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Acute Exacerbations of Chronic Obstructive
Pulmonary Disease
Identification of Biologic Clusters and Their Biomarkers
Mona Bafadhel1,2, Susan McKenna1, Sarah Terry1, Vijay Mistry1,2, Carlene Reid1, Pranabashis Haldar2,
Margaret McCormick3, Koirobi Haldar2, Tatiana Kebadze4, Annelyse Duvoix5, Kerstin Lindblad6,
Hemu Patel7, Paul Rugman3, Paul Dodson3, Martin Jenkins3, Michael Saunders3, Paul Newbold3,
Ruth H. Green1, Per Venge6, David A. Lomas5, Michael R. Barer2,7, Sebastian L. Johnston4,
Ian D. Pavord1, and Christopher E. Brightling1,2
1
 Institute for Lung Health, and 2Department of Infection, Immunity and Inflammation, University of Leicester, Leicester, United Kingdom;
3
 AstraZeneca R&D Charnwood, Loughborough, Leicestershire, United Kingdom; 4Department of Respiratory Medicine, National Heart and Lung
Institute, Centre for Respiratory Infections, Imperial College London, United Kingdom; 5Cambridge Institute for Medical Research, University of
Cambridge, Cambridge, United Kingdom; 6Department of Medical Sciences, Clinical Chemistry, University of Uppsala, Uppsala, Sweden; and
7
 Department of Clinical Microbiology, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom


Rationale: Exacerbations of chronic obstructive pulmonary disease
(COPD) are heterogeneous with respect to inflammation and etiology.                        AT A GLANCE COMMENTARY
Objectives: Investigate biomarker expression in COPD exacerbations
to identify biologic clusters and determine biomarkers that recog-                        Scientific Knowledge on the Subject
nize clinical COPD exacerbation phenotypes, namely those associ-                          Exacerbations of chronic obstructive pulmonary disease
ated with bacteria, viruses, or eosinophilic airway inflammation.                          (COPD) are a major health burden worldwide, and affect
Methods: Patients with COPD were observed for 1 year at stable and                        a vulnerable population at risk of significant comorbidities.
exacerbation visits. Biomarkers were measured in sputum and                               COPD exacerbations are heterogeneous with respect to
serum. Viruses and selected bacteria were assessed in sputum by                           etiology and inflammation and biomarkers are required to
polymerase chain reaction and routine diagnostic bacterial culture.
                                                                                          phenotype this heterogeneity.
Biologic phenotypes were explored using unbiased cluster analysis
and biomarkers that differentiated clinical exacerbation phenotypes
were investigated.                                                                        What This Study Adds to the Field
Measurements and Main Results: A total of 145 patients (101 men
and 44 women) entered the study. A total of 182 exacerbations                             We have shown that there are biologic COPD exacerbation
were captured from 86 patients. Four distinct biologic exacerbation                       clusters that are clinically indistinguishable, and that bio-
clusters were identified. These were bacterial-, viral-, or eosinophilic-                  markers can be used to identify specific clinical phenotypes
predominant, and a fourth associated with limited changes in the                          during exacerbations of COPD (specifically those associ-
inflammatory profile termed “pauciinflammatory.” Of all exacerba-                            ated with bacteria, virus, and sputum eosinophilia). Bac-
tions, 55%, 29%, and 28% were associated with bacteria, virus, or a                       terial and eosinophilic clinical exacerbation phenotypes can
                                                                                          be identified from stable state. Our data further delineate
                                                                                          the heterogeneity during COPD exacerbations and may
(Received in original form April 2, 2011; accepted in final form June 15, 2011)            identify populations that appropriately require cortico-
Supported by the Medical Research Council (United Kingdom) and AstraZeneca                steroids and antibiotics at the onset of an exacerbation.
jointly as a “Biomarker Call Project”; C.E.B. is a Wellcome Trust Senior Clinical
Fellow, and GlaxoSmithKline supported the measurement of surfactant protein
D. The research was performed in laboratories partly funded by the European
Regional Development Fund (ERDF 05567). The Medical Research Council, Well-
come Trust, and the European Regional Development Fund had no involvement               sputum eosinophilia. The biomarkers that best identified these clinical
in the design of the study, data collection, analysis and interpretation of the data,   phenotypes were sputum IL-1b, 0.89 (area under receiver operating
in the writing of the manuscript, or in the decision to submit the manuscript.
                                                                                        characteristic curve) (95% confidence interval [CI], 0.83–0.95); serum
Author Contributions: S.M. and S.T. were involved in the recruitment of volunteers      CXCL10, 0.83 (95% CI, 0.70–0.96); and percentage peripheral eosino-
and in data collection. C.R., V.M., K.H., H.P., A.D., and K.L. were involved in data    phils, 0.85 (95% CI, 0.78–0.93), respectively.
collection and interpretation. M.M., P.R., P.D., P.N., M.J., and M.S. were involved
                                                                                        Conclusions: The heterogeneity of the biologic response of COPD
in study design, data collection, and interpretation. R.H.G. and P.H. were in-
                                                                                        exacerbations can be defined. Sputum IL-1b, serum CXCL10, and
volved in study design and data interpretation. M.R.B., D.A.L., S.L.J., P.V., and
I.D.P. were involved in the design of the study, data collection, and interpreta-       peripheral eosinophils are biomarkers of bacteria-, virus-, or eosinophil-
tion. M.B. and C.E.B. were involved in the study design, volunteer recruitment,         associated exacerbations of COPD. Whether phenotype-specific bio-
data collection, data interpretation, and data analysis, and had full access to the     markers can be applied to direct therapy warrants further investigation.
data and are responsible for the integrity of the data and final decision to submit.
All authors contributed to the writing of the manuscript and have approved the          Keywords: chronic obstructive pulmonary disease; phenotypes; exac-
final version for submission.                                                            erbations; airway inflammation; infection
Correspondence and requests for reprints should be addressed to Christopher
E. Brightling, M.B.B.S., B.Sc. (Hons.), Ph.D., Institute for Lung Health, Clinical      Acute exacerbations of chronic obstructive pulmonary disease
Sciences Wing, University Hospitals of Leicester, Leicester, LE3 9QP, UK. E-mail:
                                                                                        (COPD) are associated with substantial morbidity and mortality
ceb17@le.ac.uk
                                                                                        (1, 2). Exacerbations are typically associated with increased neu-
This article has an online supplement, which is accessible from this issue’s table of
                                                                                        trophilic and to a lesser extent eosinophilic airway inflammation
contents at www.atsjournals.org
                                                                                        (3, 4). Respiratory viral and bacterial infections have been impli-
Am J Respir Crit Care Med Vol 184. pp 662–671, 2011
Originally Published in Press as DOI: 10.1164/rccm.201104-0597OC on June 16, 2011
                                                                                        cated in causing most exacerbations (5–7), but how these infec-
Internet address: www.atsjournals.org                                                   tions alter lower airway inflammation and relate to treatment
Bafadhel, McKenna, Terry, et al.: Biomarkers in COPD Exacerbations                                                                                  663


response is not completely understood. This heterogeneity trans-              and single ELISA at stable and exacerbation visits (see Table E1 in the
lates that at present clinicians have limited tools to phenotype              online supplement).
exacerbations. During stable state a sputum eosinophilia is asso-
ciated with corticosteroid responsiveness (8–10), whereas the                 Definition of Bacteria-, Virus-, and Sputum
presence of a high bacterial load and sputum purulence has favor-             Eosinophil–associated Exacerbations of COPD
able outcomes with antibiotics (11–15). These findings suggest                 Bacteria-associated exacerbations were defined as a positive bacterial
that it is possible to identify clinically important COPD exacer-             pathogen on routine culture (Haemophilus influenzae, Moraxella catar-
bation phenotypes. This is crucial because systemic corticosteroids           rhalis, Streptococcus pneumoniae, Staphylococcus aureus, or Pseudo-
and antibiotics have marginal efficacy (16–21) and the potential to            monas aeruginosa) or a total aerobic CFU count greater than or
cause adverse events in an already vulnerable population.                     equal to 107 cells (12, 15). qPCR bacterial detection methods were
    We hypothesize that approaches aimed at the identification of              not used to define bacteria-associated exacerbations in this study.
COPD exacerbation phenotypes may allow for better prognostic,                     A virus-associated exacerbation was defined as one that had a positive
therapeutic, and mechanistic applications (22–24). In this study              sputum viral PCR, whether in isolation or in combination with a positive
                                                                              bacterial pathogen on routine culture. A sputum eosinophil–associated
we investigated whether during exacerbations of COPD there are
                                                                              exacerbation was defined as the presence of more than 3% nonsquamous
(1) definable biologic phenotypes using unbiased mathematical                  cells.
tools (namely factor and cluster analysis); (2) identifiable bio-
markers associated with clinical phenotypes, specifically those
                                                                              Statistical Analyses
associated with bacteria, viruses, or sputum eosinophilia; and
(3) exacerbation phenotypes that can be predicted from stable                 Statistical analyses were performed using PRISM version 4 (Graph-
state.                                                                        PAD PRISM, La Jolla, CA) and SPSS version 16 (IBM, Chicago,
                                                                              IL). Parametric and nonparametric data are presented as mean
                                                                              (SEM) and median (interquartile range). Log transformed data are
METHODS                                                                       presented as geometric mean (95% confidence interval [CI]). Multi-
                                                                              variate modeling using principal component analysis in sputum bio-
Patients                                                                      markers was used to explore biomarker pattern expression at
Patients with a physician diagnosis of COPD and a post-bronchodilator         exacerbations. No adjustments for multiple comparisons have been
FEV1/FVC ratio of less than 0.7 as per global initiative for chronic          made across biomarkers.
obstructive lung disease (GOLD) criteria (1) were recruited from the              Factor analysis, a mathematical method that discovers patterns of
Glenfield Hospital, Leicester, United Kingdom, and through local ad-           relationships within large datasets, was used to identify factors in sputum
vertising. All patients fulfilled the inclusion criteria of age greater than   mediators at exacerbations thereby demonstrating biologic factors inde-
40 years, GOLD stage I–IV, and greater than or equal to one exacer-           pendent of each other and of any clinical expression. This method using
bation in the preceding 12 months defined as the requirement of emer-          unsupervised principal component analysis demonstrated three factors
gency health care (25). Patients were excluded if there was a documented      accounting for 75% of the total variance (see Table E2). Cluster analysis,
inability to produce sputum after the induced sputum procedure, a cur-        an unbiased mathematical method, allows one to classify groups on
rent or previous history of asthma, currently active pulmonary tubercu-       similar chosen characteristics alone. Thus, after demonstrating three bi-
losis, or any other clinically relevant lung disease other than COPD. The     ologic factors, we used hierarchical cluster analysis to generate four bi-
presence of comorbidity, reported atopy to common aeroallergens, or           ologic clusters for exacerbation events and cases. Clinical characteristics
reversibility on lung function testing was not an exclusion criterion. All    for all exacerbation events were tabulated for each biologic cluster. One-
patients gave informed written consent and the study was approved by          way analysis of variance, Kruskal-Wallis test, and the chi-square test
the local ethics committee.                                                   were used to compare the clinical characteristics between cluster groups.
                                                                                  For comparison of clinical and biomarker changes between baseline
                                                                              and exacerbation visits the paired t test or Wilcoxon matched pairs test
Study Design                                                                  was used. For comparison of exacerbations associated with or without
This was a prospective observational study. Patients were seen at stable      bacteria, virus, and sputum eosinophilia the t test and Mann-Whitney
state and during exacerbations for the duration of 1 year. Stable visits      test were used, respectively. To determine suitable biomarkers, the
including the baseline visits were 8 weeks free from an exacerbation. All     receiver operating characteristic curves were plotted for (1) exacerba-
patients were given daily diary cards to complete, and asked to contact       tion versus stable state; (2) bacteria- versus nonbacteria-associated
the research team if there was an increase in symptoms of breathless-         exacerbations; (3) virus- versus nonvirus-associated exacerbations;
ness, sputum volume, and purulence. Exacerbations were defined                 and (4) sputum eosinophilia– (. 3% nonsquamous cells) versus non-
according to Anthonisen criteria (14) and health care use (25). Exac-         sputum eosinophilia–associated exacerbations.
erbation data recording and sampling were only performed in patients              Validation of the identified biomarkers for bacteria-, virus-, and spu-
who had not received prior oral corticosteroids or antibiotics. Patients      tum eosinophil–associated exacerbation was performed in a further 89
were all clinically assessed (including chest radiograph, temperature         exacerbation events from an independent cohort of subjects with
recording, and blood gas analysis if clinically necessary) to exclude         COPD. These subjects with COPD were recruited to enter a prospec-
other causes of breathlessness. Patients with an exacerbation of COPD         tive study with identical inclusion and exclusion criteria and study de-
were then treated according to guidelines (2).                                sign as the current study. Stable and exacerbation visits were treated in
                                                                              accordance to the main study.
                                                                                  A P value of less than 0.05 was taken as the threshold of statistical
Measurements                                                                  significance.
At all visits, patients underwent pre– and post–400-mg albuterol broncho-
dilator spirometry (Vitalograph, Buckingham, Buckinghamshire, UK); in-        RESULTS
duced or spontaneous sputum collection (26); and measurements of
symptoms and health quality assessments using the Visual Analog Scale         One hundred fifty-six patients were enrolled; 145 (101 men and
(27) and the Chronic Respiratory Disease Interviewer-Administered Stan-       44 women) completed the first visit and 115 completed 12
dardized Questionnaire (CRQ) (28). Sputum was collected and analyzed          months (Figure 1; see Figure E1). At baseline 3%, 48%,
for bacteria (29–31) (using standard routine culture, CFU, and real-time
                                                                              30%, and 19% had GOLD I, II, III, and IV, respectively. Most
quantitative polymerase chain reaction [qPCR]), for viruses by PCR (32),
and processed to produce cytospins for cell differential and supernatant
                                                                              patients recruited were current or exsmokers (142 of 145),
for fluid phase measurements (33). A broad panel of serum and sputum           with a mean (range) pack-year history of 49 (10–153) with
biomarkers were measured using the Meso-Scale-Discovery (MSD,                 an absolute and percentage mean (SEM) reversibility to in-
Gaithersburg, MD) platform standard preprepared plates (MSD, MD)              haled bronchodilator on study entry of 47 ml (11 patients) and
664                                               AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE         VOL 184    2011




