Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

被引：285

作者：

Mahajan, Anubha ^{[1
]}

Wessel, Jennifer ^{[2
,3
]}

Willems, Sara M. ^{[4
]}

Zhao, Wei ^{[5
]}

Robertson, Neil R. ^{[1
,6
]}

Chu, Audrey Y. ^{[7
,8
]}

Gan, Wei ^{[1
]}

Kitajima, Hidetoshi ^{[1
]}

Taliun, Daniel ^{[9
,10
]}

Rayner, N. William ^{[1
,6
,11
]}

Guo, Xiuqing ^{[12
]}

Lu, Yingchang ^{[13
]}

Li, Man ^{[14
,15
]}

Jensen, Richard A. ^{[16
,17
,18
]}

Hu, Yao ^{[19
]}

Huo, Shaofeng ^{[19
]}

Lohman, Kurt K. ^{[20
]}

Zhang, Weihua ^{[21
,22
]}

Cook, James P. ^{[23
]}

Prins, Bram Peter ^{[11
]}

Flannick, Jason ^{[24
,25
]}

Grarup, Niels ^{[26
]}

Trubetskoy, Vassily Vladimirovich ^{[9
,10
]}

Kravic, Jasmina ^{[27
]}

Kim, Young Jin ^{[28
]}

Rybin, Denis V. ^{[29
]}

Yaghootkar, Hanieh ^{[30
]}

Mueller-Nurasyid, Martina ^{[32
,33
]}

Meidtner, Karina ^{[34
,35
]}

Li-Gao, Ruifang ^{[36
]}

Varga, Tibor V. ^{[37
]}

Marten, Jonathan ^{[38
]}

Li, Jin ^{[39
]}

Smith, Albert Vernon ^{[40
,41
]}

An, Ping ^{[42
]}

Ligthart, Symen ^{[43
]}

Gustafsson, Stefan ^{[44
]}

Malerba, Giovanni ^{[45
]}

Demirkan, Ayse ^{[43
,46
]}

Tajes, Juan Fernandez ^{[1
]}

Steinthorsdottir, Valgerdur ^{[47
]}

Wuttke, Matthias ^{[48
]}

Lecoeur, Cecile ^{[49
]}

Preuss, Michael ^{[13
]}

Bielak, Lawrence F. ^{[50
]}

Graff, Marielisa ^{[51
]}

Highland, Heather M. ^{[52
]}

Justice, Anne E. ^{[51
]}

Liu, Dajiang J. ^{[53
]}

Marouli, Eirini ^{[54
]}

机构：

[1] Univ Oxford, Nuffield Dept Med, Wellcome Trust Ctr Human Genet, Oxford, England

[2] Indiana Univ, Diabet Translat Res Ctr, Dept Epidemiol, Indianapolis, IN 46204 USA

[3] Indiana Univ, Diabet Translat Res Ctr, Dept Med, Indianapolis, IN 46204 USA

[4] Univ Cambridge, Inst Metab Sci, MRC Epidemiol Unit, Cambridge, England

[5] Univ Penn, Dept Biostat & Epidemiol, Philadelphia, PA 19104 USA

[6] Univ Oxford, Radcliffe Dept Med, Oxford Ctr Diabet Endocrinol & Metab, Oxford, England

[7] Natl Heart Lung & Blood Inst, Framingham Heart Study, Framingham, MA USA

[8] Brigham & Womens Hosp, Dept Med, Div Prevent Med, 75 Francis St, Boston, MA 02115 USA

[9] Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA

[10] Univ Michigan, Ctr Stat Genet, Ann Arbor, MI 48109 USA

[11] Wellcome Trust Sanger Inst, Dept Human Genet, Hinxton, England

[12] Univ Calif Los Angeles, Med Ctr, LABioMed Harbor, Dept Pediat,Inst Translat Genom & Populat Sci, Torrance, CA 90509 USA

[13] Icahn Sch Med Mt Sinai, Charles Bronfman Inst Personalized Med, New York, NY 10029 USA

[14] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol, Baltimore, MD USA

[15] Univ Utah, Sch Med, Dept Internal Med, Div Nephrol & Hypertens, Salt Lake City, UT USA

[16] Univ Washington, Cardiovasc Hlth Res Unit, Dept Med, Seattle, WA 98195 USA

[17] Univ Washington, Cardiovasc Hlth Res Unit, Dept Epidemiol, Seattle, WA 98195 USA

