摘要
目的通过对比重型肝炎患者血清中的低相对分子质量蛋白质谱,分析其与病情严重程度及预后的关系。方法28例重型肝炎患者根据疾病转归的不同分为存活组和死亡组,利用表面增强激光解吸离子化飞行时间串联质谱技术检测患者血清中相对分子质量位于1000～10000之间的蛋白质指纹图谱,筛选出两组图谱的差异峰,再结合人工神经网络技术建立重型肝炎的预后预测模型。结果比较重型肝炎存活组与死亡组的血清蛋白质指纹图谱,发现质量电荷比为4095、2860、5179、3954等38个峰的峰强度在两组间的差异有统计学意义(P<0.05)。利用这些差异峰建立的预测模型对重型肝炎预后的预测正确率达85.7%,在该预测模型中,权重最大的5个峰的质量电荷比依次为4095、5198、3954、5354、4967。结论重型肝炎存活组与死亡组患者血清中低相对分子质量蛋白质有明显差异,这些差异蛋白与患者疾病的预后相关。
Objective To profile low molecular weight proteins in the serum that were associated with prognosis of severe hepatitis by protein chip technique. Methods Twenty-eight cases of severe hepatitis were divided into 2 subgroups： survival group and non-survival group, according to the outcome of the disease. The serum samples were analyzed with the surface enhanced laser desorption ionization-time of flight-mass spectrometry（SELDI-TOF MS） to obtain a quantitative proteomic fingerprints with molecular masses ranging from 1 000 to 10 000. The discriminating peaks of two groups were identified. Artificial neural network was then used to construct a model for predicting prognosis. Results By comparing serum proteomic fingerprints of survival group with non-survival group, the intensities of 38 peaks such as M/Z 4 095, M/Z 2 860, M/Z 5 179 and M/Z 3 954 were observed to be significantly different between two groups （P 〈 0.05）. Predictive models derived from these discriminating peaks could predict the prognosis of severe hepatitis with the accuracy of 85.7 %. The 5 most important peaks in the predictive model were M/Z 4 095. M/Z 5 198. M/Z 3 954. M/Z 5 354 and M/Z 4 967. Conclusions Differentially expressed low molecular weight serum proteins are observed between survival group and non-survival group; and these molecules were related to the prognosis of the disease.
出处
《中华传染病杂志》
CAS
CSCD
北大核心
2007年第6期327-331,共5页
Chinese Journal of Infectious Diseases
基金
"十五"国家科技攻关项目(2004BA706B02-01)
