Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

, eMERGE Consortium, Anubha Mahajan (Lead / Corresponding author), Cassandra N Spracklen, Weihua Zhang, Maggie C Y Ng, Lauren E Petty, Hidetoshi Kitajima, Grace Z Yu, Sina Rüeger, Leo Speidel, Young Jin Kim, Momoko Horikoshi, Josep M Mercader, Daniel Taliun, Sanghoon Moon, Soo-Heon Kwak, Neil R Robertson, Nigel W Rayner, Marie LohBong-Jo Kim, Joshua Chiou, Irene Miguel-Escalada, Pietro Della Briotta Parolo, Kuang Lin, Fiona Bragg, Michael H Preuss, Fumihiko Takeuchi, Jana Nano, Xiuqing Guo, Amel Lamri, Masahiro Nakatochi, Robert A. Scott, Jung-Jin Lee, Alicia Huerta-Chagoya, Mariaelisa Graff, Jin-Fang Chai, Esteban J Parra, Jie Yao, Lawrence F Bielak, Yasuharu Tabara, Yang Hai, Valgerdur Steinthorsdottir, James P Cook, Mart Kals, Niels Grarup, Jack Flanagan, Ji Chen, Andrew D. Morris, Jennifer A. Smith, Colin N. A. Palmer, Mark I. McCarthy (Lead / Corresponding author), Andrew P. Morris

Research output: Contribution to journalArticlepeer-review

188 Citations (Scopus)

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 < 5 × 10 −9), 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.

Original languageEnglish
Pages (from-to)560-572
Number of pages13
JournalNature Genetics
Volume54
Issue number5
DOIs
Publication statusPublished - 1 May 2022

Keywords

  • Diabetes Mellitus, Type 2/epidemiology
  • Ethnicity
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study
  • Humans
  • Polymorphism, Single Nucleotide/genetics
  • Risk Factors

ASJC Scopus subject areas

  • Genetics

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