                                                                                 Figure 1. Subject enrolment flow diagram for 12-month
                                                                                 observational period.




4% (one patient), respectively. Skin prick testing or serum-        GOLD severity (1), or Anthonisen criteria (14). Hospitalized
specific IgE to a wide panel of aeroallergens confirmed that          exacerbations were associated with a greater decline in lung
20% were atopic. Bacterial colonization, defined as the pres-        function compared with exacerbations that were not hospital-
ence of a potentially pathogenic microorganism (H. influen-          ized (DFEV1 [ml] 2355 vs. 2131; mean difference 224; 95% CI
zae, M. catarrhalis, S. pneumoniae, S. aureus, or P. aeruginosa)    of difference, 2356 to 292; P , 0.001), but not health status
in a standard culture technique (29), was present in 28% of         decline (DCRQ [units] 21.25 vs. 20.91; mean difference 0.34;
patients at baseline. Using qPCR a bacterial pathogen (H.           95% CI of difference, 20.83 to 0.15; P ¼ 0.18).
influenzae, M. catarrhalis, S. pneumoniae, or S. aureus) was            Serum and sputum mediator data were available in 148 ex-
detected in 86% of patients at the baseline stable visit. A virus   acerbation events from 75 patients. Serum biomarkers that in-
was detected in 5% of subjects at study entry, whereas eosin-       creased during an exacerbation were IL-6, tumor necrosis
ophilic airway inflammation (. 3% nonsquamous cells) was             factor (TNF) receptors I and II, serum amyloid-A, C-reactive pro-
present in 27% of patients. Baseline and exacerbation clinical      tein (CRP), procalcitonin, and serum eosinophil cationic protein
characteristics are shown in Table 1 (see Table E3).                (Table E4A). Sputum biomarkers that increased were IL-1b,
                                                                    TNF-a, TNFRI, TNFRII, IL6, CCL5, and CCL4 (Table E4B).
Exacerbations                                                       No single biomarker had a receiver operating curve area under
A total of 182 exacerbation events were captured from 86            the curve greater than 0.70 in determining an exacerbation
patients; of these 21 exacerbations warranted hospitalization.      from stable state (Figure E2). Of all sputum and serum bio-
There was a reduction in the FEV1 and CRQ from baseline             markers measured there was a significantly increased level of
to exacerbation (FEV1 [L] 1.33 vs. 1.10; mean difference 0.24;      serum TNF-a and CRP in patients who were hospitalized
95% CI, 0.12–0.36; P , 0.001) (CRQ [units] 4.11 vs. 3.12; mean      (CRP median [IQR] 56 (102) vs. 8 (14); P ¼ 0.002) (serum
difference 0.99; 95% CI, 0.74–1.23; P , 0.001). The magnitude       TNF-a geometric mean 4.3 [95% CI, 3.4–5.4] vs. 3.4 [95%
of these changes was independent of smoking status, sex,            CI, 3.2–3.6]; P ¼ 0.02).
Bafadhel, McKenna, Terry, et al.: Biomarkers in COPD Exacerbations                                                                                             665

TABLE 1. CLINICAL CHARACTERISTICS OF ALL PATIENTS AT ENTRY INTO THE STUDY AND CLINICAL FEATURES AT EXACERBATION
                                            Study Entry                                                              Study Entry         Exacerbation        P Value

Male, n (%)                               101 (70)           FEV1,L†
                                                                                                                  1.33    (0.05)        1.10   (0.04)        ,0.001
Age*                                       69 (43–88)        FEV1% predicted†                                       52    (2)             42   (1)           ,0.001
Age at diagnosis*                          62 (38–83)        Reversibility, ml                                      47    (11)            37   (11)           0.50
Current smokers, n (%)                     42 (29)           FEV1/FVC ratio, %†                                     52    (2)             50   (1)            0.65
Exsmokers, n (%)                          100 (69)           CRQTOTAL, units                                      4.11    (0.10)        3.12   (0.08)        ,0.001
Pack-year history*                         49 (10–153)       VASTOTAL, mm                                          142    (6)            239   (6)           ,0.001
Exacerbation rate in previous 12 mo         3 (0.2)          Peripheral leukocyte count (3109 cells/L)‡             8.2   (7.9–8.6)      9.3   (8.9–9.8)     ,0.001
Maintenance prednisolone, n (%)             9 (6)            Peripheral neutrophil count (3109 cells/L)‡           5.3    (5–5.6)        6.3   (6–6.7)       ,0.001
Prednisolone dosage, mg*                    6 (4–10)         Peripheral eosinophil count (3109 cells/L)‡          0.21    (0.18–0.23)   0.19   (0.17–0.22)    0.84
Inhaled corticosteroid use, n (%)         125 (86)           Total sputum cell count (3106 cells/g sputum)‡         3.8   (3.1–4.7)      6.4   (5.2–7.8)     ,0.001
Inhaled corticosteroid dose, mgx        1,540 (59)           Sputum neutrophil count, %                             68    (2)             74   (2)            0.02
Inhaled long-acting b agonist use, n (%) 110 (76)            Sputum eosinophil count, %‡                           1.2    (1–1.6)        1.1   (0.9–1.5)      0.58

  Definition of abbreviations: CRQ ¼ Chronic Respiratory Disease Questionnaire score; VAS ¼ visual analog score.
  Data presented as mean (SEM) unless stated.
  * Mean (range).
  y
    Post-bronchodilator.
  z
    Geometric mean (95% confidence interval).
  x
    Beclomethasone dipropionate equivalent.


