Theaimofthepresentstudywastoidentifypotential serum biomarkers for insulin resistance (IR) in patients with polycystic ovary syndrome (PCOS) by comparing the differencesinserumproteinexpressionlevelsbetweenPCOSpatients with and without IR. PCOS patients aged from 18 to 35 years were recruited at Guangdong Women and Children's Hospital from January, 2013 to February, 2014. A total of 218 PCOS patients were enrolled and divided into the insulin resistance (PCOS-IR) and non-insulin resistance (PCOS-NIR) groups according to their homeostasis model assessment of insulin resistance. Two-dimensional difference gel electrophoresis (2D-DIGE) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS/MS) techniques were used to identify differences in protein expression levels between the PCOS-IR and PCOS-NIR groups. The present study demonstrated that the total cholesterol (TCH), triglycerides (TG), low-density lipoprotein (LDL), fasting plasma glucose (FPG), 3-h blood glucose (3hBG) and uric acid (UA) levels in the PCOS-IR group were higher than those in the PCOS-NIR group (P<0.05). Between the PCOS-IR and PCOS-NIR groups, a total of 20 differentially expressed protein spots were detected by 2D-DIGE. Among these, 4 proteins, namely afamin, serotransferrin, complement C3 and apolipoprotein C3 (APOC3), were also identified by MALDI-TOF-MS/MS. The alteration of APOC3 was further confirmed by western blot analysis and enzyme–linked immunosorbent assay (ELISA). The present study also confirmed that the expression level of APOC3 was positively associated with the homeostasis model assessment of insulin resistance (HOMA-IR). On the whole, the data indicate that APOC3 may be a potential diagnostic marker for PCOS-IR patients.
CITATION STYLE
Li, L., Zhang, J., Zeng, J., Liao, B., Peng, X., Li, T., … Liang, Z. (2020). Proteomics analysis of potential serum biomarkers for insulin resistance in patients with polycystic ovary syndrome. International Journal of Molecular Medicine, 45(5), 1409–1416. https://doi.org/10.3892/ijmm.2020.4522
Mendeley helps you to discover research relevant for your work.