Relationship between inflammatory status and microbial composition in severe asthma and during exacerbation.

BACKGROUND: In T2-mediated severe asthma, biologic therapies, such as mepolizumab, are increasingly used to control disease. Current biomarkers can indicate adequate suppression of T2 inflammation, but it is unclear whether they provide information about airway microbial composition. We investigated the relationships between current T2 biomarkers and microbial profiles, characteristics associated with a ProteobacteriaHIGH microbial profile and the effects of mepolizumab on airway ecology. METHODS: Microbiota sequencing was performed on sputum samples obtained at stable and exacerbation state from 140 subjects with severe asthma participating in two clinical trials. Inflammatory subgroups were compared on the basis of biomarkers, including FeNO and sputum and blood eosinophils. ProteobacteriaHIGH subjects were identified by Proteobacteria to Firmicutes ratio ≥0.485. Where paired sputum from stable visits was available, we compared microbial composition at baseline and following ≥12 weeks of mepolizumab. RESULTS: Microbial composition was not related to inflammatory subgroup based on sputum or blood eosinophils. FeNO ≥50 ppb when stable and at exacerbation indicated a group with less dispersed microbial profiles characterised by high alpha-diversity and low Proteobacteria. ProteobacteriaHIGH subjects were neutrophilic and had a longer time from asthma diagnosis than ProteobacteriaLOW subjects. In those studied, mepolizumab did not alter airway bacterial load or lead to increased Proteobacteria. CONCLUSION: High FeNO could indicate a subgroup of severe asthma less likely to benefit from antimicrobial strategies at exacerbation or in the context of poor control. Where FeNO is <50 ppb, biomarkers of microbial composition are required to identify those likely to respond to microbiome-directed strategies. We found no evidence that mepolizumab alters airway microbial composition.

Lung microbiome composition and bronchial epithelial gene expression in patients with COPD versus healthy individuals: a bacterial 16S rRNA gene sequencing and host transcriptomic analysis.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is associated with airway inflammation and bacterial dysbiosis. The relationship between the airway microbiome and bronchial gene expression in COPD is poorly understood. We aimed to identify differences in the airway microbiome from bronchial brushings in patients with COPD and healthy individuals and to investigate whether any distinguishing bacteria are related to bronchial gene expression. METHODS: For this 16S rRNA gene sequencing and host transcriptomic analysis, individuals aged 45-75 years with mild-to-moderate COPD either receiving or not receiving inhaled corticosteroids and healthy individuals in the same age group were recruited as part of the Emphysema versus Airways Disease (EvA) consortium from nine centres in the UK, Germany, Italy, Poland, and Hungary. Individuals underwent clinical characterisation, spirometry, CT scans, and bronchoscopy. From bronchoscopic bronchial brush samples, we obtained the microbial profiles using 16S rRNA gene sequencing and gene expression using the RNA-Seq technique. We analysed bacterial genera relative abundance and the associations between genus abundance and clinical characteristics or between genus abundance and host lung transcriptional signals in patients with COPD versus healthy individuals, and in patients with COPD with versus without inhaled corticosteroids treatment. FINDINGS: Between February, 2009, and March, 2012, we obtained brush samples from 574 individuals. We used 546 of 574 samples for analysis, including 207 from healthy individuals and 339 from patients with COPD (192 with inhaled corticosteroids and 147 without). The bacterial genera that most strongly distinguished patients with COPD from healthy individuals were Prevotella (median relative abundance 33·5%, IQR 14·5-49·4, in patients with COPD vs 47·7%, 31·1-60·7, in healthy individuals; p<0·0001), Streptococcus (8·6%, 3·8-15·8, vs 5·3%, 3·0-10·1; p<0·0001), and Moraxella (0·05%, 0·02-0·14, vs 0·02%, 0-0·07; p<0·0001). Prevotella abundance was inversely related to COPD severity in terms of symptoms and positively related to lung function and exercise capacity. 446 samples had assessable RNA-seq data, 257 from patients with COPD (136 with inhaled corticosteroids and 121 without) and 189 from healthy individuals. No significant associations were observed between lung transcriptional signals from bronchial brushings and abundance of bacterial genera in patients with COPD without inhaled corticosteroids treatment and in healthy individuals. In patients with COPD treated with inhaled corticosteroids, Prevotella abundance was positively associated with expression of epithelial genes involved in tight junction promotion and Moraxella abundance was associated with expression of the IL-17 and TNF inflammatory pathways. INTERPRETATION: With increasing severity of COPD, the airway microbiome is associated with decreased abundance of Prevotella and increased abundance of Moraxella in concert with downregulation of genes promoting epithelial defence and upregulation of pro-inflammatory genes associated with inhaled corticosteroids use. Our work provides further insight in understanding the relationship between microbiome alteration and host inflammatory response, which might lead to novel therapeutic strategies for COPD. FUNDING: EU Seventh Framework Programme, National Institute for Health Research.

