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Lung microbiome dynamics in chronic obstructive pulmonary disease exacerbations

Zhang Wang, Mona Bafadhel, Koirobi Haldar, Aaron Spivak, David Mayhew, Bruce E. Miller, Ruth Tal-Singer, Sebastian L. Johnston, Mohammadali Yavari Ramsheh, Michael R. Barer, Christopher E. Brightling, James R. Brown
European Respiratory Journal 2016; DOI: 10.1183/13993003.01406-2015
Zhang Wang
1Computational Biology, Target Sciences, GSK R&D, Collegeville, PA, USA
7These authors contributed equally
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Mona Bafadhel
2Respiratory Medicine Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
7These authors contributed equally
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Koirobi Haldar
3Institute for Lung Health, National Institute for Health Research Respiratory Biomedical Research Unit, Department of Infection, Immunity and Inflammation, University of Leicester, Leicester, UK
6Department of Health Sciences, University of Leicester, Leicester, UK
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Aaron Spivak
1Computational Biology, Target Sciences, GSK R&D, Collegeville, PA, USA
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David Mayhew
1Computational Biology, Target Sciences, GSK R&D, Collegeville, PA, USA
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Bruce E. Miller
4Respiratory Therapy Area Unit, GSK R&D, King of Prussia, PA, USA
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Ruth Tal-Singer
4Respiratory Therapy Area Unit, GSK R&D, King of Prussia, PA, USA
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Sebastian L. Johnston
5Airway Disease Infection Section, National Heart and Lung Institute, Imperial College London, London, UK
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Mohammadali Yavari Ramsheh
3Institute for Lung Health, National Institute for Health Research Respiratory Biomedical Research Unit, Department of Infection, Immunity and Inflammation, University of Leicester, Leicester, UK
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Michael R. Barer
3Institute for Lung Health, National Institute for Health Research Respiratory Biomedical Research Unit, Department of Infection, Immunity and Inflammation, University of Leicester, Leicester, UK
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Christopher E. Brightling
3Institute for Lung Health, National Institute for Health Research Respiratory Biomedical Research Unit, Department of Infection, Immunity and Inflammation, University of Leicester, Leicester, UK
6Department of Health Sciences, University of Leicester, Leicester, UK
8Both authors contributed equally
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  • For correspondence: ceb17@leicester.ac.uk
James R. Brown
1Computational Biology, Target Sciences, GSK R&D, Collegeville, PA, USA
8Both authors contributed equally
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  • FIGURE 1
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    FIGURE 1

    Flow diagram for BEAT-COPD (Biomarkers to Target Antibiotic and Systemic Corticosteroid Therapy in COPD Exacerbations) subject enrolment.

  • FIGURE 2
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    FIGURE 2

    Microbiome shifts during exacerbations. a) α diversity (Faith's phylogenetic diversity (PD)) and composition of major taxonomic groups at both phylum and genus levels in samples collected across the four visit types: stable, exacerbation (Exac), post-therapy (Post) and recovery (Rec). b) Box and whisker plots showing the relative abundances of Streptococcus, Haemophilus and Moraxella in samples collected across the four visits. c) Heterogeneity in Moraxella changes among individuals. Lines connect paired stable and exacerbation samples collected in the same visit series from the same subjects, and were coloured by increase or decrease of Moraxella during exacerbations. Only paired stable and exacerbation samples were included.

  • FIGURE 3
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    FIGURE 3

    The microbiome discriminates bacterial and eosinophilic exacerbations. a) α diversity (Shannon's H) and composition of major taxonomic groups at both phylum and genus levels in exacerbation samples with different exacerbation phenotypes. The number of samples is indicated for each subgroup in the bar chart. b) Principal coordinate analysis (PCoA) and c) unweighted pair group method with arithmetic mean clustering show distinct clustering of samples in bacterial and eosinophilic subgroups. d) Partial least squares discriminant analysis classification of bacterial and eosinophilic exacerbations using clinical, microbiome and their combined variables at both phylum (L6) and operational taxonomic unit (OTU) levels. The models were evaluated in terms of area under the curve (AUC), R2 and Q2 scores. B: bacterial; V: viral; E: eosinophilic; BE: bacterial and eosinophilic; BV: bacterial and viral; and Pauci: pauci-inflammatory. *: p<0.05.

  • FIGURE 4
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    FIGURE 4

    Microbiome changes due to oral corticosteroids and antibiotics. α diversity (Shannon's H) and composition of major taxonomic groups at both phylum and genus levels in exacerbations (Exac), post-therapy (Post) and recovery (Rec) samples of subjects treated with steroids, antibiotics or a combination of both. Only visit series with a complete cycle of exacerbation, post-therapy and recovery visits were included. The number of visit series is indicated for each subgroup. *: p<0.05 using ANOVA.

