Pharmacovigilance‐Based Identification and Mechanistic Exploration of Periodontitis‐Related Drugs

Periodontitis is a common chronic inflammatory disease. However, drug-related risks and underlying molecular mechanisms remain underexplored from large real-world data. We first mined the US Food and Drug Administration Adverse Event Reporting System (FAERS) database to identify drugs disproportionately associated with periodontitis, using four signal detection algorithms and logistic regression for confounder adjustment. Identified drugs were then mapped to their protein targets via DrugBank, followed by pathway enrichment and protein-protein interaction (PPI) network analysis to explore biological relevance. To assess potential causality, we conducted Mendelian randomisation (MR) using cis-pQTLs from UKB-PPP and deCODE cohorts. Finally, we used single-cell RNA sequencing (scRNA-seq) data from gingival tissue and peripheral blood of periodontitis patients to evaluate cell type-specific expression of candidate causal genes. Five drugs (actonel, aclasta, aredia, amlodipine and avastin) were significantly positively associated with periodontitis based on FAERS. VEGFA showed an association with disease risk (OR = 1.043, p = 0.049) after meta-analysis of two cohorts. scRNA-seq data identified high VEGFA expression in monocytes in both gingival and blood samples of periodontitis patients. This study uncovered the association between drug and periodontitis and highlighted VEGFA as a potential molecular mediator. Further studies are needed to confirm causality.