A Sputum 6 Gene Expression Signature Predicts Inflammatory Phenotypes and Future Exacerbations of COPD
Received 10 January 2020
Accepted for publication 24 May 2020
Published 2 July 2020 Volume 2020:15 Pages 1577—1590
Checked for plagiarism Yes
Review by Single-blind
Peer reviewer comments 5
Editor who approved publication: Dr Richard Russell
Katherine J Baines,1 Netsanet A Negewo,1 Peter G Gibson,1,2 Juan-Juan Fu,3 Jodie L Simpson,1 Peter AB Wark,1,2 Michael Fricker,1 Vanessa M McDonald1,2,4
1Priority Research Centre for Healthy Lungs, Hunter Medical Research Institute, The University of Newcastle, Callaghan, NSW, Australia; 2Department of Respiratory and Sleep Medicine, John Hunter Hospital, Newcastle, NSW, Australia; 3Respiratory Group, Department of Integrated Traditional Chinese and Western Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan Province, People’s Republic of China; 4School of Nursing and Midwifery, Faculty of Health and Medicine, The University of Newcastle, Callaghan, NSW, Australia
Correspondence: Katherine J Baines
Hunter Medical Research Institute, Level 2 West Wing, Locked Bag 1000, New Lambton, NSW 2305, Australia
Background: The 6 gene expression signature (6GS) predicts inflammatory phenotype, exacerbation risk, and corticosteroid responsiveness in asthma. In COPD, patterns of airway inflammation are similar, suggesting the 6GS may be useful. This study determines the diagnostic and prognostic ability of 6GS in predicting inflammatory phenotypes and exacerbation risk in COPD.
Methods: We performed 2 studies: a cross-sectional phenotype prediction study in stable COPD (total N=132; n=34 eosinophilic (E)-COPD, n=42 neutrophilic (N)-COPD, n=39 paucigranulocytic (PG)-COPD, n=17 mixed-granulocytic (MG)-COPD) that assessed 6GS ability to discriminate phenotypes (eosinophilia≥ 3%; neutrophilia≥ 61%); and a prospective cohort study (total n=54, n=8 E-COPD; n=18 N-COPD; n=20 PG-COPD; n=8 MG-COPD, n=21 exacerbation prone (≥ 2/year)) that investigated phenotype and exacerbation prediction utility. 6GS was measured by qPCR and evaluated using multiple logistic regression and area under the curve (AUC). Short-term reproducibility (intra-class correlation) and phenotyping method agreement (κ statistic) were assessed.
Results: In the phenotype prediction study, 6GS could accurately identify and discriminate patients with E-COPD from N-COPD (AUC=96.4%; p< 0.0001), PG-COPD (AUC=88.2%; p< 0.0001) or MG-COPD (AUC=86.2%; p=0.0001), as well as N-COPD from PG-COPD (AUC=83.6%; p< 0.0001) or MG-COPD (AUC=87.4%; p< 0.0001) and was reproducible. In the prospective cohort study, 6GS had substantial agreement for neutrophilic inflammation (82%, κ=0.63, p< 0.001) and moderate agreement for eosinophilic inflammation (78%, κ=0.42, p< 0.001). 6GS could significantly discriminate exacerbation prone patients (AUC=77.2%; p=0.034). Higher IL1B levels were associated with poorer lung function and increased COPD severity.
Conclusion: 6GS can significantly and reproducibly discriminate COPD inflammatory phenotypes and predict exacerbation prone patients and may become a useful molecular diagnostic tool assisting COPD management.
Keywords: COPD, airway markers, inflammation, molecular biology, eosinophil
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