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Author Spotlight: Exploring Sex-Specific Glial Signatures and Therapeutic Leads for Alzheimer's Disease

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Published on: May 20, 2024

Identifying candidate gut microbiota indicators for Alzheimer's disease through integrated data.

Jing Wang^1,2, Hanting Liu³, Hao Lai²

¹Phase I clinical trial research ward, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.

|March 25, 2026

Summary

Researchers identified key gut bacteria linked to Alzheimer's disease (AD) and mild cognitive impairment (MCI). Specific bacterial genera show diagnostic potential for AD, offering new avenues for non-invasive biomarkers and therapies.

Keywords:

Alzheimer's disease candidate indicator discriminative model gut microbiota random forest

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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

Area of Science:

Microbiome research
Neurodegenerative disease biomarkers
Computational biology and bioinformatics

Background:

Alzheimer's disease (AD) is increasingly linked to gut microbiota dysbiosis.
Identifying reliable gut microbiota biomarkers is crucial for early AD diagnosis.
Previous studies often lack large-scale, multi-population data for robust biomarker discovery.

Purpose of the Study:

To characterize gut microbiota composition and diversity in AD patients across diverse populations.
To identify reliable gut microbiota indicators with diagnostic value for AD.
To explore the potential of these indicators for non-invasive AD diagnosis and targeted therapies.

Main Methods:

Integrated public data from AD dementia, mild cognitive impairment (MCI), and normal control (NC) groups.
Conducted microbiota composition, diversity (α-diversity), and network analyses.
Utilized seven common statistical methods to identify differential bacterial genera as candidate indicators.

Main Results:

The AD dementia group exhibited significantly lower α-diversity and reduced microbial network density compared to MCI and NC groups.
Identified 35 bacterial genera as candidate AD indicators, including novel findings for *RF39* and *Oligella*.
*Faecalibacterium* emerged as the top indicator overall, with population-specific key indicators like *Akkermansia* (Chinese) and *Collinsella* (Turkish/Kazakh).

Conclusions:

Gut microbiota alterations, including reduced diversity and network complexity, are characteristic of AD dementia.
A panel of 35 bacterial genera shows promise as diagnostic biomarkers for AD.
Findings support the development of non-invasive AD diagnostic tools and microbiota-targeted therapeutic strategies.