Author(s): Karasawa R, Kurokawa MS, Yudoh K, Masuko K, Ozaki S,
Abstract Share this page
Abstract Anti-endothelial cell antibodies (AECA) have been frequently detected in systemic vasculitis, which affects blood vessels of various sizes. To understand the pathogenic roles of AECA in systemic vasculitis, we attempted to identify target antigens for AECA comprehensively by a proteomic approach. Proteins extracted from human umbilical vein endothelial cells (HUVEC) were separated by two-dimensional electrophoresis, and Western blotting was subsequently conducted using sera from patients with systemic vasculitis. As a result, 53 autoantigenic protein spots for AECA were detected, nine of which were identified by mass spectrometry. One of the identified proteins was peroxiredoxin 2 (Prx2), an anti-oxidant enzyme. Frequency of anti-Prx2 autoantibodies, measured by enzyme-linked immunosorbent assay (ELISA), was significantly higher in systemic vasculitis (60\%) compared to those in collagen diseases without clinical vasculitis (7\%, P < 0·01) and healthy individuals (0\%, P < 0·01). Further, the titres changed in parallel with the disease activity during time-courses. The presence of anti-Prx2 autoantibodies correlated significantly with elevation of serum d-dimers and thrombin-antithrombin complex (P < 0·05). Immunocytochemical analysis revealed that live endothelial cells expressed Prx2 on their surface. Interestingly, stimulation of HUVEC with rabbit anti-Prx2 antibodies increased secretion of interleukin (IL)-6, IL-1β, IL-1ra, growth regulated oncogene (GRO)-α, granulocyte colony-stimulating factor (G-CSF), granulocyte macrophage colony-stimulating factor (GM-CSF), IL-8 and monocyte chemoattractant protein (MCP)-1 more than twofold compared to that of with rabbit immunoglobulin (Ig)G. Taken together, our data suggest that anti-Prx2 autoantibodies would be a useful marker for systemic vasculitis and would be involved in the inflammatory processes of systemic vasculitis. © 2010 British Society for Immunology.
This article was published in Clin Exp Immunol
and referenced in Journal of Data Mining in Genomics & Proteomics