Abstract Objectives Celiac disease (CD) is a systemic autoimmune disorder triggered by gluten in genetically predisposed individuals. Accurate diagnosis remains challenging due to clinical heterogeneity and reliance on invasive biopsy. This study aimed to evaluate the diagnostic performance of a novel multiparametric membrane-based enzyme immunoassay (AESKUBLOTS®) for the simultaneous detection of IgA antibodies targeting eight CD-related antigens. Methods A retrospective, single-centre study was conducted on 180 participants: 80 with CD (30 untreated, 50 on gluten-free diet, GFD), 50 with non-celiac wheat sensitivity (NCWS), and 50 healthy controls (HC). Serum samples were analysed using the AESKU assay. Diagnostic accuracy was assessed via ROC curve analysis and 5-fold cross-validation, examining individual markers and a composite antibody score. Results The assay demonstrated high diagnostic performance, particularly in untreated CD patients. Anti-tTG neo IgA showed the highest accuracy (AUC=0.93), followed by anti-tTG IgA (AUC=0.92). A composite score of ≥4 positive markers yielded an AUC of 0.99, while ≥6 positive markers achieved 100 % specificity and PPV, with 76.7 % sensitivity. Notably, anti-mTG IgA levels were elevated in all CD patients regardless of diet, suggesting potential utility in monitoring or identifying ongoing mucosal immune activity. Conclusions This multiparametric IgA assay offers a sensitive, specific, and non-invasive diagnostic tool for CD. Larger, prospective studies are warranted to confirm the clinical utility and expand the applicability to broader populations.
Evaluating the performance of a multiparametric IgA assay for celiac disease diagnosis
C. Gambino,L. Agnello,Fabio Del Ben,A. M. Ciaccio,Salvatore Milano,Roberta Vassallo,Francesco Cacciabaudo,A. Seidita,P. Mansueto,Antonio Carroccio,M. Ciaccio
Published 2025 in Clinical Chemistry and Laboratory Medicine
ABSTRACT
PUBLICATION RECORD
- Publication year
2025
- Venue
Clinical Chemistry and Laboratory Medicine
- Publication date
2025-08-20
- Fields of study
Medicine
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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