Ex vivo innate responses to particulate matter from livestock farms in asthma patients and healthy individuals.

BACKGROUND: Asthma patients suffer from periodic acute worsening of symptoms (i.e. loss of asthma control or exacerbations), triggered by a variety of exogenous stimuli. With the growing awareness that air pollutants impact respiratory diseases, we investigated whether particulate matter (PM) derived from various livestock farms (BioPM) differentially affected innate and oxidative stress responses in asthma and health. METHODS: Peripheral blood mononuclear cells (PBMCs), collected from patients sequentially before and during loss of asthma control and from healthy individuals, were exposed to BioPM collected from chicken, goat and pig farms (1 and 5 µg/ml), with or without pre-treatment with antioxidants. Cytokine release and oxidative stress were assessed. RESULTS: PBMCs produced IFNγ, IL-1ß, IL-10 and TNFα upon stimulation with BioPM, with that from pig farms inducing the highest cytokine levels. Overall, cytokine production was irrespective of the presence or state of disease. However, PBMCs from stable asthma patients upon exposure to the three BioPM showed more extreme TNFα responses than those from healthy subjects. Furthermore, PBMCs obtained during loss of asthma control that were exposed to BioPM from pig farms showed enhanced IFNγ release as well as decreased oxidative stress levels upon pre-treatment with N-acetylcysteine (NAC) compared to stable disease. NAC, but not superoxide dismutase and catalase, also counteracted BioPM-induced cytokine release, indicating the importance of intracellular reactive oxygen species in the production of cytokines. CONCLUSIONS: BioPM triggered enhanced pro-inflammatory responses by PBMCs from both healthy subjects and asthma patients, with those from patients during loss of asthma control showing increased susceptibility to BioPM from pig farms in particular.

Corticosteroid Withdrawal-Induced Loss of Control in Mild to Moderate Asthma Is Independent of Classic Granulocyte Activation.

BACKGROUND: Loss of asthma control and asthma exacerbations are associated with increased sputum eosinophil counts. However, whether eosinophils, or the also present neutrophils, actively contribute to the accompanying inflammation has not been extensively investigated. METHODS: Twenty-three patients with mild to moderate asthma were included in a standardized prospective inhaled corticosteroid (ICS) withdrawal study; 22 of the patients experienced loss of asthma control. The study assessed various immune, inflammatory, and oxidative stress parameters, as well as markers of eosinophil and neutrophil activity, in exhaled breath condensate, plasma, and sputum collected at three phases (baseline, during loss of control, and following recovery). RESULTS: Loss of asthma control was characterized by increased sputum eosinophils, whereas no differences were detected between the three phases for most inflammatory and oxidative stress responses. There were also no differences detected for markers of activated eosinophils (eosinophil cationic protein and bromotyrosine) and neutrophils (myeloperoxidase and chlorotyrosine). However, free eosinophilic granules and citrullinated histone H3, suggestive of eosinophil cytolysis and potentially eosinophil extracellular trap formation, were enhanced. Baseline blood eosinophils and changes in asymmetric dimethylarginine (an inhibitor of nitric oxide synthase) in plasma were found to correlate with the decrease in FEV1 percent predicted upon ICS withdrawal (both, rs = 0.46; P = .03). CONCLUSIONS: The clinical effect in mild to moderate asthma upon interruption of ICS therapy is not related to the classic inflammatory activation of eosinophils and neutrophils. It may, however, reflect another pathway underlying the onset of loss of disease control and asthma exacerbations. TRIAL REGISTRY: The Netherlands Trial Register; No.: NTR3316; URL: trialregister.nl/trial/3172.

A European Respiratory Society technical standard: exhaled biomarkers in lung disease.

Breath tests cover the fraction of nitric oxide in expired gas (FeNO), volatile organic compounds (VOCs), variables in exhaled breath condensate (EBC) and other measurements. For EBC and for FeNO, 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 FeNO, 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.

Smelling the Diagnosis: The Electronic Nose as Diagnostic Tool in Inflammatory Arthritis. A Case-Reference Study.

