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

AI Article Synopsis

Article Abstract

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.

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Source
http://dx.doi.org/10.1111/j.1478-3231.2012.02854.xDOI Listing

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