P OR P.sub.comb OR.sub.MH CCG 723 677
0.0288 1.26 749 710 0.0177 1.24 739 606 0.0037 1.34 1.88E-04 1.27
(0.777) (0.736) (0.758) (0.717) (0.77) (0.714) TTT 74 108 0.0063
0.65 97 115 0.0653 0.83 84 96 0.0213 0.75 7.05E-04 0.74 (0.079)
(0.117) (0.098) (0.116) (0.087) (0.113) TCG 61 61 0.9284 0.99 70 83
0.1503 0.83 66 72 0.0999 0.80 0.201 0.86 (0.066) (0.066) (0.071)
(0.084) (0.069) (0.085) CTT 69 72 0.6234 0.94 69 80 0.2072 0.85 62
66 0.1545 0.82 0.251 0.87 (0.074) (0.079) (0.07) (0.081) (0.065)
(0.078) Other 3 3 NC NC 3 2 NC NC 9 8 NC NC NC NC (0.003) (0.003)
(0.003) (0.002) (0.01) (0.01)
TABLE-US-00007 TABLE 7 HLA-cytokine pathway psoriasis relative risk
estimates HLA-C IL12B/IL23R/IL13.sup..dagger. P(MLG)
P(Psoriasis|MLG) RR RR (95% CI) SRR *0602 carriers Very High Risk
0.0296 0.1149 3.8286 (2.359-7.277) 11.3411 *0602 carriers High Risk
0.0733 0.0789 2.6294 (1.874-3.839) 7.7890 *0602 carriers Moderate
Risk 0.0534 0.0539 1.7971 (1.150-2.922) 5.3235 *0602 carriers Low
Risk 0.0121 0.0368 1.2266 (0.377-4.784) 3.6334 noncarriers Very
High Risk 0.1417 0.0336 1.1195 (0.827-1.511) 3.3162 noncarriers
High Risk 0.3608 0.0224 0.7474 (0.617-0.897) 2.2139 noncarriers
Moderate Risk 0.2677 0.0150 0.5011 (0.378-0.650) 1.4843 noncarriers
Low Risk 0.0615 0.0101 0.3376 (0.140-0.649) 1.0000 Cytokine Pathway
IL12B Diplotypes IL23R Diplotypes IL13 Genotypes Risk Category
(rs6887695-rs3212227) (rs7530511-rs11209026) (rs1800925) Very High
Risk AG/AG CG/CG CC High Risk AG/AG CG/CG Other High Risk AG/AG
Other CC High Risk Other CG/CG CC Moderate Risk AG/AG Other Other
Moderate Risk Other CG/CG Other Moderate Risk Other Other CC Low
Risk Other Other Other .sup..dagger.Definition of IL12B/IL23R/IL13
Risk Groups
TABLE-US-00008 TABLE 8 Table 1 of Example Two. Association analysis
of two independent SNPs in the three sample sets combined SNP ID
Gene Allele/Genotype Cases N (%) Controls N (%) OR (95% CI) P
rs11568506 SLC22A4 A 50 (0.017) 69 (0.025) 0.68 (0.47-0.99) 0.043 G
2820 (0.983) 2677 (0.975) 1.00 (reference) AA 2 (0.0014) 0 (0) NC*
0.022 AG 46 (0.032) 69 (0.050) 0.63 (0.43-0.92) GG 1387 (0.0967)
1304 (0.950) 1.00 (reference) rs1800925 IL13 T 453 (0.158) 540
(0.196) 0.77 (0.67-0.88) 0.00015 C 2417 (0.842) 2210 (0.804) 1.00
(reference) TT 36 (0.025) 56 (0.041) 0.56 (0.37-0.86) 0.00081 TC
381 (0.266) 428 (0.311) 0.78 (0.66-0.92) CC 1018 (0.709) 891
(0.648) 1.00 (reference) *not calculated See supplementary Table 2
