| Title | Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. |
| Publication Type | Journal Article |
| Year of Publication | 2018 |
| Authors | Mahajan, A, Wessel, J, Willems, SM, Zhao, W, Robertson, NR, Chu, AY, Gan, W, Kitajima, H, Taliun, D, N Rayner, W, Guo, X, Lu, Y, Li, M, Jensen, RA, Hu, Y, Huo, S, Lohman, KK, Zhang, W, Cook, JP, Prins, BPeter, Flannick, J, Grarup, N, Trubetskoy, VVladimirov, Kravic, J, Kim, YJin, Rybin, DV, Yaghootkar, H, Müller-Nurasyid, M, Meidtner, K, Li-Gao, R, Varga, TV, Marten, J, Li, J, Smith, AVernon, An, P, Ligthart, S, Gustafsson, S, Malerba, G, Demirkan, A, Tajes, JFernandez, Steinthorsdottir, V, Wuttke, M, Lecoeur, C, Preuss, M, Bielak, LF, Graff, M, Highland, HM, Justice, AE, Liu, DJ, Marouli, E, Peloso, GMarie, Warren, HR, Afaq, S, Afzal, S, Ahlqvist, E, Almgren, P, Amin, N, Bang, LB, Bertoni, AG, Bombieri, C, Bork-Jensen, J, Brandslund, I, Brody, JA, Burtt, NP, Canouil, M, Chen, Y-DI, Cho, YS, Christensen, C, Eastwood, SV, Eckardt, K-U, Fischer, K, Gambaro, G, Giedraitis, V, Grove, ML, de Haan, HG, Hackinger, S, Hai, Y, Han, S, Tybjærg-Hansen, A, Hivert, M-F, Isomaa, B, Jäger, S, Jørgensen, ME, Jørgensen, T, Käräjämäki, AM, Kim, B-J, Kim, SSoo, Koistinen, HA, Kovacs, P, Kriebel, J, Kronenberg, F, Läll, K, Lange, LA, Lee, J-J, Lehne, B, Li, H, Lin, K-H, Linneberg, A, Liu, C-T, Liu, J, Loh, M, Mägi, R, Mamakou, V, McKean-Cowdin, R, Nadkarni, G, Neville, M, Nielsen, SF, Ntalla, I, Peyser, PA, Rathmann, W, Rice, K, Rich, SS, Rode, L, Rolandsson, O, Schönherr, S, Selvin, E, Small, KS, Stančáková, A, Surendran, P, Taylor, KD, Teslovich, TM, Thorand, B, Thorleifsson, G, Tin, A, Tönjes, A, Varbo, A, Witte, DR, Wood, AR, Yajnik, P, Yao, J, Yengo, L, Young, R, Amouyel, P, Boeing, H, Boerwinkle, E, Bottinger, EP, Chowdhury, iv, R, Collins, FS, Dedoussis, G, Dehghan, A, Deloukas, P, Ferrario, MM, Ferrieres, J, Florez, JC, Frossard, P, Gudnason, V, Harris, TB, Heckbert, SR, Howson, JMM, Ingelsson, M, Kathiresan, S, Kee, F, Kuusisto, J, Langenberg, C, Launer, LJ, Lindgren, CM, Männistö, S, Meitinger, T, Melander, O, Mohlke, KL, Moitry, M, Morris, AD, Murray, AD, de Mutsert, R, Orho-Melander, M, Owen, KR, Perola, M, Peters, A, Province, MA, Rasheed, A, Ridker, PM, Rivadineira, F, Rosendaal, FR, Rosengren, AH, Salomaa, V, Sheu, WH-H, Sladek, R, Smith, BH, Strauch, K, Uitterlinden, AG, Varma, R, Willer, CJ, Blüher, M, Butterworth, AS, Chambers, JCampbell, Chasman, DI, Danesh, J, van Duijn, C, Dupuis, J, Franco, OH, Franks, PW, Froguel, P, Grallert, H, Groop, L, Han, B-G, Hansen, T, Hattersley, AT, Hayward, C, Ingelsson, E, Kardia, SLR, Karpe, F, Kooner, JSingh, Köttgen, A, Kuulasmaa, K, Laakso, M, Lin, X, Lind, L, Liu, Y, Loos, RJF, Marchini, J, Metspalu, A, Mook-Kanamori, D, Nordestgaard, BG, Palmer, CNA, Pankow, JS, Pedersen, O, Psaty, BM, Rauramaa, R, Sattar, N, Schulze, MB, Soranzo, N, Spector, TD, Stefansson, K, Stumvoll, M, Thorsteinsdottir, U, Tuomi, T, Tuomilehto, J, Wareham, NJ, Wilson, JG, Zeggini, E, Scott, RA, Barroso, I, Frayling, TM, Goodarzi, MO, Meigs, JB, Boehnke, M, Saleheen, D, Morris, AP, Rotter, JI, McCarthy, MI |
| Corporate/Institutional Authors | ExomeBP Consortium, MAGIC Consortium,, GIANT Consortium |
| Journal | Nat Genet |
| Volume | 50 |
| Issue | 4 |
| Pagination | 559-571 |
| Date Published | 2018 Apr |
| ISSN | 1546-1718 |
| Abstract | <p>We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.</p> |
| DOI | 10.1038/s41588-018-0084-1 |
| Alternate Journal | Nat. Genet. |
| PubMed ID | 29632382 |
| PubMed Central ID | PMC5898373 |
| Grant List | U01 DK085545 / DK / NIDDK NIH HHS / United States
R01 DK098032 / DK / NIDDK NIH HHS / United States
U01 DK105535 / DK / NIDDK NIH HHS / United States
P30 DK063491 / DK / NIDDK NIH HHS / United States
UL1 TR001881 / TR / NCATS NIH HHS / United States |
