Relationship of Biological Markers of Body Fat Distribution and Corticosteroidogenic Enzyme Activities in Women with Polycystic Ovary Syndrome

Abstract

AbstractThe aim of the study is to determine the impact of different anthropometric measurements of fat distribution on baseline sex-steroid concentrations and corticosteroidogenic enzyme activity in women with polycystic ovary syndrome compared to those with regular menstrual cycles. The current cross-sectional study included 106 normal cycling controls and 268 polycystic ovary syndrome patients. Patients with polycystic ovary syndrome, diagnosed by Rotterdam criteria, were divided in normoandrogenemic (n=91) and hyperandrogenemic (n=177). Anthropometric, biochemical, and hormone parameters were assessed and correlated with corticosteroidogenic enzyme activities in all three groups. Corticosteroidogenic enzyme activities were calculated using product-to-precursor ratios. Regarding sex-steroids individually, anthropometric parameters correlated with the concentrations of several androgens in polycystic ovary syndrome patients, most of them in patients with biochemical hyperandrogenism. The androgen precursors androstenedione, 17-hydroxyprogesterone, and dehydroepiandrosterone were less correlated with anthropometric parameters. The 17,20 lyase activity, in both Δ4 and Δ5 pathways, correlated with several anthropometric measurements in normo- and hyperandrogenemic polycystic ovary syndrome patients. The 17,20 lyase enzyme activity (Δ4 pathway) also correlated with conicity index, visceral adiposity index, and lipid accumulation product in the control group. 17-Hydroxylase activity positively correlated with waist-height ratio in both polycystic ovary syndrome groups. In contrast, 17-hydroxilase negatively correlated with the conicity index. Anthropometric markers of adiposity are associated with androgen levels and their precursors in blood. Body fat distribution correlates with the activities of some steroidogenic enzyme in both normo-and hyperandrogenemic polycystic ovary syndrome phenotypes. The molecular mechanisms involved in these associations are largely unclear and more investigations are required.