Exploring the Shared Genetic Characteristics of Peri-Implantitis and Osteoporosis: A Transcriptomic Analysis Perspective.

INTRODUCTION AND AIMS: Increasing evidence suggests an association between peri-implantitis and osteoporosis, both of which are prevalent diseases that significantly affect patient quality of life. This study aimed to investigate the shared genes and molecular mechanisms underlying the co-pathogenesis of peri-implantitis and osteoporosis.

METHODS

Transcriptomic data from blood samples of patients with peri-implantitis and osteoporosis. were downloaded from the Gene Expression Omnibus database and shared differentially expressed genes (DEGs) were identified. Analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways was next conducted for shared DEGs. Then, an mRNA-miRNA network of the hub genes was established based on the miRTarbase database. Potential drugs related to the hub genes were predicted using the Genecards database. Finally, the CIBERSORT core algorithm was used to calculate immune cell infiltration levels.

RESULTS

Utilizing several gene expression datasets (GSE33774, GSE106090, GSE35956, and GSE35958), we identified a total of 10,839 DEGs. Notably, we identified 3 hub genes that exhibited differential expression in 4 datasets. Functional enrichment analysis revealed that intersected DEGs are involved in regulating oxidative stress, lipid metabolism, and osteoclast differentiation, while immune cell infiltration analyses highlighted correlations between gene expression and various immune cell types. Furthermore, our miRNA-mRNA interaction network analysis suggested complex regulatory mechanisms related to the hub genes. Finally, potential drug targets associated with these hub genes are identified.

CONCLUSION

This study provides valuable insights into the molecular mechanisms underlying peri-implantitis and osteoporosis, highlighting the potential for further investigation into targeted therapies that may improve clinical outcomes for affected patients.

CLINICAL RELEVANCE: The clinical translational value ranges from biomarkers to treatment targets. Shared genes may act as diagnostic markers, informing both the risk of osteoporosis and the bone integration ability of implants. Drugs targeting common genes may offer the potential for 'one drug, two effects'.