Recent success in the discovery of coronary artery disease genes

2011 ◽  
Vol 89 (8) ◽  
pp. 609-615 ◽  
Author(s):  
Robert Roberts ◽  
Li Chen ◽  
George A. Wells ◽  
Alexandre F.R. Stewart
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Association Studies ◽  
Short Interval ◽  
Minimal Risk ◽  
Genome Wide Association Studies ◽  
Common Diseases ◽  
Multiple Genes ◽  
Increased Risk ◽  
Artery Disease

For more than 50 years, epidemiological studies have indicated that genetic predisposition accounts for approximately 50% of the susceptibility to coronary artery disease (CAD) and its sequelae, including myocardial infarction. Since common diseases such as CAD are caused by multiple genes, the age-old method of linkage analysis used to map monogenic Mendelian disorders in families unfortunately lacks the required sensitivity. The technology to identify genes predisposing individuals to CAD and other common diseases did not become available until 2005. This technology provided computerized arrays containing hundreds of thousands of DNA markers in the form of single-nucleotide polymorphisms (SNPs). This made it possible to pursue an unbiased approach referred to as genome-wide association studies. The first gene for CAD was simultaneously identified by 2 independent groups in 2007. In a very short interval, a total of 23 loci were mapped that were linked to increased risk for CAD. The results of these studies confirm that CAD is caused by multiple genes, each contributing minimal risk. The most exciting and novel findings are that these loci do not act through known risk factors for CAD and that the loci are more likely to be in DNA regions that regulate transcription rather than being in coding regions for protein.

scholarly journals Cis-epistasis at the LPA locus and risk of coronary artery disease

2019 ◽  
Author(s):  
Lingyao Zeng ◽  
Nazanin Mirza-Schreiber ◽  
Claudia Lamina ◽  
Stefan Coassin ◽  
Christopher P. Nelson ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Association Studies ◽  
Arterial Disease ◽  
Genome Wide Association Studies ◽  
Interaction Patterns ◽  
Cardiovascular Risks ◽  
Increased Risk ◽  
Artery Disease ◽  
Cad Risk

AbstractIdentification of epistasis affecting complex human traits has been challenging. Focusing on known coronary artery disease (CAD) risk loci, we explore pairwise statistical interactions between 8,068 SNPs from ten CAD genome-wide association studies (n=30,180). We discovered rs1800769 and rs9458001 in the vicinity of the LPA locus to interact in modulating CAD risk (P=1.75×10−13). Specific genotypes (e.g., rs1800769 CT) displayed either significantly decreased or increased risk for CAD in the context of genotypes of the respective other SNP (e.g., rs9458001 GG vs. AA). In the UK Biobank (n=450,112) significant interaction of this SNP pair was replicated for CAD (P=3.09×10−22), and was also found for aortic valve stenosis (P=6.95×10−7) and peripheral arterial disease (P=2.32×10−4). Identical interaction patterns affected circulating lipoprotein(a) (n=5,953; P=8.7×10−32) and hepatic apolipoprotein(a) (apo(a)) expression (n=522, P=2.6×10−11). We further interrogated potential biological implications of the variants and propose a mechanism explaining epistasis that ultimately may translate to substantial cardiovascular risks.

scholarly journals The SNP rs7865618 of 9p21.3 locus emerges as the most promising marker of coronary artery disease in the southern Indian population

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Gorre Manjula ◽  
Rayabarapu Pranavchand ◽  
Irgam Kumuda ◽  
B. Sriteja Reddy ◽  
Battini Mohan Reddy
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Indian Population ◽  
Interaction Analysis ◽  
Association Studies ◽  
Specific Marker ◽  
Genome Wide Association Studies ◽  
Coronary Syndrome ◽  
Increased Risk ◽  
Artery Disease

AbstractDevelopment of coronary artery disease (CAD) is primarily due to the process of atherosclerosis, however the prognosis of CAD depends on pleiotropic effects of the genes located at 9p21.3 region. Genome wide association studies revealed association of variants in this region with CAD pathology. However, specific marker in predicting CAD development or progression is not yet identified. In the present study, 35 SNPs at 9p21.3 region, located in the cyclin dependent kinase inhibitor (CDKN2A/CDKN2B) genes, were genotyped among 350 CAD cases and 480 controls from the southern Indian population of Hyderabad using fluidigm nanofluidic SNP genotyping system and the data were analyzed using PLINK and R softwares. Of the 35 SNPs analysed, only one SNP, rs7865618, was found to be highly significantly associated with CAD, even after correction for multiple testing (p = 0.008). The AG and GG genotypes of this SNP conferred 3.08 and 1.93 folds increased risk for CAD respectively. In particular, this SNP was significantly associated with severe anatomic (triple vessel disease p = 0.023) and phenotypic (acute coronary syndrome p = 0.007) categories of CAD. Pair wise SNP interaction analysis between the SNPs of 9p21.3 and 11q23.3 regions revealed significantly increased risk of three SNPs of 11q23.3 region that were not associated individually, in conjunction with rs7865618 of 9p21.3.

