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J Allergy Clin Immunol. 2019 Jul;144(1):70-82. doi: 10.1016/j.jaci.2019.03.013. Epub 2019 Mar 28.

Stratification of asthma phenotypes by airway proteomic signatures.

Author information

1
Centre for Proteomic Research, Biological Sciences, University of Southampton, Southampton, United Kingdom; NIHR Southampton Biomedical Research Centre, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom.
2
NIHR Southampton Biomedical Research Centre, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom.
3
Centre for Proteomic Research, Biological Sciences, University of Southampton, Southampton, United Kingdom; Mathematical Sciences, University of Southampton, Southampton, United Kingdom.
4
Centre for Proteomic Research, Biological Sciences, University of Southampton, Southampton, United Kingdom.
5
Acclarogen, Cambridge, United Kingdom.
6
Data Science Institute, Imperial College, London, United Kingdom.
7
Janssen Research & Development, High Wycombe, United Kingdom.
8
Areteva, Nottingham, United Kingdom.
9
AMC, Department of Experimental Immunology, University of Amsterdam, Amsterdam, The Netherlands; Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
10
Respiratory Research Unit, University of Nottingham, Nottingham, United Kingdom.
11
Institute of Medicine, University of Bergen, Bergen, Norway.
12
Department of Clinical and Experimental Medicine Hospital University, University of Catania, Catania, Italy.
13
Centre for Allergy Research, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
14
Respiratory and Allergy Research Group, University of Manchester, Manchester, United Kingdom.
15
Department of Pulmonology, Semmelweis University, Budapest, Hungary.
16
Fraunhofer Institute for Toxicology and Experimental Medicine Hannover, Hannover, Germany.
17
Faculty of Medicine, Catholic University of the Sacred Heart, Rome, Italy.
18
Laboratory of Molecular Biology and Clinical Genetics, Medical College, Jagiellonian University, Krakow, Poland.
19
Department of Medicine, Department of Public Health and Clinical Medicine Respiratory Medicine Unit, Umeå University, Umeå, Sweden.
20
Respiratory Therapeutic Unit, GlaxoSmithKline, Stockley Park, United Kingdom.
21
European Institute for Systems Biology and Medicine, CNRS-ENS-UCBL-INSERM, Université de Lyon, Lyon, France.
22
Cell and Molecular Biology Group, Airways Disease Section, National Heart and Lung Institute, Imperial College London, London, United Kingdom.
23
Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
24
NIHR Southampton Biomedical Research Centre, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom. Electronic address: R.Djukanovic@soton.ac.uk.

Abstract

BACKGROUND:

Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy in prediction of treatment responses and a need for better understanding of the underlying mechanisms.

OBJECTIVE:

We sought to identify molecular subphenotypes of asthma defined by proteomic signatures for improved stratification.

METHODS:

Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyze the proteomes of sputum supernatants from 246 participants (206 asthmatic patients) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms.

RESULTS:

Analysis of the sputum proteome resulted in 10 clusters (ie, proteotypes) based on similarity in proteomic features, representing discrete molecular subphenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined 3 of these as highly eosinophilic, 3 as highly neutrophilic, and 2 as highly atopic with relatively low granulocytic inflammation. For each of these 3 phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms.

CONCLUSION:

This study provides further stratification of asthma currently classified based on quantification of granulocytic inflammation and provided additional insight into their underlying mechanisms, which could become targets for novel therapies.

KEYWORDS:

Asthma; biomarkers; eosinophils; neutrophils; proteomics

PMID:
30928653
DOI:
10.1016/j.jaci.2019.03.013

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