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 < 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.

The trans-ancestral genomic architecture of glycemic traits / J. Chen, C.N. Spracklen, G. Marenne, A. Varshney, L.J. Corbin, J. Luan, S.M. Willems, Y. Wu, X. Zhang, M. Horikoshi, T.S. Boutin, R. Mägi, J. Waage, R. Li-Gao, K.H.K. Chan, J. Yao, M.D. Anasanti, A.Y. Chu, A. Claringbould, J. Heikkinen, J. Hong, J. Hottenga, S. Huo, M.A. Kaakinen, T. Louie, W. März, H. Moreno-Macias, A. Ndungu, S.C. Nelson, I.M. Nolte, K.E. North, C.K. Raulerson, D. Ray, R. Rohde, D. Rybin, C. Schurmann, X. Sim, L. Southam, I.D. Stewart, C.A. Wang, Y. Wang, P. Wu, W. Zhang, T.S. Ahluwalia, E.V.R. Appel, L.F. Bielak, J.A. Brody, N.P. Burtt, C.P. Cabrera, B.E. Cade, J.F. Chai, X. Chai, L. Chang, C. Chen, B.H. Chen, K.N. Chitrala, Y. Chiu, H.G. de Haan, G.E. Delgado, A. Demirkan, Q. Duan, J. Engmann, S.A. Fatumo, J. Gayán, F. Giulianini, J.H. Gong, S. Gustafsson, Y. Hai, F.P. Hartwig, J. He, Y. Heianza, T. Huang, A. Huerta-Chagoya, M.Y. Hwang, R.A. Jensen, T. Kawaguchi, K.A. Kentistou, Y.J. Kim, M.E. Kleber, I.K. Kooner, S. Lai, L.A. Lange, C.D. Langefeld, M. Lauzon, M. Li, S. Ligthart, J. Liu, M. Loh, J. Long, V. Lyssenko, M. Mangino, C. Marzi, M.E. Montasser, A. Nag, M. Nakatochi, D. Noce, R. Noordam, G. Pistis, M. Preuss, L. Raffield, L.J. Rasmussen-Torvik, S.S. Rich, N.R. Robertson, R. Rueedi, K. Ryan, S. Sanna, R. Saxena, K.E. Schraut, B. Sennblad, K. Setoh, A.V. Smith, T. Sparsø, R.J. Strawbridge, F. Takeuchi, J. Tan, S. Trompet, E. van den Akker, P.J. van der Most, N. Verweij, M. Vogel, H. Wang, C. Wang, N. Wang, H.R. Warren, W. Wen, T. Wilsgaard, A. Wong, A.R. Wood, T. Xie, M.H. Zafarmand, J. Zhao, W. Zhao, N. Amin, Z. Arzumanyan, A. Astrup, S.J.L. Bakker, D. Baldassarre, M. Beekman, R.N. Bergman, A. Bertoni, M. Blüher, L.L. Bonnycastle, S.R. Bornstein, D.W. Bowden, Q. Cai, A. Campbell, H. Campbell, Y.C. Chang, E.J.C. de Geus, A. Dehghan, S. Du, G. Eiriksdottir, A.E. Farmaki, M. Frånberg, C. Fuchsberger, Y. Gao, A.P. Gjesing, A. Goel, S. Han, C.A. Hartman, C. Herder, A.A. Hicks, C. Hsieh, W.A. Hsueh, S. Ichihara, M. Igase, M.A. Ikram, W.C. Johnson, M.E. Jørgensen, P.K. Joshi, R.R. Kalyani, F.R. Kandeel, T. Katsuya, C.C. Khor, W. Kiess, I. Kolcic, T. Kuulasmaa, J. Kuusisto, K. Läll, K. Lam, D.A. Lawlor, N.R. Lee, R.N. Lemaitre, H. Li, S. Lin, J. Lindström, A. Linneberg, J. Liu, C. Lorenzo, T. Matsubara, F. Matsuda, G. Mingrone, S. Mooijaart, S. Moon, T. Nabika, G.N. Nadkarni, J.L. Nadler, M. Nelis, M.J. Neville, J.M. Norris, Y. Ohyagi, A. Peters, P.A. Peyser, O. Polasek, Q. Qi, D. Raven, D.F. Reilly, A. Reiner, F. Rivideneira, K. Roll, I. Rudan, C. Sabanayagam, K. Sandow, N. Sattar, A. Schürmann, J. Shi, H.M. Stringham, K.D. Taylor, T.M. Teslovich, B. Thuesen, P.R.H.J. Timmers, E. Tremoli, M.Y. Tsai, A. Uitterlinden, R.M. van Dam, D. van Heemst, A. van Hylckama Vlieg, J.V. van Vliet-Ostaptchouk, J. Vangipurapu, H. Vestergaard, T. Wang, K. Willems van Dijk, T. Zemunik, G.R. Abecasis, L.S. Adair, C.A. Aguilar-Salinas, M.E. Alarcón-Riquelme, P. An, L. Aviles-Santa, D.M. Becker, L.J. Beilin, S. Bergmann, H. Bisgaard, C. Black, M. Boehnke, E. Boerwinkle, B.O. Böhm, K. Bønnelykke, D.I. Boomsma, E.P. Bottinger, T.A. Buchanan, M. Canouil, M.J. Caulfield, J.C. Chambers, D.I. Chasman, Y.I. Chen, C. Cheng, F.S. Collins, A. Correa, F. Cucca, H.J. de Silva, G. Dedoussis, S. Elmståhl, M.K. Evans, E. Ferrannini, L. Ferrucci, J.C. Florez, P.W. Franks, T.M. Frayling, P. Froguel, B. Gigante, M.O. Goodarzi, P. Gordon-Larsen, H. Grallert, N. Grarup, S. Grimsgaard, L. Groop, V. Gudnason, X. Guo, A. Hamsten, T. Hansen, C. Hayward, S.R. Heckbert, B.L. Horta, W. Huang, E. Ingelsson, P.S. James, M. Jarvelin, J.B. Jonas, J.W. Jukema, P. Kaleebu, R. Kaplan, S.L.R. Kardia, N. Kato, S.M. Keinanen-Kiukaanniemi, B. Kim, M. Kivimaki, H.A. Koistinen, J.S. Kooner, A. Körner, P. Kovacs, D. Kuh, M. Kumari, Z. Kutalik, M. Laakso, T.A. Lakka, L.J. Launer, K. Leander, H. Li, X. Lin, L. Lind, C. Lindgren, S. Liu, R.J.F. Loos, P.K.E. Magnusson, A. Mahajan, A. 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McCarthy, J. Dupuis, J.B. Meigs, R.A. Scott, I. Prokopenko, A. Leong, C. Liu, S.C.J. Parker, K.L. Mohlke, C. Langenberg, E. Wheeler, A.P. Morris, I. Barroso. - In: NATURE GENETICS. - ISSN 1061-4036. - (2021). [Epub ahead of print] [10.1038/s41588-021-00852-9]

The trans-ancestral genomic architecture of glycemic traits

D. Baldassarre
Membro del Collaboration Group
;
E. Tremoli
Membro del Collaboration Group
;
2021

Abstract

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 < 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.
Settore BIO/14 - Farmacologia
31-mag-2021
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