Gut Microbiota, Plasma Metabolome Profile Correlate with Amyloid Burden, Cognition in MCI Patients

Current therapies for Alzheimer's disease (AD) and mild cognitive impairment (MCI) have limited efficacy, driving interest in novel pathways. The gut-brain axis and systemic metabolic dysregulation are increasingly recognized as crucial contributors to AD pathogenesis. Understanding the specific microbial and metabolic signatures associated with amyloid pathology and cognitive decline in MCI patients could reveal new diagnostic biomarkers and therapeutic targets, addressing a significant gap in early intervention strategies.

A cross-sectional multi-omics baseline analysis was conducted in 47 MCI patients from a dietary intervention trial. Gut microbiota composition was assessed via 16S rRNA sequencing (n = 47), and plasma metabolomics by untargeted LC-MS/MS (n = 45). Patients were stratified based on plasma amyloid-beta 42/40 ratio (BA42/40) for amyloid burden and ADAScog11 score for cognitive impairment, serving as complementary biomarkers to identify specific microbial and metabolic associations.

Higher amyloid burden and worse cognitive performance were associated with significant gut microbiota alterations, including increased alpha diversity and distinct beta diversity profiles. Differential abundance analyses consistently showed enrichment of Bacteroides-associated taxa and Akkermansia, alongside depletion of short-chain fatty acid-producing genera such as Faecalibacterium, Blautia, and Phascolarctobacterium. Plasma metabolomics identified a coherent signature associated with elevated BA42/40, characterized by accumulation of secondary bile acid sulfates and depletion of sphingolipids, neuroactive steroids, and anti-inflammatory lipid mediators. These included pregnenolone sulfate, resolvin E1, and anandamide. A valid OPLS-DA discriminant model was obtained for BA42/40, indicating a strong metabolic link to amyloid pathology. > Critically, significant microbiota differences were observed, but no predictive metabolomic model was achieved for ADAScog11, suggesting a dissociation between these markers and cognitive performance in this cohort.