Microbiome-host interactions in cognitive aging

Cognitive aging is shaped by systemic interactions among the brain, peripheral organs, immune system, metabolism, and gut microbiome. This thesis investigates these interactions in an aging mouse cohort using multi-omics analyses and constraint-based metabolic modeling, with particular focus on host-microbiome co-metabolism at the colonic interface.

Integration of cognitive performance with transcriptomic, epigenomic, metagenomic, metabolomic, and model-derived features showed that host molecular signatures related to inflammation, immune activity, and tissue development and maintenance were most strongly associated with cognitive decline. Microbiome-associated features were weaker in the integrated analysis but provided complementary functional information.

A joint colon-microbiome metabolic model was subsequently developed to identify cognition-associated host-microbial metabolic interactions. The strongest co-metabolic signal involved deoxyribose-phosphate metabolism, linking host deoxyribose catabolism with bacterial deoxyribose anabolism and suggesting a potential connection between nucleotide recycling and central carbon metabolism. Additional associations involved stress-related, redox, bile-acid, nucleotide, and osmolyte metabolism.

Finally, the software MeMoMe was developed to automate the merging of metabolic models across different biochemical namespaces. Benchmarking showed that automated merging substantially reduces manual effort while preserving comparable functional predictions.

Overall, the thesis supports a systemic view of cognitive aging in which microbiome contributions emerge most clearly when interpreted in the context of host physiology and metabolism.