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ObjectivesEpicardial adipose tissue (EAT) is closely adjacent to the coronary arteries and myocardium, its role as an endocrine organ to affect the pathophysiological processes of the coronary arteries and myocardium has been increasingly recognized. However, the specific gene expression profiles of EAT in coronary artery disease (CAD) has not been well characterized. Our aim was to investigate the role of EAT in CAD at the gene level.MethodsHere, we compared the histological and gene expression difference of EAT between CAD and non-CAD. We investigated the gene expression profiles in the EAT of patients with CAD through the high-throughput RNA sequencing. We performed bioinformatics analysis such as functional enrichment analysis and protein-protein interaction network construction to obtain and verify the hub differentially expressed genes (DEGs) in the EAT of CAD.ResultsOur results showed that the size of epicardial adipocytes in the CAD group was larger than in the control group. Our findings on the EAT gene expression profiles of CAD showed a total of 747 DEGs (fold change >2, p value GNG3, MCHR1, BDKRB1, MCHR2, CXCL8, CXCR5, CCR8, CCL4L1, TAS2R10, and TAS2R41) were identified.ConclusionEpicardial adipose tissue in CAD shows unique gene expression profiles and may act as key regulators in the CAD pathological process.

Epicardial adipose tissue (EAT) contributes to the pathophysiological process of coronary artery disease (CAD). The expression profiles of long non-coding RNAs (lncRNA) in EAT of patients with CAD have not been well characterized. We conducted high-throughput RNA sequencing to analyze the expression profiles of lncRNA in EAT of patients with CAD compared to patients without CAD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were executed to investigate the principal functions of the significantly dysregulated mRNAs. We confirmed a dysregulated intergenic lncRNA (lincRNA) (LINC00968) by real-time quantitative PCR (RT-qPCR). Subsequently, we constructed a ceRNA network associated with LINC00968, which included 49 mRNAs. Compared with the control group, lncRNAs and genes of EAT in CAD were characterized as metabolic active and pro-inflammatory profiles. The sequencing analysis detected 2539 known and 1719 novel lncRNAs. Then, we depicted both lncRNA and gene signatures of EAT in CAD, featuring dysregulation of genes involved in metabolism, nuclear receptor transcriptional activity, antigen presentation, chemokine signaling, and inflammation. Finally, we identified a ceRNA network as candidate modulator in EAT and its potential role in CAD. We showed the expression profiles of specific EAT lncRNA and mRNA in CAD, and a selected non-coding associated ceRNA regulatory network, which taken together, may contribute to a better understanding of CAD mechanism and provide potential therapeutic targets.Trial registration Chinese Clinical Trial Registry, No. ChiCTR1900024782.

Background Coronary 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. Methods Microarray 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. Results The 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). Conclusions Between 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.