Proficiency of data interpretation: identification of signaling SNPs/specific loci for coronary artery disease.
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ABSTRACT:
SUBMITTER: Cheema AN
PROVIDER: S-EPMC5737196 | biostudies-literature | 2017 Jan
REPOSITORIES: biostudies-literature
Publications
Proficiency of data interpretation: identification of signaling SNPs/specific loci for coronary artery disease.
Cheema Asma N AN Rosenthal Samantha L SL Ilyas Kamboh M M
Database : the journal of biological databases and curation 20170101
<h4>Database urls</h4>http://www.regulomedb.org/;https://www.broadinstitute.org/mpg/snap/. ...[more]
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Project description:Background Coronary artery disease (CAD) is a complex disorder involving both genetic and non-genetic factors. Genome wide association studies (GWAS) have identified hundreds of single nucleotides polymorphism (SNPs) tagging over >40 CAD risk loci. We hypothesized that some non-coding variants might directly regulate the gene expression rather than tagging a nearby locus. Methods A total of 58 SNPs within 54 CAD loci was selected. Of these SNPs, 52 had accepted genome wide significant threshold (P<5×10?8) .We used SNAP webportal to identify SNPs in strong LD (r2 >0.80) with our SNPs of interest. We used RegulomeDB to identify potentially functional SNPs. RegulomeDB is a database that scores SNP’s functionality based upon their existence in a DNAase hypersensitive site or transcription factor binding site. RegulomeDB grades the SNPs from 1 to 6. The SNP showing the strongest evidence of being regulatory is given the score of 1 and SNP demonstrating the least evidence of being functional is marked as 6. Results SNAP webportal gave a total of 1,200 SNPs. Among the 1,200 SNPs [58 were genome-wide significant (P<5×10?8) and the remaining were in linkage disequilibrium (r2 >0.80) with 58 SNPs]. Of these, 97 SNPs were predicted to have regulatory function with RegulomeDB score of <3, and only 8 of them were genome-wide significant (LIPA/rs2246833 = RegulomeDB score 1b; ZC3HC1/rs11556924, CYPA1/CNNM2/NT5C2/rs12413409, APOE-APOC1/rs2075650 and UBE2Z/rs46522 RegulomeDB score = 1f; ZNF259-APOA5-APOA1/rs964184, SMG6/rs2281727, and COL4A1-COL4A2/rs4773144 = RegulomeDB score 2b). Conclusions This study supports the hypothesis that some of the non-coding variants are true signals that regulate the gene expression at the transcriptional level. Our study indicates that RegulomeDB is a useful database to examine the large number of genetic variants and it may differentiate between true or tagged SNPs by defining the functional role of variants, particularly for variants in complex disease such as CAD.
| S-EPMC5641708 | biostudies-literature
Project description:ImportanceSpontaneous coronary artery dissection (SCAD), an idiopathic disorder that predominantly affects young to middle-aged women, has emerged as an important cause of acute coronary syndrome, myocardial infarction, and sudden cardiac death.ObjectiveTo identify common single-nucleotide variants (SNVs) associated with SCAD susceptibility.Design, setting, and participantsThis single-center genome-wide association study examined approximately 5 million genotyped and imputed SNVs and subsequent SNV-targeted replication analysis results in individuals enrolled in the Mayo Clinic SCAD registry from August 30, 2011, to August 2, 2018. Data analysis was performed from June 21, 2017, to December 30, 2019.Main outcomes and measuresGenetic loci and positional candidate genes associated with SCAD.ResultsThis study included 484 white women with SCAD (mean [SD] age, 46.6 [9.2] years) and 1477 white female controls in the discovery cohort (mean [SD] age, 64.0 [14.5] years) and 183 white women with SCAD (mean [SD] age, 47.1 [9.9] years) and 340 white female controls in the replication cohort (mean [SD] age, 51.0 [15.3] years). Associations with SCAD risk reached genome-wide