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

Research output: Contribution to journalJournal articlepeer-review

  • Anubha Mahajan
  • 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 Loh
  • Bong-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
  • Grarup, Niels
  • Wei-Min Chen
  • Jette Bork-Jensen
  • Md Tariqul Islam
  • Marit E Jørgensen
  • Torben Jørgensen
  • Linneberg, Allan René
  • Daniel R Witte
  • Lars Lind
  • Loos, Ruth
  • Hansen, Torben
  • Pedersen, Oluf Borbye
  • FinnGen

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
JournalNature Genetics
Issue number5
Pages (from-to)560-572
Number of pages13
Publication statusPublished - 2022

Bibliographical note

© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.

    Research areas

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

ID: 308116769