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Methods for breath sampling and analysis require robust quality assessment to minimise the risk of false discoveries. Planning large-scale multi-site breath metabolite profiling studies also requires careful consideration of systematic and random variation as a result of sampling and analysis techniques. In this study we use breath sample data from the recent U-BIOPRED cohort to evaluate and discuss some important methodological considerations such as batch variation and correction, variation between sites, storage and transportation, as well as inter-instrument analytical differences. Based on this we provide a summary of recommended best practices for new large scale multi-site studies.

Background: Post-repair atrial septal defects (ASD) patients are frequently discharged from follow-up, but the extent of pulmonary symptoms long-term post-repair is unknown., Methods and results: The national CONgenital CORvitia registry was linked to the national Drug Registry to investigate all ambulatory-dispensed pulmonary inhalants for 2006-2014. ASD patients were compared with age- and sex-matched referents from the general population. A total of 1,959 adult patients (age 42±17 years; 66% female; 1,223 [62%] repaired) were included. Compared with the referents, ASD patients had more inhalant use, even at long-term post-repair follow-up (OR=1.81 [95% CI 1.62-2.03]; P<0.001)., Conclusions: ASD patients had 2-fold higher inhalant use compared with referents even at long-term post-repair follow-up, suggesting persistent pulmonary functional impairment.

Oxidative stress is believed to be a major driver of inflammation in smoking asthmatics. The U-BIOPRED project recruited a cohort of Severe Asthma smokers/ex-smokers (SAs/ex) and non-smokers (SAn) with extensive clinical and biomarker information enabling characterization of these subjects. We investigated oxidative stress in severe asthma subjects by analysing urinary 8-iso-PGF2α and the mRNA-expression of the main pro-oxidant (NOX2; NOSs) and anti-oxidant (SODs; CAT; GPX1) enzymes in the airways of SAs/ex and SAn. All the severe asthma U-BIOPRED subjects were further divided into current smokers with severe asthma (CSA), ex-smokers with severe asthma (ESA) and non-smokers with severe asthma (NSA) to deepen the effect of active smoking. Clinical data, urine and sputum were obtained from severe asthma subjects. A bronchoscopy to obtain bronchial biopsy and brushing was performed in a subset of subjects. The main clinical data were analysed for each subset of subjects (urine-8-iso-PGF2α; IS-transcriptomics; BB-transcriptomics; BBr-transcriptomics). Urinary 8-iso-PGF2α was quantified using mass spectrometry. Sputum, bronchial biopsy and bronchial brushing were processed for mRNA expression microarray analysis. Urinary 8-iso-PGF2α was increased in SAs/ex, median (IQR) = 31.7 (24.5-44.7) ng/mmol creatinine, compared to SAn, median (IQR) = 26.6 (19.6-36.6) ng/mmol creatinine (p< 0.001), and in CSA, median (IQR) = 34.25 (24.4-47.7), vs. ESA, median (IQR) = 29.4 (22.3-40.5), and NSA, median (IQR) = 26.5 (19.6-16.6) ng/mmol creatinine (p = 0.004). Sputum mRNA expression of NOX2 was increased in SAs/ex compared to SAn (probe sets 203922&#95;PM&#95;s&#95;at fold-change = 1.05 p = 0.006; 203923&#95;PM&#95;s&#95;at fold-change = 1.06, p = 0.003; 233538&#95;PM&#95;s&#95;at fold-change = 1.06, p = 0.014). The mRNA expression of antioxidant enzymes were similar between the two severe asthma cohorts in all airway samples. NOS2 mRNA expression was decreased in bronchial brushing of SAs/ex compared to SAn (fold-change = -1.10; p = 0.029). NOS2 mRNA expression in bronchial brushing correlated with FeNO (Kendal's Tau = 0.535; p< 0.001). From clinical and inflammatory analysis, FeNO was lower in CSA than in ESA in all the analysed subject subsets (p< 0.01) indicating an effect of active smoking. Results about FeNO suggest its clinical limitation, as inflammation biomarker, in severe asthma active smokers. These data provide evidence of greater systemic oxidative stress in severe asthma smokers as reflected by a significant changes of NOX2 mRNA expression in the airways, together with elevated urinary 8-iso-PGF2α in the smokers/ex-smokers group. Trial registration ClinicalTrials.gov-Identifier: NCT01976767., Competing Interests: M. Caruso, R. Emma, A.T. Bansal, C.E. Wheelock, M.J. Loza, L. Fabbella, T. Sandstrom, F. Singer, A.R. Sousa, D.E. Shaw, R. Lutter, S.J. Fowler, I. Horvath, I. Pandis, P. Montuschi declare non conflict of interest. J. Kolmert, B. De Meulder, D. Lefaudeux, C. Auffray, P.J. Sterk, N. Krug, M. Sanak, J. Corfield declare grants from IMI (Innovative Medicine Initiatives) during the conduct of the study. S.E. Dahlen declares financial supporting by Swedish Research Academic Foundations, RSPS Incentive, AZ, Teva and GSK consultancies. B. Dahlen declares consultancies for TEVA. P. Chanez reports grants and personal fees from Almirall, BI, Centocor, GSK, MSD, AstraZeneca, Novartis, Teva, Chiesi, Schering Plough, outside the submitted work. P.S. Bakke reports personal fees from GlaxoSmithKline, Boehringer-Ingelheim, AstraZeneca, Orionpharma, Mundipharma, outside the submitted work. R. Djukanovic reports receiving fees for lectures at symposia organised by Novartis and TEVA and consultation for these two companies as member of advisory boards. He is a co-founder and current consultant, and has shares in Synairgen, a University of Southampton spin out company. P.H. Howarth reports fees from GSK, outside the submitted work. L. Fleming reports personal fees and other from Vectura, Novartis, Boehringer ingelheim, outside the submitted work. I. Adcock reports grants from EU-IMI, during the conduct of the study; grants from MRC, BHF, Dunhill Medical Trust, personal fees from Chiesi, GSK, Boehringer Ingelheim, outside the submitted work. K.F. Chung reports personal fees from Advisory Board membership, grants for research, and personal fees from payments for lectures, outside the submitted work. ATB is employed by Acclarogen Ltd., MJL by Janssen Research & Development, LLC., ARS by GSK and JC by Astra Zeneca R&D and Areteva R&D. There are no patents, products in development or marketed products to declare. This does not alter our adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors.

