Breath analysis of smokers, non-smokers, and e-cigarette users

Abstract

Solid phase micro extraction-Gas Chromatography/Mass Spectrometry (SPME-GC/MS) analysis was performed in exhaled breath samples of 48 healthy volunteers: 20 non-smokers, 10 smokers and 18 e-cigarette (EC, vape) users. Each volunteer provided 1 L of exhaled breath in a pre-cleaned Tedlar bag, in which an SPME fiber was exposed to absorb the emitted breath volatile organic compounds (VOCs). The acquired data were processed using multivariate data analysis (MDA) methods in order to identify the characteristic chemicals of the three groups. The results revealed that the breath of non-smokers demonstrated inverse correlation with a variety of molecules related to the breath from smokers including furan, toluene, 2-butanone and other organic substances. Vapers were distinguished from smokers by the chemical speciation of the e-liquids, such as that of esters (e.g. ethyl acetate), terpenes (e.g. α-pinene, β-pinene, d-limonene, p-cymene, etc.) and oxygenated compounds (e.g. 3-hexen-1-ol, benzaldehyde, hexanal, decanal, etc). Two classification models were developed (a) using principal component analysis (PCA) with hierarchical cluster analysis (HCA) and (b) using partial least squares-discriminant analysis (PLS-DA). Both models were validated using 8 new samples (4 vapers and 4 smokers), collected in addition to the 48 samples of the calibration set. The combination of GC/MS breath analysis and MDA contributed successfully in classifying the volunteers into their respective groups and highlighted the relevant characteristic VOCs. The respective dynamic combination (SPME-GC/MS and MDA) provides a means for long term non-invasive monitoring of the population’s health status for early detection purposes.