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Updated: Jan 17, 2026

Evaluation of Hepatic Glucose Production in a Polycystic Ovary Syndrome Mouse Model
Published on: March 5, 2022
Phenotypic variations in polycystic ovary syndrome: metabolic risks and emerging biomarkers
Yi-Cih Ma1,2, Kim-Seng Law2,3, Wen-Sheng Wang2
1Department of Obstetrics and Gynecology, China Medical University Hospital, Taichung, Taiwan.
Abstract:
Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder with diverse clinical manifestations and metabolic risks. The 2012 NIH phenotypic classification, based on the presence of hyperandrogenism (HA), ovulatory dysfunction, and polycystic ovarian morphology (PCOM), has enabled more nuanced characterization of PCOS into four phenotypes (A-D). Phenotypes A and B, both hyperandrogenic and anovulatory, are consistently associated with the highest metabolic risk, including insulin resistance, dyslipidemia, and increased prevalence of metabolic syndrome. Phenotype C, though ovulatory, still exhibits metabolic abnormalities due to androgen excess. In contrast, phenotype D, lacking hyperandrogenism, generally shows the mildest hormonal and metabolic profiles. This review outlines the evolving diagnostic landscape of PCOS, including the potential use of anti-Müllerian hormone (AMH) as a surrogate marker for PCOM. It explores hormonal and metabolic biomarkers, such as total and free testosterone, SHBG, LH/FSH ratio, HOMA-IR, and lipid parameters, in phenotype differentiation. Furthermore, emerging adipokines (e.g., adiponectin, chemerin, and ZAG) and inflammatory markers (e.g., CRP, IL-6, and TNF-α) provide additional insight into the metabolic heterogeneity of PCOS beyond obesity. Genetic and genomic studies have identified over 19 susceptibility loci involved in gonadotropin regulation, steroidogenesis, and insulin signaling, with distinct gene clusters aligning with adiposity, insulin resistance, and reproductive traits. MicroRNA signatures also show potential as phenotype-specific biomarkers. Recognizing phenotype-specific variations in PCOS is critical for individualized risk assessment and therapeutic strategies. Future research should prioritize standardized diagnostic criteria and large, diverse cohorts to validate emerging biomarkers and improve long-term outcomes for women with PCOS.
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