Identification of key genes and Construction of miRNA-mRNA regulatory network in Psoriasis based on Bioinformatics Analysis

Abstract

Background Psoriasis is a chronic inflammatory skin disease with a long course of disease and a tendency to relapse, and the pathogenesis is not completely clear. This article aims to identify the key differentially expressed genes and miRNAs of PS, construct the core miRNA-mRNA regulatory network, and to explore its underlying molecular mechanism through integrated bioinformatics approaches. Methods Two gene expression profile datasets (GSE166388 and GSE153007), and two microRNA (miRNA) expression profile datasets (GSE115293 and GSE145305) were downloaded from the Gene Expression Omnibus (GEO) database and analyzed by GEO2R. Intersection differentially expressed genes (DEGs) and intersection differentially expressed miRNAs (DEMs) were screened, respectively. Metascape database was used to enrich the analysis of intersection DEGs and to explore their functions. Target genes of differentially expressed miRNAs were predicted by the online database miRNet. The protein–protein interaction files of intersection target genes were obtained by String, and the miRNA-mRNA network was constructed by Cytoscape software. In addition, the CIBERSORT online web tool was used to analyze the immune infiltration of the dataset GSE166388, and the relative abundance of 22 immune cells in the disease and normal control tissues was calculated and evaluated. Results A total of 660 intersection DEGs (397 upregulated mRNAs and 263 downregulated mRNAs) and 9 intersection DEMs (5 upregulated miRNAs and 4 downregulated miRNAs) were screened. 340 intersection dysregulated genes from 660 intersection DEGs and 7232 miRNA target genes were identified. The miRNA-mRNA regulatory network was constructed and the Top10 elements were obtained by CytoHubba, including hsa-miR-155-5p, hsa-miR-497-5p, hsa-miR-132-3p, hsa-miR-125b-5p, CDK1, CCNA2, CCNB1, STAT1, BUB1, and NCAPG. Conclusion In this study, the miRNA-mRNA core regulatory pairs formed by hsa-miR-155-5p, hsa-miR-497-5p, hsa-miR-132-3p, hsa-miR-125b-5p, CDK1, CCNA2, CCNB1, STAT1, BUB1, and NCAPG may be involved in PS in the progress. This study provides new insights for the discovery of new potential targets and further study of the molecular mechanism of PS.