significance at 3 loci (1q21.3 [OR, 1.78; 95% CI, 1.51-2.09; P = 2.63 × 10-12], 6p24.1 [OR, 1.77; 95% CI, 1.51-2.09; P = 7.09 × 10-12], and 12q13.3 [OR, 1.67; 95% CI, 1.42-1.97; P = 3.62 × 10-10]), and 7 loci had evidence suggestive of an association (1q24.2 [OR, 2.10; 95% CI, 1.58-2.79; P = 2.88 × 10-7], 3q22.3 [OR, 1.47; 95% CI, 1.26-1.71; P = 6.65 × 10-7], 4q34.3 [OR, 1.84; 95% CI, 1.44-2.35; P = 9.80 × 10-7], 8q24.3 [OR, 2.57; 95% CI, 1.76-3.75; P = 9.65 × 10-7], 15q21.1 [OR, 1.75; 95% CI, 1.40-2.18; P = 7.23 × 10-7], 16q24.1 [OR, 1.91; 95% CI, 1.49-2.44; P = 2.56 × 10-7], and 21q22.11 [OR, 2.11; 95% CI, 1.59-2.82; P = 3.12 × 10-7]) after adjusting for the top 5 principal components. Associations were validated for 5 of the 10 risk alleles in the replication cohort. In a meta-analysis of the discovery and replication cohorts, associations for the 5 SNVs were significant, with relatively large effect sizes (1q21.3 [OR, 1.77; 95% CI, 1.54-2.03; P = 3.26 × 10-16], 6p24.1 [OR, 1.71; 95% CI, 1.49-1.97; P = 4.59 × 10-14], 12q13.3 [OR, 1.69; 95% CI, 1.47-1.94; P = 1.42 × 10-13], 15q21.1 [OR, 1.79; 95% CI, 1.48-2.17; P = 2.12 × 10-9], and 21q22.11 [OR, 2.18; 95% CI, 1.70-2.81; P = 1.09 × 10-9]). Each index SNV was within or near a gene highly expressed in arterial tissue and previously linked to SCAD (PHACTR1) and/or other vascular disorders (LRP1, LINC00310, and FBN1).Conclusions and relevanceThis study revealed 5 replicated risk loci and positional candidate genes for SCAD, most of which are associated with extracoronary arteriopathies. Moreover, the alternate alleles of 3 SNVs have been previously associated with atherosclerotic coronary artery disease, further implicating allelic susceptibility to coronary artery atherosclerosis vs dissection.
| S-EPMC7203673 | biostudies-literature
Project description:Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10-8, in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms.
| S-EPMC5555387 | biostudies-literature
Project description:Recent genome-wide association studies of coronary artery disease (CAD) have revealed 58 genome-wide significant and 148 suggestive genetic loci. However, the molecular mechanisms through which they contribute to CAD and the clinical implications of these findings remain largely unknown. We aim to retrieve gene subnetworks of the 206 CAD loci and identify and prioritize candidate regulators to better understand the biological mechanisms underlying the genetic associations.We devised a new integrative genomics approach that incorporated (1) candidate genes from the top CAD loci, (2) the complete genetic association results from the 1000 genomes-based CAD genome-wide association studies from the Coronary Artery Disease Genome Wide Replication and Meta-Analysis Plus the Coronary Artery Disease consortium, (3) tissue-specific gene regulatory networks that depict the potential relationship and interactions between genes, and (4) tissue-specific gene expression patterns between CAD patients and controls. The networks and top-ranked regulators according to these data-driven criteria were further queried against literature, experimental evidence, and drug information to evaluate their disease relevance and potential as drug targets. Our analysis uncovered several potential novel regulators of CAD such as LUM and STAT3, which possess properties suitable as drug targets. We also revealed molecular relations and potential mechanisms through which the top CAD loci operate. Furthermore, we found that multiple CAD-relevant biological processes such as extracellular matrix, inflammatory and immune pathways, complement and coagulation cascades, and lipid metabolism interact in the CAD networks.Our data-driven integrative genomics framework unraveled tissue-specific relations among the candidate genes of the CAD genome-wide association studies loci and prioritized novel network regulatory genes orchestrating biological processes relevant to CAD.
