Elucidation of hub cross-talk genes as potential biomarkers and drug prediction for chronic periodontitis and rheumatoid arthritis: A bioinformatics analysis

This study aims to identify cross-talk genes and potential therapeutic drugs for chronic periodontitis (CP) and rheumatoid arthritis (RA) through bioinformatics analysis, highlighting their potential as biomarkers and therapeutic targets. We conducted a comprehensive bioinformatics analysis using gene expression omnibus datasets for CP (GSE10334, GSE16134) and RA (GSE55457, GSE55235) to identify common differentially expressed genes (DEGs). We analyzed the biological functions and pathway regulations of these DEGs. Common target genes were identified from the CTD and GeneCards databases, and hub genes were determined by intersecting common DEGs with these target genes. The expression levels of these hub genes were further analyzed, and their diagnostic performance was assessed using receiver operating characteristic (ROC) curves. Potential therapeutic drugs targeting these hub genes were predicted using the DGIdb database. We identified 4 hub genes (CD79A, CXCL13, SLAMF7, and CCL18) that were consistently expressed in both CP and RA. ROC analysis demonstrated that these genes had excellent diagnostic value. Further analysis using the random forest model and combined ROC confirmed their diagnostic potential. Additionally, we identified 19 potential therapeutic drugs targeting these hub genes. Our findings provide insights into the genetic overlap between RA and CP, offering potential biomarkers and therapeutic targets for personalized medicine protocols. These results lay the foundation for future disease mechanism studies and accelerated clinical drug translation.