ArticleFrontiers in molecular biosciences2026
Exploring the gut microbiota-microbial metabolites-targets regulatory network in metabolic dysfunction-associated steatotic liver disease.
Article in Frontiers in molecular biosciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD), which has emerged as a significant global public health concern. The regulatory role of gut microbiota and their metabolites in the pathogenesis of MASLD has attracted significant attention. Methods: Mendelian randomization (MR) analysis was performed to identify gut microbiota that were causally associated with MASLD. Evaluate the metabolites derived from the microbiota and predict their targets. Obtaining overlapping targets between metabolites and MASLD. The core targets were screened by protein-protein interaction (PPI) network, and functional enrichment analysis were performed. Binding interactions between metabolites and targets are validated through molecular docking. Meanwhile, the MASLD animal model was used to verify the expression differences of the core targets. Finally, the regulatory network of gut microbiota-metabolites-targets was constructed. Results: We identified 11 gut microbiota causally linked to MASLD by MR analysis. And 19 kinds of microbial metabolites were obtained. Enrichment analysis revealed that the intersection targets were concentrated cholesterol metabolism, PPAR and HIF-1 signaling pathways. Four core targets were identified, including ACE, HMGCR, PPARA and PPARG. Through molecular docking simulations, we predicted that there is potential stable binding affinity between the core targets and metabolites. Notably, a marked difference expression of key target genes was identified in the MASLD mice. Conclusion: Gut microbiota and microbial metabolites played an important role in the development of MASLD. This involved a multi-target and multi-pathway regulatory network, providing new evidence for the mechanism research and targeted intervention of MASLD.
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