for other significant markers
TABLE-US-00009 TABLE 9 Table 2. Conditional association tests for
5q31 markers: P-values for marker 1 conditional on marker 2 Marker
1 rs11568506 rs4143832 rs2897443 rs6884762 rs1800925 rs20541 Marker
2 rs11568506 0.0138 0.0012 0.0023 0.0002 0.0012 rs4143832 0.0022
0.2503 0.0067 0.0046 0.0591 rs2897443 0.0071 0.9922 0.0736 0.0423
0.1103 rs6884762 0.0114 0.0915 0.0740 0.0118 0.0129 rs1800925
0.0105 0.2493 0.2168 0.0648 0.1538 rs20541 0.0195 0.8541 0.2509
0.0432 0.1123 rs848 0.0197 0.6773 0.3075 0.0361 0.0676 0.7771
rs2243211 0.0145 0.5871 0.2605 0.0553 0.0330 0.0578 rs762534 0.0202
0.3471 0.2286 0.0302 0.0378 0.0822 rs2227282 0.1132 0.6841 0.1164
0.0588 0.0563 0.1368 rs12186803 0.1977 0.4103 0.0326 0.0005 0.0151
0.0153 rs10069772 0.0281 0.1877 0.0327 0.0691 0.0054 0.0642 Marker
1 rs848 rs2243211 rs762534 rs2227282 rs12186803 rs10069772 Marker
rs11568506 0.0012 0.0023 0.0094 0.0093 0.3754 0.0390 2 rs4143832
0.0353 0.0791 0.1072 0.0531 0.3720 0.0873 rs2897443 0.1386 0.1807
0.4214 0.0552 0.2559 0.1870 rs6884762 0.0099 0.0648 0.0608 0.0148
0.0239 0.2777 rs1800925 0.1006 0.1136 0.3292 0.0888 0.4419 0.1153
rs20541 0.8374 0.1031 0.4035 0.1524 0.3309 0.5399 rs848 0.2661
0.3943 0.2287 0.5391 0.5746 rs2243211 0.1443 0.2897 0.0048 0.0992
0.1132 rs762534 0.0742 0.0999 0.0034 0.0879 0.0365 rs2227282 0.1943
0.0238 0.0276 0.8115 0.8433 rs12186803 0.0342 0.0040 0.0079 0.0557
0.0116 rs10069772 0.0556 0.0372 0.0167 0.0878 0.0289 Note: P <
0.05 in boldface
TABLE-US-00010 TABLE 10 Table 3. Haplotype association tests
Haplotype.sup.a (rs11568506/ Case Count Control Count Sample set
rs1800925) (Freq.) (Freq.) P.sub.haplotype Global P OR SS1 GC 771
(0.844) 713 (0.787) 0.0019 0.0028 1.46 GT 131 (0.143) 167 (0.184)
0.018 0.74 AC 12 (0.013) 26 (0.029) 0.019 0.45 SS2 GC 796 (0.807)
765 (0.781) 0.13 0.11 1.18 GT 168 (0.170) 199 (0.203) 0.052 0.81 AC
22 (0.022) 15 (0.015) 0.36 1.48 SS3 GC 799 (0.830) 651 (0.764)
9.11E-04 0.0028 1.51 GT 147 (0.153) 175 (0.205) 6.87E-03 0.70 AC 13
(0.014) 26 (0.031) 0.031 0.45 All.sup.b GC 2366 (0.827) 2128
(0.777) 5.67E-06 8.93E-05 1.37 GT 446 (0.156) 542 (0.198) 6.01E-05
0.75 AC 47 (0.017) 68 (0.025) 0.053 0.66 .sup.aFrequency of AT
haplotype is <0.001 in both cases or controls. .sup.bBecause
haplotype counts were estimated, these counts may vary slightly
from the sum of the three individudal sample sets.
