How to Screen and Prevent Metabolic Syndrome in Patients of PCOS Early: Implications From Metabolomics

Background: Polycystic ovary syndrome (PCOS) is a complex reproductive endocrine disorder，with an increased risk of type 2 diabetes mellitus and cardiovascular disease, of which metabolic syndrome (MS) is an indispensable springboard to communicate PCOS and various comlications. Our aim was to study the potential metabolic characteristics of PCOS-MS, and identify sensitive biomarkers so as to provide targets for clinical screening, diagnosis and treatment. Methods: : 44 PCOS patients with MS, 34 PCOS patients without MS and 32 healthy controls were studied. Plasma samples of subjects were tested by ultra performance liquid chromatography (UPLC) system combined with LTQ-orbi-trap mass spectrometry. The changes of metabolic characteristics from PCOS to PCOS-MS were systematically analyzed. Correlations between differential metabolites and clinical characteristics of PCOS-MS were assessed. Differential metabolites with high correlation were further evaluated by the receiver operating characteristic (ROC) curve to identify their sensitivity as screening indicators. Results: : There were significant difference in general characteristics, reproductive hormone and metabolic parameters in PCOS-MS group when compared with PCOS group and healthy controls. We found 30 differential metabolites which were involved in 23 pathways when compared with PCOS group. The metabolic network further reflects the metabolic environment, including the interaction between metabolic pathways, modules, enzymes, reactions and metabolites.In the correlation analysis, 17 pairs of correlation coefficient between differential metabolites and clincal parameters were greater than 0.4, involving 11 metabolites that has the potential to be a marker for clinical diagnosis. They were assessed by ROC whose area under curve (AUC) were all greater than 0.7, with a good sensitivity. Furthermore, combinational metabolic biomarkers, such as glutamic acid+leucine+phenylalanine and carnitine C 4: 0+carnitine C18:1+carnitine C5:0 are expected to be sensitive combinational biomarkers in clinical practice. Conclusion: Our study provides a new insight to understand the pathogenesis mechanism, and the discriminating metabolites may help screen high-risk of MS in patients with PCOS and provide sensitive biomarkers for clinical diagnosis.