Airway hyperresponsiveness in chronic obstructive pulmonary disease: A marker of asthma-chronic obstructive pulmonary disease overlap syndrome?

Accepted Manuscript Airway Hyperresponsiveness in COPD: A Marker of Asthma-COPD Overlap Syndrome? Ruzena Tkacova, MD, PhD, Darlene L.Y. Dai, MSc, Judith M. Vonk, PhD, Janice M. Leung, MD, Pieter S. Hiemstra, PhD, Maarten van den Berge, MD, PhD, Lisette Kunz, MD, Zsuzsanna Hollander, PhD, Donald Tashkin, MD, Robert Wise, MD, John Connett, PhD, Raymond Ng, PhD, Bruce McManus, MD, PhD, S.F. Paul Man, MD, Dirkje S. Postma, MD, PhD, Don D. Sin, MD PII:

S0091-6749(16)30351-7

DOI:

10.1016/j.jaci.2016.04.022

Reference:

YMAI 12128

To appear in:

Journal of Allergy and Clinical Immunology

Received Date: 21 June 2015 Revised Date:

2 April 2016

Accepted Date: 13 April 2016

Please cite this article as: Tkacova R, Dai DLY, Vonk JM, Leung JM, Hiemstra PS, van den Berge M, Kunz L, Hollander Z, Tashkin D, Wise R, Connett J, Ng R, McManus B, Man SFP, Postma DS, Sin DD, Airway Hyperresponsiveness in COPD: A Marker of Asthma-COPD Overlap Syndrome?, Journal of Allergy and Clinical Immunology (2016), doi: 10.1016/j.jaci.2016.04.022. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Airway Hyperresponsiveness in COPD: A Marker of Asthma-COPD Overlap Syndrome?

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Ruzena Tkacova, MD, PhD1,3; Darlene L. Y. Dai, MSc1,2, Judith M. Vonk, PhD4,5; Janice M. Leung, MD1,6; Pieter S. Hiemstra, PhD7; Maarten van den Berge, MD, PhD5,8, Lisette Kunz, MD7; Zsuzsanna Hollander, PhD1,2; Donald Tashkin, MD9; Robert Wise, MD10; John Connett, PhD11; Raymond Ng, PhD1,2,12; Bruce McManus, MD, PhD1,2,13; S.F. Paul Man, MD1,6; Dirkje S. Postma, MD, PhD5,8; Don D. Sin, MD1,6 Affiliations: 1

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UBC James Hogg Research Center & the Institute for Heart and Lung Health, St. Paul’s Hospital, Vancouver, British Columbia, Canada The PROOF Center of Excellence, St. Paul’s Hospital, Vancouver, British Columbia, Canada

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Dept. od Respiratory Medicine and Tuberculosis, Faculty of Medicine, P. J. Safarik University, Kosice, Slovakia

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Department of Epidemiology, University of Groningen, University Medical Center Groningen, The Netherlands 5 University of Groningen, University Medical Center Groningen, GRIAC research institute, Groningen, The Netherlands

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Department of Medicine (Pulmonary Division), University of British Columbia, Vancouver, British Columbia, Canada Department of Pulmonology, Leiden University Medical Center, Leiden, The Netherlands

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University of Groningen, University Medical Center Groningen, Department of Pulmonary Diseases, Groningen, The Netherlands David Geffen School of Medicine at UCLA, Los Angeles, CA, USA Johns Hopkins University School of Medicine, Baltimore, MD, USA

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University of Minnesota School of Public Health, Minneapolis, MN, USA

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Department of Computer Sciences, University of British Columbia, Vancouver, British Columbia, Canada 13

Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada Corresponding author (and reprint requests): Don D. Sin, Tel: +1 604 806 8395 Fax: +1 604 806 9274 Email: [email protected]. Address: St. Paul’s Hospital, 1081 Burrard Street, Vancouver, BC, Canada, V6Z 1Y6

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Author's contributions to the study

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Ruzena Tkacova, Darlene L. Y. Dai, MSc, Zsuzsanna Hollander, PhD, and Janice M. Leung: Substantial contributions to the design of the work, to the analysis and interpretation of data, drafting the work; final approval of the version to be published; agreement to be accountable for all aspects of the work

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Judith M. Vonk, Pieter S. Hiemstra, PhD; Maarten van den Berge, Lisette Kunz; Donald Tashkin; Robert Wise; John Connett; Raymond Ng; Bruce McManus; S.F. Paul Man; Dirkje Postma: Substantial contributions to the conception and design of the work; and to the acquisition of data; revising the work critically for important intellectual content; final approval of the version to be published; agreement to be accountable for all aspects of the work.

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Don D. Sin, MD: Substantial contributions to the conception and design of the work; to the analysis and interpretation of data for the work; revising the work critically for important intellectual content; final approval of the version to be published; and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Funding Source

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The LHS Biomarker Study was funded by the Canadian Institutes of Health Research (CIHR) & Genome Canada and the Canadian Respiratory Research Network (CRRN) The original LHS was funded by the US National Heart, Lung and Blood Institute. The GLUCOLD study was originally funded by the Netherlands Organization for Scientific Research, the Netherlands Asthma Foundation, GlaxoSmithKline, University Medical Center Groningen and Leiden University Medical Center. DDS is supported by a Tier 1 Canada Research Chair in COPD. Running head: Lung function decline and mortality in ACOS

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Descriptor number: 9.12 COPD: Outcomes

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Word count: 3,942

This article has an online data supplement.

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ABSTRACT Rationale: The impact of airway hyperreactivity (AHR) on respiratory mortality and systemic inflammation among patients with COPD is largely unknown. We used data from two large

(FEV1) decline, respiratory mortality and systemic inflammation.

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studies to determine the relationship between AHR with forced expiratory volume in 1 second

Objectives: To determine the relationship of AHR with FEV1 decline, respiratory mortality and

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systemic inflammatory burden in patients with COPD in the Lung Health Study (LHS) and the GLUCOLD Study.

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Methods: LHS enrolled current smokers with mild-to-moderate COPD (n=5,887) and GLUCOLD enrolled former and current smokers with moderate-to-severe COPD (n=51). For the primary analysis, we defined AHR by a methacholine provocation concentration of ≤4 mg/mL, which led to a 20% reduction in FEV1 (PC20).

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Measurements and Results: The primary outcomes were FEV1 decline, respiratory mortality and biomarkers of systemic inflammation. Approximately 24% of LHS participants had AHR. Compared with patients without AHR, AHR increased the risk of respiratory mortality by two-

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fold (hazard ratio 2.38; 95% confidence interval 1.38-4.11, p=0.002) and accelerated FEV1 decline by 13.2 mL/yr in LHS (p=0.007) and by 12.4 mL/year in the much smaller GLUCOLD

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Study (p=0.079). Patients with AHR had generally reduced burden of systemic inflammatory biomarkers than those without AHR. Conclusions: AHR is common in mild to moderate COPD, affecting 1 in 4 patients and identifies a distinct sub-set of patients, who have increased risk of disease progression and mortality. AHR may represent a spectrum of the asthma-COPD overlap phenotype that urgently requires disease modification.

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Abstract word count: 247

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Key words: respiratory hypersensitivity, airway obstruction, lung function tests, death rate

Capsule Summary

Airway hyperresponsiveness is common in mild to moderate COPD, affecting 1 in 4 patients and identifies a distinct sub-set of patients, who have increased risk of disease progression and

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respiratory mortality.

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Key Messages

Methacholine provocation testing proved to be a powerful method for identifying patients with COPD, who have increased risk of rapid decline in lung function and respiratory mortality.

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Airway hyperresponsiveness may represent a spectrum of the asthma-COPD overlap phenotype that urgently requires disease modification.

The major relevance of our study is highlighted by its potential to initiate future

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interventional studies to modify respiratory mortality and decline in lung function in COPD patients with the asthma-COPD overlap phenotype.

