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 ◽  
...  

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.

2018 ◽  
Vol 115 (48) ◽  
pp. E11349-E11358 ◽  
Author(s):  
Matthew D. Krause ◽  
Ru-Ting Huang ◽  
David Wu ◽  
Tzu-Pin Shentu ◽  
Devin L. Harrison ◽  
...  

Biomechanical cues dynamically control major cellular processes, but whether genetic variants actively participate in mechanosensing 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 (GWAS) have identified chromosome 1p32.2 as strongly associated with CAD/IS; however, the causal mechanism related to this locus remains unknown. Using statistical analyses, assay of transposase accessible chromatin with whole-genome sequencing (ATAC-seq), H3K27ac/H3K4me2 ChIP with whole-genome sequencing (ChIP-seq), and CRISPR interference in human aortic endothelial cells (HAECs), our results demonstrate that rs17114036, a common noncoding polymorphism at 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 shear stress by regulating phospholipid phosphatase 3 (PLPP3). Chromatin accessibility quantitative trait locus (caQTL) mapping using HAECs from 56 donors, allelic imbalance assay from 7 donors, and luciferase assays demonstrate that CAD/IS-protective allele at rs17114036 in PLPP3 intron 5 confers increased endothelial enhancer activity. ChIP-PCR and luciferase assays show that CAD/IS-protective allele at rs17114036 creates a binding site for transcription factor Krüppel-like factor 2 (KLF2), which increases the enhancer activity under unidirectional flow. These results demonstrate that a human SNP contributes to critical endothelial mechanotransduction mechanisms and suggest that human haplotypes and related cis-regulatory elements provide a previously unappreciated layer of regulatory control in cellular mechanosensing mechanisms.


2018 ◽  
Vol 3 ◽  
pp. 114 ◽  
Author(s):  
Thomas Battram ◽  
Luke Hoskins ◽  
David A. Hughes ◽  
Johannes Kettunen ◽  
Susan M. Ring ◽  
...  

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.


2019 ◽  
Vol 3 ◽  
pp. 114 ◽  
Author(s):  
Thomas Battram ◽  
Luke Hoskins ◽  
David A. Hughes ◽  
Johannes Kettunen ◽  
Susan M. Ring ◽  
...  

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: 148 metabolites, with a focus on the lipidome, measured using nuclear magnetic resonance (1H-NMR) spectroscopy, and genotype data were available from 5,907 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 148 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. Along with further research, 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.


Author(s):  
Yang Li ◽  
Han Yan ◽  
Jian Guo ◽  
Yingchun Han ◽  
Cuifang Zhang ◽  
...  

Abstract Aims Genetic contribution to coronary artery disease (CAD) remains largely unillustrated. Although transcriptomic profiles have identified dozens of genes that are differentially expressed in normal and atherosclerotic vessels, whether those genes are genetically associated with CAD remains to be determined. Here, we combined genetic association studies, transcriptome profiles and in vitro and in vivo functional experiments to identify novel susceptibility genes for CAD. Methods and results Through an integrative analysis of transcriptome profiles with genome-wide association studies for CAD, we obtained 18 candidate genes and selected one representative single nucleotide polymorphism (SNP) for each gene for multi-centred validations. We identified an intragenic SNP, rs1056515 in RGS5 gene (odds ratio = 1.17, 95% confidence interval =1.10–1.24, P = 3.72 × 10−8) associated with CAD at genome-wide significance. Rare genetic variants in linkage disequilibrium with rs1056515 were identified in CAD patients leading to a decreased expression of RGS5. The decreased expression was also observed in atherosclerotic vessels and endothelial cells treated by various cardiovascular risk factors. Through siRNA knockdown and adenoviral overexpression, we further showed that RGS5 regulated endothelial inflammation, vascular remodelling, as well as canonical NF-κB signalling activation. Moreover, CXCL12, a specific downstream target of the non-canonical NF-κB pathway, was strongly affected by RGS5. However, the p100 processing, a well-documented marker for non-canonical NF-κB pathway activation, was not altered, suggesting an existence of a novel mechanism by which RGS5 regulates CXCL12. Conclusions We identified RGS5 as a novel susceptibility gene for CAD and showed that the decreased expression of RGS5 impaired endothelial cell function and functionally contributed to atherosclerosis through a variety of molecular mechanisms. How RGS5 regulates the expression of CXCL12 needs further studies.


