RSV-related Community COPD Exacerbations and Novel Diagnostics: A Binational Prospective Cohort Study

RATIONALE

Respiratory syncytial virus (RSV) is a common global respiratory virus increasingly recognized as a major pathogen in frail older adults and as a cause of chronic obstructive pulmonary disease (COPD) exacerbations. There is no single test for RSV in adults with acceptable diagnostic accuracy. Trials of RSV vaccines have recently shown excellent safety and efficacy against RSV in older adults; defining the frequency of RSV-related community infections and COPD exacerbations is important for vaccine deployment decisions.

OBJECTIVES

This prospective study aimed to establish the frequency of outpatient-managed RSV-related exacerbations of COPD in two well-characterized patient cohorts using a combination of diagnostic methods.

METHODS

Participants were recruited at specialist clinics in London, UK and Groningen, NL from 2017 and observed for three consecutive RSV seasons, during exacerbations and at least twice yearly. RSV infections were detected by reverse transcription-polymerase chain reaction (RT-PCR) and serologic testing.

MEASUREMENTS AND MAIN RESULTS

377 patients with COPD attended 1,999 clinic visits and reported 310 exacerbations. There were 27 RSV-related exacerbations (8·7% of total); of these, seven were detected only on PCR, 16 only on serology and 4 by both methods. Increases in RSV specific N-protein antibody were as sensitive as antibody to pre-F or post-F for serodiagnosis of RSV related exacerbations.

CONCLUSIONS

RSV is associated with 8.7% of outpatient managed COPD exacerbations in this study. Antibodies to RSV-N protein may have diagnostic value, potentially important in a vaccinated population. The introduction of vaccines that prevent RSV is expected to benefit patients with COPD. This article is open access and distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

Smoking induces shifts in cellular composition and transcriptome within the bronchial mucus barrier

BACKGROUND AND OBJECTIVE

Smoking disturbs the bronchial-mucus-barrier. This study assesses the cellular composition and gene expression shifts of the bronchial-mucus-barrier with smoking to understand the mechanism of mucosal damage by cigarette smoke exposure. We explore whether single-cell-RNA-sequencing (scRNA-seq) based cellular deconvolution (CD) can predict cell-type composition in RNA-seq data.

METHODS

RNA-seq data of bronchial biopsies from three cohorts were analysed using CD. The cohorts included 56 participants with chronic obstructive pulmonary disease [COPD] (38 smokers; 18 ex-smokers), 77 participants without COPD (40 never-smokers; 37 smokers) and 16 participants who stopped smoking for 1 year (11 COPD and 5 non-COPD-smokers). Differential gene expression was used to investigate gene expression shifts. The CD-derived goblet cell ratios were validated by correlating with staining-derived goblet cell ratios from the COPD cohort. Statistics were done in the R software (false discovery rate p-value < 0.05).

RESULTS

Both CD methods indicate a shift in bronchial-mucus-barrier cell composition towards goblet cells in COPD and non-COPD-smokers compared to ex- and never-smokers. It shows that the effect was reversible within a year of smoking cessation. A reduction of ciliated and basal cells was observed with current smoking, which resolved following smoking cessation. The expression of mucin and sodium channel (ENaC) genes, but not chloride channel genes, were altered in COPD and current smokers compared to never smokers or ex-smokers. The goblet cell-derived staining scores correlate with CD-derived goblet cell ratios.

CONCLUSION

Smoking alters bronchial-mucus-barrier cell composition, transcriptome and increases mucus production. This effect is partly reversible within a year of smoking cessation. CD methodology can predict goblet-cell percentages from RNA-seq.