Factor and Cluster Analysis                                                         sensitivity of 90% and a specificity of 80% (Figures 3A and
Factor analysis identified three biologic factors at exacerbation                    E4A). The best serum biomarker was CRP with an area under
representing proinflammatory, Th1, and Th2 factors as deter-                         the receiver operating characteristic curve of 0.65 (95% CI, 0.57–
mined by their cytokine expression profiles (Table E3). Cluster                      0.74). A serum CRP cutoff of 10 mg/L had a sensitivity of 60%
analysis using the highest loading biomarker from each factor                       and specificity of 70%.
(TNFRII, CXCL11, and CCL17) revealed four biologic cluster
populations for exacerbation events. Three clusters were termed                     Exacerbations Associated with Virus
as “bacteria-predominant,” “eosinophil-predominant,” and “virus-                    Twenty-nine percent of exacerbations were associated with a vi-
predominant.” A fourth cluster demonstrated low sputum medi-                        rus, most commonly rhinovirus. Virus-associated exacerbations
ator concentrations and had fewer events associated with                            had a larger fall in % FEV1 compared with nonvirus-associated
known etiology and was termed “pauciinflammatory.” Factor                            exacerbations (217% vs. 29%; mean difference 28%; 95% CI,
mean scores were plotted for each cluster (Figures 2A, and                          216 to 21; P ¼ 0.04). Clinical assessments of change in FEV1,
E3A). Biologic cluster ellipsoids were calculated and plotted                       symptoms of cough and breathlessness, had an area under the
for all exacerbation events to schematically represent biologic                     receiver operating characteristic curve of 0.43 (95% CI, 0.32–
clusters of COPD exacerbations in three dimensions (Figure                          0.53), 0.62 (95% CI, 0.52–0.72), and 0.51 (95% CI, 0.41–0.62),
2B, Figure E3B). Exacerbation event characteristics of these                        respectively. The best marker for distinguishing the presence of
biologic clusters are presented in Table 2 (Table E5). The base-                    a virus at exacerbation was serum CXCL10 (IP-10), with an
line characteristics for each subject within each biologic cluster                  area under the receiver operating characteristic curve of 0.76
are shown in Tables 2 and E5. Cluster membership was deter-                         (95% CI, 0.67–0.86). A serum CXCL10 cut off of 56 pg/ml gave
mined using either a patient’s first exacerbation event or the                       a sensitivity of 75% and specificity of 65% (Figures 3B and
dominant cluster in patients with multiple exacerbations. The                       E4B). For exacerbations associated with virus alone the area
intraclass correlation coefficient of the biologic clusters for                      under the receiver operating characteristic curve for serum
patients with repeated exacerbations was 0.73. Each biologic                        CXCL10 improved to 0.83 (95% CI, 0.70–0.96).
cluster was found to be differentially related to inflammation
and etiology, but was otherwise clinically indistinguishable.
                                                                                    Exacerbations Associated with Sputum Eosinophilia
                                                                                    A sputum eosinophilia was observed in 28% of exacerbations.
Exacerbations Associated with Bacteria                                              The most sensitive and specific measure to determine a sputum
Fifty-five percent of exacerbations were bacteria-associated                         eosinophilia at exacerbation was the percentage peripheral
exacerbations (positive bacterial pathogen on routine culture                       blood eosinophil count with an area under the receiver operating
or CFU > 107). Blood and sputum neutrophils were increased.                         characteristic curve of 0.85 (95% CI, 0.78–0.93). A cutoff of 2%
Total bacterial load (16S) was higher in patients with a bacteria-                  peripheral blood eosinophils had a sensitivity of 90% and spec-
associated exacerbation than those without (geometric mean                          ificity of 60% for identifying a sputum eosinophilia of greater
7.67 [95% CI, 4.27 to 1.48] vs. 2.88 [95% CI, 1.78 to 4.78]; P ¼                    than 3% at exacerbation (Figure 3C, Figure E4C).
0.001). There was no difference in the 16S signal across exacer-                       In summary, the etiologic and inflammatory causes of exacerba-
bations of Anthonisen type (analysis of variance; P ¼ 0.64).                        tion events were as follows: bacteria alone 37%, virus alone 10%,
Using qPCR, acquisition of a new species occurred in 15% of                         sputum eosinophilia alone 17%, bacteria plus virus 12%, bacteria
exacerbations. Clinical assessments of change in FEV1, symp-                        plus sputum eosinophilia 6%, virus plus sputum eosinophilia 3%,
toms of sputum production, and sputum purulence had an area                         bacteria plus virus plus sputum eosinophilia 1%, and none 14%.
under the receiver operating characteristic curve of 0.45 (95%                         Multivariate modeling using combinations of two or three
CI, 0.35–0.55), 0.50 (95% CI, 0.40–0.60), and 0.58 (95% CI,                         biomarkers for the detection of bacteria-, virus-, and eosinophil-
0.48–0.68), respectively. The most suitable biomarker for deter-                    associated exacerbations did not significantly improve on the single
mining bacteria-associated exacerbations was sputum IL-1b                           mediators alone (data not shown). Differential clinical and bio-
with an area under the receiver operating characteristic curve                      marker expression for exacerbations associated with bacteria,
of 0.89 (95% CI, 0.83–0.95). A cutoff of 125 pg/ml had a                            virus, and sputum eosinophilia are shown in Tables E4–E6.
666                                               AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE           VOL 184     2011




                                                                                             Figure 2. (A) Bar chart representing the
                                                                                             mean factor scores for the three identi-
                                                                                             fied biologic factors (proinflammatory,
                                                                                             Th1, and Th 2) categorized according
                                                                                             to the four biologic clusters. (B) Propor-
                                                                                             tional representation of biologic chronic
                                                                                             obstructive pulmonary disease exacerba-
                                                                                             tion clusters in three-dimensional ellip-
                                                                                             soids. Cluster 1 is termed “bacteria-
                                                                                             predominant” and is outlined in blue,
                                                                                             cluster 2 is termed “eosinophil-predomi-
                                                                                             nant” and is outlined in green, cluster 3 is
                                                                                             termed “virus-predominant” and is out-
                                                                                             lined in red, and cluster 4 is termed “pau-
                                                                                             ciinflammatory” and is outlined in gray.




Predicting Bacteria-, Virus-, or                                    and mean (SEM) FEV1% predicted of 46 (2) percent sputum
Sputum-associated Exacerbations                                     IL-1b and serum CXCL10 was measured using a commercial
The odds ratio for a bacteria or an eosinophil-associated exac-     ELISA (R&D Systems, Abingdon, UK). The area under the
erbation was 4.9 (95% CI, 2.4–9.9; P , 0.001) or 2.7 (95% CI,       receiver operating characteristic curve for percentage blood
1.3–5.7; P ¼ 0.01) if the patient had a bacterial pathogen on       eosinophils to identify a sputum eosinophil–associated exacer-
diagnostic routine culture or a sputum eosinophilia on greater      bation was 0.95 (95% CI, 0.87–1.00) with a cutoff of 2% having
than or equal to one occasion at stable state. The odds ratio for   a sensitivity and specificity of 90% and 60%. The area under
a virus-associated exacerbation if the patient had a virus at       the receiver operating characteristic curve for sputum IL-1b
stable state was 0.5 (95% CI, 0.1–3.9; P ¼ 0.67).                   and serum CRP to identify a bacteria-associated exacerbation
                                                                    was 0.73 (95% CI, 0.61–0.85) and 0.70 (95% CI, 0.59–0.82);
                                                                    a sputum IL-1b cutoff of 130 pg/ml had a sensitivity and spec-
Validation of the Biomarkers Peripheral Blood Eosinophils,          ificity of 80% and 60%, and a serum CRP cutoff of 10 mg/L
Sputum IL-1b, Serum CRP, and Serum CXCL10                           had sensitivity and specificity of 65%. The area under the re-
In an independent study of COPD exacerbations, 89 subjects (57      ceiver operating characteristic curve for serum CXCL10 to
men and 32 women) with a mean (range) age of 68 (46–86) years       identify a virus-associated exacerbation was 0.65 (95% CI,
Bafadhel, McKenna, Terry, et al.: Biomarkers in COPD Exacerbations                                                                                       667

TABLE 2. BIOLOGIC CLUSTERS OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE EXACERBATIONS, WITH CLINICAL
EXACERBATION AND BASELINE CHARACTERISTICS
                                                Cluster 1:                 Cluster 2:                  Cluster 3:                Cluster 4:
                                          Bacteria-predominant      Eosinophil-predominant        Virus-predominant          Pauciinflammatory         P Value

Exacerbation characteristics
Number (%)                                   52   (35)                 44   (30)                   36   (24)                  16   (11)                —
Sputum TNFRII (pg/ml)*                    1,722   (1,402–2,117)       353   (287–433)           1,254   (969–1,623)           77   (41–147)          ,0.0001
Sputum CXCL11 (pg/ml)*                      3.1   (2.2–4.3)          10.9   (7.7–15.5)            799   (415–1,539)         17.3   (5.6–53.1)        ,0.0001
Sputum CCL17 (pg/ml)*                       5.5   (4.5–6.7)          34.8   (27.3–44.5)          23.5   (16.2–34.1)          4.7   (3.5–6.3)         ,0.0001
Bacterial exacerbation, % (95% CI)           86   (73–92)              29   (18–45)                44   (28–61)               31   (12–58)           ,0.0001
Viral exacerbation, % (95% CI)               22   (13–35)              10   (3–23)                 57   (39–73)               30   (10–61)           ,0.0001
Eosinophilic exacerbation, % (95% CI)         6   (1–16)               60   (45–74)                28   (16–44)               27   (10–52)           ,0.0001
D FEV1, ml†                               2132    (2251 to 235)     2110    (2230 to 231)       2232    (2340 to 2124)     2280    (2524 to 236)      0.32
D CRQ, units †                             20.9   (21.2 to 20.6)    20.9    (21.3 to 20.5)       20.9   (21.4 to 20.4)       21    (21.9 to 20.1)     0.99
D VASTOTAL, mm†                              79   (42–116)             80   (41–119)              120   (86–154)              73   (38–108)           0.39
Baseline characteristics
Number, (%)                                  28   (37)                 19   (25)                   20   (27)                   8   (11)                 —
Male, n (%)                                  18   (64)                 14   (74)                   14   (70)                   7   (88)                0.63
Age, yrs‡                                    69   (52–84)              68   (45–88)                70   (49–84)               69   (61–85)             0.62
Current smokers, n (%)                        8   (29)                  8   (42)                    4   (20)                   3   (38)                0.48
Pack-years smoked‡                           44   (10–122)             50   (20–106)               47   (10–134)              72   (23–120)            0.11
Exacerbation rate in previous 12 mo         3.8   (0.5)               4.3   (0.5)                   4   (0.7)                4.9   (1.2)               0.58
Exacerbation rate during study              3.8   (0.3)               3.6   (0.4)                 3.2   (0.3)                3.1   (0.5)               0.64
Inhaled corticosteroid dose, mgx          1,507   (147)             1,567   (133)               1,470   (160)              1,150   (188)               0.55
Residual volume, %                          134   (8)                 150   (9)                   120   (8)                  146   (23)                0.11
TLCO % predicted                             56   (5)                  59   (5)                    57   (6)                   46   (7)                 0.62
FEV1% predicted, baseline                    53   (3)                  51   (5)                    53   (5)                   40   (7)                 0.34
FEV1/FVC ratio (%)                           51   (2)                  47   (2)                    50   (3)                   47   (5)                 0.67
CRQTOTAL , units                           4.14   (0.20)             3.90   (0.22)               4.10   (0.26)              3.66   (0.50)              0.74
VASTOTAL , mm                               178   (15)                142   (18)                  124   (18)                 147   (37)                0.14
Total sputum cell count (3106 cells/g)*     8.3   (5.5–12.5)          2.3   (1.6–3.2)             2.5   (1.2–5.3)            3.5   (1.2–10.7)          0.002
Sputum neutrophil count, %                   75   (5)                  53   (4)                    68   (4)                   81   (6)                 0.003
Sputum eosinophil count, %*                   1   (0.6–1.6)           3.1   (1.4–6.6)               1   (0.5–1.9)            0.5   (0.2–1)             0.012
Bacterial colonization, % (95% CI)           63   (48–77)              27   (15–43)                11   (3–29)                38   (18–61)             0.001

  Definition of abbreviations: CCL ¼ ; CI ¼ confidence interval; CRQ ¼ Chronic Respiratory Disease Questionnaire score; CXCL ¼ ; TLCO ¼ carbon monoxide transfer
factor; TNF ¼ tumor necrosis factor; VAS ¼ visual analog score.
  Data presented as mean (SEM), unless stated.
  * Geometric mean (95% CI).
  y
     Mean change (95% CI) between exacerbation and baseline.
  z
     Mean (range).
  x
     Beclomethasone dipropionate equivalent.



