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Gut Microbiome Alterations Precede Cerebral Amyloidosis and Microglial Pathology in a Mouse Model of Alzheimer’s Disease 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: 2020-01-01

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
Mus musculus

What was studied?

This study investigated gut microbiome alterations in Alzheimer’s disease using APP/PS1 transgenic mice to determine whether intestinal microbial changes emerge before hallmark neuropathology. Researchers performed longitudinal 16S rRNA sequencing of fecal samples collected at 1, 2, 3, 6, and 9 months of age. By pairing high-resolution microbial profiling with parallel measurement of amyloid plaque formation and microglial activation, the investigators aimed to determine temporal relationships between gut dysbiosis and central nervous system pathology. Immunohistochemistry of cortical tissue was used to quantify amyloid-beta deposition and plaque-associated microglial activity. The study’s design provides a developmental timeline showing when microbiome divergence begins relative to cerebral amyloidosis.

Who was studied?

Male APP/PS1 mice and age-matched wild-type littermates were studied under identical housing conditions to control for environmental influences on microbial communities. Sample sizes per age group ranged from 14–24 in young cohorts and 31–34 in the 6-month cohort, providing robust statistical power. Only male animals were used to minimize sex-driven microbiome variation and hormone-related differences in Alzheimer-like pathology. Fecal samples from individual mice were collected at each time point for microbiome sequencing, while matched brain tissue was processed for amyloid and microglial quantification to map microbiome shifts against disease progression.

Most important findings

Microbiome divergence appeared early—between 1 and 3 months—well before detectable cortical amyloid plaques or microglial activation. Beta-diversity analyses (PERMANOVA) demonstrated significant separation between APP/PS1 and wild-type microbiomes at 2 and 6 months. Several inflammation-associated taxa were altered:

AgeIncreased in APP/PS1Decreased in APP/PS1
1 monthEnterobacteriaceae
2 monthsVerrucomicrobiaceae, Prevotellaceae, Bifidobacteriaceae, Actinobacteria
3 monthsLachnospiraceae_UCG-001Ruminococcaceae_UCG_010
6 monthsEscherichia-Shigella, Akkermansia, Blautia, TuricibacterBacteroides, Rikenellaceae_RC9
9 monthsDesulfovibrio, Akkermansia, Clostridiales_vadinBB60_groupCarnobacteriaceae, Alistipes

Of particular relevance to microbiome signature databases, the study consistently observed increased Proteobacteria (including Escherichia-Shigella), Verrucomicrobia/Akkermansia, Blautia, and Desulfovibrio—a constellation associated with inflammatory potential. Amyloid plaques became prominent only at 6–9 months, aligning with more pronounced dysbiosis.

Key implications

The temporal pattern strongly suggests that gut dysbiosis precedes and potentially contributes to cerebral amyloidosis. Early expansion of Proteobacteria—including endotoxin-producing Enterobacteriaceae—supports a model where peripheral inflammatory drivers prime microglial reactivity and may accelerate amyloid accumulation. Later increases in Akkermansia, Desulfovibrio, and Blautia align with the shift toward inflammation-linked microbial communities observed in human Alzheimer’s disease. Clinically, these taxa are promising candidates for early microbiome-based biomarkers or targets for microbial modulation. This study reinforces the gut–brain axis as a mechanistic pathway in Alzheimer’s pathology and encourages exploration of microbiome-directed interventions before neurodegeneration becomes established.

Citation

Chen Y, Fang L, Chen S, et al. Gut microbiome alterations precede cerebral amyloidosis and microglial pathology in a mouse model of Alzheimer’s disease.BioMed Research International. 2020;2020:8456596. doi:10.1155/2020/8456596

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