Peltrini_2021_J._Breath_Res._15_027102.pdf (1.72 MB)

Volatile organic compounds in a headspace sampling system and asthmatics sputum samples

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journal contribution
posted on 26.01.2021, 15:09 by Rosa Peltrini, Rebecca L Cordell, Wadah Ibrahim, Michael J Wilde, Dahlia Salman, Amisha Singapuri, Beverley Hargadon, Christopher E Brightling, Paul Thomas, Paul S Monks, Salman Siddiqui
The headspace of a biological sample contains exogenous volatile organic compounds (VOCs) present within the sampling environment which represent the background signal. This study aimed to characterise the background signal generated from a headspace sampling system in a clinical site, to evaluate intra- and inter-day variation of background VOC and to understand the impact of a sample itself upon commonly reported background VOC using sputum headspace samples from severe asthmatics. The headspace, in absence of a biological sample, was collected hourly from 11am to 3pm within a day (time of clinical samples acquisition), and from Monday to Friday in a week, and analysed by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). Chemometric analysis identified 1120 features, 37 of which were present in at least the 80% of all the samples. The analyses of intra- and inter-day background variations were performed on 13 of the most abundant features, ubiquitously present in headspace samples. The concentration ratios relative to background were reported for the selected abundant VOC in 36 asthmatic sputum samples, acquired from 36 stable severe asthma patients recruited at Glenfield Hospital, Leicester, UK. The results identified no significant intra- or inter-day variations in compounds levels and no systematic bias of z-scores, with the exclusion of benzothiazole, whose abundance increased linearly between 11am and 3pm with a maximal intra-day fold change of 2.13. Many of the identified background features are reported in literature as components of headspace of biological samples and are considered potential biomarkers for several diseases. The selected background features were identified in headspace of all severe asthma sputum samples, albeit with varying levels of enrichment relative to background. Our observations support the need to consider the background signal derived from the headspace sampling system when developing and validating headspace biomarker signatures using clinical samples.

Funding

East Midlands Breathomics Pathology Node (EMBER)

Medical Research Council

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Midlands Asthma and Allergy Research Association (MAARA)

British Lung Foundation (Grant No. BLFPHD17-1)

History

School

  • Science

Department

  • Chemistry

Published in

Journal of Breath Research

Volume

15

Issue

2

Publisher

IOP Publishing

Version

VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an Open Access Article. It is published by IOP Publishing under the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/

Acceptance date

23/11/2020

Publication date

2021-01-11

Copyright date

2021

ISSN

1752-7155

eISSN

1752-7163

Language

en

Depositor

Prof Paul Thomas. Deposit date: 23 January 2021

Article number

027102