ECE2022 Eposter Presentations Reproductive and Developmental Endocrinology (93 abstracts)
Association of SPISE and HOMA-IR indexes with metabolic characteristics of different age groups of women with polycystic ovary syndrome
Milica Opalic 1 , Sanja Ognjanovic 1 , Bojana Popovic 1 , Dusan Ilic 1 , Jelica Bjekic - Macut 2 , Valentina Elezovic 1 , Lena Radic 1 , Danijela Vojnovic Milutinovic 3 , Olivera Stanojlovic 4 & Djuro P. Macut 1
1Clinic for Endocrinology, Diabetes and Metabolic Diseases, University Clinical Centre of Serbia, Department for Endocrine Tumors and Hereditary Cancer Syndromes, Belgrade, Serbia; 2CHC Bezanijska Kosa, Belgrade, Serbia; 3IBISS, University of Belgrade, Belgrade, Serbia; 4Institute of Physiology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
Introduction: Polycystic ovary syndrome (PCOS) is the most prevalent endocrinopathy among women during reproductive age. PCOS cardinal manifestations include hyperandrogenism, oligo/anovulation, and/or polycystic ovarian morphology, and is closely linked to metabolic disorders such as obesity and insulin resistance (IR). It was observed that single-point insulin sensitivity estimator (SPISE) index is associated with metabolic abnormalities and could predict glucose regulation during life. The aim of this study was to analyze metabolic and hormonal characteristics among two age groups of women with PCOS and their association with SPISE index and homeostatic model assessment of insulin resistance (HOMA-IR) index.
Subjects and methods: We analyzed 150 women with PCOS diagnosed using ESHRE/ASRM. Patients were divided into two age groups, younger/equal to 30 years (PCOS-A, n = 74, age: 23.3±3.1 years, BMI: 23.1± 4.5 kg/m2), and older than 30 years (PCOS-B, n = 74, age: 35.7±4.9 years, BMI: 25.3± 6.4 kg/m2). We measured lipids indices, glucose and insulin during oral glucose tolerance test (OGTT), while HOMA-IR and SPISE index were calculated. Statistical analysis was performed by SPSS software.
Results: Both groups had similar body mass index (P=0.071) and waist circumference (77.0±12.9 cm vs. 82.0±15.3 cm, P=0.07), but the incidence of obesity was higher in PCOS-B group (PCOS-A 5.9% vs. PCOS-B 23.5%, P=0.004). Women in PCOS-B in comparison to PCOS-A had higher total cholesterol (P<0.001), LDL cholesterol (P=0.022) and triglycerides (P=0.012). Incidence of impaired glucose tolerance was same in both groups, and no patient had diabetes. Although fasting glucose was statistically higher in PCOS-B group (P<0.001), there was no between-groups differences in levels of fasting insulin (P=0.12) and HOMA-IR (P=0.151). SPISE index was statistically lower in PCOS-B (P=0.022), showed negative correlation with HOMA-IR, baseline glucose and glucose in 120 minute of OGTT in PCOS-B (r=-0.483, P=0.004, r=-0.360, P=0.007, r=-0.337, P=0.004, respectively) and negative correlation with only fasting insulin in PCOS-A (r=-0.284, P=0.024).
Conclusion: PCOS is characterized by the existence of risk factors including obesity, elevated glucose and lipid concentrations all leading to an increased risk of cardiometabolic vascular disorders. The assessment of different indicators during time-line of PCOS could be used for prediction of long-term metabolic outcomes.
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Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
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