TABLE-US-00011 TABLE 11 Table 4. Association of putative CD SNPs
with psoriasis Psoriasis (SS1 + SS2 + SS3) CD (WTCCC).sup.a Control
Control Case allele allele Case allele allele OR Marker Chr
Position (bp) Gene frequency frequency P.sub.allelic OR (95% CI)
frequency frequency P.sub.allelic (95% CI) rs6596075 5 131,770,127
0.162 0.164 0.82 0.98 (0.85-1.14) 0.127 0.166 5.40E-07 0.73
(0.65-0.83) rs2285673 5 131,783,868 LOC441108 0.226 0.235 0.43 0.95
(0.84-1.08) 0.212 0.252 1.50E-05 0.80 (0.73-0.89) rs4540166 5
131,807,756 LOC441108 0.205 0.212 0.52 0.96 (0.84-1.09) 0.189 0.228
8.98E-06 0.79 (0.71-0.88) rs10077785 5 131,829,057 0.209 0.218 0.45
0.95 (0.84-1.09) 0.192 0.234 1.81E-06 0.78 (0.70-0.86) rs2522057 5
131,829,846 0.444 0.414 0.022 1.13 (1.02-1.26) 0.478 0.422 1.01E-07
1.29 (1.20-1.33) .sup.aData are from WTCCC (3).
TABLE-US-00012 TABLE 12 Association results in sample set 1.
Case.sup.b Control.sup.b RS Number Gene Position and alleles.sup.a
11 12 22 HWE.sup.c 11 12 22 HWE.sup.c P.sub.allelic P.sub.genotypic
rs12656759 C131395509T 98 237 126 0.51 99 240 120 0.35 0.75 0.92
rs2073506 T131422637C 4 63 394 0.33 2 71 386 0.76 0.71 0.55 rs31481
IL3 A131425101G 13 107 339 0.19 12 120 325 0.86 0.45 0.59
rs11575022 C131429914A 2 43 416 0.33 7 42 410 0.0006 0.35 0.23
rs2069626 CSF2 G131438678A 0 15 446 1 0 9 450 1 0.22 rs743564 CSF2
C131438778T 76 228 155 0.63 72 222 165 0.92 0.51 0.78 rs25882 CSF2
C131439359T 18 142 298 0.88 19 150 290 1 0.57 0.84 rs25887
C131443960A 83 232 146 0.64 87 223 149 0.85 0.96 0.86 rs25888
A131444345G 0 25 436 1 0 21 438 1 0.56 rs31467 C131464737T 106 233
122 0.85 116 227 116 0.85 0.46 0.71 rs39897 C131464795T 96 235 130
0.64 93 239 127 0.35 0.96 0.95 rs154735 A131465431G 2 56 402 1 1 56
402 1 0.86 0.86 rs247008 A131475003G 42 198 221 0.91 41 213 205
0.20 0.47 0.56 rs156055 A131528076G 4 65 390 0.51 3 64 391 0.74
0.80 0.93 rs156033 T131555220C 12 126 323 1 11 131 317 0.74 0.82
0.91 rs2278398 P4HA2 G131558340A 100 244 117 0.23 97 229 132 0.93
0.40 0.49 rs156030 P4HA2 A131558816G 0 49 411 0.63 2 33 424 0.16
0.19 rs152050 T131564725C 52 215 193 0.54 54 217 186 0.48 0.69 0.92
rs10520127 P4HA2 T131567154C 2 64 394 1 3 68 387 1 0.58 0.83
rs17618604 P4HA2 T131570083C 9 84 368 0.15 2 112 345 0.02 0.30 0.01
rs283763 P4HA2 T131581144A 14 159 288 0.19 16 162 281 0.26 0.65
0.89 rs7733814 P4HA2 T131584208C 2 59 400 1 1 55 401 1 0.60 0.81
rs157578 P4HA2 C131589221G 3 102 356 0.18 12 108 339 0.34 0.09 0.04
