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

Christopher I Amos,Neil D Shephard,Katherine A Siminovitch,Elaine Remmers,Robert M Plenge,Jane Worthington,Annette T Lee,Daniel L Kastner,Francois Cornelis,Wei Vivien Chen,Sally John,Thomas D Dyer,Ann B Begovich,Peter K Gregersen,Michael F Seldin,Lindsey A Criswell

doi:10.1186/1753-6561-1-s1-s3

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.

Highlights

Rheumatoid arthritis (RA) is a complex disease with a moderately strong genetic component
Previous research has identified a few loci that consistently show association with rheumatoid arthritis, a great deal remains unknown about the mechanisms by which genetic factors interrelate to increase disease risk, and the impact that environmental factors such as smoking behavior have upon disease risk
The collaborative approach that has been adopted by rheumatoid arthritis researchers provided an excellent platform for integrating data from multiple sites in an effort to obtain a larger and more powerful collection of data resources than was possible from a single site

Summary

Introduction

Rheumatoid arthritis (RA) is a complex disease with a moderately strong genetic component. The recurrence risk ratio for siblings is typically estimated at around six in Caucasians, but with a broad range of values, primarily because the prevalence in the population is not well characterized [1]. The prevalence varies among populations, ranging from around 0.8% in Caucasians to 10% in some Native American groups, it is not clear that this is always the same phenotype. RA appears to be rare in rural African populations. Females are at higher risk than males, with about a three to one preponderance of females to males. The mean age of disease onset is in the fifth decade, with considerable variability in age at presentation, including occasional presentation in the teenage years

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Discussion

Conclusion