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Analysis of human liver disease using a cluster of differentiation (CD) antibody microarray

机译:使用分化(CD)抗体簇微阵列分析人类肝脏疾病

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Background: A CD antibody microarray has been previously developed allowing semi-quantitative identification of greater than 80 CD antigens on circulating leucocytes from peripheral blood samples. This assay, which uses a live cell-capture technique, enables an extensive leucocyte immunophenotype determination in a single analysis and to date this has been used successfully to characterise diseases including human leukaemias and HIV infection. Aims: To determine CD antigen expression profiles for patients with various liver diseases and to look for preserved disease-specific signatures. Methods: Three liver disease groups including hepatitis C (HCV) (n = 35), non-alcoholic steatohepatitis (NASH) (n = 21) and alcohol-related liver disease (n = 14) were compared with a normal group (n = 23). Hierarchal Clustering (HCL) and Principal Component Analysis (PCA) of the data revealed distinct binding patterns for patients with and without cirrhosis. Results: Patients with cirrhosis and portal hypertension compared with those without cirrhosis had significantly reduced expression of several markers of T-cell function including CD45, CD8, CD28 and TCR α/β. Disease prediction algorithms based on the expression data were able to discriminate cirrhotics from non-cirrhotics with 71% overall success, which improved to 77% when only patients with HCV were considered. Conclusions: These results demonstrate disease-specific consensus patterns of expression of CD antigens for patients with chronic liver disease, suggesting that the CD antibody array is a promising tool in the analysis of human liver disease, and with further refinement may have future research and clinical utility.
机译:背景:CD抗体微阵列先前已经开发,可以半定量鉴定外周血样本中循环白细胞上的80种以上CD抗原。该测定法采用活细胞捕获技术,可在一次分析中进行广泛的白细胞免疫表型测定,迄今为止,该测定法已成功用于表征包括人类白血病和HIV感染在内的疾病。目的:确定患有各种肝病的患者的CD抗原表达谱,并寻找保留的疾病特异性特征。方法:将三类肝病包括丙型肝炎(HCV)(n = 35),非酒精性脂肪性肝炎(NASH)(n = 21)和酒精相关性肝病(n = 14)与正常组(n = 23)。数据的分层聚类(HCL)和主成分分析(PCA)显示了有和没有肝硬化患者的独特结合模式。结果:肝硬化和门静脉高压症患者与非肝硬化患者相比,CD45,CD8,CD28和TCRα/β等几种T细胞功能标志物的表达明显降低。基于表达数据的疾病预测算法能够区分肝硬化和非肝硬化,总体成功率为71%,仅考虑HCV患者时,成功率提高到77%。结论:这些结果证明了慢性肝病患者CD抗原表达的疾病特异性共识模式,这表明CD抗体阵列是分析人类肝病的有前途的工具,并且进一步的完善可能有未来的研究和临床应用效用。

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