Inflammatory Endotype-associated Airway Microbiome in Chronic Obstructive Pulmonary Disease Clinical Stability and Exacerbations: A Multicohort Longitudinal Analysis.

Rationale: Understanding the role of the airway microbiome in chronic obstructive pulmonary disease (COPD) inflammatory endotypes may help to develop microbiome-based diagnostic and therapeutic approaches. Objectives: To understand the association of the airway microbiome with neutrophilic and eosinophilic COPD at stability and during exacerbations. Methods: An integrative analysis was performed on 1,706 sputum samples collected longitudinally from 510 patients with COPD recruited at four UK sites of the BEAT-COPD (Biomarkers to Target Antibiotic and Systemic COPD), COPDMAP (Chronic Obstructive Pulmonary Disease Medical Research Council/Association of the British Pharmaceutical Industry), and AERIS (Acute Exacerbation and Respiratory Infections in COPD) cohorts. The microbiome was analyzed using COPDMAP and AERIS as a discovery data set and BEAT-COPD as a validation data set. Measurements and Main Results: The airway microbiome in neutrophilic COPD was heterogeneous, with two primary community types differentiated by the predominance of Haemophilus. The Haemophilus-predominant subgroup had elevated sputum IL-1ß and TNFα (tumor necrosis factor α) and was relatively stable over time. The other neutrophilic subgroup with a balanced microbiome profile had elevated sputum and serum IL-17A and was temporally dynamic. Patients in this state at stability were susceptible to the greatest microbiome shifts during exacerbations. This subgroup can temporally switch to both neutrophilic Haemophilus-predominant and eosinophilic states that were otherwise mutually exclusive. Time-series analysis on the microbiome showed that the temporal trajectories of Campylobacter and Granulicatella were indicative of intrapatient switches from neutrophilic to eosinophilic inflammation, in track with patient sputum eosinophilia over time. Network analysis revealed distinct host-microbiome interaction patterns among neutrophilic Haemophilus-predominant, neutrophilic balanced microbiome, and eosinophilic subgroups. Conclusions: The airway microbiome can stratify neutrophilic COPD into subgroups that justify different therapies. Neutrophilic and eosinophilic COPD are interchangeable in some patients. Monitoring temporal variability of the airway microbiome may track patient inflammatory status over time.

The sputum microbiome is distinct between COPD and health, independent of smoking history.

BACKGROUND: Airway bacterial dysbiosis is a feature of chronic obstructive pulmonary disease (COPD). However, there is limited comparative data of the lung microbiome between healthy smokers, non-smokers and COPD. METHODS: We compared the 16S rRNA gene-based sputum microbiome generated from pair-ended Illumina sequencing of 124 healthy subjects (28 smokers and 96 non-smokers with normal lung function), with single stable samples from 218 COPD subjects collected from three UK clinical centres as part of the COPDMAP consortium. RESULTS: In healthy subjects Firmicutes, Bacteroidetes and Actinobacteria were the major phyla constituting 88% of the total reads, and Streptococcus, Veillonella, Prevotella, Actinomyces and Rothia were the dominant genera. Haemophilus formed only 3% of the healthy microbiome. In contrast, Proteobacteria was the most dominant phylum accounting for 50% of the microbiome in COPD subjects, with Haemophilus and Moraxella at genus level contributing 25 and 3% respectively. There were no differences in the microbiome profile within healthy and COPD subgroups when stratified based on smoking history. Principal coordinate analysis on operational taxonomic units showed two distinct clusters, representative of healthy and COPD subjects (PERMANOVA, p = 0·001). CONCLUSION: The healthy and COPD sputum microbiomes are distinct and independent of smoking history. Our results underline the important role for Gammaproteobacteria in COPD.

