Automated evaluation of autoantibodies on human epithelial-2 cells as an approach to standardize cell-based immunofluorescence tests

• Published in: Arthritis research & therapy 2010-01, Vol.12 (2), p.R40-R40, Article R40
• Main Authors: Egerer, Karl, Roggenbuck, Dirk, Hiemann, Rico, Weyer, Max-Georg, Büttner, Thomas, Radau, Boris, Krause, Rosemarie, Lehmann, Barbara, Feist, Eugen, Burmester, Gerd-Rüdiger
• Format: Article
• Language: English
• Subjects: Autoantibodies; Autoantibodies - blood; Automatic Data Processing; Cell differentiation; Cell Line; Diagnosis; Epithelial cells; Fluorescent antibody technique; Fluorescent Antibody Technique, Indirect - methods; Hep G2 Cells - immunology; Humans; Image Processing, Computer-Assisted; Immunofluorescence; Observations; Observer Variation; Properties; Reproducibility of Results; Research article; Rheumatic Diseases - blood; Rheumatic Diseases - diagnosis; Rheumatic Diseases - immunology; Rheumatoid arthritis; Serologic Tests - economics; Serologic Tests - methods
• ISSN: 1478-6354; 1478-6362; 1478-6354
• DOI: 10.1186/ar2949

Analysis of autoantibodies (AAB) by indirect immunofluorescence (IIF) is a basic tool for the serological diagnosis of systemic rheumatic disorders. Automation of autoantibody IIF reading including pattern recognition may improve intra- and inter-laboratory variability and meet the demand for cost-effective assessment of large numbers of samples. Comparing automated and visual interpretation, the usefulness for routine laboratory diagnostics was investigated. Autoantibody detection by IIF on human epithelial-2 (HEp-2) cells was conducted in a total of 1222 consecutive sera of patients with suspected systemic rheumatic diseases from a university routine laboratory (n = 924) and a private referral laboratory (n = 298). IIF results from routine diagnostics were compared with a novel automated interpretation system. Both diagnostic procedures showed a very good agreement in detecting AAB (kappa = 0.828) and differentiating respective immunofluorescence patterns. Only 98 (8.0%) of 1222 sera demonstrated discrepant results in the differentiation of positive from negative samples. The contingency coefficients of chi-square statistics were 0.646 for the university laboratory cohort with an agreement of 93.0% and 0.695 for the private laboratory cohort with an agreement of 90.6%, P < 0.0001, respectively. Comparing immunofluorescence patterns, 111 (15.3%) sera yielded differing results. Automated assessment of AAB by IIF on HEp-2 cells using an automated interpretation system is a reliable and robust method for positive/negative differentiation. Employing novel mathematical algorithms, automated interpretation provides reproducible detection of specific immunofluorescence patterns on HEp-2 cells. Automated interpretation can reduce drawbacks of IIF for AAB detection in routine diagnostics providing more reliable data for clinicians.