title: Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip approach.
abstract: OBJECTIVE
  To identify serum protein biomarkers specific for rheumatoid arthritis (RA), using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology.
  
  
  METHODS
  A total of 103 serum samples from patients and healthy controls were analyzed. Thirty-four of the patients had a diagnosis of RA, based on the American College of Rheumatology criteria. The inflammation control group comprised 20 patients with psoriatic arthritis (PsA), 9 with asthma, and 10 with Crohn's disease. The noninflammation control group comprised 14 patients with knee osteoarthritis and 16 healthy control subjects. Serum protein profiles were obtained by SELDI-TOF-MS and compared in order to identify new biomarkers specific for RA. Data were analyzed by a machine learning algorithm called decision tree boosting, according to different preprocessing steps.
  
  
  RESULTS
  The most discriminative mass/charge (m/z) values serving as potential biomarkers for RA were identified on arrays for both patients with RA versus controls and patients with RA versus patients with PsA. From among several candidates, the following peaks were highlighted: m/z values of 2,924 (RA versus controls on H4 arrays), 10,832 and 11,632 (RA versus controls on CM10 arrays), 4,824 (RA versus PsA on H4 arrays), and 4,666 (RA versus PsA on CM10 arrays). Positive results of proteomic analysis were associated with positive results of the anti-cyclic citrullinated peptide test. Our observations suggested that the 10,832 peak could represent myeloid-related protein 8.
  
  
  CONCLUSIONS
  SELDI-TOF-MS technology allows rapid analysis of many serum samples, and use of decision tree boosting analysis as the main statistical method allowed us to propose a pattern of protein peaks specific for RA.
authors.affiliation: University of Liège, Centre Hospitalier Universitaire, Liege, Belgium. ddeseny@chu.ulg.ac.be
authors.forename: Dominique
authors.initials: D
authors.lastname: de Seny
authors.forename: Marianne
authors.initials: M
authors.lastname: Fillet
authors.forename: Marie-Alice
authors.initials: MA
authors.lastname: Meuwis
authors.forename: Pierre
authors.initials: P
authors.lastname: Geurts
authors.forename: Laurence
authors.initials: L
authors.lastname: Lutteri
authors.forename: Clio
authors.initials: C
authors.lastname: Ribbens
authors.forename: Vincent
authors.initials: V
authors.lastname: Bours
authors.forename: Louis
authors.initials: L
authors.lastname: Wehenkel
authors.forename: Jacques
authors.initials: J
authors.lastname: Piette
authors.forename: Michel
authors.initials: M
authors.lastname: Malaise
authors.forename: Marie-Paule
authors.initials: MP
authors.lastname: Merville
mesh_terms: D000328:Adult; D000368:Aged; D015535:Arthritis, Psoriatic / Q000097:blood / Q000175:diagnosis / Q000276:immunology; D001172:Arthritis, Rheumatoid / Q000097:blood* / Q000175:diagnosis / Q000276:immunology; D001323:Autoantibodies / Q000097:blood; D015415:Biomarkers / Q000097:blood*; D003424:Crohn Disease / Q000097:blood / Q000175:diagnosis / Q000276:immunology; D003663:Decision Trees; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010456:Peptides, Cyclic / Q000276:immunology; D040081:Protein Array Analysis / Q000379:methods* / Q000592:standards; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods* / Q000592:standards
chemical_list: D001323:Autoantibodies; D015415:Biomarkers; D010456:Peptides, Cyclic; C487763:cyclic citrullinated peptide