scholarly journals Association Between Genetic Variation in Blood Pressure and Increased Lifetime Risk of Peripheral Artery Disease

2021 ◽  
Author(s):  
Michael G. Levin ◽  
Derek Klarin ◽  
Venexia M. Walker ◽  
Dipender Gill ◽  
Julie Lynch ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Peripheral Artery Disease ◽  
Pulse Pressure ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Peripheral Artery ◽  
Increased Risk ◽  
Artery Disease

Objective: We aimed to estimate the effect of blood pressure (BP) traits and BP-lowering medications (via genetic proxies) on peripheral artery disease. Approach and Results: Genome-wide association studies summary statistics were obtained for BP, peripheral artery disease (PAD), and coronary artery disease. Causal effects of BP on PAD were estimated by 2-sample Mendelian randomization using a range of pleiotropy-robust methods. Increased systolic BP (SBP), diastolic BP, mean arterial pressure (MAP), and pulse pressure each significantly increased risk of PAD (SBP odds ratio [OR], 1.20 [1.16–1.25] per 10 mm Hg increase, P =1×10 −24 ; diastolic BP OR, 1.27 [1.18–1.35], P =4×10 − 11 ; MAP OR, 1.26 [1.19–1.33], P =6×10 − 16 ; pulse pressure OR, 1.31 [1.24–1.39], P =9×10 − 23 ). The effects of SBP, diastolic BP, and MAP were greater for coronary artery disease than PAD (SBP ratio of Ors, 1.06 [1.0–1.12], P = 0.04; MAP ratio of OR, 1.15 [1.06–1.26], P =8.6×10 − 4 ; diastolic BP ratio of OR, 1.21 [1.08–1.35], P =6.9×10 − 4 ). Considered jointly, both pulse pressure and MAP directly increased risk of PAD (pulse pressure OR, 1.26 [1.17–1.35], P =3×10 − 10 ; MAP OR, 1.14 [1.06–1.23], P =2×10 − 4 ). The effects of antihypertensive medications were estimated using genetic instruments. SBP-lowering via β-blocker (OR, 0.74 per 10 mm Hg decrease in SBP [95% CI, 0.65–0.84]; P =5×10 − 6 ), loop diuretic (OR, 0.66 [0.48–0.91], P =0.01), and thiazide diuretic (OR, 0.57 [0.41–0.79], P =6×10 − 4 ) associated variants were protective of PAD. Conclusions: Higher BP is likely to cause PAD. BP-lowering through β blockers, loop diuretics, and thiazide diuretics (as proxied by genetic variants) was associated with decreased risk of PAD. Future study is needed to clarify the specific mechanisms by which BP influences PAD.

Genetic Interactions Effects of Cardiovascular Disorder Using Computational Models: A Review

2020 ◽  
Vol 9 (3) ◽  
pp. 177-191
Author(s):  
Sridharan Priya ◽  
Radha K. Manavalan
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Cardiovascular Diseases ◽  
Computational Models ◽  
Genetic Interaction ◽  
Association Studies ◽  
Genetic Interactions ◽  
Computational Techniques ◽  
Genome Wide Association Studies ◽  
Artery Disease

Background: The diseases in the heart and blood vessels such as heart attack, Coronary Artery Disease, Myocardial Infarction (MI), High Blood Pressure, and Obesity, are generally referred to as Cardiovascular Diseases (CVD). The risk factors of CVD include gender, age, cholesterol/ LDL, family history, hypertension, smoking, and genetic and environmental factors. Genome- Wide Association Studies (GWAS) focus on identifying the genetic interactions and genetic architectures of CVD. Objective: Genetic interactions or Epistasis infer the interactions between two or more genes where one gene masks the traits of another gene and increases the susceptibility of CVD. To identify the Epistasis relationship through biological or laboratory methods needs an enormous workforce and more cost. Hence, this paper presents the review of various statistical and Machine learning approaches so far proposed to detect genetic interaction effects for the identification of various Cardiovascular diseases such as Coronary Artery Disease (CAD), MI, Hypertension, HDL and Lipid phenotypes data, and Body Mass Index dataset. Conclusion: This study reveals that various computational models identified the candidate genes such as AGT, PAI-1, ACE, PTPN22, MTHR, FAM107B, ZNF107, PON1, PON2, GTF2E1, ADGRB3, and FTO, which play a major role in genetic interactions for the causes of CVDs. The benefits, limitations, and issues of the various computational techniques for the evolution of epistasis responsible for cardiovascular diseases are exhibited.

