U.S. patent application number 10/845473 was filed with the patent office on 2005-01-06 for biological markers for evaluating therapeutic treatment of inflammatory and autoimmune disorders.
Invention is credited to Alters, Susan E., Cheal, Karen L., Kantor, Aaron B..
Application Number | 20050002862 10/845473 |
Document ID | / |
Family ID | 27499728 |
Filed Date | 2005-01-06 |
United States Patent
Application |
20050002862 |
Kind Code |
A1 |
Alters, Susan E. ; et
al. |
January 6, 2005 |
Biological markers for evaluating therapeutic treatment of
inflammatory and autoimmune disorders
Abstract
Novel biological markers indicative of the action of an
anti-inflammatory or immunosuppressive drug can be used to evaluate
drug efficacy and compare local and systemic drug effects. They can
also aid in comparison of different drugs, doses, and delivery
routes. The biological markers include cell populations, cell
surface antigen expression levels, and soluble factor
concentrations. Measurement values of the novel biomarkers were
shown to change significantly in allergic, atopic asthmatic, and
healthy subjects after administration of prednisone.
Inventors: |
Alters, Susan E.; (Palo
Alto, CA) ; Cheal, Karen L.; (Mountain View, CA)
; Kantor, Aaron B.; (San Carlos, CA) |
Correspondence
Address: |
SWANSON & BRATSCHUN L.L.C.
1745 SHEA CENTER DRIVE
SUITE 330
HIGHLANDS RANCH
CO
80129
US
|
Family ID: |
27499728 |
Appl. No.: |
10/845473 |
Filed: |
May 12, 2004 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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10845473 |
May 12, 2004 |
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09956757 |
Sep 20, 2001 |
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6753135 |
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60234313 |
Sep 20, 2000 |
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60239281 |
Oct 10, 2000 |
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60246137 |
Nov 6, 2000 |
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60304563 |
Jul 10, 2001 |
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Current U.S.
Class: |
424/9.1 ;
435/7.1 |
Current CPC
Class: |
G01N 2800/52 20130101;
G01N 33/5008 20130101; G01N 2333/70535 20130101; G01N 33/505
20130101; G01N 33/5094 20130101; G01N 33/5088 20130101; G01N
33/5082 20130101; G01N 33/5047 20130101; G01N 33/5052 20130101;
G01N 33/5023 20130101 |
Class at
Publication: |
424/009.1 ;
435/007.1 |
International
Class: |
A61K 049/00; G01N
033/53 |
Claims
What is claimed is:
1. A method for determining whether a candidate drug is effective
in treating a disease, comprising: administering said candidate
drug to a subject; obtaining a biological sample from said subject;
measuring CD89 expression on granulocytes in said sample; and
comparing said measured expression with a standard expression.
2. The method of claim 1, wherein said standard expression is
obtained by measuring CD89 expression on granulocytes in an
additional sample obtained from said subject before said candidate
drug is administered.
3. The method of claim 1, wherein a particular dose of said
candidate drug is administered, and wherein the method further
comprises determining whether said particular dose is effective in
treating said disease in dependence on said comparison.
4. The method of claim 1, wherein said candidate drug is
administered by a particular delivery route, and wherein the method
further comprises determining whether said particular delivery
route is effective in treating said disease in dependence on said
comparison.
5. The method of claim 1, further comprising determining whether
said candidate drug is effective in treating said disease in
dependence on said comparison.
6. The method of claim 5, wherein determining whether said
candidate drug is effective comprises determining whether said
measured expression is significantly higher than said standard
expression.
7. The method of claim 1, wherein said disease is selected from the
group consisting of inflammatory diseases and autoimmune
diseases.
8. The method of claim 7, wherein said disease is asthma.
9. The method of claim 7, wherein said inflammatory disease is
atopy.
10. The method of claim 1, wherein said biological sample is a
blood sample.
11. The method of claim 1, wherein measuring CD89 expression
comprises measuring a percentage of said granulocytes that express
CD89.
12. The method of claim 1, wherein measuring CD89 expression
comprises measuring intensity of CD89 expression per
granulocyte.
13. A method for determining whether a candidate drug is effective
in treating a disease, comprising: administering said candidate
drug to a subject; obtaining a biological sample from said subject;
measuring a quantity of MMP-3 in said sample; and comparing said
measured quantity with a standard quantity.
14. The method of claim 13, wherein said standard quantity is
obtained by measuring a quantity of MMP-3 in an additional sample
obtained from said subject before said candidate drug is
administered.
15. The method of claim 13, wherein a particular dose of said
candidate drug is administered, and wherein the method further
comprises determining whether said particular dose is effective in
treating said disease in dependence on said comparison.
16. The method of claim 13, wherein said candidate drug is
administered by a particular delivery route, and wherein the method
further comprises determining whether said particular delivery
route is effective in treating said disease in dependence on said
comparison.
17. The method of claim 13, further comprising determining whether
said candidate drug is effective in treating said disease in
dependence on said comparison.
18. The method of claim 17, wherein determining whether said
candidate drug is effective comprises determining whether said
measured quantity is significantly higher than said standard
quantity.
19. The method of claim 13, wherein said disease is selected from
the group consisting of inflammatory diseases and autoimmune
diseases.
20. The method of claim 19, wherein said disease is asthma.
21. The method of claim 19, wherein said disease is atopy.
22. The method of claim 13, wherein said biological sample is a
blood sample.
23. A method for determining whether a candidate drug is effective
in treating a disease, comprising: administering said candidate
drug to a subject; obtaining a biological sample from said subject;
measuring values of a set of factors in said sample, wherein said
set of factors comprises at least two factors selected from the
group consisting of: CD89 expression on granulocytes, CD38
expression on CD4 T cells, HLA-DP, HLA-DQ, HLA-DR, and HLA-PAN
expression on B cells, CD62L expression on B cells, monocyte count,
HLA-DP, HLA-DQ, HLA-DR, and HLA-PAN expression on monocytes, MMP-3
concentration, and SAA concentration; and comparing said measured
values with standard values.
24. The method of claim 23, wherein said set of factors comprises
at least three factors selected from said group.
25. The method of claim 23, wherein said standard values are
obtained by measuring values of said set of factors in an
additional sample acquired from said subject before said candidate
drug is administered.
26. The method of claim 23, further comprising determining whether
said candidate drug is effective in treating said disease in
dependence on said comparison.
27. The method of claim 23, wherein a particular dose of said
candidate drug is administered, and wherein the method further
comprises determining whether said particular dose is effective in
treating said disease in dependence on said comparison.
28. The method of claim 23, wherein said candidate drug is
administered by a particular delivery route, and wherein the method
further comprises determining whether said particular delivery
route is effective in treating said disease in dependence on said
comparison.
29. The method of claim 23, wherein said disease is selected from
the group consisting of inflammatory diseases and auto-immune
diseases.
30. The method of claim 29, wherein said disease is asthma.
31. The method of claim 29, wherein said disease is atopy.
32. The method of claim 23, wherein said biological sample is a
blood sample.
33. The method of claim 23, further comprising measuring values of
at least one of granulocyte count and CRP concentration.
34. A method for detecting a systemic effect of a drug in a
subject, comprising: obtaining a biological sample from said
subject, wherein said sample is correlated with systemic activity;
measuring values of a set of factors in said sample, wherein said
set comprises at least one factor selected from the group
consisting of: CD89 expression on granulocytes, CD38 expression on
CD4 T cells, HLA-DP, HLA-DQ, HLA-DR, and HLA-PAN expression on B
cells, CD62L expression on B cells, monocyte count, HLA-DP, HLA-DQ,
HLA-DR, and HLA-PAN expression on monocytes, MMP-3 concentration,
and SAA concentration; and comparing said measured values with
standard values.
35. The method of claim 34, wherein said drug is selected from the
group consisting of anti-inflammatory drugs and immunosuppressive
drugs.
36. The method of claim 35, wherein said drug is a
glucocorticoid.
37. The method of claim 36, wherein said glucocorticoid is
prednisone.
