title: Serum proteomic analysis focused on fibrosis in patients with hepatitis C virus infection.
abstract: BACKGROUND
  Despite its widespread use to assess fibrosis, liver biopsy has several important drawbacks, including that is it semi-quantitative, invasive, and limited by sampling and observer variability. Non-invasive serum biomarkers may more accurately reflect the fibrogenetic process. To identify potential biomarkers of fibrosis, we compared serum protein expression profiles in patients with chronic hepatitis C (CHC) virus infection and fibrosis.
  
  
  METHODS
  Twenty-one patients with no or mild fibrosis (METAVIR stage F0, F1) and 23 with advanced fibrosis (F3, F4) were retrospectively identified from a pedigreed database of 1600 CHC patients. All samples were carefully phenotyped and matched for age, gender, race, body mass index, genotype, duration of infection, alcohol use, and viral load. Expression profiling was performed in a blinded fashion using a 2D polyacrylamide gel electrophoresis/LC-MS/MS platform. Partial least squares discriminant analysis and likelihood ratio statistics were used to rank individual differences in protein expression between the 2 groups.
  
  
  RESULTS
  Seven individual protein spots were identified as either significantly increased (alpha2-macroglobulin, haptoglobin, albumin) or decreased (complement C-4, serum retinol binding protein, apolipoprotein A-1, and two isoforms of apolipoprotein A-IV) with advanced fibrosis. Three individual proteins, haptoglobin, apolipoprotein A-1, and alpha2-macroglobulin, are included in existing non-invasive serum marker panels.
  
  
  CONCLUSIONS
  Biomarkers identified through expression profiling may facilitate the development of more accurate marker algorithms to better quantitate hepatic fibrosis and monitor disease progression.
authors.affiliation: Department of Disease and Biomarker Proteomics, GlaxoSmithKline Pharmaceuticals, Stevenage, UK. whiteir@aol.com
authors.forename: Ian R
authors.initials: IR
authors.lastname: White
authors.forename: Keyur
authors.initials: K
authors.lastname: Patel
authors.forename: William T
authors.initials: WT
authors.lastname: Symonds
authors.forename: Anouk
authors.initials: A
authors.lastname: Dev
authors.forename: Philip
authors.initials: P
authors.lastname: Griffin
authors.forename: Nikos
authors.initials: N
authors.lastname: Tsokanas
authors.forename: Mark
authors.initials: M
authors.lastname: Skehel
authors.forename: Chiang
authors.initials: C
authors.lastname: Liu
authors.forename: Amany
authors.initials: A
authors.lastname: Zekry
authors.forename: Paul
authors.initials: P
authors.lastname: Cutler
authors.forename: Mahanandeeshwar
authors.initials: M
authors.lastname: Gattu
authors.forename: Don C
authors.initials: DC
authors.lastname: Rockey
authors.forename: Michelle M
authors.initials: MM
authors.lastname: Berrey
authors.forename: John G
authors.initials: JG
authors.lastname: McHutchison
mesh_terms: D000328:Adult; D003710:Demography; D018450:Disease Progression; D015180:Electrophoresis, Gel, Two-Dimensional; D005260:Female; D006526:Hepatitis C / Q000097:blood* / Q000150:complications* / Q000473:pathology; D006801:Humans; D008103:Liver Cirrhosis / Q000097:blood* / Q000150:complications* / Q000473:pathology; D008297:Male; D025341:Principal Component Analysis; D040901:Proteomics