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.