OBJECTIVE: To investigate whether exhaled breath analysis using an electronic nose can identify differences between inflammatory joint diseases and healthy controls. METHODS: In a cross-sectional study, the exhaled breath of 21 rheumatoid arthritis (RA) and 18 psoriatic arthritis (PsA) patients with active disease was compared to 21 healthy controls using an electronic nose (Cyranose 320; Smiths Detection, Pasadena, CA, USA). Breathprints were analyzed with principal component analysis, discriminant analysis, and area under curve (AUC) of receiver operating characteristics (ROC) curves. Volatile organic compounds (VOCs) were identified by gas chromatography and mass spectrometry (GC-MS), and relationships between breathprints and markers of disease activity were explored. RESULTS: Breathprints of RA patients could be distinguished from controls with an accuracy of 71% (AUC 0.75, 95% CI 0.60-0.90, sensitivity 76%, specificity 67%). Breathprints from PsA patients were separated from controls with 69% accuracy (AUC 0.77, 95% CI 0.61-0.92, sensitivity 72%, specificity 71%). Distinction between exhaled breath of RA and PsA patients exhibited an accuracy of 69% (AUC 0.72, 95% CI 0.55-0.89, sensitivity 71%, specificity 72%). There was a positive correlation in RA patients of exhaled breathprints with disease activity score (DAS28) and number of painful joints. GC-MS identified seven key VOCs that significantly differed between the groups. CONCLUSIONS: Exhaled breath analysis by an electronic nose may play a role in differential diagnosis of inflammatory joint diseases. Data from this study warrant external validation.

Comparison of classification methods in breath analysis by electronic nose.

Currently, many different methods are being used for pre-processing, statistical analysis and validation of data obtained by electronic nose technology from exhaled air. These various methods, however, have never been thoroughly compared. We aimed to empirically evaluate and compare the influence of different dimension reduction, classification and validation methods found in published studies on the diagnostic performance in several datasets. Our objective was to facilitate the selection of appropriate statistical methods and to support reviewers in this research area. We reviewed the literature by searching Pubmed up to the end of 2014 for all human studies using an electronic nose and methodological quality was assessed using the QUADAS-2 tool tailored to our review. Forty-six studies were evaluated regarding the range of different approaches to dimension reduction, classification and validation. From forty-six reviewed articles only seven applied external validation in an independent dataset, mostly with a case-control design. We asked their authors to share the original datasets with us. Four of the seven datasets were available for re-analysis. Published statistical methods for eNose signal analysis found in the literature review were applied to the training set of each dataset. The performance (area under the receiver operating characteristics curve (ROC-AUC)) was calculated for the training cohort (in-set) and after internal validation (leave-one-out cross validation). The methods were also applied to the external validation set to assess the external validity of the performance. Risk of bias was high in most studies due to non-random selection of patients. Internal validation resulted in a decrease in ROC-AUCs compared to in-set performance: -0.15,-0.14,-0.1,-0.11 in dataset 1 through 4, respectively. External validation resulted in lower ROC-AUC compared to internal validation in dataset 1 (-0.23) and 3 (-0.09). ROC-AUCs did not decrease in dataset 2 (+0.07) and 4 (+0.04). No single combination of dimension reduction and classification methods gave consistent results between internal and external validation sets in this sample of four datasets. This empirical evaluation showed that it is not meaningful to estimate the diagnostic performance on a training set alone, even after internal validation. Therefore, we recommend the inclusion of an external validation set in all future eNose projects in medicine.

Toward composite molecular signatures in the phenotyping of asthma.

