Novel salivary biomarkers of Alzheimer's disease identified by integrated metabolomics and microbiomics analysis.

OBJECTIVES: Alzheimer's disease (AD) and mild cognitive impairment (MCI) represent significant health challenges, with identification of biomarkers from non-invasive biofluid critical for large-scale screening and effective intervention. MATERIAL AND METHODS: In this study, we performed a comprehensive analysis integrating non-targeted metabolomics and 16S rDNA sequencing of saliva samples from 3 age and sex-matched groups containing 18 AD patients, 15 MCI individuals and 19 healthy controls (HC). RESULTS: Salivary metabolites including histamine (biogenic amine), carveol (monoterpene), and 2-phosphoglycerate (glycolytic intermediate) were significantly altered in AD patients. In addition, L-glutamic acid (excitatory neurotransmitter) levels were notably reduced in MCI patients, suggesting its potential as a biomarker for MCI. Microbial analysis revealed a decrease in the abundance of Actinomyces and Stomatobaculum in AD patients. In contrast, MCI patients exhibited a reduction in Atopobium and Actinomyces, along with an increase in Gemella and Peptostreptococcus compared to HC. An integrated analysis of microbiota and metabolites uncovered significant correlations, such as a positive correlation between Lactobacillus crispatus and GABA in AD patients, and an association between Klebsiella pneumoniae and multiple metabolites in AD patients. Additionally, MCI patients exhibited a higher abundance of "potentially pathogenic" microbiota species, highlighting a distinct microbiome profile. CONCLUSIONS: Our findings revealed distinct metabolic and microbiomic alterations across the groups. CLINICAL RELEVANCE: These findings suggest that saliva may harbor valuable biomarkers for the early diagnosis of AD and MCI. Moreover, our results underscore the involvement of the "oral-brain axis" in the pathogenesis of neurodegenerative diseases, offering new insights into potential therapeutic targets.