TY - JOUR AU - Jenkins C. AU - Taylor Steven AU - Leong Lex AU - Choo Jocelyn AU - Wesselingh Steve AU - Yang Ian AU - Upham John AU - Reynolds Paul AU - Hodge Sandra AU - James Alan AU - Peters Matthew AU - Baraket Melissa AU - Marks Guy AU - Gibson Peter AU - Simpson Jodie AU - Rogers Geraint AB -

BACKGROUND: Asthma pathophysiology and treatment responsiveness are predicted by inflammatory phenotype. However, the relationship between airway microbiology and asthma phenotype is poorly understood.

OBJECTIVE: We aimed to characterize the airway microbiota in patients with symptomatic stable asthma and relate composition to airway inflammatory phenotype and other phenotypic characteristics.

METHODS: The microbial composition of induced sputum specimens collected from adult patients screened for a multicenter randomized controlled trial was determined by using 16S rRNA gene sequencing. Inflammatory phenotypes were defined by sputum neutrophil and eosinophil cell proportions. Microbiota were defined by using α- and β-diversity measures, and interphenotype differences were identified by using similarity of percentages, network analysis, and taxon fold change. Phenotypic predictors of airway microbiology were identified by using multivariate linear regression.

RESULTS: Microbiota composition was determined in 167 participants and classified as eosinophilic (n = 84), neutrophilic (n = 14), paucigranulocytic (n = 60), or mixed neutrophilic-eosinophilic (n = 9) asthma phenotypes. Airway microbiology was significantly less diverse (P = .022) and more dissimilar (P = .005) in neutrophilic compared with eosinophilic participants. Sputum neutrophil proportions, but not eosinophil proportions, correlated significantly with these diversity measures (α-diversity: Spearman r = -0.374, P < .001; β-diversity: r = 0.238, P = .002). Interphenotype differences were characterized by a greater frequency of pathogenic taxa at high relative abundance and reduced Streptococcus, Gemella, and Porphyromonas taxa relative abundance in patients with neutrophilic asthma. Multivariate regression confirmed that sputum neutrophil proportion was the strongest predictor of microbiota composition.

CONCLUSIONS: Neutrophilic asthma is associated with airway microbiology that is significantly different from that seen in patients with other inflammatory phenotypes, particularly eosinophilic asthma. Differences in microbiota composition might influence the response to antimicrobial and steroid therapies and the risk of lung infection.

BT - J Allergy Clin Immunol C1 - https://www.ncbi.nlm.nih.gov/pubmed/28479329?dopt=Abstract DO - 10.1016/j.jaci.2017.03.044 IS - 1 J2 - J. Allergy Clin. Immunol. LA - eng N2 -

BACKGROUND: Asthma pathophysiology and treatment responsiveness are predicted by inflammatory phenotype. However, the relationship between airway microbiology and asthma phenotype is poorly understood.

OBJECTIVE: We aimed to characterize the airway microbiota in patients with symptomatic stable asthma and relate composition to airway inflammatory phenotype and other phenotypic characteristics.

METHODS: The microbial composition of induced sputum specimens collected from adult patients screened for a multicenter randomized controlled trial was determined by using 16S rRNA gene sequencing. Inflammatory phenotypes were defined by sputum neutrophil and eosinophil cell proportions. Microbiota were defined by using α- and β-diversity measures, and interphenotype differences were identified by using similarity of percentages, network analysis, and taxon fold change. Phenotypic predictors of airway microbiology were identified by using multivariate linear regression.

RESULTS: Microbiota composition was determined in 167 participants and classified as eosinophilic (n = 84), neutrophilic (n = 14), paucigranulocytic (n = 60), or mixed neutrophilic-eosinophilic (n = 9) asthma phenotypes. Airway microbiology was significantly less diverse (P = .022) and more dissimilar (P = .005) in neutrophilic compared with eosinophilic participants. Sputum neutrophil proportions, but not eosinophil proportions, correlated significantly with these diversity measures (α-diversity: Spearman r = -0.374, P < .001; β-diversity: r = 0.238, P = .002). Interphenotype differences were characterized by a greater frequency of pathogenic taxa at high relative abundance and reduced Streptococcus, Gemella, and Porphyromonas taxa relative abundance in patients with neutrophilic asthma. Multivariate regression confirmed that sputum neutrophil proportion was the strongest predictor of microbiota composition.

CONCLUSIONS: Neutrophilic asthma is associated with airway microbiology that is significantly different from that seen in patients with other inflammatory phenotypes, particularly eosinophilic asthma. Differences in microbiota composition might influence the response to antimicrobial and steroid therapies and the risk of lung infection.

PY - 2018 SP - 94 EP - 103.e15 T2 - J Allergy Clin Immunol TI - Inflammatory phenotypes in patients with severe asthma are associated with distinct airway microbiology. VL - 141 SN - 1097-6825 ER -