0.52–0.78) with a cutoff of 145 pg/ml having a sensitivity and                    these exacerbation clinical phenotypes are likely to represent dis-
specificity of 70% and 60%.                                                        tinct pathophysiologic entities with specific biomarker signatures.
   Further details and results are available in the online supplement.                Biomarker profiling in COPD exacerbations has the potential
                                                                                  to further the understanding of disease mechanisms (22),
                                                                                  whereas phenotypic approaches lend to prognostic and thera-
DISCUSSION                                                                        peutic strategies (37, 38). Using factor and cluster analysis,
In this study we have used two methods to investigate bio-                        a novel approach of characterizing COPD and exacerbations
markers in COPD. The first using unbiased statistical tools, free                  (23), we were able to reduce an extensive panel of measured
from bias and independent of clinical expression, identified bi-                   sputum biomarkers into three factors, from which we deter-
ologic COPD exacerbation phenotypes and characterized exac-                       mined four biologic clusters. This analytic strategy is free from
erbations into four biologic clusters, The second method used                     investigator bias. These biologic clusters could not be distin-
current clinical exacerbation phenotypes of COPD related to po-                   guished clinically or by Anthonisen criteria (14) and the exac-
tential etiology and inflammation, namely exacerbations that are                   erbation severity was similar across the clusters. Importantly,
associated with bacteria, virus, or a sputum eosinophilia. Inter-                 using factor analysis we have shown differential inflammatory
estingly, we were unable to define biomarkers for exacerbations                    profiles between the bacteria-predominant, eosinophil-predominant,
per se, despite a generalized increase in systemic and airway in-                 virus-predominant, and pauciinflammatory clusters. In patients
flammation (34–36). The biologic exacerbation clusters were bac-                   with multiple exacerbations the biologic clusters were repeat-
terial-, viral-, or eosinophilic-predominant, and a fourth was                    able, and exacerbations associated with bacteria or a sputum
associated with limited changes in the inflammatory profile and                     eosinophilia but not viruses could be predicted from stable state.
was termed “pauciinflammatory.” These clusters were remark-                        Therefore, our data are consistent with the view that bacterial
ably similar to our clinical exacerbation phenotypes. We identi-                  and eosinophilic exacerbations may reflect instability within
fied biomarkers for our clinical exacerbation phenotypes that                      a complex and inherently unstable system, whereas viral exacer-
were then validated in an independent cohort. The bacteria-                       bations are more likely to represent acquisition of a new patho-
and sputum eosinophil–associated exacerbations rarely coexisted,                  gen. It is likely both of these mechanisms drive exacerbations, but
and were reliably predicted from stable state suggesting funda-                   critically we have determined biologic clusters and clinical phe-
mental differences in their immunopathogenesis. Therefore, in                     notypes that may respond to different management strategies,
addition to identifying potential biomarkers to direct therapy,                   which can potentially be identified using biomarker profiles.
668   AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE             VOL 184      2011




                                   Figure 3. Receiver operating characteristic curve with
                                   area under the curve (95% confidence interval) illustrating
                                   biomarkers that positively predict (A) bacteria-, (B) virus-,
                                   and (C) eosinophil-associated exacerbations. Area under
                                   the curve (95% confidence interval) is shown in the paren-
                                   theses. CCL ¼ ; CRP ¼ C-reactive protein; CXCL ¼ ; TNF ¼
                                   tumor necrosis factor.
Bafadhel, McKenna, Terry, et al.: Biomarkers in COPD Exacerbations                                                                                      669


    The inflammatory profile of a COPD exacerbation is typically          exacerbation. In our study a statistical analytic limitation was
neutrophilic, but eosinophilic airway inflammation also exists,          that we did not correct for repeated measures and assessed
and is associated with a favorable response to corticosteroid ther-     changes in biomarkers in paired or unpaired tests; however,
apy (8–10). Eosinophilia in inflammatory airways disease is as-          we examined two methods to investigate biomarkers in COPD
sociated with increased all-cause mortality (39, 40) and may            exacerbations, using unbiased statistical tools to demonstrate
highlight different genetic, biologic, and pathologic disease pro-      four biologic clusters and analysis of biomarkers to look at pre-
cesses. Importantly, the sputum differential rather than total          defined clinical exacerbation subgroups, and further used multi-
eosinophil count has consistently been shown to be associated           variate analysis to determine that combinations of markers did
with important clinical outcomes (9, 10). We found that the             not improve our predictive model. The presence of coinfection
peripheral percentage eosinophil count was a sensitive biomarker        with virus and bacteria in our study was lower than that previ-
of a sputum eosinophilia. Current guidelines recommend the use          ously reported (5), but may reflect differences in the severity
of systemic corticosteroids for COPD exacerbations, although the        of exacerbations. The relationship between virus and bacterial
magnitude of the benefit is marginal and their use associated with       infection in exacerbations, however, remains poorly understood
significant side effects (18). Our findings raise the possibility that    (5, 45). We chose to define a bacteria-associated exacerbation
targeting corticosteroid therapy in a subgroup of exacerbations         based on a positive routine culture or a high bacterial load;
dependent on the peripheral eosinophil count may reduce inap-           however, the causal links between the presence of bacteria
propriate use of systemic corticosteroids.                              and exacerbations has not been rigorously confirmed, and evi-
    Bacteria are considered to play a role in up to 50% of exac-        dence for efficacy of antibiotics in treatment is conflicting (13,
erbations (7). Current guidelines propose sputum purulence              19–21, 46). Developments in molecular bacterial identification
to guide antibiotic therapy (13). Sputum purulence is sensitive         of bacteria (47) and emerging microbiomics (48) are beginning
for detecting bacterial culture or high bacterial yields at exac-       to redefine the microbiota of the airway in health and disease
erbation in COPD (12). However, the use of sputum purulence             and will likely change the view of what defines a bacterial in-
alone is confounded by its presence at stable state and chronic         fection. Improvements in viral detection and the identification
bacterial colonization (41), possibly as a consequence of poor          of new respiratory viruses are also changing the understanding
bacterial clearance (42). Furthermore, the change in sputum             of the associations between exacerbations and these agents.
purulence or sputum production symptoms in our cohort was               Further work is required before therapeutic implications and
not sensitive or specific for identifying a bacteria-associated          interpretative criteria can be established for these sensitive de-
exacerbation. The most sensitive and specific assay for deter-           tection methods. Whether identification of a pauciinflammatory
mining bacteria-associated exacerbations was sputum IL-1b.              biologic cluster and a proportion of subjects without clear evi-
This extends previous findings that bronchoalveolar lavage IL-
                                                                        dence of a cause for their exacerbation reflect the insensitivity
1b was a good biomarker for ventilator-associated pneumonia
                                                                        of our chosen cutoffs for definitions or a real entity requires
(43), and suggests that this airway marker may suitably deter-
                                                                        further clarifications.
mine bacterial infections, above that of serum CRP or procalci-
                                                                            In conclusion, COPD exacerbations are heterogeneous. This
tonin whose use could not be demonstrated in this study or in
                                                                        phenotypic heterogeneity can be defined. Using unbiased statis-
others (34, 35). Sputum IL-1b could thus be used as a biomarker
                                                                        tical tools we have determined four biologic exacerbation clus-
to correctly identify bacteria-associated exacerbations but
                                                                        ters that relate to identifiable patterns of inflammation and
would require the development of a rapid near patient test to
                                                                        potential causative pathogens. We have defined sensitive and
be of use in clinical practice.
                                                                        specific biomarkers to identify predefined clinical exacerbation
    Viruses have been implicated as a major cause of COPD exac-
                                                                        phenotypes, which need to be tested in randomized prospective
erbations and are detected in approximately half of severe
                                                                        studies of targeted therapy. These subgroups are independent
COPD exacerbations (5, 6). The total sputum eosinophil count
has been proposed as a potential biomarker of a viral exacerbation      and suggest that the mechanisms driving their exacerbations
(5). Here we also found that the total absolute sputum eosino-          are distinct and may be amenable to more specific interventions,
phil count was increased in virus-associated exacerbations, but         potentially moving the management of COPD exacerbations to-
not the differential sputum eosinophil count, suggesting the            ward the realization of phenotype-specific management.
association was largely a consequence of a change in the total-         Author Disclosure: M.B. received grant support from the Medical Research Coun-
cell count. The application of clinical symptoms in combination         cil (MRC). S.M. does not have a financial relationship with a commercial entity
with serum CXCL10 (IP-10) has been proposed as a possible               that has an interest in the subject of this manuscript. S.T. does not have a financial
                                                                        relationship with a commercial entity that has an interest in the subject of this
biomarker for rhinovirus infection at exacerbation (44). This           manuscript. V.M. does not have a financial relationship with a commercial entity
study confirms that serum CXCL10 levels as a potential pre-              that has an interest in the subject of this manuscript. C.R. does not have a financial
dictor of a virus-associated exacerbation, independent of a re-         relationship with a commercial entity that has an interest in the subject of this
                                                                        manuscript. P.H. does not have a financial relationship with a commercial entity
quirement for symptom evaluation. Novel antiviral approaches            that has an interest in the subject of this manuscript. M.M. is employed by and
are in development and CXCL10 is thus a promising biomarker             owns stocks in AstraZeneca (AZ). K.H. does not have a financial relationship with
to direct future antiviral therapy.                                     a commercial entity that has an interest in the subject of this manuscript. T.K.
                                                                        does not have a financial relationship with a commercial entity that has an in-
    One potential criticism is that this is a single-center study and   terest in the subject of this manuscript. A.D. does not have a financial relationship
therefore our findings need to be replicated across multiple cen-        with a commercial entity that has an interest in the subject of this manuscript.
ters, and validated prospectively to identify the biologic clusters     K.L. does not have a financial relationship with a commercial entity that has an
                                                                        interest in the subject of this manuscript. H.P. does not have a financial relation-
and our proposed biomarkers for the clinical exacerbation phe-          ship with a commercial entity that has an interest in the subject of this manu-
notypes; nonetheless, this approach may represent a new para-           script. P.R., P.D., and M.J. are employed by and own stocks in AZ. M.S. is
digm in the management of COPD exacerbations. Importantly,              employed by AZ. P.N. was an employee of AZ at the time of conducting this
we have replicated the biomarkers peripheral blood eosinophils,         research and preparation of the manuscript. He is now an employee of MedI-
                                                                        mmune LLC, which is a subsidiary of AZ and owns stocks in AZ. R.H.G. was
sputum IL-1b, and serum CXCL10 in a validation cohort. Pe-              a consultant for Nycomed and received travel accommodations from Chiesi.
ripheral blood eosinophils remained a strong marker of a sputum         P.V. received institutional grant support from the Swedish Research Council.
eosinophilia. Sputum IL-1b and serum CXCL10 were measured               D.A.L. received institutional grant support and was a consultant for GlaxoSmithK-
                                                                        line (GSK). He is on the Advisory Board and received honorarium from GSK.
using a different platform but remained significant albeit weaker        M.R.B. received institutional grant support form the MRC. S.L.J. was a consultant
predictive markers of identifying a bacteria- or virus-associated       for AZ, Centocor, Sanofi-Pasteur, Synairgen, GSK, and Chiesi. He received
670                                                              AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE                          VOL 184      2011