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List of Abbreviations

ACOS, asthma-COPD overlap syndrome

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ACRP, adiponectin

AHR, airway hyperreactivity AIC, Akaike Information Criterion AUC, area-under-the-curve

BDR, bronchodilator response BNDF, brain neurotrophic derived factor CC16, club cell protein-16 COPD, chronic obstructive pulmonary disease CRP, C–reactive protein 4

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CVD, cardiovascular disease ENA78, epithelial neutrophil-activating protein 78 FEV1, forced expiratory volume in 1 second FDR, false discovery rate

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FVC, forced vital capacity

GLUCOLD, Groningen Leiden Universities Corticosteroids in Obstructive Lung Disease ICAM1, intracellular adhesion molecule 1 ICS, inhaled corticosteroids

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IFNg, interferon gamma IL1b, interleukin-1b

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IL1ra, interleukin 1 receptor antagonist IL6, interleukin 6 IL8, interleukin 8 IL15, interleukin 15

IP10, interferon-gamma-inducible protein 10 kDa LHS, Lung Health Study

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MCP1, monocyte chemoattractant protein 1

MIP1b, macrophage inflammatory protein 1beta MMP-9, matrix metalloproteinase 9

MPIF1, myeloid progenitor inhibitory factor-1

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MPO, myeloperoxidase

PARC, pulmonary and activation-regulated chemokine

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RANTES, Regulated on activation, normal T cell expressed and secreted SPD, surfactant protein D

TIMP, tissue inhibitor of metalloproteinase TNFa, tumor necrosis factor alpha TNFR1, tumor necrosis factor receptor 1 TNFR2, tumor necrosis factor receptor 2 ROC, receiver operating characteristics curve

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INTRODUCTION About 300 million people in the world suffer from chronic obstructive pulmonary disease

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(COPD) (1). Although asthma and COPD are distinct disorders, some patients may have components of both diseases, especially among those who persistently smoke. Recently, a joint task force of GINA and GOLD published a set of criteria to identify smokers with both asthma

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and COPD features (i.e. asthma-COPD overlap syndrome, ACOS) (1, 2). One of the diagnostic criteria of ACOS is marked bronchial responsiveness to short acting bronchodilators in patients

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with COPD. Although not mentioned in the GINA/GOLD document, another way of assessing bronchial responsiveness is by performing bronchoprovocation challenge tests to induce bronchoconstriction. Bronchodilation and bronchoconstriction are not interchangeable, and mark different aspects of airway responsiveness. In the general population, airway hyperreactivity

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(AHR) is a powerful predictor of respiratory symptoms (3) and future risk of COPD (4). Among COPD patients, AHR has been associated with a rapid decline in lung function (5) and measures of gas trapping and airway inflammation (6). AHR may also identify a subgroup of patients with

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COPD who may be responsive to inhaled corticosteroids (ICS) (7). Thus, AHR may represent a subgroup of COPD patients with an “asthmatic" component, since most asthmatics demonstrate

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airway hyperresponsiveness. Recently, there has been a growing interest in identifiying such patients because these patients have not been well studied and most importantly have been systematically excluded in major therapeutic trials in COPD. In this study, we explored the use of a methacholine challenge test as a possible diagnostic tool for identifying COPD patients with an “asthmatic" phenotype and most importantly determining the relation of AHR to important

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clinical characteristics and endpoints including symptoms, lung function decline, systemic inflammation and mortality in a large group of patients with mild-to-moderate COPD.

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MATERIALS AND METHODS

LHS Subjects

The characteristics of Lung Health Study (LHS) patients, the study design, spirometric

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methodology, and measurement of AHR have all been reported in detail previously (5, 8, 9). Briefly, the original multicenter clinical trial LHS enrolled active smokers between the ages of

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35 and 60 years who had smoked at least 10 cigarettes a day within the 30 days prior to initial screening and who demonstrated mild to moderate airflow limitation on spirometry defined by FEV1 of 55% to 90% of predicted, in the presence of FEV1/forced vital capacity (FVC) ratio of < 0.70 after bronchodilation.

After enrollment, patients were asked to visit the study center annually for 5 years and

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based on self-report and objective measures of cigarette exposure at every visit (e.g. salivary cotinine levels), they were classified as sustained quitters (non-smokers at all 5 visits), continued

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smokers (smokers at all 5 visits) or intermittent quitters (varying smoking status at visits) (8). Patients were then passively followed for additional 7-9 years during which their vital status data

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were captured biannually (10). An independent mortality and morbidity committee reviewed death certificates, autopsy reports, relevant hospital records, and summaries of interviews with attending physicians or eyewitnesses and assigned the causes of death for all patients who died during the study. These data were supplemented by linkages with a National Death Index, which provided the date and cause of death for all US study patients for up to 14 years. Vital status was successfully determined for 98.3% of the patients. Mortality end points were classified into

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cardiovascular disease (CVD), lung cancer, other cancers, respiratory diseases excluding lung cancer, others, and unknown (10).

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Lung Function Measurements and Methacholine Challenge Testing in LHS

Spirometry was performed at the time of recruitment and annually for 5 years after recruitment (8). Owing to smoking cessation and use of a bronchodilator (i.e., ipratropium), some individuals

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experienced a significant increase in FEV1 during the first 2 years. In subsequent years, however, study patients (on average) experienced a linear rate of decline in FEV1 (8). To remove this “first

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2-year” effect, we determined the rate of decline using year 2 FEV1 as the baseline measurement. The methacholine inhalation test was performed at the screening visit according to a previously described protocol; the nebulizer output was determined by weight to be 10.5 ± 1.3 (SD) µL per actuation (5). Patients were instructed to avoid theophylline and antihistamine compounds for 24

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hours, inhaled bronchodilators for 12 hours, caffeine for 6 hours, and cigarette smoking for 2 hours prior to undergoing testing. Patients inhaled five inspiratory capacity breaths of increasing methacholine concentrations (0, 1, 5, 10, and 25 mg/mL). The session was completed when

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either the highest concentration was administered or there was a > 20% fall in FEV1 compared to

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the FEV1 after the diluent inhalation.

Serum Sample collection and Measurements in LHS At the 5th annual visit, venipuncture was carried out. After collection, the blood samples were separated into their various components and transferred to the LHS data coordinating center on dry ice and were kept in -70 oC freezers until use (11). The serum samples were thawed and 30 serum proteins were measured using a highly sensitive chemiluminescence multiplexed

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sandwich ELISA analyzer (SearchLight proteome array system; Pierce Biotechnology Inc, Rockford, IL). The details of the biomarker measurements have been published elsewhere (12).

Care Research Ethics Committee (No. H08-01864).

The GLUCOLD Study

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The protocol of this study was approved by University of British Columbia/Providence Health

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The relationship between AHR and rate of FEV1 decline was also examined in the Groningen Leiden Universities Corticosteroids in Obstructive Lung Disease (GLUCOLD) Study; the details

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have been previously reported (NCT00158847) (13). In brief, GLUCOLD recruited patients with COPD between the ages of 45 and 75 years with moderate-to-severe COPD (FEV1 30 to 80% of predicted); most had never used ICS and all did not use ICS for at least 6 months prior to study entry. The GLUCOLD Study was originally a randomized controlled trial with four treatment

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arms: 1) fluticasone (500 µg BID) for 30 months; 2) fluticasone/salmeterol (500/50 µg BID) for 30 months; 3) fluticasone (500 µg BID) for 6 months followed by placebo for 24 months and 4) placebo for 30 months. To mitigate the effects of ICS and long-acting bronchodilators on FEV1

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decline, only participants who were assigned either to group 3 (ICS followed by placebo) or 4 (placebo) were included in the current analyses. Subsequent to the 30 months of the original trial,

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the patients were seen in-person and spirometry was performed yearly for up to 5 years. The rate of decline data were calculated from baseline to year 7.5 of follow-up except for group 3 where the baseline was considered to be the 6-month measurement (in order to eliminate the effects of ICS). We also excluded all FEV1 measurements after the initial 30-month trial period of patients who started using ICS following the initial trial. Post-bronchodilator FEV1 was used in all measurements. In the GLUCOLD cohort the PC20 methacholine responsiveness was tested at

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baseline, at 6, and 30 months (6) as described previously (14). The value, 78.4, was assigned to those who were not hyperresponsive (i.e. did not experience a 20% drop in FEV1 even at the

Statistical Analyses Statistical

analyses

were

performed

with

R

(www.r-project.org)

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given by 2 (i.e. 2 * 39.2).

