中文摘要：

目的探讨液态芯片结合基质辅助激光解析离子化飞行时间质谱（MALDI-TOF-MS）技术筛选慢性肾小球肾炎（CGN）患者的唾液蛋白质标记物并建立诊断模型,为CGN临床诊断提供依据。方法采集43例CGN患者和45例健康体检者的唾液标本,采用液态芯片（WCX磁珠）制备唾液样品,并结合MALDI-TOF-MS质谱仪对唾液标本进行蛋白质检测,筛选出2组间特异性表达差异蛋白,并结合生物信息学方法建立诊断模型。结果比较2组唾液蛋白质指纹图谱数据,共获得116个差异有统计学意义的蛋白峰（P〈0.05）,选择质荷比（m/z）为2 499.11、2 159.09、3 622.30Da的3个蛋白质峰用于构建最佳决策树模型,该诊断模型测试组总准确率为85.23%（75/88）,灵敏度为83.72%（36/43）,特异度为86.67%（39/45）。结论初步建立了CGN唾液蛋白质组诊断模型,为CGN的早期诊断提供了新的方法和途径。

英文摘要：

Objective To explore the specific biomarkers in saliva of Chronic Glomerulonephritis patients using matrix assisted laser desorption/ionization time-of-flight mass spectrometry,MALDI-TOF MS（MALDI-TOF-MS）technique and to establish diagnostic model.Methods The saliva protein fingerprints of 43 Chronic Glomerulonephritis cases and 45 healthy controls were detected by weak cationic-exchange magnetic beads（MB-WCX）and then analyzed by MALDI-TOF-MS.Then the specifically expressed differential proteins in two groups were used to establish the diagnostic model combined with bioinformatic methods.Results The saliva protein fingerprint data of the two groups were compared and 116 discrepant protein peaks were found（P〈0.05）.The 3peaks of m/z 2 499.11 Da,2 159.09 Da and 3 622.30 Da were used to build the best decision tree model.The accuracy,sensitivity and specificity of the diagnostic model were 85.23%（75/88）,83.72%（36/43）and 86.67%（39/45）respectively.Conclusion Preliminary saliva proteome diagnosis model of chronic glomerulonephritis was set up providing new ways and means for the early diagnosis of chronic glomerulonephritis.