Detection of Cell-Dissociated Non-Typeable Haemophilus influenzae in the Airways of Patients with Chronic Obstructive Pulmonary Disease.

Background: Non-typeable Haemophilus influenzae (NTHi) is the most commonly found pathogen in the lower respiratory airways of patients with COPD. NTHi is predominantly regarded as an intracellular pathogen; however, like most pathogens, it can exist and co-exist in two broad forms: cell-associated (intracellularly or adhered to cells) or cell-dissociated (biofilm dispersed or planktonic). We sought to investigate if cell-dissociated NTHi can be detected from the sputum of COPD patients and assess this relationship to disease severity and airway inflammation. Methods: DNA was extracted from the sputum plug and cell-free supernatant to quantify absolute (cell-associated and cell-dissociated NTHi) and cell-dissociated NTHi, respectively, from 87 COPD subjects attending an observational longitudinal COPD exacerbation study. NTHi was quantified using TaqMan hydrolysis probes, targeting the OMP P6 gene using qPCR. Results: At stable state cell-dissociated NTHi was detected 56% of subjects with a median (IQR) of 9.95x102 gene copies (1.26x102 to 1.90x104). Cell-dissociated NTHi correlated with absolute NTHi levels (r=0.34, p<0.01) but not airway inflammation or spirometry at stable state. At exacerbation, cell-dissociated NTHi correlated with lung function (FEV1 r=0.629, p=0.005; FEV1%predicted r=0.564, p=0.015; FVC r=0.476 p=0.046) and sputum neutrophilic inflammation (% neutrophils r=0.688, p=0.002; total neutrophils r=0.518, p=0.028). Conclusion: In patients with COPD, NTHi can exist in both cell-associated and cell-dissociated forms. Cell-dissociated NTHi is associated with neutrophilic airway inflammation during exacerbations of COPD and may be a driving factor in worsening lung function during these episodes.

Sputum microbiomic clustering in asthma and chronic obstructive pulmonary disease reveals a Haemophilus-predominant subgroup.

BACKGROUND: Airway ecology is altered in asthma and chronic obstructive pulmonary disease (COPD). Anti-microbial interventions might have benefit in subgroups of airway disease. Differences in sputum microbial profiles at acute exacerbation of airways disease are reflected by the γProteobacteria:Firmicutes (γP:F) ratio. We hypothesized that sputum microbiomic clusters exist in stable airways disease, which can be differentiated by the sputum γP:F ratio. METHODS: Sputum samples were collected from 63 subjects with severe asthma and 78 subjects with moderate-to-severe COPD in a prospective single centre trial. Microbial profiles were obtained through 16S rRNA gene sequencing. Topological data analysis was used to visualize the data set and cluster analysis performed at genus level. Clinical characteristics and sputum inflammatory mediators were compared across the clusters. RESULTS: Two ecological clusters were identified across the combined airways disease population. The smaller cluster was predominantly COPD and was characterized by dominance of Haemophilus at genus level (n = 20), high γP:F ratio, increased H influenzae, low diversity measures and increased pro-inflammatory mediators when compared to the larger Haemophilus-low cluster (n = 121), in which Streptococcus demonstrated the highest relative abundance at the genus level. Similar clusters were identified within disease groups individually and the γP:F ratio consistently differentiated between clusters. CONCLUSION: Cluster analysis by airway ecology of asthma and COPD in stable state identified two subgroups differentiated according to dominance of Haemophilus. The γP:F ratio was able to distinguish the Haemophilus-high versus Haemophilus-low subgroups, whether the Haemophilus-high group might benefit from treatment strategies to modulate the airway ecology warrants further investigation.

