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Observational Study
. 2024 Nov 15;230(5):e1112-e1120.
doi: 10.1093/infdis/jiae232.

Cytokine Biomarkers of Exacerbations in Sputum From Patients With Chronic Obstructive Pulmonary Disease: A Prospective Cohort Study

Affiliations
Observational Study

Cytokine Biomarkers of Exacerbations in Sputum From Patients With Chronic Obstructive Pulmonary Disease: A Prospective Cohort Study

Sonia Budroni et al. J Infect Dis. .

Abstract

Background: We determined the relationships between cytokine expression in sputum and clinical data to characterize and understand chronic obstructive pulmonary disease (COPD) exacerbations in people with COPD.

Methods: We measured 30 cytokines in 936 sputum samples, collected at stable state and exacerbation visits from 99 participants in the Acute Exacerbation and Respiratory InfectionS in COPD (AERIS) study (ClinicalTrials.gov NCT01360398). We determined their longitudinal expression and examined differential expression based on disease status or exacerbation type.

Results: Of the cytokines, 17 were suitable for analysis. As for disease states, in exacerbation sputum samples, interleukin (IL) 17A, tumor necrosis factor alpha (TNF-α), IL-1β, and IL-10 were significantly increased compared to stable state sputum samples, but a logistic mixed model could not predict disease state. As for exacerbation types, bacteria-associated exacerbations showed higher expression of IL-17A, TNF-α, IL-1β, and IL-1α. IL-1α, IL-1β, and TNF-α were identified as suitable biomarkers for bacteria-associated exacerbation. Bacteria-associated exacerbations also formed a cluster separate from other exacerbation types in principal component analysis.

Conclusions: Measurement of cytokines in sputum from COPD patients could help identify bacteria-associated exacerbations based on increased concentrations of IL-1α, IL-1β, or TNF-α. This finding may provide a point-of-care assessment to distinguish a bacterial exacerbation of COPD from other exacerbation types.

Keywords: biomarkers; chronic obstructive pulmonary disease; cytokine signature; exacerbation; sputum.

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Conflict of interest statement

Potential conflicts of interest. S. B., M. T., M. S., S. A., F. S., M. Ba., C. L., S. R., V. W., M. C., M. Br., and S. R. P. are employees of GSK; M. Ba., C. L., S. R., V. W., M. C., M. Br., and S. R. P. also hold financial equities in GSK. S. B., M. T., M. S., F. S., M. Ba., S. R., and S. R. P. declare a patent filling on cytokines as biomarkers. C. L. declares a patent filling relating to SARS-CoV-2, and is the co-leader for AVDTIG subgroup as GSK representative. V. W. declares patents related to vaccine development in the field of COPD. T. M. A. W. discloses payment of a grant to his institution by GSK for the conduct of this study. He also declares payment of grants to his institution by AstraZeneca (AZ), Bergenbio, UCB, Synairgen, Janssen, Sanofi, National Institute for Health and Care Research (NIHR), and UK Research and Innovation, outside this study. T. M. A. W. received consulting fees from AZ, GSK, Synairgen, my mhealth ltd, Sanofi, Janssen, and OM pharm; payment from AZ, GSK, and Roche for lectures, presentations, speakers’ bureaus, manuscript writing, and educational events; and support from AZ for travel to meeting(s). T. M. A. W. also discloses a patent filed by university on lung imaging platform; participation on a data and safety monitoring board or advisory board for Synairgen and NIHR; payment to institution for his role of national clinical lead for National Respiratory Audit Programme (NRAP), Royal College of Physicians; medical writing support from AZ, UCB, and Sanofi Pfizer; and stocks in my mhealth ltd. Authors declare no other financial and non-financial relationships and activities. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

Figures

Figure 1.
Figure 1.
Plain language summary of the manuscript. Abbreviations: COPD, chronic obstructive pulmonary disease; IL, interleukin; TNF, tumor necrosis factor.
Figure 2.
Figure 2.
Sputum cytokines differentiate between stable state (ST) and exacerbation state (EX). Cytokine concentrations were measured in sputum samples (n = 936) obtained from 99 participants during ST (n = 701) and EX (n = 235) visits. A, Depicted are the estimated marginal means (EMMs) from a linear mixed-effects model. Vertical axis shows cytokine concentrations in pg/mL. Circles: EMM; bar: 95% confidence interval of the EMM. B, Geometric mean concentration (GMC) ratios of EX over ST. The GMCs at EX of IL-17A, TNF-α, IL-1β, and IL-10 are >2-fold higher compared to the GMCs at ST. Abbreviations: CI, confidence interval; EMM, estimated marginal mean; EX, exacerbation state; GMR, geometric mean ratio; IFN, interferon; IL, interleukin; MCP, monocyte chemoattractant protein; MIP, macrophage inflammatory protein; ST, stable state; TNF, tumor necrosis factor.
Figure 3.
Figure 3.
Sputum cytokine signatures correlate with the type of exacerbation (bacterial [B], eosinophilic [E], viral [V], Pauci) and disease state. Cytokine concentrations were measured in sputum samples (n = 513) obtained from 99 participants during stable state (ST; n = 369) and exacerbation state (EX; n = 144) visits (samples with mixed exacerbation types were not included). Depicted are the estimated marginal means (EMMs) and 95% confidence intervals (CIs) computed using a mixed effect specific for each cytokine grouped by type of exacerbation and disease state. Note that mixed exacerbation types (BV, BE, VE, BVE) were excluded, leaving 513 sputum samples for this analysis. Number of samples in each group: n = 16 in V ST, n = 106 in Pauci ST, n = 69 in E ST, n = 178 in B ST, n = 21 in V EX, n = 33 in Pauci EX, n = 22 in E EX, and n = 68 in B EX. Horizontal axis shows cytokine concentration in pg/mL. Circles: EMM; bar: 95% CI of the EMM. Abbreviations: B, bacterial; CI, confidence interval; E, eosinophilic; EMM, estimated marginal mean; EX, exacerbation state; IFN, interferon; IL, interleukin; MCP, monocyte chemoattractant protein; MIP, macrophage inflammatory protein; ST, stable state; TNF, tumor necrosis factor; V, viral.
Figure 4.
Figure 4.
Principal component analysis (PCA) distinguishes a cluster of bacterial exacerbation state (EX) samples from other exacerbation types and disease states. PCA scatterplots, each dot represents 1 sample, color-coded by exacerbation type. A, PCA of 63 EX sputum samples, 1 per participant. B, PCA of 93 stable state samples, 1 per participant. Abbreviations: B, bacterial; E, eosinophilic; PC, principal component; V, viral.

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