Optimization of High-throughput Autoantibody Profiling for the Discovery of Novel Antigenic Targets in Rheumatoid Arthritis

Abstract

A major focus in rheumatoid arthritis (RA) research is the identification of the antigens that are targeted by the joint-directed autoimmune response. B cells and associated autoantibodies have been studied in RA to identify the antigenic targets and to discover RA-associated autoantibodies which can be used as disease markers. This research indicated the heterogeneity of the autoantibody profile in RA and the large overlap in antibody specificities with other rheumatic diseases pointing toward the need for multiplexing to identify an RA-associated autoantibody profile. The discovery of antibodies directed against cyclic citrullinated peptides (ACPA) has led to great advances in RA research. This finding generated novel autoantigen suspects in ACPA-positive RA patients, which comprise approximately two-thirds of the entire RA population, namely citrullinated peptides and/or proteins. One-third of the RA patients, however, do not show ACPA, and it is now postulated that ACPA-positive and ACPA-negative RA are two different disease entities with different genetic associations, pathogenesis, and etiology. The analysis of autoantibodies in ACPA-negative RA could provide insight into the identity of antigenic targets and markers for this disease subtype. We report here the optimization of an unbiased, high-throughput autoantibody profiling procedure based on cDNA phage display for the detection of novel autoantibody targets in ACPA-negative RA. The discovery of specific autoantibodies in this RA subtype could lead to great advances in the diagnosis of these patients and could provide clues regarding disease etiology and pathogenesis of ACPA-negative RA.