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Data for Genetic Analysis Workshop (GAW) 15 Problem 2, genetic causes of rheumatoid arthritis and associated traits.

ABSTRACT: For Genetic Analysis Workshop 15 Problem 2, we organized data from several ongoing studies designed to identify genetic and environmental risk factors for rheumatoid arthritis. Data were derived from the North American Rheumatoid Arthritis Consortium (NARAC), collaboration among Canadian researchers, the European Consortium on Rheumatoid Arthritis Families (ECRAF), and investigators from Manchester, England. All groups used a common standard for defining rheumatoid arthritis, but NARAC also further selected for a more severe phenotype in the probands. Genotyping and family structures for microsatellite-based linkage analysis were provided from all centers. In addition, all centers but ECRAF have genotyped families for linkage analysis using SNPs and these data were additionally provided. NARAC also had additional data from a dense genotyping analysis of a region of chromosome 18 and results from candidate gene studies, which were provided. Finally, smoking influences risk for rheumatoid arthritis, and data were provided from the NARAC study on this behavior as well as some additional phenotypes measuring severity. Several questions could be evaluated using the data that were provided. These include comparing linkage analysis using single-nucleotide polymorphisms versus microsatellites and identifying credible regions of linkage outside the HLA region on chromosome 6p13, which has been extensively documented; evaluating the joint effects of smoking with genetic factors; and identifying more homogenous subsets of families for whom genetic susceptibility might be stronger, so that linkage and association studies may be more efficiently conducted.

SUBMITTER: Amos CI

PROVIDER: S-EPMC2367518 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature

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Data for Genetic Analysis Workshop (GAW) 15 Problem 2, genetic causes of rheumatoid arthritis and associated traits.

Amos Christopher I CI Chen Wei Vivien WV Remmers Elaine E Siminovitch Katherine A KA Seldin Michael F MF Criswell Lindsey A LA Lee Annette T AT John Sally S Shephard Neil D ND Worthington Jane J Cornelis Francois F Plenge Robert M RM Begovich Ann B AB Dyer Thomas D TD Kastner Daniel L DL Gregersen Peter K PK

BMC proceedings 20071218

For Genetic Analysis Workshop 15 Problem 2, we organized data from several ongoing studies designed to identify genetic and environmental risk factors for rheumatoid arthritis. Data were derived from the North American Rheumatoid Arthritis Consortium (NARAC), collaboration among Canadian researchers, the European Consortium on Rheumatoid Arthritis Families (ECRAF), and investigators from Manchester, England. All groups used a common standard for defining rheumatoid arthritis, but NARAC also furt ...[more]

PMID: 18466527

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Project description:ObjectiveTo investigate the association between obesity-related traits and risk of rheumatoid arthritis (RA).MethodsWe conducted genetic correlation analysis and a 2-sample Mendelian randomization (MR) study, using genome-wide genetic data based on >850,000 individuals of European ancestry. Summary statistics were collected from the largest genome-wide association study conducted to date for body mass index (BMI; n = 806,810), waist-to-hip ratio (WHR; n = 697,734), WHR adjusted for BMI (WHRadjBMI; n = 694,649), and RA (ncase = 14,361, ncontrol = 43,923). We conducted cross-trait linkage disequilibrium score regression and ρ-HESS analyses to quantify genetic correlation between pairs of traits (causal overlap). For each obesity-related exposure, we utilized independent, genome-wide significant single-nucleotide polymorphisms (P < 5 × 10-9 ) as instruments to perform MR analysis (causal relationship). We interrogated the causal relationship both in the general population and in a sex-specific manner and calculated odds ratios (ORs) and 95% confidence intervals (95% CIs). Sensitivity analyses were performed to validate MR model assumptions.ResultsDespite a negligible overall genetic correlation between the 3 obesity-related traits and RA, we found significant local genetic correlations at several regions on chromosome 6 (positions 28-29M, 30-35M, and 50-52M), highlighting a shared genetic basis. We further observed an increased risk of RA per SD increment (4.8 kg/m2 ) in genetically predicted BMI (OR 1.22 [95% CI 1.09-1.37]). The effect was consistent across sensitivity analyses and comparable between sexes (OR 1.22 [95% CI 1.04-1.44] in male subjects and 1.19 [95% CI 1.04-1.36] in female subjects). However, we did not find evidence supporting a causal role of either WHR (OR 0.98 [95% CI 0.84-1.14]) or WHRadjBMI (OR 0.90 [95% CI 0.79-1.04]) in RA.ConclusionGenetically predicted BMI significantly increases RA risk. Future studies are needed to understand the biologic mechanisms underlying this link.

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Data for Genetic Analysis Workshop (GAW) 15 Problem 2, genetic causes of rheumatoid arthritis and associated traits.

Publications

Data for Genetic Analysis Workshop (GAW) 15 Problem 2, genetic causes of rheumatoid arthritis and associated traits.

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