Abstract
Psoriasis (PS) is a chronic inflammatory skin disease with a long course and tendency to recur, the pathogenesis of which is not fully understood. This article aims to identify the key differentially expressed genes (DEGs) and microRNA (miRNAs) of PS, construct the core miRNA-mRNA regulatory network, and investigate the underlying molecular mechanism through integrated bioinformatics approaches. Two gene expression profile datasets and 2 miRNA expression profile datasets were downloaded from the gene expression omnibus (GEO) database and analyzed by GEO2R. Intersection DEGs and intersection differentially expressed miRNAs (DEMs) were each screened. The Metascape database and R software were used to perform enrichment analysis of intersecting DEGs and study their functions. Target genes of DEMs were predicted from the online database miRNet. The protein-protein interaction files of the overlapping target genes were obtained from string and the miRNA-mRNA network was constructed by Cytoscape software. In addition, the online web tool CIBERSORT was used to analyze the immune infiltration of dataset GSE166388, and the relative abundance of 22 immune cells in the diseased and normal control tissues was calculated and assessed. Finally, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to verify the relative expression of the screened miRNAs and mRNAs to assess the applicability of DEMs and DEGs as biomarkers in PS. A total of 205 mating DEGs and 6 mating DEMs were screened. 103 dysregulated crossover genes from 205 crossover DEGs and 7878 miRNA target genes were identified. The miRNA-mRNA regulatory network was constructed and the top 10 elements were obtained from CytoHubba, including hsa-miR-146a-5p, hsa-miR-17-5p, hsa-miR-106a-5p, hsa-miR-18a-5p, CDK1, CCNA2, CCNB1, MAD2L1, RRM2, and CCNB2. QRT-PCR revealed significant differences in miRNA and gene expression between inflammatory and normal states. In this study, the miRNA-mRNA core regulator pairs hsa-miR-146a-5p, hsa-miR-17-5p, hsa-miR-106a-5p, hsa-miR-18a-5p, CDK1, CCNA2, CCNB1, MAD2L1, RRM2, and CCNB2 may be involved in the course of PS. This study provides new insights to discover new potential targets and biomarkers to further investigate the molecular mechanism of PS.