The metabochip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits
| Autor: | Kathy Stirrups, Inga Prokopenko, Jeanette Erdmann, Jun Ding, Serena Sanna, Patricia B. Munroe, Ramaiah Nagaraja, Antonella Mulas, Christian Fuchsberger, Cameron D. Palmer, Simon C. Potter, Ruth J. F. Loos, Nicole Soranzo, Tuomas O. Kilpeläinen, Michael Boehnke, Sekar Kathiresan, Francesco Cucca, David Altshuler, Hyun Min Kang, Melissa Parkin, Neil Robertson, Heribert Schunkert, Timothy M. Frayling, Gonçalo R. Abecasis, Arne Pfeufer, Toby Johnson, Joshua C. Randall, Mark I. McCarthy, Joel N. Hirschhorn, Nilesh J. Samani, Anne U. Jackson, Tanya M. Teslovich, Eleanor Wheeler, Benjamin F. Voight, Yun Li, Carlo Sidore, Panagiotis Deloukas, N P Burtt, Nigel W. Rayner, Richa Saxena, Peter S. Chines, Jared Maguire, Wendy Winckler, Cecilia M. Lindgren, Andrew P. Morris, Iris M. Heid, Christopher Newton-Cheh, Inês Barroso, Elizabeth K. Speliotes |
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| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Cancer Research
Genotyping Techniques Genome-wide association study 030204 cardiovascular system & hematology QH426-470 Cardiovascular 0302 clinical medicine Endocrinology Gene Frequency Genetics (clinical) Oligonucleotide Array Sequence Analysis 2. Zero hunger Genetics 0303 health sciences Anthropometry Statistics 3. Good health Phenotype Cardiovascular Diseases Medicine Research Article Genotype Quantitative Trait Loci Genomics Single-nucleotide polymorphism Quantitative trait locus Biology Polymorphism Single Nucleotide 03 medical and health sciences SNP Humans Metabolomics Molecular Biology Genotyping Ecology Evolution Behavior and Systematics Alleles 030304 developmental biology Genetic association Diabetic Endocrinology 0604 Genetics Genome Human Human Genetics Diabetes Mellitus Type 2 Diabetes Mellitus Type 2 Metabolic Disorders Mathematics Genome-Wide Association Study Developmental Biology |
| Zdroj: | PLoS Genet. 8:e1002793 (2012) PLoS Genetics, Vol 8, Iss 8, p e1002793 (2012) PLoS Genetics |
| Popis: | 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. Author Summary 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. |
| Databáze: | OpenAIRE |
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