NYMC Faculty Publications

Multi-Ancestry Genetic Study of Type 2 Diabetes Highlights the Power of Diverse Populations for Discovery and Translation

Anubha Mahajan, Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK. mahajan.anubha@gene.com.
Cassandra N. Spracklen, Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Weihua Zhang, Department of Epidemiology and Biostatistics, Imperial College London, London, UK.
Maggie C. Ng, Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
Lauren E. Petty, Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
Hidetoshi Kitajima, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Grace Z. Yu, Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
Sina Rüeger, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
Leo Speidel, Genetics Institute, University College London, London, UK.
Young Jin Kim, Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Republic of Korea.
Momoko Horikoshi, Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
Josep M. Mercader, Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
Daniel Taliun, Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.
Sanghoon Moon, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Soo-Heon Kwak, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Neil R. Robertson, Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
Nigel W. Rayner, Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
Marie Loh, Department of Epidemiology and Biostatistics, Imperial College London, London, UK.
Bong-Jo Kim, Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Republic of Korea.
Joshua Chiou, Biomedical Sciences Graduate Studies Program, University of California San Diego, La Jolla, CA, USA.
Irene Miguel-Escalada, Regulatory Genomics and Diabetes, Centre for Genomic Regulation, the Barcelona Institute of Science and Technology, Barcelona, Spain.
Pietro Della Briotta Parolo, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
Kuang Lin, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Fiona Bragg, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Michael H. Preuss, The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Fumihiko Takeuchi, Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan.
Jana Nano, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.
Xiuqing Guo, The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, the Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA.
Amel Lamri, Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
Masahiro Nakatochi, Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Robert A. Scott, MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
Jung-Jin Lee

Author Type(s)

Faculty

DOI

10.1038/s41588-022-01058-3

Journal Title

Nature Genetics

First Page

560

Last Page

572

Document Type

Article

Publication Date

5-1-2022

Department

Medicine

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), 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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