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-DIda, Cho, YShin, 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, A, 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, Tonjes, 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 Authors | ExomeBP Consortium, MAGIC Consortium, GIANT Consortium |
Journal | Nat Genet |
Volume | 50 |
Issue | 4 |
Pagination | 559-571 |
Date Published | 2018 Apr |
ISSN | 1546-1718 |
Keywords | Alleles, Chromosome Mapping, Diabetes Mellitus, Type 2, Exome Sequencing, Female, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Male, White People |
Abstract | 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. |
DOI | 10.1038/s41588-018-0084-1 |
Alternate Journal | Nat Genet |
PubMed ID | 29632382 |
PubMed Central ID | PMC5898373 |
Grant List | MR/L020149/1 / MRC_ / Medical Research Council / United Kingdom MR/L003120/1 / MRC_ / Medical Research Council / United Kingdom R35 HL135824 / HL / NHLBI NIH HHS / United States MC_PC_13040 / MRC_ / Medical Research Council / United Kingdom P30 DK063491 / DK / NIDDK NIH HHS / United States MR/S003746/1 / MRC_ / Medical Research Council / United Kingdom MR/K007017/1 / MRC_ / Medical Research Council / United Kingdom U01 DK078616 / DK / NIDDK NIH HHS / United States G0601261 / MRC_ / Medical Research Council / United Kingdom P30 DK020572 / DK / NIDDK NIH HHS / United States P30 DK116074 / DK / NIDDK NIH HHS / United States P20 GM121334 / GM / NIGMS NIH HHS / United States U54 GM115428 / GM / NIGMS NIH HHS / United States R01 DK093757 / DK / NIDDK NIH HHS / United States R01 DK078616 / DK / NIDDK NIH HHS / United States MR/K023241/1 / MRC_ / Medical Research Council / United Kingdom U01 DK085545 / DK / NIDDK NIH HHS / United States RG/13/13/30194 / BHF_ / British Heart Foundation / United Kingdom MR/M501633/1 / MRC_ / Medical Research Council / United Kingdom G0601463 / MRC_ / Medical Research Council / United Kingdom U01 HL130114 / HL / NHLBI NIH HHS / United States R01 DK098032 / DK / NIDDK NIH HHS / United States MC_UU_12015/1 / MRC_ / Medical Research Council / United Kingdom R01 DK072193 / DK / NIDDK NIH HHS / United States R00 HL130580 / HL / NHLBI NIH HHS / United States R01 HL119443 / HL / NHLBI NIH HHS / United States U01 DK105535 / DK / NIDDK NIH HHS / United States R01 DK062370 / DK / NIDDK NIH HHS / United States R01 HL105756 / HL / NHLBI NIH HHS / United States K24 DK080140 / DK / NIDDK NIH HHS / United States RG/14/5/30893 / BHF_ / British Heart Foundation / United Kingdom MC_UU_00007/10 / MRC_ / Medical Research Council / United Kingdom U01 DK062370 / DK / NIDDK NIH HHS / United States UL1 TR001881 / TR / NCATS NIH HHS / United States T32 HL007055 / HL / NHLBI NIH HHS / United States |
Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.
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