The complex biology of respiratory diseases such as asthma is feeding the discovery of various disease phenotypes. Although the clinical management of asthma phenotypes by using a single biomarker (e.g., sputum eosinophils) is successful, emerging evidence shows the requirement of multiscale, high-dimensional biological and clinical measurements to capture the complexity of various asthma phenotypes. High-throughput "omics" technologies, including transcriptomics, proteomics, lipidomics, and metabolomics, are increasingly standardized for biomarker discovery in asthma. The leading principle is obeying available guidelines on omics analysis, thereby strictly limiting false discovery. In this review we address the concept of transcriptomics using microarrays or next-generation RNA sequencing and their applications in asthma, highlighting the strengths and limitations of both techniques, and review metabolomics in exhaled air (breathomics) as a noninvasive alternative for sampling the airways directly. These developments will inevitably lead to the integration of molecular signatures in the phenotyping of asthma and other diseases.

Subphenotypes of mild-to-moderate COPD by factor and cluster analysis of pulmonary function, CT imaging and breathomics in a population-based survey.

INTRODUCTION: Classification of COPD is currently based on the presence and severity of airways obstruction. However, this may not fully reflect the phenotypic heterogeneity of COPD in the (ex-) smoking community. We hypothesized that factor analysis followed by cluster analysis of functional, clinical, radiological and exhaled breath metabolomic features identifies subphenotypes of COPD in a community-based population of heavy (ex-) smokers. METHODS: Adults between 50-75 years with a smoking history of at least 15 pack-years derived from a random population-based survey as part of the NELSON study underwent detailed assessment of pulmonary function, chest CT scanning, questionnaires and exhaled breath molecular profiling using an electronic nose. Factor and cluster analyses were performed on the subgroup of subjects fulfilling the GOLD criteria for COPD (post-BD FEV1/FVC < 0.70). RESULTS: Three hundred subjects were recruited, of which 157 fulfilled the criteria for COPD and were included in the factor and cluster analysis. Four clusters were identified: cluster 1 (n = 35; 22%): mild COPD, limited symptoms and good quality of life. Cluster 2 (n = 48; 31%): low lung function, combined emphysema and chronic bronchitis and a distinct breath molecular profile. Cluster 3 (n = 60; 38%): emphysema predominant COPD with preserved lung function. Cluster 4 (n = 14; 9%): highly symptomatic COPD with mildly impaired lung function. In a leave-one-out validation analysis an accuracy of 97.4% was reached. CONCLUSIONS: This unbiased taxonomy for mild to moderate COPD reinforces clusters found in previous studies and thereby allows better phenotyping of COPD in the general (ex-) smoking population.

Airway inflammation and mannitol challenge test in COPD.

BACKGROUND: Eosinophilic airway inflammation has successfully been used to tailor anti-inflammatory therapy in chronic obstructive pulmonary disease (COPD). Airway hyperresponsiveness (AHR) by indirect challenges is associated with airway inflammation. We hypothesized that AHR to inhaled mannitol captures eosinophilia in induced sputum in COPD. METHODS: Twenty-eight patients (age 58 ± 7.8 yr, packyears 40 ± 15.5, post-bronchodilator FEV1 77 ± 14.0%predicted, no inhaled steroids ≥4 wks) with mild-moderate COPD (GOLD I-II) completed two randomized visits with hypertonic saline-induced sputum and mannitol challenge (including sputum collection). AHR to mannitol was expressed as response-dose-ratio (RDR) and related to cell counts, ECP, MPO and IL-8 levels in sputum. RESULTS: There was a positive correlation between RDR to mannitol and eosinophil numbers (r = 0.47, p = 0.03) and level of IL-8 (r = 0.46, p = 0.04) in hypertonic saline-induced sputum. Furthermore, significant correlations were found between RDR and eosinophil numbers (r = 0.71, p = 0.001), level of ECP (r = 0.72, p = 0.001), IL-8 (r = 0.57, p = 0.015) and MPO (r = 0.64, p = 0.007) in sputum collected after mannitol challenge. ROC-curves showed 60% sensitivity and 100% specificity of RDR for >2.5% eosinophils in mannitol-induced sputum. CONCLUSIONS: In mild-moderate COPD mannitol hyperresponsiveness is associated with biomarkers of airway inflammation. The high specificity of mannitol challenge suggests that the test is particularly suitable to exclude eosinophilic airways inflammation, which may facilitate individualized treatment in COPD. TRIAL REGISTRATION: Netherlands Trial Register (NTR): NTR1283.

