Coronary artery disease: differential expression of ceRNAs and interaction analyses.

BACKGROUND

Previous studies have demonstrated associations between cardiovascular disease and the expression of various messenger RNAs (mRNAs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs). This study aimed to investigate the differential expression of mRNAs, lncRNAs, and miRNAs between tissues from patients with coronary artery disease (CAD) and healthy controls, and to determine the interactions between these molecules in CAD.

METHODS

We investigated the differential expression of competitive endogenous RNAs (ceRNAs) between patients with CAD and healthy controls by collecting data from Gene Expression Omnibus (GEO) microarrays. We also investigated the biological function of these differentially expressed ceRNAs by performing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. We then created a protein-protein interaction (PPI) network to identify the hub genes. Biosystems and literature searches were also carried out to identify relevant signaling pathways and the potential function of the differentially expressed ceRNAs.

RESULTS

We identified 456 expression profiles for miRNAs, 16,325 mRNA expression profiles, and 2,869 lncRNA expression profiles. With regards to connectivity, GO and KEGG analyses (count ≥9) identified the top 11 PPI network nodes in rank order. We also identified the top 15 significant nodes for the ceRNAs identified according to degree centrality (DC) (P<0.05). Collectively, our analyses confirmed that the differential expression of certain ceRNAs, and their respective signaling pathways were associated with CAD.

CONCLUSIONS

Data arising from 11 GO and KEGG pathways, the top 15 PPI network nodes with the best connectivity rank, and the top 15 ceRNA network nodes, as determined by DC rank in CAD population, indicated that the differential expression of these ceRNAs plays a key role in the CAD. Our findings highlight new molecular mechanisms for CAD and provide new options for the development of therapeutic targets.