38. The method of claim 34, wherein said biological sample is
selected from the group consisting of blood and urine.
39. The method of claim 34, further comprising obtaining a local
biological sample from said subject, wherein said local biological
sample is correlated with local activity, and measuring local
values in said local biological sample.
Description
RELATED APPLICATIONS
[0001] This application is a continuation of U.S. application Ser.
No. 09/956,757, "Biological Marker for Evaluating Therapeutic
Treatment of Inflammatory and Autoimmune Disorders," filed Sep. 20,
2001, which claims the benefit of U.S. Provisional Application No.
60/234,313, "Identification of Biomarkers in Atopic Asthma: Effects
of Glucocorticoids on Cell Surface and Soluble Factors," filed Sep.
20, 2000; U.S. Provisional Application No. 60/239,281, "Measurement
and Analysis of Cellular Response to Treatment in Asthma," filed
Oct. 10, 2000; U.S. Provisional Application No. 60/246,137,
"Effects of Oral Prednisone on Biological Markers of Asthma and
Allergy," filed Nov. 6, 2000; and U.S. Provisional Application No.
60/304,563, "Effects of Oral Prednisone on Biological Markers of
Asthma and Allergy," filed Jul. 10, 2001; all of which are herein
incorporated by reference in their entirety.
FIELD OF THE INVENTION
[0002] The present invention relates generally to treatment of
disease in humans and other mammals. More particularly, it relates
to biological markers such as cell populations, cell surface
antigen expression levels, and soluble factor concentrations that
are indicative of the efficacy of treatment of atopic asthma and
other inflammatory disorders.
BACKGROUND OF THE INVENTION
[0003] Prednisone is a corticosteroid used to treat a wide variety
of inflammatory disorders, including asthma, atopy, arthritis,
multiple sclerosis, ulcerative colitis, and Crohn's disease. While
a comprehensive understanding of the action of prednisone and other
glucocorticoids (a class of corticosteroids) is lacking, the drugs
are known to have broad-ranging anti-inflammatory and
immunosuppressive effects, including inhibition of pro-inflammatory
mediators and activation of anti-inflammatory mediators. They
affect the growth, differentiation, and function of monocytes and
lymphocytes; the distribution of cellular subsets; and the
production of cytokines, cellular proteins that are secreted and
affect the behavior of other cells. Because the disorders treated
by glucocorticoids themselves involve unknown immunological
mechanisms, it is unclear which of the many effects of prednisone
are most important in inhibiting the inflammatory response.
[0004] In addition, because of their broad-ranging systemic
effects, prednisone and other glucocorticoids have a large number
of side effects, some of them quite serious, which restrict their
applicability in many patients, particularly for long-term use.
These side effects include weight gain, hyperglycemia, bone
thinning, digestive problems, cataracts, susceptibility to
infection, hypertension, mood swings, and insomnia. It would be
beneficial to have a drug that could provide the desired
anti-inflammatory and immunosuppressive effects of prednisone
without the detrimental side effects. Additionally, localizing the
effects to the region of inflammation (e.g., the lungs) would
minimize the systemic side effects. In order to do so, however,
more information must be obtained about the mechanism of action of
glucocorticoids in treating inflammatory disorders.
[0005] One very common inflammatory disease that has long been
treated with prednisone is asthma, a chronic respiratory syndrome
of uncertain etiology. Typical asthma symptoms include coughing,
wheezing, chest tightness, and shortness of breath. These clinical
symptoms are thought to result from hyper-responsiveness of the
airways and a long-term inflammatory process that causes reversible
obstruction of the airways. Many asthma sufferers also suffer from
atopy, a hypersensitive allergic response to airborne antigens. The
clinical manifestations of atopic asthma arise from the
superposition of environmental factors on genetic predispositions
that increase the probability of developing the syndrome.
[0006] Atopic asthma is an immunologic disease mediated by IgE
antibodies and characterized by infiltration of the airways with
mast cells, lymphocytes, and eosinophils. The allergic response
results from a hyperactivity of T.sub.H2 (type 2 helper) T
lymphocytes, triggering the production of cytokines such as
interleukin (IL)-4, IL-5, IL-6, IL-10, and IL-13, which enhance
antibody production from B cells and induce essential aspects of
the allergic response, such as mucosal tissue injury by
eosinophils. T cells also support IgE-mediated responses to
airborne allergens and orchestrate the recruitment and activation
of primary effector cells. Products released by the inflammatory
cells accumulated in the airways contribute to the tissue
destruction characteristic of asthma.
[0007] A large number of studies have been performed, mostly in
vitro, to elucidate the anti-inflammatory mechanism of
glucocorticoids in diseases such as asthma. One hypothesis is that
glucocorticoids suppress the activation of cells that produce
cytokines to prime eosinophils and induce the migration of
lymphocytes, eosinophils, and basophils into the airway. Upon
entering a cell, glucocorticoids bind with intracellular
glucocorticoid receptors (GR), which are widely distributed among
different cell types. The glucocorticoid-receptor complex then
enters the cell nucleus and turns on specific genes by binding with
DNA and directing the transcription process. In particular,
glucocorticoids interact with two transcription factors, activating
protein 1 (AP-1) and nuclear factor NF-.kappa.B. AP-1 is involved
in the regulation of several genes, including those that express
adhesion molecules and cytokines, while NF-.kappa.B regulates the
transcription of genes involved in the inflammatory response. It is
estimated that each cell type has ten or more target genes per
cell, although they may not all be expressed. It would be highly
desirable to develop new glucocorticoids or other drugs that would
be more selective moderators of gene expression, leading to a
reduction in toxic effects and localization of effects to disease
regions.
[0008] Current studies on the effect of glucocorticoids on asthma
and other inflammatory disorders are performed by measuring the
effect of the drug on quantities of cell types, cell surface
antigen expression, and soluble factors, both in vivo and in vitro.
A number of factors have been shown to be correlated with
glucocorticoid use, such as an increase in circulating granulocytes
or decrease in number of eosinophils, which are responsible for
many of the inflammatory tissue damage effects of asthma. However,
while many studies examine IgE levels and related factors, there
are few data available with respect to other measurements in vivo,
such as cell surface marker expression on granulocytes and
lymphocytes, or soluble factors in serum. Available data are also
conflicting. For example, variable effects of glucocorticoids on T
cell counts have been shown, while B cells are believed to be only
minimally affected by glucocorticoids, with redistribution from
peripheral blood to other lymphoid compartments being of main
importance. There have also been conflicting reports on
immunoglobulin levels post glucocorticoid treatment. As is well
known to those of skill in the art, the correlation b7etween in
vitro and in vivo measurements is tenuous at best, and in vivo
measurements must be performed to obtain information that can be
used for treatment or diagnostic purposes.
[0009] Methods and compositions are currently being developed for
alternative treatments of asthma and other inflammatory disorders
that minimize side effects. Much of this work is devoted to
regulation of the various interleukins. For example, U.S. Pat. No.
5,908,839, issued to Levitt et al., discloses methods for treating
asthma by regulating the function of the IL-9 receptor. U.S. Pat.
No. 5,683,983, issued to Barrett et al., discloses compounds that
bind to the IL-5 receptor. U.S. Pat. No. 5,874,080, issued to
Hebert et al., provides anti-IL-8 monoclonal antibodies for
treatment of asthma.
[0010] In general, much more information must be obtained before
less broad ranging but sufficiently effective anti-inflammatory
drugs can be developed for treatment of autoimmune or inflammatory
diseases such as asthma. In addition, accurate but simple methods
for evaluating drug efficacy are lacking. One of the problems in
elucidating both drug action and disease pathogenesis is that
appropriate tools are lacking to measure a broad range of
applicable immunological components in vivo from a large number of
subjects. Thus many studies on the effects of glucocorticoids on
cellular responses are performed in vitro or in animal models,
neither of which is directly applicable to humans. In addition, the
studies tend to examine factors that are already known to be
implicated in glucocorticoid action, rather than searching for
novel factors that may be useful for indicating the disease
progression or treatment efficacy.
