Exhaled breath condensate (EBC) is a non-invasive biological matrix that allows easy access to the lung epithelial lining fluid. It can provide, for instance, useful biochemical information in workers following inhalatory exposure. Recently, nuclear magnetic resonance (NMR)-based metabolomics has been applied to EBC profiling to identify metabolic phenotypes (“metabotypes”) of relevance in respiratory medicine. We aimed at verifying if NMR-based metabolomics of EBC, combined with statistical analysis, could find differences in metabolomic profiles between groups of subjects occupationally exposed to levels of airborne inhalable dust, phenol, formaldehyde and volatile organic compounds (VOCs) below regulatory limits. Samples were collected from 20 blue-collar workers without wearing a mask (therefore “exposed” to ambient air) and after wearing a mask (“not exposed”). This procedure was only allowed after the standard air quality tests had shown levels of airborne xenobiotics below the occupational exposure limit or even below the LOD. Ten white-collar controls were also included. After partial least squares discriminant analysis, the exposed to the controlled plant environment and the not exposed groups were clearly separated, and discrimination was due to alteration of fatty acids and alcohols, whose statistical significance was also evaluated. Our results show that NMR-based metabolomics of EBC is a useful tool that has the potential to be successfully used in occupational health to distinguish between subjects exposed and non-exposed to very low airborne levels of chemicals.

Biomonitoring of workers using nuclear magnetic resonance-based metabolomics of exhaled breath condensate: A pilot study / Maniscalco, Mauro; Paris, Debora; Melck, Dominique; Chiariello, Nunzio; Di Napoli, Fiorentino; Manno, Maurizio; Iavicoli, Ivo; Motta, Andrea. - In: TOXICOLOGY LETTERS. - ISSN 0378-4274. - 298:(2018), pp. 4-12. [10.1016/j.toxlet.2018.10.018]

Biomonitoring of workers using nuclear magnetic resonance-based metabolomics of exhaled breath condensate: A pilot study

Maniscalco, Mauro;Melck, Dominique;Manno, Maurizio;Iavicoli, Ivo;
2018

Abstract

Exhaled breath condensate (EBC) is a non-invasive biological matrix that allows easy access to the lung epithelial lining fluid. It can provide, for instance, useful biochemical information in workers following inhalatory exposure. Recently, nuclear magnetic resonance (NMR)-based metabolomics has been applied to EBC profiling to identify metabolic phenotypes (“metabotypes”) of relevance in respiratory medicine. We aimed at verifying if NMR-based metabolomics of EBC, combined with statistical analysis, could find differences in metabolomic profiles between groups of subjects occupationally exposed to levels of airborne inhalable dust, phenol, formaldehyde and volatile organic compounds (VOCs) below regulatory limits. Samples were collected from 20 blue-collar workers without wearing a mask (therefore “exposed” to ambient air) and after wearing a mask (“not exposed”). This procedure was only allowed after the standard air quality tests had shown levels of airborne xenobiotics below the occupational exposure limit or even below the LOD. Ten white-collar controls were also included. After partial least squares discriminant analysis, the exposed to the controlled plant environment and the not exposed groups were clearly separated, and discrimination was due to alteration of fatty acids and alcohols, whose statistical significance was also evaluated. Our results show that NMR-based metabolomics of EBC is a useful tool that has the potential to be successfully used in occupational health to distinguish between subjects exposed and non-exposed to very low airborne levels of chemicals.
2018
Biomonitoring of workers using nuclear magnetic resonance-based metabolomics of exhaled breath condensate: A pilot study / Maniscalco, Mauro; Paris, Debora; Melck, Dominique; Chiariello, Nunzio; Di Napoli, Fiorentino; Manno, Maurizio; Iavicoli, Ivo; Motta, Andrea. - In: TOXICOLOGY LETTERS. - ISSN 0378-4274. - 298:(2018), pp. 4-12. [10.1016/j.toxlet.2018.10.018]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/728099
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