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Inflammatory phenotypes in patients with severe asthma are associated with distinct airway microbiology

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... Full description

Journal Title: Journal of allergy and clinical immunology 2017, Vol.141 (1), p.94-103.e15
Main Author: Taylor, Steven L., BSc
Other Authors: Leong, Lex E.X., PhD , Choo, Jocelyn M., PhD , Wesselingh, Steve, FRACP, PhD , Yang, Ian A., FRACP, PhD , Upham, John W., FRACP, PhD , Reynolds, Paul N., MBBS, PhD , Hodge, Sandra, PhD , James, Alan L., FRACP, PhD , Jenkins, Christine, MBBS, FRACP , Peters, Matthew J., MD, FRACP , Baraket, Melissa, FRACP, PhD , Marks, Guy B., MBBS, PhD , Gibson, Peter G., MBBS, FRACP , Simpson, Jodie L., PhD , Rogers, Geraint B., PhD
Format: Electronic Article Electronic Article
Language: English
Subjects:
DNA
Quelle: Alma/SFX Local Collection
Publisher: United States: Elsevier Inc
ID: ISSN: 0091-6749
Link: https://www.ncbi.nlm.nih.gov/pubmed/28479329
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title: Inflammatory phenotypes in patients with severe asthma are associated with distinct airway microbiology
format: Article
creator:
  • Taylor, Steven L., BSc
  • Leong, Lex E.X., PhD
  • Choo, Jocelyn M., PhD
  • Wesselingh, Steve, FRACP, PhD
  • Yang, Ian A., FRACP, PhD
  • Upham, John W., FRACP, PhD
  • Reynolds, Paul N., MBBS, PhD
  • Hodge, Sandra, PhD
  • James, Alan L., FRACP, PhD
  • Jenkins, Christine, MBBS, FRACP
  • Peters, Matthew J., MD, FRACP
  • Baraket, Melissa, FRACP, PhD
  • Marks, Guy B., MBBS, PhD
  • Gibson, Peter G., MBBS, FRACP
  • Simpson, Jodie L., PhD
  • Rogers, Geraint B., PhD
subjects:
  • Abridged Index Medicus
  • Abundance
  • Adult
  • Aged
  • Allergy and Immunology
  • Asthma
  • Asthma - immunology
  • Asthma - microbiology
  • Bacteria - classification
  • Bacteria - genetics
  • Bacteria - immunology
  • Cystic fibrosis
  • Deoxyribonucleic acid
  • DNA
  • eosinophil
  • Female
  • Flight corridors
  • Gene expression
  • Gene sequencing
  • Genotype & phenotype
  • Health risks
  • Humans
  • Inflammation
  • Leukocytes (eosinophilic)
  • Leukocytes (neutrophilic)
  • Lungs
  • Male
  • Microbiology
  • microbiome
  • Microbiota
  • Microbiota - genetics
  • Microbiota - immunology
  • Middle Aged
  • Network analysis
  • neutrophil
  • Neutrophils
  • Neutrophils - immunology
  • Patients
  • Phylogenetics
  • Pneumonia
  • Relative abundance
  • Respiratory tract
  • Respiratory tract diseases
  • RNA, Bacterial - genetics
  • RNA, Bacterial - immunology
  • RNA, Ribosomal, 16S - genetics
  • RNA, Ribosomal, 16S - immunology
  • rRNA 16S
  • Sample variance
  • Severity of Illness Index
  • Software
  • Sputum
  • Taxa
ispartof: Journal of allergy and clinical immunology, 2017, Vol.141 (1), p.94-103.e15
description: 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  
language: eng
source: Alma/SFX Local Collection
identifier: ISSN: 0091-6749
fulltext: fulltext
issn:
  • 0091-6749
  • 1097-6825
url: Link


