BMI-dependent methylation and clinical signatures in North Indian women with PCOS
Kajal Rawat, Arushi Sandhu, Anil Kumar, Lekha Saha, Rama Walia, Pradip Kumar Saha, Alka BhatiaBackground 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.