While there is a clear inherited basis to rheumatoid arthritis, a destructive arthritis that afflicts up to 1% of the adult population, our genetic understanding remains incomplete. From the mid-1970's until 2007, only two RA susceptibility loci had been confirmed unequivocally;over the last year, we have identified and validated two additional gene loci. However, three key issues are: (1) we do not know the exact causal mutation at each locus, (2) we do not yet have a complete catalogue of all RA mutations, and (3) we do not understand how these alleles perturb human immune cells to cause disease. The goal of this proposal is to address these three key issues. Importantly, these key issues impact the long-term goal of using genetics to predict risk of RA prior to clinical onset and to develop new therapeutics. To accomplish our goals, we proposed three Specific Aims:
Specific Aim 1 : Identify the common causal mutations two newly identified RA susceptibility gene loci. We have recently identified two new RA susceptibility loci on chromosomes 9q33 (includes TRAF1 the gene) and 6q23 (includes TNFAIP3). We will use state-of-the-art sequencing technology (Solexa) to identify all known genetic variants within these loci, and define the most accurate set of putative causal mutations at each locus in more than 5,000 RA case-control samples.
Specific Aim 2 : Search for rare protein coding mutations in the TRAF1 and TNFAIP3 genes that also contribute to RA risk (independent of common mutations). We will again use state- of-the-art sequencing technology (Solexa). Here, we will search for rare DNA variants that are more commonly observed in RA cases than in controls by re-sequencing the coding regions of TRAF1 and TNFAIP3 in 500 RA cases and 500 RA controls.
Specific Aim 3 : Test the function of common and rare RA susceptibility mutations using hypothesis-driven experiments. We will generate hypotheses about the predicted function of common and rare variants (Aims 1 and 2), and test these hypotheses in a relevant immune tissue type (e.g., mononuclear and B-cells). This will provide insight into how these alleles cause RA. Completing these Aims will provide substantial progress towards our ultimate goal of a complete understanding of all RA genetic mutations - a necessary step before genetics can be translated to clinical care. Moreover, this approach will be applicable to other RA susceptibility genes as they are identified.

Public Health Relevance

A long-term goal of understanding the genetic basis of rheumatoid arthritis is to improve care of patients with this common and debilitating disease. In theory, identifying specific pieces of DNA (alleles) should aid in diagnosing a treatable condition either prior to onset of symptoms, or early in the course of disease before bone destruction occurs. In addition, genetics should provide insight into important steps of the disease pathway, allowing for the development of new therapies that target these pathways in at-risk individuals.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Research Project (R01)
Project #
5R01AR056768-04
Application #
8259526
Study Section
Genetics of Health and Disease Study Section (GHD)
Program Officer
Wang, Yan Z
Project Start
2009-05-15
Project End
2014-04-30
Budget Start
2012-05-01
Budget End
2013-04-30
Support Year
4
Fiscal Year
2012
Total Cost
$381,704
Indirect Cost
$167,864
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Okada, Yukinori; Diogo, Dorothee; Greenberg, Jeffrey D et al. (2014) Integration of sequence data from a Consanguineous family with genetic data from an outbred population identifies PLB1 as a candidate rheumatoid arthritis risk gene. PLoS One 9:e87645
Okada, Yukinori; Wu, Di; Trynka, Gosia et al. (2014) Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 506:376-81
Diogo, Dorothee; Okada, Yukinori; Plenge, Robert M (2014) Genome-wide association studies to advance our understanding of critical cell types and pathways in rheumatoid arthritis: recent findings and challenges. Curr Opin Rheumatol 26:85-92
Hutchinson, John N; Raj, Towfique; Fagerness, Jes et al. (2014) Allele-specific methylation occurs at genetic variants associated with complex disease. PLoS One 9:e98464
Liao, Katherine P; Diogo, Dorothee; Cui, Jing et al. (2014) Association between low density lipoprotein and rheumatoid arthritis genetic factors with low density lipoprotein levels in rheumatoid arthritis and non-rheumatoid arthritis controls. Ann Rheum Dis 73:1170-5
Li, Gang; Diogo, Dorothee; Wu, Di et al. (2013) Human genetics in rheumatoid arthritis guides a high-throughput drug screen of the CD40 signaling pathway. PLoS Genet 9:e1003487
Cui, Jing; Stahl, Eli A; Saevarsdottir, Saedis et al. (2013) Genome-wide association study and gene expression analysis identifies CD84 as a predictor of response to etanercept therapy in rheumatoid arthritis. PLoS Genet 9:e1003394
Ananthakrishnan, A N; Gainer, V S; Perez, R G et al. (2013) Psychiatric co-morbidity is associated with increased risk of surgery in Crohn's disease. Aliment Pharmacol Ther 37:445-54
Diogo, Dorothee; Kurreeman, Fina; Stahl, Eli A et al. (2013) Rare, low-frequency, and common variants in the protein-coding sequence of biological candidate genes from GWASs contribute to risk of rheumatoid arthritis. Am J Hum Genet 92:15-27
Liao, Katherine P; Kurreeman, Fina; Li, Gang et al. (2013) Associations of autoantibodies, autoimmune risk alleles, and clinical diagnoses from the electronic medical records in rheumatoid arthritis cases and non-rheumatoid arthritis controls. Arthritis Rheum 65:571-81

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