Resistome analyses of sputum from COPD and healthy subjects reveals bacterial load-related prevalence of target genes.

BACKGROUND: Antibiotic resistance is a major global threat. We hypothesised that the chronic obstructive pulmonary disease (COPD) airway is a reservoir of antimicrobial resistance genes (ARGs) that associate with microbiome-specific COPD subgroups. OBJECTIVE: To determine the resistance gene profiles in respiratory samples from COPD patients and healthy volunteers. METHODS: Quantitative PCR targeting 279 specific ARGs was used to profile the resistomes in sputum from subjects with COPD at stable, exacerbation and recovery visits (n=55; COPD-BEAT study), healthy controls with (n=7) or without (n=22) exposure to antibiotics in the preceding 12 months (EXCEED study) and in bronchial brush samples from COPD (n=8) and healthy controls (n=7) (EvA study). RESULTS: ARG mean (SEM) prevalence was greater in stable COPD samples (35.2 (1.6)) than in healthy controls (27.6 (1.7); p=0.004) and correlated with total bacterial abundance (r2=0.23; p<0.001). Prevalence of ARG positive signals in individuals was not related to COPD symptoms, lung function or their changes at exacerbation. In the COPD subgroups designated High γProteobacteria and High Firmicutes, ARG prevalence was not different at stable state but significantly declined from stable through exacerbation to recovery in the former (p=0.011) without changes in total bacterial abundance. The ARG patterns were similar in COPD versus health, COPD microbiome-subgroups and between sputum and bronchoscopic samples independent of antibiotic exposure in the last 12 months. CONCLUSIONS: ARGs are highly prevalent in sputum, broadly in proportion to bacterial abundance in both healthy and COPD subjects. Thus, COPD appears to be an ARG reservoir due to high levels of bacterial colonisation.

Sputum Streptococcus pneumoniae is reduced in COPD following treatment with benralizumab.

We hypothesized whether the reduction in eosinophilic airway inflammation in patients with chronic obstructive pulmonary disease (COPD) following treatment with benralizumab, a humanized, afucosylated, monoclonal antibody that binds to interleukin-5 receptor α, increases the airway bacterial load. Analysis of sputum samples of COPD patients participating in a Phase II trial of benralizumab indicated that sputum 16S rDNA load and Streptococcus pneumoniae were reduced following treatment with benralizumab. However, in vitro, eosinophils did not affect the killing of the common airway pathogens S. pneumoniae or Haemophilus influenzae. Thus, benralizumab may have an indirect effect upon airway bacterial load.

Sputum Moraxella catarrhalis strains exhibit diversity within and between COPD subjects.

PURPOSE: Moraxella catarrhalis is implicated in the pathogenesis of some COPD exacerbations. We sought to investigate whether the M. catarrhalis strain is variable between COPD subjects; that an exacerbation is associated with acquisition of a new strain and that certain strains are more commonly associated with exacerbations. PATIENTS AND METHODS: Sputum samples were collected at stable and exacerbation visits from COPD subjects from a single center as part of the COPDMAP consortium. Samples identified as M. catarrhalis positive by qPCR were recultured in liquid cultures grown to extract genomic DNA; underwent Illumina MiSeq and bacterial genome sequences were de novo assembled and Multi Locus Sequence Type (MLST) was determined. RESULTS: Thirty-five samples were obtained from 18 subjects. These included 13 stable and 22 exacerbation samples. The diversity between samples was very large with 25 different M. catarrhalis MLSTs being identified out of the 35 samples of which 12 MSLTs have not been described previously. Change and persistence of M. catarrhalis strain were observed between stable visits, from stable to exacerbation and vice-a-versa, and between exacerbation visits. CONCLUSION: Sputum M. catarrhalis strains exhibit marked diversity within and between COPD subjects. Acquisition of a new strain is common between stable and exacerbation events such that no strain is specifically associated with an exacerbation.

Face mask sampling reveals antimicrobial resistance genes in exhaled aerosols from patients with chronic obstructive pulmonary disease and healthy volunteers.