2020 ◽  
Vol 9 (3) ◽  
pp. 177-191
Author(s):  
Sridharan Priya ◽  
Radha K. Manavalan

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.


Author(s):  
Rebekah J Nicholson ◽  
Annelise M Poss ◽  
J Alan Maschek ◽  
James E Cox ◽  
Paul N Hopkins ◽  
...  

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.


2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
M Oguri ◽  
K Kato ◽  
H Horibe ◽  
T Fujimaki ◽  
J Sakuma ◽  
...  

Abstract Background Early-onset coronary artery disease (CAD) has a strong genetic component. Although genome-wide association studies have identified various genes and loci significantly associated with CAD mainly in European ancestry populations, genetic variants that contribute to susceptibility to this condition in Japanese individuals remain to be identified definitively. Purpose The purpose of the study was to identify genetic variants that confer susceptibility to early-onset CAD in Japanese. We have now performed exome-wide association studies (EWASs) in subjects with early-onset CAD and controls. Methods A total of 7256 individuals aged ≤65 years was enrolled in the study. The EWAS was conducted with 1482 subjects with CAD and 5774 controls. Genotyping of single nucleotide polymorphisms (SNPs) was performed with Illumina Human Exome-12 DNA Analysis BeadChip or Infinium Exome-24 BeadChip arrays. The relation of allele frequencies for 31,465 SNPs that passed quality control to CAD was examined with Fisher's exact test. To compensate for multiple comparisons of allele frequencies with CAD, we applied a false discovery rate (FDR) of <0.05 for statistical significance of association. Results The relation of allele frequencies for 31,465 SNPs to CAD with the use of Fisher's exact test showed that 170 SNPs were significantly (FDR <0.05) associated with CAD. Multivariable logistic regression analysis with adjustment for age, sex, and the prevalence of hypertension, diabetes mellitus, and dyslipidemia revealed that 162 SNPs were significantly (P<0.05) related to CAD. A stepwise forward selection procedure was performed to examine the effects of genotypes for the 162 SNPs on CAD. The 54 SNPs were significant (P<0.05) and independent [coefficient of determination (R2), 0.0008 to 0.0297] determinants of CAD. These SNPs together accounted for 15.5% of the cause of CAD. After examination of results from previous genome-wide association studies and linkage disequilibrium of the identified SNPs, we newly identified 21 genes (RNF2, YEATS2, USP45, ITGB8, TNS3, FAM170B-AS1, PRKG1, BTRC, MKI67, STIM1, OR52E4, KIAA1551, MON2, PLUT, LINC00354, TRPM1, ADAT1, KRT27, LIPE, GFY, EIF3L) and five chromosomal regions (2p13, 4q31.2, 5q12, 13q34, 20q13.2) that were significantly associated with CAD. Gene ontology analysis showed that various biological functions were predicted in the 18 genes identified in the present study. The network analysis revealed that the 18 genes had potential direct or indirect interactions with the 30 genes previously shown to be associated with CAD or with the 228 genes identified in previous genome-wide association studies of CAD. Conclusion We have newly identified 26 loci that confer susceptibility to CAD. Determination of genotypes for the SNPs at these loci may prove informative for assessment of the genetic risk for CAD in Japanese.


2020 ◽  
Vol 11 ◽  
Author(s):  
Haimiao Chen ◽  
Ting Wang ◽  
Jinna Yang ◽  
Shuiping Huang ◽  
Ping Zeng

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 &lt; 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 &lt; 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.


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