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.

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., (© 2018 Wiley Periodicals, Inc.)

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.

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.

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., Competing Interests: Conflict of interest: K. Takahashi received personal fees from Asahi General Hospital, during the conduct of the study. Conflict of interest: M. Loza is employed by and owns stock in Johnson & Johnson, the parent company of Janssen R&D. Conflict of interest: F. Baribaud is an employee and shareholder of Janssen R&D. Conflict of interest: P. Chanez has provided consultancy services for Boehringer Ingelheim, Johnson & Johnson, GlaxoSmithKline, Merck Sharp & Dohme, AstraZeneca, Novartis, Teva, Chiesi, Sanofi and SNCF; has served on advisory boards for Almirall, Boehringer Ingelheim, Johnson & Johnson, GlaxoSmithKline, AstraZeneca, Novartis, Teva, Chiesi and Sanofi; has received lecture fees from Boehringer Ingelheim, Centocor, GlaxoSmithKline, AstraZeneca, Novartis, Teva, Chiesi, Boston Scientific and ALK; and has received industry-sponsored grants from Roche, Boston Scientific, Boehringer Ingelheim, Centocor, GlaxoSmithKline, AstraZeneca, ALK, Novartis, Teva and Chiesi. Conflict of interest: I. Horvath has received personal fees from Astra Zeneca, Boehringer Ingelheim, Novartis, CSL, Chiesi, Roche, GSK, Berlin-Chemie and Sandoz, outside the submitted work. Conflict of interest: P. Montuschi reports personal fees from advisory board meetings with AstraZeneca, outside the submitted work. Conflict of interest: F. Singer has received personal fees and honoraria for speaking engagements from Vertex and Novartis, outside the submitted work. Conflict of interest: S-E. Dahlén has received research grants from several Swedish funding bodies such as MRC, Heart-Lung-Foundation and the Strategic Research Foundation, during the conduct of the study; and has received personal fees for advisory board meetings from GSK, AZ, Novartis, Teva, Regeneron/Sanofi, Merck and RSPR AB, grants on asthma phenotyping from AZ, and honoraria for speaking engagements from GSK and Teva, outside the submitted work. Conflict of interest: B. Dahlén has received personal fees from Teva (for advisory board membership) and AstraZeneca (payments for lectures), outside the submitted work. Conflict of interest: N. Krug reports grants from IMI (U-BIOPRED consortium IMI number 115010), during the conduct of the study. Conflict of interest: T. Sandström has received personal fees from advisory board meetings with pharmaceutical companies GSK, AZ, Novartis, Teva and Boehringer Ingelheim, and honoraria for speaking engagements for AZ, Novartis, Boehringer Ingelheim, outside the submitted work. Conflict of interest: D.E. Shaw has received personal fees for advisory board work from GSK, AZ, Teva and Boehringer Ingelheim, outside the submitted work. Conflict of interest: R. Lutter has received personal fees for advisory board meetings from GSK and Boehringer Ingelheim, and grants on asthma and COPD from GSK, Lung Foundation and MedImmune, outside the submitted work. Conflict of interest: P. Bakke has received personal fees for advisory board meetings from GSK, AZ, Novartis and Teva, and honoraria for speaking engagements from AZ and Boehringer Ingelheim, outside the submitted work. Conflict of interest: L.J. Fleming has received personal fees for advisory board meetings from Novartis, Vectura and Boehringer Ingelheim, grants from Asthma UK and BLF, and honoraria for speaking engagements for Novartis, outside the submitted work. Conflict of interest: P.H. Howarth was employed part time by GSK as Global Medical Expert. Conflict of interest: M. Caruso received grants (paid to institute) from the Innovative Medicines Initiative (IMI), during the conduct of the study. Conflict of interest: C. Auffray received grants from the Innovative Medicine Initiative (U-BIOPRED Consortium IMI number 115010 and eTRIKS Consortium IMI number 115446), during the conduct of the study. Conflict of interest: B. De Meulder received grants from the Innovative Medicine Initiative (U-BIOPRED Consortium IMI number 115010 and eTRIKS Consortium IMI number 115446), during the conduct of the study. Conflict of interest: D. Lefaudeux received grants from the Innovative Medicine Initiative (U-BIOPRED Consortium IMI number 115010 and eTRIKS Consortium IMI number 115446), during the conduct of the study. Conflict of interest: R. Djukanovic has received personal fees for lectures at company sponsored symposia and consulting in advisory boards from TEVA, grants (for an investigator led study of mechanisms of action of omalizumab) and personal fees (for lectures at company sponsored symposia and consulting in advisory boards) from Novartis, and is a consultant to, co-founder of, and holds shares in Synairgen, outside the submitted work. Conflict of interest: P.J. Sterk has received a public-private grant (paid to institute) from Innovative Medicines Initiative (IMI) covered by the European Union (EU) and the European Federation of Pharmaceutical Industries and Associations (EFPIA), during the conduct of the study. Conflict of interest: I.M. Adcock has received personal fees for advisory board meetings from GSK, AZ, Novartis, Boehringer Ingelheim and Vectura, grants on asthma and COPD from Pfizer, GSK, MRC, EU, BI and IMI, and honoraria for speaking engagements for AZ and BI, outside the submitted work. Conflict of interest: K.F. Chung has received personal fees for advisory board meetings from GSK, AZ, Novartis, Teva, Boehringer Ingelheim and J&J, grants on asthma and COPD from Pfizer, GSK, MRC, EU IMI and NIH, and honoraria for speaking engagements for AZ and Merck, outside the submitted work., (Copyright ©ERS 2018.)

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.

Purpose of Review: Asthma features a high degree of heterogeneity in both pathophysiology and therapeutic response, resulting in many asthma patients being treated inadequately. Biomarkers indicative of underlying pathological processes could be used to identify disease subtypes, determine prognosis and to predict or monitor treatment response. However, the newly identified as well as more established biomarkers have different applications and limitations., Recent Findings: Conventional markers for type 2-high asthma, such as blood eosinophils, fraction of exhaled nitric oxide, serum IgE and periostin, feature limited sensitivity and specificity despite their significant correlations. More distinctive models have been developed by combining biomarkers and/or using omics techniques. Recently, a model with a positive predictive value of 100% for identification of type 2-high asthma based on a combination of minimally invasive biomarkers was developed., Summary: Individualisation of asthma treatment regimens on the basis of biomarkers is necessary to improve asthma control. However, the suboptimal properties of currently available conventional biomarkers limit its clinical utility. Newly identified biomarkers and models based on combinations and/or omics analysis must be validated and standardised before they can be routinely applied in clinical practice. The development of robust biomarkers will allow development of more efficacious precision medicine-based treatment approaches for asthma.

