Differences in IgE and IgG4 binding patterns before and after sublingual immunotherapy

Authors: KULIS, MICHAEL - University Of North Carolina; RAMBO, IAN - Oak Ridge Institute For Science And Education (ORISE); SWIENTONIEWSKI, LAUREN - Oak Ridge National Laboratory; Rivers, Adam; DUVALL, RACHEL - University Of Texas At Austin; KIM, EDWIN - University Of North Carolina; Maleki, Soheila

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 11/20/2025
Publication Date: N/A
Citation: N/A

Interpretive Summary: This study looked at how certain antibodies, specifically IgE and IgG4, react to allergens from peanuts and tree nuts before and after a treatment called sublingual immunotherapy, which involves placing allergen extracts under the tongue to build tolerance. Researchers compared blood samples from patients taken before and after this treatment to see how well these antibodies attached to different allergenic proteins. They used a special method called peptide microarrays, which allows them to test many protein pieces at once. They first looked at how antibodies reacted to a wide variety of nut and peanut proteins and then focused on specific groups of antibodies. They also considered factors like age, gender, and medical history related to allergies and asthma. The study found that the ratio of IgE to IgG4 antibodies was the most useful for predicting changes from the treatment. By combining the best-performing peptides, researchers created models that could accurately distinguish between the tests before and after treatment. One of the models had a nearly 89% success rate in predicting outcomes. Certain proteins, particularly some from walnuts, peanuts, and cashews, showed significant changes after treatment. In conclusion, the way these antibodies bind to different proteins gives insights into how patients' immune responses change with treatment. This information could help in assessing how effective food allergy treatments are.

Technical Abstract: Rationale: Identification of the peptide binding preferences of IgE and IgG4 antibodies before and after peanut sublingual immunotherapy may reveal predictive immune response patterns. Methods: Serum IgE and IgG4 from subjects before and after sublingual immunotherapy were compared for binding to peanut and tree nut allergen peptides using peptide microarrays containing overlapping 15-mers offset by 5 amino acids. Initially, antibody binding to a wide range of peanut and tree nut allergen peptides was assessed, followed by a focus on specific subsets, including IgE, IgG4, and the IgE:IgG4 ratio. Clinical features such as age, sex, and histories of asthma, eczema, and rhinitis were also evaluated in an ablation study. We built classifiers to determine if peptide binding could distinguish pre-treatment from post-treatment or if it shifted with treatment. Results: The IgE:IgG4 ratio features yielded the best performance. Combining the most distinct peptides across models into a union set further improved predictive accuracy. The most effective model, utilizing this combination of top peptides, achieved an AUROC near 0.89. Several peptides, including Jug r 2 (#102) (walnut), Ara h 5 (#2), Ara h 3 (#16) (peanut), and Ana o 1 (#104) (cashew), consistently ranked among those that shifted during treatment. A SHAP dot plot was generated with the top-performing model. Conclusions: Peptide binding patterns can capture immune changes with treatment, allowing us to identify specific peptides that may aid in evaluating the outcomes of food allergy treatments.