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The interaction between airway microbiome and host in chronic obstructive pulmonary disease (COPD) is poorly understood. Here we used a multi-omic meta-analysis approach to characterize the functional signature of airway microbiome in COPD. We retrieved all public COPD sputum microbiome datasets, totaling 1640 samples from 16S rRNA gene datasets and 26 samples from metagenomic datasets from across the world. We identified microbial taxonomic shifts using random effect meta-analysis and established a global classifier for COPD using 12 microbial genera. We inferred the metabolic potentials for the airway microbiome, established their molecular links to host targets, and explored their effects in a separate meta-analysis on 1340 public human airway transcriptome samples for COPD. 29.6% of differentially expressed human pathways were predicted to be targeted by microbiome metabolism. For inferred metabolite-host interactions, the flux of disease-modifying metabolites as predicted from host transcriptome was generally concordant with their predicted metabolic turnover in microbiome, suggesting a synergistic response between microbiome and host in COPD. The metaanalysis results were further validated by a pilot multi-omic study on 18 COPD patients and 10 controls, in which airway metagenome, metabolome, and host transcriptome were simultaneously characterized. 69.9% of the proposed "microbiomemetabolite-host" interaction links were validated in the independent multi-omic data. Butyrate, homocysteine, and palmitate were the microbial metabolites showing strongest interactions with COPD-associated host genes. Our meta-analysis uncovered functional properties of airway microbiome that interacted with COPD host gene signatures, and demonstrated the possibility of leveraging public multi-omic data to interrogate disease biology.

In summary, in clinically stable patients with COPD, 8 weeks of R-IMT was superior to 8 weeks of equal-intensity T-IMT in improving HRQoL, degree of dyspnoea, and exercise capacity.

PurposeHospitalization brings considerable economic pressure on COPD patients in China. A clear understanding of hospitalization costs for patients with COPD is warranted to improve treatment strategies and to control costs. Currently, investigation on factors contributing to hospitalization costs for patients with COPD in China is limited. This study aimed to measure the hospitalization costs of COPD and to determine the contributing factors.Patients and methodsMedical record data from the First Affiliated Hospital of Guangzhou Medical University from January 2016 to December 2016 were used for a retrospective analysis. Patients who were hospitalized with a diagnosis of COPD were included. Patient characteristics, medical treatment, and hospitalization costs were analyzed by descriptive statistics and multivariable regression.ResultsAmong the 1,943 patients included in this study, 87.85% patients were male; the mean (SD) age was 71.15 (9.79) years; 94.49% patients had comorbidities; and 82.30% patients had health insurance. Regarding medical treatment, the mean (SD) length of stay was 9.38 (7.65) days; 11.12% patients underwent surgery; 87.91% used antibiotics; and 4.53% underwent emergency treatment. For hospitalization costs, the mean (SD) of the total costs per COPD patient per admission was 24,372.75 (44,173.87) CNY (3,669.33 [6,650.38] USD), in which Western medicine fee was the biggest contributor (45.53%) followed by diagnosis fee (27.00%) and comprehensive medical fee (12.04%). Regression found that reimbursement (−0.032; 95% CI −0.046 to 0.007), length of stay (0.738; 95% CI 0.832–0.892), comorbidity (0.044; 95% CI 0.029–0.093), surgery (0.145; 95% CI 0.120–0.170), antibiotic use (0.086; 95% CI 0.060–0.107), and emergency treatment (0.121; 95% CI 0.147–0.219) were significantly (P<0.01) associated with total hospitalization costs.ConclusionTo control hospitalization costs for COPD patients in China, the significance of comorbidity, length of stay, antibiotic use, surgery, and emergency treatment suggests the importance of controlling the COPD progression and following clinical guidelines for inpatients. Interventions such as examination of pulmonary function for early detection, quality control of medical treatment, and patient education warrant further investigation.

Little is known about the underlying airway microbiome diversity in chronic obstructive pulmonary disease (COPD) at in-depth taxonomic levels. Here we present the first insights on the COPD airway microbiome at species and strain-levels. The full-length 16S rRNA gene was characterized from sputum in 98 COPD patients and 27 age-matched healthy controls, using the Pacific Biosciences sequencing platform. Individual species within the same genus exhibited reciprocal relationships with COPD and disease severity. Species dominant in health can be taken over by another species within the same genus but with potentially increasing pathogenicity in severe COPD patients. Ralstonia mannitolilytica , an opportunistic pathogen, was significantly increased in frequent exacerbators (fold-change = 4.94, FDR P = 0.005). There were distinct patterns of interaction between bacterial species and host inflammatory mediators according to neutrophilic or eosinophilic inflammations, two major airway inflammatory phenotypes in COPD. Haemophilus influenza e, Moraxella catarrhalis, Pseudomonas aeruginosa , and Neisseria meningitidis were associated with enhanced Th1, Th17 and pro-inflammatory mediators, while a group of seven species including Tropheryma whipplei were specifically associated with Th2 mediators related to eosinophilia. We developed an automated pipeline to assign strain-level taxonomy leveraging bacterial intra-genomic 16S allele frequency. Using this pipeline we further resolved three non-typeable H. influenzae strains PittEE, PittGG and 86-028NP with reasonable precision and uncovered strain-level variation related to airway inflammation. In particular, 86-028NP and PittGG strains exhibited inverse associations with Th2 chemokines CCL17 and CCL13, suggesting their abundances may inversely predict eosinophilic inflammation. A systematic comparison of 16S hypervariable regions indicated V1V3 instead of the commonly used V4 region was the best surrogate for airway microbiome. The full-length 16S data augmented the power of functional inference, which slightly better recapitulated the actual metagenomes. This led to the unique identification of butyrate-producing and nitrate reduction pathways as depleted in COPD. Our analysis uncovered finer-scale airway microbial diversity that was previously underappreciated, thus enabled a refined view of the airway microbiome in COPD.

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Epstein-Barr virus (EBV)-