학술논문
Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
Document Type
article
Author
Mahajan, Anubha; Spracklen, Cassandra N; Zhang, Weihua; Ng, Maggie CY; Petty, Lauren E; Kitajima, Hidetoshi; Yu, Grace Z; Rüeger, Sina; Speidel, Leo; Kim, Young Jin; Horikoshi, Momoko; Mercader, Josep M; Taliun, Daniel; Moon, Sanghoon; Kwak, Soo-Heon; Robertson, Neil R; Rayner, Nigel W; Loh, Marie; Kim, Bong-Jo; Chiou, Joshua; Miguel-Escalada, Irene; della Briotta Parolo, Pietro; Lin, Kuang; Bragg, Fiona; Preuss, Michael H; Takeuchi, Fumihiko; Nano, Jana; Guo, Xiuqing; Lamri, Amel; Nakatochi, Masahiro; Scott, Robert A; Lee, Jung-Jin; Huerta-Chagoya, Alicia; Graff, Mariaelisa; Chai, Jin-Fang; Parra, Esteban J; Yao, Jie; Bielak, Lawrence F; Tabara, Yasuharu; Hai, Yang; Steinthorsdottir, Valgerdur; Cook, James P; Kals, Mart; Grarup, Niels; Schmidt, Ellen M; Pan, Ian; Sofer, Tamar; Wuttke, Matthias; Sarnowski, Chloe; Gieger, Christian; Nousome, Darryl; Trompet, Stella; Long, Jirong; Sun, Meng; Tong, Lin; Chen, Wei-Min; Ahmad, Meraj; Noordam, Raymond; Lim, Victor JY; Tam, Claudia HT; Joo, Yoonjung Yoonie; Chen, Chien-Hsiun; Raffield, Laura M; Lecoeur, Cécile; Prins, Bram Peter; Nicolas, Aude; Yanek, Lisa R; Chen, Guanjie; Jensen, Richard A; Tajuddin, Salman; Kabagambe, Edmond K; An, Ping; Xiang, Anny H; Choi, Hyeok Sun; Cade, Brian E; Tan, Jingyi; Flanagan, Jack; Abaitua, Fernando; Adair, Linda S; Adeyemo, Adebowale; Aguilar-Salinas, Carlos A; Akiyama, Masato; Anand, Sonia S; Bertoni, Alain; Bian, Zheng; Bork-Jensen, Jette; Brandslund, Ivan; Brody, Jennifer A; Brummett, Chad M; Buchanan, Thomas A; Canouil, Mickaël; Chan, Juliana CN; Chang, Li-Ching; Chee, Miao-Li; Chen, Ji; Chen, Shyh-Huei; Chen, Yuan-Tsong; Chen, Zhengming; Chuang, Lee-Ming; Cushman, Mary
Source
Nature Genetics. 54(5)
Subject
Language
Abstract
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 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.