Atrial septal defect in adults is associated with airway hyperresponsiveness

OBJECTIVE

The association between secundum atrial septal defects (ASD) and asthma-like dyspnea with consequent long-term pulmonary inhalant use, is poorly understood in adult ASD patients. Airway hyperresponsiveness is suggested to be the underlying mechanism of cardiac asthma from mitral valve disease and ischemic cardiomyopathy. We hypothesized that airway hyperresponsiveness may also be found in adult ASD patients. Our aim was to study airway responsiveness in adult ASD patients before percutaneous closure and at short-and long-term postprocedural follow-up.

METHODS

This prospective study included 31 ASD patients (65% female, mean age 49 ± 15y) who underwent spirometry and bronchoprovocation testing pre-and six-month postprocedurally, with additional bronchoprovocation at 2-year follow-up. Airway hyperresponsiveness was defined as ≥20% fall of forced expiratory volume in 1-second (FEV₁ ) following <8.0 mg/mL of inhaled methacholine.

RESULTS

Airway hyperresponsiveness was found in 19/30 patients (63%[95%CI 45%-81%]; post hoc statistical power = 89%). Asthma-like symptoms wheezing, chest tightness, and cough were more frequently reported in airway hyperresponsive patients. Airway responsiveness was not influenced by successful percutaneous ASD closure, corresponding to persistence of asthma-like symptoms postclosure. Regardless of airway responsiveness, postprocedural right-sided reverse remodeling significantly improved dyspnea and pulmonary function.

CONCLUSIONS

This study is the first to report a high prevalence of airway hyperresponsiveness in a cohort of unrepaired adult ASD patients, and confirms the association between asthma-like symptoms and ASD in adults. Attention to symptoms and pulmonary function should be given during clinical follow-up of adult ASD patients, both before and long after repair.

Lipid phenotyping of lung epithelial lining fluid in healthy human volunteers

BACKGROUND

Lung epithelial lining fluid (ELF)-sampled through sputum induction-is a medium rich in cells, proteins and lipids. However, despite its key role in maintaining lung function, homeostasis and defences, the composition and biology of ELF, especially in respect of lipids, remain incompletely understood.

OBJECTIVES

To characterise the induced sputum lipidome of healthy adult individuals, and to examine associations between different ELF lipid phenotypes and the demographic characteristics within the study cohort.

METHODS

Induced sputum samples were obtained from 41 healthy non-smoking adults, and their lipid compositions analysed using a combination of untargeted shotgun and liquid chromatography mass spectrometry methods. Topological data analysis (TDA) was used to group subjects with comparable sputum lipidomes in order to identify distinct ELF phenotypes.

RESULTS

The induced sputum lipidome was diverse, comprising a range of different molecular classes, including at least 75 glycerophospholipids, 13 sphingolipids, 5 sterol lipids and 12 neutral glycerolipids. TDA identified two distinct phenotypes differentiated by a higher total lipid content and specific enrichments of diacyl-glycerophosphocholines, -inositols and -glycerols in one group, with enrichments of sterols, glycolipids and sphingolipids in the other. Subjects presenting the lipid-rich ELF phenotype also had significantly higher BMI, but did not differ in respect of other demographic characteristics such as age or gender.

CONCLUSIONS

We provide the first evidence that the ELF lipidome varies significantly between healthy individuals and propose that such differences are related to weight status, highlighting the potential impact of (over)nutrition on lung lipid metabolism.

Epithelial IL-6 trans-signaling defines a new asthma phenotype with increased airway inflammation

BACKGROUND

Although several studies link high levels of IL-6 and soluble IL-6 receptor (sIL-6R) to asthma severity and decreased lung function, the role of IL-6 trans-signaling (IL-6TS) in asthmatic patients is unclear.

OBJECTIVE

We sought to explore the association between epithelial IL-6TS pathway activation and molecular and clinical phenotypes in asthmatic patients.

METHODS

An IL-6TS gene signature obtained from air-liquid interface cultures of human bronchial epithelial cells stimulated with IL-6 and sIL-6R was used to stratify lung epithelial transcriptomic data (Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes [U-BIOPRED] cohorts) by means of hierarchical clustering. IL-6TS-specific protein markers were used to stratify sputum biomarker data (Wessex cohort). Molecular phenotyping was based on transcriptional profiling of epithelial brushings, pathway analysis, and immunohistochemical analysis of bronchial biopsy specimens.

