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Frontiers in pharmacology · 2026

Multi-omics integration identifies a gut-microbiota-associated plasma metabolite signature for alzheimer disease diagnosis and metabolic pathway targeting.

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Chen Jiao, Chen Xuhui, Yu Weiwei, Chen Ting, Liu Zhigang, Hu Jun

Аннотация

BACKGROUND: Alzheimer's disease (AD) is the leading cause of dementia, with early diagnosis remaining constrained by the invasiveness and limited accessibility of current biomarkers. The gut-brain axis has emerged as a critical communication network linking intestinal homeostasis with central nervous system function, yet the diagnostic utility of gut-microbiota-associated circulating metabolites in AD remains largely unexplored.

METHODS: In this case-control study, 85 participants (37 AD patients and 48 cognitively normal controls) were enrolled. Targeted plasma metabolomics using four complementary UPLC-MS/MS assays covering 375 endogenous metabolites was integrated with fecal metagenomic sequencing in 72 participants with paired samples. Differential metabolites were screened using the Mann-Whitney U test, orthogonal partial least squares discriminant analysis, and fold-change thresholds. Gut-microbiota-associated plasma metabolites were defined through Spearman correlation with linear discriminant analysis effect size-identified differential bacterial species. A diagnostic panel was constructed using least absolute shrinkage and selection operator logistic regression with stability selection, and its performance was evaluated by support vector machine with repeated cross-validation, with age and sex evaluated as covariates.

METHODS: We identified 27 differential plasma metabolites enriched in tricarboxylic acid cycle and amino acid metabolic pathways. Correlation analysis identified 10 gut-microbiota-associated plasma metabolites significantly associated with gut microbial alterations. A three-metabolite panel (citric acid, 3-hydroxyoctanoic acid, and glyoxylic acid) achieved a cross-validated area under the curve of 0.865, with a modest sensitivity of 62.2% and specificity of 100.0%, positioning it as a confirmatory auxiliary tool rather than a broad screening instrument. The panel score correlated negatively with Mini-Mental State Examination scores (r = -0.544, P < 0.001), and integration with clinical cognitive assessment yielded an area under the curve of 0.978.

CONCLUSION: These findings potentially advance the translational understanding of the gut-brain metabolic axis in neurodegeneration and support the exploratory clinical utility of microbiota-linked peripheral metabolic signatures as non-invasive auxiliary diagnostic tools for AD, awaiting external validation in larger, multi-center cohorts.