Antigen microarray profiling of autoantibodies in rheumatoid arthritis - PubMed (original) (raw)

. 2005 Sep;52(9):2645-55.

doi: 10.1002/art.21269.

Brian A Kidd, Beren H Tomooka, Byung J Lee, Bonnie Bruce, James F Fries, Grete Sønderstrup, Paul Monach, Jan W Drijfhout, Walther J van Venrooij, Paul J Utz, Mark C Genovese, William H Robinson

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• PMID: 16142722
• DOI: 10.1002/art.21269

Free article

Antigen microarray profiling of autoantibodies in rheumatoid arthritis

Wolfgang Hueber et al. Arthritis Rheum. 2005 Sep.

Free article

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.

Conclusion: Proteomic analysis of autoantibody reactivities provides diagnostic information and allows stratification of patients with early RA into clinically relevant disease subsets.

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