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A genome-wide association study identifies LIPA as a susceptibility gene for coronary artery disease.

ABSTRACT: BACKGROUND:eQTL analyses are important to improve the understanding of genetic association results. We performed a genome-wide association and global gene expression study to identify functionally relevant variants affecting the risk of coronary artery disease (CAD). METHODS AND RESULTS:In a genome-wide association analysis of 2078 CAD cases and 2953 control subjects, we identified 950 single-nucleotide polymorphisms (SNPs) that were associated with CAD at P<10(-3). Subsequent in silico and wet-laboratory replication stages and a final meta-analysis of 21 428 CAD cases and 38 361 control subjects revealed a novel association signal at chromosome 10q23.31 within the LIPA (lysosomal acid lipase A) gene (P=3.7×10(-8); odds ratio, 1.1; 95% confidence interval, 1.07 to 1.14). The association of this locus with global gene expression was assessed by genome-wide expression analyses in the monocyte transcriptome of 1494 individuals. The results showed a strong association of this locus with expression of the LIPA transcript (P=1.3×10(-96)). An assessment of LIPA SNPs and transcript with cardiovascular phenotypes revealed an association of LIPA transcript levels with impaired endothelial function (P=4.4×10(-3)). CONCLUSIONS:The use of data on genetic variants and the addition of data on global monocytic gene expression led to the identification of the novel functional CAD susceptibility locus LIPA, located on chromosome 10q23.31. The respective eSNPs associated with CAD strongly affect LIPA gene expression level, which was related to endothelial dysfunction, a precursor of CAD.

SUBMITTER: Wild PS

PROVIDER: S-EPMC3157552 | biostudies-literature | 2011 Aug

REPOSITORIES: biostudies-literature

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A genome-wide association study identifies LIPA as a susceptibility gene for coronary artery disease.

Wild Philipp S PS Zeller Tanja T Schillert Arne A Szymczak Silke S Sinning Christoph R CR Deiseroth Arne A Schnabel Renate B RB Lubos Edith E Keller Till T Eleftheriadis Medea S MS Bickel Christoph C Rupprecht Hans J HJ Wilde Sandra S Rossmann Heidi H Diemert Patrick P Cupples L Adrienne LA Perret Claire C Erdmann Jeanette J Stark Klaus K Kleber Marcus E ME Epstein Stephen E SE Voight Benjamin F BF Kuulasmaa Kari K Li Mingyao M Schäfer Arne S AS Klopp Norman N Braund Peter S PS Sager Hendrik B HB Demissie Serkalem S Proust Carole C König Inke R IR Wichmann Heinz-Erich HE Reinhard Wibke W Hoffmann Michael M MM Virtamo Jarmo J Burnett Mary Susan MS Siscovick David D Wiklund Per Gunnar PG Qu Liming L El Mokthari Nour Eddine NE Thompson John R JR Peters Annette A Smith Albert V AV Yon Emmanuelle E Baumert Jens J Hengstenberg Christian C März Winfried W Amouyel Philippe P Devaney Joseph J Schwartz Stephen M SM Saarela Olli O Mehta Nehal N NN Rubin Diana D Silander Kaisa K Hall Alistair S AS Ferrieres Jean J Harris Tamara B TB Melander Olle O Kee Frank F Hakonarson Hakon H Schrezenmeir Juergen J Gudnason Vilmundur V Elosua Roberto R Arveiler Dominique D Evans Alun A Rader Daniel J DJ Illig Thomas T Schreiber Stefan S Bis Joshua C JC Altshuler David D Kavousi Maryam M Witteman Jaqueline C M JC Uitterlinden Andre G AG Hofman Albert A Folsom Aaron R AR Barbalic Maja M Boerwinkle Eric E Kathiresan Sekar S Reilly Muredach P MP O'Donnell Christopher J CJ Samani Nilesh J NJ Schunkert Heribert H Cambien Francois F Lackner Karl J KJ Tiret Laurence L Salomaa Veikko V Munzel Thomas T Ziegler Andreas A Blankenberg Stefan S

