Dataset Information

Novel risk genes identified in a genome-wide association study for coronary artery disease in patients with type 1 diabetes.

ABSTRACT: BACKGROUND:Patients with type 1 diabetes are more at risk of coronary artery disease than the general population. Although evidence points to a genetic risk there have been no study investigating genetic risk factors of coronary artery disease specific to individuals with type 1 diabetes. To identify low frequency and common genetic variations associated with coronary artery disease in populations of individuals with type 1 diabetes. METHODS:A two-stage genome wide association study was conducted. The discovery phase involved the meta-analysis of three genome-wide association cohorts totaling 434 patients with type 1 diabetes and coronary artery disease (cases) and 3123 T1D individuals with no evidence of coronary artery disease (controls). Replication of the top association signals (p?

SUBMITTER: Charmet R

PROVIDER: S-EPMC5916834 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Novel risk genes identified in a genome-wide association study for coronary artery disease in patients with type 1 diabetes.

Charmet Romain R Duffy Seamus S Keshavarzi Sareh S Gyorgy Beata B Marre Michel M Rossing Peter P McKnight Amy Jayne AJ Maxwell Alexander P AP Ahluwalia Tarun Veer Singh TVS Paterson Andrew D AD Trégouët David-Alexandre DA Hadjadj Samy S

Cardiovascular diabetology 20180425 1

<h4>Background</h4>Patients with type 1 diabetes are more at risk of coronary artery disease than the general population. Although evidence points to a genetic risk there have been no study investigating genetic risk factors of coronary artery disease specific to individuals with type 1 diabetes. To identify low frequency and common genetic variations associated with coronary artery disease in populations of individuals with type 1 diabetes.<h4>Methods</h4>A two-stage genome wide association stu ...[more]

PMID: 29695241

Similar Datasets

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.

Dataset Information

Novel risk genes identified in a genome-wide association study for coronary artery disease in patients with type 1 diabetes.

Publications

Novel risk genes identified in a genome-wide association study for coronary artery disease in patients with type 1 diabetes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets