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Breath Analysis in Disease Diagnosis: Methodological Considerations and Applications

Department of Life, Health & Chemical Sciences, Chemistry and Analytical Sciences, The Open University, Walton Hall, Milton Keynes, MK7 6AA, UK
Author to whom correspondence should be addressed.
Metabolites 2014, 4(2), 465-498;
Received: 7 February 2014 / Revised: 2 June 2014 / Accepted: 9 June 2014 / Published: 20 June 2014
(This article belongs to the Special Issue Breath Analysis in Metabolomics)
PDF [339 KB, uploaded 20 June 2014]


Breath analysis is a promising field with great potential for non-invasive diagnosis of a number of disease states. Analysis of the concentrations of volatile organic compounds (VOCs) in breath with an acceptable accuracy are assessed by means of using analytical techniques with high sensitivity, accuracy, precision, low response time, and low detection limit, which are desirable characteristics for the detection of VOCs in human breath. “Breath fingerprinting”, indicative of a specific clinical status, relies on the use of multivariate statistics methods with powerful in-built algorithms. The need for standardisation of sample collection and analysis is the main issue concerning breath analysis, blocking the introduction of breath tests into clinical practice. This review describes recent scientific developments in basic research and clinical applications, namely issues concerning sampling and biochemistry, highlighting the diagnostic potential of breath analysis for disease diagnosis. Several considerations that need to be taken into account in breath analysis are documented here, including the growing need for metabolomics to deal with breath profiles. View Full-Text
Keywords: volatile organic compounds (VOCs); trace gas analysis; volatile biomarkers; metabolomics volatile organic compounds (VOCs); trace gas analysis; volatile biomarkers; metabolomics
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Lourenço, C.; Turner, C. Breath Analysis in Disease Diagnosis: Methodological Considerations and Applications. Metabolites 2014, 4, 465-498.

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