Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications.
Suzuki K., Hatzikotoulas K., Southam L., Taylor HJ., Yin X., Lorenz KM., Mandla R., Huerta-Chagoya A., Rayner NW., Bocher O., Arruda ALDSV., Sonehara K., Namba S., Lee SSK., Preuss MH., Petty LE., Schroeder P., Vanderwerff B., Kals M., Bragg F., Lin K., Guo X., Zhang W., Yao J., Kim YJ., Graff M., Takeuchi F., Nano J., Lamri A., Nakatochi M., Moon S., Scott RA., Cook JP., Lee J-J., Pan I., Taliun D., Parra EJ., Chai J-F., Bielak LF., Tabara Y., Hai Y., Thorleifsson G., Grarup N., Sofer T., Wuttke M., Sarnowski C., Gieger C., Nousome D., Trompet S., Kwak S-H., Long J., Sun M., Tong L., Chen W-M., Nongmaithem SS., Noordam R., Lim VJY., Tam CHT., Joo YY., Chen C-H., Raffield LM., Prins BP., Nicolas A., Yanek LR., Chen G., Brody JA., Kabagambe E., An P., Xiang AH., Choi HS., Cade BE., Tan J., Broadaway KA., Williamson A., Kamali Z., Cui J., Adair LS., Adeyemo A., Aguilar-Salinas CA., Ahluwalia TS., Anand SS., Bertoni A., Bork-Jensen J., Brandslund I., Buchanan TA., Burant CF., Butterworth AS., 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., Danesh J., 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., Franco OH., Frayling TM., Freedman BI., Genter P., Gerstein HC., Giedraitis V., González-Villalpando C., González-Villalpando ME., Gordon-Larsen P., Gross M., Guare LA., Hackinger S., Han S., Hattersley AT., Herder C., Horikoshi M., 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 T., Kandeel FR., Kasturiratne A., Katsuya T., Kaur V., Kawaguchi T., Keaton JM., Kho AN., Khor C-C., Kibriya MG., Kim D-H., Kronenberg F., Kuusisto J., Läll K., Lange LA., Lee KM., Lee M-S., Lee NR., Leong A., Li L., Li Y., Li-Gao R., Lithgart S., Lindgren CM., Linneberg A., Liu C-T., Liu J., Locke AE., Louie T., Luan J., Luk AO., Luo X., Lv J., Lynch JA., Lyssenko V., Maeda S., Mamakou V., Mansuri SR., Matsuda K., Meitinger T., Metspalu A., Mo H., Morris AD., Nadler JL., Nalls MA., Nayak U., Ntalla I., Okada Y., Orozco L., Patel SR., Patil S., Pei P., Pereira MA., Peters A., Pirie FJ., Polikowsky HG., Porneala B., Prasad G., Rasmussen-Torvik LJ., Reiner AP., Roden M., Rohde R., Roll K., Sabanayagam C., Sandow K., Sankareswaran A., Sattar N., Schönherr S., Shahriar M., Shen B., Shi J., Shin DM., Shojima N., Smith JA., So WY., Stančáková A., Steinthorsdottir V., Stilp AM., Strauch K., Taylor KD., Thorand B., Thorsteinsdottir U., Tomlinson B., Tran TC., Tsai F-J., Tuomilehto J., Tusie-Luna T., Udler MS., Valladares-Salgado A., van Dam RM., van Klinken JB., Varma R., Wacher-Rodarte N., Wheeler E., Wickremasinghe AR., van Dijk KW., Witte DR., Yajnik CS., Yamamoto K., Yamamoto K., Yoon K., Yu C., Yuan J-M., Yusuf S., Zawistowski M., Zhang L., Zheng W., VA Million Veteran Program None., AMED GRIFIN Diabetes Initiative Japan None., Biobank Japan Project None., Penn Medicine BioBank None., Regeneron Genetics Center None., eMERGE Consortium None., International Consortium for Blood Pressure (ICBP) None., Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC) None., Raffel LJ., Igase M., Ipp E., Redline S., Cho YS., Lind L., Province MA., Fornage M., Hanis CL., Ingelsson E., Zonderman AB., Psaty BM., Wang Y-X., Rotimi CN., Becker DM., Matsuda F., Liu Y., Yokota M., Kardia SLR., Peyser PA., Pankow JS., Engert JC., Bonnefond A., Froguel P., Wilson JG., Sheu WHH., Wu J-Y., Hayes MG., Ma RCW., Wong T-Y., Mook-Kanamori DO., Tuomi T., Chandak GR., Collins FS., Bharadwaj D., Paré G., Sale MM., Ahsan H., Motala AA., Shu X-O., Park K-S., Jukema JW., Cruz M., Chen Y-DI., Rich SS., McKean-Cowdin R., Grallert H., Cheng C-Y., Ghanbari M., Tai E-S., Dupuis J., Kato N., Laakso M., Köttgen A., Koh W-P., Bowden DW., Palmer CNA., Kooner JS., Kooperberg C., Liu S., North KE., Saleheen D., Hansen T., Pedersen O., Wareham NJ., Lee J., Kim B-J., Millwood IY., Walters RG., Stefansson K., Goodarzi MO., Mohlke KL., Langenberg C., Haiman CA., Loos RJF., Florez JC., Rader DJ., Ritchie MD., Zöllner S., Mägi R., Denny JC., Yamauchi T., Kadowaki T., Chambers JC., Ng MCY., Sim X., Below JE., Tsao PS., Chang K-M., McCarthy MI., Meigs JB., Mahajan A., Spracklen CN., Mercader JM., Boehnke M., Rotter JI., Vujkovic M., Voight BF., Morris AP., Zeggini E.
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5×10-8) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.