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Data for Genetic Analysis Workshop (GAW) 15 Problem 2, Genetic Causes of Rheumatoid Arthritis and Associated Traits

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2007

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BioMed Central
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Amos, Christopher I., Wei Vivien Chen, Elaine Remmers, Katherine A. Siminovitch, Michael F. Seldin, Lindsey A. Criswell, Annette T. Lee, et al. 2007. Data for genetic analysis workshop (GAW) 15 problem 2, genetic causes of rheumatoid arthritis and associated traits. BMC Proceedings 1(Suppl 1): S3.

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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.

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