RESULTS

Activation of IL-6TS in air-liquid interface cultures reduced epithelial integrity and induced a specific gene signature enriched in genes associated with airway remodeling. The IL-6TS signature identified a subset of patients with IL-6TS-high asthma with increased epithelial expression of IL-6TS-inducible genes in the absence of systemic inflammation. The IL-6TS-high subset had an overrepresentation of frequent exacerbators, blood eosinophilia, and submucosal infiltration of T cells and macrophages. In bronchial brushings Toll-like receptor pathway genes were upregulated, whereas expression of cell junction genes was reduced. Sputum sIL-6R and IL-6 levels correlated with sputum markers of remodeling and innate immune activation, in particular YKL-40, matrix metalloproteinase 3, macrophage inflammatory protein 1β, IL-8, and IL-1β.

CONCLUSIONS

Local lung epithelial IL-6TS activation in the absence of type 2 airway inflammation defines a novel subset of asthmatic patients and might drive airway inflammation and epithelial dysfunction in these patients.

The use of pharmacogenomics, epigenomics, and transcriptomics to improve childhood asthma management: Where do we stand?

Asthma is a complex multifactorial disease and it is the most common chronic disease in children. There is a high variability in response to asthma treatment, even in patients with good adherence to maintenance treatment, and a correct inhalation technique. Distinct underlying disease mechanisms in childhood asthma might be the reason of this heterogeneity. A deeper knowledge of the underlying molecular mechanisms of asthma has led to the recent development of advanced and mechanism-based treatments such as biologicals. However, biologicals are recommended only for patients with specific asthma phenotypes who remain uncontrolled despite high dosages of conventional asthma treatment. One of the main unmet needs in their application is lack of clinically available biomarkers to individualize pediatric asthma management and guide treatment. Pharmacogenomics, epigenomics, and transcriptomics are three omics fields that are rapidly advancing and can provide tools to identify novel asthma mechanisms and biomarkers to guide treatment. Pharmacogenomics focuses on variants in the DNA, epigenomics studies heritable changes that do not involve changes in the DNA sequence but lead to alteration of gene expression, and transcriptomics investigates gene expression by studying the complete set of mRNA transcripts in a cell or a population of cells. Advances in high-throughput technologies and statistical tools together with well-phenotyped patient inclusion and collaborations between different centers will expand our knowledge of underlying molecular mechanisms involved in disease onset and progress. Furthermore, it could help to select and stratify appropriate therapeutic strategies for subgroups of patients and hopefully bring precision medicine to daily practice.

A computational framework for complex disease stratification from multiple large-scale datasets

BACKGROUND

Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states.

METHODS

The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification.

RESULTS

We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-'omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes.

CONCLUSIONS

This framework will help health researchers plan and perform multi-'omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine.

Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome

Analysis of induced sputum supernatant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (unbiased biomarkers predictive of respiratory disease outcomes) international project. We present practical and analytical techniques to optimize the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMS^E applied to 40 healthy nonsmoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The "core" sputum proteome (proteins detected in ≥40% of participants) was composed of 284 proteins, and the extended proteome (proteins detected in ≥3 participants) contained 1666 proteins. Quality control procedures were developed to optimize the accuracy and consistency of measurement of sputum proteins and analyze the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMS^E is influenced by several factors, with some proteins being measured in all participants' samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high interindividual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitization. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance.

Sputum proteomics and airway cell transcripts of current and ex-smokers with severe asthma in U-BIOPRED: an exploratory analysis

