DATA ACCESS WITH REGARDS TO EXOME-WIDE ASSOCIATION ANALYSIS OF CORONARY ARTERY DISEASE IN THE KINGDOM OF SAUDI ARABIA POPULATION
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PROVIDER: EGAC00001000420 | EGA |
REPOSITORIES: EGA
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Project description:Coronary Artery Disease (CAD) remains the leading cause of mortality worldwide. Mortality rates associated with CAD have shown an exceptional increase particularly in fast developing economies like the Kingdom of Saudi Arabia (KSA). Over the past twenty years, CAD has become the leading cause of death in KSA and has reached epidemic proportions. This rise is undoubtedly caused by fast urbanization that is associated with a life-style that promotes CAD. However, the question remains whether genetics play a significant role and whether genetic susceptibility is increased in KSA compared to the well-studied Western European populations. Therefore, we performed an Exome-wide association study (EWAS) in 832 patients and 1,076 controls of Saudi Arabian origin to test whether population specific, strong genetic risk factors for CAD exist, or whether the polygenic risk score for known genetic risk factors for CAD, lipids, and Type 2 Diabetes show evidence for an enriched genetic burden. Our results do not show significant associations for a single genetic locus. However, the heritability estimate for CAD for this population was high (h(2) = 0.53, S.E. = 0.1, p = 4e(-12)) and we observed a significant association of the polygenic risk score for CAD that demonstrates that the population of KSA, at least in part, shares the genetic risk associated to CAD in Western populations.
| S-EPMC4744043 | biostudies-literature
Project description:Coronary Artery Disease (CAD) remains the leading cause of mortality worldwide. Mortality rates associated with CAD have shown an exceptional increase particularly in fast developing economies like the Kingdom of Saudi Arabia (KSA). Over the past twenty years, CAD has become the leading cause of death in KSA and has reached epidemic proportions. This rise is undoubtedly caused by fast urbanization that is associated with a life-style that promotes CAD. However, the question remains whether genetics play a significant role and whether genetic susceptibility is increased in KSA compared to the well-studied Western European populations. Therefore, we performed an Exome-wide association study (EWAS) in 832 patients and 1,076 controls of Saudi Arabian origin to test whether population specific, strong genetic risk factors for CAD exist, or whether the polygenic risk score for known genetic risk factors for CAD, lipids, and Type 2 Diabetes show evidence for an enriched genetic burden. Our results do not show significant associations for a single genetic locus. However, the heritability estimate for CAD for this population was high (h2 = 0.53, S.E. = 0.1, p = 4e-12) and we observed a significant association of the polygenic risk score for CAD that demonstrates that the population of KSA, at least in part, shares the genetic risk associated to CAD in Western populations.
| EGAS00001001645 | EGA
Project description:Coronary artery disease (CAD) and cerebral infarction (CI) remain major causes of morbidity and mortality in humans. Recent genome-wide association studies have identified various genetic variants associated with these diseases. However, these studies were commonly conducted in a cross-sectional manner. Therefore, the present research performed longitudinal exome-wide association studies for CAD and CI using data on ~244,000 genotyped variants and the clinical data of 6,026 Japanese individuals who had attended annual health checkups for several years (mean followed-up period, 5±3 years). Following quality controls, the significance [false discovery rate (FDR) of <0.05] of association of the diseases with 24,651 single nucleotide polymorphisms (SNPs) in 5,989 individuals for three inheritance models was tested using the generalized estimating equation model. SNPs that reached statistical significance were further screened against a threshold of approxdf (a scale of small effective sample size) of >30. The longitudinal exome-wide association studies revealed that three SNPs [rs4606855 of ADGRE3 (P=2.5×10-6; FDR=0.031; approxdf=71), rs3746414 of ZFP64 (P=5.9×10-6; FDR=0.048; approxdf=93) and rs7132908 of FAIM2 (P<2.0×10-16; FDR<4.9×10-12; approxdf=65)] were significantly associated with the prevalence of CAD. A different set of three SNPs [rs6580741 of FAM186A (P<2.0×10-16; FDR<4.9×10-12; approxdf=48), rs1324015 of LINC00400 (P<2.0×10-16; FDR<4.9×10-12; approxdf=49) and rs884205 of TNFRSF11A (P<2.0×10-16; FDR<4.9×10-12; approxdf=32)] was significantly associated with CI. The comparison of disease incidence with these SNPs demonstrated that all the minor alleles were associated with decreased susceptibility to CAD or CI. In conclusion, six novel SNPs were identified as susceptibility loci for CAD (rs4606855 of ADGRE3, rs3746414 of ZFP64, and rs7132908 of FAIM2) or CI (rs6580741 of FAM186A, rs1324015 of LINC00400, and rs884205 of TNFRSF11A).
| S-EPMC6020445 | biostudies-literature
Project description:Coronary artery disease (CAD) is a multifactorial disease with environmental and genetic determinants. The genetic determinants of CAD have previously been explored by the candidate gene approach. Recently, the data from the International HapMap Project and the development of dense genotyping chips have enabled us to perform genome-wide association studies (GWAS) on a large number of subjects without bias towards any particular candidate genes. In 2007, three chip-based GWAS simultaneously revealed the significant association between common variants on chromosome 9p21 and CAD. This association was replicated among other ethnic groups and also in a meta-analysis. Further investigations have detected several other candidate loci associated with CAD. The chip-based GWAS approach has identified novel and unbiased genetic determinants of CAD and these insights provide the important direction to better understand the pathogenesis of CAD and to develop new and improved preventive measures and treatments for CAD.
