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Design and analysis of genome-wide association studies

Despite many years of effort, linkage and candidate gene association studies have yielded disappointingly few risk loci for common human diseases such as diabetes, auto-immune disorders and cancers. Large sample sizes, increased understanding of the patterns of correlation in genetic variation, and plunging genotyping costs have enabled genome-wide association studies, which have good power to detect common risk alleles of modest effect. I present an evaluation of SNP choice in study design and show that overall, despite substantial differences in genotyping technologies, marker selection strategies and number of markers assayed, the first generation platforms all offer good levels of genome coverage (∼ 70%). I next describe the largest such project undertaken to date, the Wellcome Trust Case Control Consortium, which consisted of 2000 cases from each of seven common diseases and 3000 shared controls. It identified nearly two dozen new associations. I demonstrate the importance of careful data quality control, including both standard and unorthodox analyses. I next focus on the association results therein for Crohn’s disease. I present a replication experiment in over 1000 additional Crohn’s patients which unambiguously confirmed six previously published loci and four new loci. Next I describe, in a general context, several issues impeding the combination of genome-wide scans, including data annotation, population structure and differences in genotyping platform. Each of these problems is shown to be tractable with available methods, provided that these methods are applied prudently. I present the results of a meta-analysis of three genome-wide scans for Crohn’s disease. The data showed a striking excess of significant associations, and a replication experiment involving over 4000 independent Crohn’s patients verified twenty new risk loci. Finally, I discuss the early success of genome-wide association and its consequences for further understanding the biology of human disease.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:489410
Date January 2008
CreatorsBarrett, Jeffrey C.
ContributorsDonnelly, Peter J. : Cardon, Lon R.
PublisherUniversity of Oxford
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://ora.ox.ac.uk/objects/uuid:45790b5c-e50c-406a-bb3c-a96868b11a28

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