Identification and Interaction Analysis of Key Genes and MicroRNAs in Systemic Sclerosis by Bioinformatics Approaches

Systemic sclerosis (SSc) is a highly heterogeneous autoimmune disease with a high mortality rate. However, the cellular and molecular mechanisms of SSc remain unclear. Here, we identified the key hub genes and microRNAs (miRNAs) that modulate the occurrence and development of SSc. We downloaded the microarray dataset GSE95065 from the Gene Expression Omnibus (GEO) database and then analyzed the data by using GEO2R. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for functional pathway enrichment analyses of differentially expressed genes (DEGs), and Cytoscape software was used to generate the protein-protein interaction (PPI) network. In addition, OmicsNet was used to predict the miRNAs for the hub genes of SSc. As a result, 783 DEGs were identified, of which 770 genes (142 up-regulated genes and 628 down-regulated genes) were matched to the genes in SSc skin samples. Gene Ontology (GO) analyses by DAVID indicated that the up-regulated genes were mainly involved in immune response, and the down-regulated genes were greatly enriched in glycinergic synaptic transmission. In the PPI network, 22 nodes were selected as key genes, including several members of the chemokine family. Furthermore, after uploading these key genes to the OmicsNet tool, we found that hsa-miR-26b-5p might target CXCL9 and CXCL13. Moreover, we demonstrated that the hsa-miR-26b-5p inhibitor might inhibit fibrosis in TGF-β-activated fibroblasts, which would be a promising target for SSc therapy.