Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
Anubha Mahajan
1, 2, 3
,
Cassandra N Spracklen
4, 5
,
Weihua Zhang
6, 7
,
Maggie C.Y. Ng
8, 9, 10
,
Lauren E. Petty
8
,
Hidetoshi Kitajima
2, 11, 12, 13
,
Grace Z. Yu
1, 2
,
Leo Speidel
14, 15
,
Young Jin Kim
16
,
Momoko Horikoshi
17
,
Josep Mercader
18, 19, 20
,
Daniel Taliun
21
,
Sanghoon Moon
2, 16
,
Soo Heon Kwak
2, 22
,
Neil R. Robertson
1, 2
,
Nigel W Rayner
1, 2, 23, 24
,
Marie Loh
6, 25, 26
,
Bong-Jo Kim
16
,
Joshua Chiou
27, 28
,
Irene Miguel-Escalada
29, 30
,
Kuang Lin
31
,
Fiona Bragg
31, 32
,
Michael H Preuss
33
,
Fumihiko Takeuchi
34
,
Jana Nano
35
,
Xiuqing Guo
36
,
Amel Lamri
37, 38
,
Masahiro Nakatochi
39
,
Robert A Scott
40
,
Jung-Jin Lee
41
,
Alicia Huerta Chagoya
42, 43
,
Mariaelisa Graff
44
,
Jin Fang Chai
45
,
Esteban J. Parra
46
,
JIE YAO
36
,
Lawrence F. Bielak
47
,
Yasuharu Tabara
48
,
Yang Hai
36
,
Valgerdur Steinthorsdottir
49
,
James P. Cook
50
,
Mart Kals
51
,
Niels Grarup
52
,
Ellen M. Schmidt
21
,
Ian Pan
53
,
Tamar Sofer
54, 55, 56
,
Matthias Wuttke
57
,
Chloé Sarnowski
58, 59
,
Christian Gieger
60, 61, 62
,
Darryl Nousome
63
,
Stella Trompet
64, 65
,
Jirong Long
66
,
Meng Sun
2
,
Tong Lin
67
,
Wei-Min Chen
68
,
Meraj Ahmad
69
,
Raymond Noordam
65
,
Victor J Y Lim
45
,
Claudia H.T. Tam
70, 71
,
Chien-Hsiun Chen
72
,
Laura M Raffield
4
,
Cécile Lecoeur
73, 74
,
Bram Peter Prins
23
,
Aude Nicolas
75
,
Lisa R Yanek
76
,
GUANJIE CHEN
77
,
RICHARD A. JENSEN
78
,
Salman Tajuddin
79
,
Edmond K Kabagambe
66, 80
,
Ping An
81
,
Anny H. Xiang
82
,
Hyeok Sun Choi
83
,
Brian E. Cade
20, 55
,
Jingyi Tan
36
,
Jack Flanagan
17, 50
,
Fernando Abaitua
2, 84
,
Linda S Adair
85
,
Adebowale Adeyemo
2, 77
,
Carlos A. Aguilar-Salinas
86
,
Masato Akiyama
87, 88
,
Sonia S. Anand
37, 38, 89
,
Alain Bertoni
90
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Zheng Bian
91
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Jette Bork-Jensen
52
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Ivan Brandslund
92, 93
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Jennifer A. Brody
78
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Chad M. Brummett
94
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Thomas A. Buchanan
95
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Mickaël Canouil
73, 74
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Juliana C.N. Chan
70, 71, 96, 97
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Li-Ching Chang
72
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Miao Li Chee
98
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Ji Chen
99, 100
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Shyh-Huei Chen
101
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Yuan-Tsong Chen
72
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Zhengming Chen
31, 32
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LEE-MING CHUANG
102, 103
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Mary Cushman
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Swapan K. Das
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4
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Symen Ligthart
35
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Cecilia M Lindgren
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Allan Linneberg
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58
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Andrea O Luk
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164
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176
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K. Radha Mani
69
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Thomas Meitinger
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Uma Nayak
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191
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Mark A Pereira
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Annette Peters
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Fraser J Pirie
193
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Bianca Porneala
163
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Gauri Prasad
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Sebastian Preissl
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Laura J. Rasmussen-Torvik
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Alexander P Reiner
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Michael Roden
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Charumathi Sabanayagam
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Toshimasa Yamauchi
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Kyungheon Yoon
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Canqing Yu
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JIAN-MIN YUAN
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Wei Zheng
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Sina Rüeger
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Pietro Della Briotta Parolo