Severe asthma patients with a significant smoking history have airflow obstruction with reported neutrophilia. We hypothesise that multi-omic analysis will enable the definition of smoking and ex-smoking severe asthma molecular phenotypes.The U-BIOPRED cohort of severe asthma patients, containing current-smokers (CSA), ex-smokers (ESA), nonsmokers and healthy nonsmokers was examined. Blood and sputum cell counts, fractional exhaled nitric oxide and spirometry were obtained. Exploratory proteomic analysis of sputum supernatants and transcriptomic analysis of bronchial brushings, biopsies and sputum cells was performed.Colony-stimulating factor (CSF)2 protein levels were increased in CSA sputum supernatants, with azurocidin 1, neutrophil elastase and CXCL8 upregulated in ESA. Phagocytosis and innate immune pathways were associated with neutrophilic inflammation in ESA. Gene set variation analysis of bronchial epithelial cell transcriptome from CSA showed enrichment of xenobiotic metabolism, oxidative stress and endoplasmic reticulum stress compared to other groups. CXCL5 and matrix metallopeptidase 12 genes were upregulated in ESA and the epithelial protective genes, mucin 2 and cystatin SN, were downregulated.Despite little difference in clinical characteristics, CSA were distinguishable from ESA subjects at the sputum proteomic level, with CSA patients having increased CSF2 expression and ESA patients showing sustained loss of epithelial barrier processes.

Blood biomarkers in chronic airways diseases and their role in diagnosis and management

INTRODUCTION

The complexity and heterogeneous nature of asthma and chronic obstructive pulmonary disease (COPD) results in difficulties in diagnosing and treating patients. Biomarkers that can identify underlying mechanisms, identify patient phenotypes and to predict treatment response could be of great value for adequate treatment. Areas covered: Biomarkers play an important role for the development of novel targeted therapies in airways disease. Blood biomarkers are relatively non-invasive, easy to obtain and easy to apply in routine care. Several blood biomarkers are being used to diagnose and monitor chronic airways diseases, as well as to predict response to treatment and long-term prognosis. Blood eosinophils are the best studied biomarker, the most applied in clinical practice, and until now the most promising of all blood biomarkers. Other blood biomarkers, including serum periostin, IgE and ECP and plasma fibrinogen are less studied and less relevant in clinical practice. Recent developments include the use of antibody assays of many different cytokines at the same time, and 'omics' techniques and systems medicine. Expert commentary: With the exception of blood eosinophils, the use of blood biomarkers in asthma and COPD has been rather disappointing. Future research using new technologies like big-data analysis of blood samples from real-life patient cohorts will probably gain better insight into underlying mechanisms of different disease phenotypes. Identification of specific molecular pathways and associated biomarkers will then allow the development of new targets for precision medicine.

Exacerbations in Adults with Asthma: A Systematic Review and External Validation of Prediction Models

BACKGROUND

Several prediction models assessing future risk of exacerbations in adult patients with asthma have been published. Applicability of these models is uncertain because their predictive performance has often not been assessed beyond the population in which they were derived.

OBJECTIVE

This study aimed to identify and critically appraise prediction models for asthma exacerbations and validate them in 2 clinically distinct populations.

METHODS

PubMed and EMBASE were searched to April 2017 for reports describing adult asthma populations in which multivariable models were constructed to predict exacerbations during any time frame. After critical appraisal, the models' predictive performances were assessed in a primary and a secondary care population for author-defined exacerbations and for American Thoracic Society/European Respiratory Society-defined severe exacerbations.

RESULTS

We found 12 reports from which 24 prediction models were evaluated. Three predictors (previous health care utilization, symptoms, and spirometry values) were retained in most models. Assessment was hampered by suboptimal methodology and reporting, and by differences in exacerbation outcomes. Discrimination (area under the receiver-operating characteristic curve [c-statistic]) of models for author-defined exacerbations was better in the primary care population (mean, 0.71) than in the secondary care population (mean, 0.60) and similar (0.65 and 0.62, respectively) for American Thoracic Society/European Respiratory Society-defined severe exacerbations. Model calibration was generally poor, but consistent between the 2 populations.

CONCLUSIONS

The preservation of 3 predictors in models derived from variable populations and the fairly consistent predictive properties of most models in 2 distinct validation populations suggest the feasibility of a generalizable model predicting severe exacerbations. Nevertheless, improvement of the models is warranted because predictive performances are below the desired level.

