Classical approaches have pursued the use of autoantibodies in the serum as useful biomarkers in RA. The presence of autoantibodies is a common feature in autoimmune diseases like RA and the pattern of autoantibodies present is used to distinguish between diseases. For RA the presence of specific autoantibodies against antigens containing one or more citrulline residues, the so-called anti-cyclic citrulline peptide (CCP) antibodies, and rheumatoid factor (RF) are instrumental in the classifying diagnosis [2, 11]. The fact that subsets of patients with RA carry either one of the RF or anti-CCP autoantibodies, both or neither in their serum is consistent with the heterogeneous nature of RA. In approximately two-thirds of the RA patients RF is present. Evidence exists that RF positivity predicts more severe disease . Recent studies have demonstrated the use of anti-CCP as a valuable sero-
logic marker to diagnose RA early in its development and distinguish it from other non-erosive types of arthritis [13-17]. A combination of biomarkers that involve RF and anti-CCP could reflect different aspects of the disease process, and therefore might be useful for evaluating prognosis in individual patients with early rheumatoid arthritis .
The advent of high-throughput technologies that allow parallel profiling of hundreds and thousands of proteins and genes has dramatically transformed the search for genes and proteins that might be important in diagnosis and disease management. Recent developments in the production of miniaturised autoantigen arrays allows parallel detection of autoantibody specificities . Such protein arrays enable profiling of the specificity of autoantibody responses against panels of pep-tides and proteins representing known autoantigens as well as candidate autoantigens. This technology holds the promise to define autoantibody signatures that define subsets of patients with different clinical disease subtypes and treatment responses.
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