Breath Analysis as a Potential and Non-Invasive Frontier in Disease Diagnosis: An Overview

Metabolites

Jorge Pereira³  Priscilla Porto-Figueira³  Carina Cavaco³  Khushman Taunk²  Srikanth Rapole²  Rahul Dhakne¹  Hampapathalu Nagarajaram¹  José S. Câmara³ 

[1] Laboratory of Computational Biology, Centre for DNA Fingerprinting & Diagnostics, Hyderabad, Andhra Pradesh 500 001, India; E-Mails:;Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune 411007, India; E-Mails:;CQM—Centro de Química da Madeira, Universidade da Madeira, Campus Universitário da Penteada, Funchal 9000-390, Portugal; E-Mails:

关键词: Exhaled Breath (EB) analysis;    Disease diagnosis;    volatile organic compounds (VOCs);    volatile fingerprint;   

DOI  :  10.3390/metabo5010003

来源: mdpi

【 摘 要 】

Currently, a small number of diseases, particularly cardiovascular (CVDs), oncologic (ODs), neurodegenerative (NDDs), chronic respiratory diseases, as well as diabetes, form a severe burden to most of the countries worldwide. Hence, there is an urgent need for development of efficient diagnostic tools, particularly those enabling reliable detection of diseases, at their early stages, preferably using non-invasive approaches. Breath analysis is a non-invasive approach relying only on the characterisation of volatile composition of the exhaled breath (EB) that in turn reflects the volatile composition of the bloodstream and airways and therefore the status and condition of the whole organism metabolism. Advanced sampling procedures (solid-phase and needle traps microextraction) coupled with modern analytical technologies (proton transfer reaction mass spectrometry, selected ion flow tube mass spectrometry, ion mobility spectrometry, e-noses, etc.) allow the characterisation of EB composition to an unprecedented level. However, a key challenge in EB analysis is the proper statistical analysis and interpretation of the large and heterogeneous datasets obtained from EB research. There is no standard statistical framework/protocol yet available in literature that can be used for EB data analysis towards discovery of biomarkers for use in a typical clinical setup. Nevertheless, EB analysis has immense potential towards development of biomarkers for the early disease diagnosis of diseases.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.