摘要目的 应用血清蛋白质图谱分析,寻找有意义蛋白峰,建立重症肌无力(MG)的诊断模型,用于MG的诊断.方法 利用表面增强激光解吸离子化飞行时间质谱(SELDI-TOF MS)技术对56份MG患者术前血液标本和16份正常对照组血液标本进行蛋白质图谱分析,找寻出有差异蛋白峰.建立MG诊断模型并初步验证.结果 56例MG患者和16名正常对照蛋白质图谱分析中,能找到38个特异性差异蛋白峰.系统优化出M4168.94、M1122.57两个蛋白峰构建的MG诊断模型可将56例MG患者和16名正常对照进行正确分组.结论 用血清蛋白质图谱可筛选出与MG发病相关的蛋白峰,初步建立MG诊断模型,有望成为诊断MG的一种新方法.

abstractsObjective To identify the significant protein peaks and establish the diagnostic model of myasthenia gravis (MG) by serum proteomics profiling analysis. Methods The serum samples from 56 MG patients and 16 healthy controls were detected by the technology of surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF MS). The differentially expressed protein peaks were identified to establish a MG diagnostic model And preliminary validation was performed. Results Thirty-eight specific protein peaks with significant differences were found in the serum protein pattern of 56 MG patients and 16 healthy controls. Systemic optimization identified 2 protein peaks of M4168.94 and M1122. 57. And they were used to build the MG diagnostic model of differentiating 56 cases from 16 controls. Conclusion The serum protein profiling can be a novel, effective and sensitive tool to screen for MG-related protein peaks and establish a diagnostic model.