[0011] There is a need, therefore, for a simple but effective
method of gauging the anti-inflammatory or immunosuppressive
response of candidate drugs for treating asthma, atopy, and other
inflammatory diseases. There is also a need for more information
about the mechanism by which glucocorticoids inhibit the
inflammatory response. Further, there is a need for methods to
determine systemic versus local effects of administered drugs.
SUMMARY OF THE INVENTION
[0012] The present invention addresses these needs by providing
novel biological markers (biomarkers) indicative of
anti-inflammatory or immunosuppressive action of a drug in a
subject. These novel biomarkers can be used to assess the
anti-inflammatory action of a drug, detect systemic versus local
effects of an anti-inflammatory drug, and better understand the
mechanism of action of glucocorticoids such as prednisone. The
information obtained can aid in selection of an appropriate
glucocorticoid, dose, and administration route. Additionally, the
information provided by the present invention can help in designing
next generation drugs that have strong anti-inflammatory effects
but fewer or less significant side effects than existing
glucocorticoids.
[0013] The inventive biomarkers include cell populations, cell
surface antigens, and soluble factors whose measurement values in a
biological sample change significantly (either increase or
decrease) after an anti-inflammatory drug is administered to the
subject from whom the sample is obtained. In particular, these
biomarkers include CD89 expression on granulocytes, CD38 expression
on CD4 T cells, HLA class II expression on B cells, CD62L
expression on B cells, monocyte count, HLA class II expression on
monocytes, MMP-3 concentration, and SAA concentration.
[0014] In one embodiment, the invention provides a method for
determining whether a candidate drug is effective in treating an
inflammatory or autoimmune disease. Specific doses and delivery
routes can also be examined. The method is performed by
administering the candidate drug to a subject; obtaining a
biological sample, such as a blood sample, from the subject;
measuring the level of at least one of the inventive biological
markers in the biological sample; and comparing the measured level
with a standard level. Typically, the standard level is obtained by
measuring the same marker or markers in the subject before drug
administration. Depending upon the difference between the measured
and standard levels, the drug can be considered to have an
anti-inflammatory or immunosuppressive effect. Typical
anti-inflammatory diseases treated by the candidate drug include
atopy and asthma. If multiple biomarkers are measured, at least one
and up to all of the biomarkers must change significantly, in the
expected direction, for the drug to be considered
anti-inflammatory. Preferably, multiple markers must change for the
drug to be considered effective.
[0015] In an alternative embodiment, the present invention provides
a method for detecting a systemic effect of an anti-inflammatory
drug (e.g., a glucocorticoid such as prednisone) in a subject. In
this method, a biological sample correlated with systemic activity,
such as blood or urine, is obtained from the subject. Next, a set
of factors including at least one of the inventive biomarkers is
measured in the biological sample. The measured values are then
compared with standard values, preferably measurements of the same
biomarkers taken from the same subject before the drug was
administered. Preferably, measurements are also made of a local
biological sample, one correlated with local rather than systemic
activity, extracted from the same subject. The change in local
values after drug can be analyzed to determine whether the drug has
local effects in addition to or instead of systemic effects.
BRIEF DESCRIPTION OF THE FIGURES
[0016] FIGS. 1A-1B are schematic diagrams illustrating a preferred
embodiment of a method of the invention.
DETAILED DESCRIPTION OF THE INVENTION
[0017] The present inventors have discovered novel biological
markers whose presence and measurement levels are indicative of
action of a drug, particularly a glucocorticoid, to inhibit
inflammation or otherwise suppress the immune response in humans or
other mammals. The inventive biomarkers include cell populations,
cell surface antigen expression levels, and soluble factor
concentrations. According to one definition (NIH), a biological
marker (biomarker) is "a characteristic that is objectively
measured and evaluated as an indicator of normal biologic
processes, pathogenic processes, or pharmacological responses to
therapeutic interventions." Biomarkers can also include patterns or
ensembles of characteristics indicative of particular biological
processes. Note that the biomarker measurement can increase or
decrease to indicate a particular biological event or process. In
addition, if the biomarker measurement typically changes in absence
of the target event, a constant measurement value can indicate
occurrence of the particular biological process. For more
information on biomarker measurement and discovery, see U.S.
application Ser. No. 09/558,909, "Phenotype and Biological Marker
Identification System," filed Apr. 26, 2000, herein incorporated by
reference in its entirety.
[0018] A wide variety of biomarkers can be imagined, including
those for diagnostic, therapeutic, prophylactic, drug discovery,
and patient stratification purposes. In the present invention, the
biomarkers are primarily indicative of a pharmacological response
to a therapeutic intervention. They therefore can be considered to
be efficacy biomarkers, a type of biomarker used to estimate the
efficacy of a drug. In general, efficacy biomarkers must correlate
with the clinical outcome (for example, reduced inflammation), be
mechanistically linked to the disease progress, and significantly
capture the treatment effect of the drug. The biomarkers of the
present invention are believed to satisfy all of these
criteria.
[0019] As described in further detail below, measurement values of
the inventive biomarkers were found to change significantly after
administration of oral prednisone to atopic asthmatics (allergic
asthmatics), allergy sufferers, and healthy subjects, while no
significant changes in their values were found in subjects taking a
placebo. Because the administered dose of prednisone has been
widely documented to inhibit inflammatory effects, it is believed
that these markers are indicators of the anti-inflammatory action
of glucocorticoids. Although the markers have not been predicted
from existing knowledge of asthma pathogenesis and glucocorticoid
action, they can be explained in the context of such knowledge.
[0020] The present invention includes all methods relying on
correlations between the inventive biomarkers and anti-inflammatory
or immunosuppressive actions of a drug. In a preferred embodiment,
the invention provides methods for determining whether a candidate
drug, particularly a glucocorticoid, is effective at treating an
autoimmune or inflammatory disorder such as asthma or atopy.
Different drugs, doses, and delivery routes can be considered by
performing the method for different drug administration conditions
of interest. In alternative embodiments, methods are provided for
detecting systemic effects of anti-inflammatory drugs and comparing
systemic and local effects. Additionally, methods are provided for
designing drugs that target, supply, or stimulate production of the
inventive biomarkers and are therefore effective at treating
inflammatory or autoimmune disorders.
[0021] It is expected that the inventive biomarkers, described in
detail below, will be measured in combination with known markers of
glucocorticoid action. For example, C-reactive protein (CRP) is an
acute-phase plasma protein that can increase 100- to 1000-fold
after a subject's exposure to acute inflammatory stimuli, with
serum levels typically peaking two or three days after stimulation.
Intermediate levels (5- to 50-fold increase above normal) of CRP
are associated with chronic inflammatory conditions such as
cardiovascular disease. Glucocorticoids have been shown to decrease
significantly the levels of CRP. Similarly, glucocorticoids have
been shown to increase the total number of circulating
granulocytes. They have also been shown to decrease expression of
HLA-DP on monocytes. Of course, measurement of the inventive
biomarkers along with any other markers known in the art, including
those not specifically listed herein, falls within the scope of the
present invention.
[0022] In one embodiment, the present invention provides a method
for determining whether a candidate drug is effective in treating
an inflammatory or autoimmune disease. An effective drug is one
that provides a detectable change in the disease symptoms, such as
a reduction in the amount of inflammation. For example,
effectiveness in treating asthma can be gauged by measuring
FEV.sub.1 (forced expiratory volume in one second) with a flow
meter before and after treatment. Inhibition of allergic response
can be correlated with decreasing levels of the immunoglobulin IgE
or an allergen-specific IgE in serum. Of course, there are ranges
of drug efficacy in reducing inflammation or other disease
symptoms, and any range of efficacy falls within the scope of the
present invention. Methods of the present invention are used to
determine whether a candidate drug is effective, independent of
monitoring the disease symptoms themselves. Biomarker measurements
are taken before and after drug administration, and significant
changes in measurement values (in the correct direction) indicate
anti-inflammatory action of the drug. Diseases and disorders whose
treatments can be evaluated using the present method include atopy,
asthma, and autoimmune diseases such as multiple sclerosis, Graves'
disease, myasthenia gravis, rheumatoid arthritis, Crohn's disease,
scleroderma, and acute rheumatic fever.
