Effect of PET-MPs exposure on the toxicology of PCOS: a multi-platform computational toxicology investigation

Polyethylene terephthalate microplastics (PET-MPs) function as endocrine-disrupting agents that interfere with steroidogenesis and folliculogenesis, potentially contributing to polycystic ovary syndrome (PCOS). This study integrates computational toxicology and machine learning to delineate the mechanisms linking PET-MP exposure to PCOS pathogenesis. We conducted systematic multi-omics analysis by merging PET-MP-associated targets from ChemBL, PubChem, SwissTargetPrediction, SuperPred, and GeneCards with PCOS-related genes from GeneCards and the Comparative Toxicogenomics Database. Differential expression and weighted gene co-expression network analysis (WGCNA) were then applied to ovarian transcriptome datasets (GSE106724 and GSE137684). LASSO regression was used to prioritize hub genes, which underwent validation via diagnostic nomograms, molecular docking, molecular dynamics simulations, single-cell expression analysis, immune microenvironment profiling, and pathway enrichment. The results identified 22 overlapping genes connecting PET-MP exposure to PCOS, with RAB9A and MAOB highlighted as potential diagnostic biomarkers that appear to influence inflammatory responses, disrupt steroid hormone homeostasis, and induce mitochondrial dysfunction. Single-cell analysis revealed hub gene enrichment in ovarian granulosa cells (GCs), indicating targeted impacts on the follicular microenvironment, while immune profiling showed macrophage and γδ T cells as possible mediators of PET-MP-induced PCOS. Molecular docking and dynamics simulations demonstrated stable binding affinities of PET-MPs to RAB9A and MAOB. Overall, these findings position RAB9A and MAOB as environmental susceptibility biomarkers associating PET-MP exposure with PCOS development, providing molecular insights for targeted interventions.