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highest dose given). This figure was derived by multiplying the the highest methacholine dose

Bioconductor

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(www.bioconductor.org) or SPSS (version 22, IBM). The results are presented as mean±SD for continuous variables and counts of events (percentage) for categorical variables. In the primary analysis, patients were divided into two categories (AHR and non-AHR groups) based on the PC20 threshold value of 4 mg/mL, which indicates a positive result according to the ATS guidelines for methacholine testing (15). The baseline characteristics for AHR and non-AHR

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COPD groups were compared using t-tests for continuous variables and a χ2 test for categorical variables. In LHS, to calculate the rate of lung function decline, a mixed linear effects model was applied to FEV1 for all the patients from year 2 to year 5. In multivariable models, we adjusted

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for the possible confounding effects of baseline FEV1, age, sex, body mass index (BMI), and smoking status (continuous smokers vs. intermittent smokers vs. sustained quitters). A similar

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approach was used for the GLUCOLD data except that the multivariate model was adjusted for only age and baseline FEV1, two leading risk factors for AHR and FEV1 decline, because of the limited sample size that precluded inclusion of many variables. Based on the ECLIPSE study, we chose a FEV1 decline cutoff of 40 mL per year (more than 120 mL over the 3-year study period) to define rapid decliners (16), and we determined the performance characteristics of AHR (as determined by PC20 values), bronchodilator response (BDR) and smoking sttus (sustained

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quitters versus intermittent smokers versus continous smokers). The latter parameter is a recognized clinical predictor of FEV1 decline. The receiver operating characteristics curve (ROC) and its area-under-the-curve (AUC) were calculated. We then used the DeLong's test

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(using the pROC R package) to compare the sensitivity and specificity of PC20, BDR and smoking status on the rate of FEV1 decline (17). A Cox proportional hazards model, modified for competing risks for death as suggested by Fine and Gray (18), was used to evaluate respiratory,

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CVD and total mortality from the date of blood draw to end of the follow-up. The proportional hazards assumption, which was imposed on its sub-distribution hazards, was checked visually

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and it was met. For the biomarker analysis, a generalized linear model was used to test which of the 30 measured proteins were differentially expressed between AHR and non-AHR subjects. Adjustments were made in the model for age, sex, BMI, smoking status, and baseline FEV1. Proteins with a false discovery rate (FDR) <0.05 were considered significantly different between

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the two groups. FDR was calculated using the Benjamini & Hochberg method. Since there is no consensus on what constitutes the most optimal cutoff for defining AHR in COPD, in an exploratory analysis, we investigated the impact of using other PC20 values for defining ACOS

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on the endpoints of FEV1 decline and respiratory mortality. In this exploratory analysis, we defined the “best” PC20 threshold for both FEV1 and respiratory death as the value that was

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associated with the lowest Akaike Information Criterion (AIC), indicating the best goodness of fit. The AIC is a measure of the relative quality of statistical models for a given set of data. In general, adding features (i.e. covariates) to a model improves its fit with the actual data up to a point, after which the marginal improvements to the model’s fit are outweighed by the cost of adding more features. To avoid over-fitting, AIC values are penalized through inflation when features/covariates that are not informative are added to the model. Thus, to achieve the lowest

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AIC value possible, investigators are encouraged to include only those covariates that are truly informative (and exclude those that are not informative). In general, the preferred model is the

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one with the minimum AIC value among a set of candidate models for the data.

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RESULTS Clinical Characteristics of ACOS and non-ACOS Patients in LHS A total of 5,887 LHS patients underwent a methacholine provocation test at baseline. In the

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primary analysis based on PC20 of ≤4 mg/mL, 1,434 patients (24%) were classified as having AHR. The demographic and clinical characteristics of patients with AHR [PC20 (median, 2575%) 2.5 (1.4-3.3) mg/mL] and without AHR [PC20 19.1 (7.6-20.0) mg/mL] at screening are

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presented in Table 1. Compared to non-AHR COPD patients, those with AHR demonstrated reduced FEV1 and FEV1/FVC at baseline and a larger bronchodilator response. The proportion of

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women was also higher in AHR compared to non-AHR patients. Although wheezing was the most common symptom in both groups, patients with AHR reported a lower frequency of wheezing compared to non-AHR patients. The prevalence of cough or phlegm production was

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also lower among AHR patients.

FEV1 Decline and Death from Respiratory Causes in LHS The estimated coefficients and their p-values are shown in Table 2. AHR patients experienced a

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faster rate of decline in FEV1 compared with non-AHR patients (Figure 1A, Figure 1B, Figure E1). The difference in FEV1 decline between AHR and non-AHR patients was 10.3 mL/year

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(95% confidence interval (CI): 6.3 – 14.2, p<0.0001) without any adjustments and 13.2 mL/year (95% CI: 7.3 – 19.0, p=0.007) with full adjustments including baseline FEV1. The summary of hazard ratios and cumulative incidence function for respiratory deaths is shown in Table 3 and Figure 2A, indicating that patients with AHR had a higher risk of respiratory mortality after adjustments. In contrast, there was no statistically significant difference in the risk of total or CVD mortality between the two groups (Figure 2B and 2C). The number of death cases in each category is indicated in Table E1 in the online data supplement. 13

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Demographic data of GLUCOLD The details of patients with AHR [PC20 0.34 (0.01-3.16) mg/mL] versus those without AHR [PC20 8.82 (4.23-78.60) mg/mL] in GLUCOLD are shown in Table 1. Similar to LHS, AHR

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COPD patients in GLUCOLD had a lower FEV1/FVC than non-AHR patients.

FEV1 decline in GLUCOLD

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Patients with AHR defined by PC20≤4 mg/mL had a faster decline in FEV1 by 11.9 mL/year (95% CI: -1.46 – 25.16, p=0.081) compared to non-AHR patients without any adjustments and

Serum Biomarker Analysis in LHS

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by 12.4 mL/year (95% CI: -1.4 – 26.2, p=0.079) after adjustments for age and baseline FEV1.

Out of the 30 proteins analyzed, which were chosen a priori based on previous literature on the

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pathogenesis of COPD, there were 15 biomarkers that were differentially expressed between AHR and non-AHR patients at a FDR<0.05 following adjustments for age, sex, BMI, and smoking status (Table 4). Of these 15, only adiponectin was up-regulated in the AHR group

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compared with the non-AHR group; the remaining biomarkers [myeloid progenitor inhibitory

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factor-1 (MPIF1), interferon gamma (IFNg), tumor necrosis factor receptor (TNFR) 1, TNFR2, interleukin (IL) IL 1b, IL6, IL8, IL15, interferon-gamma-inducible protein 10 kDa (IP10), C– reactive protein (CRP), interleukin 1 receptor antagonist (IL1ra), tumor necrosis factor alpha (TNFa), intracellular adhesion molecule 1 (ICAM1), macrophage inflammatory protein 1beta (MIP1b), myeloperoxidase (MPO)] were all down-regulated in patients with AHR.

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Alternative PC20 Thresholds in LHS The AICs of FEV1 decline based on incremental cut-off values of PC20 are shown in Figures E2A and E2B. The best cutoff threshold for PC20 based on AIC values was 15 mg/mL. The plot

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of AICs for respiratory mortality is shown in Figure 3. The summaries of coefficients for FEV1 decline based on a 15 mg/mL threshold of PC20 are shown in Table E2 in the online data supplement. The difference in FEV1 decline between AHR and non-AHR patients was 13.5

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mL/year (95% CI: 9.7-17.2, p<0.0001) without any adjustments and 17.8 mL/year (95% CI: 12.2 – 23.4, p<0.0001) with full adjustments of the variables listed in Methods.

