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1
The trans-ancestral genomic architecture of glycemic traits
Chen, J
;
Spracklen, CN
;
Marenne, G
;
Varshney, A
;
Corbin, LJ
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Luan, J
;
Willems, SM
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Wu, Y
;
Zhang, X
;
Horikoshi, M
;
Boutin, TS
;
Mägi, R
;
Waage, J
;
Li-Gao, R
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Chan, KHK
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Yao, J
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Anasanti, MD
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Chu, AY
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Claringbould, A
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Heikkinen, J
;
Hong, J
;
Hottenga, J-J
;
Huo, S
;
Kaakinen, MA
;
Louie, T
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März, W
;
Moreno-Macias, H
;
Ndungu, A
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Nelson, SC
;
Nolte, IM
;
North, KE
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Raulerson, CK
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Ray, D
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Rohde, R
;
Rybin, D
;
Schurmann, C
;
Sim, X
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Southam, L
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Stewart, ID
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Wang, CA
;
Wang, Y
;
Wu, P
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Zhang, W
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Ahluwalia, TS
;
Appel, EVR
;
Bielak, LF
;
Brody, JA
;
Burtt, NP
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Cabrera, CP
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Cade, BE
;
Chai, JF
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Chai, X
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Chang, L-C
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Chen, C-H
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Chen, BH
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Chitrala, KN
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Chiu, Y-F
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de Haan, HG
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Delgado, GE
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Demirkan, A
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Duan, Q
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Engmann, J
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Fatumo, SA
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Gayán, J
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Giulianini, F
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Gong, JH
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Gustafsson, S
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Hai, Y
;
Hartwig, FP
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He, J
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Heianza, Y
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Huang, T
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Huerta-Chagoya, A
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Hwang, MY
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Jensen, RA
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Kawaguchi, T
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Kentistou, KA
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Kim, YJ
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Kleber, ME
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Kooner, IK
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Lai, S
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Lange, LA
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Langefeld, CD
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Lauzon, M
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Li, M
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Ligthart, S
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Liu, J
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Loh, M
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Long, J
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Lyssenko, V
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Mangino, M
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Marzi, C
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Montasser, ME
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Nag, A
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Nakatochi, M
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Noce, D
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Noordam, R
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Pistis, G
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Preuss, M
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Raffield, L
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Rasmussen-Torvik, LJ
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Rich, SS
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Robertson, NR
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Rueedi, R
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Ryan, K
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Sanna, S
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Saxena, R
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Schraut, KE
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Sennblad, B
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Setoh, K
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Smith, AV
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Sparsø, T
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Strawbridge, RJ
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Takeuchi, F
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Tan, J
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Trompet, S
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van den Akker, E
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van der Most, PJ
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Verweij, N
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Vogel, M
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Wang, H
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Wang, C
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Wang, N
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Warren, HR
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Wen, W
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Wilsgaard, T
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Wong, A
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Wood, AR
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Xie, T
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Zafarmand, MH
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Zhao, J-H
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Zhao, W
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Amin, N
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Arzumanyan, Z
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Astrup, A
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Bakker, SJL
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Baldassarre, D
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Beekman, M
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Bergman, RN
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Bertoni, A
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Blüher, M
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Bonnycastle, LL
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Bornstein, SR
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Bowden, DW
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Cai, Q
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Campbell, A
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Campbell, H
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Chang, YC
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de Geus, EJC
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Dehghan, A
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Du, S
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Eiriksdottir, G
;
Farmaki, AE
;
Frånberg, M
;
Fuchsberger, C
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Gao, Y
;
Gjesing, AP
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Goel, A
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Han, S
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Hartman, CA
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Herder, C
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Hicks, AA
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Hsieh, C-H
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Hsueh, WA
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Ichihara, S
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Igase, M
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Ikram, MA
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Johnson, WC
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Jørgensen, ME
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Joshi, PK
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Kalyani, RR
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Kandeel, FR
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Katsuya, T
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Khor, CC
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Kiess, W
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Kolcic, I
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Kuulasmaa, T
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Kuusisto, J
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Läll, K
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Lam, K
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Lawlor, DA
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Lee, NR
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Lemaitre, RN
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Li, H
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Lifelines Cohort Study
;
Lin, S-Y
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Lindström, J
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Linneberg, A
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Lorenzo, C
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Matsubara, T
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Matsuda, F
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Mingrone, G
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Mooijaart, S
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Moon, S
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Nabika, T
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Nadkarni, GN
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Nadler, JL
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Nelis, M
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Neville, MJ
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Norris, JM
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Ohyagi, Y
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Peters, A
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Peyser, PA
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Polasek, O
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Qi, Q
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Raven, D
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Reilly, DF
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Reiner, A
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Rivideneira, F
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Roll, K
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Rudan, I
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Sabanayagam, C
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Sandow, K
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Sattar, N
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Schürmann, A
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Shi, J
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Stringham, HM
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Taylor, KD
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Teslovich, TM
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Thuesen, B
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Timmers, PRHJ
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Tremoli, E
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Tsai, MY
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Uitterlinden, A
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van Dam, RM
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van Heemst, D
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van Hylckama Vlieg, A
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van Vliet-Ostaptchouk, JV
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Vangipurapu, J
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Vestergaard, H
;
Wang, T
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Willems van Dijk, K
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Zemunik, T
;
Abecasis, GR
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Adair, LS
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Aguilar-Salinas, CA
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Alarcón-Riquelme, ME
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An, P
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Aviles-Santa, L
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Becker, DM
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Beilin, LJ
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Bergmann, S
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Bisgaard, H
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Black, C
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Boehnke, M
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Boerwinkle, E
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Böhm, BO
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Bønnelykke, K
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Boomsma, DI
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Bottinger, EP
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Buchanan, TA
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Canouil, M
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Caulfield, MJ
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Chambers, JC
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Chasman, DI
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Chen, Y-DI
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Cheng, C-Y
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Collins, FS
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Correa, A
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Cucca, F
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de Silva, HJ
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Dedoussis, G
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Elmståhl, S
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Evans, MK
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Ferrannini, E
;
Ferrucci, L
;
Florez, JC
;
Franks, PW
;
Frayling, TM
;
Froguel, P
;
Gigante, B
;
Goodarzi, MO
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Gordon-Larsen, P
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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
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.
URL:
https://doi.org/10.1038/s41588-021-00852-9
http://hdl.handle.net/10871/125997
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2
The trans-ancestral genomic architecture of glycemic traits.
Chen, J
;
Spracklen, CN
;
Marenne, G
. - 2021
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3
The trans-ancestral genomic architecture of glycemic traits.
Chen, J.
;
Spracklen, C.N.
;
Marenne, G.
...
In: Nature genetics, vol. 53, no. 6, pp. 840-860 (2021)
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