Environmental triggers and future risk of developing autoimmune diseases: Molecular mechanism and network toxicology analysis of bisphenol A

Bisphenol A (BPA), a chemical compound in plastics and resins, widely exist in people's production and life which have great potential to damage human and animal health. It has been proved that BPA could affect human immune function and promote the occurrence and development of autoimmune diseases (ADs). However, the mechanism and pathophysiology remain unknown. Therefore, this study aims to advance network toxicology strategies to efficiently investigate the putative toxicity and underlying molecular mechanisms of environmental pollutants, focusing on ADs induced by BPA exposure. Leveraging databases including ChEMBL, STITCH, SwissTargetPrediction, GeneCards, and OMIM, we identified potential targets associated with BPA exposure and ADs, including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), multiple sclerosis (MS), Hashimoto's thyroiditis (HT), inflammatory bowel disease (IBD), and type 1 diabetes (T1D). Subsequent refinement using STRING and Cytoscape software highlighted core targets respectively, and Metascape was utilized for enrichment analysis. Gene expression data from the GEO database revealed the upregulation or downregulation of these targets across these ADs. Molecular docking performed with Autodock confirmed robust binding between BPA and core targets, notably PPARG, CTNNB1, ESR1, EGFR, SRC, and CCND1. These findings suggest that BPA exposure may serve as an environmental trigger in the development of autoimmunity, underscoring potential environmental risk factors for the onset of autoimmune conditions. Graphic abstract Potential mechanisms influencing ADs through BPA exposure. • BPA exposure may serve as an environmental trigger in the development of autoimmunity. • Core targets, PPARG, CTNNB1, ESR1, EGFR, SRC, and CCND1, were identified for BPA-induced immune dysregulation. • A robust in silico framework is established to predict toxicological impacts of environmental pollutants like BPA. • Preliminary data were offered to guide future animal studies and enhance the translation of computational predictions to real-world applications.