INTRODUCTION: The degree to which bacteria in the human respiratory tract are aerosolised by individuals is not established. Building on our experience sampling bacteria exhaled by individuals with pulmonary tuberculosis using face masks, we hypothesised that patients with conditions frequently treated with antimicrobials, such as chronic obstructive pulmonary disease (COPD), might exhale significant numbers of bacteria carrying antimicrobial resistance (AMR) genes and that this may constitute a previously undefined risk for the transmission of AMR. METHODS: Fifteen-minute mask samples were taken from 13 patients with COPD (five paired with contemporaneous sputum samples) and 10 healthy controls. DNA was extracted from cell pellets derived from gelatine filters mounted within the mask. Quantitative PCR analyses directed to the AMR encoding genes: blaTEM (ß-lactamase), ErmB (target methylation), mefA (macrolide efflux pump) and tetM (tetracycline ribosomal protection protein) and six additional targets were investigated. Positive signals above control samples were obtained for all the listed genes; however, background signals from the gelatine precluded analysis of the additional targets. RESULTS: 9 patients with COPD (69%), aerosolised cells containing, in order of prevalence, mefA, tetM, ErmB and blaTEM, while three healthy controls (30%) gave weak positive signals including all targets except blaTEM. Maximum estimated copy numbers of AMR genes aerosolised per minute were mefA: 3010, tetM: 486, ErmB: 92 and blaTEM: 24. The profile of positive signals found in sputum was not concordant with that in aerosol in multiple instances. DISCUSSION: We identified aerosolised AMR genes in patients repeatedly exposed to antimicrobials and in healthy volunteers at lower frequencies and levels. The discrepancies between paired samples add weight to the view that sputum content does not define aerosol content. Mask sampling is a simple approach yielding samples from all subjects and information distinct from sputum analysis. Our results raise the possibility that patient-generated aerosols may be a significant means of AMR dissemination that should be assessed further and that consideration be given to related control measures.

Biological exacerbation clusters demonstrate asthma and chronic obstructive pulmonary disease overlap with distinct mediator and microbiome profiles.

BACKGROUND: Exacerbations of asthma and chronic obstructive pulmonary disease (COPD) are heterogeneous. OBJECTIVE: We sought to investigate the sputum cellular, mediator, and microbiome profiles of both asthma and COPD exacerbations. METHODS: Patients with severe asthma or moderate-to-severe COPD were recruited prospectively to a single center. Sputum mediators were available in 32 asthmatic patients and 73 patients with COPD assessed at exacerbation. Biologic clusters were determined by using factor and cluster analyses on a panel of sputum mediators. Patterns of clinical parameters, sputum mediators, and microbiome communities were assessed across the identified clusters. RESULTS: The asthmatic patients and patients with COPD had different clinical characteristics and inflammatory profiles but similar microbial ecology. Three exacerbation biologic clusters were identified. Cluster 1 was COPD predominant, with 27 patients with COPD and 7 asthmatic patients exhibiting increased blood and sputum neutrophil counts, proinflammatory mediators (IL-1ß, IL-6, IL-6 receptor, TNF-α, TNF receptors 1 and 2, and vascular endothelial growth factor), and proportions of the bacterial phylum Proteobacteria. Cluster 2 had 10 asthmatic patients and 17 patients with COPD with increased blood and sputum eosinophil counts, type 2 mediators (IL-5, IL-13, CCL13, CCL17, and CCL26), and proportions of the bacterial phylum Bacteroidetes. Cluster 3 had 15 asthmatic patients and 29 patients with COPD with increased type 1 mediators (CXCL10, CXCL11, and IFN-γ) and proportions of the phyla Actinobacteria and Firmicutes. CONCLUSIONS: A biologic clustering approach revealed 3 subgroups of asthma and COPD exacerbations, each with different percentages of patients with overlapping asthma and COPD. The sputum mediator and microbiome profiles were distinct between clusters.

Microbiome balance in sputum determined by PCR stratifies COPD exacerbations and shows potential for selective use of antibiotics.

