title: Analysis of human liver disease using a cluster of differentiation (CD) antibody microarray.
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.
  
  
  OBJECTIVE
  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.
authors.affiliation: A.W. Morrow Gastroenterology and Liver Centre, Royal Prince Alfred Hospital, Sydney, NSW, Australia.
authors.forename: Wassim
authors.initials: W
authors.lastname: Rahman
authors.forename: Pauline
authors.initials: P
authors.lastname: Huang
authors.forename: Larissa
authors.initials: L
authors.lastname: Belov
authors.forename: Jeremy S
authors.initials: JS
authors.lastname: Chrisp
authors.forename: Richard I
authors.initials: RI
authors.lastname: Christopherson
authors.forename: Peter M
authors.initials: PM
authors.lastname: Stapelberg
authors.forename: Fiona J
authors.initials: FJ
authors.lastname: Warner
authors.forename: Jacob
authors.initials: J
authors.lastname: George
authors.forename: David G
authors.initials: DG
authors.lastname: Bowen
authors.forename: Simone I
authors.initials: SI
authors.lastname: Strasser
authors.forename: David
authors.initials: D
authors.lastname: Koorey
authors.forename: Alexandra F
authors.initials: AF
authors.lastname: Sharland
authors.forename: Geoffrey W
authors.initials: GW
authors.lastname: McCaughan
authors.forename: Nicholas A
authors.initials: NA
authors.lastname: Shackel
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000906:Antibodies / Q000378:metabolism; D015703:Antigens, CD / Q000378:metabolism*; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D016130:Immunophenotyping / Q000379:methods*; D007962:Leukocytes / Q000378:metabolism; D008107:Liver Diseases / Q000175:diagnosis*; D008297:Male; D008875:Middle Aged; D025341:Principal Component Analysis; D040081:Protein Array Analysis / Q000379:methods*
chemical_list: D000906:Antibodies; D015703:Antigens, CD