EBioMedicine · 2026
Brain-gut crosstalk associated with brain ageing in young and mid-life adults: a multicohort cross-sectional study.
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Zhao Kanhao, Vignolle Gabriel A, Labus Jennifer S, Mayer Emeran A, Vaughan Allison, Dy Marika, Vora Priten, Hung Ming W, Vossel Keith, Gill Chris, Del Rio Daniele, Stanton Catherine, Ross R Paul, Cryan John F, Kaddurah-Daouk Rima, Zhang Yu, Church Arpana
Аннотация
BACKGROUND: Brain age deviation is a promising neuroimaging biomarker of brain health, but its relevance in young and mid-life adults and its biological underpinnings remain insufficiently characterised. We aimed to test whether a functional-connectivity-derived brain ageing index (BAI) captures reproducible variability in early brain ageing and whether it is associated with cognitive-affective function and gut-derived biological signatures.
METHODS: We analysed resting-state fMRI from a discovery cohort (n = 674) with validation in a replication cohort (n = 444) and an independent cohort (n = 344). Whole-brain functional connectivity was computed using a 100-region Schaefer parcellation, and Bayesian ridge regression was used to predict chronological age; BAI was defined as the age-bias-corrected residual (predicted brain age minus chronological age). We tested associations between BAI and cognitive and affective measures across cohorts. In the independent cohort, we applied multi-view sparse partial least squares to integrate stool metagenomic and metabolomic profiles with BAI, and performed KEGG pathway enrichment analyses on features with non-zero weights.
FINDINGS: Predicted brain age correlated with chronological age across cohorts (r = 0.50-0.59). Higher BAI was consistently associated with connectivity patterns involving posterior cingulate/praecuneus and medial frontal regions, poorer cognitive performance, particularly working memory and executive function, and greater depressive symptoms. Multi-omics integration identified microbial taxa and stool metabolites, including ceramides, 24-hydroxycholesterol, dicarboxylic acids, and inverse associations with estetrol, linked to BAI. Enrichment analyses suggested involvement of neuroimmune, vascular, synaptic, and mitochondrial pathways.
INTERPRETATION: A connectivity-derived BAI captures reproducible variability in early brain ageing and links large-scale brain network organisation to gut-derived biological signatures. These findings suggest that BAI captures individual variability associated with brain health-related phenotypes and support the potential association of peripheral brain-gut biological pathways in early brain ageing.
FUNDING: National Institutes of Health, National Institute on Ageing.
METHODS: We analysed resting-state fMRI from a discovery cohort (n = 674) with validation in a replication cohort (n = 444) and an independent cohort (n = 344). Whole-brain functional connectivity was computed using a 100-region Schaefer parcellation, and Bayesian ridge regression was used to predict chronological age; BAI was defined as the age-bias-corrected residual (predicted brain age minus chronological age). We tested associations between BAI and cognitive and affective measures across cohorts. In the independent cohort, we applied multi-view sparse partial least squares to integrate stool metagenomic and metabolomic profiles with BAI, and performed KEGG pathway enrichment analyses on features with non-zero weights.
FINDINGS: Predicted brain age correlated with chronological age across cohorts (r = 0.50-0.59). Higher BAI was consistently associated with connectivity patterns involving posterior cingulate/praecuneus and medial frontal regions, poorer cognitive performance, particularly working memory and executive function, and greater depressive symptoms. Multi-omics integration identified microbial taxa and stool metabolites, including ceramides, 24-hydroxycholesterol, dicarboxylic acids, and inverse associations with estetrol, linked to BAI. Enrichment analyses suggested involvement of neuroimmune, vascular, synaptic, and mitochondrial pathways.
INTERPRETATION: A connectivity-derived BAI captures reproducible variability in early brain ageing and links large-scale brain network organisation to gut-derived biological signatures. These findings suggest that BAI captures individual variability associated with brain health-related phenotypes and support the potential association of peripheral brain-gut biological pathways in early brain ageing.
FUNDING: National Institutes of Health, National Institute on Ageing.