[18] Univ Washington, Cardiovasc Hlth Res Unit, Dept Hlth Serv, Seattle, WA 98195 USA

[19] Univ Chinese Acad Sci, Chinese Acad Sci, Shanghai Inst Biol Sci, Inst Nutrit Sci, Shanghai, Peoples R China

[20] Wake Forest Univ Hlth Sci, Div Publ Hlth Sci, Dept Biostatist Sci, Winston Salem, NC USA

[21] Imperial Coll London, Dept Epidemiol & Biostat, London, England

[22] London North West Healthcare NHS Trust, Ealing Hosp, Dept Cardiol, London, Middx, England

[23] Univ Liverpool, Dept Biostat, Liverpool, Merseyside, England

[24] Broad Inst, Program Med & Populat Genet, Cambridge, MA USA

[25] Massachusetts Gen Hosp, Dept Mol Biol, Boston, MA 02114 USA

[26] Univ Copenhagen, Fac Hlth & Med Sci, Novo Nordisk Fdn, Ctr Basic Metab Res, Copenhagen, Denmark

[27] Lund Univ, Diabet Ctr, Dept Clin Sci Diabet & Endocrinol, Malmo, Sweden

[28] Korea Natl Inst Hlth, Ctr Genome Sci, Chungcheongbuk Do, South Korea

[29] Boston Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02215 USA

[30] Univ Exeter, Med Sch, Genet Complex Traits, Exeter, Devon, England

[31] Helmholtz Zentrum Munchen German Res Ctr Environm, Inst Genet Epidemiol, Neuherberg, Germany

[32] Ludwig Maximilians Univ Munchen, Univ Hosp Grosshadern, Dept Med 1, Munich, Germany

[33] DZHK German Ctr Cardiovasc Res, Munich Heart Alliance, Partner Site, Munich, Germany

[34] German Inst Human Nutr Potsdam Rehbruecke DIfE, Dept Mol Epidemiol, Nuthetal, Germany

[35] German Ctr Diabet Res DZD, Neuherberg, Germany

[36] Leiden Univ, Med Ctr, Dept Clin Epidemiol, Leiden, Netherlands

[37] Lund Univ, Genet & Mol Epidemiol Unit, Diabet Ctr, Dept Clin Sci, Malmo, Sweden

[38] Univ Edinburgh, Inst Genet & Mol Med, MRC Human Genet Unit, Edinburgh, Midlothian, Scotland

[39] Stanford Univ, Dept Med, Sch Med, Div Cardiovasc Med, Stanford, CA 94305 USA

[40] Iceland Heart Assoc, Kopavogur, Iceland

[41] Univ Iceland, Fac Med, Reykjavik, Iceland

[42] Washington Univ, Sch Med, Dept Genet, Div Stat Genom, St Louis, MO 63110 USA

[43] Erasmus Univ, Med Ctr, Dept Epidemiol, Rotterdam, Netherlands

[44] Uppsala Univ, Dept Med Sci Mol Epidemiol & Sci Life Lab, Uppsala, Sweden

[45] Univ Verona, Dept Neurosci Biomed & Movement Sci, Sect Biol & Genet, Verona, Italy

[46] Leiden Univ, Med Ctr, Dept Human Genet, Leiden, Netherlands

[47] deCODE Genet Amgen Inc, Reykjavik, Iceland

[48] Univ Freiburg, Fac Med, Inst Genet Epidemiol, Med Ctr, Freiburg, Germany

[49] Lille Univ, Lille Pasteur Inst, CNRS, UMR 8199, Lille, France

[50] Univ Michigan, Sch Publ Hlth, Dept Epidemiol, Ann Arbor, MI 48109 USA

来源：

NATURE GENETICS | 2018年 / 50卷 / 04期

关键词：

GENOME-WIDE ASSOCIATION; BODY-MASS INDEX; GENETIC ARCHITECTURE; CONFERS SUSCEPTIBILITY; GENOTYPE IMPUTATION; QUALITY-CONTROL; RARE VARIANTS; LOW-FREQUENCY; METAANALYSIS; RISK;

D O I：

10.1038/s41588-018-0084-1

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

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 x 10(-7)); 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.

引用

页码：559 / +

页数：16

共 25 条

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[25] R230C but not-565C/T variant of the ABCA1 gene is associated with type 2 diabetes in Mexicans through an effect on lowering HDL-cholesterol levels
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