Host-microbiome asynchronous decoupling reveals systemic metabolic allostatic overload mediated by gut genomic potential degradation
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Zhe Wang1, Xingzhou Xu2, Shipeng Shang3
1School of Basic Medicine, Qingdao Medical College, Qingdao University, Qingdao, 266071, China.
Background & Aims:
Metagenomic aging clocks predict chronological age but lose explanatory power during midlife (35-65 years). We hypothesized that cumulative allostatic load drives microenvironmental alterations, leading to asynchronous decoupling of metagenomic and metabolomic profiles.
Methods:
A metagenomic clock was trained on a lifespan cohort (N = 4551) and evaluated in a midlife sub-cohort (N = 1868). Independent metagenomic (N = 843) and fecal metabolomic (N = 106) cohorts assessed functional and phenotypic trajectories. Within a paired multi-omics cohort (N = 99), Procrustes and spatial dispersion analyses quantified topological decoupling. Metabolic biological age gap (metBAG) and metabolome-wide association studies (MWAS) characterized allostatic load signatures.
Results:
The lifespan model achieved R2 = 0.444 (MAE = 13.09 years). In midlife, model fit decreased (R2 = 0.187), whereas MAE narrowed to 6.73 years, indicating greater phenotypic stability. Concurrently, core taxa (e.g., Bifidobacterium breve) exhibited age-related declines. Paired analysis revealed significant spatial decoupling; microbial dispersion exceeded metabolic dispersion, suggesting host metabolic remodeling buffers microbial divergence. Elevated metBAG correlated with clinical parameters. Under high allostatic load, 1,3,7-trimethyluric acid enrichment and all-trans retinoic acid depletion were associated with the systemic aging transition.
Conclusions:
We identified an asynchronous decoupling during midlife: basal microbial decline precedes systemic aging and is initially buffered by host metabolic remodeling. When allostatic load exceeds compensatory capacity, specific metabolite enrichment may accelerate systemic aging. This framework facilitates sub-health quantification and informs microbiome-targeted interventions.
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