rs10036208 T131599222C 48 206 207 0.83 62 186 211 0.05 0.64 0.24
rs11749843 A131600397G 0 8 452 1 0 5 454 1 0.41 rs2405271
C131601292G 11 151 299 0.13 19 138 302 0.55 0.82 0.26 rs334902
C131614458G 78 244 139 0.11 101 207 151 0.06 0.61 0.04 rs4594848
A131614497C 94 247 120 0.13 107 208 143 0.07 0.63 0.05 rs7727038
C131618156T 86 226 149 1 98 214 147 0.22 0.52 0.57 rs162881 PDLIM4
G131636693T 4 73 383 0.77 5 85 369 1 0.26 0.54 rs162896 T131640775C
0 33 427 1 0 20 439 1 0.07 rs7737937 A131642880G 10 125 325 0.73 8
118 333 0.71 0.49 0.77 rs162899 G131643492A 26 175 260 0.71 25 178
254 0.45 0.87 0.95 rs272895 G131644273A 6 114 341 0.43 6 101 352
0.83 0.39 0.63 rs381870 T131650200A 11 146 304 0.21 18 142 299 0.77
0.52 0.41 rs162892 A131651149G 47 210 203 0.53 48 194 216 0.67 0.53
0.59 rs162889 T131652285C 18 191 252 0.02 22 177 260 0.31 0.78 0.59
rs2662314 T131653068C 7 115 338 0.56 7 107 344 0.84 0.61 0.85
rs157572 C131654011G 39 204 218 0.44 38 187 234 0.91 0.36 0.52
rs3792876 SLC22A4 T131665208C 4 62 394 0.32 3 60 396 0.72 0.73 0.92
rs3792884 SLC22A4 G131679160A 5 90 361 1 3 90 361 0.45 0.79 0.78
rs11739484 SLC22A4 G131684659A 0 25 436 1 0 23 436 1 0.78 rs273912
SLC22A4 G131689248T 37 186 238 0.91 50 179 230 0.10 0.30 0.33
rs272879 SLC22A4 C131698445G 61 211 189 0.84 69 209 181 0.49 0.45
0.72 rs11568506 SLC22A4 A131699359G 0 12 449 1 0 27 430 1 0.01
rs17622208 SLC22A5 A131744949G 97 252 112 0.05 114 208 137 0.05
0.71 0.02 rs7731390 SLC22A5 G131749648C 0 47 413 0.62 1 38 420 0.59
0.45 rs17689550 SLC22A5 T131750964C 5 86 370 1 6 96 356 1 0.35 0.64
rs35306350 SLC22A5 T131751187C 81 253 125 0.02 102 213 143 0.19
0.89 0.03 rs274549 SLC22A5 A131757017C 13 140 307 0.64 7 135 317
0.09 0.30 0.36 rs11739135 C131761296G 79 214 167 0.50 79 216 161
0.70 0.80 0.95 rs6596075 G131770127C 13 140 307 0.64 7 135 317 0.09
0.30 0.36 rs4705943 LOC441108 G131782903A 6 87 368 0.63 7 80 372
0.30 0.73 0.83 rs4705944 LOC441108 A131783163T 1 31 429 0.45 3 26
430 0.01 0.91 0.50 rs2285673 LOC441108 T131783868C 25 183 252 0.32
25 178 255 0.45 0.83 0.96 rs1004234 LOC441108 A131785000G 2 56 401
1 0 54 405 0.39 0.56 rs11958162 LOC441108 A131799815T 8 105 348 1 3
107 349 0.13 0.60 0.31 rs4540166 LOC441108 T131807756C 19 164 277
0.50 22 158 279 1 0.96 0.85 rs7713818 LOC441108 T131816650C 45 201
213 0.91 46 216 197 0.25 0.40 0.56 rs10477741 LOC441108 G131823209T
7 94 358 0.82 5 95 359 0.82 0.83 0.85 rs6894249 LOC441108
