title: Antigen microarray profiling of autoantibodies in rheumatoid arthritis.
abstract: OBJECTIVE
  Because rheumatoid arthritis (RA) is a heterogeneous autoimmune disease in terms of disease manifestations, clinical outcomes, and therapeutic responses, we developed and applied a novel antigen microarray technology to identify distinct serum antibody profiles in patients with RA.
  
  
  METHODS
  Synovial proteome microarrays, containing 225 peptides and proteins that represent candidate and control antigens, were developed. These arrays were used to profile autoantibodies in randomly selected sera from 2 different cohorts of patients: the Stanford Arthritis Center inception cohort, comprising 18 patients with established RA and 38 controls, and the Arthritis, Rheumatism, and Aging Medical Information System cohort, comprising 58 patients with a clinical diagnosis of RA of <6 months duration. Data were analyzed using the significance analysis of microarrays algorithm, the prediction analysis of microarrays algorithm, and Cluster software.
  
  
  RESULTS
  Antigen microarrays demonstrated that autoreactive B cell responses targeting citrullinated epitopes were present in a subset of patients with early RA with features predictive of the development of severe RA. In contrast, autoimmune targeting of the native epitopes contained on synovial arrays, including several human cartilage gp39 peptides and type II collagen, were associated with features predictive of less severe RA.
  
  
  CONCLUSIONS
  Proteomic analysis of autoantibody reactivities provides diagnostic information and allows stratification of patients with early RA into clinically relevant disease subsets.
authors.affiliation: Division of Immunology and Rheumatology, Department of Medicine, Stanford University School of Medicine, Stanford, California, USA. whueber@stanford.edu
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Hueber
authors.forename: Brian A
authors.initials: BA
authors.lastname: Kidd
authors.forename: Beren H
authors.initials: BH
authors.lastname: Tomooka
authors.forename: Byung J
authors.initials: BJ
authors.lastname: Lee
authors.forename: Bonnie
authors.initials: B
authors.lastname: Bruce
authors.forename: James F
authors.initials: JF
authors.lastname: Fries
authors.forename: Grete
authors.initials: G
authors.lastname: Sønderstrup
authors.forename: Paul
authors.initials: P
authors.lastname: Monach
authors.forename: Jan W
authors.initials: JW
authors.lastname: Drijfhout
authors.forename: Walther J
authors.initials: WJ
authors.lastname: van Venrooij
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Utz
authors.forename: Mark C
authors.initials: MC
authors.lastname: Genovese
authors.forename: William H
authors.initials: WH
authors.lastname: Robinson
mesh_terms: D000465:Algorithms; D000941:Antigens / Q000276:immunology* / Q000378:metabolism; D001172:Arthritis, Rheumatoid / Q000175:diagnosis* / Q000276:immunology* / Q000378:metabolism; D001323:Autoantibodies / Q000032:analysis*; D016000:Cluster Analysis; D042241:Early Diagnosis; D006801:Humans; D040081:Protein Array Analysis / Q000379:methods; D020543:Proteome / Q000276:immunology* / Q000378:metabolism; D040901:Proteomics; D013583:Synovial Membrane / Q000276:immunology / Q000378:metabolism
chemical_list: D000941:Antigens; D001323:Autoantibodies; D020543:Proteome