The sputum transcriptome better predicts COPD exacerbations after the withdrawal of inhaled corticosteroids than sputum eosinophils.

Ditz, B; Sarma, A; Kerstjens, HAM; Liesker, JJW; Bathoorn, E; Vonk, JM; Bernal, V; Horvatovich, P; Guryev, V; Caldera, S; Langelier, C; Faiz, A; Christenson, SA; van den Berge, M

The sputum transcriptome better predicts COPD exacerbations after the withdrawal of inhaled corticosteroids than sputum eosinophils.

Ditz, B Sarma, A Kerstjens, HAM Liesker, JJW Bathoorn, E Vonk, JM Bernal, V Horvatovich, P Guryev, V Caldera, S Langelier, C Faiz, A

Christenson, SA van den Berge, M

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Publisher:: European Respiratory Society
Publication Type:: Journal Article
Citation:: ERJ Open Research, 2021, 7, (3), pp. 1-11
Issue Date:: 2021-07

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Field	Value	Language
dc.contributor.author	Ditz, B
dc.contributor.author	Sarma, A
dc.contributor.author	Kerstjens, HAM
dc.contributor.author	Liesker, JJW
dc.contributor.author	Bathoorn, E
dc.contributor.author	Vonk, JM
dc.contributor.author	Bernal, V
dc.contributor.author	Horvatovich, P
dc.contributor.author	Guryev, V
dc.contributor.author	Caldera, S
dc.contributor.author	Langelier, C
dc.contributor.author	Faiz, A https://orcid.org/0000-0003-1740-3538
dc.contributor.author	Christenson, SA
dc.contributor.author	van den Berge, M
dc.date.accessioned	2022-01-11T05:12:08Z
dc.date.available	2021-04-26
dc.date.available	2022-01-11T05:12:08Z
dc.date.issued	2021-07
dc.identifier.citation	ERJ Open Research, 2021, 7, (3), pp. 1-11
dc.identifier.issn	2312-0541
dc.identifier.issn	2312-0541
dc.identifier.uri	http://hdl.handle.net/10453/152909
dc.description.abstract	Introduction: Continuing inhaled corticosteroid (ICS) use does not benefit all patients with COPD, yet it is difficult to determine which patients may safely sustain ICS withdrawal. Although eosinophil levels can facilitate this decision, better biomarkers could improve personalised treatment decisions. Methods: We performed transcriptional profiling of sputum to explore the molecular biology and compared the predictive value of an unbiased gene signature versus sputum eosinophils for exacerbations after ICS withdrawal in COPD patients. RNA-sequencing data of induced sputum samples from 43 COPD patients were associated with the time to exacerbation after ICS withdrawal. Expression profiles of differentially expressed genes were summarised to create gene signatures. In addition, we built a Bayesian network model to determine coregulatory networks related to the onset of COPD exacerbations after ICS withdrawal. Results: In multivariate analyses, we identified a gene signature (LGALS12, ALOX15, CLC, IL1RL1, CD24, EMR4P) associated with the time to first exacerbation after ICS withdrawal. The addition of this gene signature to a multiple Cox regression model explained more variance of time to exacerbations compared to a model using sputum eosinophils. The gene signature correlated with sputum eosinophil as well as macrophage cell counts. The Bayesian network model identified three coregulatory gene networks as well as sex to be related to an early versus late/nonexacerbation phenotype. Conclusion: We identified a sputum gene expression signature that exhibited a higher predictive value for predicting COPD exacerbations after ICS withdrawal than sputum eosinophilia. Future studies should investigate the utility of this signature, which might enhance personalised ICS treatment in COPD patients.
dc.format	Electronic-eCollection
dc.language	eng
dc.publisher	European Respiratory Society
dc.relation.ispartof	ERJ Open Research
dc.relation.isbasedon	10.1183/23120541.00097-2021
dc.rights	info:eu-repo/semantics/openAccess
dc.title	The sputum transcriptome better predicts COPD exacerbations after the withdrawal of inhaled corticosteroids than sputum eosinophils.
dc.type	Journal Article
utslib.citation.volume	7
utslib.location.activity	England
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney/Centre for Health Technologies (CHT)
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
dc.date.updated	2022-01-11T05:12:05Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	7
utslib.citation.issue	3

Abstract:

Introduction: Continuing inhaled corticosteroid (ICS) use does not benefit all patients with COPD, yet it is difficult to determine which patients may safely sustain ICS withdrawal. Although eosinophil levels can facilitate this decision, better biomarkers could improve personalised treatment decisions. Methods: We performed transcriptional profiling of sputum to explore the molecular biology and compared the predictive value of an unbiased gene signature versus sputum eosinophils for exacerbations after ICS withdrawal in COPD patients. RNA-sequencing data of induced sputum samples from 43 COPD patients were associated with the time to exacerbation after ICS withdrawal. Expression profiles of differentially expressed genes were summarised to create gene signatures. In addition, we built a Bayesian network model to determine coregulatory networks related to the onset of COPD exacerbations after ICS withdrawal. Results: In multivariate analyses, we identified a gene signature (LGALS12, ALOX15, CLC, IL1RL1, CD24, EMR4P) associated with the time to first exacerbation after ICS withdrawal. The addition of this gene signature to a multiple Cox regression model explained more variance of time to exacerbations compared to a model using sputum eosinophils. The gene signature correlated with sputum eosinophil as well as macrophage cell counts. The Bayesian network model identified three coregulatory gene networks as well as sex to be related to an early versus late/nonexacerbation phenotype. Conclusion: We identified a sputum gene expression signature that exhibited a higher predictive value for predicting COPD exacerbations after ICS withdrawal than sputum eosinophilia. Future studies should investigate the utility of this signature, which might enhance personalised ICS treatment in COPD patients.

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http://hdl.handle.net/10453/152909