The Microbiome in Bronchial Biopsies from Smokers and Ex-Smokers with Stable COPD - A Metatranscriptomic Approach

Current knowledge about the respiratory microbiome is mainly based on 16S ribosomal RNA gene sequencing. Newer sequencing approaches, such as metatranscriptomics, offer the technical ability to measure the viable microbiome response to environmental conditions such as smoking as well as to explore its functional role by investigating host-microbiome interactions. However, knowledge about its feasibility in respiratory microbiome research, especially in lung biopsies, is still very limited. RNA sequencing was performed in bronchial biopsies from clinically stable smokers (n = 5) and ex-smokers (n = 6) with COPD not using (inhaled) steroids. The Trinity assembler was used to assemble non-human reads in order to allow unbiased taxonomical and microbial transcriptional analyses. Subsequently, host-microbiome interactions were analyzed based on associations with host transcriptomic data. Ultra-low levels of microbial mass (0.009%) were identified in the RNA-seq data. Overall, no differences were identified in microbiome diversity or transcriptional profiles of microbial communities or individual microbes between COPD smokers and ex-smokers in the initial test dataset as well as a larger replication dataset. We identified an upregulated host gene set, related to the simultaneous presence of Bradyrhizobium, Roseomonas, Brevibacterium.spp., which were related to PERK-mediated unfolded protein response (UPR) and expression of the microRNA-155-5p. Our results show that metatranscriptomic profiling in bronchial biopsy samples from stable COPD patients yields ultra-low levels of microbial mass. Further, this study illustrates the potential of using transcriptional profiling of the host and microbiome to gain more insight into their interaction in the airways.

Responsivity and Reproducibility of Sputum Inflammatory Biomarkers During COPD Exacerbation and Stable Phases - A Pilot Study

Introduction

There is a great interest to identify airway biomarkers to evaluate the potential and efficacy of anti-inflammatory therapeutic interventions. In this pilot study, we compared cytokine mRNA and protein levels of IL-6, IL-8, CCL2, CCL4, and TNF-α, as well as LTB-4 expression regarding their reproducibility and responsivity in induced sputum in COPD patients.

Methods

We recruited a cohort of 17 patients with a moderate COPD exacerbation, necessitating antibiotics and/or oral corticosteroids. Patients were followed for two consecutive stable phase visits. Cytokine mRNA and protein levels were measured in induced sputum samples.

Results

IL-6 and CCL4 protein levels decreased from exacerbation to stable phase, whereas their mRNA expression showed the same trend (not statistically significant). Coefficients of variation were overall lower (ie, more favorable for responsiveness) at protein levels compared to mRNA levels. No significant differences were observed in the reproducibility between cytokine mRNA expression and protein measurements. IL-6, IL-8, CCL2, and TNF-α gene expression levels yielded moderate to high intraclass correlation coefficients and/or Spearman correlation coefficients between both stable phase samples in contrast to their protein levels.

Conclusion

Our findings suggest that several protein levels yield better responsivity with lower noise-to-signal ratios compared to their respective mRNA levels. In contrast, cytokine mRNA expression was more reproducible as it varied less in a stable state than proteins. Future studies are needed with a larger sample size to further evaluate the differences of responsivity and reproducibility between cytokine mRNA and protein measurements, not only during exacerbations.

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

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.

Sputum gene expression may have utility in biomarker development for identifying subjects who are at higher risk of exacerbation after ICS withdrawalhttps://bit.ly/3gYl2OL

RAGE and TLR4 differentially regulate airway hyperresponsiveness: Implications for COPD

BACKGROUND

The receptor for advanced glycation end products (RAGE) and Toll-like receptor 4 (TLR4) is implicated in COPD. Although these receptors share common ligands and signalling pathways, it is not known whether they act in concert to drive pathological processes in COPD. We examined the impact of RAGE and/or TLR4 gene deficiency in a mouse model of COPD and also determined whether expression of these receptors correlates with airway neutrophilia and airway hyperresponsiveness (AHR) in COPD patients.

METHODS

We measured airway inflammation and AHR in wild-type, RAGE^-/- , TLR4^-/- and TLR4^-/- RAGE^-/- mice following acute exposure to cigarette smoke (CS). We also examined the impact of smoking status on AGER (encodes RAGE) and TLR4 bronchial gene expression in patients with and without COPD. Finally, we determined whether expression of these receptors correlates with airway neutrophilia and AHR in COPD patients.

