Machine learning and SHAP-based identification of RNASE1 linking environmental endocrine-disrupting chemicals...

Environmental endocrine-disrupting chemicals (EDCs) are ubiquitous pollutants implicated in cardiometabolic disorders, yet their mechanistic contribution to atherosclerosis (AS) remains elusive. Seven prevalent EDCs - bisphenol A, dibutyl phthalate, di(2-ethylhexyl) phthalate, dioxins, polychlorinated biphenyls (PCBs), perfluorooctanoic acid and PFOS - were selected. Network toxicology integrated ChEMBL, STITCH and SwissTargetPrediction to compile human EDCs targets. Differentially expressed genes were derived from 3 Gene Expression Omnibus AS datasets after batch correction. Key genes were filtered by least absolute shrinkage and selection operator regression and support vector machine-recursive feature elimination (SVM-RFE) and intersected with EDCs targets. Diagnostic performance was evaluated by receiver operating characteristic analysis; functional relevance was assessed by KEGG-GSEA, and feature importance was quantified with SHapley Additive exPlanations (SHAP). A total of 1294 nonredundant EDCs target genes were enriched in lipid and AS and endocrine resistance pathways (FDR < 0.05). From 789 AS differentially expressed genes, least absolute shrinkage and selection operator and SVM-RFE converged on 11 robust candidates. Intersection with EDCs targets pinpointed NTRK3 and RNASE1. Receiver operating characteristic analysis yielded AUCs of 0.777 and 0.859, respectively, with a combined AUC of 0.871. GSEA indicated enrichment of cytokine/chemokine and NOD-like receptor signaling for both genes. SHAP scores highlighted RNASE1 as the dominant predictor (mean SHAP = 0.215), whereas NTRK3 contributed modestly (mean SHAP = 0.005). RNASE1 and NTRK3 were identified as key molecular links between endocrine-disrupting chemical exposure and AS. Among them, RNASE1 was revealed as a novel and dominant predictor, highlighting its unique mechanistic role and potential clinical utility in environmental cardiovascular risk stratification and targeted prevention.