Gut Microbiota Composition Is Related to AD Pathology

Area of Science:

• Microbiome research
• Neurodegenerative disease biomarkers
• Machine learning in medicine

Background:

• Inconsistent findings exist regarding gut microbiota alterations in Alzheimer's disease (AD).
• Investigating the link between gut microbiome and AD biomarkers is crucial for understanding disease mechanisms.

Purpose of the Study:

• To explore associations between gut microbiota composition and AD biomarkers (amyloid and p-tau).
• To utilize machine learning models to identify microbial signatures related to AD pathology in patients with AD dementia, mild cognitive impairment (MCI), and subjective cognitive decline (SCD).

Main Methods:

• 170 participants (AD dementia, MCI, SCD) from the Amsterdam Dementia Cohort.
• 16S rRNA sequencing for gut microbiome analysis.
• Machine learning classification models to assess associations between microbiota and CSF amyloid-beta 1-42, p-tau, and MRI visual scores.

Main Results:

• Machine learning models achieved AUCs of 0.64 for amyloid and 0.63 for p-tau prediction from microbiota.
• Specific microbes, including SCFA-producing species, were significantly associated with amyloid and p-tau positivity.
• Lower abundance of SCFA-producing microbes like *Lachnospiraceae* spp. and *Roseburia hominis* was linked to increased odds of amyloid and p-tau positivity.

Conclusions:

• Gut microbiota composition is significantly associated with amyloid and p-tau status in individuals with cognitive decline.
• Reduced abundance of SCFA-producing microbes may increase the risk or indicate the presence of AD pathology.