[0023] FIGS. 1A and 1B schematically illustrate this embodiment of
the invention, a study of the effectiveness of a candidate
anti-inflammatory drug. A subject population 12 having an
inflammatory or autoimmune disorder such as asthma, atopy, or
atopic asthma is selected for the study. The population 12 is
typically selected using standard protocols for selecting clinical
trial subjects. For example, the subjects are generally healthy,
are not taking other medication, and are evenly distributed in age
and sex. The subject population 12 can also be divided into
multiple groups; for example, different sub-populations may be
suffering from different disorders to which the candidate drug is
addressed.
[0024] In general, a number of statistical considerations must be
made in designing the study to ensure that statistically
significant changes in biomarker measurements can be detected
following drug administration. The amount of change in a biomarker
depends upon a number of factors, including strength of the drug,
dose of the drug, and treatment schedule. While larger changes are
easier to detect, even small changes can be statistically
significant and indicative of anti-inflammatory action of the drug.
However, to be detected as significant, smaller changes require a
larger subject population than do larger changes. In particular,
the effect size of a measurement, the expected mean difference in
measurements before and after drug divided by the standard
deviation of the differences, determines the number of subjects
that must be included in the study to observe significant
differences. The number of subjects also depends upon the number of
different independent biomarkers and the effect size being
measured. For example, in order to observe a significant effect
size of 1 or greater in measuring 5 uncorrelated variables, using a
paired t-test, 22 subjects are needed. For detecting effect sizes
of 0.5, 72 subjects are needed. It will be apparent to one skilled
in statistics how to determine appropriate subject population
sizes. Preferably, the study is designed to detect relatively small
effect sizes. It is expected that newly developed drugs will be
designed to have fewer and less severe side effects than currently
available drugs, and therefore produce smaller overall changes at
the cellular level.
[0025] The subjects are "washed out" from any previous drug use for
a suitable period of time. Washout removes effects of any previous
medications so that an accurate baseline measurement can be taken.
At time t.sub.0, a biological sample 14 is obtained from each
subject in the population 12. Preferably, the sample is a blood
sample, but other biological fluids may be used; for example,
possible biological fluids include, but are not limited to, sputum,
urine, bronchoalveolar lavage, bronchoalveolar wash, and nasal
wash. Next, a variety of assays are performed on each subject's
sample 14 to measure levels of particular cell populations,
expressed cell surface antigens, and/or soluble factors. The assays
can use conventional methods and reagents, as described below. If
the sample is blood, then the assays are performed on either whole
blood or on red blood cell-lysed blood. For other fluids,
additional sample preparation steps are included as necessary
before the assays are performed. The assays measure values of
between one and all of the biological markers described below, and
preferably all. In some embodiments, only a single factor is
monitored, while in other embodiments, a combination of factors, up
to the total number of factors, is monitored. The number of
biological markers whose values are measured depends upon, for
example, the availability of assay reagents, biological fluid, and
other resources. Assay results are illustrated schematically in a
chart 16, which contains the baseline measurement values.
[0026] Next, a predetermined dose of a candidate drug 18 is
administered to a portion or sub-population 20 of the same subject
population 12. Drug administration can follow any suitable schedule
over any time period, and the sub-population 20 can include some or
all of the subjects in the population 12. In some cases, varying
doses are administered to different subjects within the
sub-population 20, or the drug is administered by different routes
(e.g., orally vs. inhaled). Suitable doses and administration
routes depend upon specific characteristics of the drug. At time
t.sub.1, after drug administration, a biological sample 22 is
acquired from the sub-population 20. Typically, the acquired sample
is the same type of sample and processed in the same manner (for
example, red blood cell-lysed) as the sample 14 acquired from the
subject population 12 before drug administration. The same assays
are performed on the biological sample 22 as on the biological
sample 14 to obtain measurement values illustrated schematically in
a chart 24. Subsequent sample acquisitions and measurements can be
performed as many times as desired over a range of times t.sub.2 to
t.sub.n.
[0027] Typically, a different sub-population of the subject
population 12, a sub-population 26, is used as a control group, to
which a placebo is administered. The same procedure is then
followed for the control group 26: obtaining the biological sample,
processing the sample, and measuring the biological markers to
obtain a measurement chart 28. Additionally, different drugs can be
administered to any number of different sub-populations to compare
the effects of the multiple drugs. As will be apparent to those of
ordinary skill in the art, the above description is a highly
simplified description of a method involving a clinical trial.
Clinical trials have many more procedural requirements, and it is
to be understood that the method is typically implemented following
all such requirements.
[0028] Paired measurements of the various biomarkers are now
available for each subject. The different measurement values,
represented by charts 16, 24, and 28, are compared and analyzed to
determine whether the biological markers changed significantly in
the expected direction for the drug group but not for the placebo
group, indicating that the candidate drug is effective in treating
the disease. The measurement values at time t.sub.1 for the group
that received the candidate drug are compared with standard
measurement values, preferably the measured values before the drug
was given to the group, i.e., at time t.sub.0. Typically, the
comparison takes the form of statistical analysis of the measured
values of the entire population 20 before and after administration
of the drug or placebo. Any conventional statistical method can be
used to determine whether the changes in biological marker values
are statistically significant. For example, paired comparisons can
be made for each biomarker using either a parametric paired t-test
or a non-parametric sign or sign rank test, depending upon the
distribution of the data.
[0029] In addition, tests should be performed to ensure that
statistically significant changes found in the drug group are not
also found in the placebo group. Without such tests, it cannot be
determined whether the observed changes occur in all patients and
are therefore not a result of candidate drug administration. In
essence, the slopes of the responses over time for both groups are
compared, and only if the two groups do not behave similarly can
the biomarker level changes in the drug group be attributed to the
drug. One possible statistical technique to make this assessment is
the repeated measures analysis of variance test. Other techniques,
such as generalized linear models or linear mixed models, may also
be employed. Note that a statistically significant difference
between the slopes does not guarantee that the marker changed
significantly in the candidate drug group; for this guarantee, the
paired tests described above must be performed.
[0030] Preferably, the analysis also includes modifications to
accommodate the performance of multiple tests on a single data set.
Statistical tests of hypothesis validity are typically assessed by
a p-value, the probability that a given outcome (or a more extreme
one) could have occurred by chance alone. The p-value is computed
assuming the null hypothesis to be true, i.e., that there is no
significant difference between (in this case) the two paired
points. If a p-value is found to be below the significance level
.alpha., usually taken to be 0.05 in the univariate case, then the
null hypothesis is rejected and the result considered to be
statistically significant. A so-called type I error occurs when a
true null hypothesis is rejected and a false positive result found.
For this reason, .alpha. is often referred to as the false positive
rate.
[0031] When multiple independent tests are made on the same
dataset, as is the case with measuring multiple biomarkers, a
distinction must be made between an individual test's false
positive rate and the experiment-wise (overall) false positive
rate. As the number of tests increases, the overall false positive
rate quickly exceeds the desired rate. For the overall rate to
remain at .alpha., the individual values used to assess the
significance of each test's result must be lower than the overall
rate. That is, the p-value for each biomarker's test must be
significantly below 0.05 to maintain an overall false positive rate
of 0.05. Preferably, the p-values are adjusted using the Bonferroni
step-down adjustment method of Holm, a conservative technique to
control the false positive rate. The adjusted values, which are
higher than the unadjusted values, incorporate the effect of
performing multiple tests and can be compared individually to the
overall .alpha.. Biomarkers whose adjusted p-values are less than
.alpha. have changed significantly after drug administration. Note
that conservative statistics are most important when many variables
are considered to obtain a complete pharmacodynamic profile of the
administered drug. When fewer variables are measured, conservative
statistics are less important.
