90 research outputs found

    Sputum microbiome profiling in COPD:beyond singular pathogen detection

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    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

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

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    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

    Clinical Significance of Symptoms in Smokers with Preserved Pulmonary Function

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    Currently, the diagnosis of chronic obstructive pulmonary disease (COPD) requires a ratio of forced expiratory volume in 1 second (FEV1) to forced vital capacity (FVC) of less than 0.70 as assessed by spirometry after bronchodilator use. However, many smokers who do not meet this definition have respiratory symptoms

    Airway Mucin Concentration as a Marker of Chronic Bronchitis

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    Chronic obstructive pulmonary disease (COPD) is characterized by chronic bronchitic and emphysematous components. In one biophysical model, the concentration of mucin on the airway surfaces is hypothesized to be a key variable that controls mucus transport in healthy persons versus cessation of transport in persons with muco-obstructive lung diseases. Under this model, it is postulated that a high mucin concentration produces the sputum and disease progression that are characteristic of chronic bronchitis

    An airway epithelial IL-17A response signature identifies a steroid-unresponsive COPD patient subgroup

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    BACKGROUND. Chronic obstructive pulmonary disease (COPD) is a heterogeneous smoking-related disease characterized by airway obstruction and inflammation. This inflammation may persist even after smoking cessation and responds variably to corticosteroids. Personalizing treatment to biologically similar "molecular phenotypes" may improve therapeutic efficacy in a COPD. IL-17A is involved in neutrophilic inflammation and corticosteroid resistance, and thus may be particularly important in a COPD molecular phenotype. METHODS. We generated a gene expression signature of IL-17A response in bronchial airway epithelial brushings from smokers with and without COPD (n = 238) , and validated it using data from 2 randomized trials of IL-17 blockade in psoriasis. This IL-17 signature was related to clinical and pathologic characteristics in 2 additional human studies of COPD: (a) SPIROMICS (n = 47), which included former and current smokers with COPD, and (b) GLUCOLD (n = 79), in which COPD participants were randomized to placebo or corticosteroids. RESULTS. The IL-17 signature was associated with an inflammatory profile characteristic of an IL-17 response, including increased airway neutrophils and macrophages. In SPIROMICS the signature was associated with increased airway obstruction and functional small airways disease on quantitative chest CT. In GLUCOLD the signature was associated with decreased response to corticosteroids, irrespective of airway eosinophilic or type 2 inflammation. CONCLUSION. These data suggest that a gene signature of IL-17 airway epithelial response distinguishes a biologically, radiographically, and clinically distinct COPD subgroup that may benefit from personalized therapy
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