An allergy diagnostic method has been developed that could correctly predict symptomatic peanut allergy by using peptide microarray immunoassays and bioinformatic methods.

Peanut allergy is relatively common, typically permanent, and often severe and a laboratory test that could accurately diagnose symptomatic peanut allergy would greatly facilitate clinical practice.

Scientists at the Mount Sinai School of Medicine, (New York, NY, USA) recruited selectively 62 children and adolescents from a larger group of referred patients for the evaluation of peanut allergy between 2001 and 2007. Of the 62 patients, 31 had symptomatic peanut allergy and 31 had outgrown their peanut allergy or were sensitized, but were clinically tolerant to peanut.

A peptide microarray immunoassay was used to compare immunoglobulin E (IgE) and IgG4 binding to the peptides of three major peanut allergens between those with symptomatic peanut allergy and those who had outgrown their allergy or were sensitized but clinically tolerant to peanut ingestion. Specific IgE and IgG4 binding to 419 overlapping peptides covering the amino acid sequences of Arachis hypogaea (Ara h) allergens Ara h 1, Ara h 2, and Ara h 3 were measured by using a peptide microarray immunoassay. Bioinformatic methods were applied for data analysis. The library of overlapping peptides was printed in two sets of duplicates onto Arrayit SuperEpoxy glass slides (Arrayit Corporation, Sunnyvale, CA, USA).

The patients who had symptomatic peanut allergy showed significantly greater IgE binding and broader epitope diversity than did peanut-tolerant individuals. No significant difference in IgG4 binding was found between groups. By using machine-learning methods, four peptide biomarkers were identified and prediction models that can predict the outcome of double blind, placebo-controlled food challenges with high accuracy were developed by using a combination of the biomarkers.

The authors concluded that the novel diagnostic approach could predict peanut allergy with high accuracy by combining the results of a peptide microarray immunoassay and bioinformatic methods. However, they note that further studies are needed to validate the efficacy of this assay in clinical practice. The study was published on in the May 2012 issue of the Journal of Allergy and Clinical Immunology.

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Arrayit Corporation
Mount Sinai School of Medicine