Abstract
BACKGROUND: Peri-implantitis is implant-associated inflammation that leads to irreversible loss of surrounding bone. Early diagnosis increases the success of peri-implantitis treatment. Despite various studies associated with this most common complication, early detection of the onset of peri-implantitis remains a major challenge. Molecular biomarkers are applicable detectors for the early detection of numerous diseases and monitoring their development. The present study aimed to predict interactome networks of up/down regulated proteins and analyze drug-gene interaction in peri-implantitis to identify the diagnostic and druggable genes. MATERIALS AND METHODS: In this in silico study, a suitable gene expression profile related to peri-implantitis was retrieved from Gene Expression Omnibus. Screening differentially expressed genes (DEGs) was carried out based on the cut-off criteria |log2 (fold change)|>2 and P < 0.05. Interactome networks were constructed and analyzed by the STRING database (Version: 12.0) and the Cytoscape software (version: 3.9.1). Finally, to investigate drug-gene interaction, detected hub genes were analyzed by DGIdb (version: 5.0.6). RESULTS: A total of 216 genes were identified as DEGs (129 down-regulated and 87 up-regulated genes) in peri-implantitis. Regarding Cytoscape analysis, FCGR3B, CSF3R, AQP9, TREM1, and P2RY13 were the top 5 hub nodes of up-regulated DEGs, and CXCL10, OASL, IFIT1, RSAD2, and ISG15 were the top 5 hub nodes of down-regulated DEGs. Among these key nods, AQP9, CSF3R, CXCL10, IFIT1, ISG15, OASL, and, FCGR3B were therapeutic targets and had approved drugs. CONCLUSION: In this research, seven genes have been identified as druggable genes in peri-implantitis which can be used to treat and diagnose this disease. However, these results and identified genes need to be validated by clinical or experimental methods.