institutional grant support from AZ, Centocor, Sanofi-Pasteur, Synairgen, and AZ.                pulmonary disease: a prospective randomised controlled trial. Lancet
He received lecture fees from AZ, owns stocks in Synairgen, and received travel                 1999;354:456–460.
accommodations from Pfizer. I.D.P. received institutional grant support from the
                                                                                       18.   Niewoehner DE, Erbland ML, Deupree RH, Collins D, Gross NJ, Light
MRC and received honorarium from GSK, AZ, Merck, and Novartis. He received
travel accommodations from Boehringer Ingelheim (BI). C.E.B. received institu-                  RW, Anderson P, Morgan NA. Effect of systemic glucocorticoids on
tional grant support from the MRC, AZ, MedImmune, and Roche. He received                        exacerbations of chronic obstructive pulmonary disease. Department
support for the development of SPD assays in Cambridge from GSK. He is on the                   of Veterans Affairs Cooperative Study Group. N Engl J Med 1999;
Advisory Board of GSK, AZ, Roche, Novartis, Genentech, and MedImmune and                        340:1941–1947.
was a consultant for MedImmune and Novartis. He received travel accommoda-
                                                                                       19.   Puhan MA, Vollenweider D, Latshang T, Steurer J, Steurer-Stey C.
tions from BI.
                                                                                                Exacerbations of chronic obstructive pulmonary disease: when are
Acknowledgment: The authors thank all the research volunteers who participated                  antibiotics indicated? A systematic review. Respir Res 2007;8:30.
in the study, and also the following people for their valuable assistance throughout   20.   Puhan MA, Vollenweider D, Steurer J, Bossuyt PM, Ter RG. Where is
the study: J. Aniscenko, M. Bourne, R. Braithwaite, D. Burke, J. Footitt, E. Goldie,            the supporting evidence for treating mild to moderate chronic ob-
J. Goldie, N. Goodman, S. Gupta, B. Hargadon, I. Rushby, M. Shelley, A. Singapuri,
                                                                                                structive pulmonary disease exacerbations with antibiotics? A sys-
D. Vara, R. Walton, and S. Winpress.
                                                                                                tematic review. BMC Med 2008;6:28.
                                                                                       21.   Rothberg MB, Pekow PS, Lahti M, Brody O, Skiest DJ, Lindenauer PK.
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Fenótipos e biomarcadores na exacerbação da DPOC

