Literature DB >> 25662806

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

Chu-Chun Huang1, Yin-Jing Tien2, Mei-Jou Chen3, Chun-Houh Chen2, Hong-Nerng Ho4, Yu-Shih Yang4.   

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 (≧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 INTERESTS: This study was supported by grant NSC 100-2314-B002-027-MY3 from the National Science Council of Taiwan. TRIAL REGISTRATION NUMBER: Nil.
© The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  PCOS; SHBG; generalized association plots; metabolic syndrome

Mesh:

Substances:

Year:  2015        PMID: 25662806     DOI: 10.1093/humrep/dev010

Source DB:  PubMed          Journal:  Hum Reprod        ISSN: 0268-1161            Impact factor:   6.918


  14 in total

1.  Chronically elevated androgen and/or consumption of a Western-style diet impairs oocyte quality and granulosa cell function in the nonhuman primate periovulatory follicle.

Authors:  Cecily V Bishop; Taylor E Reiter; David W Erikson; Carol B Hanna; Brittany L Daughtry; Shawn L Chavez; Jon D Hennebold; Richard L Stouffer
Journal:  J Assist Reprod Genet       Date:  2019-06-11       Impact factor: 3.412

Review 2.  Emerging Roles of Anti-Müllerian Hormone in Hypothalamic-Pituitary Function.

Authors:  Anne-Laure Barbotin; Maëliss Peigné; Samuel Andrew Malone; Paolo Giacobini
Journal:  Neuroendocrinology       Date:  2019-07-05       Impact factor: 4.914

3.  Western-style diet, with and without chronic androgen treatment, alters the number, structure, and function of small antral follicles in ovaries of young adult monkeys.

Authors:  Cecily V Bishop; Fuhua Xu; Jing Xu; Alison Y Ting; Etienne Galbreath; Whitney K McGee; Mary B Zelinski; Jon D Hennebold; Judy L Cameron; Richard L Stouffer
Journal:  Fertil Steril       Date:  2015-12-21       Impact factor: 7.329

4.  Distinct subtypes of polycystic ovary syndrome with novel genetic associations: An unsupervised, phenotypic clustering analysis.

Authors:  Matthew Dapas; Frederick T J Lin; Girish N Nadkarni; Ryan Sisk; Richard S Legro; Margrit Urbanek; M Geoffrey Hayes; Andrea Dunaif
Journal:  PLoS Med       Date:  2020-06-23       Impact factor: 11.069

5.  Evaluation of Biochemical Hyperandrogenism in Adolescent Girls with Menstrual Irregularities.

Authors:  Hale Göksever Çelik; Engin Çelik; Ibrahim Polat
Journal:  J Med Biochem       Date:  2018-01-01       Impact factor: 3.402

Review 6.  Ameliorating Effects of Natural Antioxidant Compounds on Female Infertility: a Review.

Authors:  Jitender Kumar Bhardwaj; Harish Panchal; Priyanka Saraf
Journal:  Reprod Sci       Date:  2020-09-15       Impact factor: 3.060

7.  Functional microarray analysis of differentially expressed genes in granulosa cells from women with polycystic ovary syndrome related to MAPK/ERK signaling.

Authors:  Chen-Wei Lan; Mei-Jou Chen; Kang-Yu Tai; Danny Cw Yu; Yu-Chieh Yang; Pey-Shynan Jan; Yu-Shih Yang; Hsin-Fu Chen; Hong-Nerng Ho
Journal:  Sci Rep       Date:  2015-10-13       Impact factor: 4.379

8.  Elevated prenatal anti-Müllerian hormone reprograms the fetus and induces polycystic ovary syndrome in adulthood.

Authors:  Brooke Tata; Nour El Houda Mimouni; Anne-Laure Barbotin; Samuel A Malone; Anne Loyens; Pascal Pigny; Didier Dewailly; Sophie Catteau-Jonard; Inger Sundström-Poromaa; Terhi T Piltonen; Federica Dal Bello; Claudio Medana; Vincent Prevot; Jerome Clasadonte; Paolo Giacobini
Journal:  Nat Med       Date:  2018-05-14       Impact factor: 53.440

9.  Improving the accuracy and efficacy of diagnosing polycystic ovary syndrome by integrating metabolomics with clinical characteristics: study protocol for a randomized controlled trial.

Authors:  Cheng-Ming Ni; Wen-Long Huang; Yan-Min Jiang; Juan Xu; Ru Duan; Yun-Long Zhu; Xu-Ping Zhu; Xue-Mei Fan; Guo-An Luo; Yi-Ming Wang; Yan-Yu Li; Qing He; Lan Xu
Journal:  Trials       Date:  2020-02-11       Impact factor: 2.279

10.  Genotype based Risk Predictors for Polycystic Ovary Syndrome in Western Saudi Arabia.

Authors:  Sherin Bakhashab; Nada Ahmed
Journal:  Bioinformation       Date:  2019-12-10
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