Network toxicology and machine learning reveal the potential role of dioctyl terephthalate in systemic lupus erythematosus pathogenesis

Emerging evidence suggests that dioctyl terephthalate (DOTP) may serve as an environmental risk factor for multiple diseases. Here, we explore potential molecular associations between DOTP exposure and systemic lupus erythematosus (SLE) and identify candidate targets and pathways that may underlie these associations. Integrated network toxicology and transcriptomics identified SLE-associated targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed underlying mechanisms. Machine learning was used to prioritize candidate DOTP–SLE targets. CIBERSORT assessed target-immune cell infiltration relationships. Molecular docking evaluated DOTP-target binding affinities. We identified 39 DOTP-associated SLE targets. Enrichment analyses linked them to inflammatory cytokine production and immune activation. Protein-protein interaction (PPI) and machine learning prioritized six key targets (NFKB1, TLR4, CASP9, CDK5, DNMT1, PRKCD). Exploratory CIBERSORT analysis described associations with LM22-derived reference profiles, while ROC analysis characterized within-cohort discrimination and an exploratory nomogram summarized the combined candidate-gene pattern. Molecular docking predicted favorable binding interactions between DOTP and these key targets. Our research results suggest a potential link between DOTP exposure and SLE progression through specific genes and pathways, and molecular docking predicted favorable binding interactions between DOTP and the relevant SLE targets. The ROC and nomogram analyses provided supplementary within-cohort characterization of the prioritized candidate genes. This study provides mechanistic insights into DOTP-associated SLE and supports the development of targeted prevention strategies.