@article {Ditz00097-2021, author = {B. Ditz and A. Sarma and H.A.M. Kerstjens and J.J.W. Liesker and E. Bathoorn and J.M. Vonk and V. Bernal and P. Horvatovich and V. Guryev and S. Caldera and C. Langelier and A. Faiz and S. A. Christenson and M. van den Berge}, title = {The sputum transcriptome better predicts COPD exacerbations after the withdrawal of inhaled corticosteroids than sputum eosinophils}, elocation-id = {00097-2021}, year = {2021}, doi = {10.1183/23120541.00097-2021}, publisher = {European Respiratory Society}, abstract = {Introduction Continuing inhaled corticosteroid (ICS) use does not benefit all patients with chronic obstructive pulmonary disease (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-Seq 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 co-regulatory 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 co-regulatory gene networks as well as sex to be related to an early versus late/non- exacerbation 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.FootnotesThis manuscript has recently been accepted for publication in the ERJ Open Research. It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJOR online. Please open or download the PDF to view this article.Conflict of interest: B Ditz has nothing to discloseConflict of interest: Dr. Sarma reports grants from National Heart, Lung, and Blood Institute, during the conduct of the study.Conflict of interest: HAMK reports a grant from AstraZeneca as well as grants and fees for consultancy or advisory board participation from GlaxoSmithKline, Boehringer Ingelheim, and Novartis, and a grant from Chiesi, sll outside of the submitted work and all paid to his institution.Conflict of interest: Dr. Liesker has nothing to disclose.Conflict of interest: Dr. Bathoorn has nothing to disclose.Conflict of interest: Dr. Vonk has nothing to disclose.Conflict of interest: Dr. Bernal has nothing to disclose.Conflict of interest: Dr. Horvatovich has nothing to disclose.Conflict of interest: Dr. Guryev has nothing to disclose.Conflict of interest: Ms. Caldera has nothing to disclose.Conflict of interest: Dr. Langelier has nothing to disclose.Conflict of interest: Dr Faiz has nothing to discloseConflict of interest: S.A. Christenson reports consulting fees from AstraZeneca, GlaxoSmithKline, Amgen and Glenmark; personal fees for invited lectures from Sunovion and Genentech; and personal fees for writing for UpToDate, all outside the submitted work.Conflict of interest: Dr vd Berge has nothing to disclose}, URL = {https://openres.ersjournals.com/content/early/2021/04/29/23120541.00097-2021}, eprint = {https://openres.ersjournals.com/content/early/2021/04/29/23120541.00097-2021.full.pdf}, journal = {ERJ Open Research} }