  • 1. Acute Exacerbations of Chronic Obstructive Pulmonary Disease Identification of Biologic Clusters and Their Biomarkers Mona Bafadhel1,2, Susan McKenna1, Sarah Terry1, Vijay Mistry1,2, Carlene Reid1, Pranabashis Haldar2, Margaret McCormick3, Koirobi Haldar2, Tatiana Kebadze4, Annelyse Duvoix5, Kerstin Lindblad6, Hemu Patel7, Paul Rugman3, Paul Dodson3, Martin Jenkins3, Michael Saunders3, Paul Newbold3, Ruth H. Green1, Per Venge6, David A. Lomas5, Michael R. Barer2,7, Sebastian L. Johnston4, Ian D. Pavord1, and Christopher E. Brightling1,2 1 Institute for Lung Health, and 2Department of Infection, Immunity and Inflammation, University of Leicester, Leicester, United Kingdom; 3 AstraZeneca R&D Charnwood, Loughborough, Leicestershire, United Kingdom; 4Department of Respiratory Medicine, National Heart and Lung Institute, Centre for Respiratory Infections, Imperial College London, United Kingdom; 5Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom; 6Department of Medical Sciences, Clinical Chemistry, University of Uppsala, Uppsala, Sweden; and 7 Department of Clinical Microbiology, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom Rationale: Exacerbations of chronic obstructive pulmonary disease (COPD) are heterogeneous with respect to inflammation and etiology. AT A GLANCE COMMENTARY Objectives: Investigate biomarker expression in COPD exacerbations to identify biologic clusters and determine biomarkers that recog- Scientific Knowledge on the Subject nize clinical COPD exacerbation phenotypes, namely those associ- Exacerbations of chronic obstructive pulmonary disease ated with bacteria, viruses, or eosinophilic airway inflammation. (COPD) are a major health burden worldwide, and affect Methods: Patients with COPD were observed for 1 year at stable and a vulnerable population at risk of significant comorbidities. exacerbation visits. Biomarkers were measured in sputum and COPD exacerbations are heterogeneous with respect to serum. Viruses and selected bacteria were assessed in sputum by etiology and inflammation and biomarkers are required to polymerase chain reaction and routine diagnostic bacterial culture. phenotype this heterogeneity. Biologic phenotypes were explored using unbiased cluster analysis and biomarkers that differentiated clinical exacerbation phenotypes were investigated. What This Study Adds to the Field Measurements and Main Results: A total of 145 patients (101 men and 44 women) entered the study. A total of 182 exacerbations We have shown that there are biologic COPD exacerbation were captured from 86 patients. Four distinct biologic exacerbation clusters that are clinically indistinguishable, and that bio- clusters were identified. These were bacterial-, viral-, or eosinophilic- markers can be used to identify specific clinical phenotypes predominant, and a fourth associated with limited changes in the during exacerbations of COPD (specifically those associ- inflammatory profile termed “pauciinflammatory.” Of all exacerba- ated with bacteria, virus, and sputum eosinophilia). Bac- tions, 55%, 29%, and 28% were associated with bacteria, virus, or a terial and eosinophilic clinical exacerbation phenotypes can be identified from stable state. Our data further delineate the heterogeneity during COPD exacerbations and may (Received in original form April 2, 2011; accepted in final form June 15, 2011) identify populations that appropriately require cortico- Supported by the Medical Research Council (United Kingdom) and AstraZeneca steroids and antibiotics at the onset of an exacerbation. jointly as a “Biomarker Call Project”; C.E.B. is a Wellcome Trust Senior Clinical Fellow, and GlaxoSmithKline supported the measurement of surfactant protein D. The research was performed in laboratories partly funded by the European Regional Development Fund (ERDF 05567). The Medical Research Council, Well- come Trust, and the European Regional Development Fund had no involvement sputum eosinophilia. The biomarkers that best identified these clinical in the design of the study, data collection, analysis and interpretation of the data, phenotypes were sputum IL-1b, 0.89 (area under receiver operating in the writing of the manuscript, or in the decision to submit the manuscript. characteristic curve) (95% confidence interval [CI], 0.83–0.95); serum Author Contributions: S.M. and S.T. were involved in the recruitment of volunteers CXCL10, 0.83 (95% CI, 0.70–0.96); and percentage peripheral eosino- and in data collection. C.R., V.M., K.H., H.P., A.D., and K.L. were involved in data phils, 0.85 (95% CI, 0.78–0.93), respectively. collection and interpretation. M.M., P.R., P.D., P.N., M.J., and M.S. were involved Conclusions: The heterogeneity of the biologic response of COPD in study design, data collection, and interpretation. R.H.G. and P.H. were in- exacerbations can be defined. Sputum IL-1b, serum CXCL10, and volved in study design and data interpretation. M.R.B., D.A.L., S.L.J., P.V., and I.D.P. were involved in the design of the study, data collection, and interpreta- peripheral eosinophils are biomarkers of bacteria-, virus-, or eosinophil- tion. M.B. and C.E.B. were involved in the study design, volunteer recruitment, associated exacerbations of COPD. Whether phenotype-specific bio- data collection, data interpretation, and data analysis, and had full access to the markers can be applied to direct therapy warrants further investigation. data and are responsible for the integrity of the data and final decision to submit. All authors contributed to the writing of the manuscript and have approved the Keywords: chronic obstructive pulmonary disease; phenotypes; exac- final version for submission. erbations; airway inflammation; infection Correspondence and requests for reprints should be addressed to Christopher E. Brightling, M.B.B.S., B.Sc. (Hons.), Ph.D., Institute for Lung Health, Clinical Acute exacerbations of chronic obstructive pulmonary disease Sciences Wing, University Hospitals of Leicester, Leicester, LE3 9QP, UK. E-mail: (COPD) are associated with substantial morbidity and mortality ceb17@le.ac.uk (1, 2). Exacerbations are typically associated with increased neu- This article has an online supplement, which is accessible from this issue’s table of trophilic and to a lesser extent eosinophilic airway inflammation contents at www.atsjournals.org (3, 4). Respiratory viral and bacterial infections have been impli- Am J Respir Crit Care Med Vol 184. pp 662–671, 2011 Originally Published in Press as DOI: 10.1164/rccm.201104-0597OC on June 16, 2011 cated in causing most exacerbations (5–7), but how these infec- Internet address: www.atsjournals.org tions alter lower airway inflammation and relate to treatment
  • 2. Bafadhel, McKenna, Terry, et al.: Biomarkers in COPD Exacerbations 663 response is not completely understood. This heterogeneity trans- and single ELISA at stable and exacerbation visits (see Table E1 in the lates that at present clinicians have limited tools to phenotype online supplement). exacerbations. During stable state a sputum eosinophilia is asso- ciated with corticosteroid responsiveness (8–10), whereas the Definition of Bacteria-, Virus-, and Sputum presence of a high bacterial load and sputum purulence has favor- Eosinophil–associated Exacerbations of COPD able outcomes with antibiotics (11–15). These findings suggest Bacteria-associated exacerbations were defined as a positive bacterial that it is possible to identify clinically important COPD exacer- pathogen on routine culture (Haemophilus influenzae, Moraxella catar- bation phenotypes. This is crucial because systemic corticosteroids rhalis, Streptococcus pneumoniae, Staphylococcus aureus, or Pseudo- and antibiotics have marginal efficacy (16–21) and the potential to monas aeruginosa) or a total aerobic CFU count greater than or cause adverse events in an already vulnerable population. equal to 107 cells (12, 15). qPCR bacterial detection methods were We hypothesize that approaches aimed at the identification of not used to define bacteria-associated exacerbations in this study. COPD exacerbation phenotypes may allow for better prognostic, A virus-associated exacerbation was defined as one that had a positive therapeutic, and mechanistic applications (22–24). In this study sputum viral PCR, whether in isolation or in combination with a positive bacterial pathogen on routine culture. A sputum eosinophil–associated we investigated whether during exacerbations of COPD there are exacerbation was defined as the presence of more than 3% nonsquamous (1) definable biologic phenotypes using unbiased mathematical cells. tools (namely factor and cluster analysis); (2) identifiable bio- markers associated with clinical phenotypes, specifically those Statistical Analyses associated with bacteria, viruses, or sputum eosinophilia; and (3) exacerbation phenotypes that can be predicted from stable Statistical analyses were performed using PRISM version 4 (Graph- state. PAD PRISM, La Jolla, CA) and SPSS version 16 (IBM, Chicago, IL). Parametric and nonparametric data are presented as mean (SEM) and median (interquartile range). Log transformed data are METHODS presented as geometric mean (95% confidence interval [CI]). Multi- variate modeling using principal component analysis in sputum bio- Patients markers was used to explore biomarker pattern expression at Patients with a physician diagnosis of COPD and a post-bronchodilator exacerbations. No adjustments for multiple comparisons have been FEV1/FVC ratio of less than 0.7 as per global initiative for chronic made across biomarkers. obstructive lung disease (GOLD) criteria (1) were recruited from the Factor analysis, a mathematical method that discovers patterns of Glenfield Hospital, Leicester, United Kingdom, and through local ad- relationships within large datasets, was used to identify factors in sputum vertising. All patients fulfilled the inclusion criteria of age greater than mediators at exacerbations thereby demonstrating biologic factors inde- 40 years, GOLD stage I–IV, and greater than or equal to one exacer- pendent of each other and of any clinical expression. This method using bation in the preceding 12 months defined as the requirement of emer- unsupervised principal component analysis demonstrated three factors gency health care (25). Patients were excluded if there was a documented accounting for 75% of the total variance (see Table E2). Cluster analysis, inability to produce sputum after the induced sputum procedure, a cur- an unbiased mathematical method, allows one to classify groups on rent or previous history of asthma, currently active pulmonary tubercu- similar chosen characteristics alone. Thus, after demonstrating three bi- losis, or any other clinically relevant lung disease other than COPD. The ologic factors, we used hierarchical cluster analysis to generate four bi- presence of comorbidity, reported atopy to common aeroallergens, or ologic clusters for exacerbation events and cases. Clinical characteristics reversibility on lung function testing was not an exclusion criterion. All for all exacerbation events were tabulated for each biologic cluster. One- patients gave informed written consent and the study was approved by way analysis of variance, Kruskal-Wallis test, and the chi-square test the local ethics committee. were used to compare the clinical characteristics between cluster groups. For comparison of clinical and biomarker changes between baseline and exacerbation visits the paired t test or Wilcoxon matched pairs test Study Design was used. For comparison of exacerbations associated with or without This was a prospective observational study. Patients were seen at stable bacteria, virus, and sputum eosinophilia the t test and Mann-Whitney state and during exacerbations for the duration of 1 year. Stable visits test were used, respectively. To determine suitable biomarkers, the including the baseline visits were 8 weeks free from an exacerbation. All receiver operating characteristic curves were plotted for (1) exacerba- patients were given daily diary cards to complete, and asked to contact tion versus stable state; (2) bacteria- versus nonbacteria-associated the research team if there was an increase in symptoms of breathless- exacerbations; (3) virus- versus nonvirus-associated exacerbations; ness, sputum volume, and purulence. Exacerbations were defined and (4) sputum eosinophilia– (. 3% nonsquamous cells) versus non- according to Anthonisen criteria (14) and health care use (25). Exac- sputum eosinophilia–associated exacerbations. erbation data recording and sampling were only performed in patients Validation of the identified biomarkers for bacteria-, virus-, and spu- who had not received prior oral corticosteroids or antibiotics. Patients tum eosinophil–associated exacerbation was performed in a further 89 were all clinically assessed (including chest radiograph, temperature exacerbation events from an independent cohort of subjects with recording, and blood gas analysis if clinically necessary) to exclude COPD. These subjects with COPD were recruited to enter a prospec- other causes of breathlessness. Patients with an exacerbation of COPD tive study with identical inclusion and exclusion criteria and study de- were then treated according to guidelines (2). sign as the current study. Stable and exacerbation visits were treated in accordance to the main study. A P value of less than 0.05 was taken as the threshold of statistical Measurements significance. At all visits, patients underwent pre– and post–400-mg albuterol broncho- dilator spirometry (Vitalograph, Buckingham, Buckinghamshire, UK); in- RESULTS duced or spontaneous sputum collection (26); and measurements of symptoms and health quality assessments using the Visual Analog Scale One hundred fifty-six patients were enrolled; 145 (101 men and (27) and the Chronic Respiratory Disease Interviewer-Administered Stan- 44 women) completed the first visit and 115 completed 12 dardized Questionnaire (CRQ) (28). Sputum was collected and analyzed months (Figure 1; see Figure E1). At baseline 3%, 48%, for bacteria (29–31) (using standard routine culture, CFU, and real-time 30%, and 19% had GOLD I, II, III, and IV, respectively. Most quantitative polymerase chain reaction [qPCR]), for viruses by PCR (32), and processed to produce cytospins for cell differential and supernatant patients recruited were current or exsmokers (142 of 145), for fluid phase measurements (33). A broad panel of serum and sputum with a mean (range) pack-year history of 49 (10–153) with biomarkers were measured using the Meso-Scale-Discovery (MSD, an absolute and percentage mean (SEM) reversibility to in- Gaithersburg, MD) platform standard preprepared plates (MSD, MD) haled bronchodilator on study entry of 47 ml (11 patients) and
