Symptom patterns and phenotypic subgrouping of women with polycystic ovary syndrome: Association between endocrine characteristics and metabolic aberrations

Chu Chun Huang, Yin Jing Tien, Mei Jou Chen, Chun Houh Chen, Hong Nerng Ho, Yu Shih Yang

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Study Question What are the potential endocrine characteristics related to risk and severity of metabolic disturbances in women with polycystic ovary syndrome (PCOS)? Summary Answer Women with PCOS could be subtyped into four subgroups according to heterogeneous endocrine characteristics and the major predictive endocrine factors for metabolic aberrations among different subgroups were free androgen index (FAI) and luteinizing hormone (LH) levels. What is Known Already Women diagnosed with PCOS present with highly heterogeneous phenotypes, including endocrine and metabolic aberrations. Different strategies have been proposed to predict the metabolic outcomes but whether the endocrine factors can solely predict the metabolic aberrations is still inconclusive. Study Design, Size, Duration A cross-sectional study including 460 patients recruited from a reproductive endocrinology outpatient clinic of a tertiary medical center. Participants/Materials, Setting, Methods Patients with PCOS diagnosed according to the 2003 Rotterdam criteria were studied. Clinical history recorded by questionnaires, anthropometric measurements, biochemistry tests after an overnight fast, and pelvic ultrasonography were collected from all patients. Main Results and The Role of Chance Applying a matrix visualization and clustering approach (generalized association plots), the patients were divided into four distinct clusters according to the correlation with four endocrine parameters. Each cluster exhibited specific endocrine characteristics and the prevalence of metabolic syndrome (MS) was significantly different among the clusters (P < 0.0001). The high-risk subgroups for MS included one cluster with higher mean (SD) FAI (39.6 (14.7) in cluster 4), and another one with lower mean (SD) FAI (10 (6.4) in cluster 2). A common endocrine characteristic of these two metabolically unhealthy clusters was relatively lower LH level. Contrarily, higher LH level (â ‰§ 15 mIU/ml) during early follicular phase was found to be the best indicator of the metabolically healthy cluster (cluster 1). While high FAI level did correlate with more severe metabolic aberrations, high LH level showed better predictive value than low FAI level to become a metabolically healthy cluster. Limitations, Reasons For Caution The results should be applied to other populations with caution due to racial or environmental differences. Another limitation is a lack of normal non-PCOS control in our study. Wider Implications of The Findings Stratifying women with PCOS into meaningful subtypes could provide a better understanding of related risk factors and potentially enable the design and delivery of more effective screening and treatment intervention. Study Funding/Competing Interest(S) This study was supported by grant NSC 100-2314-B002-027-MY3 from the National Science Council of Taiwan. TRIAL REGISTRATION NUMBER Nil.

Original languageEnglish
Pages (from-to)937-946
Number of pages10
JournalHuman Reproduction
Volume30
Issue number4
DOIs
Publication statusPublished - Sep 30 2015
Externally publishedYes

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Metabolic Syndrome X
Anthropometry
Endocrine System
Polycystic Ovary Syndrome
Luteinizing Hormone
Tertiary Care Centers
Androgens
Cluster Analysis
Young Adult
Body Mass Index
Cross-Sectional Studies
Phenotype
Follicular Phase
Organized Financing
Endocrinology
Ambulatory Care Facilities
Taiwan
Biochemistry
Ovary
Ultrasonography

Keywords

  • generalized association plots
  • metabolic syndrome
  • PCOS
  • SHBG

ASJC Scopus subject areas

  • Reproductive Medicine
  • Obstetrics and Gynaecology

Cite this

Symptom patterns and phenotypic subgrouping of women with polycystic ovary syndrome : Association between endocrine characteristics and metabolic aberrations. / Huang, Chu Chun; Tien, Yin Jing; Chen, Mei Jou; Chen, Chun Houh; Ho, Hong Nerng; Yang, Yu Shih.

In: Human Reproduction, Vol. 30, No. 4, 30.09.2015, p. 937-946.

Research output: Contribution to journalArticle

Huang, Chu Chun ; Tien, Yin Jing ; Chen, Mei Jou ; Chen, Chun Houh ; Ho, Hong Nerng ; Yang, Yu Shih. / Symptom patterns and phenotypic subgrouping of women with polycystic ovary syndrome : Association between endocrine characteristics and metabolic aberrations. In: Human Reproduction. 2015 ; Vol. 30, No. 4. pp. 937-946.
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