This application addresses broad Challenge Area (03) Biomarker Discovery and Validation and specific Challenge Topic, 03-AR-103 Biomarkers: Bench to Bedside for Autoimmune and Inflammatory Skin and Rheumatic Diseases. Title: Proteomic Identification of Actionable Biomarkers in Rheumatoid Arthritis Project Summary/Abstract Rheumatoid arthritis (RA) is the most common inflammatory joint disease of autoimmune etiology and remains a cause of substantial morbidity and mortality. Effective treatment of RA has been impeded by a paucity of diagnostic/predictive biomarkers of RA, largely as a result of the heterogeneity of the disease and a lack of insight into the mechanisms that underlie the onset and progression of RA. Nevertheless, the advent of biological therapeutics has led to significant advances in the treatment of RA. Promising findings from several placebo-controlled trials support the concept of treating patients in the early stages of RA (early RA) with combination therapies (e.g., methotrexate in concert with an anti-TNF agent) in order to slow and prevent joint damage. Furthermore, recent data suggest that it might be possible to induce disease remission in patients with early RA, such that anti-TNF therapy could then be withdrawn. At present, however, RA is diagnosed once arthritis is already established, a time at which the window of opportunity for effective treatment may have been missed. A test for the early diagnosis of RA is therefore warranted, as early diagnosis would enable the identification of patients with asymptomatic and/or early arthritis for their enrollment in primary RA prevention trials, and could ultimately be used by primary care physicians and rheumatologists to identify pre-disease RA patients that would benefit from early therapeutic intervention. A corollary of this is the need to determine what specific therapy an RA patient should receive, given that approximately one-third of RA patients exhibit robust responses to anti-TNF therapeutics - currently a mainstay of RA therapy - while one-third do not exhibit clinical improvement. Thus, a test that enables prediction of whether or not an RA patient will respond to anti- TNF and other disease-modifying therapies would be of great value to rheumatologists and patients alike. For this Challenge Grant application we propose the development of tests for (i) the early diagnosis of RA, (ii) predicting the severity of RA, and (iii) guiding the selection of RA patients that should receive anti-TNF or small molecule therapies. Robust biomarkers are directly related to the mechanisms underlying disease, and this proposal will provide insights into the mechanisms that underpin the development of autoimmunity in RA, the progression of RA, and the response to anti-TNF therapy. Our laboratory developed RA antigen microarrays to profile the specificity of autoantibody responses in RA. RA antigen microarray analysis revealed the targeting of a variety of candidate native and citrullinated antigens by autoantibodies in established RA. In addition, through the use of optimized BioPlex bead-array methods for the analysis of cytokines in RA sera, we demonstrated that blood cytokine levels are elevated in one-third of patients with early RA, and that elevated blood cytokines are associated with autoantibody targeting of citrullinated proteins. Furthermore, we identified autoantibody and cytokine signatures that differentiate between distinct subsets of RA patients, thus providing insight into the heterogeneity of RA.
In Aim 1, we will expand and apply RA antigen arrays and bead array cytokine assays to characterize serial pre-arthritis samples to determine the specificity and titers of autoantibodies, as well as the levels of serum cytokines, and to define their temporal relationships to the onset of clinical RA. Our overriding hypothesis is that asymptomatic individuals that ultimately develop clinical RA exhibit a series of pre-arthritis phenotypes characterized initially by the production of autoantibodies, subsequently by an increase in cytokine and chemokine levels, and finally by epitope spreading of the autoantibody response, which results in progression to clinical arthritis. Elucidation of the hierarchy of epitope spreading and cytokine elevations will provide insights into the events that trigger progression to clinical RA. Such findings could lead to development of an early RA diagnostic that could provide the basis for preventive interventions in RA. The proposed studies will also identify biomarkers associated with progression to severe RA, and these biomarkers will provide insights into the mechanisms underlying progression of disease. We will further apply these proteomic technologies to identify biomarkers that are (i) predictive of and (ii) pharmacodynamic markers for response to anti-TNF and small molecule therapies.
In Aim 2, we will extend our efforts to convert these biomarkers onto the clinical-grade BioPlex assay format, and we will use BioPlex technology for the high-throughput characterization of all samples in the pre-disease, disease progression, and response to therapy cohorts. The success of this proposal would result in the development of novel clinical diagnostic tests that would transform the care for patients with RA. Rheumatoid arthritis (RA) is a chronic autoimmune arthritis that affects 0.6% of the world population. This proposal will identify novel autoantibody and cytokine biomarkers for (i) early diagnosis, (ii) predicting disease severity, and (iii) guiding therapeutic decision making for the treatment of RA.

