Integrated Human Organic Pollutant Exposome and Metabolome Analysis Reveals Biomarkers and Health Risks from Electronic Waste Exposure

Escalating global electronic waste (e-waste) generation contrasts with 200 chemicals), oxidative damage, and metabolome by integrating nontargeted and targeted screening methods. Results showed that exposure to pollutant mixtures was significantly associated with increased oxidative damage to nucleic acids and cholesterol. Moreover, these pollutant mixtures collectively explained 46.2% of the variance in urinary metabolome alterations among e-waste workers. The affected metabolites were primarily associated with inflammatory diseases, metabolic disorders, neurological conditions, and cancers. By identifying e-waste exposure characteristic pollutants, we further developed accurate e-waste exposure prediction models (AUC > 0.986; ACC > 0.938) and derived simplified prediction functions and diagnostic indexes with comparable efficacy, which performed well across populations and industrial settings. Overall, this study underscores the significant health risks of e-waste exposure in occupational workers and offers rapid screening tools for e-waste pollution in informal settings, advancing the repurposing of large-scale national exposure monitoring databases for pollution tracking.