Clustering Identifies Subtypes With Different Phenotypic Characteristics in Women With Polycystic Ovary Syndrome
Authors' conclusion
Reproductive and metabolic traits not used for subtyping differed significantly in the subtypes. These findings suggest that the subtypes capture distinct PCOS causal pathways.
Study context
- Population
- Girls and women of European ancestry aged 13 to 45 years with polycystic ovary syndrome (PCOS) (Rotterdam criteria) attending a university hospital for reproductive endocrinology screening, February 1993–February 2021; 1067 also fulfilled NIH criteria1,067 met NIH criteria
- Participants
- 2,502 participants
- Exposure
- Metabolic vs reproductive vs background PCOS subtypes
- Outcome
- Identification of distinct PCOS subtypes using cluster analysis
Methodological detailssingle-centre (university hospital), hierarchical clustering
- Single-centre (university hospital)
- Hierarchical clustering
Main finding
As reported in the abstract
PCOS subtypes identified by clustering
- Reproductive subtype: highest total follicle count (TFC) and anti-Müllerian hormone (AMH) levels, in addition to high luteinizing hormone (LH) and sex hormone-binding globulin (SHBG)
- all P < .001
- Metabolic subtype: higher LDL and higher systolic and diastolic blood pressure, in addition to high body mass index (BMI) and insulin
- all P < .001
Observational data: associations, not effects.
Original publication
Clustering Identifies Subtypes With Different Phenotypic Characteristics in Women With Polycystic Ovary Syndrome. J Clin Endocrinol Metab. Published 16 May 2024. doi:10.
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