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Untargeted metabolic profiling of saliva by liquid chromatography-mass spectrometry for the identification of potential diagnostic biomarkers of asthma

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journal contribution
posted on 21.07.2016 by Aditya Malkar, Emma Wilson, Tim Harrison, Dominick Shaw, Colin Creaser
Current clinical tests employed to diagnose asthma are inaccurate and limited by their invasive nature. New metabolite profiling technologies offer an opportunity to improve asthma diagnosis using non-invasive sampling. A rapid analytical method for metabolite profiling of saliva is reported using ultra-high performance liquid chromatography combined with high resolution time-of-flight mass spectrometry (UHPLC-MS). The only sample pre-treatment required was protein precipitation with acetonitrile. The method has been applied to a pilot study of saliva samples obtained by passive drool from well phenotyped patients with asthma and healthy controls. Stepwise data reduction and multivariate statistical analysis was performed on the complex dataset obtained from the UHPLC-MS analysis to identify potential metabolomic biomarkers of asthma in saliva. Ten discriminant features were identified that distinguished between moderate asthma and healthy control samples with an overall recognition ability of 80% during training of the model and 97% for model cross-validation. The reported method demonstrates the potential for a non-invasive approach to the clinical diagnosis of asthma using mass spectrometry-based metabolic profiling of saliva.

Funding

The study was funded by an internal grant for the Universities of Loughborough and Nottingham.

History

School

  • Science

Department

  • Chemistry

Published in

Analytical Methods: advancing methods and applications

Volume

8

Pages

5407 - 5413 (7)

Citation

MALKAR, A. ... et al, 2016. Untargeted metabolic profiling of saliva by liquid chromatography-mass spectrometry for the identification of potential diagnostic biomarkers of asthma. Analytical Methods, 8 (27), pp. 5407 - 5413.

Publisher

© Royal Society of Chemistry

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

17/06/2016

Publication date

2016-06-20

Notes

This paper was accepted for publication in the journal Analytical Methods and the definitive published version is available at http://dx.doi.org/10.1039/C6AY00938G

ISSN

1759-9679

Language

en

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