| S-EPMC5576868 | biostudies-literature
Project description:BACKGROUND:Genome-wide association studies have identified multiple loci associated with coronary artery disease and myocardial infarction, but only a few of these loci are current targets for on-market medications. To identify drugs suitable for repurposing and their targets, we created 2 unique pipelines integrating public data on 49 coronary artery disease/myocardial infarction-genome-wide association studies loci, drug-gene interactions, side effects, and chemical interactions. METHODS:We first used publicly available genome-wide association studies results on all phenotypes to predict relevant side effects, identified drug-gene interactions, and prioritized candidates for repurposing among existing drugs. Second, we prioritized gene product targets by calculating a druggability score to estimate how accessible pockets of coronary artery disease/myocardial infarction-associated gene products are, then used again the genome-wide association studies results to predict side effects, excluded loci with widespread cross-tissue expression to avoid housekeeping and genes involved in vital processes and accordingly ranked the remaining gene products. RESULTS:These pipelines ultimately led to 3 suggestions for drug repurposing: pentolinium, adenosine triphosphate, and riociguat (to target CHRNB4, ACSS2, and GUCY1A3, respectively); and 3 proteins for drug development: LMOD1 (leiomodin 1), HIP1 (huntingtin-interacting protein 1), and PPP2R3A (protein phosphatase 2, regulatory subunit b-double prime, ?). Most current therapies for coronary artery disease/myocardial infarction treatment were also rediscovered. CONCLUSIONS:Integration of genomic and pharmacological data may prove beneficial for drug repurposing and development, as evidence from our pipelines suggests.
| S-EPMC6205215 | biostudies-literature
Project description:Genetic factors underlying coronary artery disease (CAD) have been widely studied using genome-wide association studies (GWASs). However, the functional understanding of the CAD loci has been limited by the fact that a majority of GWAS variants are located within non-coding regions with no functional role. High cholesterol and dysregulation of the liver metabolism such as non-alcoholic fatty liver disease confer an increased risk of CAD. Here, we studied the function of non-coding single-nucleotide polymorphisms in CAD GWAS loci located within liver-specific enhancer elements by identifying their potential target genes using liver cis-eQTL analysis and promoter Capture Hi-C in HepG2 cells. Altogether, 734 target genes were identified of which 121 exhibited correlations to liver-related traits. To identify potentially causal regulatory SNPs, the allele-specific enhancer activity was analyzed by (1) sequence-based computational predictions, (2) quantification of allele-specific transcription factor binding, and (3) STARR-seq massively parallel reporter assay. Altogether, our analysis identified 1,277 unique SNPs that display allele-specific regulatory activity. Among these, susceptibility enhancers near important cholesterol homeostasis genes (APOB, APOC1, APOE, and LIPA) were identified, suggesting that altered gene regulatory activity could represent another way by which genetic variation regulates serum lipoprotein levels. Using CRISPR-based perturbation, we demonstrate how the deletion/activation of a single enhancer leads to changes in the expression of many target genes located in a shared chromatin interaction domain. Our integrative genomics approach represents a comprehensive effort in identifying putative causal regulatory regions and target genes that could predispose to clinical manifestation of CAD by affecting liver function.
