Clinical & Experimental Allergy

Cross-sectional survey on immunoglobulin E reactivity in 23 077 subjects using an allergenic molecule-based microarray detection system

Authors


Correspondence:
Adriano Mari, Centre for Clinical and Experimental Allergology, IDI-IRCCS, Via dei Monti di Creta 104, Rome, Italy.
E-mail: a.mari@panservice.it

Summary

Background The availability of allergenic molecules and high-throughput microtechnologies allow the collection of a large number of IgE results at the same time in a single test. This can be carried out applying the test in the routine diagnostic work-up.

Objective The aim of this study was to make a cross-sectional evaluation of the raw prevalence of IgE reactivity to allergenic molecules in serum samples from a cohort of Italian patients using an innovative tool.

Methods The ISAC, a microarray system, has been used for specific IgE detection using 75 different allergenic molecules. Sera were collected from 23 077 unselected consecutive individuals complaining about any allergic disease.

Results Sixteen thousand four hundred and eight of 23 077 patients had IgE to at least one of 75 allergenic molecules. The top-ranked molecules in this cohort were Cup a 1 (42.7%), Der f 2 (38.7%), and Phl p 1 (37.9%), whereas all the other allergens tested scored in a range between 36.8% and 0.04%, including the first food allergen, Pru p 3, ranked 15th (9.79%). Prevalence varied quite markedly depending on the age range considered, and showing a different behaviour in the lifetime sensitization process. Unsupervised two-way hierarchical clustering analysis generated distinctive patterns of reactivity as the result of IgE recognition of either homologous allergens belonging to different biological sources or non-homologous belonging to the same biological source.

Conclusions Allergen-based microarray is a tool for the detection of IgE-related sensitization to panels of allergens and gives a more precise and comprehensive evaluation for an IgE-based epidemiology. This insight brings data for better understanding of the sensitization process.

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