The oral–vascular axis: immune mechanisms linking periodontal dysbiosis to systemic vascular pathology

Periodontitis is among the most prevalent chronic inflammatory diseases worldwide and may affect vascular health beyond the oral cavity. Framed within the concept of an oral-vascular axis, this review synthesizes clinical and mechanistic evidence linking periodontal disease with atherosclerotic cardiovascular disease (ASCVD). Epidemiological studies and meta analyses consistently associate periodontitis with higher risks of coronary heart disease (CHD), stroke, and cardiovascular mortality, with modest but reproducible effect sizes that persist after adjustment for traditional risk factors. However, heterogeneous study designs and residual confounding preclude definitive causal inference. Interventional evidence is currently dominated by surrogate endpoints, and event-level cardiovascular benefit from periodontal therapy remains unproven. Mechanistically, chronic periodontal inflammation may influence endothelial function and atherogenesis through interlocking pathways that can be viewed as a spatiotemporal, dual-regulatory network of immunity and metabolism: local dysbiosis and barrier disruption increase systemic access to microbial ligands and vesicular cargo, while systemic immune activation interacts with metabolic remodeling to shape inflammatory set-points and vascular susceptibility. Microbe-derived and host-microbe co-metabolites may further modulate redox balance, inflammatory tone, and vascular homeostasis within this network. We highlight limitations of existing interventional trials, methodological challenges in microbiome- and genetics-based causal inference, and priorities for translational research. Clinically, the oral-vascular axis motivates interdisciplinary exchange and research-facing collaboration that integrates oral health assessment with immune and vascular phenotyping, while recognizing that cardiovascular benefit from periodontal interventions remains investigational and requires event-driven validation.