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Based on the PC20 threshold of 15 mg/mL, 12 serum proteins were differentially expressed in AHR versus non-AHR patients following adjustments for age, sex, BMI, and smoking status (Table E3 in the online data supplement). Again, only adiponectin was up-regulated, and 11 serum biomarkers [MPIF1, IFNγ, TNFα, IL6, TNFR1, TNFR2, CRP, ICAM1, pulmonary and

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activation-regulated chemokine (PARC), club cell protein-16 (CC16)] and bilirubin were all downregulated in the AHR group compared with the non-AHR group.

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Bronchodilator Response in LHS

We also evaluated the endpoints of FEV1 decline and respiratory mortality using BDR of 12% or

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higher with an absolute increment of 200 mL as the threshold. Patients with a BDR <12% or an absolute increment < 200mL and those with a BDR≥12% and an absolute increment ≥200mL had a similar FEV1 at baseline (Table E4 in the online data supplement). There was no significant difference in respiratory mortality between the two groups (Table E5 in the online data supplement). Patients with a BDR≥12% and an absolute increment of ≥200 mL did not demonstrate a significantly faster decline in FEV1 [-4.79 mL/year (95% CI: -12.57, 3.00),

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p=0.228 without any adjustments; Table E6 in the online data supplement]. There was a trend towards significance with full adjustments [-9.58 mL/year (95% CI: -20.58, 1.43, p=0.088)]. AIC of the bronchodilator threshold model (191336.5) was larger than the AIC of COPD with AHR,

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defined using PC20 ≤4 or ≤15 mg/mL cutoffs (AIC, 191321.6; 191271.6, respectively), indicating that the bronchodilator cutoff approach produced worse data fit than any of the PC20 values. In addition, we found that the p-value of the ROC-AUC comparison between PC20 and

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BDR was highly significant at p=6.107e-06. In contrast, there was no significant difference in the ROC-AUC values between PC20 and smoking status (p=0.23) (Figure E3 in the online data

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supplement). There was only one protein that was differentially expressed at an FDR <0.05

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between the two groups based on BDR cutoff approach (Table E7 in the online data supplement).

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DISCUSSION The most important finding of the present study was that patients with COPD who also demonstrated AHR experienced an accelerated decline in FEV1 and had 2-fold increased risk of

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respiratory mortality as compared to patients without AHR, irrespective of disease severity, smoking status or any other confounding or disease modifying factors. On average, patients with AHR had 10.3 mL/yr more FEV1 decline than non-AHR patients without adjustment and 13.2

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mL/yr more after adjustment over 3 years of follow-up in LHS. We also found that COPD patients with AHR demonstrated either no or significantly reduced levels of serum inflammatory

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biomarkers except for circulating adiponectin that was up-regulated as compared to COPD patients without AHR.

Our findings are in keeping with previous studies, which have demonstrated a significant relationship between AHR and accelerated decline in lung function and increased respiratory

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mortality in the general population (19, 20) and in those with COPD (21, 22). The mechanism by which AHR associates with accelerated lung function decline is not clear but does not appear to relate to enhanced systemic inflammation; on the contrary we found no difference or even

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reduced inflammatory plasma parameters in patients with AHR. A recent study by Fu et al. (23) found that COPD patients with an “asthmatic“ phenotype demonstrated similar circulating levels

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of IL-6 or CRP as COPD patients without asthmatic features. Similarly, Iwamoto et al. reported similar plasma levels for surfactant protein-A and soluble receptor for advanced glycation endproducts between the two groups (24). However, these previous studies were relatively small and may have missed an important signal. In our study, although we found differential plasma expression of 15 (out of 30) systemic inflammatory biomarkers in patients with versus without AHR, all of these proteins except adiponectin levels were significantly lower in those with AHR,

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suggesting that the systemic inflammatory burden may be similar or even lower in COPD patients with AHR than those without. To what extent AHR in subjects with COPD represents a component of asthma is also

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uncertain, since there are many underlying physiological factors that can influence bronchial responsiveness in asthma and COPD such as airway wall edema, inflammation, smooth muscle hypertrophy, small airway obstruction, and loss of airway attachments (25-27). Moreover, in

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asthma, eosinophilic inflammation appears to be the main driver of AHR; whereas in COPD, neutrophils may play a larger role (28, 29). Despite these uncertainties, AHR was the single most

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important risk factor for respiratory mortality in our analysis surpassing the risk imposed by smoking, BMI, gender or even age (Tables 2 and 3). Interestingly, we found no significant relationship between AHR defined by PC20 cut-off of ≤4 mg/mL and cardiovascular or total mortality.

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In contrast to our findings on bronchoconstrictive responsiveness, we found that bronchodilator reversibility, which has been advocated as an objective measure of both asthma and ACOS (1, 2), was not associated with increased risk of respiratory mortality, though it was

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associated with a non-significant trend towards a faster decline in lung function in keeping with findings from the ECLIPSE Study (30) and that of Postma et al. (22). However, the AIC values

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suggest that PC20 was a stronger predictor for FEV1 decline than bronchodilator reversibility. Together, these data indicate that AHR defines a distinct phenotype in patients with COPD. There are clinical implications to our findings. First, based on the ≤4 mg/mL threshold, 1

in 4 patients with mild-to-moderate COPD would have AHR; while the use of ≤15 mg/mL threshold would increase this number to more than 1 in 2 (58% subjects had AHR using this PC20 threshold). For future interventional studies aimed at modifying COPD progression or

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respiratory mortality, enrichment of the study population with patients with AHR may significantly enhance the power of the study to detect differences in FEV1 decline and mortality. Second, systemic inflammation, as assessed by the inflammatory biomarkers we have evaluated

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for this study, appears to play a less significant role (if any) in COPD patients with AHR compared to those without and thus biomarkers that are able to point towards disease progression and poor health outcomes in COPD patients with AHR may be very different from those

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required in patients without AHR. Third, present findings may have clinical implications for consideration of therapy with inhaled corticosteroids (ICS) in COPD patients. Previously we

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have shown within the GLUCOLD study that ICS and ICS combined with a long-acting betaagonist improved AHR after 6 and 30 months of treatment and slowed the rate of decline in FEV1 (7), and that the severity of PC20 worsened when patients were switched from ICS to placebo (6). Here our results indicate that the best cutoff threshold for PC20 for FEV1 decline is

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15 mg/mL. Taken together, these findings suggest that ICS may be useful for patients with AHR to prevent FEV1 loss. Finally, bronchodilator reversibility is a weak substitute for methacholine provocation testing and likely has different underlying mechanisms. Hence reversibility is

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probably not optimal in predicting health outcomes in patients with mild-to-moderate COPD. Our findings of the robust relationships between AHR and clinically important outcomes in

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patients with COPD may signify a clinically relevant subtype. AHR is also common in asthma, hence this phenotype may be an important determinant for further studies on ACOS. There were some limitations to this study. First, we had only one measurement of

biomarkers and as such the stability of our observations over time is uncertain. Second, the biomarkers were assessed at the fifth year of follow-up and not at the time of bronchoprovocation testing, and thus the findings may have been different in earlier phases of

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COPD. In addition, although we identified 15 systemic inflammatory biomarkers that were statistically different between ACOS and non-ACOS patients, the magnitude of the differences in the levels was relatively small. Thus, none of these proteins are likely to be clinically useful

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predictors of ACOS. However, these differences suggest that the ACOS phenotype in COPD may be associated with reduced levels of systemic inflammation compared with non-ACOS COPD patients. Third, very few patients in LHS demonstrated a large BDR (>400 mL

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improvement), which some have suggested as a major criterion for ACOS (31). Indeed, we have attempted to evaluate the endpoints of FEV1 decline and respiratory mortality using BDR of 15%

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or higher with an absolute increment of 400 mL as the threshold; however, there was only a total of 121 (2%) LHS participants who fulfilled this BDR threshold which limited further analyses to this end. Thus, it remains uncertain whether this BDR threshold can be used as an ACOS marker in lieu of PC20. However, given the scarcity of patients in LHS who had a >400 mL

