Why exhaled breath analysis is an appealing option
Personalized medicine requires capturing complex and dynamic biological information of each individual patient. Despite the significant advances in the field, these technologies require extensive laboratory procedures and thereby, they cannot be easily applied in daily clinical practice. Therefore, the present challenge is to bring molecular medicine to point-of-care and the field of breathomics (exhaled breath analysis) is a promising candidate.
Already in the time of Hippocrates (460-370 BC), the ancient Greek physicians understood that certain diseases produced characteristic breath odours that could be used for their diagnosis[i]. For example, a patient with diabetes often had a ‘fruity acetone smell’, advanced liver disease had a ‘musty and fishy smell’ and lung abscess had a ‘putrid smell’[ii]
Composition of metabolites and VOCs
The rationale behind this is that exhaled breath contains a composite mixture of metabolites and their fragments (volatile organic compounds: VOCs) that give insight into the metabolic state of a patient. These compounds arise from local (i.e. airways) and systemic metabolic processes in the body, resident microbe in the airways or they can simply originate from inhaled and subsequently exhaled compounds present in the environment. VOCs can be measured using different analytical techniques and currently two approaches are commonly used for analysing VOCs in exhaled breath: electronic noses (eNoses) and Mass spectrometry (MS) such as Gas-chromatography-MS (GC-MS) which are the two ends of the spectrum of available techniques.
GC-MS versus eNose
Gas chromatography is a complex laboratory technique to separate a gas mixture, our breath, into individual components. Mass spectroscopy is an analytical technique to measure the mass-to-charge ratio of ions. This ratio is different for the various ions. An ion is an atom or molecule with an electrical charge. Mass spectroscopy can determine the separated ion based on the ratio and hence can indicate which VOC is present in our breath. The two techniques combined enables the detection of individual components in our breath, which is particularly useful for pathophysiologic research. However, clinical implementation of the technique in daily practice is rather complex as it is time consuming and requires offline laboratory procedures using expensive equipment run by highly trained personnel.
On the other hand, eNoses are based on cross-reactive nonspecific sensor arrays purposely not identifying individual VOCs. The VOCs competitively interact with the sensors allowing multiple VOCs to bind to the same sensor based on their affinity for both the sensor and its substrate. Likewise, multiple sensors interact with the same volatile. Notably, this is comparable to the powerful mammalian olfactory system and results in a pattern of firing sensors that is driven by the complete mixture of VOCs. This pattern, “breath profile”, is a snapshot of your metabolic state and includes the interactions and networks between VOCs that allow for powerful pattern recognition, in much the same way the powerful mammalian olfactory system works. Major advantages of this approach are e.g. direct measurements (no sampling and storage errors), low-cost hardware and real-time analysis which enables immediate feedback in the doctor’s office.
Breathomix’ approach is based on a cloud-connected eNose (SpiroNose) that enables cutting-edge molecular pattern recognition at the point-of-care. The latter has proven to be most suitable for effective diagnosis[iii], phenotyping[iv], and therapy response prediction[v] in individual patients.
[i] Souvik Das, Saurabh Pal, and Madhuchhanda Mitra; Significance of Exhaled Breath Test in Clinical Diagnosis: A Special Focus on the Detection of Diabetes Mellitus; J Med Biol Eng. 2016; 36(5): 605–624; doi: 10.1007/s40846-016-0164-6
[ii] F. Di Francesco, R. Fuoco, M.G. Trivella, A. Ceccarini; Breath analysis: trends in techniques and clinical applications; Microchemical Journal 79 (2005) 405 – 410; doi:10.1016/j.microc.2004.10.008
[iii] R. de Vries, J.M. van den Heuvel, Y.W.F. Dagelet, E. Dijkers, T. Fabius, F.H.C. de Jongh, P.M.C. Jak, E.G. Haarman, S. Kester, M. Bekkers, M.M. van den Heuvel, P. Baas, J.C.C.M. in t Veen, A.H. Maitland-van der Zee, and P.J. Sterk; Prospective Early Detection of Lung Cancer in COPD Patients by Electronic Nose Analysis of Exhaled Breath; C110. THE FUTURE OF LUNG CANCER BIOMARKERS: WHERE SHOULD WE LOOK?. May 1, 2019, A7451-A7451; DOI: 10.1164/ajrccm-conference.2019.199.1_MeetingAbstracts.A7451
[iv] Rianne de Vries, Yennece W.F. Dagelet, Pien Spoor, Erik Snoey, Patrick M.C. Jak, Paul Brinkman, Erica Dijkers, Simon K. Bootsma, Fred Elskamp, Frans H.C. de Jongh, Eric G. Haarman, Johannes C.C.M in ‘t Veen, Anke-Hilse Maitland-van der Zee, Peter J. Sterk; Clinical and inflammatory phenotyping by breathomics in chronic airway diseases irrespective of the diagnostic label; European Respiratory Journal Jan 2018, 51 (1) 1701817; DOI: 10.1183/13993003.01817-2017
[v] R. de Vries, M. Muller, V. van der Noort, W.S.M.E. Theelen, R.D. Schouten, K. Hummelink, S.H. Muller, M. Wolf-Lansdorf, J.W.F. Dagelet, K. Monkhorst, A.H. Maitland-van der Zee, P. Baas, P.J. Sterk, M.M. van den Heuvel; Prediction of response to anti-PD-1 therapy in patients with non-small-cell lung cancer by electronic nose analysis of exhaled breath; Annals of Oncology, Volume 30, Issue 10, 1660 – 1666; DOI: 10.1093/annonc/mdz279
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