BACKGROUND: While a subgroup of patients with exacerbations of chronic obstructive pulmonary disease (COPD) clearly benefit from antibiotics, their identification remains challenging. We hypothesised that selective assessment of the balance between the two dominant bacterial groups (Gammaproteobacteria (G) and Firmicutes (F)) in COPD sputum samples might reveal a subgroup with a bacterial community structure change at exacerbation that was restored to baseline on recovery and potentially reflects effective antibiotic treatment. METHODS: Phylogenetically specific 16S rRNA genes were determined by quantitative real time PCR to derive a G:F ratio in serial sputum samples from 66 extensively-phenotyped COPD exacerbation episodes. RESULTS: Cluster analysis based on Euclidean distance measures, generated across the 4 visit times (stable and exacerbation day: 0,14 and 42) for the 66 exacerbation episodes, revealed three subgroups designated HG, HF, and GF reflecting predominance or equivalence of the two target bacterial groups. While the other subgroups showed no change at exacerbation, the HG cluster (n = 20) was characterized by G:F ratios that increased significantly at exacerbation and returned to baseline on recovery (p<0.00001); ratios in the HG group also correlated positively with inflammatory markers and negatively with FEV1. At exacerbation G:F showed a significant receiver-operator-characteristic curve to identify the HG subgroup (AUC 0.90, p<0.0001). CONCLUSIONS: The G:F ratio at exacerbation can be determined on a timescale compatible with decisions regarding clinical management. We propose that the G:F ratio has potential for use as a biomarker enabling selective use of antibiotics in COPD exacerbations and hence warrants further clinical evaluation.

Investigating the role of pentraxin 3 as a biomarker for bacterial infection in subjects with COPD.

BACKGROUND: Pentraxin 3 (PTX3) is an acute phase protein, involved in antibacterial resistance. Recent studies have shown PTX3 levels to be elevated in the presence of a bacterial infection and in a murine sepsis model. OBJECTIVE: We aim to investigate if sputum PTX3 can be used as a biomarker for bacterial infection in subjects with COPD. MATERIALS AND METHODS: Sputum samples from 142 COPD patients (102 men) with a mean (range) age of 69 years (45-85) and mean (SD) post-bronchodilator percentage predicted forced expiratory volume in 1 second (FEV1) of 50% (19) were analyzed for PTX3, using a commercial assay at stable state and during an exacerbation. Association with bacteria, from culture, quantitative real-time polymerase chain reaction (qPCR) and colony-forming units (CFU) was investigated. RESULTS: The geometric mean (95% CI) PTX3 level at stable state was 50.5 ng/mL (41.4-61.7). PTX3 levels correlated with absolute neutrophil count in sputum (r=0.37; P<0.01), but not FEV1 or health status. There was a weak correlation between PTX3 and bacterial load (CFU: r=0.29, P<0.01; 16S qPCR: r=0.18, P=0.05). PTX3 was a poor predictor of bacterial colonization (defined as >105 CFU/mL at stable state) with a receiver-operating characteristic (ROC) area under the curve (AUC) of 0.59 and 95% confidence interval (CI) 0.43-0.76 (P=0.21). During an exacerbation, there was a modest increase in PTX3 (fold difference 0.15, 95% of difference 0.02-0.29; P=0.02), and PTX3 fared better at identifying a bacteria-associated exacerbation (ROC AUC 0.65, 95% CI 0.52-0.78, P=0.03). CONCLUSION: PTX3 is associated with bacterial infection in patients with COPD, but its utility as a biomarker for identifying a bacteria-associated exacerbation warrants further studies.

Lung microbiome dynamics in COPD exacerbations.

Increasing evidence suggests that the lung microbiome plays an important role in chronic obstructive pulmonary disease (COPD) severity. However, the dynamics of the lung microbiome during COPD exacerbations and its potential role in disease aetiology remain poorly understood.We completed a longitudinal 16S ribosomal RNA survey of the lung microbiome on 476 sputum samples collected from 87 subjects with COPD at four visits defined as stable state, exacerbation, 2 weeks post-therapy and 6 weeks recovery.Our analysis revealed a dynamic lung microbiota where changes appeared to be associated with exacerbation events and indicative of specific exacerbation phenotypes. Antibiotic and steroid treatments appear to have differential effects on the lung microbiome. We depict a microbial interaction network for the lung microbiome and suggest that perturbation of a few bacterial operational taxonomic units, in particular Haemophilus spp., could greatly impact the overall microbial community structure. Furthermore, several serum and sputum biomarkers, in particular sputum interleukin-8, appear to be highly correlated with the structure and diversity of the microbiome.Our study furthers the understanding of lung microbiome dynamics in COPD patients and highlights its potential as a biomarker, and possibly a target, for future respiratory therapeutics.

