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Disturbed microbial ecology in Alzheimer’s disease: evidence from the gut microbiota and fecal metabolome Original paper

Researched by:

  • Dr. Umar ID
    Dr. Umar

    User avatarClinical Pharmacist and Clinical Pharmacy Master’s candidate focused on antibiotic stewardship, AI-driven pharmacy practice, and research that strengthens safe and effective medication use. Experience spans digital health research with Bloomsbury Health (London), pharmacovigilance in patient support programs, and behavioral approaches to mental health care. Published work includes studies on antibiotic use and awareness, AI applications in medicine, postpartum depression management, and patient safety reporting. Developer of an AI-based clinical decision support system designed to enhance antimicrobial stewardship and optimize therapeutic outcomes.

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November 24, 2025

Researched by:

  • Dr. Umar ID
    Dr. Umar

    User avatarClinical Pharmacist and Clinical Pharmacy Master’s candidate focused on antibiotic stewardship, AI-driven pharmacy practice, and research that strengthens safe and effective medication use. Experience spans digital health research with Bloomsbury Health (London), pharmacovigilance in patient support programs, and behavioral approaches to mental health care. Published work includes studies on antibiotic use and awareness, AI applications in medicine, postpartum depression management, and patient safety reporting. Developer of an AI-based clinical decision support system designed to enhance antimicrobial stewardship and optimize therapeutic outcomes.

    Read More

Last Updated: 2021-01-01

Microbiome Signatures identifies and validates condition-specific microbiome shifts and interventions to accelerate clinical translation. Our multidisciplinary team supports clinicians, researchers, and innovators in turning microbiome science into actionable medicine.

Karen Pendergrass

Karen Pendergrass is a microbiome researcher specializing in microbiome-targeted interventions (MBTIs). She systematically analyzes scientific literature to identify microbial patterns, develop hypotheses, and validate interventions. As the founder of the Microbiome Signatures Database, she bridges microbiome research with clinical practice. In 2012, based on her own investigative research, she became the first documented case of FMT for Celiac Disease—four years before the first published case study.

Location
China
Sample Site
Feces
Species
Homo sapiens

What was studied?

This original research article examined disturbed microbial ecology in Alzheimer’s disease (AD), focusing on how gut microbiota and fecal metabolome differ between individuals with AD and cognitively normal controls. The study used 16S rRNA sequencing and untargeted UPLC-MS metabolomics to identify a microbiome signature potentially useful for AD screening. The research aimed to uncover gut–brain metabolic disruptions relevant to AD pathogenesis, and this review refers directly to the findings that form part of this AD gut microbiome signature.

Who was studied?

The study enrolled 21 clinically diagnosed AD participants and 44 cognitively normal controls, all older adults with similar age, sex distribution, and BMI. Participants with recent antibiotic, probiotic, or immunosuppressive drug use were excluded. All individuals provided both fecal and blood samples on the same day, enabling integrated analysis of gut microbial composition, fecal metabolites, and circulating inflammatory cytokines.

Most important findings

AD was associated with 15 significantly altered gut bacterial genera, with 13 increased and 2 decreased. Increased genera were dominated by members of Lachnospiraceae and Ruminococcaceae, including Faecalibacterium, Agathobacter, Coprococcus_1, and Ruminococcaceae UCG-007, with additional increases in Pseudomonas, Atopobium, Parvimonas, Cloacibacillus, and others. The two decreased genera were Tyzzerella and Erysipelatoclostridium. These differences were confirmed by LEfSe analysis and visualized in the taxonomic bar plots on page 3, which show strong enrichment of these taxa in AD. Fecal metabolomics revealed 15 differential metabolites, including reductions in N-Docosahexaenoyl-GABA, 12-hydroxydodecanoic acid, and several lipid-related molecules. Increases were observed in steroid-like molecules such as 22-Angeloylbarringtogenol C and Trigofoenoside F. Pathway analysis (page 5) indicated disturbances in steroid hormone biosynthesis, N-acyl amino acid metabolism, and piperidine metabolism—pathways that plausibly influence neuroinflammation and amyloid processes. Nearly half of altered genera (46.7%) correlated significantly with multiple metabolites, illustrating functional coupling between microbial shifts and metabolic outputs. Faecalibacterium and Pseudomonas were particularly influential, linking to lipid-related and amino acid-derived metabolites.

Key implications

This study highlights a coordinated shift in gut microbial ecology and metabolic output in AD, suggesting a mechanistic contribution of gut-derived metabolites—particularly lipid derivatives and N-acyl amino acids—to neuroinflammation and systemic immune signaling. Several metabolites correlated with key cytokines (e.g., G-CSF, IFN-γ), linking gut processes to peripheral immune alterations characteristic of AD. Importantly, the identified microbial-metabolite signature offers strong potential as a non-invasive fecal biomarker panel for AD risk stratification or early detection. These findings support the broader hypothesis that AD involves gut–brain metabolic disruption and may be modifiable through microbiome-targeted interventions.

Citation

Xi J, Ding D, Zhu H, et al. Disturbed microbial ecology in Alzheimer’s disease: evidence from the gut microbiota and fecal metabolome. BMC Microbiol. 2021;21:226. doi:10.1186/s12866-021-02286-z

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