RESUMO
There is a potential link between rheumatoid arthritis (RA) and idiopathic pulmonary fibrosis (IPF). The aim of this study is to investigate the molecular processes that underlie the development of these two conditions by bioinformatics methods. The gene expression samples for RA (GSE77298) and IPF (GSE24206) were retrieved from the Gene Expression Omnibus (GEO) database. After identifying the overlapping differentially expressed genes (DEGs) for RA and IPF, we conducted functional annotation, protein-protein interaction (PPI) network analysis, and hub gene identification. Finally, we used the hub genes to predict potential medications for the treatment of both disorders. We identified 74 common DEGs for further analysis. Functional analysis demonstrated that cellular components, biological processes, and molecular functions all played a role in the emergence and progression of RA and IPF. Using the cytoHubba plugin, we identified 7 important hub genes, namely COL3A1, SDC1, CCL5, CXCL13, MMP1, THY1, and BDNF. As diagnostic indicators for RA, SDC1, CCL5, CXCL13, MMP1, and THY1 showed favorable values. For IPF, COL3A1, SDC1, CCL5, CXCL13, THY1, and BDNF were favorable diagnostic markers. Furthermore, we predicted 61 Chinese and 69 Western medications using the hub genes. Our research findings demonstrate a shared pathophysiology between RA and IPF, which may provide new insights for more mechanistic research and more effective treatments. These common pathways and hub genes identified in our study offer potential opportunities for developing more targeted therapies that can address both disorders.