Background: Adult-onset severe asthma is characterized by highly symptomatic disease despite high-intensity asthma treatments. Understanding of the underlying pathways of this heterogeneous disease is needed for the development of targeted treatments. Gene set variation analysis is a statistical technique used to identify gene profiles in heterogeneous samples., Objective: We sought to identify gene profiles associated with adult-onset severe asthma., Methods: This was a cross-sectional, observational study in which adult patients with adult-onset of asthma (defined as starting at age ≥18 years) as compared with childhood-onset severe asthma (<18 years) were selected from the U-BIOPRED cohort. Gene expression was assessed on the total RNA of induced sputum (n = 83), nasal brushings (n = 41), and endobronchial brushings (n = 65) and biopsies (n = 47) (Affymetrix HT HG-U133+ PM). Gene set variation analysis was used to identify differentially enriched predefined gene signatures of leukocyte lineage, inflammatory and induced lung injury pathways., Results: Significant differentially enriched gene signatures in patients with adult-onset as compared with childhood-onset severe asthma were identified in nasal brushings (5 signatures), sputum (3 signatures), and endobronchial brushings (6 signatures). Signatures associated with eosinophilic airway inflammation, mast cells, and group 3 innate lymphoid cells were more enriched in adult-onset severe asthma, whereas signatures associated with induced lung injury were less enriched in adult-onset severe asthma., Conclusions: Adult-onset severe asthma is characterized by inflammatory pathways involving eosinophils, mast cells, and group 3 innate lymphoid cells. These pathways could represent useful targets for the treatment of adult-onset severe asthma., (Copyright © 2017. Published by Elsevier Inc.)

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 FEV 1 during 10 days after inoculation., Results: In asthmatic patients (n = 63) CNTO3157 provided no protection against FEV 1 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., (Copyright © 2017 American Academy of Allergy, Asthma & Immunology. All rights reserved.)

Background: Sputum analysis in asthmatic patients is used to define airway inflammatory processes and might guide therapy., Objective: We sought to determine differential gene and protein expression in sputum samples from patients with severe asthma (SA) compared with nonsmoking patients with mild/moderate asthma., Methods: Induced sputum was obtained from nonsmoking patients with SA, smokers/ex-smokers with severe asthma, nonsmoking patients with mild/moderate asthma (MMAs), and healthy nonsmoking control subjects. Differential cell counts, microarray analysis of cell pellets, and SOMAscan analysis of sputum analytes were performed. CRID3 was used to inhibit the inflammasome in a mouse model of SA., Results: Eosinophilic and mixed neutrophilic/eosinophilic inflammation were more prevalent in patients with SA compared with MMAs. Forty-two genes probes were upregulated (>2-fold) in nonsmoking patients with severe asthma compared with MMAs, including IL-1 receptor (IL-1R) family and nucleotide-binding oligomerization domain, leucine-rich repeat and pyrin domain containing 3 (NRLP3) inflammasome members (false discovery rate < 0.05). The inflammasome proteins nucleotide-binding oligomerization domain, leucine rich repeat and pyrin domain containing 1 (NLRP1), NLRP3, and nucleotide-binding oligomerization domain (NOD)-like receptor C4 (NLRC4) were associated with neutrophilic asthma and with sputum IL-1β protein levels, whereas eosinophilic asthma was associated with an IL-13-induced T H 2 signature and IL-1 receptor-like 1 (IL1RL1) mRNA expression. These differences were sputum specific because no activation of NLRP3 or enrichment of IL-1R family genes in bronchial brushings or biopsy specimens in patients with SA was observed. Expression of NLRP3 and of the IL-1R family genes was validated in the Airway Disease Endotyping for Personalized Therapeutics cohort. Inflammasome inhibition using CRID3 prevented airway hyperresponsiveness and airway inflammation (both neutrophilia and eosinophilia) in a mouse model of severe allergic asthma., Conclusion: IL1RL1 gene expression is associated with eosinophilic SA, whereas NLRP3 inflammasome expression is highest in patients with neutrophilic SA. T H 2-driven eosinophilic inflammation and neutrophil-associated inflammasome activation might represent interacting pathways in patients with SA., (Copyright © 2017. Published by Elsevier Inc.)

Volatile organic compounds (VOCs) in exhaled breath may identify the presence of invasive pulmonary aspergillosis. We aimed to detect VOC profiles emitted by in vitro cultured, clinical Aspergillus isolates using gas chromatography-mass spectrometry (GC-MS). Three clinical Aspergillus isolates and a reference strain were cultured while conidiation was prevented. Headspace samples were analyzed using a standardized method. Breath samples of patients from which the cultures were obtained were checked for the presence of the VOCs found in vitro. Each Aspergillus isolate produced a distinct VOC profile. These profiles could not be confirmed in exhaled breath in vivo., (© The Author 2017. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

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 (R 2 =0.581) and neutrophilic (R 2 =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., Competing Interests: Conflict of interest: Disclosures can be found alongside this article at erj.ersjournals.com, (Copyright ©ERS 2018.)

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., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

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., (© 2017 Wiley Periodicals, Inc.)

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., Competing Interests: Conflict of interest: Disclosures can be found alongside this article at erj.ersjournals.com, (Copyright ©ERS 2017.)

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 ., Competing Interests: CONFLICTS OF INTEREST None of the authors declare to have conflicts of interest. This study was presented at the ERS International Congress, 3-7 September 2016, London, UK.

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., Competing Interests: Conflict of interest: Disclosures can be found alongside this article at erj.ersjournals.com, (Copyright ©ERS 2017.)

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.

