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Exome array analysis identifies new loci and low-frequency variants influencing insulin processing and secretion

2012; Nature Portfolio; Volume: 45; Issue: 2 Linguagem: Inglês

10.1038/ng.2507

1546-1718

Jeroen R. Huyghe, Anne Jackson, Marie P. Fogarty, Martin L. Buchkovich, Alena Stančáková, Heather M. Stringham, Xueling Sim, Lingyao Yang, Christian Fuchsberger, Henna Cederberg, Peter S. Chines, Tanya M. Teslovich, Jane Romm, Hua Ling, Ivy McMullen, Roxann Ingersoll, Elizabeth Pugh, Kimberly F. Doheny, Benjamin M. Neale, Mark J. Daly, Johanna Kuusisto, Laura J. Scott, Hyun Min Kang, Francis S. Collins, Gonçalo R. Abecasis, Richard M. Watanabe, Michael Boehnke, Markku Laakso, Karen L. Mohlke,

Genetic Mapping and Diversity in Plants and Animals

Karen Mohlke, Markku Laakso, Michael Boehnke and colleagues report the first application of the Illumina HumanExome Beadchip array, examining association with insulin and glycemic traits in 8,229 nondiabetic Finnish males from the population-based Metabolic Syndrome in Men (METSIM) study. They identify low-frequency coding variants at both known and newly associated loci with insulin processing and secretion. Insulin secretion has a crucial role in glucose homeostasis, and failure to secrete sufficient insulin is a hallmark of type 2 diabetes. Genome-wide association studies (GWAS) have identified loci contributing to insulin processing and secretion1,2; however, a substantial fraction of the genetic contribution remains undefined. To examine low-frequency (minor allele frequency (MAF) 0.5–5%) and rare (MAF < 0.5%) nonsynonymous variants, we analyzed exome array data in 8,229 nondiabetic Finnish males using the Illumina HumanExome Beadchip. We identified low-frequency coding variants associated with fasting proinsulin concentrations at the SGSM2 and MADD GWAS loci and three new genes with low-frequency variants associated with fasting proinsulin or insulinogenic index: TBC1D30, KANK1 and PAM. We also show that the interpretation of single-variant and gene-based tests needs to consider the effects of noncoding SNPs both nearby and megabases away. This study demonstrates that exome array genotyping is a valuable approach to identify low-frequency variants that contribute to complex traits.