Clinical and inflammatory phenotyping by breathomics in chronic airway diseases irrespective of the diagnostic label

Asthma and chronic obstructive pulmonary disease (COPD) are complex and overlapping diseases that include inflammatory phenotypes. Novel anti-eosinophilic/anti-neutrophilic strategies demand rapid inflammatory phenotyping, which might be accessible from exhaled breath.Our objective was to capture clinical/inflammatory phenotypes in patients with chronic airway disease using an electronic nose (eNose) in a training and validation set.This was a multicentre cross-sectional study in which exhaled breath from asthma and COPD patients (n=435; training n=321 and validation n=114) was analysed using eNose technology. Data analysis involved signal processing and statistics based on principal component analysis followed by unsupervised cluster analysis and supervised linear regression.Clustering based on eNose resulted in five significant combined asthma and COPD clusters that differed regarding ethnicity (p=0.01), systemic eosinophilia (p=0.02) and neutrophilia (p=0.03), body mass index (p=0.04), exhaled nitric oxide fraction (p<0.01), atopy (p<0.01) and exacerbation rate (p<0.01). Significant regression models were found for the prediction of eosinophilic (R²=0.581) and neutrophilic (R²=0.409) blood counts based on eNose. Similar clusters and regression results were obtained in the validation set.Phenotyping a combined sample of asthma and COPD patients using eNose provides validated clusters that are not determined by diagnosis, but rather by clinical/inflammatory characteristics. eNose identified systemic neutrophilia and/or eosinophilia in a dose-dependent manner.

Breathomics from exhaled volatile organic compounds in pediatric asthma

Asthma is the most common chronic disease in children, and is characterized by airway inflammation, bronchial hyperresponsiveness, and airflow obstruction. Asthma diagnosis, phenotyping, and monitoring are still challenging with currently available methods, such as spirometry, F_E NO or sputum analysis. The analysis of volatile organic compounds (VOCs) in exhaled breath could be an interesting non-invasive approach, but has not yet reached clinical practice. This review describes the current status of breath analysis in the diagnosis and monitoring of pediatric asthma. Furthermore, features of an ideal breath test, different breath analysis techniques, and important methodological issues are discussed. Although only a (small) number of studies have been performed in pediatric asthma, of which the majority is focusing on asthma diagnosis, these studies show moderate to good prediction accuracy (80-100%, with models including 6-28 VOCs), thereby qualifying breathomics for future application. However, standardization of procedures, longitudinal studies, as well as external validation are needed in order to further develop breathomics into clinical tools. Such a non-invasive tool may be the next step toward stratified and personalized medicine in pediatric respiratory disease.

Breath analysis by gas chromatography-mass spectrometry and electronic nose to screen for pleural mesothelioma: a cross-sectional case-control study

RATIONALE

Malignant pleural mesothelioma (MPM) is mainly caused by previous exposure to asbestos fibers and has a poor prognosis. Due to a long latency period between exposure and diagnosis, MPM incidence is expected to peak between 2020-2025. Screening of asbestos-exposed individuals is believed to improve early detection and hence, MPM management. Recent developments focus on breath analysis for screening since breath contains volatile organic compounds (VOCs) which reflect the cell's metabolism.

OBJECTIVES

The goal of this cross-sectional, case-control study is to identify VOCs in exhaled breath of MPM patients with gas chromatography-mass spectrometry (GC-MS) and to assess breath analysis to screen for MPM using an electronic nose (eNose).

METHODS

Breath and background samples were taken from 64 subjects: 16 healthy controls (HC), 19 asymptomatic former asbestos-exposed (AEx) individuals, 15 patients with benign asbestos-related diseases (ARD) and 14 MPM patients. Samples were analyzed with both GC-MS and eNose.

RESULTS

Using GC-MS, AEx individuals were discriminated from MPM patients with 97% accuracy, with diethyl ether, limonene, nonanal, methylcyclopentane and cyclohexane as important VOCs. This was validated by eNose analysis. MPM patients were discriminated from AEx+ARD participants by GC-MS and eNose with 94% and 74% accuracy, respectively. The sensitivity, specificity, positive and negative predictive values were 100%, 91%, 82%, 100% for GC-MS and 82%, 55%, 82%, 55% for eNose, respectively.

CONCLUSION

This study shows accurate discrimination of patients with MPM from asymptomatic asbestos-exposed persons at risk by GC-MS and eNose analysis of exhaled VOCs and provides proof-of-principle of breath analysis for MPM screening.

Proteomics in asthma: the clinicians were right after all, were not they?

