SELDI-TOF-MS筛选慢性阻塞性肺疾病血清标志蛋白的初步研究

目的:利用表面增强激光解吸电离飞行时间质谱技术(SELDI-TOF-MS)筛选慢性阻塞性肺疾病(COPD)血清特异标志物。方法:应用SELDI-TOF-MS技术检测30例COPD稳定期患者和30例健康对照者血清蛋白指纹图谱,采用Biomarker pattern软件进行分析,建立COPD的诊断模型。结果:COPD患者血清蛋白图谱与对照组相比,在相对分子质量2000-15 000范围内共检测到75个蛋白峰,发现19个有统计学差异的蛋白峰(P0.05)。通过对COPD组与对照组间的数据作进一步分析,经BPS软件分析,建立质荷比(M/Z)3 167、4 645的差异蛋白组成的诊断模型,其诊断敏感度为96.67%,特异度为96.67%。结论:SELDI-TOF-MS技术是一种快速、简单易行、用量少和高通量的分析方法。能直接筛选出COPD血清中特异表达标志物,用特异表达标志物建立的诊断模型能有效区分COPD患者与健康对照者,有望成为COPD诊断的辅助指标。

Application of SELDI-TOF-MS Technology Analyzing SerumProtein Profiling in Diagnosis of Chronic Obstructive Pulmonary Disease

Objective:To screen the serum protein biomarkers of chronic obstructive pulmonary disease (COPD) by using surface-enhanced laser adsorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology.Methods:SELDI-TOF-MS was used to analyze serum samples including 30 cases of stable COPD patients and 30 cases of healthy controls. Biomarker Pattern Software was used to establish a diagnostic pattern.Results:Compared with normal controls, 75 protein peaks were detected at the molecular range of 2 000-15000Da and nineteen protein biomarkers were identified. Analyzed by BPS, two protein peaks (M/Z 3 167,4 645) were chosen to build the model for COPD detection. The diagnostic model separated the COPD from the control samples with sensitivity of 96.67 % and specificity of 96.67 %.Conclusion:SELDI-TOF-MS is a quick, easy and practical, high throughput analytic method. It can detect biological markers of COPD, and it shows the diagnostic model established by distinguished proteomic peaks can discriminate COPD patients fromhealthy controls. It will provide a highly accurate approach for the diagnosis of COPD.