Gut microbiome and metabolite profiles are associated with subsequent histologic MASH in a longitudinal mouse model.

UNLABELLED: Detecting metabolic dysfunction-associated steatohepatitis (MASH) before fibrosis develops remains a major challenge. We used a longitudinal streptozotocin/high-fat diet (STAM/HFD) mouse model to identify microbial and metabolic features that emerge before histological MASH onset. Integrative 16S rRNA and untargeted LC-MS/MS analyses revealed microbial and metabolite shifts weeks before disease development. Lachnospiraceae and Oscillospiraceae were enriched in non-MASH mice and were negatively correlated with fatty acids elevated under MASH conditions. Bile acid and fatty acid metabolites enriched under MASH and non-MASH states varied with collection time, showing that diurnal variation strongly shapes biomarker profiles. Analysis of a human MAFLD cohort confirmed higher abundances of Lachnospiraceae bacteria in healthy participants. Our results identify early microbial and metabolic features that are associated with subsequent histologic MASH onset and reveal how temporal factors influence biomarker detection. These time-sensitive features, together with cross-species concordance in a human MAFLD cohort, lay the groundwork for developing and validating microbiome-based diagnostics and circadian-informed interventions that target the gut-liver axis to prevent metabolic liver disease. IMPORTANCE: Metabolic dysfunction-associated steatohepatitis (MASH) often develops silently, limiting opportunities for early intervention before fibrosis occurs. In this study, we identify gut microbial taxa and stool metabolites that are associated with future histologic MASH development in a longitudinal mouse model. We show that members of the Lachnospiraceae and Oscillospiraceae families are enriched in mice that remain disease-free and that members of the Lachnospiraceae family exhibit similar patterns in a human MAFLD cohort. Importantly, we demonstrate that time of sample collection has a strong effect on metabolomic profiles, with disease-associated lipid and bile acid signals detectable only at specific sampling times. These findings highlight circadian timing as a critical variable in microbiome-based biomarker discovery and support the development of time-aware diagnostic strategies for early MASH risk assessment.