Clinical disease phenotypes with underlying information of molecular and biological signatures for the same, is a prerequisite for improving medical care and developing more effective, stratified management strategies. This commentary reviews the research carried out by Cao et al. to unravel biological networks associated with different clinical categories of asthma. It finally comments on the utility of using data from multiple platforms aided by integrated systems approaches to effectively find out the obvious underlying physiological disease signatures related to clinical disease sub-types.

Precision medicine in airway diseases: moving to clinical practice

On February 21, 2017, a European Respiratory Society research seminar held in Barcelona discussed how to best apply precision medicine to chronic airway diseases such as asthma and chronic obstructive pulmonary disease. It is now clear that both are complex and heterogeneous diseases, that often overlap and that both require individualised assessment and treatment. This paper summarises the presentations and discussions that took place during the seminar. Specifically, we discussed the need for a new taxonomy of human diseases, the role of different players in this scenario (exposome, genes, endotypes, phenotypes, biomarkers and treatable traits) and a number of unanswered key questions in the field. We also addressed how to deploy airway precision medicine in clinical practice today, both in primary and specialised care. Finally, we debated the type of research needed to move the field forward.

Transcriptomic gene signatures associated with persistent airflow limitation in patients with severe asthma

A proportion of severe asthma patients suffers from persistent airflow limitation (PAL), often associated with more symptoms and exacerbations. Little is known about the underlying mechanisms. Here, our aim was to discover unexplored potential mechanisms using Gene Set Variation Analysis (GSVA), a sensitive technique that can detect underlying pathways in heterogeneous samples.Severe asthma patients from the U-BIOPRED cohort with PAL (post-bronchodilator forced expiratory volume in 1 s/forced vital capacity ratio below the lower limit of normal) were compared with those without PAL. Gene expression was assessed on the total RNA of sputum cells, nasal brushings, and endobronchial brushings and biopsies. GSVA was applied to identify differentially enriched predefined gene signatures based on all available gene expression publications and data on airways disease.Differentially enriched gene signatures were identified in nasal brushings (n=1), sputum (n=9), bronchial brushings (n=1) and bronchial biopsies (n=4) that were associated with response to inhaled steroids, eosinophils, interleukin-13, interferon-α, specific CD4⁺ T-cells and airway remodelling.PAL in severe asthma has distinguishable underlying gene networks that are associated with treatment, inflammatory pathways and airway remodelling. These findings point towards targets for the therapy of PAL in severe asthma.

Pulmonary challenge with carbon nanoparticles induces a dose-dependent increase in circulating leukocytes in healthy males

Background

Inhalation of particulate matter, as part of air pollution, is associated with increased morbidity and mortality. Nanoparticles (< 100 nm) are likely candidates for triggering inflammatory responses and activation of coagulation pathways because of their ability to enter lung cells and pass bronchial mucosa. We tested the hypothesis that bronchial segmental instillation of carbon nanoparticles causes inflammation and activation of coagulation pathways in healthy humans in vivo.

Methods

This was an investigator-initiated, randomized controlled, dose-escalation study in 26 healthy males. Participants received saline (control) in one lung segment and saline (placebo) or carbon nanoparticles 10 μg, 50 μg, or 100 μg in the contra-lateral lung. Six hours later, blood and bronchoalveolar lavage fluid (BALF) was collected for inflammation and coagulation parameters.

Results

There was a significant dose-dependent increase in blood neutrophils (p = 0.046) after challenge with carbon nanoparticles. The individual top-dose of 100 μg showed a significant (p = 0.05) increase in terms of percentage neutrophils in blood as compared to placebo.

Conclusions

This study shows a dose-dependent effect of bronchial segmental challenge with carbon nanoparticles on circulating neutrophils of healthy volunteers. This suggests that nanoparticles in the respiratory tract induce systemic inflammation.

Trial registration

Dutch Trial Register no. 2976. 11 July 2011. http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=2976

Electronic supplementary material

The online version of this article (10.1186/s12890-017-0463-x) contains supplementary material, which is available to authorized users.

A Transcriptome-driven Analysis of Epithelial Brushings and Bronchial Biopsies to Define Asthma Phenotypes in U-BIOPRED

RATIONALE

Asthma is a heterogeneous disease driven by diverse immunologic and inflammatory mechanisms.

OBJECTIVES

Using transcriptomic profiling of airway tissues, we sought to define the molecular phenotypes of severe asthma.

