Salivary Biomarkers in Alzheimer’s Disease: Emerging Diagnostic Tools and Their Association with Periodontal Disease

Alzheimer’s disease (AD) is the most common neurodegenerative disorder and a leading cause of dementia worldwide. Current diagnostic methods, including cerebrospinal fluid analysis and neuroimaging, are often invasive, expensive, and not suitable for large-scale screening. Therefore, increasing attention has been directed toward the identification of non-invasive biomarkers. Saliva has emerged as a promising diagnostic biofluid containing proteins, metabolites, inflammatory mediators, exosomes, and nucleic acids potentially associated with neurodegenerative processes. This review aimed to summarize current evidence regarding salivary biomarkers in Alzheimer’s disease and to discuss their diagnostic potential, limitations, and association with periodontal disease within the framework of the oral–brain axis. A literature search was conducted using PubMed, Scopus, and Google Scholar databases for studies published between 2018 and 2026. Relevant English-language articles focusing on salivary biomarkers, Alzheimer’s disease, periodontitis, and oral–brain axis interactions were included. Current evidence suggests that salivary biomarkers such as amyloid-beta, tau protein, lactoferrin, exosomes, oxidative stress markers, metabolites, and nucleic acid-based biomarkers may reflect the pathological mechanisms associated with Alzheimer’s disease. In addition, increasing evidence supports a relationship between chronic periodontal inflammation, oral pathogens, and neurodegenerative processes. However, substantial heterogeneity among studies, methodological variability, and a lack of standardized protocols currently limit the reproducibility and clinical applicability of saliva-based diagnostics. Salivary biomarkers represent a promising non-invasive approach for the early detection and monitoring of Alzheimer’s disease. Nevertheless, further large-scale, longitudinal, and standardized studies are necessary to validate their diagnostic utility and support their implementation in routine clinical practice.