Salivary and gingival crevicular fluid extracellular vesicles in periodontal diseases

OBJECTIVES: This review synthesizes current biomarker-mediated, mechanistic, and clinical evidence on extracellular vesicles (EVs) derived from saliva and gingival crevicular fluid (GCF) as potential diagnostic and functional regulators in periodontal diseases (PD). DATA: Preclinical and clinical studies assessing EV-related molecular signatures, biological functions, and diagnostic utilities in PD were included without restriction on publication date. SOURCES: Scopus, Web of Science, and PubMed databases were searched. STUDY SELECTION: A narrative-scoping approach was adopted to integrate heterogeneous evidence. Findings were synthesized qualitatively owing to variability in methodologies, EV isolation methods, and analytical systems. CONCLUSION: Growing evidence supports salivary and GCF EVs as robust, non-invasive biomarkers capable of capturing real-time PD activity. EV payload reflects host-microbial interplay, immune-inflammatory signaling, and tissue remodeling mechanisms, with salivary EVs offering oral and systemic understanding, and GCF-EVs providing site-specific resolution closely linked with clinical parameters. Beyond diagnostic significance, selected EV components exhibit potential mechanistic roles in PD pathogenesis, indicating a dual function as biological mediators and biomarkers. Nevertheless, existing literature remains mainly associative, restricted by small sample size, methodological variability, and lack of standardized methods. Future research should prioritize longitudinal designs, large-scale validation, and integrated multi-omics strategies to allow predictive modeling and clinical application. CLINICAL SIGNIFICANCE: Salivary and GCF EVs allow real-time, non-invasive PD identification and monitoring, outperforming conventional approaches that reflect past injury. Their systemic and site-specific insights facilitate early diagnosis, prognosis, and personalized therapy, while clinical adoption mandates standardization and large-scale validation.