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From Loci to Biology: Functional Genomics of Genome-Wide Association for Coronary Disease.

ABSTRACT: Genome-wide association studies have provided a rich collection of ? 58 coronary artery disease (CAD) loci that suggest the existence of previously unsuspected new biology relevant to atherosclerosis. However, these studies only identify genomic loci associated with CAD, and many questions remain even after a genomic locus is definitively implicated, including the nature of the causal variant(s) and the causal gene(s), as well as the directionality of effect. There are several tools that can be used for investigation of the functional genomics of these loci, and progress has been made on a limited number of novel CAD loci. New biology regarding atherosclerosis and CAD will be learned through the functional genomics of these loci, and the hope is that at least some of these new pathways relevant to CAD pathogenesis will yield new therapeutic targets for the prevention and treatment of CAD.

SUBMITTER: Nurnberg ST

PROVIDER: S-EPMC4863243 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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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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From Loci to Biology: Functional Genomics of Genome-Wide Association for Coronary Disease.

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