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=0.581) and neutrophilic (R=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.
Fractionated exhaled nitric oxide (FeNO) expression is increased in airway inflammation and several studies have suggested that FeNO measurement can be useful in patients with asthma. Atopic individuals have increased FeNO levels, indicating that atopy may be a codeterminant in FeNO production. The aim of this study was to determine the discriminative value of FeNO for asthma and other atopic conditions in the general allergy clinic. Patients referred to the outpatient allergy clinic were screened. A standardized questionnaire was taken and atopic status was assessed (skin-prick test or specific plasma IgE). FeNO level and spirometry were measured. If the patient's history was suspect for asthma, a provocative concentration causing a 20% decrease in forced expiratory volume in 1 second (PC(20)) histamine challenge followed. One hundred fourteen steroid-naive patients were included. Forty-two subjects were diagnosed as asthmatic patients and 72 were diagnosed as nonasthmatic patients, comprising patients with allergic rhinitis (n = 32), nonallergic rhinitis (n = 11), urticaria (n = 11), eczema (n = 7), and other (n = 11). Asthmatic patients had a higher FeNO level than nonasthmatic patients (44 ppb versus 17 ppb; p < 0.001). Receiver operating characteristic curve analysis revealed the optimal FeNO level to distinguish asthma from nonasthma at 27 ppb, with a sensitivity of 78%, specificity of 92%, a positive predictive value of 86%, and a negative predictive value of 87%. Increased FeNO was positively correlated with the presence of respiratory symptoms (p < 0.01), airflow reversibility (p < 0.001), total IgE (p < 0.001), and negatively correlated with PC(20) histamine (p = 0.019). Multivariate analysis revealed that atopy was not a significant predictor of FeNO in asthmatic patients. Measuring FeNO is a simple and useful test to differentiate new asthma patients from those with other atopic conditions in a general allergy clinic.
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