Rationale: Ventilator-associated pneumonia (VAP) is the most common nosocomial infections in patients admitted to the ICU. The adapted island model predicts several changes in the respiratory microbiome during intubation and mechanical ventilation., Objectives: We hypothesised that mechanical ventilation and antibiotic administration decrease the diversity of the respiratory microbiome and that these changes are more profound in patients who develop VAP., Methods: Intubated and mechanically ventilated ICU-patients were included. Tracheal aspirates were obtained three times a week. 16S rRNA gene sequencing with the Roche 454 platform was used to measure the composition of the respiratory microbiome. Associations were tested with linear mixed model analysis and principal coordinate analysis., Measurements and Main Results: 111 tracheal aspirates were obtained from 35 patients; 11 had VAP, 18 did not have VAP. Six additional patients developed pneumonia within the first 48 hours after intubation. Duration of mechanical ventilation was associated with a decrease in α diversity (Shannon index; fixed-effect regression coefficient (β): -0.03 (95% CI -0.05 to -0.005)), but the administration of antibiotic therapy was not (fixed-effect β: 0.06; 95% CI -0.17 to 0.30). There was a significant difference in change of β diversity between patients who developed VAP and control patients for Bray-Curtis distances (p=0.03) and for Manhattan distances (p=0.04). Burkholderia, Bacillales and, to a lesser extent, Pseudomonadales positively correlated with the change in β diversity., Conclusion: Mechanical ventilation, but not antibiotic administration, was associated with changes in the respiratory microbiome. Dysbiosis of microbial communities in the respiratory tract was most profound in patients who developed VAP., Competing Interests: Competing interests: None declared., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)

Background: Assessing future risk of exacerbations is an important component of asthma management. Existing studies have investigated short- but not long-term risk. Problematic asthma patients with unfavorable long-term disease trajectory and persistently frequent severe exacerbations need to be identified early to guide treatment., Aim: To identify distinct trajectories of severe exacerbation rates among "problematic asthma" patients and develop a risk score to predict the most unfavorable trajectory., Methods: Severe exacerbation rates over five years for 177 "problematic asthma" patients presenting to a specialist asthma clinic were tracked. Distinct trajectories of severe exacerbation rates were identified using group-based trajectory modeling. Baseline predictors of trajectory were identified and used to develop a clinical risk score for predicting the most unfavorable trajectory., Results: Three distinct trajectories were found: 58.5% had rare intermittent severe exacerbations ("infrequent"), 32.0% had frequent severe exacerbations at baseline but improved subsequently ("nonpersistently frequent"), and 9.5% exhibited persistently frequent severe exacerbations, with the highest incidence of near-fatal asthma ("persistently frequent"). A clinical risk score composed of ≥2 severe exacerbations in the past year (+2 points), history of near-fatal asthma (+1 point), body mass index ≥25kg/m 2 (+1 point), obstructive sleep apnea (+1 point), gastroesophageal reflux (+1 point), and depression (+1 point) was predictive of the "persistently frequent" trajectory (area under the receiver operating characteristic curve: 0.84, sensitivity 72.2%, specificity 81.1% using cutoff ≥3 points). The trajectories and clinical risk score had excellent performance in an independent validation cohort., Conclusions: Patients with problematic asthma follow distinct illness trajectories over a period of five years. We have derived and validated a clinical risk score that accurately identifies patients who will have persistently frequent severe exacerbations in the future., (© 2017 The Authors. Allergy Published by John Wiley & Sons Ltd.)

Background: Asthma is a chronic inflammatory airway disease, associated with episodes of exacerbations. Therapy with inhaled corticosteroids (ICS) targets airway inflammation, which aims to maintain and restore asthma control. Clinical features are only modestly associated with airways inflammation. Therefore, we hypothesized that exhaled volatile metabolites identify longitudinal changes between clinically stable episodes and loss of asthma control., Objectives: To determine whether exhaled volatile organic compounds (VOCs) as measured by gas-chromatography/mass-spectrometry (GC/MS) and electronic nose (eNose) technology discriminate between clinically stable and unstable episodes of asthma., Methods: Twenty-three patients with (partly) controlled mild to moderate persistent asthma using ICS were included in this prospective steroid withdrawal study. Exhaled metabolites were measured at baseline, during loss of control and after recovery. Standardized sampling of exhaled air was performed, after which samples were analysed by GC/MS and eNose. Univariate analysis of covariance (ANCOVA), followed by multivariate principal component analysis (PCA) was used to reduce data dimensionality. Next paired t tests were utilized to analyse within-subject breath profile differences at the different time-points. Finally, associations between exhaled metabolites and sputum inflammation markers were examined., Results: Breath profiles by eNose showed 95% (21/22) correct classification for baseline vs loss of control and 86% (19/22) for loss of control vs recovery. Breath profiles using GC/MS showed accuracies of 68% (14/22) and 77% (17/22) for baseline vs loss of control and loss of control vs recovery, respectively. Significant associations between exhaled metabolites captured by GC/MS and sputum eosinophils were found (Pearson r≥.46, P<.01)., Conclusions & Clinical Relevance: Loss of asthma control can be discriminated from clinically stable episodes by longitudinal monitoring of exhaled metabolites measured by GC/MS and particularly eNose. Part of the uncovered biomarkers was associated with sputum eosinophils. These findings provide proof of principle for monitoring and identification of loss of asthma control by breathomics., (© 2017 John Wiley & Sons Ltd.)