[0032] As indicated below, some of the marker values increase with
anti-inflammatory action, while others decrease. A significant
change in the appropriate direction in the measured value of one or
more of the markers indicates that the drug has an
anti-inflammatory action. If only one biomarker is measured, then
that value must increase or decrease to indicate drug efficacy. If
more than one biomarker is measured, then drug efficacy can be
indicated by change in only one biomarker, all biomarkers, or any
number in between. Preferably, multiple markers are measured, and
drug efficacy is indicated by changes in multiple markers.
Measurements can be of both inventive biomarkers and known
biomarkers (e.g., granulocyte counts). Furthermore, the amount of
change in biomarker level may be an indication of the relative
amount of inflammatory action or extent of a systemic effect.
[0033] In addition to determining whether a particular drug is
effective in treating an inflammatory or autoimmune disorder,
biomarkers of the invention can also be used to examine dose
effects of a candidate drug. There are a number of different ways
that varying doses can be examined. For example, different doses of
a drug can be administered to different subject populations, and
measurements corresponding to each dose analyzed to determine if
the differences in the inventive biomarkers before and after drug
administration are significant. In this way, a minimal dose
required to effect a change can be estimated. In addition, results
from different doses can be compared with each other to determine
how each biomarker behaves as a function of dose.
[0034] Analogously, administration routes of a particular drug can
be examined. The drug can be administered differently to different
subject populations, and measurements corresponding to each
administration route analyzed to determined if the differences in
the inventive biomarkers before and after drug administration are
significant. Results from the different routes can also be compared
with each other directly. For example, a drug can be administered
both orally and inhaled.
[0035] The present invention provides markers indicative of the
action of an anti-inflammatory drug, specifically a glucocorticoid
such as prednisone, in a subject. These biomarkers, monitored
according to methods of the invention, have been shown by the
present inventors to indicate the activity of an anti-inflammatory
or immunosuppressive drug. The following inventive biomarkers are
discussed in more detail below:
[0036] Increase in CD89 (Fc.alpha.R) expression on granulocytes
(both intensity of expression and percentage of granulocytes
expressing CD89)
[0037] Decrease in CD38 expression on CD4 T cells
[0038] Decrease in HLA class II (DP, DR, DQ, PAN) expression on B
cells
[0039] Decrease in CD62L (L-selectin) expression on B cells
[0040] Increase in monocyte count
[0041] Decrease in HLA class II (DP, DQ, PAN) expression on
monocytes (both intensity of expression and percentage of monocytes
expressing HLA class II antigens)
[0042] Increase in MMP-3 (stromelysin) concentration
[0043] Increase in serum amyloid A (SAA) concentration
[0044] To the knowledge of the present inventors, these markers
have never before been shown or predicted to be biomarkers for
anti-inflammatory drug efficacy. In particular, there are no
previous results indicating a correlation between these
observations and prednisone or other glucocorticoids in vivo. It is
to be understood that any correlations between in vivo biological
sample measurements of these biomarkers and anti-inflammatory
action, as used for evaluating drug presence or efficacy or
designing therapies, are within the scope of the present
invention.
[0045] In methods of the invention, biomarker levels are measured
using conventional techniques. Cellular assays measure levels of
granulocytes, T cells, B cells, and monocytes and are preferably
performed by flow cytometry or microvolume laser scanning
cytometry, which allows absolute cell counts to be obtained. Cells
are labeled with commercially-available antibody reagents and
analyzed by cytometry. For measuring the inventive biological
markers, cytometry measurements are required of granulocyte count,
CD89 expression on granulocytes, CD4 T cell count, CD38 expression
on CD4 T cells, monocyte count, HLA class II expression on
monocytes, B cell count, and HLA class II and CD62L expression on B
cells.
[0046] Granulocytes are identified using antibodies for the cell
surface molecules CD15 and CD16. Within the granulocyte population,
CD89 expression is quantified using antibodies for CD89. Both the
relative number of granulocytes expressing CD89 and the intensity
of expression of CD89 can be counted. CD4 T cells are identified
using antibodies to CD4. CD38 expression on CD4 T cells is
quantified using antibodies to CD38. Monocytes are identified using
CD14 monoclonal antibodies, and B cells are identified using CD20
antibodies. Finally, HLA class II antigens are quantified using
antibodies to HLA-PAN, HLA-DR, and HLA-DQ; and CD62L is identified
using antibodies to CD62L.
[0047] MMP-3 and SAA concentrations are preferably measured by
sandwiched ELISA using matched antibody pairs and chemiluminescent
detection. Commercially available monoclonal or polyclonal
antibodies can be used. Standard protocols and data analysis are
used to determine the soluble factor concentrations from the assay
data.
[0048] CD89 Expression on Granulocytes.
[0049] Granulocytes, which include neutrophils, eosinophils, and
basophils, include both phagocytic cells and cells that release
toxic and mediating compounds. In the present invention, a
statistically significant increase in CD89 expression by
granulocytes following administration of the candidate drug
indicates that the drug has an anti-inflammatory or
immunosuppressive effect. As mentioned above, CD89 expression is
reported in two different ways, both of which are indicative of an
anti-inflammatory action. First, anti-inflammatory drugs are
correlated with an increase in the relative percentage of
granulocytes that express CD89. Second, an increase in intensity of
expression of CD89 on granulocytes indicates anti-inflammatory
action of the drug.
[0050] CD89 (Fc.alpha.R) is the Fc receptor for the antibody IgA
and is capable of binding monomeric, dimeric, and polymeric IgA.
IgA is the predominant imunoglobulin in the mucosal surfaces of the
respiratory tract, where it can eliminate excess antigens without
inducing potentially harmful inflammatory reactions. In addition to
its antibody activity, IgA is known to have an independent
regulatory activity upon interaction with CD89 on monocytes and
neutrophils. In monocytes, binding of IgA with CD89 has been shown
to down-regulate production of the inflammatory cytokines
TNF.alpha. and IL-6 and to induce IL-1 receptor antagonist
(IL-1Ra), an inhibitor of pro-inflammatory IL-1 activity (H. M.
Wolf et al., "Anti-inflammatory properties of human serum IgA:
induction of IL-1 receptor antagonist and Fc.alpha.R
(CD89)-mediated down-regulation of tumour necrosis factor-alpha
(TNF-.alpha.) and IL-6 in human monocytes," Clin. Exp. Immunol.,
105: 537-543 (1996)). It is believed that the increased CD89
expression on granulocytes has a similar regulatory effect.
[0051] CD38 Expression on CD4 T Cells.
[0052] CD4 T lymphocytes, which include helper and inflammatory T
cells, activate macrophages and B cells. According to the present
invention, anti-inflammatory drugs decrease CD38.sup.+ CD4 T cells
as a percentage of total CD4 T cells. Depending on the cellular
environment, CD38 can be either a positive or a negative regulator
of cell activation and proliferation. It has also been shown to be
involved in adhesion between human lymphocytes and endothelial
cells (S. Read et al., "CD38.sup.+ CD45RB.sup.low CD4.sup.+ T
cells: a population of T cells with immune regulatory activities in
vitro," Eur. J. Imunol., 28: 3435-3447 (1998)). In vitro
corticosteroid treatment has been shown to affect CD38.sup.+ T
cells (S. Vukmanovic et al., "An Unusual T-Cell Surface Phenotype
in Vivo Correlates with the Failure to Proliferate and Produce IL-2
in Vitro in a Patient with Common Variable Immunodeficiency," Clin.
Immunol. Immunopathol., 65: 261-270 (1992)), but there has
previously been no evidence of its correlation with corticosteroids
in vivo.
[0053] HLA Class II Expression on B Cells.
[0054] B cells whose receptors have recognized an antigen express
HLA class II molecules bound to fragments of the degraded antigen.
