Integrated gut microbiome and fecal metabolome profiling identifies taurine-associated microbial dysbiosis across the Alzheimer’s disease clinical spectrum

Background Gut microbiome alterations have been associated with Alzheimer’s disease (AD), but how microbial composition, fecal metabolites, and cognitive function relate across the cognitive impairment spectrum—from subjective cognitive decline (SCD) through mild cognitive impairment (MCI) to AD—remains unclear. We integrated microbiome and metabolome profiles across this clinical spectrum. Methods Fecal samples from 84 participants [10 healthy controls (HC), 22 SCD, 23 MCI, 29 AD] underwent 16S rRNA V3–V4 sequencing and untargeted LC–MS metabolomics. Profiles were integrated via Procrustes analysis, sparse canonical correlation, MIMOSA2 community-metabolism modeling, and mediation analysis. Differential abundance was assessed by Kruskal–Wallis, ANCOM-BC2, and LinDA. Results Microbial composition differed across groups (ANOSIM R = 0.111, p = 0.001; Adonis R 2 = 0.070, p = 0.002). Cross-method validation confirmed 8 differentially abundant genera in AD vs. HC with 100% directional concordance between ANCOM-BC2 and LinDA, including depletion of butyrate-producing Lachnospiraceae (Blautia, Dorea, Fusicatenibacter) and enrichment of opportunistic pathobionts (Klebsiella, Escherichia-Shigella). Taurine showed the highest MIMOSA2 community-prediction R 2 (0.129; n = 62) and was positively associated with MMSE scores ( r = 0.45, BH-FDR Q = 0.0005). A multi-omic random forest model (5 genera + 5 metabolites + age + sex) discriminated AD-clinical spectrum participants from HC with AUC = 0.86 (95% CI 0.82–0.90), although pairwise differences from the age + sex baseline (AUC = 0.75) did not reach statistical significance. Statistical mediation analysis was consistent with a Blautia → taurine → MMSE statistical mediation [ACME = 0.21, p = 0.008; 54% proportion mediated, bootstrap 95% CI (9%, 58%)]. Conclusion Integrated multi-omic profiling reveals coordinated microbiome–metabolome dysregulation across the AD clinical spectrum, with taurine as a candidate microbial–metabolic node linking gut dysbiosis to cognitive performance. Microbial and metabolic alterations are detectable at the SCD stage, before objective cognitive impairment. These findings warrant validation in larger, age-matched cohorts and higher-resolution metagenomic studies.

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Journal
Frontiers in Aging Neuroscience
Published
2026-10-28
DOI
https://doi.org/10.3389/fnagi.2026.1981076
Primary Topic
Gut microbiota and health
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article
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article

Integrated gut microbiome and fecal metabolome profiling identifies taurine-associated microbial dysbiosis across the Alzheimer’s disease clinical spectrum

刘根桃, Yi Feng, Yan Gao, Ruwen Zhou et al.
4 links
Frontiers in Aging Neuroscience
Gut microbiota and health
article

Integrated gut microbiome and fecal metabolome profiling identifies taurine-associated microbial dysbiosis across the Alzheimer’s disease clinical spectrum

刘根桃, Yi Feng, Yan Gao, Ruwen Zhou, Lu Xu, Yao Sha, Jinchang Tian
article en

Abstract

Background Gut microbiome alterations have been associated with Alzheimer’s disease (AD), but how microbial composition, fecal metabolites, and cognitive function relate across the cognitive impairment spectrum—from subjective cognitive decline (SCD) through mild cognitive impairment (MCI) to AD—remains unclear. We integrated microbiome and metabolome profiles across this clinical spectrum. Methods Fecal samples from 84 participants [10 healthy controls (HC), 22 SCD, 23 MCI, 29 AD] underwent 16S rRNA V3–V4 sequencing and untargeted LC–MS metabolomics. Profiles were integrated via Procrustes analysis, sparse canonical correlation, MIMOSA2 community-metabolism modeling, and mediation analysis. Differential abundance was assessed by Kruskal–Wallis, ANCOM-BC2, and LinDA. Results Microbial composition differed across groups (ANOSIM R = 0.111, p = 0.001; Adonis R 2 = 0.070, p = 0.002). Cross-method validation confirmed 8 differentially abundant genera in AD vs. HC with 100% directional concordance between ANCOM-BC2 and LinDA, including depletion of butyrate-producing Lachnospiraceae (Blautia, Dorea, Fusicatenibacter) and enrichment of opportunistic pathobionts (Klebsiella, Escherichia-Shigella). Taurine showed the highest MIMOSA2 community-prediction R 2 (0.129; n = 62) and was positively associated with MMSE scores ( r = 0.45, BH-FDR Q = 0.0005). A multi-omic random forest model (5 genera + 5 metabolites + age + sex) discriminated AD-clinical spectrum participants from HC with AUC = 0.86 (95% CI 0.82–0.90), although pairwise differences from the age + sex baseline (AUC = 0.75) did not reach statistical significance. Statistical mediation analysis was consistent with a Blautia → taurine → MMSE statistical mediation [ACME = 0.21, p = 0.008; 54% proportion mediated, bootstrap 95% CI (9%, 58%)]. Conclusion Integrated multi-omic profiling reveals coordinated microbiome–metabolome dysregulation across the AD clinical spectrum, with taurine as a candidate microbial–metabolic node linking gut dysbiosis to cognitive performance. Microbial and metabolic alterations are detectable at the SCD stage, before objective cognitive impairment. These findings warrant validation in larger, age-matched cohorts and higher-resolution metagenomic studies.

Frontiers in Aging NeuroscienceVol. 18
Tongji University (CN), Nanyang Technological University (SG), Fudan University (CN), Shanghai Mental Health Center (CN), Shanghai Tenth People's Hospital (CN)
Good health and well-being
Openalex Percentile: Top 22%
Gut microbiota and health
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