Association of allergen signatures with individualized allergic phenotypes

Abstract

Background: Allergen sensitization patterns are heterogeneous, and their clinical relevance is often obscured by extensive cross-reactivity. We applied non-negative matrix factorization (NMF) to disentangle overlapping immunoglobulin E (IgE) signals and define clinically meaningful allergen signatures in a large Korean cohort. Methods: We analyzed 45,065 patients who underwent multiplex allergen testing (35 inhalants and food components) between 2010 and 2025. Class-scaled specific IgE values (0-6) were factorized by NMF (k = 4). Signature weights were related to asthma, allergic rhinitis, and atopic dermatitis using multivariable logistic regression and to peripheral eosinophil counts and total IgE using age- and sexadjusted linear models. Results: Four signatures & horbar;mite, grass/weed, pet, and tree & horbar;explained 77.7 % of the variance in sensitization. The mite signature predominated (57.6% of patients) and was strongly associated with allergic rhinitis (adjusted OR: 7.21, 95 % CI: 5.66-9.16), as well as marked increases in eosinophils and total IgE. The pet signature was the strongest predictor of asthma (OR: 8.90, 6.48-12.24). The tree signature showed the strongest association with atopic dermatitis (OR: 6.27, 3.81-10.32) and broader multisystem allergic morbidity. The grass/weed signature exhibited a biphasic age trajectory with a late-adult resurgence but had modest clinical impact. All signatures were significant and graded as determinants of blood eosinophil counts and IgE levels. Conclusions: Data-driven factorization of multiplex IgE panels yields portable allergen signatures that refine attribution of asthma, allergic rhinitis, and atopic dermatitis and link serologic patterns to systemic inflammation. (c) 2025 Japanese Society of Allergology. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).