肾结核尿液蛋白指纹图谱诊断模型的研究
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摘要
目的：检测肾结核患者尿液中蛋白质指纹图谱,筛选特异性蛋白标记物,构建肾结核早期诊断模型并分析其临床意义。方法：收集新疆医科大学第一附属医院2010年7月-2010年12月经手术病理证实的肾结核患者术前尿液标本25例,作为病例组；健康体检者15例及非肾结核其他泌尿系疾病患者8例的尿液标本作为对照组。采用SELDI-TOF-MS蛋白芯片技术进行尿液蛋白图谱检测,将筛选出的差异蛋白用ZUCI-PDAS软件包数据分析系统进行处理。运用遗传算法(genetic arithmetic, GA)结合支持向量机(support vector machine, SVM)运算建立肾结核尿液蛋白指纹图谱诊断模型,并用盲法验证其诊断价值。结果：比较肾结核组及对照组尿液蛋白指纹图谱时共筛选出87个差异蛋白峰(P＜0.05)。选取M/Z为11837,11721,4748,11926,4769,1513共6个特异性蛋白标记物用于构建诊断模型。留一法交叉验证该诊断模型的灵敏度为84.62%,特异度为84.62%,约登指数为0.692,阳性预测值为84.62%,阴性预测值为84.62%,留一法盲法验证该诊断模型的灵敏度为83.33%,特异度为80.00%,约登指数为0.633,阳性预测值为83.33%,阴性预测值为80.00%。结论：SELDI-TOF-MS蛋白芯片技术结合生物信息学可以检测肾结核患者尿液蛋白指纹图谱,筛选出了特异性的蛋白标记物,并建立了肾结核早期诊断模型且有较好的诊断价值。
Objective:To detect the specific protein expression in the urine of renal tuberculosis, screen relatively specifical markers,and then build models for the early diagnosis of renal tuberculosis and analyze its clinical significance. Methods:Urine samples from 25 renal tuberculosis patients, which were confirmed by pathology,and the control group (including 15 healthy volunteers and 8 patients with other urogenital diseases) were obtained from First Affiliated Hospital of Xinjiang Medical University during July of 2010 to December of 2010.Urine protein fingerprint was examined using surface enhanced laser desorption/ionization time of flight-mass spectrometry (SELDI-TOF-MS) ProteinChip technology,Data was analyzed by ZUCI-protein chip data analyze system (ZUCI-PDAS) and the renal tuberculosis early diagnostic model was established by genetic (GA) combined support vector machine (SVM) and blind test its diagnostic value. Results:87 different protein peaks were identified from the two groups of Urine protein fingerprints(P<0.05). From this process,6 differential proteins (whose m/z peaks were 11837,11721,4748,11926,4769,1513, respectively) were selected to establish the diagnostic model for renal tuberculosis. Specificity、sensitivity、positive and negative predictive value was 84.62%,respecttively.The youden's index was 0.692.The blind test generated a sensitivity of 83.33%,a specificity of 80.00%,youden's index was 0.633, positive predictive value was 83.33% and negative predictive value 80.00%. Conclusion: SELDI-TOF-MS ProteinChip technology can pick out renal tuberculosis specific biomarkers from the urine of patients, establish renal tuberculosis early diagnosis model and having better diagnostic value.