  • FIGURE 5
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    FIGURE 5

    Bacterial co-existence and co-exclusion relationships with operational taxonomic units (OTUs) and host factors. Interaction networks of a) microbiome and b) microbiome and clinical factors. Each node represents an OTU or a clinical trait. The OTUs were coloured by the class-level taxonomy. The five co-existence OTUs are highlighted in the dotted ellipse in a). The clinical traits were grouped together at the left of the network in b). Each edge represents a significant correlation coloured by co-existence or co-exclusion relationships. Edge width is proportional to the absolute value of Pearson correlation coefficient. The size of the node is proportional to its degree of connectivity. The degrees are shown in parentheses for highly connected nodes. For the clinical variables, both the total degree and the degree of connectivity to OTUs are shown. MMP: matrix metalloproteinase; CXCL: chemokine (C-X-C motif) ligand; IL: interleukin.

Tables

  • Figures
  • Additional Files
  • TABLE 1

    Major clinical characteristics of subjects at baseline

    Sex male/female65/22
    Age at baseline68 (45–87)
    Age at diagnosis61 (30–83)
    BMI kg·m−226.40 (16.67–38.19)
    GOLD stage#
     11
     235
     332
     419
    Smoking status 
     Current smoker37
     Ex-smoker48
     Nonsmoker2
    Smoking history pack-years50 (6–158)
    Number of exacerbations
     146
     231
     39
     41
    Treatment¶,+
     Antibiotics21
     Steroids8
     Antibiotics and steroids65
    FEV1 L1.3±0.1
    FEV1 % pred47.4±2.0
    FEV1/FVC ratio46.7±1.4
    CRQ score16.2±0.5
    Symptom VAS total mm159.6±8.5
    SGRQ score52.9±1.9
    • Data are presented as n, mean (range) or mean±sem. BMI: body mass index; GOLD: Global Initiative for Chronic Obstructive Lung Disease; FEV1: forced expiratory volume in 1s; FVC: forced vital capacity; CRQ: Chronic Respiratory Disease Questionnaire; VAS: visual analogue scale; SGRQ: St George's Respiratory Questionnaire. #: baseline visits prior to the stable visits for sputum collection; ¶: treatments administered for exacerbations; assessments at exacerbation were prior to initiation of therapy; +: numbers represent exacerbation events, thus include subjects with more than one exacerbation.

  • TABLE 2

    Major clinical characteristics of subjects over four visits

    Visitsp-value
    StableExacerbationPost-therapyRecovery
    Visits10613713697
    FEV1 L1.3±0.11.1±0.11.2±0.11.2±0.10.1
    FEV1 % pred49.6±1.848.1±1.648.5±1.649.0±2.00.94
    FEV1/FVC ratio48.0±1.348.9±1.349.2±1.248.7±1.40.92
    CRQ score16.6±0.512.7±0.416.0±0.416.6±0.5<0.001
    Symptom VAS total mm174.2±8.5255.7±6.5150.2±7.5151.7±8.5<0.001
    Sputum pathogen detection475542320.30
    Sputum cell count cells×106·g−15.8 (4.4–7.3)14.6 (11.7–17.5)8.1 (5.7–10.4)5.1 (3.6–6.6)<0.001#
    Sputum neutrophil count %69.1 (64.8–73.5)79.1 (75.4–82.9)74.2 (70.6–77.8)68.7 (63.9–73.5)<0.001
    Sputum eosinophil count %2.8 (1.9–3.7)4.3 (2.6–6.0)1.5 (1.0–2.0)3.8 (2.3–5.3)<0.01#
    Sputum lymphocyte count %0.5 (0.4–0.7)0.5 (0.4–0.6)0.6 (0.4–0.7)0.5 (0.4–0.7)0.91
    Blood cell count cells×109·L−18.3 (7.7–8.9)9.5 (8.8–10.2)10.4 (9.5–11.2)8.8 (8.1–9.6)<0.01
    Blood neutrophils cells×109·L−15.5 (5.1–5.9)6.9 (6.4–7.4)7.6 (7.1–8.2)5.9 (5.4–6.4)<0.001
    Blood eosinophils cells×109·L−10.2 (0.2–0.3)0.3 (0.2–0.3)0.2 (0.2–0.3)0.3 (0.2–0.3)0.16
    Blood lymphocytes cells×109·L−12.1 (1.9–2.3)2.1 (2.0–2.3)2.3 (2.1–2.5)2.2 (2.0–2.5)0.29
    Blood basophils cells×109·L−10.04 (0.03–0.04)0.04 (0.04–0.04)0.04 (0.04–0.04)0.04 (0.04–0.05)0.62
    • Data are presented as n, mean±sem or mean (95% CI). FEV1: forced expiratory volume in 1 s; FVC: forced vital capacity; CRQ: Chronic Respiratory Disease Questionnaire; VAS: visual analogue score. #: these variables were log transformed for statistical analysis.

