RESUMO
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is an inflammatory lung disorder associated with lung microbiome dysbiosis. Although the upper airway microbiome is the source of the lung microbiome, the relationships between the oral, nasal, and sputum microbiota are incompletely understood. Our objective was to determine features that differentiate the oral, nasal, and sputum microbiome among subjects with stable COPD. METHODS: We recruited 15 current or former smokers to provide oral and sputum samples on day 1. On day 2, another oral sample and a nasal sample were obtained. Each sample and control underwent DNA extraction, 16S V4 rRNA amplification, 16S V4 sequencing, and qPCR of 16S rRNA. Data were analyzed using dada2 and R. RESULTS: Most (14 of 15) subjects were male with a mean age of 65.2. One subject had no pulmonary obstruction, while 5 had mild COPD, 7 had moderate COPD, and 2 had severe COPD. Three subjects (20%) were current tobacco users and 2 subjects (13%) used inhaled corticosteroids (ICS). Subjects had a mean of 49.1 pack-years of tobacco exposure. Bacterial biomass was associated with anatomic site, but no differences in biomass were observed with age, FEV1 percent predicted (FEV1pp), ICS use, smoking status, or edentulous state. Shannon index was associated with site (lower nasal diversity than oral and sputum diversity, p<0.001), but not age, ICS use, FEV1pp, tobacco use, or edentulous state. ß-diversity was illustrated by principal coordinate analysis using Bray-Curtis dissimilarity and PERMANOVA analyses, showing sample clustering by anatomic site (p = 0.001) with nasal samples forming a cluster separate from the combined oral wash samples and sputum samples. Clustering was also observed with ICS use (p = 0.029) and edentulous state (p = 0.019), while FEV1pp and current tobacco use were not significant. In an amplicon sequencing variant (ASV)-level analysis of oral samples using a linear regression model with Benjamini-Hochberg correction at an FDR<0.10, 10 ASVs were associated with age while no ASVs were associated with FEV1pp or smoking status. Sputum sample analysis demonstrated that 51 ASVs (25 unique genera) were associated with age, 61 ASVs (32 genera) were associated with FEV1pp, and no ASVs were associated with smoking status. In a combined dataset, the frequent exacerbator phenotype, rather than ICS use, was associated with decreased sputum Shannon diversity. CONCLUSIONS: Among the upper airway microbiota of COPD subjects, anatomic site was associated with bacterial biomass, Shannon diversity, and ß-diversity. ICS use and edentulous state were both associated with ß-diversity. Age was associated with taxa relative abundance in oral and sputum samples, while FEV1pp was associated with taxa relative abundance in sputum samples only.
Assuntos
Mucosa Laríngea/microbiologia , Microbiota , Mucosa Nasal/microbiologia , Doença Pulmonar Obstrutiva Crônica/microbiologia , Idoso , Feminino , Humanos , Masculino , Metagenoma , Pessoa de Meia-Idade , Doença Pulmonar Obstrutiva Crônica/epidemiologia , Doença Pulmonar Obstrutiva Crônica/patologia , Fumar/epidemiologia , Escarro/microbiologiaRESUMO
BACKGROUND: Chronic obstructive pulmonary disease (COPD) frequent exacerbators (FE) suffer increased morbidity and mortality compared to infrequent exacerbators (IE). The association between the oral and sputum microbiota and exacerbation phenotype is not well defined. The objective of this study was to determine key features that differentiate the oral and sputum microbiota of FEs from the microbiota of IEs during periods of clinical stability. METHODS: We recruited 11 FE and 11 IE who had not used antibiotics or systemic corticosteroids in the last 1 month. Subjects provided oral wash and sputum samples, which underwent 16S V4 MiSeq sequencing and qPCR of 16S rRNA. Data were analyzed using Dada2 and R. RESULTS: FE and IE were similar in terms of age, FEV1 percent predicted (FEV1pp), pack-years of tobacco exposure, and St. George's Respiratory Questionnaire score. 16S copy numbers were significantly greater in sputum vs. oral wash (p = 0.01), but phenotype was not associated with copy number. Shannon diversity was significantly greater in oral samples compared to sputum (p = 0.001), and IE samples were more diverse than FE samples (p < 0.001). Sputum samples from FE had more Haemophilus and Moraxella compared to IE sputum samples, due to dominance of these COPD-associated taxa in three FE sputum samples. Amplicon sequencing variant (ASV)-level analysis of sputum samples revealed one ASV (Actinomyces) was significantly more abundant in IE vs. FE sputum (padj = 0.048, Wilcoxon rank-sum test), and this persisted after controlling for FEV1pp. Principal coordinate analysis using Bray-Curtis distance with PERMANOVA analyses demonstrated clustering by anatomic site, phenotype, inhaled corticosteroid use, current tobacco use, COPD severity, and last professional dental cleaning. CONCLUSIONS: FE have less diverse oral and sputum microbiota than IE. Actinomyces was significantly more abundant in IE sputum than FE sputum. The oral and sputum microbiota of COPD subjects cluster based on multiple clinical factors, including exacerbation phenotype. Even during periods of clinical stability, the frequent exacerbator phenotype is associated with decreased alpha diversity, beta-diversity clustering, and changes in taxonomic abundance.