BMI-dependent methylation and clinical signatures in North Indian women with PCOS

Background and objectives Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine-metabolic disorder with unclear etiology, influenced by genetic, environmental, and epigenetic factors. This study investigated the role of gene-specific DNA methylation and transcriptional regulation in North Indian women with PCOS stratified by body mass index (BMI). Methods Thirty women with PCOS (19 obese, 11 non-obese) and 10 healthy controls (age-matched to both PCOS groups; BMI-matched to non-obese PCOS) were recruited. BMI stratification was intentional to assess obesity-specific epigenetic modifications. Clinical, hormonal, and metabolic parameters were assessed. Promoter-methylation and mRNA expression of 17 candidate genes involved in epigenetic regulation, steroidogenesis, insulin signalling, and cell proliferation were analysed using methylation-specific PCR and qRT-PCR. Correlation matrices were constructed to evaluate associations between methylation and clinical traits. Receiver operating characteristic (ROC) based modelling was used to assess the predictive utility of methylation markers. Results PCOS-obese participants exhibited significantly elevated testosterone, Luteinising Hormone (LH), and cholesterol levels compared to controls. Vitamin D₃ deficiency was observed in both PCOS subgroups. Epigenetic analysis revealed hypermethylation and downregulation of TET1 and INSIG1 , and hypomethylation-linked overexpression of SF1, CYP11A1, and cell cycle regulators. Correlation analyses revealed associative methylation expression signatures linked with key hormonal parameters ( e.g ., testosterone, LH/FSH ratio) and, to a lesser extent, metabolic traits (associative findings but not mechanistic conclusions). Interpretation and conclusions This integrative study highlights distinct methylation-expression signatures as hypothesis-generating markers that show statistical association with certain clinical traits, particularly in the obese-PCOS subgroup, but require validation in larger cohorts.