Characterizing a common CERS2 polymorphism in a mouse model of metabolic disease and in subjects from the Utah CAD Study

2021 ◽  
Author(s):  
Rebekah J Nicholson ◽  
Annelise M Poss ◽  
J Alan Maschek ◽  
James E Cox ◽  
Paul N Hopkins ◽  
...  
Keyword(s):  
Metabolic Disease ◽  
Coronary Artery Disease ◽  
Enzyme Activity ◽  
Coronary Artery ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Loss Of Function ◽  
Serum Samples ◽  
Artery Disease ◽  
Disease Study

Abstract Context Genome-wide association studies have identified associations between a common single nucleotide polymorphism (SNP, rs267738) in CERS2 – a gene that encodes a (dihydro)ceramide synthase involved in the biosynthesis of very-long chain sphingolipids (e.g. C20-C26) – and indices of metabolic dysfunction (e.g. impaired glucose homeostasis). However, the biological consequences of this mutation on enzyme activity and its causal roles in metabolic disease are unresolved. Objective The studies described herein aimed to characterize the effects of rs267738 on CERS2 enzyme activity, sphingolipid profiles, and metabolic outcomes. Design We performed in-depth lipidomic and metabolic characterization of a novel CRISPR knock-in mouse modeling the rs267738 variant. In parallel, we conducted mass spectrometry-based, targeted lipidomics on 567 serum samples collected through the Utah Coronary Artery Disease study, which included 185 patients harboring one (n = 163) or both (n = 22) rs267738 alleles. Results In-silico analysis of the amino acid substitution within CERS2 caused by the rs267738 mutation suggested that rs267738 is deleterious for enzyme function. Homozygous knock-in mice had reduced liver CERS2 activity and enhanced diet-induced glucose intolerance and hepatic steatosis. However, human serum sphingolipids and a ceramide-based CERT1 risk score of cardiovascular disease were not significantly affected by rs267738 allele count. Conclusions The rs267738 SNP leads to a partial loss-of-function of CERS2, which worsened metabolic parameters in knock-in mice. However, rs267738 was insufficient to effect changes in serum sphingolipid profiles in subjects from the Utah Coronary Artery Disease Study.

scholarly journals Improved Detection of Potentially Pleiotropic Genes in Coronary Artery Disease and Chronic Kidney Disease Using GWAS Summary Statistics

2020 ◽  
Vol 11 ◽  
Author(s):  
Haimiao Chen ◽  
Ting Wang ◽  
Jinna Yang ◽  
Shuiping Huang ◽  
Ping Zeng
Keyword(s):  
Coronary Artery Disease ◽  
Chronic Kidney Disease ◽  
Coronary Artery ◽  
Kidney Disease ◽  
Association Studies ◽  
Functional Enrichment ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Genetic Determination ◽  
Artery Disease

The coexistence of coronary artery disease (CAD) and chronic kidney disease (CKD) implies overlapped genetic foundation. However, the common genetic determination between the two diseases remains largely unknown. Relying on summary statistics publicly available from large scale genome-wide association studies (n = 184,305 for CAD and n = 567,460 for CKD), we observed significant positive genetic correlation between CAD and CKD (rg = 0.173, p = 0.024) via the linkage disequilibrium score regression. Next, we implemented gene-based association analysis for each disease through MAGMA (Multi-marker Analysis of GenoMic Annotation) and detected 763 and 827 genes associated with CAD or CKD (FDR < 0.05). Among those 72 genes were shared between the two diseases. Furthermore, by integrating the overlapped genetic information between CAD and CKD, we implemented two pleiotropy-informed informatics approaches including cFDR (conditional false discovery rate) and GPA (Genetic analysis incorporating Pleiotropy and Annotation), and identified 169 and 504 shared genes (FDR < 0.05), of which 121 genes were simultaneously discovered by cFDR and GPA. Importantly, we found 11 potentially new pleiotropic genes related to both CAD and CKD (i.e., ARHGEF19, RSG1, NDST2, CAMK2G, VCL, LRP10, RBM23, USP10, WNT9B, GOSR2, and RPRML). Five of the newly identified pleiotropic genes were further repeated via an additional dataset CAD available from UK Biobank. Our functional enrichment analysis showed that those pleiotropic genes were enriched in diverse relevant pathway processes including quaternary ammonium group transmembrane transporter, dopamine transport. Overall, this study identifies common genetic architectures overlapped between CAD and CKD and will help to advance understanding of the molecular mechanisms underlying the comorbidity of the two diseases.