Helper CD4 T cells recognize the complex of antigenic fragment and
HLA molecule and activate the B cell to proliferate and produce
antibody. In the present invention, anti-inflammatory action of the
candidate drug is correlated with a decrease in HLA class II
expression. Specifically, DP, DR, DQ, and PAN expression all
decrease. This decrease indicates a less activated state after drug
administration and may reflect a diminished capacity for B cells to
act as antigen presenting cells. Although a decrease in HLA class
II expression on CD4 T cells (V. Gemou-Engesaeth et al., "Inhaled
Glucocorticoid Therapy of Childhood Asthma Is Associated With
Reduced Peripheral Blood T Cell Activation and `Th2-Type` Cytokine
mRNA Expression," Pediatrics, 99: 695-703 (1997)) and on monocytes
(A. G. Oehling et al., "Suppression of the immune system by oral
glucocorticoid therapy in bronchial asthma," Allergy, 52: 144-154
(1997)) has been shown after prednisone treatment, the effect has
not previously been shown on B cells.
[0055] CD62L (L-Selectin) Expression on B Cells.
[0056] L-selectin is part of the selectin family of adhesion
molecules, which mediate the initial attachment of cells to venular
epithelial cells at sites of tissue injury and inflammation.
Selectin-directed therapeutic agents are effective in blocking many
pathological effects resulting from leukocyte entry into
inflammation sites (T. F. Tedder at al., "The selectins: vascular
adhesion molecules," FASEB J., 9: 866-873 (1995)). According to the
present invention, a decrease in CD62L expression on B cells is
correlated with anti-inflammatory action of the candidate drug.
[0057] Monocytes.
[0058] Monocytes are antigen-presenting cells that play a key role
in the inflammatory response. They release a variety of mediators
including complement proteins; IL-1, IL-6, and TNF.alpha.;
growth-promoting molecules such as platelet derived growth factor
and TGF-.beta.; small lipid derivatives such as arachidonate; and
enzymes that affect connective tissue and serum proteins such as
collagenase. In the present invention, a statistically significant
increase in circulating monocyte count following administration of
the candidate drug indicates that the drug has an anti-inflammatory
or immunosuppressive effect. This is in direct contrast to
teachings in the prior art, in which monocytes were found to
decrease in response to glucocorticoid therapy (A. S. Fauci et al.,
"The effect of in vivo hydrocortisone on subpopulations of human
lymphocytes," J. Clin. Invest., 53: 240-246 (1974)).
[0059] HLA Class II Expression on Monocytes.
[0060] In the present invention, anti-inflammatory action of the
candidate drug is correlated with a decrease in HLA class II
expression on monocytes, both intensity of expression and the
percentage of monocytes expressing HLA class II antigens.
Specifically, DP, DR, DQ, and PAN expression all decrease. As with
B cells, this decrease indicates a less activated state after drug
administration and may reflect a diminished capacity for monocytes
to act as antigen presenting cells.
[0061] MMP-3.
[0062] The matrix metalloproteinases (MMPs) are members of a family
of proteolytic enzymes that are capable of degrading a range of
extracellular matrix proteins. MMP-3 (stromelysin) has been
implicated in the release of growth factors that enhance airway
fibrosis (abnormal spread of fiberlike connective tissue), a
structural contributor to airway wall thickening. These structural
changes have also been correlated with progressive decline in lung
function. MMP-3 co-localizes to mast cells, eosinophils, and
neutrophils in bronchial tissue.
[0063] In the present invention, an increase in MMP-3 concentration
indicates an anti-inflammatory action of the administered candidate
drug. In previous studies, MMP-3 concentration was shown to reflect
rheumatoid arthritis activity; that is, an increase in MMP-3
indicated more inflammatory action. In osteoarthritis studies,
glucocorticoids have been shown to suppress MMP synthesis
(DiBattista et al., "Glucocorticoid Receptor Mediated Inhibition of
Interleukin-1 Stimulated Neutral Metalloprotease Synthesis in
Normal Human Chondrocytes," J. Clin. Endocrinol. Metab., 72:
316-326 (1991)), in contrast to the increase found in the present
invention.
[0064] SAA.
[0065] Serum amyloid A (SAA) is an acute-phase plasma protein whose
concentration can increase 10- to 1000-fold after exposure to acute
inflammatory stimuli. Serum levels typically peak two or three days
after stimulation. In the present invention, an increase in SAA
concentration indicates an anti-inflammatory action of the
administered candidate drug. In previous clinical and in vivo
studies in animals, SAA concentration was shown to decrease with
corticosteroids (Marhaug et al., "Serum amyloid A: an acute phase
apolipoprotein and precursor of AA amyloid," Baillieres Clin.
Rheumatol., 8: 553-572 (1994). However, in most in vitro studies,
corticosteroids increase SAA production in cultured cells (Jensen
et al., "Regulation of serum amyloid A protein expression during
the acute-phase response," Biochem J., 334: 489-503 (1998)). In
vitro, the dramatic induction of SAA mRNA in response to
pro-inflammatory stimuli is due largely to the synergistic effects
of cytokine signaling pathways, principally those of IL-1 and IL-6;
this induction can be enhanced by glucocorticoids. Note that CRP,
as mentioned above, has previously been shown to decrease in
response to glucocorticoids, in contrast to SAA. It is advantageous
to measure both soluble factors to gain more information about the
effect of the candidate drug.
[0066] One desired quality of an anti-inflammatory drug is that its
effect is local, rather than systemic. A local action addresses the
disease symptoms and directly affects the disease pathway without
causing broad-ranging side effects. Oral corticosteroids are known
to have a very large systemic effect, and therefore decrease the
disease symptoms while also producing side effects localized to
other regions of the body. Systemic effects can be detected in
biological fluids such as blood and urine. Local effects, in
contrast, can be detected only minimally, if at all, in the blood,
but can be detected in localized fluids such as sputum,
bronchoalveolar wash, and bronchoalveolar lavage. Note that
identifying a systemic effect of a drug can be desirable or
undesirable, depending upon the context. Because a drug that
affects the entire system also affects the local region of
inflammation, the detected systemic effect indicates that drug has
the desired anti-inflammatory or immunosuppressive action. However,
if the systemic effect includes undesirable side effects, then it
is desirable to minimize the systemic effect while maximizing the
local effect. The present invention can be used to evaluate the
type of effect a drug is causing.
[0067] In an alternative embodiment of the invention, a method is
provided for detecting whether a systemic effect has been produced
by an anti-inflammatory drug, particularly a glucocorticoid such as
prednisone. The specific techniques used in implementing this
embodiment are similar to those used in the embodiment described
above. Again, a subject population is chosen as described above and
washed out from all previous drug use. A baseline measurement is
obtained by acquiring a biological sample indicative of systemic
effects, such as blood or urine, from each subject. The samples are
then analyzed using the assays described above to measure the
inventive biomarkers or some number of the inventive biomarkers.
Subsequently, a suitable treatment regimen of the anti-inflammatory
drug is administered to a portion of the subjects, and the same
type of sample is acquired from the subject group at some time
after drug administration. Measurements are again made of the
inventive biomarkers, or some portion of the inventive biomarkers.
The measurements before and after are compared, preferably using
the statistical analyses described above, to determine whether
statistically significant differences in the biomarker values are
found before and after drug administration. If the values of at
least some (and preferably all) of the biomarkers are found to be
different, and if the differences are in the correct direction,
then it is likely that the administered drug has a systemic
effect.
[0068] This embodiment of the invention can be particularly useful
for testing whether a drug believed to have only a local effect, or
a method of delivery believed to have only a local effect, actually
has a systemic effect. Furthermore, the measured values of the
biomarkers can be indicative of the degree of the effect. That is,
for a given dose and type of drug, a larger change in biomarker
can, in some cases, be correlated with a larger systemic effect.
The amount of change in biomarker value can also be correlated with
the administered dose of the drug.
[0069] In a further additional embodiment, comparisons can be made
between local and systemic effects by measuring the same biomarkers
in fluids that are more representative of local action, rather than
systemic action. Such fluids include sputum, nasal wash,
bronchoalveolar lavage, and bronchoalveolar wash. In this
embodiment, different biological fluids are obtained from the
subjects at a single time point. The obtained fluids include both a
fluid indicative of local effects and a fluid indicative of
systemic effects. Measurements are made before and after drug
administration as described above for the previous embodiments.
Similar analysis is made of the different fluids as described above
for single fluids. The amount of change in biomarker values before
and after drug administration is compared for the different fluids.
