Combining Allergen Components Improves the Accuracy of Peanut Allergy Diagnosis.

BACKGROUND: IgE to peanut often occurs in the absence of peanut allergy. Detection of allergen component specific IgE (sIgE) has improved diagnosis and birthed molecular allergen component arrays, in which sensitization to multiple allergen components can be measured simultaneously. OBJECTIVE: To improve the diagnostic utility of serology for peanut allergy, by mapping interactions of sIgE to multiple components and IgE functional characteristics. METHODS: A cohort of 100 children was studied, with a 60-children cohort employed for external validation. Levels of total IgE, sIgE to peanut, and peanut components were measured using singleplex ImmunoCAP and multiplex immuno solid-phase allergen chip (ISAC). Peanut IgE specific activity, avidity, and diversity were determined. Diagnostic modeling was performed using a Bayesian hierarchical model. RESULTS: Sensitization to the 112 allergens on ISAC (model 1) demonstrated the highest accuracy to diagnose peanut allergy (area under the curve [AUC] = 0.92). Sensitization to peanut components on ISAC (model 2) reported an AUC of 0.86 and on singleplex (model 3) an AUC of 0.92, which was greater than that of Ara h 2 sIgE alone (AUC = 0.90). Functional characteristics of peanut sIgE (model 4) reported an AUC of 0.89, which was greater than that of peanut sIgE (AUC = 0.75). Model 3 offered the highest predictive value and the second highest overall diagnostic accuracy. CONCLUSIONS: sIgE to a combination of allergen components (Ara h 1, 2, 3, and 6) is highly predictive of peanut allergy and superior to individual markers. Combining the functional characteristics of IgE was superior to peanut sIgE levels alone. These models can be applied in real time during clinical consultations using online calculators.