| S-EPMC2958466 | biostudies-literature
Project description:Genome-wide association studies (GWAS) of coronary artery disease (CAD) have revealed multiple genetic risk loci. We assessed the association of 47 genome-wide significant single-nucleotide polymorphisms (SNPs) at 43 CAD loci with coronary stenosis in a Pakistani sample comprising 663 clinically ascertained and angiographically confirmed cases. Genotypes were determined using the iPLEX Gold technology. All statistical analyses were performed using R software. Linkage disequilibrium (LD) between significant SNPs was determined using SNAP web portal, and functional annotation of SNPs was performed using the RegulomeDB and Genotype-Tissue Expression (GTEx) databases. Genotyping comparison was made between cases with severe stenosis (≥70%) and mild/minimal stenosis (<30%). Five SNPs demonstrated significant associations: three with additive genetic models PLG/rs4252120 (p = 0.0078), KIAA1462/rs2505083 (p = 0.005), and SLC22A3/rs2048327 (p = 0.045) and two with recessive models SORT1/rs602633 (p = 0.005) and UBE2Z/rs46522 (p = 0.03). PLG/rs4252120 was in LD with two functional PLG variants (rs4252126 and rs4252135), each with a RegulomeDB score of 1f. Likewise, KIAA1462/rs2505083 was in LD with a functional SNP, KIAA1462/rs3739998, having a RegulomeDB score of 2b. In the GTEx database, KIAA1462/rs2505083, SLC22A3/rs2048327, SORT1/rs602633, and UBE2Z/rs46522 SNPs were found to be expression quantitative trait loci (eQTLs) in CAD-associated tissues. In conclusion, five genome-wide significant SNPs previously reported in European GWAS were replicated in the Pakistani sample. Further association studies on larger non-European populations are needed to understand the worldwide genetic architecture of CAD.
| S-EPMC7336215 | biostudies-literature
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.
| S-EPMC4460746 | biostudies-other
Project description:BACKGROUND:Modern genotyping platforms permit a systematic search for inherited components of complex diseases. We performed a joint analysis of two genomewide association studies of coronary artery disease. METHODS:We first identified chromosomal loci that were strongly associated with coronary artery disease in the Wellcome Trust Case Control Consortium (WTCCC) study (which involved 1926 case subjects with coronary artery disease and 2938 controls) and looked for replication in the German MI [Myocardial Infarction] Family Study (which involved 875 case subjects with myocardial infarction and 1644 controls). Data on other single-nucleotide polymorphisms (SNPs) that were significantly associated with coronary artery disease in either study (P<0.001) were then combined to identify additional loci with a high probability of true association. Genotyping in both studies was performed with the use of the GeneChip Human Mapping 500K Array Set (Affymetrix). RESULTS:Of thousands of chromosomal loci studied, the same locus had the strongest association with coronary artery disease in both the WTCCC and the German studies: chromosome 9p21.3 (SNP, rs1333049) (P=1.80x10(-14) and P=3.40x10(-6), respectively). Overall, the WTCCC study revealed nine loci that were strongly associated with coronary artery disease (P<1.2x10(-5) and less than a 50% chance of being falsely positive). In addition to chromosome 9p21.3, two of these loci were successfully replicated (adjusted P<0.05) in the German study: chromosome 6q25.1 (rs6922269) and chromosome 2q36.3 (rs2943634). The combined analysis of the two studies identified four additional loci significantly associated with coronary artery disease (P<1.3x10(-6)) and a high probability (>80%) of a true association: chromosomes 1p13.3 (rs599839), 1q41 (rs17465637), 10q11.21 (rs501120), and 15q22.33 (rs17228212). CONCLUSIONS:We identified several genetic loci that, individually and in aggregate, substantially affect the risk of development of coronary artery disease.
| S-EPMC2719290 | biostudies-literature
Project description:Many cardiovascular diseases are facilitated by strong inheritance. For example, large-scale genetic studies identified hundreds of genomic loci that affect the risk of coronary artery disease. At each of these loci, common variants are associated with disease risk with robust statistical evidence but individually small effect sizes. Only a minority of candidate genes found at these loci are involved in the pathophysiology of traditional risk factors, but experimental research is making progress in identifying novel, and, in part, unexpected mechanisms. Targets identified by genome-wide association studies have already led to the development of novel treatments, specifically in lipid metabolism. This review summarizes recent genetic and experimental findings in this field. In addition, the development and possible clinical usefulness of polygenic risk scores in risk prediction and individualization of treatment, particularly in lipid metabolism, are discussed.
| S-EPMC8326228 | biostudies-literature
Project description:Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of ∼185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 million low-frequency (0.005 < MAF < 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.
| S-EPMC4589895 | biostudies-literature
Project description:MIGen Exome Sequencing: Precocious Coronary Artery Disease
| PRJNA278097 | ENA