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Stratification of asthma phenotypes by airway proteomic signatures

Stratification of asthma phenotypes by airway proteomic signatures
Stratification of asthma phenotypes by airway proteomic signatures
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 to predict treatment responses and a need for better understanding of the underlying mechanisms.
Objective

Identify molecular sub-phenotypes of asthma defined by proteomic signatures for improved stratification.
Methods

Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyse the proteomes of sputum supernatants from 246 participants (206 asthmatics) 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, proteotypes, based on similarity in proteomics features, representing discrete molecular sub-phenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined three of these as highly eosinophilic, three as highly neutrophilic, and two as highly atopic with relatively low granulocytic inflammation. For each of these three 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 by quantifying granulocytic inflammation and gives additional insight into their underlying mechanisms which could become targets for novel therapies.
Asthma, proteomics, biomarkers, neutrophils, eosinophiles
0091-6749
70-82
Schofield, James P.R.
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Burg, Dominic
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Nicholas, Ben
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Strazzeri, Fabio
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Brandsma, Joost
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Staykova, Doroteya
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Folisi, Caterina
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Bansal, Aruna T.
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Xian, Yang
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Guo, Yike
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Rowe, Anthony
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Corfield, Julie
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Wilson, Susan
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Ward, Jonathan
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Lutter, Rene
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Shaw, Dominick E.
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Bakke, Per S.
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Caruso, Massimo
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Dahlen, Sven-erik
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Fowler, Stephen J.
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Horváth, Ildikó
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Howarth, Peter
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Krug, Norbert
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Montuschi, Paolo
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Sanak, Marek
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Sandström, Thomas
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Sun, Kai
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Pandis, Ioannis
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Riley, John
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Auffray, Charles
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De Meulder, Bertrand
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Lefaudeux, Diane
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Sousa, Ana R.
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Adcock, Ian M.
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Chung, Kian Fan
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Sterk, Peter J.
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Skipp, Paul J.
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Djukanović, Ratko
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U-BIOPRED Study Group
Schofield, James P.R.
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Burg, Dominic
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Nicholas, Ben
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Strazzeri, Fabio
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Brandsma, Joost
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Staykova, Doroteya
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Folisi, Caterina
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Bansal, Aruna T.
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Xian, Yang
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Guo, Yike
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Rowe, Anthony
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Corfield, Julie
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Wilson, Susan
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Ward, Jonathan
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Lutter, Rene
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Shaw, Dominick E.
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Bakke, Per S.
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Caruso, Massimo
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Dahlen, Sven-erik
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Fowler, Stephen J.
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Horváth, Ildikó
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Howarth, Peter
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Krug, Norbert
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Montuschi, Paolo
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Sanak, Marek
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Sandström, Thomas
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Sun, Kai
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Pandis, Ioannis
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Riley, John
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Auffray, Charles
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De Meulder, Bertrand
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Lefaudeux, Diane
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Sousa, Ana R.
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Adcock, Ian M.
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Chung, Kian Fan
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Sterk, Peter J.
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Skipp, Paul J.
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Djukanović, Ratko
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Schofield, James P.R., Burg, Dominic, Nicholas, Ben, Strazzeri, Fabio, Brandsma, Joost, Staykova, Doroteya, Folisi, Caterina, Bansal, Aruna T., Xian, Yang, Guo, Yike, Rowe, Anthony, Corfield, Julie, Wilson, Susan, Ward, Jonathan, Lutter, Rene, Shaw, Dominick E., Bakke, Per S., Caruso, Massimo, Dahlen, Sven-erik, Fowler, Stephen J., Horváth, Ildikó, Howarth, Peter, Krug, Norbert, Montuschi, Paolo, Sanak, Marek, Sandström, Thomas, Sun, Kai, Pandis, Ioannis, Riley, John, Auffray, Charles, De Meulder, Bertrand, Lefaudeux, Diane, Sousa, Ana R., Adcock, Ian M., Chung, Kian Fan, Sterk, Peter J., Skipp, Paul J. and Djukanović, Ratko , U-BIOPRED Study Group (2019) Stratification of asthma phenotypes by airway proteomic signatures. Journal of Allergy and Clinical Immunology, 144 (1), 70-82. (doi:10.1016/j.jaci.2019.03.013).

Record type: Article

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 to predict treatment responses and a need for better understanding of the underlying mechanisms.
Objective

Identify molecular sub-phenotypes of asthma defined by proteomic signatures for improved stratification.
Methods

Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyse the proteomes of sputum supernatants from 246 participants (206 asthmatics) 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, proteotypes, based on similarity in proteomics features, representing discrete molecular sub-phenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined three of these as highly eosinophilic, three as highly neutrophilic, and two as highly atopic with relatively low granulocytic inflammation. For each of these three 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 by quantifying granulocytic inflammation and gives additional insight into their underlying mechanisms which could become targets for novel therapies.

Text
Stratification of asthma phenotypes by airway proteomic signatures_JACI_19-03-08 - Accepted Manuscript
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More information

Accepted/In Press date: 8 March 2019
e-pub ahead of print date: 28 March 2019
Published date: July 2019
Keywords: Asthma, proteomics, biomarkers, neutrophils, eosinophiles

Identifiers

Local EPrints ID: 429984
URI: http://eprints.soton.ac.uk/id/eprint/429984
ISSN: 0091-6749
PURE UUID: bf156add-d6f0-45a0-949d-2cbec78315cc
ORCID for Ben Nicholas: ORCID iD orcid.org/0000-0003-1467-9643
ORCID for Susan Wilson: ORCID iD orcid.org/0000-0003-1305-8271
ORCID for Jonathan Ward: ORCID iD orcid.org/0000-0002-9278-0002
ORCID for Paul J. Skipp: ORCID iD orcid.org/0000-0002-2995-2959
ORCID for Ratko Djukanović: ORCID iD orcid.org/0000-0001-6039-5612

Catalogue record

Date deposited: 09 Apr 2019 16:30
Last modified: 13 Oct 2021 01:36

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Contributors

Author: James P.R. Schofield
Author: Dominic Burg
Author: Ben Nicholas ORCID iD
Author: Fabio Strazzeri
Author: Joost Brandsma
Author: Doroteya Staykova
Author: Caterina Folisi
Author: Aruna T. Bansal
Author: Yang Xian
Author: Yike Guo
Author: Anthony Rowe
Author: Julie Corfield
Author: Susan Wilson ORCID iD
Author: Jonathan Ward ORCID iD
Author: Rene Lutter
Author: Dominick E. Shaw
Author: Per S. Bakke
Author: Massimo Caruso
Author: Sven-erik Dahlen
Author: Stephen J. Fowler
Author: Ildikó Horváth
Author: Peter Howarth
Author: Norbert Krug
Author: Paolo Montuschi
Author: Marek Sanak
Author: Thomas Sandström
Author: Kai Sun
Author: Ioannis Pandis
Author: John Riley
Author: Charles Auffray
Author: Bertrand De Meulder
Author: Diane Lefaudeux
Author: Ana R. Sousa
Author: Ian M. Adcock
Author: Kian Fan Chung
Author: Peter J. Sterk
Author: Paul J. Skipp ORCID iD
Corporate Author: U-BIOPRED Study Group

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