If, for example, no significant changes are seen in blood, while
large changes are seen in sputum, there is an indication that the
drug or delivery method has predominantly local effects.
Alternatively, if statistically significant changes are noted in
both fluids, then it is likely that the drug has both local and
systemic effects.
[0070] Different fluids require different sample collection and
preparation methods. For example, sputum, bronchoalveloar wash, and
bronchoalveolar lavage are preferably collected by the following
methods. Sputum induction is accomplished after methacholine
challenge. Subjects are pre-treated with 360 .mu.g albuterol
administered by metered dose inhaler (4 puffs) with repeat
spirometry 10 minutes later to document that the post-albuterol
FEV.sub.1 is .gtoreq.60% predicted. Subjects are then seated in an
aerosol containment chamber where they inhale nebulized sterile 3%
saline for 12 minutes using a mouthpiece connected by corrugated
tubing to an ultrasonic nebulizer. The procedure is interrupted
every 2 minutes to allow for expectoration and subjects are
instructed to spit into a plastic container before coughing deeply
into a separate sterile plastic container for analysis. In all
subjects, PEF is monitored at 2-minute intervals and those whose
PEF declined to .ltoreq.80% of baseline post-bronchodilator
FEV.sub.1 will have the induction stopped. Sputum samples are
incubated with DTT, DNAse and collagenase, washed, centrifuged and
counted to yield a single cell suspension free of mucosal fluid.
Staining for airway secretions is best performed done on ice, with
washing to reduce non-specific staining.
[0071] Bronchoscopy, by which broncheoalveolar fluids are obtained,
involves passing a flexible bronchoscope through the mouth and into
the lungs. Subjects fast for 8 hours before bronchoscopy. Subjects
are given an injection of atropine to reduce bronchial secretions.
Subjects may also receive morphine, fentanyl or midazolam, if
needed, to suppress cough or to reduce anxiety. Morphine and
fentanyl are given to suppress cough. Midazolam is a drug like
diazepam and is given to reduce gagging and nervousness. Atropine
and morphine, if given, are given intramuscularly or intravenously
while midazolam, if given, is given intravenously. Mouth and throat
are anesthetized by spraying lidocaine, a bitter-tasting
anesthetic, and cotton soaked in lidocaine is touched to the back
of the throat. The bronchoscope, which is about the thickness of a
pencil (1/4 inch), is passed through the mouth and between vocal
cords, after which time the subject is unable to talk. Small
amounts of lidocaine are sprayed through the bronchoscope onto the
vocal cords and other areas within the lung to abolish cough. The
bronchoscope is passed into one of the bronchial tubes on the right
lung and 50 ml (2 ounces) of saline infused and immediately removed
by suction through the suction channel of the bronchoscope
(bronchial washing). Then the bronchoscope is wedged in the distal
airway and 2 more samples of 50 ml of saline are infused and
immediately removed by suction as well (bronchioalveolar lavage).
The bronchoscope is in place for 10-15 minutes. During the
procedure, the subject has continuous pulse oximetry monitoring and
frequent measurement of blood pressure, respiratory rate and pulse
rate. After bronchoscopy, subjects are monitored for 2 hours until
they recover the gagging reflex and are able to eat and drink.
Bronchial samples are centrifuged, counted and resuspended at
standard concentration for staining.
[0072] Note that while statistically significant effects can only
be detected in the context of a suitable sample size, trends can be
noted in single subjects or in a very small subject population. For
example, the inventive biological markers can be measured in a
single person before and after administration of a drug. If the
change in biomarker value is consistent with the change expected
for a large subject population taking an anti-inflammatory drug,
then the result may provide encouragement for proceeding with a
larger study.
[0073] As described below, the inventive biomarkers were discovered
during a study of prednisone on atopic and asthmatic subjects. Thus
it is expected that a large number of the inventive biomarkers are
relevant for anti-inflammatory drugs having a structure similar to
that of prednisone. As the drug structure becomes increasingly
different from that of prednisone, however, it is likely that only
a subset of the inventive biomarkers will change as expected.
Furthermore, it is likely that the amount of change in biomarker
value caused by the candidate drugs will be less than the amount
caused by prednisone.
[0074] Prednisone is a glucocorticoid, a class of corticosteroids,
compounds with the general ring structure of steroids. Other
glucocorticoids include dexamethasone, cortisol, cortisone,
triamcinolone acetonide, betamethasone, prednisolone, and
methylprednisolone. Briefly, glucocorticoids induce numerous
cellular and physiological effects that are mediated predominantly
through their interaction with the cytosolic steroid hormone
receptor GR (glucocorticoid receptor). Glucocorticoid enters the
cell and binds with the GR. The glucocorticoid-receptor complex
then enters the cell nucleus and turns on specific genes by binding
with DNA and directing the transcription process. Because this
mechanism is specific to glucocorticoids, it is believed that fewer
of the inventive biomarkers will be relevant to anti-inflammatory
drugs having significantly different structures.
[0075] In fact, as additional candidate drugs are tested using
methods of the invention, it will be possible to determine which of
the biomarkers are correlated with desired effects and which are
correlated with side effects or less desired effects. This
information can then be used in designing and developing drugs
tailored to address only relevant disease mechanisms while causing
fewer side effects.
[0076] In this additional embodiment of the invention, different
candidate drugs are administered to subjects, and the side effects
and anti-inflammatory or immunosuppressive actions documented. Any
conventional metrics of anti-inflammatory action and side effect
severity can be used. In addition, before and after drug
administration, the inventive biomarkers are measured, either with
or without additional markers or factors. Measurement levels are
analyzed to determine which biomarkers change significantly. In
this way, the biomarkers affected by each drug can be correlated
with the particular desirable and undesirable effects of the drug.
It is anticipated that new drugs being developed will have fewer
side effects and cause changes in fewer of the inventive
biomarkers. As additional generations of drugs are developed, the
list of relevant biomarkers and their amount of change can be
refined further. In addition, as it becomes clear whether each
biomarker is indicative of desired or undesired effects, more
information about the mechanisms of drug action are learned,
helping to direct development of next generation drugs.
[0077] Although the invention has been described in the context of
administering anti-inflammatory drugs to humans, it can be equally
well applied to detecting the effects of anti-inflammatory drugs in
animal models, particularly those with immune systems similar to
the human immune system. For example, suitable animals include
mice, rats, and rabbits.
[0078] The novel biomarkers of the present invention can also be
used to help in designing anti-inflammatory or immunosuppressive
drugs with fewer and less severe side effects than those of
prednisone. For example, treatment can be developed to increase
MMP-3 expression or CD89 expression on granulocytes.
[0079] The present invention represents a specific practical
application of a general biomarker discovery method described in
U.S. application Ser. No. 09/558,909, "Phenotype and Biological
Marker Identification System," filed Apr. 26, 2000, herein
incorporated by reference in its entirety. In this particular case,
the method was used to phenotype asthma and allergy patients before
and after administration of the glucocorticoid prednisone and a
placebo. This technique allows rapid, efficient, and accurate
measurement of a broad range of cell populations, cell surface
antigen expression levels, and soluble factors. Because the
phenotyping system can measure such a large number of variables, it
facilitates discovery of novel biomarkers. Without such a tool,
studies focus predominantly on factors already known or believed to
be important in disease pathogenesis or drug behavior. Although the
example was used to obtain a complete pharmacodynamic profile of
drug action, the present invention is focused primarily on the
novel biomarkers discovered within the profile.
[0080] The following example describes measurement, analysis, and
identification of the inventive biomarkers.
EXAMPLE
Effect of Prednisone on Biological Markers of Atopy and Asthma
[0081] Methods
[0082] The inventive biomarkers were identified in a study of the
effects of oral prednisone on biological markers of allergy and
asthma. Eighty subjects were enrolled in the study, 23 with atopic
asthma, 28 with allergy alone, 26 with neither allergy nor asthma
(healthy controls), and 3 with asthma alone. Allergy was defined by
a positive skin prick test. Mild asthma was defined as positive
methacholine challenge within the last three months, as well as one
or more of documented diagnosis of asthma, history of cough,
recurrent wheeze, recurrent difficult breathing, and recurrent
chest tightening. Approximately half of the subjects from each
disease group were given oral prednisone for three days, while the
other half was given a placebo. Blood samples were taken before
treatment and after three days of treatment with oral prednisone or
placebo.