G131825446A 64 231 166 0.28 59 230 169 0.20 0.68 0.89 rs2522051
LOC441108 C131825477T 81 241 136 0.16 108 208 143 0.06 0.35 0.04
rs10077785 T131829057C 20 164 277 0.59 19 163 277 0.50 0.90 0.99
rs2522057 G131829846C 79 237 145 0.34 79 222 157 1 0.56 0.62
rs2522064 A131834387G 10 147 304 0.12 20 148 290 0.89 0.19 0.16
rs17715481 G131843283A 1 67 393 0.50 0 77 382 0.06 0.47 rs10072700
C131844802A 37 174 249 0.41 29 174 256 1 0.41 0.59 rs2070721 IRF1
G131853741T 98 219 144 0.40 90 227 141 1 0.80 0.78 rs2548997
G131863294A 58 195 207 0.25 47 208 203 0.60 0.70 0.45 rs4143832
T131890876G 12 102 345 0.17 17 126 316 0.33 0.03 0.10 rs4705959
C131893690T 26 179 253 0.54 32 159 268 0.21 0.65 0.33 rs2706399
A131895601G 104 232 124 0.85 103 242 107 0.16 0.46 0.50 rs739719
A131900764C 6 72 383 0.25 2 71 385 0.76 0.48 0.36 rs2069822 IL5
C131906781T 0 19 441 1 1 15 442 0.14 0.75 rs2069812 A131907815G 40
216 205 0.13 43 194 220 1 0.50 0.41 rs2897443 RAD50 T131957493G 11
111 338 0.57 14 137 308 0.88 0.04 0.11 rs6884762 RAD50 T131966629C
0 15 446 1 0 34 424 1 0.01 rs17772583 RAD50 G131981409A 27 180 253
0.54 30 163 266 0.45 0.57 0.52 rs2237060 RAD50 G131998784T 93 234
134 0.64 87 222 150 0.78 0.30 0.49 rs2158177 RAD50 G132011957A 8
112 339 0.85 12 133 314 0.74 0.06 0.17 rs1800925 T132020708C 11 112
338 0.58 14 139 303 0.76 0.03 0.08 rs20541 IL13 A132023863G 6 131
326 0.11 20 140 298 0.46 0.02 0.01 rs848 IL13 A132024399C 6 132 323
0.08 19 145 294 0.88 0.01 0.01 rs1295683 A132026775G 3 78 380 1 6
70 383 0.24 0.89 0.49 rs2243297 A132027070T 0 26 435 1 2 34 423
0.18 0.12 rs2243211 A132029321C 0 54 406 0.39 5 72 379 0.39 0.01
rs762534 A132032655C 0 47 414 0.62 3 69 387 1 0.01 rs2243248
G132036543T 3 50 408 0.23 1 71 387 0.34 0.11 0.08 rs2227282 IL4
C132041078G 18 173 270 0.15 45 162 251 0.02 0.02 0.00 rs2243263 IL4
C132041198G 3 84 373 0.60 9 90 360 0.26 0.17 0.17 rs12186803 KIF3A
A132067968G 4 103 353 0.38 15 110 333 0.15 0.04 0.02 rs10069772
KIF3A A132068587G 4 90 362 0.81 11 105 343 0.43 0.04 0.08
rs17691077 KIF3A C132071250A 9 102 349 0.68 7 97 355 0.83 0.54 0.81
.sup.aPositions according to genomic contig NT_034772.5 (Entrez
Nucleotide). The minor allele is listed first, followed by the
position in National Center for Biotechnology Information Genome
Build 36.2 and then the major allele. .sup.bCounts of genotype 11,
12 and 22. .sup.cP-value from Hardy-Weinberg Equilibrium test
.sup.dThe data for these three SNPs was reported previously
(21).
