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The Metabochip, a Custom Genotyping Array for Genetic Studies of Metabolic, Cardiovascular, and Anthropometric Traits

by: Benjamin F. Voight, Hyun M. Kang, Jun Ding, Cameron D. Palmer, Carlo Sidore, Peter S. Chines, Noël P. Burtt, Christian Fuchsberger, Yanming Li, Jeanette Erdmann, Timothy M. Frayling, Iris M. Heid, Anne U. Jackson, Toby Johnson, Tuomas O. Kilpeläinen, Cecilia M. Lindgren, Andrew P. Morris, Inga Prokopenko, Joshua C. Randall, Richa Saxena, Nicole Soranzo, Elizabeth K. Speliotes, Tanya M. Teslovich, Eleanor Wheeler, Jared Maguire, Melissa Parkin, Simon Potter, N. William Rayner, Neil Robertson, Kathleen Stirrups, Wendy Winckler, Serena Sanna, Antonella Mulas, Ramaiah Nagaraja, Francesco Cucca, Inês Barroso, Panos Deloukas, Ruth J. F. Loos, Sekar Kathiresan, Patricia B. Munroe, Christopher Newton-Cheh, Arne Pfeufer, Nilesh J. Samani, Heribert Schunkert, Joel N. Hirschhorn, David Altshuler, Mark I. McCarthy, Gonçalo R. Abecasis, Michael Boehnke
PLoS Genet, Vol. 8, No. 8. (2 August 2012), e1002793, doi:10.1371/journal.pgen.1002793  Key: citeulike:11061292

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Abstract

Genome-wide association studies have identified hundreds of loci for type 2 diabetes, coronary artery disease and myocardial infarction, as well as for related traits such as body mass index, glucose and insulin levels, lipid levels, and blood pressure. These studies also have pointed to thousands of loci with promising but not yet compelling association evidence. To establish association at additional loci and to characterize the genome-wide significant loci by fine-mapping, we designed the “Metabochip,” a custom genotyping array that assays nearly 200,000 SNP markers. Here, we describe the Metabochip and its component SNP sets, evaluate its performance in capturing variation across the allele-frequency spectrum, describe solutions to methodological challenges commonly encountered in its analysis, and evaluate its performance as a platform for genotype imputation. The metabochip achieves dramatic cost efficiencies compared to designing single-trait follow-up reagents, and provides the opportunity to compare results across a range of related traits. The metabochip and similar custom genotyping arrays offer a powerful and cost-effective approach to follow-up large-scale genotyping and sequencing studies and advance our understanding of the genetic basis of complex human diseases and traits. Recent genetic studies have identified hundreds of regions of the human genome that contribute to risk for type 2 diabetes, coronary artery disease and myocardial infarction, and to related quantitative traits such as body mass index, glucose and insulin levels, blood lipid levels, and blood pressure. These results motivate two central questions: (1) can further genetic investigation identify additional associated regions?; and (2) can more detailed genetic investigation help us identify the causal variants (or variants more strongly correlated with the causal variants) in the regions identified so far? Addressing these questions requires assaying many genetic variants in DNA samples from thousands of individuals, which is expensive and timeconsuming when done a few SNPs at a time. To facilitate these investigations, we designed the “Metabochip,” a custom genotyping array that assays variation in nearly 200,000 sites in the human genome. Here we describe the Metabochip, evaluate its performance in assaying human genetic variation, and describe solutions to methodological challenges commonly encountered in its analysis.


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