Algorithm to detect IgA deficiency during automated tissue transglutaminase antibody testing

Serological screening for celiac disease (CeD) relies on tissue transglutaminase IgA antibody (tTG-IgA) testing but may be compromised in individuals with total or partial IgA deficiency. Routine measurement of serum IgA (S-IgA) increases laboratory workload and costs. Signal intensity from automated tTG-IgA assays may provide an alternative means to identify individuals with low S-IgA levels requiring IgG-based testing for CeD diagnostics. Here, we evaluated an algorithm for detecting total IgA deficiency or low S-IgA levels during routine tTG-IgA measurement.

A total of 11,596 serum samples submitted for routine tTG-IgA testing were analyzed by the EliA Celikey IgA assay. S-IgA concentrations were measured in samples yielding low assay response units (RU < 30; n = 271) and in a randomly selected subset (n = 226). Receiver operating characteristic analyses were used to determine RU cutoffs for identifying total IgA deficiency and low S-IgA levels.

RU values correlated with S-IgA concentrations, particularly at low S-IgA levels. RU cutoffs of <13.6 and < 19.2 identified total IgA deficiency and low S-IgA levels, respectively, with an estimated 100% sensitivity and ≥ 99.5% specificity. In addition, the built-in "Low RU" warning in the EliA Celikey IgA assay detected 86% of total IgA-deficient samples with an estimated 100% specificity. A few IgA-deficient samples, all of which were flagged by the "Low RU" warning, yielded IgG-based assay results suggestive of CeD.

RU-based screening using the EliA Celikey IgA assay could enable a sensitive, specific and low-cost strategy for identifying individuals requiring IgG-based CeD diagnostics, minimizing the need for routine S-IgA testing.