Dataset Information

Integration of Gene Expression Profile Data of Human Epicardial Adipose Tissue from Coronary Artery Disease to Verification of Hub Genes and Pathways.

ABSTRACT: Background:This study aim to identify the core pathogenic genes and explore the potential molecular mechanisms of human coronary artery disease (CAD). Methodology:Two gene profiles of epicardial adipose tissue from CAD patients including GSE 18612 and GSE 64554 were downloaded and integrated by R software packages. All the coexpression of deferentially expressed genes (DEGs) were picked out and analyzed by DAVID online bioinformatic tools. In addition, the DEGs were totally typed into protein-protein interaction (PPI) networks to get the interaction data among all coexpression genes. Pictures were drawn by cytoscape software with the PPI networks data. CytoHubba were used to predict the hub genes by degree analysis. Finally all the top 10 hub genes and prediction genes in Molecular complex detection were analyzed by Gene ontology and Kyoto encyclopedia of genes and genomes pathway analysis. qRT-PCR were used to identified all the 10 hub genes. Results:The top 10 hub genes calculated by the degree method were AKT1, MYC, EGFR, ACTB, CDC42, IGF1, FGF2, CXCR4, MMP2 and LYN, which relevant with the focal adhesion pathway. Module analysis revealed that the focal adhesion was also acted an important role in CAD, which was consistence with cytoHubba. All the top 10 hub genes were verified by qRT-PCR which presented that AKT1, EGFR, CDC42, FGF2, and MMP2 were significantly decreased in epicardial adipose tissue of CAD samples (p < 0.05) and MYC, ACTB, IGF1, CXCR4, and LYN were significantly increased (p < 0.05). Conclusions:These candidate genes could be used as potential diagnostic biomarkers and therapeutic targets of CAD.

SUBMITTER: Wang W

PROVIDER: S-EPMC6900948 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Integration of Gene Expression Profile Data of Human Epicardial Adipose Tissue from Coronary Artery Disease to Verification of Hub Genes and Pathways.

Wang Weitie W Liu Qing Q Wang Yong Y Piao Hulin H Li Bo B Zhu Zhicheng Z Li Dan D Wang Tiance T Xu Rihao R Liu Kexiang K

BioMed research international 20191127

<h4>Background</h4>This study aim to identify the core pathogenic genes and explore the potential molecular mechanisms of human coronary artery disease (CAD).<h4>Methodology</h4>Two gene profiles of epicardial adipose tissue from CAD patients including GSE 18612 and GSE 64554 were downloaded and integrated by <i>R</i> software packages. All the coexpression of deferentially expressed genes (DEGs) were picked out and analyzed by DAVID online bioinformatic tools. In addition, the DEGs were totally ...[more]

PMID: 31886261

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Project description:BackgroundCoronary artery disease (CAD) is a common disease with high cost and mortality. Here, we studied the differentially expressed genes (DEGs) between epicardial adipose tissue (EAT) and subcutaneous adipose tissue (SAT) from patients with CAD to explore the possible pathways and mechanisms through which EAT participates in the CAD pathological process.MethodsMicroarray data for EAT and SAT were obtained from the Gene Expression Omnibus database, including three separate expression datasets: GSE24425, GSE64554 and GSE120774. The DEGs between EAT samples and SAT control samples were screened out using the limma package in the R language. Next, we conducted bioinformatic analysis of gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways to discover the enriched gene sets and pathways associated with DEGs. Simultaneously, gene set enrichment analysis was carried out to discover enriched gene functions and pathways from all expression data rather than DEGs. The PPI network was constructed to reveal the possible protein interactions consistent with CAD. Mcode and Cytohubba in Cytoscape revealed the possible key CAD genes. In the next step, the corresponding predicted microRNAs (miRNAs) were analysed using miRNA Data Integration Portal. RT-PCR was used to validate the bioinformatic results.ResultsThe three datasets had a total of 89 DEGs (FC log2 > 1 and P value < 0.05). By comparing EAT and SAT, ten common key genes (HOXA5, HOXB5, HOXC6, HOXC8, HOXB7, COL1A1, CCND1, CCL2, HP and TWIST1) were identified. In enrichment analysis, pro-inflammatory and immunological genes and pathways were up-regulated. This could help elucidate the molecular expression mechanism underlying the involvement of EAT in CAD development. Several miRNAs were predicted to regulate these DEGs. In particular, hsa-miR-196a-5p and hsa-miR-196b-5p may be more reliably associated with CAD. Finally, RT-PCR validated the significant difference of OXA5, HOXC6, HOXC8, HOXB7, COL1A1, CCL2 between EAT and SAT (P value < 0.05).ConclusionsBetween EAT and SAT in CAD patients, a total of 89 DEGs, and 10 key genes, including HOXA5, HOXB5, HOXC6, HOXC8, HOXB7, COL1A1, CCND1, CCL2, HP and TWIST1, and miRNAs hsa-miR-196a-5p and hsa-miR-196b-5p were predicted to play essential roles in CAD pathogenesis. Pro-inflammatory and immunological pathways could act as key EAT regulators by participating in the CAD pathological process.

