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Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci.

ABSTRACT: To identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom ?50,000 SNP genotyping array (the ITMAT-Broad-CARe array) with ?2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17,418 cases and 70,298 controls. First, meta-analysis of 25 studies comprising 14,073 cases and 57,489 controls of European descent confirmed eight established T2D loci at genome-wide significance. In silico follow-up analysis of putative association signals found in independent genome-wide association studies (including 8,130 cases and 38,987 controls) performed by the DIAGRAM consortium identified a T2D locus at genome-wide significance (GATAD2A/CILP2/PBX4; p = 5.7 × 10(-9)) and two loci exceeding study-wide significance (SREBF1, and TH/INS; p < 2.4 × 10(-6)). Second, meta-analyses of 1,986 cases and 7,695 controls from eight African-American studies identified study-wide-significant (p = 2.4 × 10(-7)) variants in HMGA2 and replicated variants in TCF7L2 (p = 5.1 × 10(-15)). Third, conditional analysis revealed multiple known and novel independent signals within five T2D-associated genes in samples of European ancestry and within HMGA2 in African-American samples. Fourth, a multiethnic meta-analysis of all 39 studies identified T2D-associated variants in BCL2 (p = 2.1 × 10(-8)). Finally, a composite genetic score of SNPs from new and established T2D signals was significantly associated with increased risk of diabetes in African-American, Hispanic, and Asian populations. In summary, large-scale meta-analysis involving a dense gene-centric approach has uncovered additional loci and variants that contribute to T2D risk and suggests substantial overlap of T2D association signals across multiple ethnic groups.

SUBMITTER: Saxena R

PROVIDER: S-EPMC3309185 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature

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Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci.

Saxena Richa R Elbers Clara C CC Guo Yiran Y Peter Inga I Gaunt Tom R TR Mega Jessica L JL Lanktree Matthew B MB Tare Archana A Castillo Berta Almoguera BA Li Yun R YR Johnson Toby T Bruinenberg Marcel M Gilbert-Diamond Diane D Rajagopalan Ramakrishnan R Voight Benjamin F BF Balasubramanyam Ashok A Barnard John J Bauer Florianne F Baumert Jens J Bhangale Tushar T Böhm Bernhard O BO Braund Peter S PS Burton Paul R PR Chandrupatla Hareesh R HR Clarke Robert R Cooper-DeHoff Rhonda M RM Crook Errol D ED Davey-Smith George G Day Ian N IN de Boer Anthonius A de Groot Mark C H MC Drenos Fotios F Ferguson Jane J Fox Caroline S CS Furlong Clement E CE Gibson Quince Q Gieger Christian C Gilhuijs-Pederson Lisa A LA Glessner Joseph T JT Goel Anuj A Gong Yan Y Grant Struan F A SF Grobbee Diederick E DE Hastie Claire C Humphries Steve E SE Kim Cecilia E CE Kivimaki Mika M Kleber Marcus M Meisinger Christa C Kumari Meena M Langaee Taimour Y TY Lawlor Debbie A DA Li Mingyao M Lobmeyer Maximilian T MT Maitland-van der Zee Anke-Hilse AH Meijs Matthijs F L MF Molony Cliona M CM Morrow David A DA Murugesan Gurunathan G Musani Solomon K SK Nelson Christopher P CP Newhouse Stephen J SJ O'Connell Jeffery R JR Padmanabhan Sandosh S Palmen Jutta J Patel Sanjey R SR Pepine Carl J CJ Pettinger Mary M Price Thomas S TS Rafelt Suzanne S Ranchalis Jane J Rasheed Asif A Rosenthal Elisabeth E Ruczinski Ingo I Shah Sonia S Shen Haiqing H Silbernagel Günther G Smith Erin N EN Spijkerman Annemieke W M AW Stanton Alice A Steffes Michael W MW Thorand Barbara B Trip Mieke M van der Harst Pim P van der A Daphne L DL van Iperen Erik P A EP van Setten Jessica J van Vliet-Ostaptchouk Jana V JV Verweij Niek N Wolffenbuttel Bruce H R BH Young Taylor T Zafarmand M Hadi MH Zmuda Joseph M JM Boehnke Michael M Altshuler David D McCarthy Mark M Kao W H Linda WH Pankow James S JS Cappola Thomas P TP Sever Peter P Poulter Neil N Caulfield Mark M Dominiczak Anna A Shields Denis C DC Bhatt Deepak L DL Zhang Li L Curtis Sean P SP Danesh John J Casas Juan P JP van der Schouw Yvonne T YT Onland-Moret N Charlotte NC Doevendans Pieter A PA Dorn Gerald W GW Farrall Martin M FitzGerald Garret A GA Hamsten Anders A Hegele Robert R Hingorani Aroon D AD Hofker Marten H MH Huggins Gordon S GS Illig Thomas T Jarvik Gail P GP Johnson Julie A JA Klungel Olaf H OH Knowler William C WC Koenig Wolfgang W März Winfried W Meigs James B JB Melander Olle O Munroe Patricia B PB Mitchell Braxton D BD Bielinski Susan J SJ Rader Daniel J DJ Reilly Muredach P MP Rich Stephen S SS Rotter Jerome I JI Saleheen Danish D Samani Nilesh J NJ Schadt Eric E EE Shuldiner Alan R AR Silverstein Roy R Kottke-Marchant Kandice K Talmud Philippa J PJ Watkins Hugh H Asselbergs Folkert W FW de Bakker Paul I W PI McCaffery Jeanne J Wijmenga Cisca C Sabatine Marc S MS Wilson James G JG Reiner Alex A Bowden Donald W DW Hakonarson Hakon H Siscovick David S DS Keating Brendan J BJ

