Linking bisphenol a exposure to MASLD: insights from network toxicology and machine learning based on NHANES 2005–2012 data

Abstract Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD), one of the most prevalent chronic liver diseases worldwide, has a pathogenesis that remains incompletely understood. In recent years, Bisphenol A (BPA) has been recognized as an emerging pathogenic factor for MASLD as an environmental contaminant. By integrating multiple advanced methodologies including Network Toxicology, Machine Learning, Molecular Docking, and Molecular Dynamics Simulation, this study systematically elucidates the molecular mechanisms underlying BPA-induced MASLD. Through analysis of NHANES data, we identified a significantly positive correlation between BPA levels and MASLD risk. Integration of multiple databases identified 34 potential BPA-related targets. KEGG enrichment analysis revealed the critical role of the PI3K/AKT signaling pathway in MASLD, with COL1A1, COL1A2, and IGF1 serving as core targets that drive disease progression. Immune cell infiltration analysis demonstrated that BPA regulates immune cell function via the PI3K/AKT pathway, thereby promoting the onset and development of MASLD. These findings reveal the complex mechanisms underlying BPA-induced MASLD and provide novel therapeutic targets, along with theoretical support for the early screening and precision treatment of this disease.