[show abstract][hide abstract] ABSTRACT: Immunoassay-based anti-nuclear antibody (ANA) screens are increasingly used in the initial evaluation of autoimmune disorders, but these tests offer no "pattern information" comparable to the information from indirect fluorescence assay-based screens. Thus, there is no indication of "next steps" when a positive result is obtained. To improve the utility of immunoassay-based ANA screening, we evaluated a new method that combines a multiplex immunoassay with a k nearest neighbor (kNN) algorithm for computer-assisted pattern recognition. We assembled a training set, consisting of 1,152 sera from patients with various rheumatic diseases and non-diseased patients. The clinical sensitivity and specificity of the multiplex method and algorithm were evaluated with a test set that consisted of 173 sera collected at a rheumatology clinic from patients diagnosed by using standard criteria, as well as 152 age- and sex-matched sera from presumably healthy individuals (sera collected at a blood bank). The test set was also evaluated with a HEp-2 cell-based enzyme-linked immunosorbent assay (ELISA). Both the ELISA and multiplex immunoassay results were positive for 94% of the systemic lupus erythematosus (SLE) patients. The kNN algorithm correctly proposed an SLE pattern for 84% of the antibody-positive SLE patients. For patients with no connective tissue disease, the multiplex method found fewer positive results than the ELISA screen, and no disease was proposed by the kNN algorithm for most of these patients. In conclusion, the automated algorithm could identify SLE patterns and may be useful in the identification of patients who would benefit from early referral to a specialist, as well as patients who do not require further evaluation.
[show abstract][hide abstract] ABSTRACT: We constructed miniaturized autoantigen arrays to perform large-scale multiplex characterization of autoantibody responses directed against structurally diverse autoantigens, using submicroliter quantities of clinical samples. Autoantigen microarrays were produced by attaching hundreds of proteins, peptides and other biomolecules to the surface of derivatized glass slides using a robotic arrayer. Arrays were incubated with patient serum, and spectrally resolvable fluorescent labels were used to detect autoantibody binding to specific autoantigens on the array. We describe and characterize arrays containing the major autoantigens in eight distinct human autoimmune diseases, including systemic lupus erythematosus and rheumatoid arthritis. This represents the first report of application of such technology to multiple human disease sera, and will enable validated detection of antibodies recognizing autoantigens including proteins, peptides, enzyme complexes, ribonucleoprotein complexes, DNA and post-translationally modified antigens. Autoantigen microarrays represent a powerful tool to study the specificity and pathogenesis of autoantibody responses, and to identify and define relevant autoantigens in human autoimmune diseases.
Nature Medicine 04/2002; 8(3):295-301. · 22.86 Impact Factor