Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.
Mahajan A., Spracklen CN., Zhang W., Ng MCY., Petty LE., Kitajima H., Yu GZ., Rüeger S., Speidel L., Kim YJ., Horikoshi M., Mercader JM., Taliun D., Moon S., Kwak S-H., Robertson NR., Rayner NW., Loh M., Kim B-J., Chiou J., Miguel-Escalada I., Della Briotta Parolo P., Lin K., Bragg F., Preuss MH., Takeuchi F., Nano J., Guo X., Lamri A., Nakatochi M., Scott RA., Lee J-J., Huerta-Chagoya A., Graff M., Chai J-F., Parra EJ., Yao J., Bielak LF., Tabara Y., Hai Y., Steinthorsdottir V., Cook JP., Kals M., Grarup N., Schmidt EM., Pan I., Sofer T., Wuttke M., Sarnowski C., Gieger C., Nousome D., Trompet S., Long J., Sun M., Tong L., Chen W-M., Ahmad M., Noordam R., Lim VJY., Tam CHT., Joo YY., Chen C-H., Raffield LM., Lecoeur C., Prins BP., Nicolas A., Yanek LR., Chen G., Jensen RA., Tajuddin S., Kabagambe EK., An P., Xiang AH., Choi HS., Cade BE., Tan J., Flanagan J., Abaitua F., Adair LS., Adeyemo A., Aguilar-Salinas CA., Akiyama M., Anand SS., Bertoni A., Bian Z., Bork-Jensen J., Brandslund I., Brody JA., Brummett CM., Buchanan TA., Canouil M., Chan JCN., Chang L-C., Chee M-L., Chen J., Chen S-H., Chen Y-T., Chen Z., Chuang L-M., Cushman M., Das SK., de Silva HJ., Dedoussis G., Dimitrov L., Doumatey AP., Du S., Duan Q., Eckardt K-U., Emery LS., Evans DS., Evans MK., Fischer K., Floyd JS., Ford I., Fornage M., Franco OH., Frayling TM., Freedman BI., Fuchsberger C., Genter P., Gerstein HC., Giedraitis V., González-Villalpando C., González-Villalpando ME., Goodarzi MO., Gordon-Larsen P., Gorkin D., Gross M., Guo Y., Hackinger S., Han S., Hattersley AT., Herder C., Howard A-G., Hsueh W., Huang M., Huang W., Hung Y-J., Hwang MY., Hwu C-M., Ichihara S., Ikram MA., Ingelsson M., Islam MT., Isono M., Jang H-M., Jasmine F., Jiang G., Jonas JB., Jørgensen ME., Jørgensen T., Kamatani Y., Kandeel FR., Kasturiratne A., Katsuya T., Kaur V., Kawaguchi T., Keaton JM., Kho AN., Khor C-C., Kibriya MG., Kim D-H., Kohara K., Kriebel J., Kronenberg F., Kuusisto J., Läll K., Lange LA., Lee M-S., Lee NR., Leong A., Li L., Li Y., Li-Gao R., Ligthart S., Lindgren CM., Linneberg A., Liu C-T., Liu J., Locke AE., Louie T., Luan J., Luk AO., Luo X., Lv J., Lyssenko V., Mamakou V., Mani KR., Meitinger T., Metspalu A., Morris AD., Nadkarni GN., Nadler JL., Nalls MA., Nayak U., Nongmaithem SS., Ntalla I., Okada Y., Orozco L., Patel SR., Pereira MA., Peters A., Pirie FJ., Porneala B., Prasad G., Preissl S., Rasmussen-Torvik LJ., Reiner AP., Roden M., Rohde R., Roll K., Sabanayagam C., Sander M., Sandow K., Sattar N., Schönherr S., Schurmann C., Shahriar M., Shi J., Shin DM., Shriner D., Smith JA., So WY., Stančáková A., Stilp AM., Strauch K., Suzuki K., Takahashi A., Taylor KD., Thorand B., Thorleifsson G., Thorsteinsdottir U., Tomlinson B., Torres JM., Tsai F-J., Tuomilehto J., Tusie-Luna T., Udler MS., Valladares-Salgado A., van Dam RM., van Klinken JB., Varma R., Vujkovic M., Wacher-Rodarte N., Wheeler E., Whitsel EA., Wickremasinghe AR., van Dijk KW., Witte DR., Yajnik CS., Yamamoto K., Yamauchi T., Yengo L., Yoon K., Yu C., Yuan J-M., Yusuf S., Zhang L., Zheng W., FinnGen None., eMERGE Consortium None., Raffel LJ., Igase M., Ipp E., Redline S., Cho YS., Lind L., Province MA., Hanis CL., Peyser PA., Ingelsson E., Zonderman AB., Psaty BM., Wang Y-X., Rotimi CN., Becker DM., Matsuda F., Liu Y., Zeggini E., Yokota M., Rich SS., Kooperberg C., Pankow JS., Engert JC., Chen Y-DI., Froguel P., Wilson JG., Sheu WHH., Kardia SLR., Wu J-Y., Hayes MG., Ma RCW., Wong T-Y., Groop L., Mook-Kanamori DO., Chandak GR., Collins FS., Bharadwaj D., Paré G., Sale MM., Ahsan H., Motala AA., Shu X-O., Park K-S., Jukema JW., Cruz M., McKean-Cowdin R., Grallert H., Cheng C-Y., Bottinger EP., Dehghan A., Tai E-S., Dupuis J., Kato N., Laakso M., Köttgen A., Koh W-P., Palmer CNA., Liu S., Abecasis G., Kooner JS., Loos RJF., North KE., Haiman CA., Florez JC., Saleheen D., Hansen T., Pedersen O., Mägi R., Langenberg C., Wareham NJ., Maeda S., Kadowaki T., Lee J., Millwood IY., Walters RG., Stefansson K., Myers SR., Ferrer J., Gaulton KJ., Meigs JB., Mohlke KL., Gloyn AL., Bowden DW., Below JE., Chambers JC., Sim X., Boehnke M., Rotter JI., McCarthy MI., Morris AP.
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 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.