Coronary Artery Disease Genetics Enlightened by Genome-Wide Association Studies.
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ABSTRACT:
SUBMITTER: Kessler T
PROVIDER: S-EPMC8326228 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:With the advent of the genome-wide association (GWA) study, a promising new avenue for identifying genetic markers for complex diseases like coronary artery disease (CAD) has been opened. This avenue, however, is not without challenges and limitations, including the need for carefully designed and executed studies and the risk of false positive associations. Nonetheless, new markers have been identified through such studies that could potentially revolutionize the ways that individuals with CAD are identified and managed.
| S-EPMC2776326 | biostudies-literature
Project description:Although the importance of inflammation in atherosclerosis is now well established, the exact molecular processes linking inflammation to the development and course of the disease are not sufficiently understood. In this context, modern genetics-as applied by genome-wide association studies (GWAS)-can serve as a comprehensive and unbiased tool for the screening of potentially involved pathways. Indeed, a considerable proportion of loci discovered by GWAS is assumed to affect inflammatory processes. Despite many well-replicated association findings, however, translating genomic hits to specific molecular mechanisms remains challenging. This review provides an overview of the currently most relevant inflammation-related GWAS findings in coronary artery disease and explores their potential clinical perspectives.
| S-EPMC7921935 | 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: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:The heart diseases that account for a large amount of morbidity and mortality in the developed world (coronary artery disease, myocardial infarction and heart failure) are phenotypically heterogeneous disorders. It has been suspected for many years that genetics may have an important role in these diseases and their poor outcome. However, their complex and likely polygenic pathophysiology has confounded clear understanding of the genetic contribution to their etiology. Despite technological progress and great promise associated with genome-wide association studies, to date the results of their application to coronary artery disease, myocardial infarction and heart failure have yielded limited insights into these common diseases. This review discusses the current status of genome-wide association studies as they have been applied to these cohorts. The potential limitations of these studies, as well as potential future directions for identifying important genes are also discussed.
| S-EPMC3428120 | biostudies-literature
Project description:Genome-wide association studies have led to the discovery of many single nucleotide polymorphisms (SNPs) associated with coronary artery disease (CAD). However, many of these SNPs are in between genes (intergenic), and presumably function through the regulation of gene expression. Microarrays that measure the expression of thousands of mRNAs have allowed investigators to study how genetic variation alters gene expression at a genome-wide level. Combining these methods has led to progress in understanding the molecular basis for the genetic susceptibility to atherosclerosis.Recent studies confirm that gene expression differences due to genetic variation play an underlying role in atherosclerosis. Expression levels of SORT1 are negatively correlated with an intergenic risk allele on chromosome 1p13.3 that was previously associated with CAD. Increased SORT1 expression leads to lower hepatic secretion of low-density lipoprotein (LDL), providing a mechanistic link between a common risk variant and disease. In addition, three out of 13 newly identified CAD risk loci were found to strongly affect the expression of nearby genes. Another recent study detected variants adjacent to a newly identified atherosclerosis risk locus on chromosome 11q22 that were associated with the expression of platelet-derived growth factor D (PDGFD).Cataloging the genetics of gene expression provides a small but crucial molecular link between genetics and clinical phenotypes such as atherosclerosis. Thus, gene expression is an endophenotype that can lead to the discovery of the underlying genes responsible for increasing atherosclerosis risk and potential diagnostic and therapeutic targets.
| S-EPMC3332306 | biostudies-literature
Project description:A new understanding of the genetic basis of coronary artery disease (CAD) has recently emerged from genome-wide association (GWA) studies of common single-nucleotide polymorphisms (SNPs), thus far performed mostly in European-descent populations. To identify novel susceptibility gene variants for CAD and confirm those previously identified mostly in populations of European descent, a multistage GWA study was performed in the Japanese. In the discovery phase, we first genotyped 806 cases and 1337 controls with 451?382 SNP markers and subsequently assessed 34 selected SNPs with direct genotyping (541 additional cases) and in silico comparison (964 healthy controls). In the replication phase, involving 3052 cases and 6335 controls, 12 SNPs were tested; CAD association was replicated and/or verified for 4 (of 12) SNPs from 3 loci: near BRAP and ALDH2 on 12q24 (P=1.6 × 10(-34)), HLA-DQB1 on 6p21 (P=4.7 × 10(-7)), and CDKN2A/B on 9p21 (P=6.1 × 10(-16)). On 12q24, we identified the strongest association signal with the strength of association substantially pronounced for a subgroup of myocardial infarction cases (P=1.4 × 10(-40)). On 6p21, an HLA allele, DQB1(*)0604, could show one of the most prominent association signals in an ?8-Mb interval that encompasses the LTA gene, where an association with myocardial infarction had been reported in another Japanese study. CAD association was also identified at CDKN2A/B, as previously reported in different populations of European descent and Asians. Thus, three loci confirmed in the Japanese GWA study highlight the likely presence of risk alleles with two types of genetic effects - population specific and common - on susceptibility to CAD.