  • TABLE 3

    The prevalence (P) and average relative abundance (RA) of predominant operational taxonomic units (OTUs) (average relative abundance >1%) in the lung microbiome

    OTU IDSpecies/subspeciesAllStableExacerbationPost-therapyRecovery
    PRAPRAPRAPRAPRA
    Visits n47610613713697
    4439603Streptococcus spp.82.113.183.012.378.811.682.413.485.615.8
    4445466Streptococcus spp.44.710.147.212.145.38.946.310.139.29.5
    509773Streptococcus spp.78.46.685.87.380.36.371.36.277.36.9
    1059655Streptococcus spp.31.55.230.25.233.65.430.94.930.95.6
    4462083Streptococcus infantis31.73.929.24.332.14.031.64.234.03.0
    240755Haemophilus spp.69.710.761.39.572.312.471.39.573.211.3
    956702Haemophilus spp.25.25.133.06.524.15.123.55.420.63.0
    4385138Haemophilus spp.23.51.425.50.827.01.922.10.918.61.9
    861881Moraxella spp.46.25.645.35.057.710.041.93.437.13.3
    269930Pseudomonas veronii33.82.442.53.032.82.632.42.227.81.8
    269901Pseudomonas spp.12.81.614.21.812.41.214.71.49.32.4
    342427Veillonella dispar93.32.791.52.493.42.294.93.292.83.0
    4326277Unclassified in Gemellaceae84.02.688.72.881.82.378.72.489.73.0
    4411138Rothia mucilaginosa73.12.475.53.074.52.371.32.171.12.5
    4396235Neisseria spp.58.62.260.42.359.92.255.92.458.81.8
    12574Actinomyces spp.79.21.684.01.779.61.372.81.782.51.7
    257492Granulicatella spp.83.81.486.81.485.41.280.91.382.51.7
    4307391Prevotella melaninogenica39.11.141.51.139.41.240.41.234.00.8
    • Data are presented as %, unless otherwise stated. The OTUs were firstly grouped by their genera and then ranked by their RAs.

  • TABLE 4

    List of clinical variables significantly associated with microbial α and β diversity in group I subjects

    α diversityβ diversity
    Shannon's HObserved speciesFaith's phylogenetic diversityChao1Positive/negative correlationOTUGenus (L6)Phylum (L2)
    Sputum CXCL8/IL-8**********Negative#****
    Baseline SGRQ symptom#*********Negative
    BMI***#Positive###,¶
    Sputum CXCL11/ITAC#****Positive
    Serum TNF-α**##Positive
    Serum SAA-1#**#Positive
    Serum CCL26/eotaxin3*###Negative
    Serum CSF-2*###Positive##*
    Serum IL-10*###Positive
    Sputum MMP-8#*##Negative
    Blood monocytes##**#Positive
    Blood basophils##*#Positive
    Serum MMP-7****#
    Sputum neutrophil percentage******
    Exacerbation frequency###,¶
    • OTU: operational taxonomic units; CXCL: chemokine (C-X-C motif) ligand; IL: interleukin; SGRQ: St George's Respiratory Questionnaire; BMI: body mass index; ITAC: interferon inducible T-cell α chemoattractant; TNF: tumour necrosis factor; SAA: serum amyloid A; CCL: CC-chemokine ligand; CSF: colony stimulating factor; MMP: matrix metalloproteinase. #: p≥0.05 and absent in the model; ¶: not significantly associated with L2 β diversity, but present in its model. *: p<0.05; **: p<0.01; ***: p<0.001.

Additional Files

  • Figures
  • Tables
  • Disclosures

    • M. Bafadhel
    • J.R. Brown
    • D. Mayhew
    • B.E. Miller
    • A. Spivak
    • R. Tal-Singer
    • Z. Wang
  • Supplementary material

    Please note: supplementary material is not edited by the Editorial Office, and is uploaded as it has been supplied by the author.

    • Supplementary material - Supplementary methods, figures S1-S5 and tables S1-S5
    • Supplementary table 1
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Lung microbiome dynamics in chronic obstructive pulmonary disease exacerbations
Zhang Wang, Mona Bafadhel, Koirobi Haldar, Aaron Spivak, David Mayhew, Bruce E. Miller, Ruth Tal-Singer, Sebastian L. Johnston, Mohammadali Yavari Ramsheh, Michael R. Barer, Christopher E. Brightling, James R. Brown
European Respiratory Journal Feb 2016, ERJ-01406-2015; DOI: 10.1183/13993003.01406-2015

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Lung microbiome dynamics in chronic obstructive pulmonary disease exacerbations
Zhang Wang, Mona Bafadhel, Koirobi Haldar, Aaron Spivak, David Mayhew, Bruce E. Miller, Ruth Tal-Singer, Sebastian L. Johnston, Mohammadali Yavari Ramsheh, Michael R. Barer, Christopher E. Brightling, James R. Brown
European Respiratory Journal Feb 2016, ERJ-01406-2015; DOI: 10.1183/13993003.01406-2015
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