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  • Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
    Mahajan, Anubha; Petty, Lauren E; Chiou, Joshua; Miguel-Escalada, Irene; Nakatochi, Masahiro; Huerta-Chagoya, Alicia; Bielak, Lawrence F; Hai, Yang; Kals, Mart; Grarup, Niels; Wuttke, Matthias; Nousome, Darryl; Long, Jirong; Ahmad, Meraj; Jensen, Richard A; An, Ping; Cade, Brian E; Abaitua, Fernando; Akiyama, Masato; Bertoni, Alain; Bian, Zheng; Brummett, Chad M; Chee, Miao-Li; Das, Swapan K; Du, Shufa; Duan, Qing; Eckardt, Kai-Uwe; Fischer, Krista; Floyd, James S; Genter, Pauline; González-Villalpando, Maria Elena; Gordon-Larsen, Penny; Gorkin, David; Herder, Christian; Hung, Yi-Jen; Hwu, Chii-Min; Ikram, Mohammad Arfan; Ingelsson, Martin; Islam, Md Tariqul; Isono, Masato; Kamatani, Yoichiro; Katsuya, Tomohiro; Khor, Chiea-Chuen; Kohara, Katsuhiko; Kriebel, Jennifer; Kuusisto, Johanna; Läll, Kristi; Leong, Aaron; Luan, Jian'an; Lv, Jun; Lyssenko, Valeriya; Meitinger, Thomas; Morris, Andrew D; Nadkarni, Girish N; Nayak, Uma; Ntalla, Ioanna; Peters, Annette; Preissl, Sebastian; Rasmussen-Torvik, Laura J; Roden, Michael; Sabanayagam, Charumathi; Schönherr, Sebastian; Shahriar, Mohammad; Shi, Jinxiu; Stančáková, Alena; Strauch, Konstantin; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Tsai, Fuu-Jen; Tusie-Luna, Teresa; Udler, Miriam S; Valladares-Salgado, Adan; Yajnik, Chittaranjan S; Yoon, Kyungheon; Igase, Michiya; Hanis, Craig L; Ingelsson, Erik; Zeggini, Eleftheria; Rich, Stephen S; Kooperberg, Charles; Engert, James C; Wilson, James G; Kardia, Sharon L R; Groop, Leif; Bharadwaj, Dwaipayan; Sale, Michèle M; Cruz, Miguel; Tai, E-Shyong; Kato, Norihiro; Laakso, Markku; Köttgen, Anna; Loos, Ruth J F; Saleheen, Danish; Hansen, Torben; Kadowaki, Takashi; Walters, Robin G; Stefansson, Kari; Meigs, James B; Gloyn, Anna L; Chambers, John C

    Nature genetics, 05/2022, Volume: 54, Issue: 5
    Journal Article

    We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10 ), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

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