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C Rotimi
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Mitsuhiro YOKOTA
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3
Genentech, South San Francisco, USA
|
7
Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, London, UK
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16
Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Republic of Korea
|
26
27
28
Internal Medicine Research Unit, Pfizer Worldwide Research, Cambridge, USA
|
29
38
41
49
deCODE genetics, Amgen Inc., Reykjavik, Iceland
|
52
60
German Center for Diabetes Research (DZD), Neuherberg, Germany
|
71
73
78
80
Division of Academics, Ochsner Health, New Orleans, USA
|
82
Department of Research and Evaluation, Division of Biostatistics Research, Kaiser Permanente of Southern California, Pasadena, USA
|
84
Vertex Pharmaceuticals Ltd, Oxford, UK
|
89
96
97
98
101
114
115
117
Institute for Biomedicine, EURAC Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
|
125
130
Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai (CHGC) and Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), Shanghai, China
|
131
Division of Endocrine and Metabolism, Tri-Service General Hospital Songshan Branch, Taipei, Taiwan
|
136
University of Chicago Research Bangladesh, Dhaka, Bangladesh
|
137
Institute of Molecular and Clinical Ophthalmology Basel, Basel, Switzerland
|
139
140
Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg hospital, Frederiksberg, Denmark
|
146
151
152
154
Ibusuki Kozenkai Hospital, Ibusuki, Japan
|
156
158
160
161
USC—Office of Population Studies Foundation, Inc., University of San Carlos, Cebu City, Philippines
|
165
172
Regeneron Genetics Center, Tarrytown, USA
|
175
176
181
184
Data Tecnica International LLC, Glen Echo, USA
|
185
Center for Alzheimer’s and Related Dementias, National Institutes of Health, Baltimore, USA
|
187
189
194
Academy of Scientific and Innovative Research, CSIR—Human Resource Development Centre Campus, Ghaziabad, India
|
196
202
212
Faculty of Medicine, University of Reykjavik, Reykjavik, Iceland
|
215
Department of Medical Genetics and Medical Research, China Medical University Hospital, Taichung, Taiwan
|
217
National School of Public Health, Madrid, Spain
|
226
Southern California Eye Institute, CHA Hollywood Presbyterian Medical Center, Los Angeles, USA
|
227
232
Danish Diabetes Academy, Odense, Denmark
|
233
Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, India
|
248
249
251
255
256
Division of Endocrinology and Metabolism, Department of Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
|
258
260
261
263
268
270
276
Center for Non-Communicable Diseases, Karachi, Pakistan
|
277
Publication type: Journal Article
Publication date: 2022-05-12
scimago Q1
wos Q1
SJR: 16.586
CiteScore: 45.1
Impact factor: 29.0
ISSN: 10614036, 15461718
PubMed ID:
35551307
Genetics
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. Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations.
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Mahajan A. et al. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation // Nature Genetics. 2022. Vol. 54. No. 5. pp. 560-572.
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Mahajan A. et al. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation // Nature Genetics. 2022. Vol. 54. No. 5. pp. 560-572.
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@article{2022_Mahajan,
author = {Anubha Mahajan and Cassandra N Spracklen and Weihua Zhang and Maggie C.Y. Ng and Lauren E. Petty and Hidetoshi Kitajima and Grace Z. Yu and Leo Speidel and Young Jin Kim and Momoko Horikoshi and Josep Mercader and Daniel Taliun and Sanghoon Moon and Soo Heon Kwak and Neil R. Robertson and Nigel W Rayner and Marie Loh and Bong-Jo Kim and Joshua Chiou and Irene Miguel-Escalada and Kuang Lin and Fiona Bragg and Michael H Preuss and Fumihiko Takeuchi and Jana Nano and Xiuqing Guo and Amel Lamri and Masahiro Nakatochi and Robert A Scott and Jung-Jin Lee and Alicia Huerta Chagoya and Mariaelisa Graff and Jin Fang Chai and Esteban J. Parra and JIE YAO and Lawrence F. Bielak and Yasuharu Tabara and Yang Hai and Valgerdur Steinthorsdottir and James P. Cook and Mart Kals and Niels Grarup and Ellen M. Schmidt and Ian Pan and Tamar Sofer and Matthias Wuttke and Chloé Sarnowski and Christian Gieger and Darryl Nousome and Stella Trompet and others},
title = {Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation},
journal = {Nature Genetics},
year = {2022},
volume = {54},
publisher = {Springer Nature},
month = {may},
url = {https://doi.org/10.1038/s41588-022-01058-3},
number = {5},
pages = {560--572},
doi = {10.1038/s41588-022-01058-3}
}
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Mahajan, Anubha, et al. “Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.” Nature Genetics, vol. 54, no. 5, May. 2022, pp. 560-572. https://doi.org/10.1038/s41588-022-01058-3.