Impact of Type 2 Diabetes Susceptibility Variants on Quantitative Glycemic Traits Reveals Mechanistic Heterogeneity

被引：241

作者：

Dimas, Antigone S. ^{[1
,2
]}

Lagou, Vasiliki ^{[1
,3
]}

Barker, Adam ^{[4
]}

Knowles, Joshua W. ^{[5
,6
]}

Maegi, Reedik ^{[1
,3
,7
]}

Hivert, Marie-France ^{[8
,9
]}

Benazzo, Andrea ^{[10
]}

Rybin, Denis ^{[11
]}

Jackson, Anne U. ^{[12
,13
]}

Stringham, Heather M. ^{[12
,13
]}

Song, Ci ^{[14
,15
]}

Fischer-Rosinsky, Antje ^{[16
]}

Boesgaard, Trine Wellov ^{[17
]}

Grarup, Niels ^{[18
]}

Abbasi, Fahim A. ^{[5
,6
]}

Assimes, Themistocles L. ^{[5
,6
]}

Hao, Ke ^{[19
]}

Yang, Xia ^{[20
]}

Lecoeur, Cecile ^{[21
]}

Barroso, Ines ^{[22
,23
,24
]}

Bonnycastle, Lori L. ^{[25
]}

Boettcher, Yvonne ^{[26
]}

Bumpstead, Suzannah ^{[22
]}

Chines, Peter S. ^{[25
]}

Erdos, Michael R. ^{[25
]}

Graessler, Jurgen ^{[27
]}

Kovacs, Peter ^{[28
]}

Morken, Mario A. ^{[25
]}

Narisu, Narisu ^{[25
]}

Payne, Felicity ^{[22
]}

Stancakova, Alena ^{[29
,30
]}

Swift, Amy J. ^{[25
]}

Toenjes, Anke ^{[26
,31
]}

Bornstein, Stefan R. ^{[27
]}

Cauchi, Stephane ^{[21
]}

Froguel, Philippe ^{[21
,32
]}

Meyre, David ^{[21
,33
]}

Schwarz, Peter E. H. ^{[27
]}

Haering, Hans-Ulrich ^{[34
]}

Smith, Ulf ^{[35
]}

Boehnke, Michael ^{[12
,13
]}

Bergman, Richard N. ^{[36
]}

Collins, Francis S. ^{[25
]}

Mohlke, Karen L. ^{[37
]}

Tuomilehto, Jaakko ^{[38
,39
,40
]}

Quertemous, Thomas ^{[5
,6
]}

Lind, Lars ^{[41
]}

Hansen, Torben ^{[18
,42
]}

Pedersen, Oluf ^{[18
,43
,44
,45
]}

Walker, Mark ^{[46
]}

机构：

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

[2] Biomed Sci Res Ctr, Athens, Greece

[3] Univ Oxford, Oxford Ctr Diabet Endocrinol & Metab, Oxford, England

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

[5] Stanford Univ, Sch Med, Dept Med, Stanford, CA 94305 USA

[6] Stanford Univ, Sch Med, Cardiovasc Inst, Stanford, CA 94305 USA

[7] Univ Tartu, Estonian Genome Ctr, EE-50090 Tartu, Estonia

[8] Univ Sherbrooke, Dept Med, Sherbrooke, PQ J1K 2R1, Canada

[9] Massachusetts Gen Hosp, Div Gen Med, Boston, MA 02114 USA

[10] Univ Ferrara, Dept Biol & Evolut, I-44100 Ferrara, Italy

[11] Boston Univ, Data Coordinating Ctr, Boston, MA 02215 USA

[12] Univ Michigan, Sch Publ Hlth, Dept Biostat, Ann Arbor, MI 48109 USA

[13] Univ Michigan, Sch Publ Hlth, Ctr Stat Genet, Ann Arbor, MI 48109 USA

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

[15] Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden

[16] Charite, Dept Endocrinol & Metab, D-13353 Berlin, Germany

[17] Steno Diabet Ctr, DK-2820 Gentofte, Denmark

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

[19] Mt Sinai Sch Med, Inst Genom & Multiscale Biol, Dept Genet & Genom Sci, New York, NY USA

