Application of weighted gene co-expression network analysis to rheumatoid arthritis

The goal of this study was to identify hub genes as potential targets in rheumatoid arthritis (RA) using weighted gene co-expression network analysis (WGCNA). Gene expression profiles of GSE17755 were downloaded from the GEO database and screened for differentially expressed genes (DEGs) with the limma package in R. Significant modules in the network were identified via WGCNA. Then, Gene Ontology (GO) functional enrichment of genes in the most significant module was analyzed using Database for Annotation, Visualization, and Integrated Discovery (DAVID). Finally, the disease-related gene co-expression network was visualized using Cytoscape, and hub genes were identified on CytoHubba. Overall, 3666 DEGs and 8 modules were identified. The turquoise module including 1044 genes was identified as the most relevant to RA. GO functional enrichment showed genes in the most relevant module were mainly related to the inflammatory response and the type I interferon signaling pathway. Ten hub genes, including PIGL, PRKAA1, and MRPS10, were identified. Genes related to the inflammatory response and the type I interferon signaling pathway possibly play critical roles in RA pathogenesis. PIGL, PRKAA1, and MRPS10 may be new targets for treating RA.