No abstract

Several volatile organic compounds have been identified in exhaled breath in healthy subjects and patients with respiratory diseases by gas chromatography/mass spectrometry. Identification of selective patterns of volatile organic compounds in exhaled breath could be used as a biomarker of inflammatory lung diseases. An electronic nose (e-nose) is an artificial sensor system that generally consists of an array of chemical sensors for detection of volatile organic compound profiles (breathprints) and an algorithm for pattern recognition. E-noses are handheld, portable devices that provide immediate results. E-noses discriminate between patients with respiratory disease, including asthma, COPD and lung cancer, and healthy control subjects, and also among patients with different respiratory diseases. E-nose breathprints are associated with airway inflammation activity. In combination with other ‘omics’ platforms, e-nose technology might contribute to the identification of new surrogate markers of pulmonary inflammation and subphenotypes of patients with respiratory diseases, provide a molecular basis to a personalized pharmacological treatment, and facilitate the development of new drugs.

Electronic noses (e-noses), artificial sensor systems generally consisting of chemical sensor arrays for the detection of volatile compound profiles, have potential applications in respiratory medicine. We assessed within-day and between-day repeatability of an e-nose made from 32 sensors in patients with stable chronic obstructive pulmonary disease (COPD). We also compared between-day repeatability of an e-nose, fraction of exhaled nitric oxide (FENO) and pulmonary function testing. Within-day and between-day repeatability for the e-nose was assessed in two breath samples collected 30 min and seven days apart, respectively. Repeatability was expressed as an intraclass correlation coefficient (ICC). All sensors had ICC above 0.5, a value that is considered acceptable for repeatability. Regarding within-day repeatability, ICC ranged from 0.75 to 0.84 (mean = 0.80 ± 0.004). Sensors 6 and 19 were the most reproducible sensors (both, ICC = 0.84). Regarding between-day repeatability, ICC ranged from 0.57 to 0.76 (mean = 0.68 ± 0.01). Sensor 19 was the most reproducible sensor (ICC = 0.76). Within-day e-nose repeatability was greater than between-day repeatability (P < 0.0001). Between-day repeatability of FENO (ICC = 0.91) and spirometry (ICC range = 0.94-0.98) was greater than that of e-nose (mean ICC = 0.68). In patients with stable COPD, the e-nose used in this study has acceptable within-day and between-day repeatability which varies between different sensors.

Breathomics, the multidimensional molecular analysis of exhaled breath, includes analysis of exhaled breath with gas-chromatography/mass spectrometry (GC/MS) and electronic noses (e-noses), and metabolomics of exhaled breath condensate (EBC), a non-invasive technique which provides information on the composition of airway lining fluid, generally by high-resolution nuclear magnetic resonance (NMR) spectroscopy or MS methods. Metabolomics is the identification and quantification of small molecular weight metabolites in a biofluid. Specific profiles of volatile compounds in exhaled breath and metabolites in EBC (breathprints) are potentially useful surrogate markers of inflammatory respiratory diseases. Electronic noses (e-noses) are artificial sensor systems, usually consisting of chemical cross-reactive sensor arrays for characterization of patterns of breath volatile compounds, and algorithms for breathprints classification. E-noses are handheld, portable, and provide real-time data. E-nose breathprints can reflect respiratory inflammation. E-noses and NMR-based metabolomics of EBC can distinguish patients with respiratory diseases such as asthma, COPD, and lung cancer, or diseases with a clinically relevant respiratory component including cystic fibrosis and primary ciliary dyskinesia, and healthy individuals. Breathomics has also been reported to identify patients affected by different types of respiratory diseases. Patterns of breath volatile compounds detected by e-nose and EBC metabolic profiles have been associated with asthma phenotypes. In combination with other -omics platforms, breathomics might provide a molecular approach to respiratory disease phenotyping and a molecular basis to tailored pharmacotherapeutic strategies. Breathomics might also contribute to identify new surrogate markers of respiratory inflammation, thus, facilitating drug discovery. Validation in newly recruited, prospective independent cohorts is essential for development of e-nose and EBC NMRbased metabolomics techniques.