The trans-ancestral genomic architecture of glycemic traits.
Chen J., Spracklen CN., Marenne G., Varshney A., Corbin LJ., Luan J., Willems SM., Wu Y., Zhang X., Horikoshi M., Boutin TS., Mägi R., Waage J., Li-Gao R., Chan KHK., Yao J., Anasanti MD., Chu AY., Claringbould A., Heikkinen J., Hong J., Hottenga J-J., Huo S., Kaakinen MA., Louie T., März W., Moreno-Macias H., Ndungu A., Nelson SC., Nolte IM., North KE., Raulerson CK., Ray D., Rohde R., Rybin D., Schurmann C., Sim X., Southam L., Stewart ID., Wang CA., Wang Y., Wu P., Zhang W., Ahluwalia TS., Appel EVR., Bielak LF., Brody JA., Burtt NP., Cabrera CP., Cade BE., Chai JF., Chai X., Chang L-C., Chen C-H., Chen BH., Chitrala KN., Chiu Y-F., de Haan HG., Delgado GE., Demirkan A., Duan Q., Engmann J., Fatumo SA., Gayán J., Giulianini F., Gong JH., Gustafsson S., Hai Y., Hartwig FP., He J., Heianza Y., Huang T., Huerta-Chagoya A., Hwang MY., Jensen RA., Kawaguchi T., Kentistou KA., Kim YJ., Kleber ME., Kooner IK., Lai S., Lange LA., Langefeld CD., Lauzon M., Li M., Ligthart S., Liu J., Loh M., Long J., Lyssenko V., Mangino M., Marzi C., Montasser ME., Nag A., Nakatochi M., Noce D., Noordam R., Pistis G., Preuss M., Raffield L., Rasmussen-Torvik LJ., Rich SS., Robertson NR., Rueedi R., Ryan K., Sanna S., Saxena R., Schraut KE., Sennblad B., Setoh K., Smith AV., Sparsø T., Strawbridge RJ., Takeuchi F., Tan J., Trompet S., van den Akker E., van der Most PJ., Verweij N., Vogel M., Wang H., Wang C., Wang N., Warren HR., Wen W., Wilsgaard T., Wong A., Wood AR., Xie T., Zafarmand MH., Zhao J-H., Zhao W., Amin N., Arzumanyan Z., Astrup A., Bakker SJL., Baldassarre D., Beekman M., Bergman RN., Bertoni A., Blüher M., Bonnycastle LL., Bornstein SR., Bowden DW., Cai Q., Campbell A., Campbell H., Chang YC., de Geus EJC., Dehghan A., Du S., Eiriksdottir G., Farmaki AE., Frånberg M., Fuchsberger C., Gao Y., Gjesing AP., Goel A., Han S., Hartman CA., Herder C., Hicks AA., Hsieh C-H., Hsueh WA., Ichihara S., Igase M., Ikram MA., Johnson WC., Jørgensen ME., Joshi PK., Kalyani RR., Kandeel FR., Katsuya T., Khor CC., Kiess W., Kolcic I., Kuulasmaa T., Kuusisto J., Läll K., Lam K., Lawlor DA., Lee NR., Lemaitre RN., Li H., Lifelines Cohort Study None., Lin S-Y., Lindström J., Linneberg A., Liu J., Lorenzo C., Matsubara T., Matsuda F., Mingrone G., Mooijaart S., Moon S., Nabika T., Nadkarni GN., Nadler JL., Nelis M., Neville MJ., Norris JM., Ohyagi Y., Peters A., Peyser PA., Polasek O., Qi Q., Raven D., Reilly DF., Reiner A., Rivideneira F., Roll K., Rudan I., Sabanayagam C., Sandow K., Sattar N., Schürmann A., Shi J., Stringham HM., Taylor KD., Teslovich TM., Thuesen B., Timmers PRHJ., Tremoli E., Tsai MY., Uitterlinden A., van Dam RM., van Heemst D., van Hylckama Vlieg A., van Vliet-Ostaptchouk JV., Vangipurapu J., Vestergaard H., Wang T., Willems van Dijk K., Zemunik T., Abecasis GR., Adair LS., Aguilar-Salinas CA., Alarcón-Riquelme ME., An P., Aviles-Santa L., Becker DM., Beilin LJ., Bergmann S., Bisgaard H., Black C., Boehnke M., Boerwinkle E., Böhm BO., Bønnelykke K., Boomsma DI., Bottinger EP., Buchanan TA., Canouil M., Caulfield MJ., Chambers JC., Chasman DI., Chen Y-DI., Cheng C-Y., Collins FS., Correa A., Cucca F., de Silva HJ., Dedoussis G., Elmståhl S., Evans MK., Ferrannini E., Ferrucci L., Florez JC., Franks PW., Frayling TM., Froguel P., Gigante B., Goodarzi MO., Gordon-Larsen P., Grallert H., Grarup N., Grimsgaard S., Groop L., Gudnason V., Guo X., Hamsten A., Hansen T., Hayward C., Heckbert SR., Horta BL., Huang W., Ingelsson E., James PS., Jarvelin M-R., Jonas JB., Jukema JW., Kaleebu P., Kaplan R., Kardia SLR., Kato N., Keinanen-Kiukaanniemi SM., Kim B-J., Kivimaki M., Koistinen HA., Kooner JS., Körner A., Kovacs P., Kuh D., Kumari M., Kutalik Z., Laakso M., Lakka TA., Launer LJ., Leander K., Li H., Lin X., Lind L., Lindgren C., Liu S., Loos RJF., Magnusson PKE., Mahajan A., Metspalu A., Mook-Kanamori DO., Mori TA., Munroe PB., Njølstad I., O'Connell JR., Oldehinkel AJ., Ong KK., Padmanabhan S., Palmer CNA., Palmer ND., Pedersen O., Pennell CE., Porteous DJ., Pramstaller PP., Province MA., Psaty BM., Qi L., Raffel LJ., Rauramaa R., Redline S., Ridker PM., Rosendaal FR., Saaristo TE., Sandhu M., Saramies J., Schneiderman N., Schwarz P., Scott LJ., Selvin E., Sever P., Shu X-O., Slagboom PE., Small KS., Smith BH., Snieder H., Sofer T., Sørensen TIA., Spector TD., Stanton A., Steves CJ., Stumvoll M., Sun L., Tabara Y., Tai ES., Timpson NJ., Tönjes A., Tuomilehto J., Tusie T., Uusitupa M., van der Harst P., van Duijn C., Vitart V., Vollenweider P., Vrijkotte TGM., Wagenknecht LE., Walker M., Wang YX., Wareham NJ., Watanabe RM., Watkins H., Wei WB., Wickremasinghe AR., Willemsen G., Wilson JF., Wong T-Y., Wu J-Y., Xiang AH., Yanek LR., Yengo L., Yokota M., Zeggini E., Zheng W., Zonderman AB., Rotter JI., Gloyn AL., McCarthy MI., Dupuis J., Meigs JB., Scott RA., Prokopenko I., Leong A., Liu C-T., Parker SCJ., Mohlke KL., Langenberg C., Wheeler E., Morris AP., Barroso I., Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC) None.
Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P -8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.