Evaluating the utility of autoantibodies for disease activity and relapse in giant cell arteritis.

In patients with giant cell arteritis (GCA), autoantibodies against cytoskeletal elements, cardiolipin, neutrophil cytoplasmic antigens, ferritin, endothelial and smooth muscle cells have been reported, however no updated reviews are available evaluating their clinical utility. Methodology of detection is important, especially for quantitative assays, e.g. enzyme-linked immunoassays and multiplex beadbased immunoassays, while semiquantitative assays contribute valuable data on isoforms, epitope mapping and cellular localization. Most studies to date reporting on antiphospholipid antibodies in GCA have focused on anti-cardiolipin antibodies (aCL), while the highest prevalence of autoantibodies in GCA patients was reported for the anti-N-terminal peptides of the ferritin heavy chain (92%). Antineutrophil cytoplasmic antibodies were shown to be present in only a small percentage of GCA patients, decreasing after therapy, however in combination with aCL and antibodies against peptides of N-terminal ferritin heavy chain, they could represent an added value in detecting relapse in GCA patients.

A concise review of significantly modified serological biomarkers in giant cell arteritis, as detected by different methods.

Giant cell arteritis (GCA) is a primary systemic vasculitis present in subjects older than 50years with involvement of large- and medium-sized arteries. Early diagnosis for GCA is essential to prevent serious complications, such as permanent vision loss and/or cerebrovascular events. Elevated inflammatory cytokines, with acute phase and other proteins dominate large- and medium-sized arteries leading to stenosis or occlusion of arterial lumen. To date, there are no reliable serological markers for monitoring GCA. The review aims to provide concise overview of published GCA studies in order to: a) identify significantly changed serological biomarkers in GCA and compare the influences of techniques for marker evaluation and b) investigate most promising markers in GCA using analyte frequency and meta-analysis.