Moving towards composite biomarkers for disease management
Relevant and reliable biomarkers are the key to implementing personalised medicine in clinical practice. While single biomarkers have guided the treating physicians and researchers for decades, scientific developments over the past decades, suggest that it might be time to move toward the use of composite biomarkers [i].
What is a biomarker?
A biomarker is a (detectable) molecule or a physiological feature that could be an indicator of a normal or abnormal biological state within the body [iii]. For example, blood glucose (a molecular trait) and body temperature (a physiological feature) are two very well-known biomarkers that are widely used in clinical practice and even by patients/ caregivers at home. The improvements in science and technology have enabled the search for better biomarkers that could potentially enable a more personalized approach to disease diagnosis, prognosis, treatment and even prediction [i]. But why despite the discovery of hundreds or even thousands of candidates every year, very few biomarkers are being implemented in clinical practice? [ii]
From single to composite biomarkers
The fact is that the improvements in science and technology have also resulted in a better understanding of the human body and this has led to the realization that biological systems are highly complex and multidimensional. This means that a single biomarker is often not enough to capture the full picture of this complex entity and efforts to delineate singular biomarkers for personalized disease management seem to be too simplistic [ii]. For example, in asthma, a disorder that affects millions of individuals both young and old, the lungs, the immune system and the environment interact with each other. The interactions between thousands of molecules and cells result in complex patterns of underlying molecular mechanisms that seem to differ among individuals, requiring different treatment approaches [iii]. Therefore, assessment of patterns within the complex biological samples rather than a single biomarker can lead to a more accurate reflection of the health status of an individual. This is where pattern recognition algorithms and artificial intelligence are providing their value in the discovery of composite, multidimensional biomarkers that are maximally informative for the actual condition of individual patients [ii]. These pattern recognition-based technologies have great potential for implementation in clinical practice, especially the ones providing direct and immediate results. Electronic noses (eNose) that are linked to online cloud applications are such technologies that are specifically designed for this approach.
“Pattern recognition algorithms and artificial intelligence are providing their value in the discovery of composite, multidimensional biomarkers that are maximally informative for the actual condition of individual patients.”
Composite biomarkers in exhaled breath
Exhaled breath is a complex biological sample containing a mixture of volatile organic compounds (VOCs), that originates from metabolic processes in the body and gives insight into the health state of an individual. eNoses are based on cross-reactive sensors and together with pattern recognition algorithms, they can identify VOC mixtures that are specific to a disease or a subtype of a disease [ii, iv]. Sensors in the eNoses react to different VOCs without identifying single metabolites. 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. Similar to fingerprints, VOC mixtures generate a unique pattern, ”breathprints”, which makes them suitable as composite biomarkers. Non-invasive and easy-to-use nature of the eNoses makes them highly suitable for individuals of all ages. Additionally, when coupled with cloud applications, the results of breath analysis by the eNose can be made readily available in real-time within seconds [v]. Breathomix´ cloud connected SpiroNose® is such a technology that is designed to be used at the point of care.
From discovery to clinical practice
The quality and clinical value of a biomarker needs to be confirmed by replication of the results in an independent population (external validation). However, the usefulness of biomarkers either single or composite is often challenged by suboptimal validation, and the discovery of new biomarkers moves much faster than standardization efforts. The SpiroNose® is a technically and clinically validated technology that provides a simple and standardized approach to exhaled breath analysis [vi]. The technology is suitable for diagnosis and subtyping (aka phenotyping) of diseases such as asthma, chronic obstructive pulmonary disease, interstitial lung disease, lung cancer and respiratory infectious diseases [v, ix]. In addition, the technology has the potential to prevent ineffective immunotherapy in patients with non-small cell lung cancer [viii]. These findings illustrate the great potential of breath analysis using SpiroNose for personalized medicine. In fact, the specific features of SpiroNose have enabled international collaborations and large-scale real-world studies that are paving the last steps towards clinical implementation of the technology for a wide range of diseases.
[i] J. Skov, K. Kristiansen, J. Jespersen and P. Olesen. “Status and perspective of biomarker validation for diagnosis, stratification, and treatment” Public Health, 2020.
[ii] R. de Vries and P. J. Sterk. “eNose breathprints as composite biomarker for real-time phenotyping of complex respiratory diseases” J Allergy Clin Immunol, 2020.
[iii] R. M. Callif. “Biomarker definitions and their applications” Experimental Biology and Medicine, 2018.
[iv] M. V. Farraia, J. C. Rufo et al. “The electonic nose technology in clinical diagnosis: a systematic review” Porto Biomed J, 2019.
[v] R. de Vries, Y. W. Dagelet et al. “Clinical and inflammatory phenotyping by breathomics in chronic airway diseases irrespective of the diagnostic label” Eur Respir J, 2018.
[vi] R. de Vries. et al. “Integration of electronic nose technology with spirometry: validation of new approach for exhaled breath analysis” J Breath Res, 2015.
[vii] C Moor et al. “Exhaled breath analysis by use of eNose technology: a novel diagnostic tool for interstitial lung disease” Eur Respir J, 2020.
[viii] R. de Vries et al. “Prediction of response to anti-PD-1 therapy in patients with non-small-cell lung cancer by electronic nose analysis of exhaled breath” Anals of Oncology, 2019.
[ix] R. de Vries et al. “Ruling out SARS-CoV-2 infection using exhaled breath analysis by electronic nose in a public health setting” medRxiv, 2021.
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