Airway bacteria measured by quantitative polymerase chain reaction and culture in patients with stable COPD: relationship with neutrophilic airway inflammation, exacerbation frequency, and lung function.

BACKGROUND: Potentially pathogenic microorganisms can be detected by quantitative real-time polymerase chain reaction (qPCR) in sputum from patients with COPD, although how this technique relates to culture and clinical measures of disease is unclear. We used cross-sectional and longitudinal data to test the hypotheses that qPCR is a more sensitive measure of bacterial presence and is associated with neutrophilic airway inflammation and adverse clinical outcomes. METHODS: Sputum was collected from 174 stable COPD subjects longitudinally over 12 months. Microbial sampling using culture and qPCR was performed. Spirometry and sputum measures of airway inflammation were assessed. FINDINGS: Sputum was qPCR-positive (>10(6) copies/mL) in 77/152 samples (Haemophilus influenzae [n=52], Moraxella catarrhalis [n=24], Streptococcus pneumoniae [n=19], and Staphylococcus aureus [n=7]). Sputum was culture-positive in 50/174 samples, with 49 out of 50 culture-positive samples having pathogen-specific qPCR bacterial loads >10(6) copies/mL. Samples that had qPCR copy numbers >10(6)/mL, whether culture-positive or not, had increased sputum neutrophil counts. H. influenzae qPCR copy numbers correlated with sputum neutrophil counts (r=0.37, P<0.001), were repeatable within subjects, and were >10(6)/mL three or more times in 19 patients, eight of whom were repeatedly sputum culture-positive. Persistence, whether defined by culture, qPCR, or both, was associated with a higher sputum neutrophil count, lower forced expiratory volume in 1 second (FEV1), and worsened quality of life. INTERPRETATION: qPCR identifies a significant number of patients with potentially bacteria-associated neutrophilic airway inflammation and disease that are not identified by traditional culture-based methods.

Association between pathogens detected using quantitative polymerase chain reaction with airway inflammation in COPD at stable state and exacerbations.

BACKGROUND: Relationships between airway inflammation and respiratory potentially pathogenic microorganisms (PPMs) quantified using quantitative polymerase chain reaction (qPCR) in subjects with COPD are unclear. Our aim was to evaluate mediators of airway inflammation and their association with PPMs in subjects with COPD at stable state and during exacerbations. METHODS: Sputum from 120 stable subjects with COPD was analyzed for bacteriology (colony-forming units; total 16S; and qPCR targeting Haemophilus influenzae, Moraxella catarrhalis, and Streptococcus pneumoniae), differential cell counts, and inflammatory mediators using the Meso-Scale Discovery Platform. Subjects were classified as colonized if any PPM was identified above the threshold of detection by qPCR. Symptoms were quantified using the visual analog scale. RESULTS: At stable state, 60% of subjects were qPCR positive for H influenzae, 48% for M catarrhalis, and 28% for S pneumoniae. Elevated sputum concentrations of IL-1ß, IL-10, and tumor necrosis factor (TNF)-α were detected in samples qPCR positive for either H influenzae or M catarrhalis. Bacterial loads of H influenzae positively correlated with IL-1ß, IL-8, IL-10, TNF-α, and symptoms; and M catarrhalis correlated with IL-10 and TNF-α. H influenzae qPCR bacterial load was an independent predictor of sputum TNF-α and IL-1ß. In 55 subjects with paired exacerbation data, qPCR bacterial load fold change at exacerbation in M catarrhalis but not H influenzae correlated to changes in sputum TNF-α and IL-1ß concentrations. CONCLUSIONS: At stable state, H influenzae is associated with increased airway inflammation in COPD. The relationship between bacterial load changes of specific pathogens and airway inflammation at exacerbation and recovery warrants further investigation.

