Protein expression profilings of polycystic ovary syndrome / 北京大学学报(医学版)

ABSTRACT

Objective: To screen out serum protein profiling of polycystic ovary syndrome(PCOS) by surface - enhancedlaser desorption/ ionization time of flight mass spectrometry (SELDI-TOF MS) for discovering the discriminatory proteins. Methods: Thirty one women with PCOS and thirty healthy women were detected by Weak Cation Exchange(WCX2)chip. ProteinChip reader and Biomarker Wizard software from Ciphergen Inc were combined with a bioinformatics method (support vector machines, SVM ) to analyze protein fingerprinting. Results: There were 4 proteins which were obviously different between the PCOS group and the control. Three of them were up-regulated, and one down-regulated. To set up a analysis model by SVM using the 4 proteins could successfully distinguish between PCOS and the normal control. The corresponding sensitivity, specificity and positive predict value were 86.7%, 83.3%, 87.2%, resectively. Conclusion: Using ProteinChip technology can screen out serum discriminatory proteins quickly and efficiently. Combined with SVM, an optimal fingerprinting model has been set up, which can easily predict PCOS. In disease state of PCOS, there are significant variations which consist of four proteins. To investigate those four discriminatory proteins, especially the protein m/z 6 628 may be of benefit to pathogenic study and the development of biomarkers for PCOS.