Tan Liao, Xu Qian, Wang Qianchen, Shi Ruizheng, Zhang Guogang
Department of Cardiovascular Medicine, Xiangya Hospital, Central South University, Changsha, China.
Institute of Hypertension, Central South University, Changsha, China.
PeerJ. 2020 Mar 25;8:e8763. doi: 10.7717/peerj.8763. eCollection 2020.
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.
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.
The three datasets had a total of 89 DEGs (FC log2 > 1 and 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 ( value < 0.05).
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.
冠状动脉疾病（CAD）是一种常见疾病，治疗成本高且死亡率高。在此，我们研究了CAD患者的心外膜脂肪组织（EAT）和皮下脂肪组织（SAT）之间的差异表达基因（DEGs），以探索EAT参与CAD病理过程的可能途径和机制。
从基因表达综合数据库获得EAT和SAT的微阵列数据，包括三个独立的表达数据集：GSE24425、GSE64554和GSE120774。使用R语言中的limma软件包筛选出EAT样本和SAT对照样本之间的DEGs。接下来，我们对基因本体术语和京都基因与基因组百科全书通路进行生物信息学分析，以发现与DEGs相关的富集基因集和通路。同时，进行基因集富集分析，以从所有表达数据而非DEGs中发现富集的基因功能和通路。构建蛋白质-蛋白质相互作用（PPI）网络，以揭示与CAD一致的可能蛋白质相互作用。Cytoscape中的Mcode和Cytohubba揭示了可能的关键CAD基因。在下一步中，使用miRNA数据整合门户分析相应的预测微RNA（miRNAs）。逆转录-聚合酶链反应（RT-PCR）用于验证生物信息学结果。
这三个数据集共有89个DEGs（FC log2>1且P值<0.05）。通过比较EAT和SAT，鉴定出10个常见关键基因（HOXA5、HOXB5、HOXC6、HOXC8、HOXB7、COL1A1、CCND1、CCL2、HP和TWIST1）。在富集分析中，促炎和免疫基因及通路上调。这有助于阐明EAT参与CAD发展的分子表达机制。预测有几种miRNAs调节这些DEGs。特别是，hsa-miR-196a-5p和hsa-miR-196b-5p可能与CAD更可靠相关。最后，RT-PCR验证了EAT和SAT之间OXA5、HOXC6、HOXC8、HOXB7、COL1A1、CCL2的显著差异（P值<0.05）。
在CAD患者的EAT和SAT之间，共预测有89个DEGs以及10个关键基因，包括HOXA5、HOXB5、HOXC6、HOXC8、HOXB7、COL1A1、CCND1、CCL2、HP和TWIST1，并且miRNAs hsa-miR-196a-5p和hsa-miR-196b-5p在CAD发病机制中起重要作用。促炎和免疫通路可能通过参与CAD病理过程而成为EAT的关键调节因子。
