1. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
- 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, and Cushman, Mary
- Subjects
Genetics ,Diabetes ,Human Genome ,Metabolic and endocrine ,Diabetes Mellitus ,Type 2 ,Ethnicity ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Humans ,Polymorphism ,Single Nucleotide ,Risk Factors ,FinnGen ,eMERGE Consortium ,Biological Sciences ,Medical and Health Sciences ,Developmental Biology - 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.
- Published
- 2022