Background: Antibiotics do not reduce mortality or short-term treatment non-response in patients receiving treatment for acute exacerbations of COPD in an outpatient setting. However, the long-term effects of antibiotics are unknown. The aim of this study was to investigate if the antibiotic doxycycline added to the oral corticosteroid prednisolone prolongs time to next exacerbation in patients with COPD receiving treatment for an exacerbation in the outpatient setting., Methods: In this randomised double-blind placebo-controlled trial, we recruited a cohort of patients with COPD from outpatient clinics of nine teaching hospitals and three primary care centres in the Netherlands. Inclusion criteria were an age of at least 45 years, a smoking history of at least 10 pack-years, mild-to-severe COPD (Global Initiative of Chronic Obstructive Lung Disease [GOLD] stage 1-3), and at least one exacerbation during the past 3 years. Exclusion criteria were poor mastery of the Dutch language, poor cognitive functioning, known allergy to doxycycline, pregnancy, and a life expectancy of shorter than 1 month. If a participant had an exacerbation, we randomly assigned them (1:1; with permuted blocks of variable sizes [ranging from two to ten]; stratified by GOLD stage 1-2 vs 3) to a 7 day course of oral doxycycline 100 mg daily (200 mg on the first day) or placebo. Exclusion criteria for randomisation were fever, admission to hospital, and current use of antibiotics or use within the previous 3 weeks. Patients in both groups received a 10 day course of 30 mg oral prednisolone daily. Patients, investigators, and those assessing outcomes were masked to treatment assignment. The primary outcome was time to next exacerbation in all randomly allocated patients except for those incorrectly randomly allocated who did not meet the inclusion criteria or met the exclusion criteria. This trial is registered with the Netherlands Trial Register, number NTR2499., Findings: Between Dec 22, 2010, and Aug 6, 2013, we randomly allocated 305 (34%) patients from the cohort of 887 patients to doxycycline (152 [50%]) or placebo (153 [50%]), excluding four (1%) patients (two [1%] from each group) who were incorrectly randomly allocated from the analysis. 257 (85%) of 301 patients had a next exacerbation (131 [87%] of 150 in the doxycycline group vs 126 [83%] of 151 in the placebo group). Median time to next exacerbation was 148 days (95% CI 95-200) in the doxycycline group compared with 161 days (118-211) in the placebo group (hazard ratio 1·01 [95% CI 0·79-1·31]; p=0·91). We did not note any significant differences between groups in the frequency of adverse events during the first 2 weeks after randomisation (47 [31%] of 150 in the doxycycline group vs 53 [35%] of 151 in the placebo group; p=0·54) or in serious adverse events during the 2 years of follow-up (42 [28%] vs 43 [29%]; p=1)., Interpretation: In patients with mild-to-severe COPD receiving treatment for an exacerbation in an outpatient setting, the antibiotic doxycycline added to the oral corticosteroid prednisolone did not prolong time to next exacerbation compared with prednisolone alone. These findings do not support prescription of antibiotics for COPD exacerbations in an outpatient setting., Funding: Netherlands Organization for Health Research and Development., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Background: Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided., Objectives: We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum., Methods: Partition-around-medoids clustering was applied to a training set of 266 asthmatic participants from the European Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes (U-BIOPRED) adult cohort using 8 prespecified clinic-physiologic variables. This was repeated in a separate validation set of 152 asthmatic patients. The clusters were compared based on sputum proteomics and transcriptomics data., Results: Four reproducible and stable clusters of asthmatic patients were identified. The training set cluster T1 consists of patients with well-controlled moderate-to-severe asthma, whereas cluster T2 is a group of patients with late-onset severe asthma with a history of smoking and chronic airflow obstruction. Cluster T3 is similar to cluster T2 in terms of chronic airflow obstruction but is composed of nonsmokers. Cluster T4 is predominantly composed of obese female patients with uncontrolled severe asthma with increased exacerbations but with normal lung function. The validation set exhibited similar clusters, demonstrating reproducibility of the classification. There were significant differences in sputum proteomics and transcriptomics between the clusters. The severe asthma clusters (T2, T3, and T4) had higher sputum eosinophilia than cluster T1, with no differences in sputum neutrophil counts and exhaled nitric oxide and serum IgE levels., Conclusion: Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways., (Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

Rationale: Stratification of asthma at the molecular level, especially using accessible biospecimens, could greatly enable patient selection for targeted therapy., Objectives: To determine the value of blood analysis to identify transcriptional differences between clinically defined asthma and nonasthma groups, identify potential patient subgroups based on gene expression, and explore biological pathways associated with identified differences., Methods: Transcriptomic profiles were generated by microarray analysis of blood from 610 patients with asthma and control participants in the U-BIOPRED (Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes) study. Differentially expressed genes (DEGs) were identified by analysis of variance, including covariates for RNA quality, sex, and clinical site, and Ingenuity Pathway Analysis was applied. Patient subgroups based on DEGs were created by hierarchical clustering and topological data analysis., Measurements and Main Results: A total of 1,693 genes were differentially expressed between patients with severe asthma and participants without asthma. The differences from participants without asthma in the nonsmoking severe asthma and mild/moderate asthma subgroups were significantly related (r = 0.76), with a larger effect size in the severe asthma group. The majority of, but not all, differences were explained by differences in circulating immune cell populations. Pathway analysis showed an increase in chemotaxis, migration, and myeloid cell trafficking in patients with severe asthma, decreased B-lymphocyte development and hematopoietic progenitor cells, and lymphoid organ hypoplasia. Cluster analysis of DEGs led to the creation of subgroups among the patients with severe asthma who differed in molecular responses to oral corticosteroids., Conclusions: Blood gene expression differences between clinically defined subgroups of patients with asthma and individuals without asthma, as well as subgroups of patients with severe asthma defined by transcript profiles, show the value of blood analysis in stratifying patients with asthma and identifying molecular pathways for further study. Clinical trial registered with www.clinicaltrials.gov (NCT01982162).

Background: Acute worsening of asthma symptoms (exacerbation) is predominantly triggered by respiratory viruses, with influenza causing the most severe exacerbations. The lack of an adequate animal model hampers mechanistic insight and the development of new therapeutics., Aim: We developed and characterized a robust, consistent, and reproducible mouse model of severe exacerbation of chronic allergic asthma., Methods: Chronic allergic airway inflammation was induced following a house dust mite (HDM) sensitization protocol. HDM-sensitized mice and controls were infected with influenza virus A/X31 H3N2 and either or not treated with inhaled fluticasone propionate (FP), systemic corticosteroids (Pred), or anti-IL-5. Mice were killed at different time points after infection: Cellular accumulation and cytokines levels in the airways, PenH as a measure of airway hyper-responsiveness (AHR), and lung histology and viral replication were assessed., Results: Infection with low-dose A/X31 H3N2 led to prolonged deterioration of lung function, aggravated mucus production, peri-vascular, peri-bronchial, and allergic inflammation that was unresponsive to inhaled corticosteroids, but responsive to systemic corticosteroids. The exacerbation was preceded at 14 h after virus exposure by a marked innate, but no Th2 and Th1 response subsequently followed by enhanced numbers of eosinophils, neutrophils, dendritic, and T cells into the lung lumen, parenchyma, and draining lymph nodes in HDM-sensitized mice. Anti-IL-5 treatment attenuated eosinophils and prevented the X31-induced exacerbation., Conclusions: Together, these findings indicate that an early innate response that involves eosinophils underlies the exacerbation. This model recapitulates all major features of severe asthma exacerbations and can serve to discern driving mechanisms and promote the development of novel therapeutics., (© 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

