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Discovery and identification of serum potential biomarkers for pulmonary tuberculosis using iTRAQ-coupled two-dimensional LC-MS/MS

机译:使用iTRAQ耦合二维LC-MS / MS发现和鉴定血清肺结核潜在生物标志物

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摘要

Pulmonary tuberculosis (TB) caused by Mycobacterium tuberculosis is a chronic disease. Currently, there are no sufficiently validated biomarkers for early diagnosis of TB infection. In this study, a panel of potential serum biomarkers was identified between patients with pulmonary TB and healthy controls by using iTRAQ-coupled 2D LC-MS/MS technique. Among 100 differentially expressed proteins screened, 45 proteins were upregulated (>1.25-fold at p < 0.05) and 55 proteins were downregulated (<0.8-fold at p < 0.05) in the TB serum. Bioinformatics analysis revealed that the differentially expressed proteins were related to the response to stimulus, the metabolic and immune system processes. The significantly differential expression of apolipoprotein CII (APOCII), CD5 antigen-like (CD5L), hyaluronan-binding protein 2 (HABP2), and retinol-binding protein 4 (RBP4) was further confirmed using immunoblotting and ELISA analysis. By forward stepwise multivariate regression analysis, a panel of serum biomarkers including APOCII, CD5L, and RBP4 was obtained to form the disease diagnostic model. The receiver operation characteristic curve of the diagnostic model was 0.98 (sensitivity = 93.42%, specificity = 92.86%). In conclusion, APOCII, CD5L, HABP2, and RBP4 may be potential protein biomarkers of pulmonary TB. Our research provides useful data for early diagnosis of TB.
机译:由结核分枝杆菌引起的肺结核(TB)是一种慢性疾病。当前,没有足够有效的生物标志物可用于结核病感染的早期诊断。在这项研究中,通过使用iTRAQ耦合二维LC-MS / MS技术,在肺结核患者和健康对照之间鉴定出一组潜在的血清生物标志物。在筛选出的100种差异表达蛋白中,TB血清中有45种蛋白被上调(在p <0.05时> 1.25倍),而55种蛋白在p血清中被下调(p <0.05时<0.8倍)。生物信息学分析表明,差异表达的蛋白质与对刺激,代谢和免疫系统过程的反应有关。使用免疫印迹和ELISA分析进一步证实了载脂蛋白CII(APOCII),CD5抗原样(CD5L),透明质酸结合蛋白2(HABP2)和视黄醇结合蛋白4(RBP4)的显着差异表达。通过逐步逐步多元回归分析,获得了一组包括APOCII,CD5L和RBP4的血清生物标记物,以形成疾病诊断模型。诊断模型的接收器操作特征曲线为0.98(灵敏度= 93.42%,特异性= 92.86%)。总之,APOCII,CD5L,HABP2和RBP4可能是肺结核的潜在蛋白质生物标志物。我们的研究为结核病的早期诊断提供了有用的数据。

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