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脑脊液蛋白质指纹图谱技术在结核性脑膜炎诊断中的作用
Application of Cerebrospinal Fluid Protein Fingerprint Model in Diagnosis of Tuberculous Meningitis
【摘要】 [目的]研究脑脊液蛋白质指纹图谱技术在结核性脑膜炎(tubercular meningitis,TBM)诊断中的作用。[方法]应用表面增强激光解吸电离飞行时间质谱技术(surface-enhanced laser desorption/ionization time of flight mass spectrometry,SELDI-TOF-MS)检测80例脑脊液标本,其中TBM30例、化脓性脑膜炎30例及同期排除中枢感染的上呼吸道感染病例20例,用Biomarker Wizard软件分析找出差异蛋白峰,蛋白峰差异的比较使用Biomarker Patterns 5.0软件进行统计判别,建立决策树诊断模型,并通过盲法验证评价其准确性和有效性。[结果]蛋白质组谱图分析发现有9个差异显著的蛋白峰(P<0.01),4个在TBM组中高表达,m/z分别为15920.00,32540.50,7967.66,8046.85;有4个在TBM组中低表达,其m/z为8762.66,9411.40,6840.92,6649.47。由m/z为8046.85,15920.00及32540.50建立的决策树模型对TBM的诊断准确率为90%。通过盲法验证模型对TBM的诊断准确率为85%。[结论]由3个差异蛋白峰构成的TBM蛋白质指纹图谱诊断模型为TBM的诊断提供了新的借鉴和参考。
【Abstract】 [Objective] To find new biomarkers and to establish cerebrospinal fluid protein fingerprint model for early diagnosis of tuberculous meningitis.[Methods] 80 cerebrospinal fluid samples(including 30 cases of tuberculous meningitis,30 cases of purulent meningitis,and 20 excluded central infection) were tested by surface enhance laser desorption/ionization time of flight-mass spectrometry(SELDI-TOF-MS).The data of spectra were analyzed by bioinformatics tools like Biomarker Patterns 5.0 and discriminant analysis to establish diagnostic model. [Results] 9 protein features were stably detected in 80 cerebrospinal fluid samples,in which 4 protein features had higher expression(m/z 15920.0,32540.5,7967.66 and 8046.85,respectively) and lower expression(m/z8762.66,9411.4,6840.92 and 6649.47,respectively). The detective model combined with 3 biomarkers(m/z 8046.85,15920.0 and 32540.5) could differentiate tuberculous meningitis with accuracy of 90%. The double blind validation showed an accuracy of 90%. [Conclusion] The detective model established by 3protein features may be a novel method for diagnosis of tuberculous meningitis.
【Key words】 tuberculous meningitis; cerbrospinal fluid; SELDI-TOF-MS; protein fingerprint; different protein peak;
- 【文献出处】 浙江中医药大学学报 ,Journal of Zhejiang Chinese Medical University , 编辑部邮箱 ,2013年12期
- 【分类号】R529.3
- 【被引频次】2
- 【下载频次】64