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

Benedikt Ditz; Aartik Sarma; Huib A M Kerstjens; Jeroen J W Liesker; Erik Bathoorn; Judith M Vonk; Victor Bernal; Peter Horvatovich; Victor Guryev; Saharai Caldera; Chaz Langelier; Alen Faiz; Stephanie A Christenson; Maarten van den Berge

doi:10.1183/23120541.00097-2021

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

ERJ Open Res. 2021 Jul 5;7(3):00097-2021. doi: 10.1183/23120541.00097-2021. eCollection 2021 Jul.

Authors

Benedikt Ditz^{1

2}, Aartik Sarma³, Huib A M Kerstjens^{1

2}, Jeroen J W Liesker^{1

2}, Erik Bathoorn⁴, Judith M Vonk^{2

5}, Victor Bernal⁶, Peter Horvatovich⁶, Victor Guryev⁷, Saharai Caldera^{8

9}, Chaz Langelier^{8

9}, Alen Faiz^{1

2

10

11}, Stephanie A Christenson^{3

11}, Maarten van den Berge^{1

2

11}

Affiliations

¹ Dept of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
² University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD, Groningen, The Netherlands.
³ University of California, San Francisco, CA, USA.
⁴ Dept of Medical Microbiology and Infection Prevention, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
⁵ Dept of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
⁶ Dept of Analytical Biochemistry, Groningen Research Institute of Pharmacy, Groningen, The Netherlands.
⁷ European Research Institute for the Biology of Ageing, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
⁸ Division of Infectious Diseases, Dept of Medicine, University of California, San Francisco, CA, USA.
⁹ Chan Zuckerberg Biohub, San Francisco, CA, USA.
¹⁰ University of Technology Sydney, Respiratory Bioinformatics and Molecular Biology (RBMB), School of Life Sciences, Sydney, Australia.
¹¹ These authors contributed equally.

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.

Grants and funding

K23 HL123778/HL/NHLBI NIH HHS/United States