Avin S Jamil1, Shahla K Alalaf2, Namir G Al-Tawil3, Talha Al-Shawaf4. 1. Department of Obstetrics and Gynecology, College of Medicine, Hawler Medical University, Khanzad Street, PO Box 383-65, Erbil, Iraq. avinsadiq_2008@yahoo.com. 2. Department of Obstetrics and Gynecology, College of Medicine, Hawler Medical University, Khanzad Street, PO Box 383-65, Erbil, Iraq. shahla_alaf@yahoo.com. 3. Department of Community Medicine, College of Medicine, Hawler Medical University, Erbil, Iraq. namiraltawil@yahoo.com. 4. Women's Health Research Unit, Centre for Primary Care and Public Health, Barts and The London Medical College, Queen Mary University, London, UK. talhayas@aol.com.
Abstract
PURPOSE: Polycystic Ovary Syndrome (PCOS) is the most common endocrine disturbances in women and is divided into different phenotypes. The aim of study is to compare the clinical and hormonal parameters among the four phenotypes of PCOS based on the Rotterdam criteria and with control group. METHODS: Women with PCOS (n = 263) confirmed based on the Rotterdam criteria and 263 women with no evidence of PCOS were recruited as controls using observational case-control study. Evaluation of clinical and hormonal parameters, and differences in anti-Mullerian hormone (AMH) were compared between four phenotypes of PCOS and controls. RESULTS: Women with phenotype A (olig-anovulation (O) + hyperandrogenism (H) + polycystic ovary morphology (P)) had significantly larger waist than phenotype D (O + P) and higher body mass index than phenotype C (H + P). The LH/FSH ratio was significantly higher in phenotype A than phenotype D and controls along with significantly higher serum total testosterone levels in phenotype A compared to the phenotype B (O + H), C, D, and controls. AMH was significantly higher with phenotype A, C, and D than in women phenotype B and controls. CONCLUSIONS: The highest AMH levels were found in phenotype A. Phenotype B similar to controls had significantly low AMH compared to other three PCOS phenotypes. Women in the phenotypes D and controls showed significantly lower levels of LH/FSH ratio, total testosterone, and free androgen index, and higher levels of FSH and SHBG compared with phenotype A (P < 0.001). In logistic regression analysis, AMH and LH were predictors for PCOS.
PURPOSE:Polycystic Ovary Syndrome (PCOS) is the most common endocrine disturbances in women and is divided into different phenotypes. The aim of study is to compare the clinical and hormonal parameters among the four phenotypes of PCOS based on the Rotterdam criteria and with control group. METHODS:Women with PCOS (n = 263) confirmed based on the Rotterdam criteria and 263 women with no evidence of PCOS were recruited as controls using observational case-control study. Evaluation of clinical and hormonal parameters, and differences in anti-Mullerian hormone (AMH) were compared between four phenotypes of PCOS and controls. RESULTS:Women with phenotype A (olig-anovulation (O) + hyperandrogenism (H) + polycystic ovary morphology (P)) had significantly larger waist than phenotype D (O + P) and higher body mass index than phenotype C (H + P). The LH/FSH ratio was significantly higher in phenotype A than phenotype D and controls along with significantly higher serum total testosterone levels in phenotype A compared to the phenotype B (O + H), C, D, and controls. AMH was significantly higher with phenotype A, C, and D than in women phenotype B and controls. CONCLUSIONS: The highest AMH levels were found in phenotype A. Phenotype B similar to controls had significantly low AMH compared to other three PCOS phenotypes. Women in the phenotypes D and controls showed significantly lower levels of LH/FSH ratio, total testosterone, and free androgen index, and higher levels of FSH and SHBG compared with phenotype A (P < 0.001). In logistic regression analysis, AMH and LH were predictors for PCOS.
Authors: Jayeon Kim; Jennifer E Mersereau; Nikhil Khankari; Patrick T Bradshaw; Lauren E McCullough; Rebecca Cleveland; Sumitra Shantakumar; Susan L Teitelbuam; Alfred I Neugut; Ruby T Senie; Marilie D Gammon Journal: Cancer Causes Control Date: 2016-01-21 Impact factor: 2.506
Authors: Thozhukat Sathyapalan; Ahmed Al-Qaissi; Eric S Kilpatrick; Soha R Dargham; Brian Keevil; Stephen L Atkin Journal: Sci Rep Date: 2018-02-28 Impact factor: 4.379
Authors: María L Sánchez-Ferrer; Ernesto De La Cruz-Sánchez; Julián J Arense-Gonzalo; María T Prieto-Sánchez; Itziar Bernabeu-González; Ana Carmona-Barnosi; Jaime Mendiola; Alberto M Torres-Cantero Journal: Int J Environ Res Public Health Date: 2021-03-14 Impact factor: 3.390
Authors: Aleksandra Maria Polak; Agnieszka Adamska; Anna Krentowska; Agnieszka Łebkowska; Justyna Hryniewicka; Marcin Adamski; Irina Kowalska Journal: J Clin Med Date: 2020-03-09 Impact factor: 4.241