Objective:To detect the specific protein expression in the urine of renal tuberculosis, screen relatively specifical markers,and then build models for the early diagnosis of renal tuberculosis and analyze its clinical significance. Methods:Urine samples from 25 renal tuberculosis patients, which were confirmed by pathology,and the control group (including 15 healthy volunteers and 8 patients with other urogenital diseases) were obtained from First Affiliated Hospital of Xinjiang Medical University during July of 2010 to December of 2010.Urine protein fingerprint was examined using surface enhanced laser desorption/ionization time of flight-mass spectrometry (SELDI-TOF-MS) ProteinChip technology,Data was analyzed by ZUCI-protein chip data analyze system (ZUCI-PDAS) and the renal tuberculosis early diagnostic model was established by genetic (GA) combined support vector machine (SVM) and blind test its diagnostic value. Results:87 different protein peaks were identified from the two groups of Urine protein fingerprints(P<0.05). From this process,6 differential proteins (whose m/z peaks were 11837,11721,4748,11926,4769,1513, respectively) were selected to establish the diagnostic model for renal tuberculosis. Specificity、sensitivity、positive and negative predictive value was 84.62%,respecttively.The youden's index was 0.692.The blind test generated a sensitivity of 83.33%,a specificity of 80.00%,youden's index was 0.633, positive predictive value was 83.33% and negative predictive value 80.00%. Conclusion: SELDI-TOF-MS ProteinChip technology can pick out renal tuberculosis specific biomarkers from the urine of patients, establish renal tuberculosis early diagnosis model and having better diagnostic value.
引文
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[5]Vna Kooyk Y,Gejitenbeek TB.DC-SIGN:eseape mechanism of pathogens[J]. Nat Rev Immunol.2003,3(9):697-709.
[6]吴阶平.吴阶平泌尿外科学[M]:下册.济南：山东科技出版社,2004.595-609.
[7]Issaq H,Conrads T,Prieto D,et al.SELDI-TOF-MS for diagnostic proteomic[J]. Anal Chem,2003,75(7):148-155.
[8]Kas K.On the technicalities of discovering and applying protein biomarkers for cancer prevention[J].Eur J Cancer Prevention,2004,13(5):437-446.
[9]Gustafsson JO,Oehler MK,Ruszkiewicz A,et al.MALDI Imaging Mass Spectrometry (MALDI-IMS) Application of Spatial Proteomics for Ovarian Cancer Classification and Diagnosis[J].Int J Mol Sci.2011,12(1):773-94.
[10]孟君,刘丽华,单保恩,等.应用MALDI-TOF-MS技术建立贲门癌血清蛋白指纹图谱诊断模型[J].中国癌症杂志,2010,20(12)：881-886.
[11]Schwamborn K, Krieg RC, Grosse J, et al. Serum proteomic profiling in patients with bladder cancer[J]. Eur Urol,2009,56(5):989-996.
[12]Liu LH, Shan BE, Tian ZQ, et al. Potential biomarkers for esophageal carcinoma dete-cted by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry [J]. Clin Chem Lab Med,2010,48(6):855-861.
[13]Zhu H,Synder M.ProteinChiP technology.Curr OPin ChemBiol,2003,7(1):55-63.
[14]Khasnobis S,Escuyer VE,Chatterjee D.Emerging therapeutic targets in tuberculo sis: Post-genomic era[J].Expert Opin Ther Targets,2002,6(1):21-40.
[15]Gallagher J,Clitfon-Hadley RS.Tuberculosis in badgers;a review of the disease and its significance for other animals[J]. Res Vet Sci,2000,69(3):203-217.
[16]袁鹏飞,杨炎刚,郭建举.肾结核误诊分析[J].中国综合临床,2003,19：617.
[17]林芝,黎承杨,潘正故,等.肾结核72例临床分析[J].现代泌尿外科杂志,2005,10(2)：92-93.
[18]任选义,黄随福,窦建伟,等.晚期肾结核诊断新特征与治疗分析(附39例报告)[J].医学信息(手术学分册),2008,21(5)：395-397.
[19]Link S SJ.Genitourinary tuberculosis[J].Curr Opin Urol,2001,11:93-98.
[20]项小丰,刘燕.利用PCR反应检测肾结核病人尿标本结核菌的探讨[J].吉林医药学院学报,2006,27(4)：210-211.
[21]周述岭,胡胜利,王有宏,等.肾结核的影像表现与鉴别诊断[J].医学影像学杂志,20-10,(20)11：1664-1667.
[22]张亚雄,孙建新,党笑坤,等.肾结核72例超声诊断分析[J].中国误诊学杂志,2010,10(33)：8250-8251.
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