  • 3. 664 AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE VOL 184 2011 Figure 1. Subject enrolment flow diagram for 12-month observational period. 4% (one patient), respectively. Skin prick testing or serum- GOLD severity (1), or Anthonisen criteria (14). Hospitalized specific IgE to a wide panel of aeroallergens confirmed that exacerbations were associated with a greater decline in lung 20% were atopic. Bacterial colonization, defined as the pres- function compared with exacerbations that were not hospital- ence of a potentially pathogenic microorganism (H. influen- ized (DFEV1 [ml] 2355 vs. 2131; mean difference 224; 95% CI zae, M. catarrhalis, S. pneumoniae, S. aureus, or P. aeruginosa) of difference, 2356 to 292; P , 0.001), but not health status in a standard culture technique (29), was present in 28% of decline (DCRQ [units] 21.25 vs. 20.91; mean difference 0.34; patients at baseline. Using qPCR a bacterial pathogen (H. 95% CI of difference, 20.83 to 0.15; P ¼ 0.18). influenzae, M. catarrhalis, S. pneumoniae, or S. aureus) was Serum and sputum mediator data were available in 148 ex- detected in 86% of patients at the baseline stable visit. A virus acerbation events from 75 patients. Serum biomarkers that in- was detected in 5% of subjects at study entry, whereas eosin- creased during an exacerbation were IL-6, tumor necrosis ophilic airway inflammation (. 3% nonsquamous cells) was factor (TNF) receptors I and II, serum amyloid-A, C-reactive pro- present in 27% of patients. Baseline and exacerbation clinical tein (CRP), procalcitonin, and serum eosinophil cationic protein characteristics are shown in Table 1 (see Table E3). (Table E4A). Sputum biomarkers that increased were IL-1b, TNF-a, TNFRI, TNFRII, IL6, CCL5, and CCL4 (Table E4B). Exacerbations No single biomarker had a receiver operating curve area under A total of 182 exacerbation events were captured from 86 the curve greater than 0.70 in determining an exacerbation patients; of these 21 exacerbations warranted hospitalization. from stable state (Figure E2). Of all sputum and serum bio- There was a reduction in the FEV1 and CRQ from baseline markers measured there was a significantly increased level of to exacerbation (FEV1 [L] 1.33 vs. 1.10; mean difference 0.24; serum TNF-a and CRP in patients who were hospitalized 95% CI, 0.12–0.36; P , 0.001) (CRQ [units] 4.11 vs. 3.12; mean (CRP median [IQR] 56 (102) vs. 8 (14); P ¼ 0.002) (serum difference 0.99; 95% CI, 0.74–1.23; P , 0.001). The magnitude TNF-a geometric mean 4.3 [95% CI, 3.4–5.4] vs. 3.4 [95% of these changes was independent of smoking status, sex, CI, 3.2–3.6]; P ¼ 0.02).
  • 4. Bafadhel, McKenna, Terry, et al.: Biomarkers in COPD Exacerbations 665 TABLE 1. CLINICAL CHARACTERISTICS OF ALL PATIENTS AT ENTRY INTO THE STUDY AND CLINICAL FEATURES AT EXACERBATION Study Entry Study Entry Exacerbation P Value Male, n (%) 101 (70) FEV1,L† 1.33 (0.05) 1.10 (0.04) ,0.001 Age* 69 (43–88) FEV1% predicted† 52 (2) 42 (1) ,0.001 Age at diagnosis* 62 (38–83) Reversibility, ml 47 (11) 37 (11) 0.50 Current smokers, n (%) 42 (29) FEV1/FVC ratio, %† 52 (2) 50 (1) 0.65 Exsmokers, n (%) 100 (69) CRQTOTAL, units 4.11 (0.10) 3.12 (0.08) ,0.001 Pack-year history* 49 (10–153) VASTOTAL, mm 142 (6) 239 (6) ,0.001 Exacerbation rate in previous 12 mo 3 (0.2) Peripheral leukocyte count (3109 cells/L)‡ 8.2 (7.9–8.6) 9.3 (8.9–9.8) ,0.001 Maintenance prednisolone, n (%) 9 (6) Peripheral neutrophil count (3109 cells/L)‡ 5.3 (5–5.6) 6.3 (6–6.7) ,0.001 Prednisolone dosage, mg* 6 (4–10) Peripheral eosinophil count (3109 cells/L)‡ 0.21 (0.18–0.23) 0.19 (0.17–0.22) 0.84 Inhaled corticosteroid use, n (%) 125 (86) Total sputum cell count (3106 cells/g sputum)‡ 3.8 (3.1–4.7) 6.4 (5.2–7.8) ,0.001 Inhaled corticosteroid dose, mgx 1,540 (59) Sputum neutrophil count, % 68 (2) 74 (2) 0.02 Inhaled long-acting b agonist use, n (%) 110 (76) Sputum eosinophil count, %‡ 1.2 (1–1.6) 1.1 (0.9–1.5) 0.58 Definition of abbreviations: CRQ ¼ Chronic Respiratory Disease Questionnaire score; VAS ¼ visual analog score. Data presented as mean (SEM) unless stated. * Mean (range). y Post-bronchodilator. z Geometric mean (95% confidence interval). x Beclomethasone dipropionate equivalent. Factor and Cluster Analysis sensitivity of 90% and a specificity of 80% (Figures 3A and Factor analysis identified three biologic factors at exacerbation E4A). The best serum biomarker was CRP with an area under representing proinflammatory, Th1, and Th2 factors as deter- the receiver operating characteristic curve of 0.65 (95% CI, 0.57– mined by their cytokine expression profiles (Table E3). Cluster 0.74). A serum CRP cutoff of 10 mg/L had a sensitivity of 60% analysis using the highest loading biomarker from each factor and specificity of 70%. (TNFRII, CXCL11, and CCL17) revealed four biologic cluster populations for exacerbation events. Three clusters were termed Exacerbations Associated with Virus as “bacteria-predominant,” “eosinophil-predominant,” and “virus- Twenty-nine percent of exacerbations were associated with a vi- predominant.” A fourth cluster demonstrated low sputum medi- rus, most commonly rhinovirus. Virus-associated exacerbations ator concentrations and had fewer events associated with had a larger fall in % FEV1 compared with nonvirus-associated known etiology and was termed “pauciinflammatory.” Factor exacerbations (217% vs. 29%; mean difference 28%; 95% CI, mean scores were plotted for each cluster (Figures 2A, and 216 to 21; P ¼ 0.04). Clinical assessments of change in FEV1, E3A). Biologic cluster ellipsoids were calculated and plotted symptoms of cough and breathlessness, had an area under the for all exacerbation events to schematically represent biologic receiver operating characteristic curve of 0.43 (95% CI, 0.32– clusters of COPD exacerbations in three dimensions (Figure 0.53), 0.62 (95% CI, 0.52–0.72), and 0.51 (95% CI, 0.41–0.62), 2B, Figure E3B). Exacerbation event characteristics of these respectively. The best marker for distinguishing the presence of biologic clusters are presented in Table 2 (Table E5). The base- a virus at exacerbation was serum CXCL10 (IP-10), with an line characteristics for each subject within each biologic cluster area under the receiver operating characteristic curve of 0.76 are shown in Tables 2 and E5. Cluster membership was deter- (95% CI, 0.67–0.86). A serum CXCL10 cut off of 56 pg/ml gave mined using either a patient’s first exacerbation event or the a sensitivity of 75% and specificity of 65% (Figures 3B and dominant cluster in patients with multiple exacerbations. The E4B). For exacerbations associated with virus alone the area intraclass correlation coefficient of the biologic clusters for under the receiver operating characteristic curve for serum patients with repeated exacerbations was 0.73. Each biologic CXCL10 improved to 0.83 (95% CI, 0.70–0.96). cluster was found to be differentially related to inflammation and etiology, but was otherwise clinically indistinguishable. Exacerbations Associated with Sputum Eosinophilia A sputum eosinophilia was observed in 28% of exacerbations. Exacerbations Associated with Bacteria The most sensitive and specific measure to determine a sputum Fifty-five percent of exacerbations were bacteria-associated eosinophilia at exacerbation was the percentage peripheral exacerbations (positive bacterial pathogen on routine culture blood eosinophil count with an area under the receiver operating or CFU > 107). Blood and sputum neutrophils were increased. characteristic curve of 0.85 (95% CI, 0.78–0.93). A cutoff of 2% Total bacterial load (16S) was higher in patients with a bacteria- peripheral blood eosinophils had a sensitivity of 90% and spec- associated exacerbation than those without (geometric mean ificity of 60% for identifying a sputum eosinophilia of greater 7.67 [95% CI, 4.27 to 1.48] vs. 2.88 [95% CI, 1.78 to 4.78]; P ¼ than 3% at exacerbation (Figure 3C, Figure E4C). 0.001). There was no difference in the 16S signal across exacer- In summary, the etiologic and inflammatory causes of exacerba- bations of Anthonisen type (analysis of variance; P ¼ 0.64). tion events were as follows: bacteria alone 37%, virus alone 10%, Using qPCR, acquisition of a new species occurred in 15% of sputum eosinophilia alone 17%, bacteria plus virus 12%, bacteria exacerbations. Clinical assessments of change in FEV1, symp- plus sputum eosinophilia 6%, virus plus sputum eosinophilia 3%, toms of sputum production, and sputum purulence had an area bacteria plus virus plus sputum eosinophilia 1%, and none 14%. under the receiver operating characteristic curve of 0.45 (95% Multivariate modeling using combinations of two or three CI, 0.35–0.55), 0.50 (95% CI, 0.40–0.60), and 0.58 (95% CI, biomarkers for the detection of bacteria-, virus-, and eosinophil- 0.48–0.68), respectively. The most suitable biomarker for deter- associated exacerbations did not significantly improve on the single mining bacteria-associated exacerbations was sputum IL-1b mediators alone (data not shown). Differential clinical and bio- with an area under the receiver operating characteristic curve marker expression for exacerbations associated with bacteria, of 0.89 (95% CI, 0.83–0.95). A cutoff of 125 pg/ml had a virus, and sputum eosinophilia are shown in Tables E4–E6.
  • 5. 666 AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE VOL 184 2011 Figure 2. (A) Bar chart representing the mean factor scores for the three identi- fied biologic factors (proinflammatory, Th1, and Th 2) categorized according to the four biologic clusters. (B) Propor- tional representation of biologic chronic obstructive pulmonary disease exacerba- tion clusters in three-dimensional ellip- soids. Cluster 1 is termed “bacteria- predominant” and is outlined in blue, cluster 2 is termed “eosinophil-predomi- nant” and is outlined in green, cluster 3 is termed “virus-predominant” and is out- lined in red, and cluster 4 is termed “pau- ciinflammatory” and is outlined in gray. Predicting Bacteria-, Virus-, or and mean (SEM) FEV1% predicted of 46 (2) percent sputum Sputum-associated Exacerbations IL-1b and serum CXCL10 was measured using a commercial The odds ratio for a bacteria or an eosinophil-associated exac- ELISA (R&D Systems, Abingdon, UK). The area under the erbation was 4.9 (95% CI, 2.4–9.9; P , 0.001) or 2.7 (95% CI, receiver operating characteristic curve for percentage blood 1.3–5.7; P ¼ 0.01) if the patient had a bacterial pathogen on eosinophils to identify a sputum eosinophil–associated exacer- diagnostic routine culture or a sputum eosinophilia on greater bation was 0.95 (95% CI, 0.87–1.00) with a cutoff of 2% having than or equal to one occasion at stable state. The odds ratio for a sensitivity and specificity of 90% and 60%. The area under a virus-associated exacerbation if the patient had a virus at the receiver operating characteristic curve for sputum IL-1b stable state was 0.5 (95% CI, 0.1–3.9; P ¼ 0.67). and serum CRP to identify a bacteria-associated exacerbation was 0.73 (95% CI, 0.61–0.85) and 0.70 (95% CI, 0.59–0.82); a sputum IL-1b cutoff of 130 pg/ml had a sensitivity and spec- Validation of the Biomarkers Peripheral Blood Eosinophils, ificity of 80% and 60%, and a serum CRP cutoff of 10 mg/L Sputum IL-1b, Serum CRP, and Serum CXCL10 had sensitivity and specificity of 65%. The area under the re- In an independent study of COPD exacerbations, 89 subjects (57 ceiver operating characteristic curve for serum CXCL10 to men and 32 women) with a mean (range) age of 68 (46–86) years identify a virus-associated exacerbation was 0.65 (95% CI,
  • 6. Bafadhel, McKenna, Terry, et al.: Biomarkers in COPD Exacerbations 667 TABLE 2. BIOLOGIC CLUSTERS OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE EXACERBATIONS, WITH CLINICAL EXACERBATION AND BASELINE CHARACTERISTICS Cluster 1: Cluster 2: Cluster 3: Cluster 4: Bacteria-predominant Eosinophil-predominant Virus-predominant Pauciinflammatory P Value Exacerbation characteristics Number (%) 52 (35) 44 (30) 36 (24) 16 (11) — Sputum TNFRII (pg/ml)* 1,722 (1,402–2,117) 353 (287–433) 1,254 (969–1,623) 77 (41–147) ,0.0001 Sputum CXCL11 (pg/ml)* 3.1 (2.2–4.3) 10.9 (7.7–15.5) 799 (415–1,539) 17.3 (5.6–53.1) ,0.0001 Sputum CCL17 (pg/ml)* 5.5 (4.5–6.7) 34.8 (27.3–44.5) 23.5 (16.2–34.1) 4.7 (3.5–6.3) ,0.0001 Bacterial exacerbation, % (95% CI) 86 (73–92) 29 (18–45) 44 (28–61) 31 (12–58) ,0.0001 Viral exacerbation, % (95% CI) 22 (13–35) 10 (3–23) 57 (39–73) 30 (10–61) ,0.0001 Eosinophilic exacerbation, % (95% CI) 6 (1–16) 60 (45–74) 28 (16–44) 27 (10–52) ,0.0001 D FEV1, ml† 2132 (2251 to 235) 2110 (2230 to 231) 2232 (2340 to 2124) 2280 (2524 to 236) 0.32 D CRQ, units † 20.9 (21.2 to 20.6) 20.9 (21.3 to 20.5) 20.9 (21.4 to 20.4) 21 (21.9 to 20.1) 0.99 D VASTOTAL, mm† 79 (42–116) 80 (41–119) 120 (86–154) 73 (38–108) 0.39 Baseline characteristics Number, (%) 28 (37) 19 (25) 20 (27) 8 (11) — Male, n (%) 18 (64) 14 (74) 14 (70) 7 (88) 0.63 Age, yrs‡ 69 (52–84) 68 (45–88) 70 (49–84) 69 (61–85) 0.62 Current smokers, n (%) 8 (29) 8 (42) 4 (20) 3 (38) 0.48 Pack-years smoked‡ 44 (10–122) 50 (20–106) 47 (10–134) 72 (23–120) 0.11 Exacerbation rate in previous 12 mo 3.8 (0.5) 4.3 (0.5) 4 (0.7) 4.9 (1.2) 0.58 Exacerbation rate during study 3.8 (0.3) 3.6 (0.4) 3.2 (0.3) 3.1 (0.5) 0.64 Inhaled corticosteroid dose, mgx 1,507 (147) 1,567 (133) 1,470 (160) 1,150 (188) 0.55 Residual volume, % 134 (8) 150 (9) 120 (8) 146 (23) 0.11 TLCO % predicted 56 (5) 59 (5) 57 (6) 46 (7) 0.62 FEV1% predicted, baseline 53 (3) 51 (5) 53 (5) 40 (7) 0.34 FEV1/FVC ratio (%) 51 (2) 47 (2) 50 (3) 47 (5) 0.67 CRQTOTAL , units 4.14 (0.20) 3.90 (0.22) 4.10 (0.26) 3.66 (0.50) 0.74 VASTOTAL , mm 178 (15) 142 (18) 124 (18) 147 (37) 0.14 Total sputum cell count (3106 cells/g)* 8.3 (5.5–12.5) 2.3 (1.6–3.2) 2.5 (1.2–5.3) 3.5 (1.2–10.7) 0.002 Sputum neutrophil count, % 75 (5) 53 (4) 68 (4) 81 (6) 0.003 Sputum eosinophil count, %* 1 (0.6–1.6) 3.1 (1.4–6.6) 1 (0.5–1.9) 0.5 (0.2–1) 0.012 Bacterial colonization, % (95% CI) 63 (48–77) 27 (15–43) 11 (3–29) 38 (18–61) 0.001 Definition of abbreviations: CCL ¼ ; CI ¼ confidence interval; CRQ ¼ Chronic Respiratory Disease Questionnaire score; CXCL ¼ ; TLCO ¼ carbon monoxide transfer factor; TNF ¼ tumor necrosis factor; VAS ¼ visual analog score. Data presented as mean (SEM), unless stated. * Geometric mean (95% CI). y Mean change (95% CI) between exacerbation and baseline. z Mean (range). x Beclomethasone dipropionate equivalent. 