Abstract
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.
Highlights
Non-communicable diseases, such as cardiovascular (CVDs), oncologic (ODs), neurodegenerative (NDDs), and chronic respiratory diseases, are the major causes of death in the developed countries [1]
We focus on based disease diagnosis (BADD) discussing on the current trends and innovations from sampling procedure to the final data analysis and diagnosis opportunities
A look into the breath analysis literature reveals a set of challenges and bottlenecks and they are as follows: (a) the data produced in breath analysis are biologically complex and are very large in size; (b) the data contain several sources of variance, which include information of interest, and irrelevant variance associated with biological variation or noise [252]; (c) reported studies have very often used insufficient number of patient and control samples as compared to the large number of volatile organic compounds (VOCs) measured [251] which results in false positive correlations and (d) many of the studies suffered from confounding variables and statistical misconceptions [251,253]
Summary
Non-communicable diseases, such as cardiovascular (CVDs), oncologic (ODs), neurodegenerative (NDDs), and chronic respiratory diseases, are the major causes of death in the developed countries [1]. O2 and CO2 diffuse passively between blood and breath according to their concentration gradients across the alveolar-capillary junction, dragging together thousands of other very low abundant volatile organic compounds (VOCs), as long as they exhibit significant vapour pressures [15] These VOCs, estimated in over 3000, account for less than 100 parts per million (ppm) of the total breath volume [13,16,17], part of them, as acetone, isoprene and propanol, are more abundant, existing in the ppm to sub ppm range, while ketones, aldehydes and pentane, for instance, occur at even lower concentrations, at the parts per billion (ppb) to parts per trillion (ppt) levels [18,19,20,21]. EB volatile composition has the potential to assess disease diagnosis, and its severity, progression and response to treatment, many improvements have to be done at the methodological level to achieve this goal
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