UPLC/Q‑TOF‑MS based plasma metabolomics and clinical characteristics of polycystic ovarian syndrome.

Abstract

The present study aimed to develop novel diagnostic methods for polycystic ovarian syndrome (PCOS) by screening and identifying specific PCOS-associated metabolic markers using plasma metabolomics. Ultra-performance liquid chromatography/quadrapole-time of flight-mass spectrometry was adopted to establish the plasma metabolic fingerprint of 49 patients and 50 normal controls, in order to screen the potential metabolic markers. In addition, these markers were integrated with the clinical indexes, followed by focused analysis to obtain diagnostic markers. The present results demonstrated that not only was the concentration of palmitoyl sphingomyelin in plasma of patients with PCOS significantly increased; however, a statistically significant difference between the two PCOS subgroups was additionally demonstrated. At the same time, the concentrations of cyclic guanosine monophosphate (cGMP) and dehydroepiandrosterone sulphate in the plasma of patients of the subgroup 1 were significantly elevated. These markers were additionally integrated with the clinical index number of follicles in the left ovary and high-density lipoprotein (HDL-C), followed by receiver operating characteristic curve analysis, which demonstrated a diagnostic accuracy of ~90% in the control and the two subgroups. The integrated marker system consisting of palmitoyl sphingomyelin, cGMP and androsterone sulfate, as well as the number of left follicles and HDL-C may be used for the accurate diagnosis and classification of PCOS. These results confirmed that the abnormalities in hormone metabolism and lipid metabolism disorder were primarily involved in the onset of PCOS.