TABLE-US-00013 TABLE 13 Minor allele frequencies and allele-based
association of 5q31 SNPs with psoriasis .sup.bCase .sup.bControl RS
Number Public Position and alleles.sup.a Study 11 12 22 Sum MAF HWE
11 12 22 Sum rs11568506 SLC22A4 A131699359G SS1 0 12 449 461 0.013
1 0 27 430 457 SS2 2 18 473 493 0.022 0.02 0 16 474 490 SS3 0 16
465 481 0.017 1 0 26 400 426 All 2 46 1387 1435 0.017 0 69 1304
1373 rs4143832 LOC441108 T131890876G SS1 12 102 345 459 0.137 0.17
17 126 316 459 SS2 11 151 331 493 0.175 0.22 21 153 318 492 SS3 15
129 337 481 0.165 0.51 15 117 294 426 All 38 382 1013 1433 0.160 53
396 928 1377 rs2897443 RAD50 T131957493G SS1 11 111 338 460 0.145
0.57 14 137 308 459 SS2 9 161 323 493 0.182 0.03 22 154 316 492 SS3
14 124 344 482 0.158 0.49 22 130 273 425 All 34 396 1005 1435 0.162
58 421 897 1376 rs6884762 RAD50 T131966629C SS1 0 15 446 461 0.016
1 0 34 424 458 SS2 0 30 463 493 0.030 1 0 30 462 492 SS3 0 16 466
482 0.017 1 0 31 394 425 All 0 61 1375 1436 0.021 0 95 1280 1375
rs1800925 IL13 T132020708C SS1 11 112 338 461 0.145 0.58 14 139 303
456 SS2 9 150 335 494 0.170 0.11 21 158 316 495 SS3 16 119 345 480
0.157 0.17 21 131 272 424 All 36 381 1018 1435 0.158 56 428 891
1375 rs20541 IL13 A132023863G SS1 6 131 326 463 0.154 0.11 20 140
298 458 SS2 12 143 339 494 0.169 0.63 12 170 312 494 SS3 8 131 341
480 0.153 0.38 12 138 272 422 All 26 405 1006 1437 0.159 44 448 882
1374 rs848 IL13 A132024399C SS1 6 132 323 461 0.156 0.076 19 145
294 458 SS2 12 144 338 494 0.170 0.53 13 171 308 492 SS3 8 138 334
480 0.160 0.18 13 141 269 423 All 26 414 995 1435 0.162 45 457 871
1373 rs2243211 A132029321C SS1 0 54 406 460 0.059 0.39 5 72 379 456
SS2 0 51 441 492 0.052 0.63 3 67 420 490 SS3 1 64 416 481 0.069
0.72 2 61 362 425 All 1 169 1263 1433 0.060 10 200 1161 1371
rs762534 A132032655C SS1 0 47 414 461 0.051 0.62 3 69 387 459 SS2 1
54 437 492 0.057 1 4 67 420 491 SS3 1 48 433 482 0.052 1 1 48 376
425 All 2 149 1284 1435 0.053 8 184 1183 1375 rs2227282 IL4
C132041078G SS1 18 173 270 461 0.227 0.15 45 162 251 458 SS2 27 188
279 494 0.245 0.63 34 193 265 492 SS3 31 143 306 480 0.214 0.01 31
172 223 426 All 76 504 855 1435 0.229 110 527 739 1376 rs12186803
KIF3A A132067968G SS1 4 103 353 460 0.121 0.38 15 110 333 458 SS2
10 111 373 494 0.133 0.56 7 111 374 492 SS3 7 86 389 482 0.104 0.33
12 94 320 426 All 21 300 1115 1436 0.119 34 315 1027 1376
rs10069772 KIF3A A132068587G SS1 4 90 362 456 0.107 0.81 11 105 343
459 SS2 10 99 381 490 0.121 0.29 11 120 359 490 SS3 5 101 372 478
0.116 0.66 6 101 317 424 All 19 290 1115 1424 0.115 28 326 1019
1373 .sup.bControl RS Number Public Position and alleles.sup.a
Study MAF HWE P.sup.c OR (95% CI) rs11568506 SLC22A4 A131699359G