Public Health Relevance

Rheumatoid arthritis (RA) is a chronic autoimmune arthritis that affects 0.6% of the world population. This proposal will identify novel autoantibody and cytokine biomarkers for (i) early diagnosis, (ii) predicting disease severity, and (iii) guiding therapeutic decision making for the treatment of RA.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
NIH Challenge Grants and Partnerships Program (RC1)
Project #
1RC1AR058713-01
Application #
7828988
Study Section
Special Emphasis Panel (ZRG1-MOSS-C (58))
Program Officer
Wang, Yan Z
Project Start
2009-09-28
Project End
2011-08-31
Budget Start
2009-09-28
Budget End
2010-08-31
Support Year
1
Fiscal Year
2009
Total Cost
$500,000
Indirect Cost
Name
Stanford University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Giles, Jon T; Danoff, Sonye K; Sokolove, Jeremy et al. (2014) Association of fine specificity and repertoire expansion of anticitrullinated peptide antibodies with rheumatoid arthritis associated interstitial lung disease. Ann Rheum Dis 73:1487-94
Tan, Yann-Chong; Blum, Lisa K; Kongpachith, Sarah et al. (2014) High-throughput sequencing of natively paired antibody chains provides evidence for original antigenic sin shaping the antibody response to influenza vaccination. Clin Immunol 151:55-65
Lu, Daniel R; Tan, Yann-Chong; Kongpachith, Sarah et al. (2014) Identifying functional anti-Staphylococcus aureus antibodies by sequencing antibody repertoires of patient plasmablasts. Clin Immunol 152:77-89
Sokolove, Jeremy; Brennan, Matthew J; Sharpe, Orr et al. (2013) Brief report: citrullination within the atherosclerotic plaque: a potential target for the anti-citrullinated protein antibody response in rheumatoid arthritis. Arthritis Rheum 65:1719-24
Robinson, William H; Lindstrom, Tamsin M; Cheung, Regina K et al. (2013) Mechanistic biomarkers for clinical decision making in rheumatic diseases. Nat Rev Rheumatol 9:267-76
Maecker, Holden T; Lindstrom, Tamsin M; Robinson, William H et al. (2012) New tools for classification and monitoring of autoimmune diseases. Nat Rev Rheumatol 8:317-28
Sokolove, Jeremy; Lindstrom, Tamsin M; Robinson, William H (2012) Development and deployment of antigen arrays for investigation of B-cell fine specificity in autoimmune disease. Front Biosci (Elite Ed) 4:320-30
Zhao, Xiaoyan; Qureshi, Ferhan; Eastman, P Scott et al. (2012) Pre-analytical effects of blood sampling and handling in quantitative immunoassays for rheumatoid arthritis. J Immunol Methods 378:72-80
Lindstrom, Tamsin M; Robinson, William H (2011) Fishing for biomarkers with antigen mimics. Cell 144:13-5
Sokolove, Jeremy; Zhao, Xiaoyan; Chandra, Piyanka E et al. (2011) Immune complexes containing citrullinated fibrinogen costimulate macrophages via Toll-like receptor 4 and Fc? receptor. Arthritis Rheum 63:53-62

Showing the most recent 10 out of 16 publications