The FERM guild: a differentially correlated microbial module drives hypertension via metabolic flux perturbations
Wenkai Lai, Yuchen Zhang, Shaoping Huang, Shirong Lai, Fuxin Lin, Ziwei Wang, Shanwen Sun, Fenglong YangABSTRACT
Hypertension is a major risk factor for cardiovascular diseases, with changes in gut microbiota composition and function being closely associated with its onset and progression. However, the high inter-individual variability in gut microbiota complicates the identification of pathogenic mechanisms using traditional methods. In contrast, the smaller variability in gut microbial metabolites offers a more reliable and consistent basis for cross-individual comparisons. Parsimonious flux balance analysis (pFBA), integrated with double machine learning (DoubleML), identified 17 metabolites significantly associated with hypertension (
IMPORTANCE
Hypertension remains a major global public health burden; however, most studies on its relationship with the gut microbiota rely on traditional species-abundance analyses, which are limited by substantial inter-individual variability. In contrast, microbial metabolites show greater stability across individuals and thus offer a more reliable entry point for mechanistic research. By integrating metabolic modeling, causal inference, and network analysis, this study identified 17 key metabolites significantly associated with blood pressure and uncovered a functionally coordinated microbial community (FERM) whose contribution to critical metabolic fluxes (rather than its taxonomic abundance) was closely linked to hypertension. These findings reveal a metabolite-centered mechanism connecting microbial functions to host blood pressure regulation and provide new potential targets for microbiome-based interventions.