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improvement in FEV1 with a bronchodilator, the clinical relevance of this phenotype is uncertain. Importantly, the performance characteristics (sensitivity and specificity) of PC20 was superior to that of BDR, and was similar to that of smoking status,which is clearly an important

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predictor of rate of lung function decline. Additional studies will be required to enable translation of AHR as a clinical predictor of FEV1 decline in the future. Fourth, airflow

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obstruction reduces the specificity of bronchoprovocation testing due to the potential effects of altered airway geometry on airway responsiveness. Increased thickness of the airway wall, along with accumulation of secretions in the airway lumen and increased stiffness of the cartilage and reduced lung elastic recoil due to emphysema are all factors that can contribute to increased airway responsiveness. Thus, the increased AHR may have been a marker of altered airway geometry. Nevertheless, it was assuring that even with full adjustments for baseline FEV1 and

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other important covariates (e.g. age and smoking) in our analysis, AHR was still associated with a rapid decline in FEV1, suggesting that AHR may independently contribute to COPD progression. This, however, does not rule out the possibility that baseline FEV1 could also

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contribute to AHR and to COPD progression as the relationship between these parameters are complex. Moreover, there may be different risk factors in very early life that may drive COPD pathogenesis, AHR and respiratory mortality later in life (32). Future mechanistic studies will be

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needed to fully resolve this issue. It should also be noted that PC20 thresholds as a diagnostic tool to identifying asthmatics in smokers with early COPD has never been validated. Since

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increasing the PC20 cut point increases the sensitivity while reducing the specificity to diagnose asthma in subjects with normal lung function (and vice versa), here we chose a PC20 threshold of ≤4 mg/mL in the primary analysis to maximize the specificity of diagnosing asthma in our cohort of COPD patients. This approach is consistent with the recommendation of the American

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Thoracic Society, which suggests a cut-off of 4 mg/mL on a methacholine challenge test to indicate positivity (15). Fifth, to examine airway responsiveness, LHS used the dosimeter method while the GLUCOLD Study used the tidal breathing method. Head to head comparison

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of the two methods has been performed by a number of investigators. Some have found no significant difference between the two methods (33, 34), while others have found some minor

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differences (35, 36). Even in the latter studies, the mean difference was less than one doubling dose, with the dosimeter method showing slightly higher PC20 values most likely because the technique

involves

subjects

taking

in

full

inspirations,

which

tends

to

promote

bronchodilation. To address this concern, we have re-analyzed the LHS data using a PC20 cut off value of ≤2 mg/mL, and the results were no different than the original analysis. Using a PC20 cut-off of ≤2 mg/mL, patients with AHR demonstrated a faster FEV1 decline and higher

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respiratory mortality compared to those without AHR (Figures E2A, E2B and Figure 3). Finally, based on the present results it is not known whether COPD patients with AHR have any pathologic features of asthma, namely eosinophilic airway inflammation. A previous analysis in

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the GLUCOLD study has suggested that AHR in COPD may represent neutrophilic airway inflammation and gas trapping (compatible with small airways disease and/or emphysema) and not eosinophilic inflammation (27). Additional studies will be needed to compare and contrast

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the pathologic features of AHR in COPD versus asthma and its implication to patient care.

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The novelty of the current study includes data on: a) the relation between AHR and respiratory mortality; b) the impact of AHR on biomarkers of systemic inflammation; c) external replication of the relationship between AHR and FEV1 decline in an independent cohort; and d) evaluation of different thresholds of PC20 in identifying a subgroup of COPD patients with poor health outcomes including respiratory mortality and rapid FEV1 decline. These new data are

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critical in advancing our understanding of COPD patients who also have features of AHR. In conclusion, methacholine provocation testing is a powerful method of identifying a

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distinct COPD phenotype. Patients with COPD who express AHR appear to have a lower systemic inflammatory burden yet they are at increased risk of rapid decline in lung function and

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respiratory mortality. AHR may be a feature of ACOS phenotype that has also been related to a more rapid decline in lung function and high mortality, though additional work will be needed to fully vadilate this notion (37, 38). Notwithstanding the label, COPD patients with AHR may need further attention for targeted therapy to reduce bronchial hyperresponsiveness, an important next step to see if this can prevent further decline in lung function and mortality.

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Acknowledgements DDS is a Tier 1 Canada Research Chair in COPD.

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RT was supported the project MediPark, Kosice, ITMS:26220220185, Operational Programme Research and Development (OPVaV-2012/2.2/08-RO) (Contract No. OPVaV/12/2013).

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JML is a fellow with the Michael Smith Foundation for Health Research.

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Park HY, Churg A, Wright JL, Li Y, Tam S, Man SF, Tashkin D, Wise RA, Connett JE, Sin DD. Club cell protein 16 and disease progression in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2013;188(12):1413-1419.

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Lapperre TS, Snoeck-Stroband JB, Gosman MM, Jansen DF, van Schadewijk A, Thiadens HA, Vonk JM, Boezen HM, Ten Hacken NH, Sont JK, Rabe KF, Kerstjens HA, Hiemstra PS, Timens W, Postma DS, Sterk PJ; Groningen Leiden Universities Corticosteroids in Obstructive Lung Disease Study Group.. Effect of fluticasone with and without salmeterol on pulmonary outcomes in chronic obstructive pulmonary disease: a randomized trial. Ann Intern Med. 2009;151(8):517-527.

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Cockroft DW. Direct challenge tests: Airway hyperresponsiveness in asthma: its measurement and clinical significance. Chest 2010; 138: 18S-24S.

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DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44(3):837-45.

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O'Connor GT, Sparrow D, Weiss ST. A prospective longitudinal study of methacholine airway responsiveness as a predictor of pulmonary-function decline: the Normative Aging Study. Am J Respir Crit Care Med. 1995;152(1):87-92. de Jong JW, Koeter GH, Postma DS. The significance of airway responsiveness in the onset and evolution of chronic obstructive pulmonary disease. Clin Exp Allergy. 1997;27(10):1114-1119. 25

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Postma DS, de Vries K, Koeter GH, Sluiter HJ. Independent influence of reversibility of air-flow obstruction and nonspecific hyperreactivity on the long-term course of lung function in chronic air-flow obstruction. Am Rev Respir Dis. 1986;134(2):276-280.

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van der Wiel E, Postma DS, van der Molen T, Schiphof-Godart L, Ten Hacken NH, van den Berge M. Effects of small airway dysfunction on the clinical expression of asthma: a focus on asthma symptoms and bronchial hyper-responsiveness. Allergy. 2014;69(12):1681-1688.

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Suzuki T, Wang W, Lin JT, Shirato K, Mitsuhashi H, Inoue H. Aerosolized human neutrophil elastase induces airway constriction and hyperresponsiveness with protection by intravenous pretreatment with half-length secretory leukoprotease inhibitor. Am J Respir Crit Care Med. 1996;153(4 Pt 1):1405-11.

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Postma DS, Bush A, van den Berge M. Risk factors and early origins of chronic obstructive pulmonary disease. Lancet. 2015;385(9971):899-909. 26

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Siersted HC, Walker CM, O'Shaughnessy AD, Willan AR, Wiecek EM, Sears MR. Comparison of two standardized methods of methacholine inhalation challenge in young adults. Eur Respir J. 2000;15(1):181-4.

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33.

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FIGURE LEGEND

Figure 1 Decline of FEV1 (A) and absolute FEV1 (B) in patients with COPD with AHR and

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without AHR (black: PC20 cutoff of 4 mg/mL; red: PC20 cutoff of 15 mg/mL) in LHS.

Figure 2 Estimates of cumulative incidence of respiratory mortality (A), cardiovascular disease

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(CVD) mortality (B) and total mortality (C) for COPD patients with AHR and without AHR (non-AHR) (black: PC20 cutoff of 4 mg/mL; red: PC20 cutoff of 15 mg/mL). For each plot, x-

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axis is follow-up in years from the date of blood draw to the end of the passive follow-up of LHS and y-axis is the probability of mortality for a given time.

