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L.; Baldassarre, Damiano; Beekman, Marian; Bergman, Richard N.; Bertoni, Alain; Blüher, Matthias; Bonnycastle, Lori L.; Bornstein, Stefan R.; Bowden, Donald W.; Cai, Qiuyin; Campbell, Archie; Campbell, Harry; Chang, Yi Cheng; de Geus, Eco J. C.; Dehghan, Abbas; Du, Shufa; Eiriksdottir, Gudny; Farmaki, Aliki Eleni; Frånberg, Mattias; Fuchsberger, Christian; Gao, Yutang; Gjesing, Anette P.; Goel, Anuj; Han, Sohee; Hartman, Catharina A.; Herder, Christian; Hicks, Andrew A.; Hsieh, Chang-Hsun; Hsueh, Willa A.; Ichihara, Sahoko; Igase, Michiya; Ikram, M. Arfan; Johnson, W. Craig; Jørgensen, Marit E.; Joshi, Peter K.; Kalyani, Rita R.; Kandeel, Fouad R.; Katsuya, Tomohiro; Khor, Chiea Chuen; Kiess, Wieland; Kolcic, Ivana; Kuulasmaa, Teemu; Kuusisto, Johanna; Läll, Kristi; Lam, Kelvin; Lawlor, Deborah A.; Lee, Nanette R.; Lemaitre, Rozenn N.; Li, Honglan; Lin, Shih-Yi; Lindström, Jaana; Linneberg, Allan; Liu, Jianjun; Lorenzo, Carlos; Matsubara, Tatsuaki; Matsuda, Fumihiko; Mingrone, Geltrude; Mooijaart, Simon; Moon, Sanghoon; Nabika, Toru; Nadkarni, Girish N.; Nadler, Jerry L.; Nelis, Mari; Neville, Matt J.; Norris, Jill M.; Ohyagi, Yasumasa; Peters, Annette ORCID: https://orcid.org/0000-0001-6645-0985; Peyser, Patricia A.; Polasek, Ozren; Qi, Qibin; Raven, Dennis; Reilly, Dermot F.; Reiner, Alex; Rivideneira, Fernando; Roll, Kathryn; Rudan, Igor; Sabanayagam, Charumathi; Sandow, Kevin; Sattar, Naveed; Schürmann, Annette; Shi, Jinxiu; Stringham, Heather M.; Taylor, Kent D.; Teslovich, Tanya M.; Thuesen, Betina; Timmers, Paul R. H. 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(2021):
The trans-ancestral genomic architecture of glycemic traits.
In: Nature Genetics, Bd. 53, Nr. 6: S. 840-860
Volltext auf 'Open Access LMU' nicht verfügbar.
Abstract
Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10−8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
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