UHPLC/Q-TOFMS-based plasma metabolomics of polycystic ovary syndrome patients with and without insulin resistance

摘要

Polycystic ovary syndrome (PCOS), characterized with menstrual irregularities, hyperandrogenism and ovulatory abnormalities, is usually companied with insulin resistance (IR) and accounts for one of the most prevalent reproductive dysfunction of premenopausal women. Despite accumulating investigations, diagnostic standards of this pathological condition remain obscure. The aim of present study is to characterize the plasma metabolic characteristics of PCOS patients with and without IR, and subsequently identify the potential biomarkers for the diagnosis of PCOS and its IR complication. A total of 59 plasma samples from eligible healthy controls (CON, n=19), PCOS patients without IR (non-IR PCOS, n=19) and PCOS patients with IR (IR PCOS, n=21) were profiled by an ultra high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC/Q-TOFMS) followed by multivariate statistical analysis. Compared to the healthy controls, significant decrease in the levels of phosphocholines (PCs) and lyso PC (18:2), and increase in trilauric glyceride level were observed in the plasma of IR PCOS. Meanwhile, the significant increase in the levels of saturated fatty acids (palmitic acid and stearic acid) and decanoylcarnitine, and decrease in PC (36:2) and PS (36:0) were found in non-IR PCOS patients. Trilauric glyceride and decanoylcarnitine were identified as the potential biomarkers with the highest sensitivity and specificity for the diagnosis of PCOS patients with and without IR, respectively. Furthermore, based on these alterations of metabolites, MetPA network pathway analysis suggested a profound involvement of the abnormalities of glycerophospholipid, glycerolipid and fatty acid metabolisms in the pathogenesis of PCOS and IR complications. Collectively, LC-MS-based metabolomics provides a promising strategy for complementary diagnosis of PCOS and its IR complication and offers a new insight to understand their pathogenesis mechanisms. (C) 2016 Elsevier B.V. All rights reserved.