Steven L Taylor1, Lex E X Leong1, Jocelyn M Choo1, Steve Wesselingh1, Ian A Yang2, John W Upham3, Paul N Reynolds4, Sandra Hodge4, Alan L James5, Christine Jenkins6, Matthew J Peters7, Melissa Baraket8, Guy B Marks9, Peter G Gibson10, Jodie L Simpson11, Geraint B Rogers12. 1. South Australian Health and Medical Research Institute, Adelaide, Australia; SAHMRI Microbiome Research Laboratory, School of Medicine, Flinders University, Adelaide, Australia. 2. School of Medicine, University of Queensland, St Lucia, Australia; Department of Thoracic Medicine, The Prince Charles Hospital, Chermside, Australia. 3. School of Medicine, University of Queensland, St Lucia, Australia; Translational Research Institute, Princess Alexandra Hospital, Woolloongabba, Australia. 4. Department of Thoracic Medicine, Royal Adelaide Hospital and Lung Research Laboratory, Hanson Institute, Adelaide, Australia; School of Medicine, University of Adelaide, Adelaide, Australia. 5. Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Nedlands, Australia; School of Medicine and Pharmacology, University of Western Australia, Crawley, Australia. 6. Respiratory Trials, George Institute for Global Health, Newtown, Australia; Australian School of Advanced Medicine, Macquarie University, North Ryde, Australia. 7. Australian School of Advanced Medicine, Macquarie University, North Ryde, Australia; Department of Thoracic Medicine, Concord General Hospital, Concord, Australia. 8. Respiratory Medicine Department and Ingham Institute, Liverpool Hospital, Liverpool, Australia; South Western Sydney Clinical School, University of New South Wales, Sydney, Australia. 9. Respiratory Medicine Department and Ingham Institute, Liverpool Hospital, Liverpool, Australia; Woolcock Institute of Medical Research, Glebe, Australia; South Western Sydney Clinical School, University of New South Wales, Sydney, Australia. 10. Woolcock Institute of Medical Research, Glebe, Australia; Respiratory and Sleep Medicine, Priority Research Centre for Healthy Lungs, University of Newcastle, Callaghan, Australia. 11. Respiratory and Sleep Medicine, Priority Research Centre for Healthy Lungs, University of Newcastle, Callaghan, Australia. 12. South Australian Health and Medical Research Institute, Adelaide, Australia; SAHMRI Microbiome Research Laboratory, School of Medicine, Flinders University, Adelaide, Australia. Electronic address: geraint.rogers@sahmri.com.
Abstract
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.
RCT Entities:
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.
Authors: Claire Healy; Natalia Munoz-Wolf; Janné Strydom; Lynne Faherty; Niamh C Williams; Sarah Kenny; Seamas C Donnelly; Suzanne M Cloonan Journal: Respir Res Date: 2021-04-29
Authors: Juliana Durack; Laura S Christian; Snehal Nariya; Jeanmarie Gonzalez; Nirav R Bhakta; K Mark Ansel; Avraham Beigelman; Mario Castro; Anne-Marie Dyer; Elliot Israel; Monica Kraft; Richard J Martin; David T Mauger; Stephen P Peters; Sharon R Rosenberg; Christine A Sorkness; Michael E Wechsler; Sally E Wenzel; Steven R White; Susan V Lynch; Homer A Boushey; Yvonne J Huang Journal: J Allergy Clin Immunol Date: 2020-04-13 Impact factor: 10.793