Characterizing plasma phospholipid fatty acid profiles of polycystic ovary syndrome patients with and without insulin resistance using GC-MS and chemometrics approach

Abstract

Polycystic ovary syndrome (PCOS), a heterogeneous endocrine and metabolic disorder, is the leading cause of infertility in women of reproductive age. Insulin resistance (IR) occurs in 50-70% of women with PCOS. In this study, we aimed to characterize the plasma phospholipid fatty acid profile for PCOS patients with and without IR, as well as for the early prognosis of PCOS and its IR complication. A gas chromatography-mass spectrometry (GC-MS) followed by multivariate statistical analysis was established to globally characterize the phospholipid fatty acid profiles in plasma from non-IR PCOS, IR PCOS, and eligible healthy controls, and subsequently discovered fatty acid biomarkers. A total of 22 fatty acids were identified and quantified. Their proportions varied among three groups, suggesting each group has its own fatty acid pattern. Orthogonal partial least squares discriminant analysis (OPLS-DA) according to their fatty acid profiles showed that 29 tested samples could be clearly differentiated according to groups. More importantly, nervonic acid (C24:1 n-9) and dihomo-γ-linolenic acid (C20:3 n-6) were identified as the potential fatty acid biomarkers of PCOS and its IR complication, respectively, for their most contribution to group separation. Pearson correlation analysis indicated that C24:1 n-9 and C20:3 n-6 were well correlated with clinical characteristics of PCOS and IR indicators, respectively. These findings demonstrated that GC-MS-based plasma phospholipid fatty acid profile might provide a complementary approach for clinical diagnosis of PCOS and its IR complication.

Keywords: Gas chromatography–mass spectrometry; Insulin resistance; Multivariate statistical analysis; Plasma phospholipid fatty acid profile; Polycystic ovary syndrome.