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Multidimensional endotyping in patients with severe asthma reveals inflammatory heterogeneity in matrix metalloproteinases and chitinase 3–like protein 1 - 01/07/16

Doi : 10.1016/j.jaci.2015.11.020 
Timothy S.C. Hinks, MD a, b, , Tom Brown, MD c, Laurie C.K. Lau, PhD a, b, Hitasha Rupani, MD a, b, Clair Barber, BSc b, Scott Elliott, BSc c, Jon A. Ward, BSc a, b, Junya Ono, BSc d, Shoichiro Ohta, MD e, Kenji Izuhara, MD f, Ratko Djukanović, MD a, b, Ramesh J. Kurukulaaratchy, MD g, Anoop Chauhan, MD c, Peter H. Howarth, MD a, b
a Clinical and Experimental Sciences, University of Southampton Faculty of Medicine, Sir Henry Wellcome Laboratories, Southampton University Hospital, Southampton, United Kingdom 
b NIHR Southampton Respiratory Biomedical Research Unit, Southampton University Hospital, Southampton, United Kingdom 
c Portsmouth Hospitals NHS Trust, Portsmouth, United Kingdom 
d Shino-Test Corporation, Kanagawa, Japan 
e Department of Laboratory Medicine, Saga Medical School, Saga, Japan 
f Department of Biomolecular Sciences, Saga Medical School, Saga, Japan 
g Department of Respiratory Medicine, Southampton General Hospital, Southampton, United Kingdom 

Corresponding author: Timothy S. C. Hinks, MD, Clinical and Experimental Sciences, University of Southampton Faculty of Medicine, Sir Henry Wellcome Laboratories, Southampton University Hospital, Southampton SO16 6YD, United Kingdom.Clinical and Experimental SciencesUniversity of Southampton Faculty of MedicineSir Henry Wellcome LaboratoriesSouthampton University HospitalSouthamptonSO16 6YDUnited Kingdom

Abstract

Background

Disease heterogeneity in patients with severe asthma and its relationship to inflammatory mechanisms remain poorly understood.

Objective

We aimed to identify and replicate clinicopathologic endotypes based on analysis of blood and sputum parameters in asthmatic patients.

Methods

One hundred ninety-four asthmatic patients and 21 control subjects recruited from 2 separate centers underwent detailed clinical assessment, sputum induction, and phlebotomy. One hundred three clinical, physiologic, and inflammatory parameters were analyzed by using topological data analysis and Bayesian network analysis.

Results

Severe asthma was associated with anxiety and depression, obesity, sinonasal symptoms, decreased quality of life, and inflammatory changes, including increased sputum chitinase 3–like protein 1 (YKL-40) and matrix metalloproteinase (MMP) 1, 3, 8, and 12 levels. Topological data analysis identified 6 clinicopathobiologic clusters replicated in both geographic cohorts: young, mild paucigranulocytic; older, sinonasal disease; obese, high MMP levels; steroid resistant TH2 mediated, eosinophilic; mixed granulocytic with severe obstruction; and neutrophilic, low periostin levels, severe obstruction. Sputum IL-5 levels were increased in patients with severe particularly eosinophilic forms, whereas IL-13 was suppressed and IL-17 levels did not differ between clusters. Bayesian network analysis separated clinical features from intricately connected inflammatory pathways. YKL-40 levels strongly correlated with neutrophilic asthma and levels of myeloperoxidase, IL-8, IL-6, and IL-6 soluble receptor. MMP1, MMP3, MMP8, and MMP12 levels were associated with severe asthma and were correlated positively with sputum IL-5 levels but negatively with IL-13 levels.

Conclusion

In 2 distinct cohorts we have identified and replicated 6 clinicopathobiologic clusters based on blood and induced sputum measures. Our data underline a disconnect between clinical features and underlying inflammation, suggest IL-5 production is relatively steroid insensitive, and highlight the expression of YKL-40 in patients with neutrophilic inflammation and the expression of MMPs in patients with severe asthma.

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Key words : Asthma, cytokines, eosinophils, neutrophils, phenotype, endotype, heterogeneity, matrix metalloproteinase, chitinase 3–like protein 1, topological data analysis

Abbreviations used : ACQ, ECP, Feno, FGF, GINA, HAD, ICS, K-S, MMP, TDA, YKL-40


Plan


 Supported by the Medical Research Council (G0800649). T.S.C.H. was supported by a Wellcome Trust Clinical Research Fellowship (088365/z/09/z) and by the Academy of Medical Sciences. Infrastructure support was funded by the National Institute for Health Research (NIHR) Southampton Respiratory Biomedical Research Unit. We acknowledge the support of the NIHR through the Primary Care Research Network and through an Academic Clinical Fellowship (to T.S.C.H.).
 Disclosure of potential conflict of interest: T. S. C. Hinks has received research support from Wellcome Trust. T. Brown has received speakers' fees from Chiesi and Novartis and has received travel support from Chiesi. S. Elliott and A. Chauhan have received research support from the Medical Research Council (MRC) UK. K. Izuhara has received research support from Shino-Test and has received consultancy fees from Chugai Pharmaceutical Co Ltd and AQUA Therapetics. R. Djukanović has received research support through a personal Clinical Training Fellowship from the Wellcome Trust and the IMI-funded EU project UBIOPRED and an MRC-funded project on COPD: COPD-MAP, has received consultancy fees from Teva Pharmaceuticals, has received lecture fees from Novartis, has received travel support from Boehringer Ingelheim, and owns stock in Synairgen. R. Kurukulaaratchy has received research support from the MRC (G0800649). P. H. Howarth has received research support from the MRC UK (Wessex Severe Asthma Cohort) and National Institute of Health Research UK (Respiratory Biomedical Research Unit) and is on the advisory boards for Novartis, Roche, Johnson & Johnson, and Aventis. The rest of the authors declare that they have no relevant conflicts of interest.


© 2015  The Authors. Publié par Elsevier Masson SAS. Tous droits réservés.
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