Discovery of Distinct Protein Profiles Specific for PCOS With and Without IR by SELDI Mass Spectrometry

Abstract

To screen the serum protein expression profiling in polycystic ovary syndrome (PCOS) patients with and without insulin resistance (IR) states by surface-enhanced laser adsorption/ionization time of flight mass spectrometry (SELDI-TOF MS) to discover the discriminatory proteins. Cross-sectional study Proteomic spectra were generated by mass spectroscopy (surface-enhanced laser desorption and ionization) from Ciphergen Inc. Using Weak Cation Exchange (WCX2) chip, 30 cases of PCOS with IR, 30 cases of PCOS without IR and 30 cases of healthy women were studied by ProteinChip reader and Biomarker Wizard software. A bioinformatics tool, Support Vector Machine (SVM), was used to identify proteomic patterns that distinguish three groups from each other. At the M/Z values ranging from 2007.15 Da to 66641.60 Da, there are 231 proteins were filtered from captured proteins. The algorithm identified three cluster pattern which conclude three groups of proteins that could distinguish three groups significantly: Eight of 27 distinguish proteins were obviously different between PCOS IR and control. Their M/Z are 6628.672, 3400.33, 2025.78, 4136.755, 3469.457, 3265.445,3936.048 and 2383.455, respectively. Six of them were up-regulate; two of them are down-regulated. Those 8 proteins can be seen as a diagnostic computational model which can distinguish PCOS IR and normal group significantly. The corresponding, specificity, sensitivity and positive predict value were 83.33%, 80.00%, 86.67% and 84.62%, respectively; Six of 17 distinguish proteins were screened out and were significantly up-regulate compared PCOS without IR and normal. Their M/Z values are 6834.708, 2818.46, 6628.672, 3610.746, 3092.029 and 3286.68, respectively. The corresponding, specificity, sensitivity and positive predict value were 88.33%%,86.67%, 90.00% and 88.33%, respectively; PCOS IR and non IR group were also compared which result in selection of 3 proteins from 19 distinguish proteins and M/Z values are 9292.096, 2048.973 and 4178.517, respectively. All of them were up-regulate. This analysis model can distinguish PCOS IR and PCOS non-IR group significantly. The corresponding, specificity, sensitivity and positive predict value are 85. 00%,90.00%, 80.00% and 89.18%, respectively. There are different proteomic patterns in different disease state of PCOS. Using protein chip combined with SVM, computer diagnostic models were set up quickly and efficiency between PCOS with IR or PCOS without IR and normal, PCOS with IR and PCOS without IR. Those discriminatory proteins may help us to know the proteomic changes in serum and find out potential biomarker of PCOS and IR.