Electronic nose breathprints are independent of acute changes in airway caliber in asthma.

Molecular profiling of exhaled volatile organic compounds (VOC) by electronic nose technology provides breathprints that discriminate between patients with different inflammatory airway diseases, such as asthma and COPD. However, it is unknown whether this is determined by differences in airway caliber. We hypothesized that breathprints obtained by electronic nose are independent of acute changes in airway caliber in asthma. Ten patients with stable asthma underwent methacholine provocation (Visit 1) and sham challenge with isotonic saline (Visit 2). At Visit 1, exhaled air was repetitively collected pre-challenge, after reaching the provocative concentration (PC(20)) causing 20% fall in forced expiratory volume in 1 second (FEV(1)) and after subsequent salbutamol inhalation. At Visit 2, breath was collected pre-challenge, post-saline and post-salbutamol. At each occasion, an expiratory vital capacity was collected after 5 min of tidal breathing through an inspiratory VOC-filter in a Tedlar bag and sampled by electronic nose (Cyranose 320). Breathprints were analyzed with principal component analysis and individual factors were compared with mixed model analysis followed by pairwise comparisons. Inhalation of methacholine led to a 30.8 ± 3.3% fall in FEV(1) and was followed by a significant change in breathprint (p = 0.04). Saline inhalation did not induce a significant change in FEV(1), but altered the breathprint (p = 0.01). However, the breathprint obtained after the methacholine provocation was not significantly different from that after saline challenge (p = 0.27). The molecular profile of exhaled air in patients with asthma is altered by nebulized aerosols, but is not affected by acute changes in airway caliber. Our data demonstrate that breathprints by electronic nose are not confounded by the level of airway obstruction.

Exhaled breath profiling enables discrimination of chronic obstructive pulmonary disease and asthma.

RATIONALE: Chronic obstructive pulmonary disease (COPD) and asthma can exhibit overlapping clinical features. Exhaled air contains volatile organic compounds (VOCs) that may qualify as noninvasive biomarkers. VOC profiles can be assessed using integrative analysis by electronic nose, resulting in exhaled molecular fingerprints (breathprints). OBJECTIVES: We hypothesized that breathprints by electronic nose can discriminate patients with COPD and asthma. METHODS: Ninety subjects participated in a cross-sectional study: 30 patients with COPD (age, 61.6 +/- 9.3 years; FEV(1), 1.72 +/- 0.69 L), 20 patients with asthma (age, 35.4 +/- 15.1 years; FEV(1) 3.32 +/- 0.86 L), 20 nonsmoking control subjects (age, 56.7 +/- 9.3 years; FEV(1), 3.44 +/- 0.76 L), and 20 smoking control subjects (age, 56.1 +/- 5.9 years; FEV(1), 3.58 +/- 0.78). After 5 minutes of tidal breathing through an inspiratory VOC filter, an expiratory vital capacity was collected in a Tedlar bag and sampled by electronic nose. Breathprints were analyzed by discriminant analysis on principal component reduction resulting in cross-validated accuracy values (accuracy). Repeatability and reproducibility were assessed by measuring samples in duplicate by two devices. MEASUREMENTS AND MAIN RESULTS: Breathprints from patients with asthma were separated from patients with COPD (accuracy 96%; P < 0.001), from nonsmoking control subjects (accuracy, 95%; P < 0.001), and from smoking control subjects (accuracy, 92.5%; P < 0.001). Exhaled breath profiles of patients with COPD partially overlapped with those of asymptomatic smokers (accuracy, 66%; P = 0.006). Measurements were repeatable and reproducible. CONCLUSIONS: Molecular profiling of exhaled air can distinguish patients with COPD and asthma and control subjects. Our data demonstrate a potential of electronic noses in the differential diagnosis of obstructive airway diseases and in the risk assessment in asymptomatic smokers. Clinical trial registered with www.trialregister.nl (NTR 1282).