Lung microbiota associations with clinical features of COPD in the SPIROMICS cohort

Abstract

Chronic obstructive pulmonary disease (COPD) is heterogeneous in development, progression, and phenotypes. Little is known about the lung microbiome, sampled by bronchoscopy, in milder COPD and its relationships to clinical features that reflect disease heterogeneity (lung function, symptom burden, and functional impairment). Using bronchoalveolar lavage fluid collected from 181 never-smokers and ever-smokers with or without COPD (GOLD 0-2) enrolled in the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS), we find that lung bacterial composition associates with several clinical features, in particular bronchodilator responsiveness, peak expiratory flow rate, and forced expiratory flow rate between 25 and 75% of FVC (FEF_25-75). Measures of symptom burden (COPD Assessment Test) and functional impairment (six-minute walk distance) also associate with disparate lung microbiota composition. Drivers of these relationships include members of the Streptococcus, Prevotella, Veillonella, Staphylococcus, and Pseudomonas genera. Thus, lung microbiota differences may contribute to airway dysfunction and airway disease in milder COPD.

Fig. 1. Variation in lung bacterial community composition is associated with specific measures of lung function and symptoms.

a Principal component analysis (PCA) of the overall variation in BAL bacterial composition and relationships to the associated clinical measures for the entire cohort (N = 181). Contrasting relationships exist between lung microbiota and measures of airflow limitation (FEF_25–75 and peak expiratory flow rate, PEFR) compared to that for measures of bronchodilator response and symptoms (COPD Assessment Test, CAT). PCA based on Hellinger transformation of OTU abundance counts. Vectors indicate direction and magnitude of the linear relationship between a clinical variable and the gradient of bacterial composition shown by PCA (R function envfit). b, c Correlations between within-sample bacterial diversity (inverse Simpson index) to FVC bronchodilator response and FEF_25–75 (Spearman r = −0.26, p = 0.005 and r = 0.17, p = 0.02, respectively).

Fig. 2. Differential relationships between lung bacterial composition, specific lung function measures, and symptoms are maintained among ever-smokers without or with mild-moderate COPD.

Principal coordinate analysis (PCoA) of lung bacterial community variation (weighted Unifrac distance) among ever-smokers without (gray circles) or with (gray Xs) mild-moderate COPD and relationships to the clinical variables shown (blue arrows; R envfit). An overlaid biplot analysis shows the microbiota members (red arrows) driving the observed variation in lung bacterial community structure amongst these ever-smokers.

Fig. 3. Post-bronchodilator FVC response and 6-min walk distance correlate with variation in lung bacterial composition along principal component 1, which explained 23.5% of the total variation in lung bacterial community structure among ever-smokers.

Each dot represents an individual BAL sample and is colored according to its PC score. OTUs contributing significantly (q-value < 0.10) to PC1 are shown in the accompanying table, ranked by Pearson’s correlation coefficient. The relative abundances of Prevotella, Pseudomonas, and Streptococcus are primary drivers of PC1 variation. a Post-bronchodilator FVC response measured by change in percent and volume in mL. b Six-minute walk distance (meters).

Fig. 4. Streptococcus, PEFR and CAT score in ever-smokers with or without COPD.

The relative abundance of Streptococcus Otu5, either alone (top panels) or together with other Streptococcus OTUs (bottom panels), correlate negatively with peak expiratory flow rate (PEFR) and positively with COPD Assessment Test (CAT) score.

Fig. 5. Heatmap summarizing results of DESeq analysis showing lung bacterial taxa significantly associated (q-value < 0.10) with measures of lung function, symptoms (CAT score), and percentage of BAL neutrophils.

Further information is provided in Supplementary Table 3.