| Title | {The trans-ancestral genomic architecture of glycemic traits |
| Publication Type | Journal Article |
| Year of Publication | 2021 |
| Authors | 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, JJ, 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, LC, Chen, CH, Chen, BH, Chitrala, KN, Chiu, YF, 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, JH, 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, CH, 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, Lin, SY, 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, A. Vlieg, vanHylckama, Van Vliet-Ostaptchouk, JV, Vangipurapu, J, Vestergaard, H, Wang, T, K. van Dijk, W, 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, YI, Cheng, CY, 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, MR, Jonas, JB, Jukema, JW, Kaleebu, P, Kaplan, R, Kardia, SLR, Kato, N, Keinanen-Kiukaanniemi, SM, Kim, BJ, 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, XO, 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, Tonjes, 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, TY, Wu, JY, 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, CT, Parker, SCJ, Mohlke, KL, Langenberg, C, Wheeler, E, Morris, AP, Barroso, I, de Haan, HG, van den Akker, E, van der Most, PJ, de Geus, EJC, van Dam, RM, van Heemst, D, A. Vlieg, vanHylckama, K. van Dijk, vanWillems, de Silva, HJ, van der Harst, P, van Duijn, C |
| Journal | Nat Genet |
| Volume | 53 |
| Pagination | 840–860 |
| Date Published | 06 |
| Abstract | 10.1038/s41588-021-00852-9Glycemic 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 < 5 × 10-8), 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. |
