中华皮肤科杂志 ›› 2013, Vol. 46 ›› Issue (1): 52-53.

• 研究报道 • 上一篇    下一篇

尿蛋白组学筛选检测过敏性紫癜患者的肾损害

孙秀坤1,唐旭2,沈宏2,余捷凯3   

  1. 1. 杭州市第三人民医院
    2. 杭州市第三人民医院皮肤科
    3. 杭州浙江大学医学院附属第二医院肿瘤研究所
  • 收稿日期:2012-04-05 修回日期:2012-05-18 出版日期:2013-01-15 发布日期:2013-01-01
  • 通讯作者: 沈宏 E-mail:shenhongsh@medmail.com.cn
  • 基金资助:
    杭州市科技局资助项目

Urinary proteomics for the prediction of nephritis in patients with Henoch-Sch-nlein purpura

  • Received:2012-04-05 Revised:2012-05-18 Online:2013-01-15 Published:2013-01-01

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摘要： 目的 表面增强激光解析电离飞行时间质谱技术（SELDI-TOF－MS）筛选早期过敏性紫癜肾炎患者尿液中的特异标志蛋白。方法 CM10（弱阳离子交换表面）蛋白芯片结合SELDI-TOF－MS技术，检测60例过敏性紫癜患者（30例伴发紫癜性肾炎，30例不伴肾炎）尿液中的蛋白质质谱，用浙江大学肿瘤研究所蛋白芯片数据分析系统筛选过敏性紫癜肾炎特异的尿液蛋白标志物。结果 共检测到154个经过信噪比和强调过滤的高质量质谱蛋白质峰，从中筛选出2个表达差异显著（P < 0.05）的蛋白标志物。用遗传算法结合支持向量机模型的方法筛选出最佳模型，用留一法评估模型的预测效果为敏感性84%，特异性71％。结论 尿蛋白质谱与生物信息学分析方法对早期过敏性紫癜肾炎的检测具有一定的敏感性和特异性。

关键词: 紫癜，过敏性, 肾疾病, 尿, 蛋白组

Abstract: SUN Xiu-kun*, TANG Xu, SHEN Hong, YU Jie-kai. *Department of Dermatology, Third People′s Hospital of Hangzhou, Hangzhou 310009, China Corresponding author: SHEN Hong, Email: shenhangzhou@sina.com 【Abstract】 Objective To identify novel biomarkers from urinary protein profiles for the early diagnosis of nephritis in patients with Henoch-Sch?觟nlein purpura by surface enhanced laser desorption/ionization time of flight-mass spectrometry （SELDI-TOF-MS） technique. Methods Urine samples were collected from 60 untreated patients with Henoch-Sch?觟nlein purpura, including 30 patients with nephritis and 30 without. SELDI-TOF-MS technique was used to characterize the protein profile in these urine samples, and the Zhejiang University Cancer Institute - Protein Chip Data Analysis System （ZUCI-PDAS） to identify urine protein markers and construct diagnostic model for nephritis in patients with Henoch-Sch?觟nlein purpura. Results Totally, 154 mass peaks were identified with high quality, and two proteins at a mass-to-charge ratio （m/z） of 2454.971 and 2439.686 showed significantly differential expression between the two groups of patients （P < 0.05）. Seven biomarkers were used to establish a diagnostic model. As estimated by the leave-one-out cross-validation, the diagnostic model distinguished patients with nephritis from those without with a specificity of 71% and sensitivity of 84%. Conclusions The developed diagnostic model based on SELDI-TOF-MS technique and bioinformatics is somewhat specific and sensitive for the prediction of nephritis in patients with Henoch-Sch?觟nlein purpura.