alexa Characterizing discrete subsets of polycystic ovary syndrome as defined by the Rotterdam criteria: the impact of weight on phenotype and metabolic features.
Diabetes & Endocrinology

Diabetes & Endocrinology

Journal of Steroids & Hormonal Science

Author(s): Welt CK, Gudmundsson JA, Arason G, Adams J, Palsdottir H,

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Abstract CONTEXT: The Rotterdam criteria for polycystic ovary syndrome (PCOS) defines discrete subgroups whose phenotypes are not yet clear. OBJECTIVE: The phenotypic characteristics of women in the PCOS subgroups defined by the Rotterdam criteria were compared. DESIGN: The study was observational. SETTING: Subjects were studied in an outpatient setting in Boston and Reykjavik. PATIENTS: Four subgroups of subjects with PCOS defined by 1) irregular menses (IM), hyperandrogenism (HA), and polycystic ovary morphology (PCOM, n = 298); 2) IM/HA (n = 7); 3) HA/PCOM (n = 77); and 4) IM/PCOM (n = 36) and a group of controls (n = 64), aged 18-45 yr, were examined. INTERVENTION: Subjects underwent a physical exam; fasting blood samples for androgens, gonadotropins, and metabolic parameters; and a transvaginal ultrasound. MAIN OUTCOME MEASURES: The phenotype was compared between groups. RESULTS: Ninety-seven percent of women with IM/HA had PCOM. Therefore, the groups with and without PCOM were combined. The Ferriman-Gallwey score and androgen levels were highest in the hyperandrogenic groups (IM/HA and HA/PCOM), whereas ovarian volume was higher in all PCOS subgroups compared with controls, as expected based on the definitions of the PCOS subgroups. Body mass index and insulin levels were highest in the IM/HA subgroup. CONCLUSIONS: Subjects with PCOS defined by IM/HA are the most severely affected women on the basis of androgen levels, ovarian volumes, and insulin levels. Their higher body mass index partially accounts for the increased insulin levels, suggesting that weight gain exacerbates the symptoms of PCOS. This article was published in J Clin Endocrinol Metab and referenced in Journal of Steroids & Hormonal Science

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