Identification of candidate targets for the diagnosis and treatment of atherosclerosis by bioinformatics analysis

Atherosclerosis, a chronic inflammatory disease, is the primary cause of most cardiovascular diseases. Circular RNAs (circRNAs) were reported to serve as post-transcriptional regulators and diagnostic markers in various diseases, but the underlying correlation between circRNAs and atherosclerosis remains elusive. In this study, we downloaded the microarray dataset GSE107522 from the Gene Expression Omnibus (GEO) and identified nine differentially expressed circRNAs (DECs). DECs expression in exosomes were investigated, and hsa_circ_0005699 was selected for subsequent analysis. We then identified 14 RNA-binding proteins (RBPs) and 71 possible hsa_ circ_0005699-interacting microRNAs. Subsequently, target gene prediction and enrichment analyses were performed. The enriched pathways of RBP elF4AIII include spliceosome, cell cycle, and pathways in cancer. We constructed a protein-protein interaction network, and 20 hub genes were identified using Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape. Hub gene analysis revealed significant enrichment in mRNA splicing via the spliceosome, RNA splicing, protein binding, neurotrophin signaling pathway, and Ras signaling pathway. Using DrugMatrix of the Enrichr database, we identified 16 most significant small-molecule compounds that interacted with hub genes. Finally, seven hub genes (NEDD4L, FBX044, FBX027, WSB1, FBXW8, UBE2F, and ASB1) in cluster 1 were considered key targets associated with atherosclerosis according to MCODE analysis and the intersection between the module and hub genes. Thus, hsa_circ_0005699, RBP eIF4A111, and the seven identified hub genes (NEDD4L, FBX044, FBX027, WSB1, FBXW8, UBE2F, and ASB1) could help to elucidate the pathogenesis and progression of atherosclerosis. This work may contribute to providing candidate targets for the diagnosis and treatment of atherosclerosis.

Automated summary

This study investigated the correlation between circRNAs and atherosclerosis, identified DECs and analyzed their role in the disease progression. Through bioinformatics analysis, potential hub genes and small-molecule compounds interacting with them were identified, providing candidate targets for the diagnosis and treatment of atherosclerosis.