FRI0414 Evaluation of a novel multi-analyte assay for the detection of autoantibodies in the diagnosis of systemic sclerosis

ANNALS OF THE RHEUMATIC DISEASES(2018)

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摘要
Background Systemic sclerosis (SSc) is a chronic autoimmune disease characterised by vascular changes and progressive fibrosis of skin and various internal organs. In SSc a variety of autoantibodies have been detected which are useful for the diagnosis and management of the disease. Some of these autoantibodies are well-established tools strongly associated with SSc (e.g. anti-centromere, anti-topoisomerase I, anti-RNA polymerase III). Other autoantibodies are less frequent and/or less-specific for SSc even if potentially useful to better assess disease subsets and prognosis. Objectives Our goal was to assess the frequency of SSc-related autoantibodies detected using a novel technology as well as to study the associations between these antibodies and clinical features in an Italian SSc cross sectional cohort. Methods Serum samples from 218 consecutive patients with SSc collected at three Italian sites were tested for a variety of autoantibodies (see table 1) using a novel fully automated system utilising bead-based immunoassays (research use only, Inova Diagnostics, San Diego, CA). The Italian cohort included: women 200 (92%), limited cutaneous SSc (lc-SSc) 166 (76%), patients with history of digital ulcers 91 (42%), calcinosis 46 (21%), lung fibrosis 84 (39%), heart involvement 38 (17.4%), pulmonary arterial hypertension 20 (9%), and esophageal involvement 138 (63.3%). Results The prevalence of antibodies is summarised in the table 1 below. Of note, anti-BICD2, anti-CENP-B, and anti-nucleosome antibodies were significantly associated with lc-SSc subtype (p=0.0237, p Conclusions Autoantibodies identified via the novel system in this SSc cohort were found in the expected frequencies and also correlated to clinical features of the patients. The multiparameter approach combined with cluster analysis holds promise for a molecular and more precise stratification of SSc subsets. Disclosure of Interest None declared
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