SS1 0.030 1 0.014 0.43 (0.21-0.86) SS2 0.016 1 0.34 1.37
(0.71-2.63) SS3 0.031 1 0.050 0.53 (0.28-1.00) All 0.025 0.043 0.68
(0.47-0.99) rs4143832 LOC441108 T131890876G SS1 0.174 0.33 0.029
0.75 (0.58-0.97) SS2 0.198 0.67 0.20 0.86 (0.68-1.08) SS3 0.173
0.40 0.68 0.94 (0.74-1.21) All 0.182 0.026 0.85 (0.74-0.98)
rs2897443 RAD50 T131957493G SS1 0.180 0.88 0.041 0.77 (0.60-0.98)
SS2 0.201 0.57 0.27 0.88 (0.70-1.10) SS3 0.205 0.23 0.0092 0.72
(0.57-0.92) All 0.195 0.0010 0.78 (0.69-0.91) rs6884762 RAD50
T131966629C SS1 0.037 1 0.0055 0.42 (0.23-0.79) SS2 0.030 1 0.96
0.99 (0.59-1.66) SS3 0.036 1 0.0078 0.44 (0.24-0.82) All 0.035
0.0025 0.61 (0.44-0.84) rs1800925 IL13 T132020708C SS1 0.183 0.76
0.029 0.76 (0.59-0.97) SS2 0.202 0.78 0.068 0.81 (0.64-1.02) SS3
0.204 0.37 0.010 0.73 (0.57-0.93) All 0.196 0.00015 0.77
(0.67-0.88) rs20541 IL13 A132023863G SS1 0.197 0.46 0.018 0.75
(0.59-0.95) SS2 0.196 0.047 0.12 0.83 (0.66-1.05) SS3 0.192 0.35
0.029 0.76 (0.60-0.97) All 0.195 0.00043 0.78 (0.68-0.90) rs848
IL13 A132024399C SS1 0.200 0.88 0.015 0.74 (0.58-0.94) SS2 0.200
0.067 0.085 0.82 (0.65-1.03) SS3 0.197 0.36 0.040 0.78 (0.61-0.99)
All 0.199 0.00035 0.78 (0.68-0.89) rs2243211 A132029321C SS1 0.090
0.39 0.011 0.63 (0.44-0.90) SS2 0.074 0.74 0.039 0.67 (0.46-0.98)
SS3 0.076 1 0.52 0.88 (0.62-1.26) All 0.080 0.0024 0.72 (0.58-0.89)
rs762534 A132032655C SS1 0.082 1 0.0081 0.60 (0.41-0.87) SS2 0.076
0.51 0.084 0.72 (0.51-1.04) SS3 0.059 1 0.52 0.87 (0.58-1.31) All
0.073 0.0031 0.72 (0.58-0.89) rs2227282 IL4 C132041078G SS1 0.275
0.02 0.017 0.77 (0.62-0.95) SS2 0.265 1 0.30 0.89 (0.73-1.10) SS3
0.275 0.90 0.0024 0.71 (0.57-0.88) All 0.271 0.00022 0.79
(0.70-0.89) rs12186803 KIF3A A132067968G SS1 0.153 0.15 0.045 0.76
(0.58-0.99) SS2 0.127 0.84 0.71 1.05 (0.80-1.36) SS3 0.138 0.15
0.023 0.71 (0.54-0.95) All 0.139 0.027 0.83 (0.71-0.98) rs10069772
KIF3A A132068587G SS1 0.138 0.43 0.044 0.74 (0.56-0.99) SS2 0.145
0.72 0.13 0.81 (0.62-1.05) SS3 0.133 0.67 0.27 0.85 (0.64-1.13) All
0.139 0.0074 0.80 (0.68-0.94) .sup.aPositions according to genomic
contig NT_034772.5 (Entrez Nucleotide). The minor allele is listed
first, followed by the position in National Center for
Biotechnology Information Genome Build 36.2 and then the major
allele. .sup.bCounts for genotypes 11, 12 and 22; MAF: minor allele
frequency: HWE: Hardy-Weinberg P-value .sup.cP values and ORs are
calculated by chi-square method for SS1, SS2 and SS3 and by
Mantel-Haenszel method for the three sample sets combined (All);
P-values for the three IL13 markers in the combined sample sets are
slightly different from our previous report which used Fisher's
exact test (21).
