Zhang Wang1, Nicholas Locantore2, Koirobi Haldar3, Mohammadali Yavari Ramsheh3, Augusta S Beech4, Wei Ma5, James R Brown6, Ruth Tal-Singer7, Michael R Barer3, Mona Bafadhel8, Gavin C Donaldson9, Jadwiga A Wedzicha9, Dave Singh4, Tom M A Wilkinson10, Bruce E Miller2, Christopher E Brightling3. 1. Institute of Ecological Sciences, School of Life Sciences, South China Normal University, Guangzhou, China. 2. Medical Innovation, Value Evidence and Outcomes, and. 3. Human Genetics, Research and Development, GlaxoSmithKline, Collegeville, Pennsylvania. 4. Department of Respiratory Sciences, Institute for Lung Health, Leicester National Institute for Health Research Biomedical Research Centre, University of Leicester, Leicester, United Kingdom. 5. Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom. 6. Institute of Statistics and Big Data, Renmin University of China, Beijing, China. 7. Chronic Obstructive Pulmonary Disease Foundation, Research Department, Washington, District of Columbia. 8. Respiratory Medicine Unit, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom. 9. National Heart and Lung Institute, Imperial College London, London, United Kingdom; and. 10. National Institute for Health Research Southampton Respiratory Biomedical Research Unit, University Hospital Southampton National Health Service Foundation Trust, Southampton, United Kingdom.
Abstract
Rationale: Understanding the role of the airway microbiome in chronic obstructive pulmonary disease (COPD) inflammatory endotypes may help to develop microbiome-based diagnostic and therapeutic approaches. Objectives: To understand the association of the airway microbiome with neutrophilic and eosinophilic COPD at stability and during exacerbations. Methods: An integrative analysis was performed on 1,706 sputum samples collected longitudinally from 510 patients with COPD recruited at four UK sites of the BEAT-COPD (Biomarkers to Target Antibiotic and Systemic COPD), COPDMAP (Chronic Obstructive Pulmonary Disease Medical Research Council/Association of the British Pharmaceutical Industry), and AERIS (Acute Exacerbation and Respiratory Infections in COPD) cohorts. The microbiome was analyzed using COPDMAP and AERIS as a discovery data set and BEAT-COPD as a validation data set. Measurements and Main Results: The airway microbiome in neutrophilic COPD was heterogeneous, with two primary community types differentiated by the predominance of Haemophilus. The Haemophilus-predominant subgroup had elevated sputum IL-1β and TNFα (tumor necrosis factor α) and was relatively stable over time. The other neutrophilic subgroup with a balanced microbiome profile had elevated sputum and serum IL-17A and was temporally dynamic. Patients in this state at stability were susceptible to the greatest microbiome shifts during exacerbations. This subgroup can temporally switch to both neutrophilic Haemophilus-predominant and eosinophilic states that were otherwise mutually exclusive. Time-series analysis on the microbiome showed that the temporal trajectories of Campylobacter and Granulicatella were indicative of intrapatient switches from neutrophilic to eosinophilic inflammation, in track with patient sputum eosinophilia over time. Network analysis revealed distinct host-microbiome interaction patterns among neutrophilic Haemophilus-predominant, neutrophilic balanced microbiome, and eosinophilic subgroups. Conclusions: The airway microbiome can stratify neutrophilic COPD into subgroups that justify different therapies. Neutrophilic and eosinophilic COPD are interchangeable in some patients. Monitoring temporal variability of the airway microbiome may track patient inflammatory status over time.
Rationale: Understanding the role of the airway microbiome in chronic obstructive pulmonary disease (COPD) inflammatory endotypes may help to develop microbiome-based diagnostic and therapeutic approaches. Objectives: To understand the association of the airway microbiome with neutrophilic and eosinophilic COPD at stability and during exacerbations. Methods: An integrative analysis was performed on 1,706 sputum samples collected longitudinally from 510 patients with COPD recruited at four UK sites of the BEAT-COPD (Biomarkers to Target Antibiotic and Systemic COPD), COPDMAP (Chronic Obstructive Pulmonary Disease Medical Research Council/Association of the British Pharmaceutical Industry), and AERIS (Acute Exacerbation and Respiratory Infections in COPD) cohorts. The microbiome was analyzed using COPDMAP and AERIS as a discovery data set and BEAT-COPD as a validation data set. Measurements and Main Results: The airway microbiome in neutrophilic COPD was heterogeneous, with two primary community types differentiated by the predominance of Haemophilus. The Haemophilus-predominant subgroup had elevated sputum IL-1β and TNFα (tumor necrosis factor α) and was relatively stable over time. The other neutrophilic subgroup with a balanced microbiome profile had elevated sputum and serum IL-17A and was temporally dynamic. Patients in this state at stability were susceptible to the greatest microbiome shifts during exacerbations. This subgroup can temporally switch to both neutrophilic Haemophilus-predominant and eosinophilic states that were otherwise mutually exclusive. Time-series analysis on the microbiome showed that the temporal trajectories of Campylobacter and Granulicatella were indicative of intrapatient switches from neutrophilic to eosinophilic inflammation, in track with patientsputum eosinophilia over time. Network analysis revealed distinct host-microbiome interaction patterns among neutrophilic Haemophilus-predominant, neutrophilic balanced microbiome, and eosinophilic subgroups. Conclusions: The airway microbiome can stratify neutrophilic COPD into subgroups that justify different therapies. Neutrophilic and eosinophilic COPD are interchangeable in some patients. Monitoring temporal variability of the airway microbiome may track patient inflammatory status over time.
Authors: Fernando J Martinez; Alvar Agusti; Bartolome R Celli; MeiLan K Han; James P Allinson; Surya P Bhatt; Peter Calverley; Sanjay H Chotirmall; Badrul Chowdhury; Patrick Darken; Carla A Da Silva; Gavin Donaldson; Paul Dorinsky; Mark Dransfield; Rosa Faner; David M Halpin; Paul Jones; Jerry A Krishnan; Nicholas Locantore; Fernando D Martinez; Hana Mullerova; David Price; Klaus F Rabe; Colin Reisner; Dave Singh; Jørgen Vestbo; Claus F Vogelmeier; Robert A Wise; Ruth Tal-Singer; Jadwiga A Wedzicha Journal: Am J Respir Crit Care Med Date: 2022-02-01 Impact factor: 21.405
Authors: Arindam Chakrabarti; Jordan S Mar; David F Choy; Yi Cao; Nisha Rathore; Xiaoying Yang; Gaik W Tew; Olga Li; Prescott G Woodruff; Christopher E Brightling; Michele Grimbaldeston; Stephanie A Christenson; Mona Bafadhel; Carrie M Rosenberger Journal: ERJ Open Res Date: 2021-08-02