Wu Guo-Yong, Pang Jing-Zhuo, Cheng Chao, Lu Jian-Jun, Ma Jun, Gu Yong, Zhong Fu-Tian, Luo Hong-He
Department of Cardiothoracic Surgery, First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China.
Zhonghua Yi Xue Za Zhi. 2009 Aug 18;89(31):2184-7.
To identify the significant protein peaks and establish the diagnostic model of myasthenia gravis (MG) by serum proteomics profiling analysis.
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.
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.
The serum protein profiling can be a novel, effective and sensitive tool to screen for MG-related protein peaks and establish a diagnostic model.
通过血清蛋白质组图谱分析，识别重症肌无力（MG）的显著蛋白峰并建立诊断模型。
采用表面增强激光解吸电离飞行时间质谱（SELDI-TOF MS）技术检测56例MG患者和16例健康对照者的血清样本。识别差异表达的蛋白峰以建立MG诊断模型，并进行初步验证。
在56例MG患者和16例健康对照者的血清蛋白图谱中发现38个具有显著差异的特异性蛋白峰。系统优化后确定了M4168.94和M1122.57这2个蛋白峰，并用于构建区分56例患者与16例对照者的MG诊断模型。
血清蛋白质图谱可作为一种新型、有效且灵敏的工具，用于筛选与MG相关的蛋白峰并建立诊断模型。
