Phenotypic variations in polycystic ovary syndrome: metabolic risks and emerging biomarkers

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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Publication Details

Journal
Journal of Endocrinology
Published
2025-09-19
DOI
https://doi.org/10.1530/joe-25-0226
Citations
1
Primary Topic
Ovarian function and disorders
Type
article
Field-Weighted Citation Impact
1.70
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article

Phenotypic variations in polycystic ovary syndrome: metabolic risks and emerging biomarkers

Kim-Seng Law, Yi-Cih Ma, Wensheng Wang, Hsun‐Ming Chang
1 citations
Journal of Endocrinology
Ovarian function and disorders
1.70
article

Phenotypic variations in polycystic ovary syndrome: metabolic risks and emerging biomarkers

Kim-Seng Law, Yi-Cih Ma, Wensheng Wang, Hsun‐Ming Chang
article en
1 citations

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.

Journal of EndocrinologyVol. 267(1)
National Chung Hsing University (TW), China Medical University (TW), China Medical University Hospital (TW), Tungs' Taichung MetroHarbor Hospital (TW)
Openalex Percentile: Top 13%
Ovarian function and disorders
1.70
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