Identification of genetic, serum, and clinical factors to allow stratification of patients with early rheumatoid arthritis (RA) according to risk of radiographic severity would improve quality of life for RA patients and benefit society by substantially lowering morbidity and treatment costs. Genetic influences on radiographic severity of RA may vary by race/ethnicity, and African-Americans are significantly under-represented in RA research studies. Genome-wide gene expression profiling and proteomic techniques have revolutionized approaches to identifying markers of disease susceptibility and severity. We hypothesize that a combination of gene expression patterns in PBMCs, serum protein profiles, and clinical parameters can successfully distinguish African-Americans with early RA who will develop severe radiographic damage from those who will not. The NIH-funded CLEAR (Consortium for the Longitudinal Evaluation of African-Americans with Early RA) Registry is a unique multi-center, prospective, longitudinal study in which comprehensive demographic, socioeconomic, clinical, and serial radiographic data, as well as DNA and serum, are available. Through collaboration with the Autoimmune Biomarkers Collaborative Network (ABCoN), RNA samples suitable for gene expression microarray analyses are currently banked on CLEAR patients. We propose the following specific aims: 1. To identify differences in baseline gene expression profiles in PBMCs of African-American RA patients with severe vs. mild radiographic damage at 3 years'disease duration, using microarrays;2. To identify serologic factors influencing radiographic severity of RA in African-Americans by analyzing baseline serum levels of a panel of cytokines, growth factors, and soluble receptors using chip and bead-based assays;and 3. To determine the relative contributions of clinical, genetic, and serologic factors on radiographic severity of RA in African-Americans using statistical models developed by the MCRC Methology Core. The ultimate goal of this proposal is to translate insights from clinical rheumatology, biotechnology, and statistical genetics into clinically useful tests to predict radiographic severity of RA in African-Americans. When robust, reliable markers of radiographic severity are established, treatment stategies can be optimized for individual patients, which will significantly improve the clinical care of African-Americans with RA. In addition, these studies will provide considerable new insights into the pathogenesis of RA.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Comprehensive Center (P60)
Project #
5P60AR048095-10
Application #
8380610
Study Section
Special Emphasis Panel (ZAR1-CHW-G)
Project Start
Project End
2014-06-30
Budget Start
2012-07-01
Budget End
2013-06-30
Support Year
10
Fiscal Year
2012
Total Cost
$276,673
Indirect Cost
$87,528
Name
University of Alabama Birmingham
Department
Type
DUNS #
063690705
City
Birmingham
State
AL
Country
United States
Zip Code
35294
Li, Peng; Redden, David T (2015) Comparing denominator degrees of freedom approximations for the generalized linear mixed model in analyzing binary outcome in small sample cluster-randomized trials. BMC Med Res Methodol 15:38
Cui, Xiangqin; Yu, Shaohua; Tamhane, Ashutosh et al. (2015) Simple regression for correcting ΔCt bias in RT-qPCR low-density array data normalization. BMC Genomics 16:82
Deshane, Jessy S; Redden, David T; Zeng, Meiqin et al. (2015) Subsets of airway myeloid-derived regulatory cells distinguish mild asthma from chronic obstructive pulmonary disease. J Allergy Clin Immunol 135:413-424.e15
Tang, Qi; Danila, Maria I; Cui, Xiangqin et al. (2015) Expression of Interferon-γ Receptor Genes in Peripheral Blood Mononuclear Cells Is Associated With Rheumatoid Arthritis and Its Radiographic Severity in African Americans. Arthritis Rheumatol 67:1165-70
Bruce, Ian N; O'Keeffe, Aidan G; Farewell, Vern et al. (2015) Factors associated with damage accrual in patients with systemic lupus erythematosus: results from the Systemic Lupus International Collaborating Clinics (SLICC) Inception Cohort. Ann Rheum Dis 74:1706-13
Yang, Celeste; Bartolucci, Alfred A; Cui, Xiangqin (2015) Multigroup Equivalence Analysis for High-Dimensional Expression Data. Cancer Inform 14:253-63
Li, Peng; Redden, David T (2015) Small sample performance of bias-corrected sandwich estimators for cluster-randomized trials with binary outcomes. Stat Med 34:281-96
Danila, M I; Westfall, A O; Raman, K et al. (2015) The role of genetic variants in CRP in radiographic severity in African Americans with early and established rheumatoid arthritis. Genes Immun 16:446-51
Tamhane, Ashutosh; McGwin Jr, Gerald; Redden, David T et al. (2014) Complementary and alternative medicine use in African Americans with rheumatoid arthritis. Arthritis Care Res (Hoboken) 66:180-9
Aslibekyan, Stella; Sha, Jin; Redden, David T et al. (2014) Gene-body mass index interactions are associated with methotrexate toxicity in rheumatoid arthritis. Ann Rheum Dis 73:785-6

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