IgE and IgG4 epitopes of the peanut allergens shift following oral immunotherapy

Front Allergy. 2023 Nov 29:4:1279290. doi: 10.3389/falgy.2023.1279290. eCollection 2023.

Abstract

Background: Oral immunotherapy (OIT) with peanut (Arachis hypogaea) allergen powder-dnfp (PTAH; Aimmune Therapeutics) is an FDA-approved treatment to desensitize peanut allergic participants.

Objective: Here we assessed shifts in IgE and IgG4 binding to peanut allergens and their epitopes recognized by United States (US) peanut allergic participants (n = 20) enrolled in phase 3 PTAH OIT clinical trials.

Methods: Pre- and post- trial participant sera were collected approximately 12 months apart and tested for IgE binding to intact peanut proteins via ImmunoCAP ISAC immunoassays. IgE and IgG4 linear epitopes were identified based on binding to synthetic overlapping 15-mer linear peptides of 10 peanut allergens (Ara h 1-11) synthesized on microarray slides.

Results: Statistically significant decreases in IgE binding were identified for intact Ara h 2, 3, and 6, and known and newly identified IgE epitopes were shown to exhibit shifts towards IgG4 binding post-OIT, with most linear peptides having increased IgG4 binding after treatment with PTAH. While PTAH does not seem to alter the actual peptide binding patterns significantly after one year of treatment, the IgE and IgG4 binding ratios and intensity are altered.

Conclusion: At a population level, the linear IgE and IgG4 epitopes of 10 peanut allergens overlap and that increase in IgG4 with OIT results in displacement of IgE binding to both conformational and linear epitopes. Furthermore, it appears as though the increase in IgG4 is more important to achieve desensitization at the 12-month timepoint than the decrease in IgE. This type of knowledge can be useful in the identification of IgE and IgG4-binding allergen and peptide biomarkers that may indicate desensitization or sustained unresponsiveness of allergic individuals to peanut.

Keywords: ISAC; epitope; immunoglobulin; linear peptide; machine learning; microarray; oral immunotherapy; peanut allergy.