ArticleJournal of clinical laboratory analysis2026
Validation of a Multiparametric, Automated, Macroarray-Based Assay for the Detection of Autoantibodies in Autoimmune Liver Disease.
Article in Journal of clinical laboratory analysis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe Presence of autoantibodies plays a central role in Autoimmune Liver Diseases (AiLD) diagnosis and classification: such antibodies discriminate between distinct subtypes of the AiLD, including Primary Biliary Cholangitis (PBC) and Autoimmune Hepatitis (AIH), and facilitate diagnosis of the overlap syndromes. This paper describes the optimization and validation of a novel procedure to quantify autoantibodies using a multiparametric test and a fully automated device.
methodsThe CHORUS Macroarray Liver Diseases kit was optimized to detect the following biomarkers: autoantibodies anti-AMA-M2, anti-Sp100, and anti-gp210 for PBC and autoantibodies anti-LKM-1, anti-LC1, and anti-SLA/LP for AIH types 2 and 3. To validate the assay, the limit of detection, the limit of quantitation (LoQ), precision, specificity, and sensitivity were determined. The assay was also compared with a predicate ELISA that singularly determined each antigen.
resultsA total of 216 serum samples were used to validate the assay, including 91 samples from patients with AIH or PBC and 125 samples from age-matched blood donors serving as controls. The assay was linear in the range of concentrations between the LoQs determined for each autoantibody, accurate, and precise. When compared with the predicate ELISA, the assay was sensitive and specific, with excellent agreement for each autoantibody. PBC and AIH markers were correlated, and no interaction was present between the two groups.
conclusionThe CHORUS Macroarray Liver Diseases assay was accurate, sensitive, and specific for the detection of autoantibodies in AiLD and may become a useful tool for rapidly obtaining multiparametric information using a minimal sample volume.
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