Systemic and pulmonary inflammation is independent of skeletal muscle changes in patients with chronic obstructive pulmonary disease.

BACKGROUND: Nutritional depletion is an important manifestation of chronic obstructive pulmonary disease (COPD), which has been related to systemic inflammation. It remains unclear to what degree airway inflammation contributes to the presence or progression of nutritional depletion. OBJECTIVES: To determine whether airway inflammation and lung bacterial colonization are related to nutritional status or predict progressive weight loss and muscle atrophy in patients with COPD. METHODS: Body composition using dual energy X-ray absorptiometry, indices of airway inflammation, and bacterial colonization were measured in 234 COPD patients. Systemic inflammation was assessed from serum C reactive protein (CRP) and circulating total and differential leukocyte counts. Nutritional depletion was defined as a body mass index (BMI) less than 21 kg/m(2) and/or fat-free mass index (FFMI) less than 15 or 17 kg/m(2) in women and men, respectively. FFMI was calculated as the fat-free mass (FFM) corrected for body surface area. Measurements were repeated in 94 patients after a median 16-month follow-up. Regression analysis was used to assess the relationships of weight change and FFM change with indices of bacterial colonization and airway and systemic inflammation. RESULTS: Nutritional depletion occurred in 37% of patients. Lung function was worsened in patients with nutritional depletion compared to those without (forced expiratory volume in 1 second 1.17 L versus 1.41 L, mean difference 0.24, 95% confidence interval 0.10 to 0.38, P<0.01). There were no differences in airway inflammation and bacterial colonization in patients with and without nutritional depletion. At baseline, BMI correlated positively with serum CRP (rs=0.14, P=0.04). Change in weight and change in FFM over time could not be predicted from baseline patient characteristics. CONCLUSION: Nutritional depletion and progressive muscle atrophy are not related to airway inflammation or bacterial colonization. Overspill of pulmonary inflammation is not a key driver of muscle atrophy in COPD.

Acute exacerbations of chronic obstructive pulmonary disease: identification of biologic clusters and their biomarkers.

RATIONALE: Exacerbations of chronic obstructive pulmonary disease (COPD) are heterogeneous with respect to inflammation and etiology. OBJECTIVES: Investigate biomarker expression in COPD exacerbations to identify biologic clusters and determine biomarkers that recognize clinical COPD exacerbation phenotypes, namely those associated with bacteria, viruses, or eosinophilic airway inflammation. METHODS: Patients with COPD were observed for 1 year at stable and exacerbation visits. Biomarkers were measured in sputum and serum. Viruses and selected bacteria were assessed in sputum by polymerase chain reaction and routine diagnostic bacterial culture. Biologic phenotypes were explored using unbiased cluster analysis and biomarkers that differentiated clinical exacerbation phenotypes were investigated. MEASUREMENTS AND MAIN RESULTS: A total of 145 patients (101 men and 44 women) entered the study. A total of 182 exacerbations were captured from 86 patients. Four distinct biologic exacerbation clusters were identified. These were bacterial-, viral-, or eosinophilic-predominant, and a fourth associated with limited changes in the inflammatory profile termed "pauciinflammatory." Of all exacerbations, 55%, 29%, and 28% were associated with bacteria, virus, or a sputum eosinophilia. The biomarkers that best identified these clinical phenotypes were sputum IL-1ß, 0.89 (area under receiver operating characteristic curve) (95% confidence interval [CI], 0.83­0.95); serum CXCL10, 0.83 (95% CI, 0.70­0.96); and percentage peripheral eosinophils, 0.85 (95% CI, 0.78­0.93), respectively. CONCLUSIONS: The heterogeneity of the biologic response of COPD exacerbations can be defined. Sputum IL-1ß, serum CXCL10, and peripheral eosinophils are biomarkers of bacteria-, virus-, or eosinophil-associated exacerbations of COPD. Whether phenotype-specific biomarkers can be applied to direct therapy warrants further investigation.