| S-EPMC8008493 | biostudies-literature
Project description:ObjectivesClinical and epidemiological findings indicate an association between coronary artery disease (CAD) and low birth weight (BW). However, the mechanisms underlying this relationship are largely unknown. Here, we aimed to identify novel single-nucleotide polymorphisms (SNPs) associated with CAD, BW, and their shared pleiotropic loci, and to detect the potential causal relationship between CAD and BW.MethodsWe first applied a genetic pleiotropic conditional false discovery rate (cFDR) method to two independent genome-wide association studies (GWAS) summary statistics of CAD and BW to estimate the pleiotropic enrichment between them. Then, bi-directional Mendelian randomization (MR) analyses were performed to clarify the causal association between these two traits.ResultsBy incorporating related traits into a conditional analysis framework, we observed the significant pleiotropic enrichment between CAD and BW. By applying the cFDR level of 0.05, 109 variants were detected for CAD, 203 for BW, and 26 pleiotropic variants for both traits. We identified 11 CAD- and/or BW-associated SNPs that showed more than three of the metabolic quantitative trait loci (metaQTL), protein QTL (pQTL), methylation QTL (meQTL), or expression QTL (eQTL) effects. The pleiotropic SNP rs10774625, located at ATXN2, showed metaQTL, pQTL, meQTL, and eQTL effects simultaneously. Using the bi-directional MR approach, we found a negative association from BW to CAD (odds ratio [OR] = 0.68, 95% confidence interval [CI]: 0.59 to 0.80, p = 1.57× 10-6).ConclusionWe identified several pleiotropic loci between CAD and BW by leveraging GWAS results of related phenotypes and identified a potential causal relationship from BW to CAD. Our findings provide novel insights into the shared biological mechanisms and overlapping genetic heritability between CAD and BW.
| S-EPMC7906162 | biostudies-literature
Project description:IL1b signaling is critically involved in inflammatory diseases. However, the gene targets and mechanisms of IL1b mediated inflammatory processes in adult human vascular endothelium still remain unclear. We show that IL1b regulates genes coding for inflammatory cytokines, cell adhesion molecules and pathways through NFkB transcriptional activation. We further identify the genes regulated by IL1b that regulate endothelial barrier function and act as targets for known clinically relevant compunds. These findings stimulate further research to identify novel signaling mechanisms modulating endothelial barrier function in IL1b driven inflammatory pathologies.
2019-05-15 | GSE118297 | GEO
Project description:Inflammatory Wnt5A signalling in human macrophages was found to be critically involved in severe systemic inflammatory response. However, the targets of Wnt5A in endothelial cells and downstream mechanisms by which Wnt5A might induce endothelial inflammation still remain unclear. We show that Wnt5A principally regulate genes involved endothelial cytoskeleton rearrangements and impairs the barrier function of cultured endothelial monolayer causing hyper permeability. We further prove that Wnt5A neither affects the expression of adhesion molecules nor induces cytokine storm in endothelial cells. These findings suggest that Wnt5A, secreted by activated macrophages during septic inflammation, paracrinically act on the endothelial wall, causing endothelial barrier breakdown and subsequent vascular leakage in sepsis.
2016-10-03 | GSE62281 | GEO
Project description:Genome-wide association studies have to date identified 159 significant and suggestive loci for coronary artery disease (CAD). We now report comprehensive bioinformatics analyses of sequence variation in these loci to predict candidate causal genes.All annotated genes in the loci were evaluated with respect to protein-coding single-nucleotide polymorphism and gene expression parameters. The latter included expression quantitative trait loci, tissue specificity, and miRNA binding. High priority candidate genes were further identified based on literature searches and our experimental data. We conclude that the great majority of causal variations affecting CAD risk occur in noncoding regions, with 41% affecting gene expression robustly versus 6% leading to amino acid changes. Many of these genes differed from the traditionally annotated genes, which was usually based on proximity to the lead single-nucleotide polymorphism. Indeed, we obtained evidence that genetic variants at CAD loci affect 98 genes which had not been linked to CAD previously.Our results substantially revise the list of likely candidates for CAD and suggest that genome-wide association studies efforts in other diseases may benefit from similar bioinformatics analyses.
| S-EPMC4583353 | biostudies-literature