Trans-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation Anubha Mahajan , Spracklen Cn , W Zhang , Ng Mh , Petty Le , Hidetoshi Kitajima , Yu Gz , Sina Rüeger , Leo Speidel , Yoon Jun Kim , Momoko Horikoshi , Mercader Jm , Daniel Taliun , Sanghoon Moon , Soo Heon Kwak , Robertson Nr , N. William Rayner , Marie Loh , Bonglee Kim , Joshua Chiou , Irene Miguel-Escalada , Briotta Parolo Pd , Keqin Lin , Fiona Bragg , Preuss Mh , Fumihiko Takeuchi , Jana Nano , Guo X , Amel Lamri , Masahiro Nakatochi , Scott Ra , Lee J , Alicia Huerta-Chagoya , Mariaelisa Graff , Jin-Fang Chai , Parra Ej , Jing Yao , Bielak Lf , Yasuharu Tabara , Yong Hai , Steinthorsdottir , Cook Jp , Mart Kals , Niels Grarup , Schmidt Em , Pan I , Tamar Sofer , Matthias Wuttke , Chloé Sarnowski , Christian Gieger , Darryl Nousome , Stella Trompet , Jirong Long , Min Sun , Tong Lin , W Chen , Meraj Ahmad , Raymond Noordam , Lim Vj , Tam Ch , Joo Yy , C Chen , Laura M. Raffield , Cécile Lecœur , Maruthur Nm , Prins Bp , Aude Nicolas , Yanek Lr , G Chen , Jensen Ra , Salman M. Tajuddin , Edmond K. Kabagambe , Peng An , Xiang Ah , HS Choi , Cade Be , Jia-Yi Tan , Fernando Abaitua , Adair Ls , Adebowale Adeyemo , Alford Ca , Masato Akiyama , SS Anand , Alain G. Bertoni , Bin Zheng , Jette Bork-Jensen , Ivan Brandslund , JA Brody , Brummett Cm , Buchanan Ta , Mickaël Canouil , Chan Jc , Li Chang , Miao-Li Chee , Junhong Chen , S Chen , Y Chen , Z Chen , Li Chung Chuang , Mary Cushman , Das Sk , de Silva Hj , George Dedoussis , Latchezar Dimitrov , Doumatey Ap , Shaowu Du , Qing Duan , Kai‐Uwe Eckardt , Emery Ls , Evans Ds , Michele K. Evans , Krista Fischer , Floyd Js , Ian Ford , Myriam Fornage , Franco Oh , Frayling Tm , Fangfang Bi , Christian Fuchsberger , Pauline Genter , Gerstein Hc , Giedraitis , Clicerio González‐Villalpando , González-Villalpando Me , MO Goodarzi , Penny Gordon‐Larsen , David U. Gorkin , Myron D. Gross , Yuanqiang Guo , Sophie Hackinger , Song Han , Andrew T. Hattersley , Christian Herder , Annie Green Howard , Willa A. Hsueh , Mengna Huang , Wei Huang , Yi‐Jen Hung , Hwang My , Hwu C , Sahoko Ichihara , Ikram Ma , Martin Ingelsson , Tofazzal Islam , Motohide Isono , Hak Chul Jang , Farzana Jasmine , Guozhi Jiang , Jb Jonas , Jørgensen Me , Torben Jørgensen , Y. Kamatani , Kandeel Fr , Anuradhani Kasturiratne , Tomohiro Katsuya , Varinder Kaur , Takahisa Kawaguchi , Keaton Jm , Kho An , Chiea Chuen Khor , Kibriya Mg , Kim D , Katsuhiko Kohara , Jennifer Kriebel , Florian Kronenberg , Johanna Kuusisto , Kristi Läll , Lange La , Lee M , Lee Nr , Aaron Leong , Li L , Li Y , Ruifang Li‐Gao , Symen Ligthart , Lindgren Cm , Allan Linneberg , Liu C , Jing Liu , Locke Ae , Tin Louie , Jian’an Luan , Luk Ao , Luo X , Jian Lv , Lyssenko , Mamakou , Mani Kr , Thomas Meitinger , Andres Metspalu , AD Morris , Nadkarni Gn , Nadler Jl , Ning Ma , Uma Nayak , Ιωάννα Ντάλλα , Yukinori Okada , Lorena Orozco , M. S. Patel , Pereira Ma , Annette Peters , FJ Pirie , Bianca Porneala , Gauri Prasad , Sebastian Preißl , Rasmussen-Torvik Lj , Reiner Ap , Michael Roden , Rebecca Rohde , Kathryn Roll , Charumathi Sabanayagam , Maike Sander , Kevin Sandow , Naveed Sattar , Sebastian Schönherr , Claudia Schurmann , Mohammad Hasan Shahriar , Jing Shi , Shin Dm , Daniel Shriner , Smith Ja , So Wy , Alena Stančáková , Stilp Am , Konstantin Strauch , Ken Suzuki , Atsushi Takahashi , Kelly Taylor , Barbara Thorand , Guðmar Þorleifsson , Unnur Þorsteinsdóttir , Brian Tomlinson , Torres Jm , Fuu Jen Tsai , J. Tuomilehto , Teresa Tusié-Luna , Udler Ms , Adán Valladares‐Salgado , van Dam Rm , van Klinken Jb , Rohit Varma , Marijana Vujkovic , Niels Wacher-Rodarte , Eleanor Wheeler , Whitsel Ea , Anand Bhatt medRxiv (Cold Spring Harbor Laboratory)（2020）
摘要
ABSTRACT We assembled an ancestrally diverse collection of genome-wide association studies of type 2 diabetes (T2D) in 180,834 cases and 1,159,055 controls (48.9% non-European descent). We identified 277 loci at genome-wide significance ( p <5×10 -8 ), including 237 attaining a more stringent trans-ancestry threshold ( p <5×10 -9 ), which were delineated to 338 distinct association signals. Trans-ancestry meta-regression offered substantial enhancements to fine-mapping, with 58.6% of associations more precisely localised due to population diversity, and 54.4% of signals resolved 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 foundations for functional investigations. Trans-ancestry genetic risk scores enhanced transferability across diverse populations, providing a step towards more effective clinical translation to improve global health.
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diabetes, genetic study, diverse populations, trans-ancestry
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