BACKGROUND: The adipokines leptin, adiponectin, and ghrelin are expressed not only in adipose tissue but also in the hypothalamic-pituitary-gonadal axis organs and the uterus. They regulate the gonadotropin-releasing hormone and gonadotropin secretion, steroidogenesis, folliculogenesis, and implantation, and serve as promising markers of assisted reproductive technology program outcomes. AIM: The aim of this study was to evaluate the dynamics of blood adipokine levels and their ratios during the controlled ovarian hyperstimulation in assisted reproductive technology programs depending on the onset of clinical pregnancy. MATERIALS AND METHODS: This study involved 51 patients undergoing infertility treatment using assisted reproductive technology in a short protocol with gonadotropin-releasing hormone antagonists. Depending on the onset of clinical pregnancy, two study groups were formed: non-pregnant (group 1, n = 22) and pregnant (group 2, n = 29). Blood leptin, adiponectin, and ghrelin levels were assessed using enzyme immunoassay at three points: assisted reproductive technology protocol start-up, the day of oocyte pick-up, and the day of embryo transfer. RESULTS: On the day of oocyte pick-up, patients in group 1 had higher leptin levels (5.47 ± 1.92 vs. 3.76 ± 0.75 ng/ml; p = 0.0004), leptin/adiponectin ratios (11.45 ± 4.50 vs. 4.73 ± 1.08; p 0.001), and leptin/ghrelin ratios (0.43 ± 0.17 vs. 0.24 ± 0.07; p 0.001). On the day of embryo transfer, patients in group 1 had higher levels of leptin (6.37 ± 2.13 vs. 3.29 ± 1.21 ng/ml; p 0.001) and adiponectin (0.75 ± 0.22 vs. 0.60 ± 0.09 ng/ml; p = 0.001), as well as ratios of leptin/adiponectin (9.06 ± 3.73 vs. 5.59 ± 2.32; p 0.001), leptin/ghrelin (0.48 ± 0.15 vs. 0.20 ± 0.07; p 0.001), and adiponectin/ghrelin (0.06 ± 0.02 vs. 0.04 ± 0.01; p 0.001). CONCLUSIONS: The data obtained indicate that blood adipokine levels change during the controlled ovarian hyperstimulation in assisted reproductive technology protocols depending on clinical pregnancy and can be used to predict its onset.
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