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

Howard H.F. Tang, Shu Mei Teo, Danielle C.M. Belgrave, Michael D. Evans, Daniel J. Jackson, Marta Brozynska, Merci M.H. Kusel, Sebastian L. Johnston, James E. Gern, Robert F. Lemanske, Angela Simpson, Adnan Custovic, Peter D. Sly, Patrick G. Holt, Kathryn E. Holt, Michael Inouye
doi: https://doi.org/10.1101/237073
Howard H.F. Tang
1School of BioSciences, The University of Melbourne, Parkville, Victoria, Australia
2Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
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Shu Mei Teo
2Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
3Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia
4Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
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Danielle C.M. Belgrave
5Department of Paediatrics, Imperial College, London, United Kingdom
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Michael D. Evans
6University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
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Daniel J. Jackson
6University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
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Marta Brozynska
1School of BioSciences, The University of Melbourne, Parkville, Victoria, Australia
2Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
4Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
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Merci M.H. Kusel
7Telethon Kids Institute, University of Western Australia, Perth, Western Australia, Australia
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Sebastian L. Johnston
8Airway Disease Infection Section and MRC & Asthma UK Centre in Allergic Mechanisms of Asthma, National Heart and Lung Institute, Imperial College London, Norfolk Place, London, United Kingdom
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James E. Gern
6University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
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Robert F. Lemanske
6University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
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Angela Simpson
9Division of Infection, Immunity and Respiratory Medicine, The University of Manchester
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Adnan Custovic
5Department of Paediatrics, Imperial College, London, United Kingdom
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Peter D. Sly
7Telethon Kids Institute, University of Western Australia, Perth, Western Australia, Australia
10Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia
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Patrick G. Holt
7Telethon Kids Institute, University of Western Australia, Perth, Western Australia, Australia
10Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia
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Kathryn E. Holt
3Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia
11Department of Biochemistry and Molecular Biology, The University of Melbourne, Parkville, Victoria, Australia
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Michael Inouye
1School of BioSciences, The University of Melbourne, Parkville, Victoria, Australia
2Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
4Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
12Department of Pathology, The University of Melbourne, Parkville, Victoria, Australia
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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.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted December 20, 2017.
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Non-parametric mixture models identify trajectories of childhood immune development relevant to asthma and allergy
Howard H.F. Tang, Shu Mei Teo, Danielle C.M. Belgrave, Michael D. Evans, Daniel J. Jackson, Marta Brozynska, Merci M.H. Kusel, Sebastian L. Johnston, James E. Gern, Robert F. Lemanske, Angela Simpson, Adnan Custovic, Peter D. Sly, Patrick G. Holt, Kathryn E. Holt, Michael Inouye
bioRxiv 237073; doi: https://doi.org/10.1101/237073
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Non-parametric mixture models identify trajectories of childhood immune development relevant to asthma and allergy
Howard H.F. Tang, Shu Mei Teo, Danielle C.M. Belgrave, Michael D. Evans, Daniel J. Jackson, Marta Brozynska, Merci M.H. Kusel, Sebastian L. Johnston, James E. Gern, Robert F. Lemanske, Angela Simpson, Adnan Custovic, Peter D. Sly, Patrick G. Holt, Kathryn E. Holt, Michael Inouye
bioRxiv 237073; doi: https://doi.org/10.1101/237073

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