Abstract
RATIONALE: While studies suggest that the lung microbiome may influence risk of chronic obstructive pulmonary disease (COPD) exacerbations, little is known about the relationship between the nasal biome and clinical characteristics of COPD patients. METHODS: We sampled the nasal lining fluid by nasosorption of both nares of 20 people with moderate-to-severe COPD. All 40 samples, plus 4 negative controls, underwent DNA extraction, and 16SV4 ribosomal RNA (rRNA) (bacterial) and ribosomal internal transcribed spacer 2 (ITS2) (fungal) sequencing. We measured the proportion of variance (R(2)) in beta diversity explained by clinical factors, including age, sex, body mass index (BMI), COPD treatment, disease severity (forced expiratory volume in 1 second [FEV(1)], symptom/exacerbation frequency), peripheral eosinophil level (≥150 versus <150 cells/µL) and season of sampling, with the PERMANOVA test on the Bray-Curtis dissimilarities, accounting for within-person correlation of samples. We assessed the relative abundance of microbial features in the nasal community and their associations with clinical characteristics using the Microbiome Multivariable Association with Linear Models (MaAsLin2) package. RESULTS: The most abundant nasal fluid bacterial taxa were Corynebacterium, Staphylococcus, Streptococcus, Moraxella, and Dolosigranulum, and fungal taxa were Malassezia, Candida, Malasseziales, Cladosporium and Aspergillus. Bacterial microbiome composition was associated with short-acting muscarinic antagonist use (R(2) 11.8%, p=0.002), sex (R(2) 8.3%, p=0.044), nasal steroid use (R(2) 7.7%, p=0.064), and higher eosinophil level (R(2) 7.6%, p=0.084). Mycobiome composition was associated with higher eosinophil level (R(2) 14.4%, p=0.004) and low FEV(1) (R(2) 7.5%, p=0.071). No specific bacterium or fungus differed significantly in relative abundance by clinical characteristics in the multivariate per-feature analysis. CONCLUSION: The taxonomical composition of the nasal biome is heterogeneous in COPD patients and may be explained in part by clinical characteristics.