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titleInflammatory phenotypes in patients with severe asthma are associated with distinct airway microbiology
sourceAlma/SFX Local Collection
creatorTaylor, Steven L., BSc ; Leong, Lex E.X., PhD ; Choo, Jocelyn M., PhD ; Wesselingh, Steve, FRACP, PhD ; Yang, Ian A., FRACP, PhD ; Upham, John W., FRACP, PhD ; Reynolds, Paul N., MBBS, PhD ; Hodge, Sandra, PhD ; James, Alan L., FRACP, PhD ; Jenkins, Christine, MBBS, FRACP ; Peters, Matthew J., MD, FRACP ; Baraket, Melissa, FRACP, PhD ; Marks, Guy B., MBBS, PhD ; Gibson, Peter G., MBBS, FRACP ; Simpson, Jodie L., PhD ; Rogers, Geraint B., PhD
creatorcontribTaylor, Steven L., BSc ; Leong, Lex E.X., PhD ; Choo, Jocelyn M., PhD ; Wesselingh, Steve, FRACP, PhD ; Yang, Ian A., FRACP, PhD ; Upham, John W., FRACP, PhD ; Reynolds, Paul N., MBBS, PhD ; Hodge, Sandra, PhD ; James, Alan L., FRACP, PhD ; Jenkins, Christine, MBBS, FRACP ; Peters, Matthew J., MD, FRACP ; Baraket, Melissa, FRACP, PhD ; Marks, Guy B., MBBS, PhD ; Gibson, Peter G., MBBS, FRACP ; Simpson, Jodie L., PhD ; Rogers, Geraint B., PhD
descriptionBackground 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.
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0ISSN: 0091-6749
1EISSN: 1097-6825
2DOI: 10.1016/j.jaci.2017.03.044
3PMID: 28479329
languageeng
publisherUnited States: Elsevier Inc
subjectAbridged Index Medicus ; Abundance ; Adult ; Aged ; Allergy and Immunology ; Asthma ; Asthma - immunology ; Asthma - microbiology ; Bacteria - classification ; Bacteria - genetics ; Bacteria - immunology ; Cystic fibrosis ; Deoxyribonucleic acid ; DNA ; eosinophil ; Female ; Flight corridors ; Gene expression ; Gene sequencing ; Genotype & phenotype ; Health risks ; Humans ; Inflammation ; Leukocytes (eosinophilic) ; Leukocytes (neutrophilic) ; Lungs ; Male ; Microbiology ; microbiome ; Microbiota ; Microbiota - genetics ; Microbiota - immunology ; Middle Aged ; Network analysis ; neutrophil ; Neutrophils ; Neutrophils - immunology ; Patients ; Phylogenetics ; Pneumonia ; Relative abundance ; Respiratory tract ; Respiratory tract diseases ; RNA, Bacterial - genetics ; RNA, Bacterial - immunology ; RNA, Ribosomal, 16S - genetics ; RNA, Ribosomal, 16S - immunology ; rRNA 16S ; Sample variance ; Severity of Illness Index ; Software ; Sputum ; Taxa
ispartofJournal of allergy and clinical immunology, 2017, Vol.141 (1), p.94-103.e15
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0Taylor, Steven L., BSc
1Leong, Lex E.X., PhD
2Choo, Jocelyn M., PhD
3Wesselingh, Steve, FRACP, PhD
4Yang, Ian A., FRACP, PhD
5Upham, John W., FRACP, PhD
6Reynolds, Paul N., MBBS, PhD
7Hodge, Sandra, PhD
8James, Alan L., FRACP, PhD
9Jenkins, Christine, MBBS, FRACP
10Peters, Matthew J., MD, FRACP
11Baraket, Melissa, FRACP, PhD
12Marks, Guy B., MBBS, PhD
13Gibson, Peter G., MBBS, FRACP
14Simpson, Jodie L., PhD
15Rogers, Geraint B., PhD
title
0Inflammatory phenotypes in patients with severe asthma are associated with distinct airway microbiology
1Journal of allergy and clinical immunology
addtitleJ Allergy Clin Immunol
descriptionBackground 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.
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1Abundance
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3Aged
4Allergy and Immunology
5Asthma
6Asthma - immunology
7Asthma - microbiology
8Bacteria - classification
9Bacteria - genetics
10Bacteria - immunology
11Cystic fibrosis
12Deoxyribonucleic acid
13DNA
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15Female
16Flight corridors
17Gene expression
18Gene sequencing
19Genotype & phenotype
20Health risks
21Humans
22Inflammation
23Leukocytes (eosinophilic)
24Leukocytes (neutrophilic)
25Lungs
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27Microbiology
28microbiome
29Microbiota
30Microbiota - genetics
31Microbiota - immunology
32Middle Aged
33Network analysis
34neutrophil
35Neutrophils
36Neutrophils - immunology
37Patients
38Phylogenetics
39Pneumonia
40Relative abundance
41Respiratory tract
42Respiratory tract diseases
43RNA, Bacterial - genetics
44RNA, Bacterial - immunology
45RNA, Ribosomal, 16S - genetics
46RNA, Ribosomal, 16S - immunology
47rRNA 16S
48Sample variance
49Severity of Illness Index
50Software
51Sputum
52Taxa
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4Yang, Ian A., FRACP, PhD
5Upham, John W., FRACP, PhD
6Reynolds, Paul N., MBBS, PhD
7Hodge, Sandra, PhD
8James, Alan L., FRACP, PhD
9Jenkins, Christine, MBBS, FRACP
10Peters, Matthew J., MD, FRACP
11Baraket, Melissa, FRACP, PhD
12Marks, Guy B., MBBS, PhD
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titleInflammatory phenotypes in patients with severe asthma are associated with distinct airway microbiology
authorTaylor, Steven L., BSc ; Leong, Lex E.X., PhD ; Choo, Jocelyn M., PhD ; Wesselingh, Steve, FRACP, PhD ; Yang, Ian A., FRACP, PhD ; Upham, John W., FRACP, PhD ; Reynolds, Paul N., MBBS, PhD ; Hodge, Sandra, PhD ; James, Alan L., FRACP, PhD ; Jenkins, Christine, MBBS, FRACP ; Peters, Matthew J., MD, FRACP ; Baraket, Melissa, FRACP, PhD ; Marks, Guy B., MBBS, PhD ; Gibson, Peter G., MBBS, FRACP ; Simpson, Jodie L., PhD ; Rogers, Geraint B., PhD
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0Abridged Index Medicus
1Abundance
2Adult
3Aged
4Allergy and Immunology
5Asthma
6Asthma - immunology
7Asthma - microbiology
8Bacteria - classification
9Bacteria - genetics
10Bacteria - immunology
11Cystic fibrosis
12Deoxyribonucleic acid
13DNA
14eosinophil
15Female
16Flight corridors
17Gene expression
18Gene sequencing
19Genotype & phenotype
20Health risks
21Humans
22Inflammation
23Leukocytes (eosinophilic)
24Leukocytes (neutrophilic)
25Lungs
26Male
27Microbiology
28microbiome
29Microbiota
30Microbiota - genetics
31Microbiota - immunology
32Middle Aged
33Network analysis
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35Neutrophils
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37Patients
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40Relative abundance
41Respiratory tract
42Respiratory tract diseases
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5Upham, John W., FRACP, PhD
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abstractBackground 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.
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pmid28479329
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