| S-EPMC3283177 | biostudies-literature
Project description:Genome-wide association studies have identified multiple genetic variants affecting the risk of coronary artery disease (CAD). However, individually these explain only a small fraction of the heritability of CAD and for most, the causal biological mechanisms remain unclear. We sought to obtain further insights into potential causal processes of CAD by integrating large-scale GWA data with expertly curated databases of core human pathways and functional networks.Using pathways (gene sets) from Reactome, we carried out a 2-stage gene set enrichment analysis strategy. From a meta-analyzed discovery cohort of 7 CAD genome-wide association study data sets (9889 cases/11?089 controls), nominally significant gene sets were tested for replication in a meta-analysis of 9 additional studies (15?502 cases/55?730 controls) from the Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) Consortium. A total of 32 of 639 Reactome pathways tested showed convincing association with CAD (replication P<0.05). These pathways resided in 9 of 21 core biological processes represented in Reactome, and included pathways relevant to extracellular matrix (ECM) integrity, innate immunity, axon guidance, and signaling by PDRF (platelet-derived growth factor), NOTCH, and the transforming growth factor-?/SMAD receptor complex. Many of these pathways had strengths of association comparable to those observed in lipid transport pathways. Network analysis of unique genes within the replicated pathways further revealed several interconnected functional and topologically interacting modules representing novel associations (eg, semaphoring-regulated axonal guidance pathway) besides confirming known processes (lipid metabolism). The connectivity in the observed networks was statistically significant compared with random networks (P<0.001). Network centrality analysis (degree and betweenness) further identified genes (eg, NCAM1, FYN, FURIN, etc) likely to play critical roles in the maintenance and functioning of several of the replicated pathways.These findings provide novel insights into how genetic variation, interpreted in the context of biological processes and functional interactions among genes, may help define the genetic architecture of CAD.
| S-EPMC4841833 | biostudies-literature
Project description:AIMS:To evaluate the associations of emergent genome-wide-association study-derived coronary heart disease (CHD)-associated single nucleotide polymorphisms (SNPs) with established and emerging risk factors, and the association of genome-wide-association study-derived lipid-associated SNPs with other risk factors and CHD events. METHODS AND RESULTS:Using two case-control studies, three cross-sectional, and seven prospective studies with up to 25 000 individuals and 5794 CHD events we evaluated associations of 34 genome-wide-association study-identified SNPs with CHD risk and 16 CHD-associated risk factors or biomarkers. The Ch9p21 SNPs rs1333049 (OR 1.17; 95% confidence limits 1.11-1.24) and rs10757274 (OR 1.17; 1.09-1.26), MIA3 rs17465637 (OR 1.10; 1.04-1.15), Ch2q36 rs2943634 (OR 1.08; 1.03-1.14), APC rs383830 (OR 1.10; 1.02, 1.18), MTHFD1L rs6922269 (OR 1.10; 1.03, 1.16), CXCL12 rs501120 (OR 1.12; 1.04, 1.20), and SMAD3 rs17228212 (OR 1.11; 1.05, 1.17) were all associated with CHD risk, but not with the CHD biomarkers and risk factors measured. Among the 20 blood lipid-related SNPs, LPL rs17411031 was associated with a lower risk of CHD (OR 0.91; 0.84-0.97), an increase in Apolipoprotein AI and HDL-cholesterol, and reduced triglycerides. SORT1 rs599839 was associated with CHD risk (OR 1.20; 1.15-1.26) as well as total- and LDL-cholesterol, and apolipoprotein B. ANGPTL3 rs12042319 was associated with CHD risk (OR 1.11; 1.03, 1.19), total- and LDL-cholesterol, triglycerides, and interleukin-6. CONCLUSION:Several SNPs predicting CHD events appear to involve pathways not currently indexed by the established or emerging risk factors; others involved changes in blood lipids including triglycerides or HDL-cholesterol as well as LDL-cholesterol. The overlapping association of SNPs with multiple risk factors and biomarkers supports the existence of shared points of regulation for these phenotypes.
| S-EPMC3270041 | 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