Evolution of IgE responses to multiple allergen components throughout childhood - 05/10/18
Abstract |
Background |
There is a paucity of information about longitudinal patterns of IgE responses to allergenic proteins (components) from multiple sources.
Objectives |
This study sought to investigate temporal patterns of component-specific IgE responses from infancy to adolescence, and their relationship with allergic diseases.
Methods |
In a population-based birth cohort, we measured IgE to 112 components at 6 follow-ups during childhood. We used a Bayesian method to discover cross-sectional sensitization patterns and their longitudinal trajectories, and we related these patterns to asthma and rhinitis in adolescence.
Results |
We identified 1 sensitization cluster at age 1, 3 at age 3, 4 at ages 5 and 8, 5 at age 11, and 6 at age 16 years. “Broad” cluster was the only cluster present at every follow-up, comprising components from multiple sources. “Dust mite” cluster formed at age 3 years and remained unchanged to adolescence. At age 3 years, a single-component “Grass” cluster emerged, which at age 5 years absorbed additional grass components and Fel d 1 to form the “Grass/cat” cluster. Two new clusters formed at age 11 years: “Cat” cluster and “PR-10/profilin” (which divided at age 16 years into “PR-10” and “Profilin”). The strongest contemporaneous associate of asthma at age 16 years was sensitization to dust mite cluster (odds ratio: 2.6; 95% CI: 1.2-6.1; P < .05), but the strongest early life predictor of subsequent asthma was sensitization to grass/cat cluster (odds ratio: 3.5; 95% CI: 1.6-7.4; P < .01).
Conclusions |
We describe the architecture of the evolution of IgE responses to multiple allergen components throughout childhood, which may facilitate development of better diagnostic and prognostic biomarkers for allergic diseases.
Le texte complet de cet article est disponible en PDF.Key words : Allergens, asthma, childhood, component-resolved diagnostics, IgE, machine learning, rhinitis
Abbreviations used : CRD, HDM, ISAC, MCMC, OR, PR, SPT
Plan
| Supported by the UK Medical Research Council (MRC) grants MR/K002449/1 and MR/LO12693/1, and the MRC Health eResearch Centre grant MR/K006665/1; D.B. is supported by the MRC Career Development grant MRC MR/M015181/1. |
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| Disclosure of potential conflict of interest: D. Belgrave is an employee of Microsoft Research. A. Simpson has received grants from the MRC, JP Moulton Charitable Foundation, and the National Institute for Health Research Clinical Research Facility and has received personal fees from Thermo Fisher Scientific. M. Rattray has received a grant from the UK MRC (grant MR/L012693/1). A. Custovic has received personal fees from Novartis, Regeneron/Sanofi, ALK, Bayer, Thermo Fisher Scientific, GlaxoSmithKline, and Boehringer Ingelheim. The rest of the authors declare that they have no relevant conflicts of interest. |
Vol 142 - N° 4
P. 1322-1330 - octobre 2018 Retour au numéro
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