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Non-parametric mixture models identify trajectories of childhood immune development relevant to asthma and allergy

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Title: Non-parametric mixture models identify trajectories of childhood immune development relevant to asthma and allergy
Authors: Tang, HHF
Teo, SM
Belgrave, DCM
Evans, M
Jackson, D
Brozynska, M
Kusel, MMH
Johnston, S
Gern, J
Lemanske, R
Simpson, A
Custovic, A
Sly, P
Holt, P
Holt, K
Inouye, M
Item Type: Working Paper
Abstract: Events in early life contribute to subsequent risk of asthma; however, the causes and trajectories of childhood wheeze are heterogeneous and do not always result in asthma. Similarly, not all atopic individuals develop wheeze, and vice versa. The reasons for these differences are unclear. Using unsupervised model-based cluster analysis, we identified latent clusters within a prospective birth cohort with deep immunological and respiratory phenotyping. We characterised each cluster in terms of immunological profile and disease risk, and replicated our results in external cohorts from the UK and USA. We discovered three distinct trajectories, one of which is a high-risk "atopic" cluster with increased propensity for allergic diseases throughout childhood. Atopy contributes varyingly to later wheeze depending on cluster membership. Our findings demonstrate the utility of unsupervised analysis in elucidating heterogeneity in asthma pathogenesis and provide a foundation for improving management and prevention of childhood asthma.
Issue Date: 20-Dec-2017
URI: http://hdl.handle.net/10044/1/63017
DOI: https://dx.doi.org/10.1101/237073
Publisher: bioRxiv
Copyright Statement: © 2017 The Author(s). This item is made available under a CC-BY 4.0 International license (https://creativecommons.org/licenses/by/4.0/).
Sponsor/Funder: Medical Research Council
Medical Research Council (MRC)
Funder's Grant Number: MR/L012693/1
MR/K002449/1
Publication Status: Published
Appears in Collections:Department of Medicine
Faculty of Medicine



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