Project description:BackgroundEpicardial adipose tissue (EAT) is closely related to coronary artery disease (CAD). Hemodynamically significant CAD has a worse prognosis and is more likely to benefit from revascularization. However, the specific relationship between EAT and hemodynamically significant CAD remains unclear.MethodsA total of 164 inpatients received single-photon emission computerized tomography-myocardial perfusion imaging (SPECT/MPI) and coronary angiography (CAG) between March 2018 and October 2019 at the Third Affiliated Hospital of Soochow University were enrolled in the retrospective cross-sectional study. Data on body mass index (BMI), hypertension, hyperlipidemia, diabetes mellitus (DM), active smoking, and symptoms were gathered. Epicardial fat volume (EFV) and coronary artery calcium (CAC) were quantified by noncontrast computed tomography (CT). Hemodynamically significant CAD was defined by coronary stenosis severity ≥50% with reversible perfusion defects in the corresponding areas of SPECT/MPI.ResultsA total of 37.8% of patients had hemodynamically significant CAD. Age and BMI increased with tertiles of EFV (P for trend =0.009 and P<0.001). The ratios of hemodynamically significant CAD in EFV from low to high were 16.4%, 37.0%, and 60.0%, respectively (P for the trend <0.001). In univariate regression analysis, EFV was associated with hemodynamically significant CAD [odds ratio (OR) per 10 cm3 =1.36; 95% confidence interval (CI): 1.20-1.55; P<0.001]. After correcting for traditional risk factors and CAC, EFV was firmly linked to hemodynamically significant CAD (OR per 10 cm3 =1.53; 95% CI: 1.25-1.88; P<0.001). With an increasing trend in EFV for the tripartite groups, the likelihood of hemodynamically significant CAD increased significantly (P for trend <0.001). There was a saturation effect between EFV and hemodynamically significant CAD according to the generalized additive model (GAM). When EFV <134.43 cm3, EFV was linearly correlated with hemodynamically significant CAD (OR per 10 cm3 =2.06; 95% CI: 1.45-2.94; P<0.001). When EFV ≥134.43 cm3, the hemodynamically significant CAD risk was steeper and gradually reached saturation. Hypertension affected the relationship between EFV and hemodynamically significant CAD (P for the interaction =0.02) with an interaction effect.ConclusionsThere was a robust relationship between EFV and hemodynamically significant CAD. After adjustment for confounders, we found that the risk of hemodynamically significant CAD onset increased nonlinearly for EFV above 134.4 cm3. This refined understanding of the relationship is helpful for the accurate clinical prediction of hemodynamically significant CAD.

Project description:BackgroundRecent studies have focused on the potential role of epicardial adipose tissue (EAT) in the development of coronary artery disease (CAD). ABCA1 and ABCG1 transporters regulate cell cholesterol content and reverse cholesterol transport. We aimed to determine whether DNA methylation and mRNA levels of the ABCA1 and ABCG1 genes in EAT and subcutaneous adipose tissue (SAT) were associated with CAD.MethodsPaired EAT and SAT samples were collected from 82 patients undergoing elective cardiac surgery either for coronary artery bypass grafting (CAD group, N = 66) or valve surgery (NCAD group, N = 16). ABCA1 and ABCG1 mRNA levels in EAT and SAT samples were analyzed using real time polymerase chain reaction, ABCA1 protein levels in EAT samples were assessed by western blotting. ABCA1 and ABCG1 DNA methylation analysis was performed in 24 samples from the CAD group and 9 samples from the NCAD group via pyrosequencing.ResultsDNA methylation levels in the ABCA1 promoter and ABCG1 cg27243685 and cg06500161 CpG sites were higher in EAT samples from patients with CAD compared with NCAD (21.92% vs 10.81%, p = 0.003; 71.51% vs 68.42%, p = 0.024; 46.11% vs 37.79%, p = 0.016, respectively). In patients with CAD, ABCA1 and ABCG1 DNA methylation levels were higher in EAT than in SAT samples (p < 0.05). ABCA1 mRNA levels in EAT samples were reduced in the subgroup of patients with CAD and concomitant carotid artery disease or peripheral artery disease compared with the NCAD group (p = 0.024). ABCA1 protein levels in EAT samples tended to be lower in CAD patients than in the NCAD group (p = 0.053). DNA methylation levels at the ABCG1 cg27243685 site positively correlated with plasma triglyceride concentration (r = 0.510, p = 0.008), body mass index (r = 0.556, p = 0.013) and waist-to-hip ratio (r = 0.504, p = 0.012) in SAT samples.ConclusionCAD is associated with ABCA1 and ABCG1 DNA hypermethylation in EAT. CAD with concomitant carotid artery disease or peripheral artery disease is accompanied by decreased ABCA1 gene expression in EAT. DNA methylation levels at the ABCG1 cg27243685 locus in SAT are associated with hypertriglyceridemia and obesity.

Dataset Information

Integration of Gene Expression Profile Data of Human Epicardial Adipose Tissue from Coronary Artery Disease to Verification of Hub Genes and Pathways.

Publications

Integration of Gene Expression Profile Data of Human Epicardial Adipose Tissue from Coronary Artery Disease to Verification of Hub Genes and Pathways.

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