Circulation. Cardiovascular genetics 20110523 4

<h4>Background</h4>eQTL analyses are important to improve the understanding of genetic association results. We performed a genome-wide association and global gene expression study to identify functionally relevant variants affecting the risk of coronary artery disease (CAD).<h4>Methods and results</h4>In a genome-wide association analysis of 2078 CAD cases and 2953 control subjects, we identified 950 single-nucleotide polymorphisms (SNPs) that were associated with CAD at P<10(-3). Subsequent in ...[more]

PMID: 21606135

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Project description:BACKGROUND:Recent genome-wide association studies (GWAS) have identified several novel loci that reproducibly associate with coronary artery disease (CAD) and/or myocardial infarction risk. However, known common CAD risk variants explain only 10% of the predicted genetic heritability of the disease, suggesting that important genetic signals remain to be discovered. METHODS AND RESULTS:We performed a discovery meta-analysis of 5 GWAS involving 13 949 subjects (7123 cases, 6826 control subjects) imputed at approximately 5 million single nucleotide polymorphisms, using pilot 1000 Genomes-based haplotypes. Promising loci were followed up in an additional 5 studies with 11 032 subjects (5211 cases, 5821 control subjects). A novel CAD locus on chromosome 6p21.3 in the major histocompatibility complex (MHC) between HCG27 and HLA-C was identified and achieved genome-wide significance in the combined analysis (rs3869109; p(discovery)=3.3×10(-7), p(replication)=5.3×10(-4)p(combined)=1.12×10(-9)). A subanalysis combining discovery GWAS showed an attenuation of significance when stringent corrections for European population structure were used (P=4.1×10(-10) versus 3.2×10(-7)), suggesting that the observed signal is partly confounded due to population stratification. This gene dense region plays an important role in inflammation, immunity, and self-cell recognition. To determine whether the underlying association was driven by MHC class I alleles, we statistically imputed common HLA alleles into the discovery subjects; however, no single common HLA type contributed significantly or fully explained the observed association. CONCLUSIONS:We have identified a novel locus in the MHC associated with CAD. MHC genes regulate inflammation and T-cell responses that contribute importantly to the initiation and propagation of atherosclerosis. Further laboratory studies will be required to understand the biological basis of this association and identify the causative allele(s).

Project description:Coronary artery disease (CAD), one of the leading causes of death globally, is influenced by both environmental and genetic risk factors. Gene-centric genome-wide association studies (GWAS) involving cases and controls have been remarkably successful in identifying genetic loci contributing to CAD. Modern in silico platforms, such as candidate gene prediction tools, permit a systematic analysis of GWAS data to identify candidate genes for complex diseases like CAD. Subsequent integration of drug-target data from drug databases with the predicted candidate genes can potentially identify novel therapeutics suitable for repositioning towards treatment of CAD.Previously, we were able to predict 264 candidate genes and 104 potential therapeutic targets for CAD using Gentrepid (http://www.gentrepid.org), a candidate gene prediction platform with two bioinformatic modules to reanalyze Wellcome Trust Case-Control Consortium GWAS data. In an expanded study, using five bioinformatic modules on the same data, Gentrepid predicted 647 candidate genes and successfully replicated 55% of the candidate genes identified by the more powerful CARDIoGRAMplusC4D consortium meta-analysis. Hence, Gentrepid was capable of enhancing lower quality genotype-phenotype data, using an independent knowledgebase of existing biological data. Here, we used our methodology to integrate drug data from three drug databases: the Therapeutic Target Database, PharmGKB and Drug Bank, with the 647 candidate gene predictions from Gentrepid. We utilized known CAD targets, the scientific literature, existing drug data and the CARDIoGRAMplusC4D meta-analysis study as benchmarks to validate Gentrepid predictions for CAD.Our analysis identified a total of 184 predicted candidate genes as novel therapeutic targets for CAD, and 981 novel therapeutics feasible for repositioning in clinical trials towards treatment of CAD. The benchmarks based on known CAD targets and the scientific literature showed that our results were significant (p < 0.05).We have demonstrated that available drugs may potentially be repositioned as novel therapeutics for the treatment of CAD. Drug repositioning can save valuable time and money spent on preclinical and phase I clinical studies.

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A genome-wide association study identifies LIPA as a susceptibility gene for coronary artery disease.

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A genome-wide association study identifies LIPA as a susceptibility gene for coronary artery disease.

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