Elucidating the effects of probiotics on metabolic dysfunction-associated steatotic liver disease: a meta-analysis
摘要
The gut microbiota plays a crucial role in the pathogenesis of metabolic dysfunction-associated steatotic liver disease (MASLD). This meta-analysis evaluates the efficacy of probiotics, prebiotics, and symbiotics in improving liver biomarkers, including liver enzymes, hepatic steatosis, fibrosis, and stiffness, based on randomised controlled trials (RCTs) from the past decade. A systematic search of PubMed, ScienceDirect, Cochrane Library, and ClinicalTrials.gov identified eligible RCTs reporting liver biomarkers, including aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT), hepatic steatosis, fibrosis, and stiffness. Effect sizes were calculated using Hedges' g in MetaEssentials 1.5 software under a random-effects model. Heterogeneity was assessed via I2 and T2 statistics, and publication bias was examined using funnel plots, Egger's regression, and the trim-and-fill method. Twenty-six RCTs, including 766 MASLD patients in the probiotic intervention arm, were analysed. Probiotic interventions significantly reduced AST (Hedges' g = -1.30, p < 0.005), ALT (Hedges' g = -1.20, p < 0.001), and GGT (Hedges' g = -1.08, p = 0.009). Improvements were also observed in hepatic steatosis and fibrosis. Subgroup analyses highlighted superior efficacy for multi-strain probiotic blends, while dosage and intervention duration showed no significant moderating effects. A unique strength of this meta-analysis is its focus on baseline-to-endpoint comparisons within the probiotic arm, complemented by a separate placebo subgroup analysis to account for placebo effects. Probiotics and symbiotics show significant potential in improving MASLD biomarkers, with strain-specific and regional effects emerging as critical determinants of efficacy. Future research should prioritise optimising probiotic formulations, expanding prebiotic evaluations, and tailoring interventions to individual patient profiles for enhanced clinical outcomes.