This international task force report updates general considerations for bronchial challenge testing and the performance of the methacholine challenge test. There are notable changes from prior recommendations in order to accommodate newer delivery devices. Rather than basing the test result upon a methacholine concentration (provocative concentration (PC 20 ) causing a 20% fall in forced expiratory volume in 1 s (FEV 1 )), the new recommendations base the result upon the delivered dose of methacholine causing a 20% fall in FEV 1 (provocative dose (PD 20 )). This end-point allows comparable results from different devices or protocols, thus any suitable nebuliser or dosimeter may be used, so long as the delivery characteristics are known. Inhalation may be by tidal breathing using a breath-actuated or continuous nebuliser for 1 min (or more), or by a dosimeter with a suitable breath count. Tests requiring maximal inhalations to total lung capacity are not recommended because the bronchoprotective effect of a deep breath reduces the sensitivity of the test., Competing Interests: Conflict of interest: Disclosures can be found alongside this article at erj.ersjournals.com, (Copyright ©ERS 2017.)

Breath tests cover the fraction of nitric oxide in expired gas ( F eNO ), volatile organic compounds (VOCs), variables in exhaled breath condensate (EBC) and other measurements. For EBC and for F eNO , official recommendations for standardised procedures are more than 10 years old and there is none for exhaled VOCs and particles. The aim of this document is to provide technical standards and recommendations for sample collection and analytic approaches and to highlight future research priorities in the field. For EBC and F eNO , new developments and advances in technology have been evaluated in the current document. This report is not intended to provide clinical guidance on disease diagnosis and management.Clinicians and researchers with expertise in exhaled biomarkers were invited to participate. Published studies regarding methodology of breath tests were selected, discussed and evaluated in a consensus-based manner by the Task Force members.Recommendations for standardisation of sampling, analysing and reporting of data and suggestions for research to cover gaps in the evidence have been created and summarised.Application of breath biomarker measurement in a standardised manner will provide comparable results, thereby facilitating the potential use of these biomarkers in clinical practice., Competing Interests: Conflict of interest: T. Tonia acts as a methodologist for the European Respiratory Society. Further disclosures can be found alongside this article at erj.ersjournals.com, (Copyright ©ERS 2017.)

Continuous glucose monitoring (CGM) can be beneficial in critically ill patients. Current CGM devices rely on subcutaneous or blood plasma glucose measurements and consequently there is an increased risk of infections and the possibility of loss of blood with each measurement. A potential method to continuously and non-invasively measure blood glucose levels is using exhaled breath. A correlation between blood glucose levels and volatile organic compounds (VOCs) in the exhaled breath was already reported. VOCs can be analyzed continuously using a so-called electronic nose (eNose). We hypothesize that continuous exhaled breath analysis using an eNose can be used to accurately predict blood glucose levels in intubated, mechanically ventilated ICU-patients. Mechanically ventilated patients whose blood glucose concentration was monitored with a CGM device were eligible. An eNose with four metal oxide sensors was used to continuously measure changes in exhaled breath. After pre-processing the data, several regression models were trained, consisting of: (1) only eNose sensor values; (2) only the 1st and 2nd principal components (PC) of eNose values; (3) eNose sensor values and last known blood glucose value as random effect; (4) 1st and 2nd PC of eNose sensor values and CGM value of one minute ago as fixed effect; (5) CGM value of one minute ago as fixed effect. Model performance was measured using the R 2 value, the akaike information criterion and the Clarke error grid. Twenty-three patients were included in the study and 1165 hours of measurements were collected. Performance was low in models 1, 2 and 3 with a mean R 2 of 0.07 [95%-CI: 0.00-0.28], 0.10 [95%-CI: 0.00-0.40] and 0.30 [0.02-0.79], respectively. Performance in models 4 and 5 was better with a mean R 2 of 0.77 [0.02-1.00]. Subsequently, eNose data in model 4 had no added value over using CGM only in model 5. Continuous exhaled breath analysis using this eNose cannot be used to accurately predict blood glucose levels in intubated, mechanically ventilated ICU-patients.

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.

Patients with difficult-to-manage asthma represent a heterogeneous subgroup of asthma patients who require extensive assessment and tailored management. The International Primary Care Respiratory Group approach emphasises the importance of differentiating patients with asthma that is difficult to manage from those with severe disease. Local adaptation of this approach, however, is required to ensure an appropriate strategy for implementation in the Dutch context. We used a modified three-round e-Delphi approach to assess the opinion of all relevant stakeholders (general practitioners, pulmonologists, practice nurses, pulmonary nurses and people with asthma). In the first round, the participants were asked to provide potentially relevant items for a difficult-to-manage asthma programme, which resulted in 67 items. In the second round, we asked participants to rate the relevance of specific items on a seven-point Likert scale, and 46 items were selected as relevant. In the third round, the selected items were categorised and items were ranked within the categories according to relevance. Finally, we created the alphabet acronym for the categories 'the A-I of difficult-to-manage asthma' to resonate with an established Dutch 'A-E acronym for determining asthma control'. This should facilitate implementation of this programme within the existing structure of educational material on asthma and chronic obstructive pulmonary disease (COPD) in primary care, with potential for improving management of difficult-to-manage asthma. Other countries could use a similar approach to create a locally adapted version of such a programme., Competing Interests: HP received an honorarium from the IPCRG for speaking at the initial 'Train the Trainers’ meeting in Rome. In the last 3 years, RD and/or his department received research grants, unrestricted educational grants and/or fees for lectures and advisory board meetings from Almirall, AstraZeneca, Boehringer-Ingelheim, Chiesi, GSK, Mundipharma, Novartis, Takeda and Teva. In the last 3 years, JCCMiV and/or his department received research grants, unrestricted educational grants and/or fees for lectures and advisory board meetings from AstraZeneca, Boehringer-Ingelheim, Chiesi, GSK, Lilly, Novartis and Teva.