Figure 3 Akaike Information Criterion (AIC) of respiratory death, indicating the best goodness

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of fit, of different thresholds of PC20.

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LHS*

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Table 1. Demographic data, smoking history, lung function and symptoms in LHS and GLUCOLD patients with COPD and AHR (PC20 ≤4 mg/mL) or without AHR (PC20>4 mg/mL) GLUCOLD*

Non-AHR N = 4453

P value

AHR N = 41

50.0 (44.0,54.0)

49.0 (43.0,54.0)

0.010

64.0 (58.0-68.0)

644 (45)

3058 (69)

<0.001

35 (85)

10 (100)

0.331

Pack-years of smoking

37.0 (28.0,49.0)

37.0 (28.0,50.5)

0.663

40.0 (27.6-53.4)

51.5 (42.0-64.0)

0.015

Age started smoking, yr

17.0 (16.0,19.0)

17.0 (15.0,19.0)

0.016

NA

NA

--

Cigarettes/ day, No

30.0 (20.0,40.0)

30.0 (20.0,40.0)

0.033

NA

NA

--

BMI, kg/m2

25.1 (22.5,28.0)

25.2 (22.8,27.8)

0.371

24.8 (22.1-27.4)

26.6 (23.3-29.2)

0.184

Cough

652 (45)

2376 (53)

Phlegm

761 (53)

2589 (58)

Wheeze

1085 (76)

3797 (85)

2.4 (2.0,2.8)

Symptoms, No (%)

P value

56.5 (55.8-65.5)

0.221

NA

NA

--

<0.001

NA

NA

--

<0.001

NA

NA

--

2.8 (2.4,3.3)

<0.001

1.89 (1.52-2.47)

2.25 (1.80-2.78)

0.052

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<0.001

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FEV1, L

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Male, No (%)

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Age at baseline, yr

Non-AHR N = 10

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AHR N = 1434

Variable

FEV1, % predicted

75.2 (67.6,81.9)

80.2 (73.5,86.0)

<0.001

64.1 (56.9-69.8)

66.5 (60.4-73.9)

0.275

FEV1/FVC, %

63.2 (57.7,67.4)

66.7 (62.6,69.9)

<0.001

48.1 (41.4-56.5)

58.2 (47.7-63.4)

0.015

5.1 (1.7,8.7)

3.7 (0.9,6.6)

<0.001

NA

NA

--

Bronchodilator %

response,

*data presented as median (IQR) unless indicated otherwise 29

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Abbreviations: AHR, airway hyperreactivity; BMI, body mass index; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; GLUCOLD, Groningen Leiden Universities Corticosteroids in Obstructive Lung Disease, LHS, Lung Health Study; NA, not available.

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Table 2. Rate of FEV1 decline in LHS and GLUCOLD patients with COPD and AHR (PC20 ≤4 mg/mL) or without AHR (PC20>4 mg/mL)

Univariate

Variable

GLUCOLD

Multi-variate

Univariate

p-value

Estimated Coefficient

p-value

Estimated Coefficient

(Intercept)

2811.51

<0.001

167.54

<0.001

2401.03

Time, year

-56.62

<0.001

6.87

0.710

AHR vs non-AHR

-422.53

<0.001

-15.92

0.028

0.95

<0.001

0.55

0.489

-22.16

0.038

-11.81

0.105

45.93

<0.001

2

Intermittent smokers vs quitters Continuing vs quitters

smokers

Women vs men 1

year

Time:FEV1 interaction

baseline

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Age, per increase Time: interaction

-1.23

0.015

-12.68

<0.001

-0.004

0.250

-0.30

0.390

-4.20

0.376

-20.15

<0.001

Time:Women interaction

-10.28

0.011

Time:Age interaction

-0.55

0.015

AHR

Time: intermittent smokers interaction

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Time: Continuing smokers interaction

<0.001

EP

-11.09

Time:BMI interaction

P

Est. coefficient

p

<0.001

770.4

0.270

-56.77

<0.001

27.49

0.537

-417.25

0.026

-226.28

0.070

39.31

<0.001

-16.56

0.020

-12.40

0.079

-0.09

0.019

-0.05

0.333

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BMI, per kg/m

Multi-variate

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Estimated Coefficient

FEV1 at baseline, per % predicted

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LHS

-11.85

0.081

Abbreviations: AHR, airway hyperreactivity; BMI, body mass index; FEV1, forced expiratory volume in 1 second; LHS, Lung Health Study

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Table 3. The risk of total, respiratory and cardiovascular mortality in LHS patients with COPD and AHR (PC20 ≤4 mg/mL) versus without AHR (PC20>4 mg/mL) Respiratory Mortality CVD Mortality Total Mortality HR* 95% CI P-value HR* 95% CI P-value HR* 95% CI P-value 2.38 1.38-4.11 0.002 1.27 0.75-2.12 0.370 1.15 0.97-1.37 0.107 AHR Intermittent smokers 1.64 0.56-4.86 0.370 1.71 0.58-5.07 0.330 1.84 1.37-2.48 <0.001 Continuing smokers 1.97 0.89-4.33 0.093 3.06 1.41-6.67 0.005 1.84 1.47-2.29 <0.001 1.69 0.93-3.08 0.086 1.30 0.77-2.17 0.320 1.28 1.08-1.51 0.005 Women 1.08 1.03-1.13 0.001 1.11 1.07-1.16 0.000 1.09 1.08-1.11 <0.001 Age 0.87 0.79-0.96 0.005 1.03 0.97-1.09 0.300 1.00 0.98-1.02 0.860 BMI

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Variable

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Abbreviations: AHR, airway hyperreactivity; BMI, body mass index; CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio; LHS, Lung Health Study

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* adjusted for age, sex, BMI and smoking status

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Table 4. Serum proteins in LHS patients with COPD and AHR (PC20 ≤4 mg/mL) or without AHR (PC20>4 mg/mL) Non-AHR*

FDR#

9.64(9.22,10.00) 2.46(1.72,3.60) 7.06(6.53,7.55) 9.88(9.48,10.23) 0.28(-0.43,1.06) 11.49(11.13,11.90) 19.2(18.86,19.62) 3.93(3.31,4.79) 2.25(1.59,2.91) 4.42(3.57,5.57) 24.59(23.99,25.30) 7.31(6.84,7.79) 1.33(0.85,2.01) 7.38(6.93,7.88) 16.49(15.79,17.18) 16.48(15.93,17.02) 11.99(11.45,12.69) 0.46(-0.72,1.58) 18.84(18.17,19.46) 9.71(9.32,10.13) 17.9(17.55,18.29) 2.81(2.32,3.17) 1.53(0.78,2.18) 20.91(20.53,21.29) 16.35(15.88,16.85) 12.52(11.94,13.11) 6.53(6.04,7.01) 15.65(15.21,16.03) 28.23(27.74,28.71) 11.16(10.60,11.79)

9.71(9.33,10.09) 2.72(1.87,3.98) 7.15(6.62,7.66) 9.98(9.61,10.34) 0.48(-0.32,1.35) 11.57(11.19,12.00) 19.27(18.91,19.68) 4.05(3.41,5.16) 2.34(1.71,2.99) 4.55(3.63,5.85) 24.35(23.70,25.07) 7.39(6.88,7.91) 1.42(0.87,2.15) 7.41(6.92,7.95) 16.6(15.85,17.35) 16.58(16.07,17.09) 12.07(11.46,12.78) 0.49(-0.68,1.63) 18.93(18.29,19.54) 9.75(9.38,10.11) 17.93(17.54,18.38) 2.81(2.32,3.17) 1.7(1.02,2.25) 20.91(20.53,21.32) 16.33(15.83,16.87) 12.44(11.86,13.06) 6.53(6.02,7.01) 15.61(15.18,16.04) 28.24(27.76,28.78) 11.1(10.50,11.69)

<0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 0.02 0.02 0.02 0.02 0.07 0.08 0.09 0.11 0.16 0.20 0.29 0.29 0.31 0.67 0.76 0.80 0.86 0.93 0.96

