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The trans-ancestral genomic architecture of glycemic traits
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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; Lin, S-Y; Lindström, J; Linneberg, A; 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; 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). - : Nature Research, 2021
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Abstract:
This is the author accepted manuscript. The final version is available from nature Research via the DOI in this record ; Note: There are differences between the text of the author accepted manuscript in this record and that of the final published version. this is due to a large number of textual changes and cuts made by the authors after official final acceptance, at the request of the journal editorial office. ; Code availability: Source code implementing the methods described in the paper are publicly available at https://doi.org/10.5281/zenodo.4607311. ; Data availability: Ancestry-specific and overall meta-analysis summary level results are available through the MAGIC website (https://www.magicinvestigators.org/). Summary statistics are also available through the GWAS catalog (https://www.ebi.ac.uk/gwas/) with the following accession codes: GCST90002225, GCST90002226, GCST90002227, GCST90002228, GCST90002229, GCST90002230, GCST90002231, GCST90002232, GCST90002233, GCST90002234, GCST90002235, GCST90002236, GCST90002237, GCST90002238, GCST90002239, GCST90002240, GCST90002241, GCST90002242, GCST90002243, GCST90002244, GCST90002245, GCST90002246, GCST90002247 and GCST90002248. ; 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.
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URL: https://doi.org/10.1038/s41588-021-00852-9
http://hdl.handle.net/10871/125997
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The trans-ancestral genomic architecture of glycemic traits.
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The trans-ancestral genomic architecture of glycemic traits.
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