eNose breathprints as composite biomarker for real-time phenotyping of complex respiratory diseases
REVIEW
Take home message: eNose technology offers a powerful, non-invasive tool for real-time diagnosis and phenotyping of respiratory diseases. By analyzing breath profiles as composite biomarkers, it provides rapid, accurate insights that support personalized medicine and improve clinical decision-making.
Summary
Respiratory diseases, such as asthma, COPD, and lung cancer, are highly complex and diverse, making accurate diagnosis and tailored treatment challenging. Current diagnostic strategies rely on identifying specific biomarkers, but many of these fail to deliver consistent clinical value due to the inherent complexity of biological systems. Electronic nose (eNose) technology offers a promising alternative by capturing patterns of volatile organic compounds (VOCs) from exhaled breath, serving as composite, multidimensional biomarkers.
The eNose is a metabolomics platform that uses an array of sensors sensitive to groups of VOCs. Exhaled VOCs reflect metabolic processes from the respiratory tract and systemic circulation, making eNose signals representative of a patient’s physiological state. Advanced pattern recognition algorithms interpret these signals, providing rapid, non-invasive assessments that are readily available in clinical settings through cloud-based analysis.
Clinical studies have shown promising results, particularly in diagnosing and phenotyping asthma, COPD, and lung cancer. The eNose can distinguish inflammatory phenotypes (e.g., eosinophilic, neutrophilic) in asthma and COPD patients, aiding in treatment decisions. In lung cancer, eNose analysis demonstrates high accuracy (80-90%) and could serve as a triage tool before more invasive procedures like CT scans. Furthermore, it shows potential in predicting non-responders to immunotherapy, enabling more precise treatment strategies.
Beyond these applications, the eNose has shown diagnostic potential in interstitial lung diseases and respiratory infections. It can also be valuable in rapidly identifying viral infections, including utility in COVID-19 diagnostics.
In summary, eNose technology offers a novel approach for real-time phenotyping and stratification of respiratory diseases, facilitating personalized medicine. Its ease of use, non-invasive nature, and integration with cloud computing make it a viable option for routine clinical practice, improving patient outcomes by enabling more accurate and timely diagnoses.
