Abstract
IntroductionAutoantibodies directed against citrullinated proteins/peptides (ACPAs) are highly specific and predictive for the development of rheumatoid arthritis (RA). Different subgroups of RA patients, which have different prognoses and may require different treatments, are characterized by different autoantibody profiles. The objective of this study was to develop a microarray for the detection of multiple RA-associated autoantibodies, initially focusing on responses against citrullinated epitopes on candidate autoantigens in RA.MethodsThe microarray is based on Phadia's ImmunoCAP ISAC system, with which reactivity to more than 100 antigens can be analyzed simultaneously, by using minute serum volumes (< 10 μl). Twelve citrullinated peptides, and the corresponding native arginine-containing control peptides, were immobilized in an arrayed fashion onto a chemically modified glass slide, allowing a three-dimensional layer with high binding capacity. The assay was optimized concerning serum dilution and glass surface, whereas each individual antigen was optimized concerning coupling chemistry, antigen concentration, and selection of spotting buffer. The performance of each peptide in the ImmunoCAP ISAC system was compared with the performance in enzyme-linked immunosorbent assays (ELISAs). Serum from 927 RA patients and 461 healthy controls from a matched case-control study were applied onto reaction sites on glass slides, followed by fluorescent-labeled anti-human immunoglobulin G (IgG) antibody. Fluorescence intensities were detected with a laser scanner, and the results analyzed by using image-analysis software.ResultsStrong correlations between the ImmunoCAP ISAC system and ELISA results were found for individual citrullinated peptides (Spearman ρ typically between 0.75 and 0.90). Reactivity of RA sera with the peptides was seen mainly in the anticyclic citrullinated peptide 2 (CCP2)-positive subset, but some additional reactivity with single citrullinated peptides was seen in the anti-CCP2-negative subset. Adjusting for reactivity against arginine-containing control peptides did not uniformly change the diagnostic performance for antibodies against the individual citrullinated peptides.ConclusionsThe multiplexed array, for detection of autoantibodies against multiple citrullinated epitopes on candidate RA autoantigens, will be of benefit in studies of RA pathogenesis, diagnosis, and potentially as a guide to individualized treatment.
Highlights
Autoantibodies directed against citrullinated proteins/peptides (ACPAs) are highly specific and predictive for the development of rheumatoid arthritis (RA)
During our work with establishment of different anti-citrullinated proteins/peptide antibody (ACPA) enzyme-linked immunosorbent assays (ELISAs), we found that certain peptide backbones yield increased ELISA reactivity, irrespective of whether the peptide is investigated in its citrullinated or in its native arginine-containing form
Performance of the ACPA microarray When the laser-scanned slides were processed with the Microarray Image Analysis software, the sites where the citrullinated peptides had been spotted in triplicate were clearly visualized after treatment with serum positive for the corresponding autoantibodies
Summary
Autoantibodies directed against citrullinated proteins/peptides (ACPAs) are highly specific and predictive for the development of rheumatoid arthritis (RA). Some studies have investigated the impact of having simultaneous ACPA reactivity to different citrullinated peptides (see, for example, [6,7,8,9,10]), such studies have hitherto been performed with multiple parallel enzyme-linked immunosorbent assay (ELISA) tests, an approach that is laborious and can demand sizeable volumes of scarce serum samples (for example, from historical cohorts) Such studies of multiple detailed ACPA specificities have proven informative concerning both the risk for RA development in the context of risk genes [8,11], and the development of risk of arthritis in healthy individuals [6] as well as in arthralgia patients [7]
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