scholarly journals Genome-Wide Association Study of Coronary Artery Disease

2010 ◽  
Vol 2010 ◽  
pp. 1-8 ◽  
Author(s):  
Naomi Ogawa ◽  
Yasushi Imai ◽  
Hiroyuki Morita ◽  
Ryozo Nagai
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Association Studies ◽  
Genome Wide Association ◽  
Candidate Gene Approach ◽  
International Hapmap Project ◽  
Genome Wide Association Studies ◽  
Genetic Determinants ◽  
Genome Wide ◽  
Artery Disease

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.

scholarly journals A genetic variant at coronary artery disease and ischemic stroke locus 1p32.2 regulates endothelial responses to hemodynamics

2018 ◽  
Author(s):  
Matthew D. Krause ◽  
Ru-Ting Huang ◽  
David Wu ◽  
Tzu-Pin Shentu ◽  
Devin L. Harrison ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Ischemic Stroke ◽  
Coronary Artery ◽  
Genetic Variants ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Enhancer Activity ◽  
Protective Allele ◽  
Unidirectional Flow ◽  
Artery Disease

AbstractBiomechanical cues dynamically control major cellular processes but whether genetic variants actively participate in mechano-sensing mechanisms remains unexplored. Vascular homeostasis is tightly regulated by hemodynamics. Exposure to disturbed blood flow at arterial sites of branching and bifurcation causes constitutive activation of vascular endothelium contributing to atherosclerosis, the major cause of coronary artery disease (CAD) and ischemic stroke (IS). Conversely, unidirectional flow promotes quiescent endothelium. Genome-wide association studies have identified chromosome 1p32.2 as one of the most strongly associated loci with CAD/IS; however, the causal mechanism related to this locus remains unknown. Employing statistical analyses, ATAC-seq, and H3K27ac/H3K4me2 ChIP-Seq in human aortic endothelium (HAEC), our results demonstrate that rs17114036, a common noncoding polymorphism at the 1p32.2, is located in an endothelial enhancer dynamically regulated by hemodynamics. CRISPR/Cas9-based genome editing shows that rs17114036-containing region promotes endothelial quiescence under unidirectional flow by regulating phospholipid phosphatase 3 (PLPP3). Chromatin accessibility quantitative trait locus mapping using HAECs from 56 donors, allelic imbalance assay from 7 donors, and luciferase assays further demonstrate that CAD/IS protective allele at rs17114036 in PLPP3 intron 5 confers an increased endothelial enhancer activity. ChIPPCR and luciferase assays show that CAD/IS protective allele at rs17114036 creates a binding site for transcription factor Krüppel-like factor 2, which increases the enhancer activity under unidirectional flow. These results demonstrate for the first time that a human single-nucleotide polymorphism contributes to critical endothelial mechanotransduction mechanisms and suggest that human haplotypes and related cisregulatory elements provide a previously unappreciated layer of regulatory control in cellular mechano-sensing mechanisms.Significance StatementBiomechanical stimuli control major cellular functions and play critical roles in the pathogenesis of diverse human diseases. Although recent studies have implicated genetic variation in regulating key biological processes, whether human genetic variants contribute to the cellular mechano-sensing mechanisms remains unclear. This study provides the first line of evidence supporting an underappreciated role of genetic predisposition in cellular mechanotransduction mechanisms. Employing epigenomic profiling, genome-editing, and latest human genetics approaches, our data demonstrate that rs17114036, a common noncoding polymorphism implicated in coronary artery disease and ischemic stroke by genome-wide association studies, dynamically regulates endothelial responses to blood flow (hemodynamics) related to atherosclerosis via regulation of an intronic enhancer. The results provide new molecular insights linking disease-associated genetic variants to cellular mechanobiology.

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