Details

Autor(en) / Beteiligte

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

Titel

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

Ist Teil von

• Nature genetics, 2013-02, Vol.45 (2), p.197-201

Ort / Verlag

United States: Nature Publishing Group

Erscheinungsjahr

2013

Quelle

MEDLINE

Beschreibungen/Notizen

• 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 secretion; 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.