American journal of human genetics 20120209 3

To identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) with ∼2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17,418 cases and 70,298 controls. First, meta-analysis of 25 studies comprising 14,073 cases and 57,489 controls of European descent confirmed eight established T2D loci at genome-wide significanc ...[more]

PMID: 22325160

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Project description:Coronary artery disease (CAD) has a significant genetic contribution that is incompletely characterized. To complement genome-wide association (GWA) studies, we conducted a large and systematic candidate gene study of CAD susceptibility, including analysis of many uncommon and functional variants. We examined 49,094 genetic variants in ∼2,100 genes of cardiovascular relevance, using a customised gene array in 15,596 CAD cases and 34,992 controls (11,202 cases and 30,733 controls of European descent; 4,394 cases and 4,259 controls of South Asian origin). We attempted to replicate putative novel associations in an additional 17,121 CAD cases and 40,473 controls. Potential mechanisms through which the novel variants could affect CAD risk were explored through association tests with vascular risk factors and gene expression. We confirmed associations of several previously known CAD susceptibility loci (eg, 9p21.3:p<10(-33); LPA:p<10(-19); 1p13.3:p<10(-17)) as well as three recently discovered loci (COL4A1/COL4A2, ZC3HC1, CYP17A1:p<5×10(-7)). However, we found essentially null results for most previously suggested CAD candidate genes. In our replication study of 24 promising common variants, we identified novel associations of variants in or near LIPA, IL5, TRIB1, and ABCG5/ABCG8, with per-allele odds ratios for CAD risk with each of the novel variants ranging from 1.06-1.09. Associations with variants at LIPA, TRIB1, and ABCG5/ABCG8 were supported by gene expression data or effects on lipid levels. Apart from the previously reported variants in LPA, none of the other ∼4,500 low frequency and functional variants showed a strong effect. Associations in South Asians did not differ appreciably from those in Europeans, except for 9p21.3 (per-allele odds ratio: 1.14 versus 1.27 respectively; P for heterogeneity = 0.003). This large-scale gene-centric analysis has identified several novel genes for CAD that relate to diverse biochemical and cellular functions and clarified the literature with regard to many previously suggested genes.

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Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci.

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Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci.

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