CAJ | 학술논문

目的采用表面增强激光解吸离子化-飞行时间-质谱(surface enhanced laser desorption and ionization time of flight mass spectrometry,SELDI-TOF- MS)技术研究慢性肾衰竭(CRF)患者的尿液相关蛋白标志物.方法采集150例CRF患者和50例健康人的尿液,采用H4蛋白芯片技术进行尿液蛋白质组学研究；用蛋白芯片阅读器PBSII对芯片进行扫描、分析.结果 CRF组与健康对照组尿液样本的蛋白质图谱在质荷比(M/Z) 1000～20 000范围内检测到141个差异有统计学意义的蛋白峰(均P＜0.01).经生物信息学分析建立CRF尿液蛋白预测模型,得到M/Z 4649.81和M/Z 9536.92两个差异蛋白峰组成的生物标记物可以将CRF组和健康对照组样本较好地分类,其正确率为96.0％,敏感性为100.0％,特异性为94.7％.CRF组与健康对照组尿液中差异蛋白峰经SwissProt数据库鉴定,可能为17种蛋白质.结论筛选出CRF的尿液候选蛋白标志物并建立了CRF尿液蛋白预测模型,通过数据库对尿液候选蛋白标志物进行了鉴定,为CRF的早期临床诊断提供了依据.
목적 채용표면증강격광해흡리자화-비행시간-질보(surface enhanced laser desorption and ionization time of flight mass spectrometry,SELDI-TOF- MS)기술연구만성신쇠갈(CRF)환자적뇨액상관단백표지물.방법 채집150례CRF환자화50례건강인적뇨액,채용H4단백심편기술진행뇨액단백질조학연구；용단백심편열독기PBSII대심편진행소묘、분석.결과 CRF조여건강대조조뇨액양본적단백질도보재질하비(M/Z) 1000～20 000범위내검측도141개차이유통계학의의적단백봉(균P＜0.01).경생물신식학분석건립CRF뇨액단백예측모형,득도M/Z 4649.81화M/Z 9536.92량개차이단백봉조성적생물표기물가이장CRF조화건강대조조양본교호지분류,기정학솔위96.0％,민감성위100.0％,특이성위94.7％.CRF조여건강대조조뇨액중차이단백봉경SwissProt수거고감정,가능위17충단백질.결론 사선출CRF적뇨액후선단백표지물병건립료CRF뇨액단백예측모형,통과수거고대뇨액후선단백표지물진행료감정,위CRF적조기림상진단제공료의거.
Objective To investigate the associated protein markers in urine of patients with chronic renal failure (CRF) based on surface enhanced laser desorption and ionization time of flight mass spectrometry (SELDI-TOF MS)technique.Methods Urine samples were taken from 150 CRF patients and 50 healthy people,and investigated by proteomic techniques with H4 gene chip.Results Compared to healthy group,141 different protein peaks were identified within the range of 1000 to 20 000 M/Z in the protein map of CRF group,whose differences were all significant (all P＜0.01).The decision tree model for CRF urine was constructed after bioinformation analysis to significantly differentiate between CRF and healthy group.The accuracy rate,sensitivity and specificity of the decision tree model were 96.0％,100.0％ and 94.7％ respectively.In CRF group and healthy group,the different protein peaks in urine were identified to probably be 17 proteins with reference to SwissProt database.Conclusions Candidate protein markers in urine are screened and prediction model of CRF urine is established.The markers are identified with the database which provides a more accurate prediction and solid evidence for early diagnosis of CRF.