[20] Univ Calif Los Angeles, Dept Integrat Biol & Physiol, Los Angeles, CA USA

[21] Univ Lille 2, Inst Pasteur, Inst Biol, CNRS,UMR8199, Lille, France

[22] Wellcome Trust Sanger Inst, Hinxton, England

[23] Univ Cambridge, Metab Res Labs, Cambridge, England

[24] Addenbrookes Hosp, Natl Inst Hlth Res, Cambridge Biomed Res Ctr, Inst Metab Sci, Cambridge, England

[25] NHGRI, Genome Technol Branch, Bethesda, MD 20892 USA

[26] Univ Leipzig, Med Ctr, IFB AdiposityDis, D-04109 Leipzig, Germany

[27] Univ Dresden, Div Prevent & Care Diabet, Dept Med 3, Dresden, Germany

[28] Interdisciplinary Ctr Clin Res Leipzig, Leipzig, Germany

[29] Univ Eastern Finland, Dept Med, Kuopio, Finland

[30] Kuopio Univ Hosp, SF-70210 Kuopio, Finland

[31] Univ Leipzig, Dept Med, D-04109 Leipzig, Germany

[32] Univ London Imperial Coll Sci Technol & Med, Dept Genom Common Dis, London, England

[33] McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON, Canada

[34] Univ Tubingen, Dept Internal Med, Div Endocrinol Diabetol Vasc Med Nephrol & Clin C, Tubingen, Germany

[35] Univ Gothenburg, Sahlgrenska Acad, Dept Mol & Clin Med, Lundberg Lab Diabet Res,Ctr Excellence Metab & Ca, Gothenburg, Sweden

[36] Univ So Calif, Keck Sch Med, Dept Physiol & Biophys, Los Angeles, CA 90033 USA

[37] Univ N Carolina, Dept Genet, Chapel Hill, NC USA

[38] Natl Inst Hlth & Welf, Diabet Prevent Unit, Helsinki, Finland

[39] Danube Univ Krems, Ctr Vasc Prevent, Krems, Austria

[40] King Abdulaziz Univ, Jeddah 21413, Saudi Arabia

[41] Uppsala Univ, Akad Sjukhuset, Dept Med Sci, Uppsala, Sweden

[42] Univ Southern Denmark, Fac Hlth Sci, Odense, Denmark

[43] Hagedorn Res Inst, Copenhagen, Denmark

[44] Univ Copenhagen, Fac Hlth Sci, Inst Biomed Sci, Copenhagen, Denmark

[45] Univ Aarhus, Fac Hlth Sci, Aarhus, Denmark

[46] Newcastle Univ, Inst Cellular Med, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England

[47] German Inst Human Nutr, Dept Clin Nutr, Nuthetal, Germany

[48] Harvard Univ, Sch Med, Dept Med, Boston, MA USA

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

[50] NHLBI, Framingham Heart Study, Framingham, MA USA

来源：

DIABETES | 2014年 / 63卷 / 06期

基金：

芬兰科学院; 英国惠康基金; 英国医学研究理事会; 瑞典研究理事会;

关键词：

BETA-CELL FUNCTION; BODY-MASS INDEX; PROINSULIN LEVELS; TCF7L2; GENE; INSULIN; ASSOCIATION; GLUCOSE; LOCI; PATHOPHYSIOLOGY; POLYMORPHISMS;

D O I：

10.2337/db13-0949

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

Patients with established type 2 diabetes display both beta-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity. We included data from up to 58,614 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used additive genetic models with adjustment for sex, age, and BMI, followed by fixed-effects, inverse-variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second cluster (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (TCF712, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.

引用

页码：2158 / 2171

页数：14

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