Asthma is characterised by heterogeneous clinical phenotypes. Our objective was to determine molecular phenotypes of asthma by analysing sputum cell transcriptomics from 104 moderate-to-severe asthmatic subjects and 16 nonasthmatic subjects.After filtering on the differentially expressed genes between eosinophil- and noneosinophil-associated sputum inflammation, we used unbiased hierarchical clustering on 508 differentially expressed genes and gene set variation analysis of specific gene sets.We defined three transcriptome-associated clusters (TACs): TAC1 (characterised by immune receptors IL33R , CCR3 and TSLPR ), TAC2 (characterised by interferon-, tumour necrosis factor-α- and inflammasome-associated genes) and TAC3 (characterised by genes of metabolic pathways, ubiquitination and mitochondrial function). TAC1 showed the highest enrichment of gene signatures for interleukin-13/T-helper cell type 2 (Th2) and innate lymphoid cell type 2. TAC1 had the highest sputum eosinophilia and exhaled nitric oxide fraction, and was restricted to severe asthma with oral corticosteroid dependency, frequent exacerbations and severe airflow obstruction. TAC2 showed the highest sputum neutrophilia, serum C-reactive protein levels and prevalence of eczema. TAC3 had normal to moderately high sputum eosinophils and better preserved forced expiratory volume in 1 s. Gene-protein coexpression networks from TAC1 and TAC2 extended this molecular classification.We defined one Th2-high eosinophilic phenotype TAC1, and two non-Th2 phenotypes TAC2 and TAC3, characterised by inflammasome-associated and metabolic/mitochondrial pathways, respectively., (Copyright ©ERS 2017.)

Background: The diagnosis of ventilator-associated pneumonia (VAP) remains time-consuming and costly, the clinical tools lack specificity and a bedside test to exclude infection in suspected patients is unavailable. Breath contains hundreds to thousands of volatile organic compounds (VOCs) that result from host and microbial metabolism as well as the environment. The present study aims to use breath VOC analysis to develop a model that can discriminate between patients who have positive cultures and who have negative cultures with a high sensitivity., Methods/design: The Molecular Analysis of Exhaled Breath as Diagnostic Test for Ventilator-Associated Pneumonia (BreathDx) study is a multicentre observational study. Breath and bronchial lavage samples will be collected from 100 and 53 intubated and ventilated patients suspected of VAP. Breath will be analysed using Thermal Desorption - Gas Chromatography - Mass Spectrometry (TD-GC-MS). The primary endpoint is the accuracy of cross-validated prediction for positive respiratory cultures in patients that are suspected of VAP, with a sensitivity of at least 99% (high negative predictive value)., Discussion: To our knowledge, BreathDx is the first study powered to investigate whether molecular analysis of breath can be used to classify suspected VAP patients with and without positive microbiological cultures with 99% sensitivity., Trial Registration: UKCRN ID number 19086, registered May 2015; as well as registration at www.trialregister.nl under the acronym 'BreathDx' with trial ID number NTR 6114 (retrospectively registered on 28 October 2016).

The Strategic Implementation Plan of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) proposed six Action Groups. After almost three years of activity, many achievements have been obtained through commitments or collaborative work of the Action Groups. However, they have often worked in silos and, consequently, synergies between Action Groups have been proposed to strengthen the triple win of the EIP on AHA. The paper presents the methodology and current status of the Task Force on EIP on AHA synergies. Synergies are in line with the Action Groups' new Renovated Action Plan (2016-2018) to ensure that their future objectives are coherent and fully connected. The outcomes and impact of synergies are using the Monitoring and Assessment Framework for the EIP on AHA (MAFEIP). Eight proposals for synergies have been approved by the Task Force: Five cross-cutting synergies which can be used for all current and future synergies as they consider overarching domains (appropriate polypharmacy, citizen empowerment, teaching and coaching on AHA, deployment of synergies to EU regions, Responsible Research and Innovation), and three cross-cutting synergies focussing on current Action Group activities (falls, frailty, integrated care and chronic respiratory diseases).

The Allergic Rhinitis and its Impact on Asthma (ARIA) initiative commenced during a World Health Organization workshop in 1999. The initial goals were (1) to propose a new allergic rhinitis classification, (2) to promote the concept of multi-morbidity in asthma and rhinitis and (3) to develop guidelines with all stakeholders that could be used globally for all countries and populations. ARIA-disseminated and implemented in over 70 countries globally-is now focusing on the implementation of emerging technologies for individualized and predictive medicine. MASK [MACVIA ( Contre les Maladies Chroniques pour un Vieillissement Actif )-ARIA Sentinel NetworK] uses mobile technology to develop care pathways for the management of rhinitis and asthma by a multi-disciplinary group and by patients themselves. An app (Android and iOS) is available in 20 countries and 15 languages. It uses a visual analogue scale to assess symptom control and work productivity as well as a clinical decision support system. It is associated with an inter-operable tablet for physicians and other health care professionals. The scaling up strategy uses the recommendations of the European Innovation Partnership on Active and Healthy Ageing. The aim of the novel ARIA approach is to provide an active and healthy life to rhinitis sufferers, whatever their age, sex or socio-economic status, in order to reduce health and social inequalities incurred by the disease.

Background: Asthma is a disease of varying severity and differing disease mechanisms. To date, studies aimed at stratifying asthma into clinically useful phenotypes have produced a number of phenotypes that have yet to be assessed for stability and to be validated in independent cohorts. The aim of this study was to define and validate, for the first time ever, clinically driven asthma phenotypes using two independent, severe asthma cohorts: ADEPT and U-BIOPRED., Methods: Fuzzy partition-around-medoid clustering was performed on pre-specified data from the ADEPT participants (n = 156) and independently on data from a subset of U-BIOPRED asthma participants (n = 82) for whom the same variables were available. Models for cluster classification probabilities were derived and applied to the 12-month longitudinal ADEPT data and to a larger subset of the U-BIOPRED asthma dataset (n = 397). High and low type-2 inflammation phenotypes were defined as high or low Th2 activity, indicated by endobronchial biopsies gene expression changes downstream of IL-4 or IL-13., Results: Four phenotypes were identified in the ADEPT (training) cohort, with distinct clinical and biomarker profiles. Phenotype 1 was "mild, good lung function, early onset", with a low-inflammatory, predominantly Type-2, phenotype. Phenotype 2 had a "moderate, hyper-responsive, eosinophilic" phenotype, with moderate asthma control, mild airflow obstruction and predominant Type-2 inflammation. Phenotype 3 had a "mixed severity, predominantly fixed obstructive, non-eosinophilic and neutrophilic" phenotype, with moderate asthma control and low Type-2 inflammation. Phenotype 4 had a "severe uncontrolled, severe reversible obstruction, mixed granulocytic" phenotype, with moderate Type-2 inflammation. These phenotypes had good longitudinal stability in the ADEPT cohort. They were reproduced and demonstrated high classification probability in two subsets of the U-BIOPRED asthma cohort., Conclusions: Focusing on the biology of the four clinical independently-validated easy-to-assess ADEPT asthma phenotypes will help understanding the unmet need and will aid in developing tailored therapies., Trial Registration: NCT01274507 (ADEPT), registered October 28, 2010 and NCT01982162 (U-BIOPRED), registered October 30, 2013.