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*data presented as median (IQR) #

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AHR*

Protein

adjusted for age, sex, BMI and smoking status

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Abbreviations: AHR, airway hyperreactivity; ACRP, adiponectin; BNDF, brain neurotrophic derived factor; CC16, club cell protein-16; CRP, C–reactive protein; ENA78, epithelial neutrophil-activating protein 78; FDR, false discovery rate; ICAM1, intracellular adhesion molecule 1; IFNg, interferon gamma; IL1b, interleukin-1b; IL1ra, interleukin 1 receptor antagonist; IL6, interleukin 6; IL8, interleukin 8; IL15, interleukin 15; IP10, interferon-gammainducible protein 10 kDa; LHS, Lung Health Study; MCP1, monocyte chemoattractant protein 1; MIP1b, macrophage inflammatory protein 1beta; MMP-9, matrix metalloproteinase 9; MPIF1, myeloid progenitor inhibitory factor-1; MPO, myeloperoxidase; PARC, pulmonary and activation-regulated chemokine; RANTES, Regulated on activation, normal T cell expressed and secreted; SPD, surfactant protein D; TIMP, tissue inhibitor of metalloproteinase; TNFa, tumor necrosis factor alpha; TNFR1, tumor necrosis factor receptor 1; TNFR2, tumor necrosis factor receptor 2

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Airway Hyperresponsiveness in COPD: A Marker of Asthma-COPD Overlap Syndrome?

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Online Data Supplement

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Ruzena Tkacova, MD, PhD; Darlene L. Y. Dai, MSc, Judith M. Vonk, PhD; Janice M. Leung, MD; Pieter S. Hiemstra, PhD; Maarten van den Berge, MD, PhD, Lisette Kunz, MD; Zsuzsanna Hollander, PhD; Donald Tashkin, MD; Robert Wise, MD; John Connett, PhD; Raymond Ng, PhD; Bruce McManus, MD, PhD; S.F. Paul Man, MD; Dirkje Postma, MD, PhD; Don D. Sin, MD

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Table E1. Number of death cases in LHS patients with COPD and AHR (PC20 ≤4 mg/mL) or without AHR (PC20>4 mg/mL) No AHR

Total

Respiratory Mortality

24 (1.69%)

34 (0.77%)

58

CVD Mortality

22 (1.55%)

55 (1.24%)

Total Mortality

180 (12.67%)

502 (11.34%)

Total Samples

1421

4427

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AHR

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Abbreviations: LHS, Lung Health Study; AHR, airway hyperreactivity; CVD, cardiovascular disease

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Estimated Coefficient

p-value

170.27 24.00 -11.31 0.95 0.54 -22.21 -11.50 45.67 -1.24 -17.81 -0.01 -0.28 -4.70 -20.28 -10.71 -0.63

<0.001 0.202 0.080 <0.001 0.498 0.038 0.115 <0.001 0.015 <0.001 0.062 0.435 0.321 <0.001 0.008 0.005

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Variable (Intercept) Time, year AHR vs non-AHR FEV1 at baseline, per % predicted BMI, per kg/m2 Intermittent smokers vs quitters Continuing smokers vs quitters Women vs men Age, per 1 year increase Time: BHR interaction Time:FEV1 baseline interaction Time:BMI interaction Time: intermittent smokers interaction Time: Continuing smokers interaction Time:Women interaction Time:Age interaction

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Table E2. Rate of FEV1 decline in LHS patients with COPD and AHR (PC20 ≤15 mg/mL) or without AHR (PC20>15 mg/mL)

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Abbreviations: AHR, airway hyperreactivity; BMI, body mass index; FEV1, forced expiratory volume in 1 second; LHS, Lung Health Study

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Table E3. Serum proteins in LHS patients with COPD and AHR (PC20 ≤15 mg/mL) or without AHR (PC20>15 mg/mL) AHR*

Non-AHR*

24.55(23.9,25.23) 1.56(0.82,2.17) 9.66(9.27,10.05) 0.46(-0.74,1.60) 19.24(18.89,19.65) 3.97(3.33,4.96) 9.91(9.55,10.29) 16.51(15.98,17.06) 2.61(1.82,3.79) 1.37(0.84,2.04) 11.52(11.16,11.94) 2.81(2.32,3.17) 2.30(1.65,2.93) 7.10(6.59,7.60) 7.33(6.86,7.85) 0.38(-0.37,1.23) 12.52(11.92,13.13) 4.50(3.62,5.76) 9.73(9.35,10.11) 12.03(11.43,12.72) 16.36(15.87,16.87) 28.22(27.72,28.75) 18.90(18.26,19.52) 17.92(17.55,18.34) 7.40(6.94,7.91) 20.92(20.53,21.30) 6.53(6.05,7.02) 16.56(15.86,17.29) 15.64(15.21,16.04) 11.11(10.55,11.76)

24.24(23.58,24.95) 1.81(1.15,2.32) 9.73(9.36,10.09) 0.53(-0.62,1.64) 19.27(18.91,19.68) 4.09(3.48,5.21) 10.00(9.64,10.34) 16.60(16.12,17.1) 2.73(1.86,4.03) 1.44(0.89,2.23) 11.60(11.21,12.03) 2.81(2.32,3.17) 2.35(1.72,3.05) 7.16(6.61,7.66) 7.41(6.89,7.94) 0.49(-0.31,1.36) 12.39(11.84,12.97) 4.55(3.62,5.8) 9.75(9.38,10.12) 12.07(11.49,12.79) 16.31(15.81,16.86) 28.26(27.79,28.8) 18.91(18.26,19.54) 17.94(17.55,18.38) 7.40(6.89,7.95) 20.9(20.52,21.32) 6.53(6.01,7.01) 16.58(15.81,17.34) 15.59(15.15,16.04) 11.11(10.49,11.68)

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ACRP, pg/mL CC16, pg/mL MPIF1, pg/mL CRP, mg/L ICAM1, pg/mL TNFa, pg/mL TNFR1, pg/mL PARC, pg/mL IFNg, pg/mL Il6, pg/mL TNFR2, pg/mL Bilirubin, ug/L IL15, pg/mL IL1ra, pg/mL MIP1b, pg/mL IL1b, pg/mL ENA78, pg/mL IL8, pg/mL MCP1, pg/mL Eotaxin, pg/mL RANTES, pg/mL Fibronectin, pg/mL MMP-9, pg/mL TIMP, pg/mL IP10, pg/mL Selectin, pg/mL SP-D, ng/mL MPO, pg/mL BNDF, pg/mL Prolactin, pg/mL

*data presented as median (IQR) #

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Protein

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<0.01 <0.01 <0.01 0.02 0.02 0.02 0.02 0.02 0.03 0.03 0.03 0.05 0.10 0.10 0.11 0.26 0.42 0.42 0.42 0.51 0.59 0.68 0.68 0.68 0.72 0.84 0.84 0.88 0.92 0.98

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Abbreviations: AHR, airway hyperreactivity; ACRP, adiponectin; BNDF, brain neurotrophic derived factor; CC16, club cell protein-16; CRP, C–reactive protein; ENA78, epithelial neutrophil-activating protein 78; FDR, false discovery rate; ICAM1, intracellular adhesion molecule 1; IFNg, interferon gamma; IL1b, interleukin-1b; IL1ra, interleukin 1 receptor antagonist; IL6, interleukin 6; IL8, interleukin 8; IL15, interleukin 15; IP10, interferon-gammainducible protein 10 kDa; LHS, Lung Health Study; MCP1, monocyte chemoattractant protein 1; MIP1b, macrophage inflammatory protein 1beta; MMP-9, matrix metalloproteinase 9; MPIF1, myeloid progenitor inhibitory factor-1; MPO, myeloperoxidase; PARC, pulmonary and activation-regulated chemokine; RANTES, Regulated on activation, normal T cell expressed and secreted; SPD, surfactant protein D; TIMP, tissue inhibitor of metalloproteinase; TNFa, tumor necrosis factor alpha; TNFR1, tumor necrosis factor receptor 1; TNFR2, tumor necrosis factor receptor 2

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Table E4. Demographic data, smoking history, lung function at baseline and symptoms in patients with bronchodilator response of <12% or absolute increment < 200mL and those with ≥12% and absolute increment ≥200 mL in LHS.