0.52–0.78) with a cutoff of 145 pg/ml having a sensitivity and these exacerbation clinical phenotypes are likely to represent dis- specificity of 70% and 60%. tinct pathophysiologic entities with specific biomarker signatures. Further details and results are available in the online supplement. Biomarker profiling in COPD exacerbations has the potential to further the understanding of disease mechanisms (22), whereas phenotypic approaches lend to prognostic and thera- DISCUSSION peutic strategies (37, 38). Using factor and cluster analysis, In this study we have used two methods to investigate bio- a novel approach of characterizing COPD and exacerbations markers in COPD. The first using unbiased statistical tools, free (23), we were able to reduce an extensive panel of measured from bias and independent of clinical expression, identified bi- sputum biomarkers into three factors, from which we deter- ologic COPD exacerbation phenotypes and characterized exac- mined four biologic clusters. This analytic strategy is free from erbations into four biologic clusters, The second method used investigator bias. These biologic clusters could not be distin- current clinical exacerbation phenotypes of COPD related to po- guished clinically or by Anthonisen criteria (14) and the exac- tential etiology and inflammation, namely exacerbations that are erbation severity was similar across the clusters. Importantly, associated with bacteria, virus, or a sputum eosinophilia. Inter- using factor analysis we have shown differential inflammatory estingly, we were unable to define biomarkers for exacerbations profiles between the bacteria-predominant, eosinophil-predominant, per se, despite a generalized increase in systemic and airway in- virus-predominant, and pauciinflammatory clusters. In patients flammation (34–36). The biologic exacerbation clusters were bac- with multiple exacerbations the biologic clusters were repeat- terial-, viral-, or eosinophilic-predominant, and a fourth was able, and exacerbations associated with bacteria or a sputum associated with limited changes in the inflammatory profile and eosinophilia but not viruses could be predicted from stable state. was termed “pauciinflammatory.” These clusters were remark- Therefore, our data are consistent with the view that bacterial ably similar to our clinical exacerbation phenotypes. We identi- and eosinophilic exacerbations may reflect instability within fied biomarkers for our clinical exacerbation phenotypes that a complex and inherently unstable system, whereas viral exacer- were then validated in an independent cohort. The bacteria- bations are more likely to represent acquisition of a new patho- and sputum eosinophil–associated exacerbations rarely coexisted, gen. It is likely both of these mechanisms drive exacerbations, but and were reliably predicted from stable state suggesting funda- critically we have determined biologic clusters and clinical phe- mental differences in their immunopathogenesis. Therefore, in notypes that may respond to different management strategies, addition to identifying potential biomarkers to direct therapy, which can potentially be identified using biomarker profiles.
  • 7. 668 AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE VOL 184 2011 Figure 3. Receiver operating characteristic curve with area under the curve (95% confidence interval) illustrating biomarkers that positively predict (A) bacteria-, (B) virus-, and (C) eosinophil-associated exacerbations. Area under the curve (95% confidence interval) is shown in the paren- theses. CCL ¼ ; CRP ¼ C-reactive protein; CXCL ¼ ; TNF ¼ tumor necrosis factor.
  • 8. Bafadhel, McKenna, Terry, et al.: Biomarkers in COPD Exacerbations 669 The inflammatory profile of a COPD exacerbation is typically exacerbation. In our study a statistical analytic limitation was neutrophilic, but eosinophilic airway inflammation also exists, that we did not correct for repeated measures and assessed and is associated with a favorable response to corticosteroid ther- changes in biomarkers in paired or unpaired tests; however, apy (8–10). Eosinophilia in inflammatory airways disease is as- we examined two methods to investigate biomarkers in COPD sociated with increased all-cause mortality (39, 40) and may exacerbations, using unbiased statistical tools to demonstrate highlight different genetic, biologic, and pathologic disease pro- four biologic clusters and analysis of biomarkers to look at pre- cesses. Importantly, the sputum differential rather than total defined clinical exacerbation subgroups, and further used multi- eosinophil count has consistently been shown to be associated variate analysis to determine that combinations of markers did with important clinical outcomes (9, 10). We found that the not improve our predictive model. The presence of coinfection peripheral percentage eosinophil count was a sensitive biomarker with virus and bacteria in our study was lower than that previ- of a sputum eosinophilia. Current guidelines recommend the use ously reported (5), but may reflect differences in the severity of systemic corticosteroids for COPD exacerbations, although the of exacerbations. The relationship between virus and bacterial magnitude of the benefit is marginal and their use associated with infection in exacerbations, however, remains poorly understood significant side effects (18). Our findings raise the possibility that (5, 45). We chose to define a bacteria-associated exacerbation targeting corticosteroid therapy in a subgroup of exacerbations based on a positive routine culture or a high bacterial load; dependent on the peripheral eosinophil count may reduce inap- however, the causal links between the presence of bacteria propriate use of systemic corticosteroids. and exacerbations has not been rigorously confirmed, and evi- Bacteria are considered to play a role in up to 50% of exac- dence for efficacy of antibiotics in treatment is conflicting (13, erbations (7). Current guidelines propose sputum purulence 19–21, 46). Developments in molecular bacterial identification to guide antibiotic therapy (13). Sputum purulence is sensitive of bacteria (47) and emerging microbiomics (48) are beginning for detecting bacterial culture or high bacterial yields at exac- to redefine the microbiota of the airway in health and disease erbation in COPD (12). However, the use of sputum purulence and will likely change the view of what defines a bacterial in- alone is confounded by its presence at stable state and chronic fection. Improvements in viral detection and the identification bacterial colonization (41), possibly as a consequence of poor of new respiratory viruses are also changing the understanding bacterial clearance (42). Furthermore, the change in sputum of the associations between exacerbations and these agents. purulence or sputum production symptoms in our cohort was Further work is required before therapeutic implications and not sensitive or specific for identifying a bacteria-associated interpretative criteria can be established for these sensitive de- exacerbation. The most sensitive and specific assay for deter- tection methods. Whether identification of a pauciinflammatory mining bacteria-associated exacerbations was sputum IL-1b. biologic cluster and a proportion of subjects without clear evi- This extends previous findings that bronchoalveolar lavage IL- dence of a cause for their exacerbation reflect the insensitivity 1b was a good biomarker for ventilator-associated pneumonia of our chosen cutoffs for definitions or a real entity requires (43), and suggests that this airway marker may suitably deter- further clarifications. mine bacterial infections, above that of serum CRP or procalci- In conclusion, COPD exacerbations are heterogeneous. This tonin whose use could not be demonstrated in this study or in phenotypic heterogeneity can be defined. Using unbiased statis- others (34, 35). Sputum IL-1b could thus be used as a biomarker tical tools we have determined four biologic exacerbation clus- to correctly identify bacteria-associated exacerbations but ters that relate to identifiable patterns of inflammation and would require the development of a rapid near patient test to potential causative pathogens. We have defined sensitive and be of use in clinical practice. specific biomarkers to identify predefined clinical exacerbation Viruses have been implicated as a major cause of COPD exac- phenotypes, which need to be tested in randomized prospective erbations and are detected in approximately half of severe studies of targeted therapy. These subgroups are independent COPD exacerbations (5, 6). The total sputum eosinophil count has been proposed as a potential biomarker of a viral exacerbation and suggest that the mechanisms driving their exacerbations (5). Here we also found that the total absolute sputum eosino- are distinct and may be amenable to more specific interventions, phil count was increased in virus-associated exacerbations, but potentially moving the management of COPD exacerbations to- not the differential sputum eosinophil count, suggesting the ward the realization of phenotype-specific management. association was largely a consequence of a change in the total- Author Disclosure: M.B. received grant support from the Medical Research Coun- cell count. The application of clinical symptoms in combination cil (MRC). S.M. does not have a financial relationship with a commercial entity with serum CXCL10 (IP-10) has been proposed as a possible that has an interest in the subject of this manuscript. S.T. does not have a financial relationship with a commercial entity that has an interest in the subject of this biomarker for rhinovirus infection at exacerbation (44). This manuscript. V.M. does not have a financial relationship with a commercial entity study confirms that serum CXCL10 levels as a potential pre- that has an interest in the subject of this manuscript. C.R. does not have a financial dictor of a virus-associated exacerbation, independent of a re- relationship with a commercial entity that has an interest in the subject of this manuscript. P.H. does not have a financial relationship with a commercial entity quirement for symptom evaluation. Novel antiviral approaches that has an interest in the subject of this manuscript. M.M. is employed by and are in development and CXCL10 is thus a promising biomarker owns stocks in AstraZeneca (AZ). K.H. does not have a financial relationship with to direct future antiviral therapy. a commercial entity that has an interest in the subject of this manuscript. T.K. does not have a financial relationship with a commercial entity that has an in- One potential criticism is that this is a single-center study and terest in the subject of this manuscript. A.D. does not have a financial relationship therefore our findings need to be replicated across multiple cen- with a commercial entity that has an interest in the subject of this manuscript. ters, and validated prospectively to identify the biologic clusters K.L. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript. H.P. does not have a financial relation- and our proposed biomarkers for the clinical exacerbation phe- ship with a commercial entity that has an interest in the subject of this manu- notypes; nonetheless, this approach may represent a new para- script. P.R., P.D., and M.J. are employed by and own stocks in AZ. M.S. is digm in the management of COPD exacerbations. Importantly, employed by AZ. P.N. was an employee of AZ at the time of conducting this we have replicated the biomarkers peripheral blood eosinophils, research and preparation of the manuscript. He is now an employee of MedI- mmune LLC, which is a subsidiary of AZ and owns stocks in AZ. R.H.G. was sputum IL-1b, and serum CXCL10 in a validation cohort. Pe- a consultant for Nycomed and received travel accommodations from Chiesi. ripheral blood eosinophils remained a strong marker of a sputum P.V. received institutional grant support from the Swedish Research Council. eosinophilia. Sputum IL-1b and serum CXCL10 were measured D.A.L. received institutional grant support and was a consultant for GlaxoSmithK- line (GSK). He is on the Advisory Board and received honorarium from GSK. using a different platform but remained significant albeit weaker M.R.B. received institutional grant support form the MRC. S.L.J. was a consultant predictive markers of identifying a bacteria- or virus-associated for AZ, Centocor, Sanofi-Pasteur, Synairgen, GSK, and Chiesi. He received
  • 9. 670 AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE VOL 184 2011 institutional grant support from AZ, Centocor, Sanofi-Pasteur, Synairgen, and AZ. pulmonary disease: a prospective randomised controlled trial. Lancet He received lecture fees from AZ, owns stocks in Synairgen, and received travel 1999;354:456–460. accommodations from Pfizer. I.D.P. received institutional grant support from the 18. Niewoehner DE, Erbland ML, Deupree RH, Collins D, Gross NJ, Light MRC and received honorarium from GSK, AZ, Merck, and Novartis. He received travel accommodations from Boehringer Ingelheim (BI). C.E.B. received institu- RW, Anderson P, Morgan NA. Effect of systemic glucocorticoids on tional grant support from the MRC, AZ, MedImmune, and Roche. He received exacerbations of chronic obstructive pulmonary disease. Department support for the development of SPD assays in Cambridge from GSK. He is on the of Veterans Affairs Cooperative Study Group. N Engl J Med 1999; Advisory Board of GSK, AZ, Roche, Novartis, Genentech, and MedImmune and 340:1941–1947. was a consultant for MedImmune and Novartis. He received travel accommoda- 19. Puhan MA, Vollenweider D, Latshang T, Steurer J, Steurer-Stey C. tions from BI. Exacerbations of chronic obstructive pulmonary disease: when are Acknowledgment: The authors thank all the research volunteers who participated antibiotics indicated? A systematic review. Respir Res 2007;8:30. in the study, and also the following people for their valuable assistance throughout 20. Puhan MA, Vollenweider D, Steurer J, Bossuyt PM, Ter RG. Where is the study: J. Aniscenko, M. Bourne, R. Braithwaite, D. Burke, J. Footitt, E. Goldie, the supporting evidence for treating mild to moderate chronic ob- J. Goldie, N. Goodman, S. Gupta, B. Hargadon, I. Rushby, M. Shelley, A. Singapuri, structive pulmonary disease exacerbations with antibiotics? A sys- D. Vara, R. Walton, and S. Winpress. tematic review. 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