Polycystic ovary syndrome (PCOS) is a common and heterogeneous disorder currently diagnosed only in reproductive-age women. Familial clustering and twin studies have provided strong evidence for a genetic contribution to PCOS pathogenesis. First-degree relatives, including males and non-reproductive-age females, have reproductive and metabolic phenotypes consistent with a genetic susceptibility to these traits. PCOS is now recognized as a complex trait influenced by both genetic and environmental factors. Genome-wide association studies have identified ∼30 loci linked to PCOS, implicating pathways involved in gonadotropin secretion and action, folliculogenesis, steroidogenesis, age at menopause, and carbohydrate metabolism. Next-generation sequencing has found rare variants in AMH , AMHR2 , and DENND1A , supporting these genes' central role in developing PCOS. Epigenetic mechanisms such as DNA methylation and non-coding RNAs influence gene regulation and may contribute to phenotypic heterogeneity. Unsupervised clustering has identified distinct reproductive and metabolic subtypes with unique genetic architectures, providing a biologically meaningful framework for classification. This shift from expert opinion-based diagnosis to data-driven classification has the potential to transform PCOS management and enable precision medicine approaches tailored to distinct subtypes of the disorder.
Louwers et al. (Fri,) studied this question.