49.0 (43.0,54.0)

215 (59)

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3486 (63)

37.0 (28.0,50.0) 17.0 (15.0,19.0) 30.0 (20.0,40.0) 25.2 (22.7,27.8)

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148 (41) 186 (51) 249 (68)

2879 (52) 3164 (57) 4631 (84)

2.8 (2.3,3.2) 78.4 (71.9,85.5) 64.5 (59.3,69.0) 4.3 (2.0,9.5) 14.4 (13.1,17.0)

2.7 (2.3,3.2) 79.0 (72.0,85.3) 66.0 (61.6,69.5) 9.5 (4.3,20.0) 3.6 (0.9,6.4)

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Mean age at baseline, yr Men, No (%) Packyears Age started smoking, yr Cigarettes/ day BMI, kg/m2 Symptoms, No (%) Cough Phlegm Wheeze FEV1, L FEV1, % predicted FEV1/FVC, % Methacholine reactivity (PC20), mg/mL Bronchodilator response, %

BDR < 12% or absolute increment <200mL N = 5521

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Variable

BDR ≥ 12% and absolute increment ≥200mL N = 364

P value <0.001 0.133 0.056 0.336 0.062 0.001

<0.001 0.024 <0.001 0.646 0.623 0.002 <0.001

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Abbreviations: BMI, body mass index; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; BDR, bronchodilation response; LHS, Lung Health Study; PC20, the geometric mean of provocation concentration of methacholine causing a 20% drop in FEV1.

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Bronchodilator (≥12% & ≥ 200mL) Intermittent smokers Continuing smokers Women Age, per 1 year increase BMI, per 1 kg/m2 increase

HR*

95% CI

P-value

HR*

95% CI

Pvalue

Death from all causes PHR* 95% CI value

1.39

0.50-3.85

0.530

1.46

0.64-3.34

0.370

1.31

1.66

0.56-4.9

0.360

1.71

0.58-5.08

0.330

1.97

0.89-4.35

0.094

3.07

1.41-6.69

0.005

1.39

0.78-2.46

0.260

1.08

1.03-1.13

<0.001

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0.8-0.96

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0.97-1.76

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1.85

1.38-2.48

<0.001

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Table E5. Estimation of hazard ratio, 95% confidence interval, and p-value from the subdistribution hazards models by Fine & Gray of respiratory death between subjects with bronchodilator response of <12% or absolute increment < 200mL and those with ≥12% and absolute increment ≥200 mL in LHS.

1.25

0.76-2.03

0.380

1.25

1.06-1.47

0.009

1.11

1.07-1.16

<0.001

1.09

1.08-1.11

<0.001

1.03

0.97-1.09

0.310

1.00

0.98-1.02

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Table E6. FEV1 rate of decline in subjects with bronchodilator response of <12% or absolute increment < 200 mL and those with ≥12% and ≥200 mL increase in LHS.

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P-value <0.001 0.866 0.491 <0.001 0.566 0.040 0.138 <0.001 0.024

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(Intercept) Time Bronchodilator Response (≥12% & ≥ 200ml increase) FEV1 at baseline, per % predicted BMI, per kg/m2 Intermittent smokers vs. quitters Continuing smokers vs. quitters Women vs. men Age, per 1 year increase Time: Bronchodilator (≥12% and ≥ 200 mL) interaction Time:FEV1 baseline interaction Time:BMI interaction Time: Intermittent smokers interaction Time: Continuing smokers interaction Time:Women interaction Time:Age interaction

Estimated Coefficient 150.96 -3.10 8.70 0.95 0.46 -21.99 -10.83 46.11 -1.14

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-0.001 -0.36 -4.39 -19.91 -10.07 -0.51

0.677 0.312 0.356 <0.001 0.013 0.024

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Abbreviations: FEV1, forced expiratory volume in 1 second; BMI, body mass index; LHS, Lung Health Study

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Table E7. Serum proteins in subjects with bronchodilator response of <12% or absolute increment < 200 mL and those with ≥12% and absolute increment ≥200 mL in LHS.

0.50(-0.67,1.63) 7.37(6.88,7.89) 16.57(16.05,17.08) 19.26(18.90,19.66) 11.56(11.18,11.98) 6.54(6.04,7.02) 24.40(23.77,25.13) 15.62(15.19,16.04) 12.06(11.46,12.75) 28.24(27.76,28.76) 2.67(1.83,3.89) 0.43(-0.34,1.31) 7.12(6.6,7.63) 7.40(6.93,7.93) 20.91(20.53,21.3) 9.74(9.37,10.11) 9.70(9.31,10.07) 16.57(15.84,17.31) 11.11(10.53,11.71) 17.93(17.55,18.36) 9.96(9.59,10.32) 2.32(1.69,2.97) 16.34(15.84,16.87) 2.81(2.32,3.17) 12.46(11.88,13.07) 18.91(18.26,19.53) 4.02(3.38,5.07) 4.51(3.62,5.78) 1.40(0.87,2.13) 1.67(0.97,2.24)

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FDR #

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0.17(-1.09,1.27) 7.30(6.80,7.78) 16.40(15.90,16.99) 19.19(18.86,19.63) 11.46(11.07,11.90) 6.41(5.97,6.93) 24.51(23.75,25.07) 15.62(15.14,16.03) 11.96(11.41,12.75) 28.22(27.77,28.79) 2.62(1.87,3.83) 0.40(-0.44,1.26) 7.20(6.50,7.63) 7.36(6.79,7.84) 20.91(20.54,21.35) 9.72(9.33,10.15) 9.62(9.26,10.02) 16.54(15.75,17.27) 11.11(10.45,11.74) 17.87(17.53,18.36) 9.89(9.52,10.27) 2.34(1.60,3.06) 16.30(15.87,16.85) 2.81(2.32,3.17) 12.41(11.83,13.06) 18.88(18.27,19.45) 3.98(3.49,5.01) 4.56(3.62,5.93) 1.31(0.80,2.00) 1.62(0.90,2.21)

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0.01 0.51 0.51 0.63 0.63 0.63 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.95 0.95 0.95 0.95 0.95 0.95 0.95 0.98 0.99

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Abbreviations: ACRP, adiponectin; BNDF, brain neurotrophic derived factor; CC16, club cell protein-16; CRP, C–reactive protein; ENA78, epithelial neutrophil-activating protein 78; FDR, false discovery rate; ICAM1, intracellular adhesion molecule 1; IFNg, interferon gamma; IL1b, interleukin-1b; IL1ra, interleukin 1 receptor antagonist; IL6, interleukin 6; IL8, interleukin 8; IL15, interleukin 15; IP10, interferon-gamma-inducible protein 10 kDa; MCP1, monocyte chemoattractant protein 1; MIP1b, macrophage inflammatory protein 1beta; MMP-9, matrix metalloproteinase 9; MPIF1, myeloid progenitor inhibitory factor-1; MPO, myeloperoxidase; PARC, pulmonary and activation-regulated chemokine; RANTES, Regulated on activation, normal T cell expressed and secreted; SPD, surfactant protein D; TIMP, tissue inhibitor of metalloproteinase; TNFa, tumor necrosis factor alpha; TNFR1, tumor necrosis factor receptor 1; TNFR2, tumor necrosis factor receptor 2

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Online Repository Figure Legends

Figure E1 Decline of FEV1 (boxplots) in patients with COPD with AHR and without

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AHR (black: PC20 cutoff of 4 mg/mL; red: PC20 cutoff of 15 mg/mL) in LHS.

Figure E2 Akaike Information Criterion (AIC) for for FEV1 decline, indicating the best

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Figure E3. Receiver operating characteristic (ROC) curves of airway responsiveness (PC 20),

bronchodilator response (BDR) and smoking status for FEV1 decline of more than 120 m

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