TABLE-US-00014 TABLE 14 LD measures of the twelve significant
markers in controls of sample set 1. D' rs11568506 rs4143832
rs2897443 rs6884762 rs1800925 rs20541 r.sup.2 rs11568506 0.394
0.467 0.04 0.953 0.996 rs4143832 0.001 0.721 0.918 0.747 0.296
rs2897443 0.001 0.501 1 0.908 0.525 rs6884762 0.001 0.154 0.177 1
0.56 rs1800925 0.006 0.517 0.801 0.174 0.552 rs20541 0.007 0.075
0.245 0.05 0.278 rs848 0.008 0.076 0.241 0.048 0.273 0.979
rs2243211 0.003 0.067 0.177 0.121 0.263 0.318 rs762534 0.003 0.091
0.169 0.133 0.212 0.245 rs2227282 0.01 0.067 0.066 0.031 0.059 0.12
rs12186803 0.027 0.049 0.044 0.007 0.035 0.057 rs10069772 0.005
0.007 0.011 0.061 0.016 0.046 D' rs848 rs2243211 rs762534 rs2227282
rs12186803 rs10069772 r.sup.2 rs11568506 0.997 1 1 0.349 0.408
0.993 rs4143832 0.3 0.378 0.465 0.349 0.24 0.097 rs2897443 0.524
0.628 0.646 0.34 0.231 0.123 rs6884762 0.556 0.549 0.555 0.557
0.987 0.505 rs1800925 0.55 0.778 0.735 0.316 0.21 0.148 rs20541
0.993 0.895 0.825 0.431 0.279 0.265 rs848 0.913 0.826 0.441 0.3
0.271 rs2243211 0.328 0.805 0.175 0.855 0.344 rs762534 0.244 0.588
0.26 1 0.415 rs2227282 0.128 0.008 0.016 0.956 0.849 rs12186803
0.065 0.013 0.016 0.436 0.999 rs10069772 0.047 0.074 0.096 0.305
0.029
TABLE-US-00015 TABLE 15 Chromosome 5q31 markers in high LD with
rs1800925 Position Gene r.sup.2 with marker (bp) Symbol SNPType
1800925 rs12652920 131,913,139 IL5 putative 0.895 TFBS.sup.a
rs2706338 131,923,748 RAD50 Intron 0.897 rs2244012 131,929,124
LOC441108 Intron 0.897 rs2299015 131,929,396 RAD50 Intron 0.877
rs2706347 131,933,016 RAD50 putative 0.897 TFBS.sup.a rs2706348
131,933,709 RAD50 Intron 0.897 rs17166050 131,943,112 RAD50
putative 0.897 TFBS.sup.a rs2522403 131,943,216 RAD50 Intron 0.897
rs2246176 131,945,249 RAD50 Intron 0.895 rs2252775 131,946,343
RAD50 Intron 0.897 rs10463893 131,955,938 RAD50 Intron 0.895
rs2897443 131,957,493 RAD50 putative 0.897 TFBS.sup.a rs2706370
131,960,915 RAD50 Intron 0.829 rs2706372 131,963,376 RAD50 Intron
0.89 rs12187537 131,967,803 RAD50 Intron 0.817 rs2522394
131,972,028 RAD50 Intron 0.897 rs10520114 131,976,790 RAD50 Intron
0.897 rs2301713 131,979,895 RAD50 Intron 0.892 rs6596086
131,980,121 RAD50 Intron 0.897 rs2106984 131,980,965 RAD50 Intron
0.897 rs7449456 131,981,326 RAD50 Intron 0.89 rs3798135 131,993,008
RAD50 Intron 0.897 rs3798134 131,993,078 RAD50 Intron 0.894
rs6596087 131,996,508 RAD50 Intron 0.881 rs6871536 131,997,773
RAD50 Intron 0.897 rs12653750 131,999,801 RAD50 Intron 0.897
rs2040703 132,000,157 RAD50 Intron 0.897 rs2040704 132,001,076
RAD50 putative 0.897 TFBS.sup.a rs2074369 132,001,562 RAD50 Intron
0.892 rs7737470 132,001,962 RAD50 Intron 0.897 rs2240032
132,005,026 RAD50 Intron 0.892 rs3091307 132,017,035 Intron 0.897
putative TFBS* (transcription factor binding site)
TABLE-US-00016 TABLE 16 Pairwise genotype counts for cases and
controls. rs11568506 rs1800925 Cases N Controls N GG CC 978 831 GG
CT 370 414 AG CC 38 52 GG TT 35 56 AG CT 7 16 AA CC 2 AG TT 1
TABLE-US-00017 MEGA
* * * * *
References