Worldwide, the number of professional and sports divers is increasing. Most of them breathe diving gases with a raised partial pressure of oxygen (P O 2 ). However, if the P O 2 is between 50 and 300 kPa (375-2250 mmHg) (hyperoxia), pathological pulmonary changes can develop, known as pulmonary oxygen toxicity (POT). Although in its acute phase, POT is reversible, it can ultimately lead to non-reversible pathological changes. Therefore, it is important to monitor these divers to prevent them from sustaining irreversible lesions.This review summarises the pulmonary pathophysiological effects when breathing oxygen with a P O 2 of 50-300 kPa (375-2250 mmHg). We describe the role and the limitations of lung function testing in monitoring the onset and development of POT, and discuss new techniques in respiratory medicine as potential markers in the early development of POT in divers., (Copyright ©ERS 2016.)

Background: Patients with atrial septal defects (ASD) are often misdiagnosed as asthma patients and accordingly receive erroneous bronchodilator treatment. In order to characterise their symptoms of dyspnoea to explain this clinical observation, we investigated the prevalence of asthma-like symptoms in patients with secundum ASD who then underwent successful percutaneous closure., Methods: A total of 80 ASD patients (74 % female, mean age 46.7 ± 16.8 years, median follow-up 3.0 [2.0-5.0] years) retrospectively completed dyspnoea questionnaires determining the presence and extent of cough, wheezing, chest tightness, effort dyspnoea and bronchodilator use on a 7-point scale (0 = none, 6 = maximum) before and after ASD closure. The Mini Asthma Quality of Life (Mini-AQLQ) and Asthma Control Questionnaire with bronchodilator use (ACQ6) were administered., Results: A total of 48 (60 %) patients reported cough, 27 (34 %) wheezing, 26 (33 %) chest tightness and 62 (78 %) effort dyspnoea. Symptom resolution or reduction was found in 64 (80 %) patients after ASD closure. Asthma symptom scores decreased significantly on the Mini-AQLQ and ACQ6 (both p < 0.001). The number of patients using bronchodilators decreased from 16 (20 %) to 8 (10 %) patients after ASD closure (p = 0.039) with less frequent use of bronchodilators (p = 0.015)., Conclusions: A high prevalence of asthma-like symptoms and bronchodilator use is present in ASD patients, which exceeds the low prevalence of bronchial asthma in this study population. Future prospective research is required to confirm this phenomenon. The presence of an ASD should be considered in the differential diagnosis of patients with asthma-like symptoms, after which significant symptom relief can be achieved by ASD closure., Competing Interests: Conflict of interestM. Nassif, C.B.B.C. Heuschen, H. Lu, B.J. Bouma, R.P. van Steenwijk, P.J. Sterk, B.J.M. Mulder and R. J. de Winter state that they have no competing interest.

Respiratory diseases are highly complex, being driven by host-environment interactions and manifested by inflammatory, structural, and functional abnormalities that vary over time. Traditional reductionist approaches have contributed vastly to our knowledge of biological systems in health and disease to date; however, they are insufficient to provide an understanding of the behavior of the system as a whole. In this Pulmonary Perspective, we discuss systems biology approaches, especially but not limited to the study of the lung as a complex system. Such integrative approaches take into account the large number of dynamic subunits and their interactions found in biological systems. Borrowing methods from physics and mathematics, it is possible to study the collective behavior of these systems over time and in a multidimensional manner. We first examine the physiological basis for complexity in the respiratory system and its implications for disease. We then expand on the potential applications of systems biology methods to study complex systems, within the context of diagnosis and monitoring of respiratory diseases including asthma, chronic obstructive pulmonary disease (COPD), and critical illness. We summarize the significant advances made in recent years using systems approaches for disease phenotyping, applied to data ranging from the molecular to clinical level, obtained from large-scale asthma and COPD networks. We describe new studies using temporal complexity patterns to characterize asthma and COPD and predict exacerbations as well as predict adverse outcomes in critical care. We highlight new methods that are emerging with this approach and discuss remaining questions that merit greater attention in the field.

The U-BIOPRED study is a multicentre European study aimed at a better understanding of severe asthma. It included three steroid-treated adult asthma groups (severe nonsmokers (SAn group), severe current/ex-smokers (SAs/ex group) and those with mild-moderate disease (MMA group)) and healthy controls (HC group). The aim of this cross-sectional, bronchoscopy substudy was to compare bronchial immunopathology between these groups.In 158 participants, bronchial biopsies and bronchial epithelial brushings were collected for immunopathologic and transcriptomic analysis. Immunohistochemical analysis of glycol methacrylate resin-embedded biopsies showed there were more mast cells in submucosa of the HC group (33.6 mm -2 ) compared with both severe asthma groups (SAn: 17.4 mm -2 , p<0.001; SAs/ex: 22.2 mm -2 , p=0.01) and with the MMA group (21.2 mm -2 , p=0.01). The number of CD4 + lymphocytes was decreased in the SAs/ex group (4.7 mm -2 ) compared with the SAn (11.6 mm -2 , p=0.002), MMA (10.1 mm -2 , p=0.008) and HC (10.6 mm -2 , p<0.001) groups. No other differences were observed.Affymetrix microarray analysis identified seven probe sets in the bronchial brushing samples that had a positive relationship with submucosal eosinophils. These mapped to COX-2 (cyclo-oxygenase-2), ADAM-7 (disintegrin and metalloproteinase domain-containing protein 7), SLCO1A2 (solute carrier organic anion transporter family member 1A2), TMEFF2 (transmembrane protein with epidermal growth factor like and two follistatin like domains 2) and TRPM-1 (transient receptor potential cation channel subfamily M member 1); the remaining two are unnamed.We conclude that in nonsmoking and smoking patients on currently recommended therapy, severe asthma exists despite suppressed tissue inflammation within the proximal airway wall., (Copyright ©ERS 2016.)