METHODS

The transcriptome derived from bronchial biopsies and epithelial brushings of 107 subjects with moderate to severe asthma were annotated by gene set variation analysis using 42 gene signatures relevant to asthma, inflammation, and immune function. Topological data analysis of clinical and histologic data was performed to derive clusters, and the nearest shrunken centroid algorithm was used for signature refinement.

MEASUREMENTS AND MAIN RESULTS

Nine gene set variation analysis signatures expressed in bronchial biopsies and airway epithelial brushings distinguished two distinct asthma subtypes associated with high expression of T-helper cell type 2 cytokines and lack of corticosteroid response (group 1 and group 3). Group 1 had the highest submucosal eosinophils, as well as high fractional exhaled nitric oxide levels, exacerbation rates, and oral corticosteroid use, whereas group 3 patients showed the highest levels of sputum eosinophils and had a high body mass index. In contrast, group 2 and group 4 patients had an 86% and 64% probability, respectively, of having noneosinophilic inflammation. Using machine learning tools, we describe an inference scheme using the currently available inflammatory biomarkers sputum eosinophilia and fractional exhaled nitric oxide levels, along with oral corticosteroid use, that could predict the subtypes of gene expression within bronchial biopsies and epithelial cells with good sensitivity and specificity.

CONCLUSIONS

This analysis demonstrates the usefulness of a transcriptomics-driven approach to phenotyping that segments patients who may benefit the most from specific agents that target T-helper cell type 2-mediated inflammation and/or corticosteroid insensitivity.

Emerging understanding of the mechanism of action of Bronchial Thermoplasty in asthma

Bronchial Thermoplasty (BT) is an endoscopic treatment for moderate-to-severe asthma patients who are uncontrolled despite optimal medical therapy. Effectiveness of BT has been demonstrated in several randomized clinical trials. However, the asthma phenotype that benefits most of this treatment is unclear, partly because the mechanism of action is incompletely understood. BT was designed to reduce the amount of airway smooth muscle (ASM), but additional direct and indirect effects on airway pathophysiology are expected. This review will provide an overview of the different components of airway pathophysiology including remodeling, with the ASM as the key player. Current concepts in the understanding of BT clinical effectiveness with a focus on its impact on airway remodeling will be reviewed.

Toll-like receptor 3 blockade in rhinovirus-induced experimental asthma exacerbations: A randomized controlled study

BACKGROUND

Human rhinoviruses (HRVs) commonly precipitate asthma exacerbations. Toll-like receptor 3, an innate pattern recognition receptor, is triggered by HRV, driving inflammation that can worsen asthma.

OBJECTIVE

We sought to evaluate an inhibitory mAb to Toll-like receptor 3, CNTO3157, on experimental HRV-16 inoculation in healthy subjects and asthmatic patients.

METHODS

In this double-blind, multicenter, randomized, parallel-group study in North America and Europe, healthy subjects and patients with mild-to-moderate stable asthma received single or multiple doses of CNTO3157 or placebo, respectively, and were then inoculated with HRV-16 within 72 hours. All subjects were monitored for respiratory symptoms, lung function, and nasal viral load. The primary end point was maximal decrease in FEV₁ during 10 days after inoculation.

RESULTS

In asthmatic patients (n = 63) CNTO3157 provided no protection against FEV₁ decrease (least squares mean: CNTO3157 [n = 30] = -7.08% [SE, 8.15%]; placebo [n = 25] = -5.98% [SE, 8.56%]) or symptoms after inoculation. In healthy subjects (n = 12) CNTO3157 versus placebo significantly attenuated upper (P = .03) and lower (P = .02) airway symptom scores, with area-under-the-curve increases of 9.1 (15.1) versus 34.9 (17.6) and 13.0 (18.4) versus 50.4 (25.9) for the CNTO3157 (n = 8) and placebo (n = 4) groups, respectively, after inoculation. All of the severe and 4 of the nonserious asthma exacerbations occurred while receiving CNTO3157.

CONCLUSION

In summary, CNTO3157 was ineffective in attenuating the effect of HRV-16 challenge on lung function, asthma control, and symptoms in asthmatic patients but suppressed cold symptoms in healthy subjects. Other approaches, including blockade of multiple pathways or antiviral agents, need to be sought for this high unmet medical need.