[0083] Cellular markers in the blood samples were evaluated using
the SurroScan.TM. microvolume laser scanning cytometry system for
multiparameter cellular analysis. Monoclonal antigen-specific
antibodies were purchased from commercial vendors and coupled to
one of three different fluorophores, Cy5, Cy5.5, and Cy7-APC.
Assays were performed to monitor cell counts of more than 200
different cell populations, including granulocytes, eosinophils,
monocytes, CD4 and CD8 T cells, B cells, and NK cells. In addition,
the relative levels of 49 different cell surface antigens
(activation antigens, co-stimulatory molecules, adhesion molecules,
antigen receptors, cytokine receptors) on specific cell populations
were measured. The prepared antibody-dye reagents were combined
into cocktails and incubated with aliquots of whole or red blood
cell-lysed blood in the dark at room temperature for 20 minutes.
The samples were then diluted with an appropriate buffer and loaded
into capillary arrays for analysis. Each fluorophore was measured
in a separate detection channel, and images were converted to flow
cytometry standard format and analyzed with FlowJo.TM. cytometry
analysis software. Template gates were used to enumerate the cell
populations of interest in all of the assays.
[0084] Soluble factor assays were in a sandwich ELISA format using
matched antibody pairs and chemiluminescent detection. Sixty-seven
soluble factor assays were performed using commercially-available
monoclonal and polyclonal analyte-specific antibodies. Capture
antibodies were incubated in 96-well black opaque microtiter plates
overnight at 4.degree. C., washed, and blocked. Samples were added
to the wells, incubated, and washed. Biotinylated detection
antibody was then added, incubated, and washed, followed by
incubation with avidin-alkaline phosphatase and another wash.
Finally, the chemiluminescent alkaline phosphatase substrate was
added and incubated before reading. Standard curves and analyte
amounts were determined using curve fitting techniques.
[0085] Data Analysis
[0086] Following data acquisition, variables were analyzed to
assess differences in subject groups before drug administration, as
well as changes following drug administration. A total of 713
variables, including cell populations, cell surface antigen
expression, and soluble factors, were analyzed. Because this data
set contains more variables than subjects, and because all
variables were considered potential biomarkers, many statistical
techniques were not applicable, and a more conservative approach
was used to analyze the data. Univariate tests were performed on
individual variables, and the step-down Bonferroni p-value
adjustment method of Holm was employed to control for multiple
comparisons. The Bonferroni correction, which reduces the number of
false positives, is described above.
[0087] The drug and placebo samples before drug administration were
analyzed using the nonparametric Wilcoxon two-sample test and a
parametric two-sample t-test. All of the p-values were adjusted
using the step-down Bonferroni method. The different disease groups
(allergy, asthma-allergy, healthy) were compared using the
nonparametric Kruskal-Wallis test and analysis of variables (ANOVA)
techniques, with p-values adjusted by the step-down Bonferroni
method.
[0088] Univariate tests were performed on the data before and after
drug administration for both the drug and placebo groups. In order
to determine whether any non-normality of the data affected the
tests, both non-parametric tests (sign rank or sign) and parametric
paired t-tests were performed. Statistical tests for normality,
skewness, and kurtosis were performed per variable to assess
normality. For sufficiently normally distributed data, the paired
t-test result was used; otherwise, the nonparametric result was
used. All p-values were adjusted using the step-down Bonferroni
method, maintaining the overall study false positive rate below 5%.
27% of the variables showed significant differences before and
after drug administration. When the analysis was performed on the
separate disease classes individually, no significant differences
were found before and after drug administration.
[0089] Additionally, a linear-mixed model was used to evaluate
fixed and random effects for the prednisone and placebo groups.
This model notes the difference in response in the drug and placebo
to indicate whether the observed trends can be attributed to the
drug alone. The model, executed with PROC MIXED in SAS.TM., used
the three fixed effects of drug, time, and (drug.times.time) to fit
the data. All of the inventive biomarkers found to change
significantly with the paired tests were also found to be
significant with the linear mixed model.
[0090] Finally, one and two variable discriminant analyses were
performed to differentiate the prednisone and placebo groups.
Discriminant analysis determines which variables can be used to
classify subjects into groups. Normalized variables (difference
over time divided by initial value) were calculated from the raw
data to create better discriminators. All of the variables were
analyzed in the single variable discriminant analysis, and
variables shown to be significantly different between the two
groups were included in the two variable discriminant analysis.
Good discriminators were selected based on two criteria: a low
classification error rate and a low number of missing values.
[0091] Results
[0092] The two subject groups, prednisone and placebo, were found
to be statistically equivalent. There was only one significant
difference, based on the adjusted p-value, among the three
different disease groups before treatment. As expected, the
asthma-allergy and allergy-only groups had significantly higher
(adjusted p-value<0.007) serum IgE levels than the healthy group
before treatment.
[0093] Table 1 shows mean values before and after drug
administration for the inventive biomarkers. Standard deviations
are shown in parentheses. The results are for all disease groups,
atopic, atopic asthmatic, and healthy subjects. Results for other
measured variables are not shown. Tests for all biomarkers had an
adjusted p-value of less than 0.001. Cell surface expression
intensity levels are in arbitrary units.
1TABLE 1 Mean Pre Drug Mean Post Drug Population/Antigen/Analyte
(SD) (SD) CD89.sup.+ granulocyte population (% of 85 (20) 96 (9)
total granulocytes) CD89 on granulocytes 2047 (1549) 2527 (1691)
CD38.sup.+ CD4 T cells (% of all CD4 T 32.9 (9.8) 29.3 (9.1) cells)
HLA-DQ on B cells 3123 (1090) 1680 (817) HLA-DR on B cells 8108
(2711) 4486 (2025) HLA-PAN on B cells 11684 (3190) 6550 (3123)
CD62L on B cells 2998 (505) 2479 (478) Monocytes (cells/.mu.l) 369
(121) 478 (160) HLADQ.sup.+ monocyte population 8.7 (4.39) 3.6
(2.49) (% of total monocytes) HLADR.sup.+ monocyte population 84.4
(14.0) 75.4 (16.9) (% of total monocytes) HLAPAN.sup.+ monocyte
population 91.8 (8.4) 83.0 (15.1) (% of total monocytes) HLA-DQ on
monocytes 165 (103) 69 (52) HLA-DR on monocytes 2966 (1068) 1970
(729) HLA-PAN on monocytes 4961 (1738) 3196 (1046) MMP-3 (ng/ml) 37
(29) 188 (140) SAA (.mu.g/ml) 2.73 (3.3) 6.71 (14.5)
[0094] Note that HLA-DP expression on monocytes and B cells was not
measured. However, it is expected that the HLA-DP response to
glucocorticoids is similar to that of the other HLA class II
antigens.
[0095] The discriminant analysis showed HLA class II expression on
B cells to be one of the best discriminators between prednisone and
placebo. HLA-PAN misclassified only 3 subjects, while HLA-DQ and
HLA-DR misclassified only 4 subjects. These three subjects were in
the prednisone group but were misclassified into the placebo group.
Based on other information, the misclassified subjects are believed
not to have complied with the study protocol.
[0096] Note also that although only asthma and allergy were
studied, the effects were noted in all subjects, even the healthy
controls. Thus the anti-inflammatory and immunosuppressive effects
are not specific to treatment of asthma or atopy, but to any
disorder being treated by glucocorticoids.
[0097] It should be noted that the foregoing description is only
illustrative of the invention. Various alternatives and
modifications can be devised by those skilled in the art without
departing from the invention. Accordingly, the present invention is
intended to embrace all such alternatives, modifications and
variances which fall within the scope of the disclosed
invention.
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