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Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci.

ABSTRACT: Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ?50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ?2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.

SUBMITTER: Asselbergs FW

PROVIDER: S-EPMC3487124 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature

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Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci.

Asselbergs Folkert W FW Guo Yiran Y van Iperen Erik P A EP Sivapalaratnam Suthesh S Tragante Vinicius V Lanktree Matthew B MB Lange Leslie A LA Almoguera Berta B Appelman Yolande E YE Barnard John J Baumert Jens J Beitelshees Amber L AL Bhangale Tushar R TR Chen Yii-Der Ida YD Gaunt Tom R TR Gong Yan Y Hopewell Jemma C JC Johnson Toby T Kleber Marcus E ME Langaee Taimour Y TY Li Mingyao M Li Yun R YR Liu Kiang K McDonough Caitrin W CW Meijs Matthijs F L MF Middelberg Rita P S RP Musunuru Kiran K Nelson Christopher P CP O'Connell Jeffery R JR Padmanabhan Sandosh S Pankow James S JS Pankratz Nathan N Rafelt Suzanne S Rajagopalan Ramakrishnan R Romaine Simon P R SP Schork Nicholas J NJ Shaffer Jonathan J Shen Haiqing H Smith Erin N EN Tischfield Sam E SE van der Most Peter J PJ van Vliet-Ostaptchouk Jana V JV Verweij Niek N Volcik Kelly A KA Zhang Li L Bailey Kent R KR Bailey Kristian M KM Bauer Florianne F Boer Jolanda M A JM Braund Peter S PS Burt Amber A Burton Paul R PR Buxbaum Sarah G SG Chen Wei W Cooper-Dehoff Rhonda M RM Cupples L Adrienne LA deJong Jonas S JS Delles Christian C Duggan David D Fornage Myriam M Furlong Clement E CE Glazer Nicole N Gums John G JG Hastie Claire C Holmes Michael V MV Illig Thomas T Kirkland Susan A SA Kivimaki Mika M Klein Ronald R Klein Barbara E BE Kooperberg Charles C Kottke-Marchant Kandice K Kumari Meena M LaCroix Andrea Z AZ Mallela Laya L Murugesan Gurunathan G Ordovas Jose J Ouwehand Willem H WH Post Wendy S WS Saxena Richa R Scharnagl Hubert H Schreiner Pamela J PJ Shah Tina T Shields Denis C DC Shimbo Daichi D Srinivasan Sathanur R SR Stolk Ronald P RP Swerdlow Daniel I DI Taylor Herman A HA Topol Eric J EJ Toskala Elina E van Pelt Joost L JL van Setten Jessica J Yusuf Salim S Whittaker John C JC Zwinderman A H AH Anand Sonia S SS Balmforth Anthony J AJ Berenson Gerald S GS Bezzina Connie R CR Boehm Bernhard O BO Boerwinkle Eric E Casas Juan P JP Caulfield Mark J MJ Clarke Robert R Connell John M JM Cruickshanks Karen J KJ Davidson Karina W KW Day Ian N M IN de Bakker Paul I W PI Doevendans Pieter A PA Dominiczak Anna F AF Hall Alistair S AS Hartman Catharina A CA Hengstenberg Christian C Hillege Hans L HL Hofker Marten H MH Humphries Steve E SE Jarvik Gail P GP Johnson Julie A JA Kaess Bernhard M BM Kathiresan Sekar S Koenig Wolfgang W Lawlor Debbie A DA März Winfried W Melander Olle O Mitchell Braxton D BD Montgomery Grant W GW Munroe Patricia B PB Murray Sarah S SS Newhouse Stephen J SJ Onland-Moret N Charlotte NC Poulter Neil N Psaty Bruce B Redline Susan S Rich Stephen S SS Rotter Jerome I JI Schunkert Heribert H Sever Peter P Shuldiner Alan R AR Silverstein Roy L RL Stanton Alice A Thorand Barbara B Trip Mieke D MD Tsai Michael Y MY van der Harst Pim P van der Schoot Ellen E van der Schouw Yvonne T YT Verschuren W M Monique WM Watkins Hugh H Wilde Arthur A M AA Wolffenbuttel Bruce H R BH Whitfield John B JB Hovingh G Kees GK Ballantyne Christie M CM Wijmenga Cisca C Reilly Muredach P MP Martin Nicholas G NG Wilson James G JG Rader Daniel J DJ Samani Nilesh J NJ Reiner Alex P AP Hegele Robert A RA Kastelein John J P JJ Hingorani Aroon D AD Talmud Philippa J PJ Hakonarson Hakon H Elbers Clara C CC Keating Brendan J BJ Drenos Fotios F

American journal of human genetics 20121011 5

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP g ...[more]

PMID: 23063622

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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 32 studies identifies multiple lipid loci.

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Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci.

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