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.

Identification of Phosphorylation Associated SNPs for Blood Pressure, Coronary Artery Disease and Stroke from Genome-wide Association Studies

2019 ◽  
Vol 19 (10) ◽  
pp. 731-738
Author(s):  
Xingchen Wang ◽  
Xingbo Mo ◽  
Huan Zhang ◽  
Yonghong Zhang ◽  
Yueping Shen
Keyword(s):  
Blood Pressure ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Cardiovascular Diseases ◽  
Association Studies ◽  
Serum Levels ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Artery Disease

Purpose: Phosphorylation-related SNP (phosSNP) is a non-synonymous SNP that might influence protein phosphorylation status. The aim of this study was to assess the effect of phosSNPs on blood pressure (BP), coronary artery disease (CAD) and ischemic stroke (IS). Methods: We examined the association of phosSNPs with BP, CAD and IS in shared data from genome-wide association studies (GWAS) and tested if the disease loci were enriched with phosSNPs. Furthermore, we performed quantitative trait locus analysis to find out if the identified phosSNPs have impacts on gene expression, protein and metabolite levels. Results: We found numerous phosSNPs for systolic BP (count=148), diastolic BP (count=206), CAD (count=20) and IS (count=4). The most significant phosSNPs for SBP, DBP, CAD and IS were rs1801131 in MTHFR, rs3184504 in SH2B3, rs35212307 in WDR12 and rs3184504 in SH2B3, respectively. Our analyses revealed that the associated SNPs identified by the original GWAS were significantly enriched with phosSNPs and many well-known genes predisposing to cardiovascular diseases contain significant phosSNPs. We found that BP, CAD and IS shared for phosSNPs in loci that contain functional genes involve in cardiovascular diseases, e.g., rs11556924 (ZC3HC1), rs1971819 (ICA1L), rs3184504 (SH2B3), rs3739998 (JCAD), rs903160 (SMG6). Four phosSNPs in ADAMTS7 were significantly associated with CAD, including the known functional SNP rs3825807. Moreover, the identified phosSNPs seemed to have the potential to affect transcription regulation and serum levels of numerous cardiovascular diseases-related proteins and metabolites. Conclusion: The findings suggested that phosSNPs may play important roles in BP regulation and the pathological mechanisms of CAD and IS.

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.

scholarly journals Coronary artery disease, genetic risk and the metabolome in young individuals

2018 ◽  
Vol 3 ◽  
pp. 114 ◽  
Author(s):  
Thomas Battram ◽  
Luke Hoskins ◽  
David A. Hughes ◽  
Johannes Kettunen ◽  
Susan M. Ring ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Genetic Variants ◽  
Genetic Risk ◽  
Association Studies ◽  
Genetic Risk Score ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Genome Wide Association Studies ◽  
Artery Disease

Background: Genome-wide association studies have identified genetic variants associated with coronary artery disease (CAD) in adults – the leading cause of death worldwide. It often occurs later in life, but variants may impact CAD-relevant phenotypes early and throughout the life-course. Cohorts with longitudinal and genetic data on thousands of individuals are letting us explore the antecedents of this adult disease. Methods: 149 metabolites, with a focus on the lipidome, measured using nuclear magnetic resonance (1H-NMR) spectroscopy, and genotype data were available from 5,905 individuals at ages 7, 15, and 17 years from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Linear regression was used to assess the association between the metabolites and an adult-derived genetic risk score (GRS) of CAD comprising 146 variants. Individual variant-metabolite associations were also examined. Results: The CAD-GRS associated with 118 of 149 metabolites (false discovery rate [FDR] < 0.05), the strongest associations being with low-density lipoprotein (LDL) and atherogenic non-LDL subgroups. Nine of 146 variants in the GRS associated with one or more metabolites (FDR < 0.05). Seven of these are within lipid loci: rs11591147 PCSK9, rs12149545 HERPUD1-CETP, rs17091891 LPL, rs515135 APOB, rs602633 CELSR2-PSRC1, rs651821 APOA5, rs7412 APOE-APOC1. All associated with metabolites in the LDL or atherogenic non-LDL subgroups or both including aggregate cholesterol measures. The other two variants identified were rs112635299 SERPINA1 and rs2519093 ABO. Conclusions: Genetic variants that influence CAD risk in adults are associated with large perturbations in metabolite levels in individuals as young as seven. The variants identified are mostly within lipid-related loci and the metabolites they associated with are primarily linked to lipoproteins. This knowledge could allow for preventative measures, such as increased monitoring of at-risk individuals and perhaps treatment earlier in life, to be taken years before any symptoms of the disease arise.