RESULTS

RAGE^-/- mice were protected against CS-induced neutrophilia and AHR. In contrast, TLR4^-/- mice were not protected against CS-induced neutrophilia and had more severe CS-induced AHR. TLR4^-/- RAGE^-/- mice were not protected against CS-induced neutrophilia but were partially protected against CS-induced mediator release and AHR. Current smoking was associated with significantly lower AGER and TLR4 expression irrespective of COPD status, possibly reflecting negative feedback regulation. However, consistent with preclinical findings, AGER expression correlated with higher sputum neutrophil counts and more severe AHR in COPD patients. TLR4 expression did not correlate with neutrophilic inflammation or AHR.

CONCLUSIONS

Inhibition of RAGE but not TLR4 signalling may protect against airway neutrophilia and AHR in COPD.

Comparison of genome-wide gene expression profiling by RNA Sequencing versus microarray in bronchial biopsies of COPD patients before and after inhaled corticosteroid treatment: does it provide new insights?

More DEGs are detected by RNA-Seq than microarrays in COPD lung biopsies and are associated with immunological pathways. Performing bulk tissue cell-type deconvolution in microarray lung samples, using the SVR method, reflects RNA-Seq results. https://bit.ly/2N8sY3s.

Cholinergic neuroplasticity in asthma driven by TrkB signaling

Parasympathetic neurons in the airways control bronchomotor tone. Increased activity of cholinergic neurons are mediators of airway hyperresponsiveness (AHR) in asthma, however, mechanisms are not elucidated. We describe remodeling of the cholinergic neuronal network in asthmatic airways driven by brain‐derived neurotrophic factor (BDNF) and Tropomyosin receptor kinase B (TrkB). Human bronchial biopsies were stained for cholinergic marker vesicular acetylcholine transporter (VAChT). Human lung gene expression and single nucleotide polymorphisms (SNP) in neuroplasticity‐related genes were compared between asthma and healthy patients. Wild‐type (WT) and mutated TrkB knock‐in mice (Ntrk2tm1Ddg/J) with impaired BDNF signaling were chronically exposed to ovalbumin (OVA). Neuronal VAChT staining and airway narrowing in response to electrical field stimulation in precision cut lung slices (PCLS) were assessed. Increased cholinergic fibers in asthmatic airway biopsies was found, paralleled by increased TrkB gene expression in human lung tissue, and SNPs in the NTRK2 [TrkB] and BDNF genes linked to asthma. Chronic allergen exposure in mice resulted in increased density of cholinergic nerves, which was prevented by inhibiting TrkB. Increased nerve density resulted in AHR in vivo and in increased nerve‐dependent airway reactivity in lung slices mediated via TrkB. These findings show cholinergic neuroplasticity in asthma driven by TrkB signaling and suggest that the BDNF‐TrkB pathway may be a potential target.

Sputum microbiome profiling in COPD: beyond singular pathogen detection

Culture-independent microbial sequencing techniques have revealed that the respiratory tract harbours a complex microbiome not detectable by conventional culturing methods. The contribution of the microbiome to chronic obstructive pulmonary disease (COPD) pathobiology and the potential for microbiome-based clinical biomarkers in COPD are still in the early phases of investigation. Sputum is an easily obtainable sample and has provided a wealth of information on COPD pathobiology, and thus has been a preferred sample type for microbiome studies. Although the sputum microbiome likely reflects the respiratory microbiome only in part, there is increasing evidence that microbial community structure and diversity are associated with disease severity and clinical outcomes, both in stable COPD and during the exacerbations. Current evidence has been limited to mainly cross-sectional studies using 16S rRNA gene sequencing, attempting to answer the question ‘who is there?’ Longitudinal studies using standardised protocols are needed to answer outstanding questions including differences between sputum sampling techniques. Further, with advancing technologies, microbiome studies are shifting beyond the examination of the 16S rRNA gene, to include whole metagenome and metatranscriptome sequencing, as well as metabolome characterisation. Despite being technically more challenging, whole-genome profiling and metabolomics can address the questions ‘what can they do?’ and ‘what are they doing?’ This review provides an overview of the basic principles of high-throughput microbiome sequencing techniques, current literature on sputum microbiome profiling in COPD, and a discussion of the associated limitations and future perspectives.