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Alzheimer's Association International Conference 2026

July 12-15, 2026 | London, United Kingdom, and Online

5689

Gut Resistome Signatures Distinguish Cognitively Impaired Individuals From Controls

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Poster Presenter

Rohit Shukla

Authors

Rohit Shukla

Part of Topic

Background

Growing evidence suggests that microbial dysbiosis in Alzheimer’s disease (AD) is accompanied by functional changes in the resistome. Alterations in antimicrobial resistance genes (ARGs) may reflect a shift from a stable, commensal-associated microbial community toward a dysbiotic and inflammation-prone environment. Therefore, resistome analysis provides an important functional perspective for understanding microbiome alterations across Controls vs Cognitively impaired (CI) participants.

Methodology

We analyzed the gut microbiome data of older adults from the MiaGB Consortium using whole-genome sequencing, comparing Controls (n=280) and CI (n=165) individuals. Participants were categorized based on the Montreal Cognitive Assessment (MoCA) assessments into Controls (Ctrl) and CI groups according to their MoCA scores. The abundance of ARGs was calculated using AMR++ software, and taxonomy analysis of bacteria was done.

Major ARG signatures in Controls and CI participants:

1. We observed distinct ARG patterns between Control and CI participants, suggesting resistome alterations in CI. ANT9, DFRF, Trimethoprim, and MLS23S were more strongly associated with CI participants. Their correlations with anaerobic and commensal bacteria may indicate dysbiotic ARG enrichment, mobile resistance gene transfer, and inflammation-associated resistome restructuring in CI.

2. DFRF and Trimethoprim resistance genes showed positive correlations with Eubacterium ramulus, Blautia wexlerae, and Dorea longicatena, but negative associations with Escherichia coli and MoCA scores. This suggests possible mobile resistance gene propagation in CI.

3. MLS23S showed positive associations with Ruminococcus and Blautia species, while showing negative associations with Escherichia coli and aminoglycoside resistance genes. This may indicate CI-specific ARG-bacteria network remodeling.

4. Aminoglycoside resistance genes were higher in Controls and positively associated with Escherichia coli, Streptococcus thermophilus, and MoCA scores. This may reflect a more stable, commensal-associated resistome in Controls.

5.TET40 was positively associated with Blautia wexlerae and Blautia luti, suggesting that its reduction in CI may reflect the loss of beneficial butyrate-producing commensals.

Conclusion:

Overall, the ARG analysis clearly suggests that Control and CI participants have distinct resistome profiles. The enrichment of mobile resistance genes in CI may indicate dysbiosis, ARG mobility, and inflammation-associated resistome disruption, while Controls appear to maintain a more stable and commensal-associated resistome.

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