Exhaled breath condensate volatilome allows sensitive diagnosis of persistent asthma. Issue 3 (11th October 2018)

• Record Type: Journal Article
• Authors: Cavaleiro Rufo, João; Paciência, Inês; Mendes, Francisca Castro; Farraia, Mariana; Rodolfo, Ana; Silva, Diana; de Oliveira Fernandes, Eduardo; Delgado, Luís; Moreira, André
• Is Part Of: Allergy. Volume 74:Issue 3(2019)
• Page Start: 527
• Page End: 534
• Publication Date: 2018-10-11
• Subjects: asthma diagnosis -- electronic nose -- exhaled breath condensate -- multivariate analysis -- volatile organic compounds; Allergy -- Periodicals; 616.97
• DOI: 10.1111/all.13596
• Languages: English
• ISSNs: 0105-4538

Abstract

Abstract: Background: The diagnosis and phenotyping of paediatric asthma are particularly complex due to the lack of currently available sensitive diagnostic tools. This often results in uncertainties associated with inhaled steroid therapy prescription. Therefore, this study aimed to investigate whether volatile organic compounds measured in exhaled breath condensate can be used as biomarkers for asthma diagnosis in the paediatric population. Methods: A total of 64 participants, aged 6‐18 years, were recruited on a random basis during visits to an outpatient allergy clinic and to a juvenile football team training session. Lung function, airway reversibility and skin prick tests were performed. Exhaled breath condensate samples were collected, and breathprints were assessed using an electronic nose. Information on medical diagnosis of asthma, rhinitis and atopic dermatitis was retrieved for each participant. A hierarchical cluster model based on the volatilome profiles was then created. Results: A two‐cluster exhaled volatile organic compound‐based hierarchical model was able to significantly discriminate individuals with asthma from those without the disease (AUC = 0.81 [0.69‐0.93], P < 0.001). Individuals who had persistent asthma and were prescribed corticosteroid therapy by the physician were also significantly distinguished in the model (AUC = 0.81 [0.70‐0.92], P < 0.001). Despite being less specific, the method showed higher overall accuracy, sensitivity and AUC values when compared to spirometry with bronchodilation. Conclusions: Analysis of the exhaled breath condensate volatilome allowed the distinction of paediatric individuals with a medical diagnosis of asthma, identifying those in need of corticosteroid therapy. Abstract : The developed breathomics model was able to identify individuals with asthma and with persistent asthma with improved performance over spirometry with bronchodilation. The study shows that a breathomics model was able to identify individuals with a medical diagnosis of asthma with high accuracy. Individuals with asthma in need of inhaled corticosteroid therapy were significantly clustered in the model. Breathomics has the potential to assist the physician in the diagnosis of asthma and/or administration of corticosteroid therapy for paediatric patients with asthma.