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J.; Varga, Tibor V.; Green, Todd; Beer, Nicola L.; Day-Williams, Aaron G.; Ferreira, Teresa; Fingerlin, Tasha; Horikoshi, Momoko; Hu, Cheng; Huh, Iksoo; Ikram, Mohammad Kamran; Kim, Bong-Jo; Kim, Yongkang; Kim, Young Jin; Kwon, Min-Seok; Lee, Juyoung; Lee, Selyeong; Lin, Keng-Han; Maxwell, Taylor J.; Nagai, Yoshihiko; Wang, Xu; Welch, Ryan P.; Yoon, Joon; Zhang, Weihua; Barzilai, Nir; Voight, Benjamin F.; Han, Bok-Ghee; Jenkinson, Christopher P.; Kuulasmaa, Teemu; Kuusisto, Johanna; Manning, Alisa; Ng, Maggie C. Y.; Palmer, Nicholette D.; Balkau, Beverley; Stancakova, Alena; Abboud, Hanna E.; Boeing, Heiner; Giedraitis, Vilmantas; Prabhakaran, Dorairaj; Gottesman, Omri; Scott, James; Carey, Jason; Kwan, Phoenix; Grant, George; Smith, Joshua D.; Neale, Benjamin M.; Purcell, Shaun; Butterworth, Adam S.; Howson, Joanna M. M.; Lee, Heung Man; Lu, Yingchang; Kwak, Soo-Heon; Zhao, Wei; Danesh, John; Lam, Vincent K. L.; Park, Kyong Soo; Saleheen, Danish; So, Wing Yee; Tam, Claudia H. 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(2016):
The genetic architecture of type 2 diabetes.
In: Nature, Bd. 536, Nr. 7614: S. 41-47
Volltext auf 'Open Access LMU' nicht verfügbar.
Abstract
The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.
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