| Title | Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications. |
| Publication Type | Journal Article |
| Year of Publication | 2023 |
| Authors | Suzuki, K, Hatzikotoulas, K, Southam, L, Taylor, HJ, Yin, X, Lorenz, KM, Mandla, R, Huerta-Chagoya, A, Rayner, NW, Bocher, O, de, SVArruda A, Sonehara, K, Namba, S, Lee, SSK, Preuss, MH, Petty, LE, Schroeder, P, Vanderwerff, B, Kals, M, Bragg, F, Lin, K, Guo, X, Zhang, W, Yao, J, Kim, YJin, Graff, M, Takeuchi, F, Nano, J, Lamri, A, Nakatochi, M, Moon, S, Scott, RA, Cook, JP, Lee, J-J, Pan, I, Taliun, D, Parra, EJ, Chai, J-F, Bielak, LF, Tabara, Y, Hai, Y, Thorleifsson, G, Grarup, N, Sofer, T, Wuttke, M, Sarnowski, C, Gieger, C, Nousome, D, Trompet, S, Kwak, S-H, Long, J, Sun, M, Tong, L, Chen, W-M, Nongmaithem, SS, Noordam, R, J Y Lim, V, Tam, CHT, Joo, YYoonie, Chen, C-H, Raffield, LM, Prins, BPeter, Nicolas, A, Yanek, LR, Chen, G, Brody, JA, Kabagambe, E, An, P, Xiang, AH, Choi, HSun, Cade, BE, Tan, J, K Broadaway, A, Williamson, A, Kamali, Z, Cui, J, Adair, LS, Adeyemo, A, Aguilar-Salinas, CA, Ahluwalia, TS, Anand, SS, Bertoni, A, Bork-Jensen, J, Brandslund, I, Buchanan, TA, Burant, CF, Butterworth, AS, Canouil, M, Chan, JCN, Chang, L-C, Chee, M-L, Chen, J, Chen, S-H, Chen, Y-T, Chen, Z, Chuang, L-M, Cushman, M, Danesh, J, Das, SK, H de Silva, J, Dedoussis, G, Dimitrov, L, Doumatey, AP, Du, S, Duan, Q, Eckardt, K-U, Emery, LS, Evans, DS, Evans, MK, Fischer, K, Floyd, JS, Ford, I, Franco, OH, Frayling, TM, Freedman, BI, Genter, P, Gerstein, HC, Giedraitis, V, González-Villalpando, C, Gonzalez-Villalpando, MElena, Gordon-Larsen, P, Gross, M, Guare, LA, Hackinger, S, Han, S, Hattersley, AT, Herder, C, Horikoshi, M, Howard, A-G, Hsueh, W, Huang, M, Huang, W, Hung, Y-J, Hwang, MYeong, Hwu, C-M, Ichihara, S, Ikram, MArfan, Ingelsson, M, Islam, MTariqul, Isono, M, Jang, H-M, Jasmine, F, Jiang, G, Jonas, JB, Jørgensen, T, Kandeel, FR, Kasturiratne, A, Katsuya, T, Kaur, V, Kawaguchi, T, Keaton, JM, Kho, AN, Khor, C-C, Kibriya, MG, Kim, D-H, Kronenberg, F, Kuusisto, J, Läll, K, Lange, LA, Lee, KMin, Lee, M-S, Lee, NR, Leong, A, Li, L, Li, Y, Li-Gao, R, Lithgart, S, Lindgren, CM, Linneberg, A, Liu, C-T, Liu, J, Locke, AE, Louie, T, Luan, J'an, Luk, AO, Luo, X, Lv, J, Lynch, JA, Lyssenko, V, Maeda, S, Mamakou, V, Mansuri, SRafik, Matsuda, K, Meitinger, T, Metspalu, A, Mo, H, Morris, AD, Nadler, JL, Nalls, MA, Nayak, U, Ntalla, I, Okada, Y, Orozco, L, Patel, SR, Patil, S, Pei, P, Pereira, MA, Peters, A, Pirie, FJ, Polikowsky, HG, Porneala, B, Prasad, G, Rasmussen-Torvik, LJ, Reiner, AP, Roden, M, Rohde, R, Roll, K, Sabanayagam, C, Sandow, K, Sankareswaran, A, Sattar, N, Schönherr, S, Shahriar, M, Shen, B, Shi, J, Shin, DMun, Shojima, N, Smith, JA, So, WYee, Stančáková, A, Steinthorsdottir, V, Stilp, AM, Strauch, K, Taylor, KD, Thorand, B, Thorsteinsdottir, U, Tomlinson, B, Tran, TC, Tsai, F-J, Tuomilehto, J, Tusié-Luna, T, Udler, MS, Valladares-Salgado, A, van Dam, RM, van Klinken, JB, Varma, R, Wacher-Rodarte, N, Wheeler, E, Wickremasinghe, AR, van Dijk, KW, Witte, DR, Yajnik, CS, Yamamoto, K, Yamamoto, K, Yoon, K, Yu, C, Yuan, J-M, Yusuf, S, Zawistowski, M, Zhang, L, Zheng, W, Project, BJapan, BioBank, PMedicine, Center, RGenetics, Consortium, eMERGE, Raffel, LJ, Igase, M, Ipp, E, Redline, S, Cho, YS, Lind, L, Province, MA, Fornage, M, Hanis, CL, Ingelsson, E, Zonderman, AB, Psaty, BM, Wang, Y-X, Rotimi, CN, Becker, DM, Matsuda, F, Liu, Y, Yokota, M, Kardia, SLR, Peyser, PA, Pankow, JS, Engert, JC, Bonnefond, A, Froguel, P, Wilson, JG, Sheu, WHH, Wu, J-Y, M Hayes, G, Ma, RCW, Wong, T-Y, Mook-Kanamori, DO, Tuomi, T, Chandak, GR, Collins, FS, Bharadwaj, D, Paré, G, Sale, MM, Ahsan, H, Motala, AA, Shu, X-O, Park, K-S, J Jukema, W, Cruz, M, Chen, Y-DI, Rich, SS, McKean-Cowdin, R, Grallert, H, Cheng, C-Y, Ghanbari, M, Tai, E-S, Dupuis, J, Kato, N, Laakso, M, Köttgen, A, Koh, W-P, Bowden, DW, Palmer, CNA, Kooner, JS, Kooperberg, C, Liu, S, North, KE, Saleheen, D, Hansen, T, Pedersen, O, Wareham, NJ, Lee, J, Kim, B-J, Millwood, IY, Walters, RG, Stefansson, K, Goodarzi, MO, Mohlke, KL, Langenberg, C, Haiman, CA, Loos, RJF, Florez, JC, Rader, DJ, Ritchie, MD, Zöllner, S, Mägi, R, Denny, JC, Yamauchi, T, Kadowaki, T, Chambers, JC, C Y Ng, M, Sim, X, Below, JE, Tsao, PS, Chang, K-M, McCarthy, MI, Meigs, JB, Mahajan, A, Spracklen, CN, Mercader, JM, Boehnke, M, Rotter, JI, Vujkovic, M, Voight, BF, Morris, AP, Zeggini, E |
| Corporate/Institutional Authors | VA Million Veteran Program, AMED GRIFIN Diabetes Initiative Japan, International Consortium for Blood Pressure (ICBP), Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC) |
| Journal | medRxiv |
| Date Published | 2023 Mar 31 |
| Abstract | <p>Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5×10 ) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.</p> |
| DOI | 10.1101/2023.03.31.23287839 |
| Alternate Journal | medRxiv |
| PubMed ID | 37034649 |
| PubMed Central ID | PMC10081410 |