scholarly journals High-Resolution Regulatory Maps Connect Vascular Risk Variants to Disease-Related Pathways

2019 ◽  
Vol 12 (3) ◽  
Author(s):  
Örjan Åkerborg ◽  
Rapolas Spalinskas ◽  
Sailendra Pradhananga ◽  
Anandashankar Anil ◽  
Pontus Höjer ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
High Resolution ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Expression Levels ◽  
Risk Variants ◽  
Genome Wide ◽  
Artery Disease

Background: Genetic variant landscape of coronary artery disease is dominated by noncoding variants among which many occur within putative enhancers regulating the expression levels of relevant genes. It is crucial to assign the genetic variants to their correct genes both to gain insights into perturbed functions and better assess the risk of disease. Methods: In this study, we generated high-resolution genomic interaction maps (≈750 bases) in aortic endothelial, smooth muscle cells and THP-1 (human leukemia monocytic cell line) macrophages stimulated with lipopolysaccharide using Hi-C coupled with sequence capture targeting 25 429 features, including variants associated with coronary artery disease. We also sequenced their transcriptomes and mapped putative enhancers using chromatin immunoprecipitation with an antibody against H3K27Ac. Results: The regions interacting with promoters showed strong enrichment for enhancer elements and validated several previously known interactions and enhancers. We detected interactions for 727 risk variants obtained by genome-wide association studies and identified novel, as well as established genes and functions associated with cardiovascular diseases. We were able to assign potential target genes for additional 398 genome-wide association studies variants using haplotype information, thereby identifying additional relevant genes and functions. Importantly, we discovered that a subset of risk variants interact with multiple promoters and their expression levels were strongly correlated. Conclusions: In summary, we present a catalog of candidate genes regulated by coronary artery disease–related variants and think that it will be an invaluable resource to further the investigation of cardiovascular pathologies and disease.

scholarly journals 2018 George Lyman Duff Memorial Lecture

2019 ◽  
Vol 39 (10) ◽  
pp. 1925-1937 ◽  
Author(s):  
Ruth McPherson
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Disease Risk ◽  
Association Studies ◽  
Genome Wide Association ◽  
Data Sets ◽  
Genome Wide Association Studies ◽  
Coronary Artery Disease Risk ◽  
Genome Wide ◽  
Artery Disease

Recent studies have led to a broader understanding of the genetic architecture of coronary artery disease and demonstrate that it largely derives from the cumulative effect of multiple common risk alleles individually of small effect size rather than rare variants with large effects on coronary artery disease risk. The tools applied include genome-wide association studies encompassing over 200 000 individuals complemented by bioinformatic approaches including imputation from whole-genome data sets, expression quantitative trait loci analyses, and interrogation of ENCODE (Encyclopedia of DNA Elements), Roadmap Epigenetic Project, and other data sets. Over 160 genome-wide significant loci associated with coronary artery disease risk have been identified using the genome-wide association studies approach, 90% of which are situated in intergenic regions. Here, I will describe, in part, our research over the last decade performed in collaboration with a series of bright trainees and an extensive number of groups and individuals around the world as it applies to our understanding of the genetic basis of this complex disease. These studies include computational approaches to better understand missing heritability and identify causal pathways, experimental approaches, and progress in understanding at the molecular level the function of the multiple risk loci identified and potential applications of these genomic data in clinical medicine and drug discovery.

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