The goal of this study is to identify the genetic determinants of rheumatoid arthritis (RA). The proposed study uses Perlegen Sciences' high density oligonucleotide array-based genotyping platform to genotype over 1.5 million single nucleotide polymorphisms (SNPs) distributed across the genome with an average spacing of 2-kb in the context of a whole-genome association study of RA. RA is a genetically complex disorder. A group of susceptibility alleles are located within the major histocompatibility complex on chromosome 6. A large collaborative effort by the North American Rheumatoid Arthritis Consortium (NARAC) has provided evidence that numerous other genetic susceptibility genes are present in the genome. The NARAC has assembled a unique resource of multiplex RA families containing nearly 1,000 affected sibling pairs. Using Perlegen Sciences' high density array technology, SNPs associated with rheumatoid arthritis will be identified by measuring SNP allele frequency differences between 400 probands with RA in the NARAC sib pair families, and 400 matched unaffected controls. In Phase I, the case and control groups will be examined for genetic stratification, and allele frequency differences between the two groups for 210,000 SNPs will be estimated by quantitative pooled genotyping. In Phase II, the whole genome scan will be completed by estimating allele frequency differences for the remaining ~ 1.29 million SNPs by pooled genotyping. Differences in SNP allele frequencies between RA cases and controls inferred by pooled genotyping will be verified by genotyping of the individual RA case and control samples, as well as replicate populations. SNPs will be selected for individual genotyping based on the largest estimated allele frequency differences, haplotype structure and biological relevance. The number of SNPs to be analyzed in this study is orders of magnitude higher than in previously published case-control studies, rendering this the most comprehensive search for genetic loci involved in RA. In addition to providing further evidence regarding the role of previously identified candidate loci, the study may also identify novel associations with unsuspected loci. Identification of new genetic factors associated with IRA will lead to a better understanding of the molecular mechanisms underlying the disease and provide a basis for new approaches to treatment and prevention. ? ?
