Breathomics, a burgeoning field within metabolomics, focuses on the analysis of volatile organic compounds (VOCs) in exhaled breath, offering a promising non-invasive diagnostic tool for assessing the physiological and pathological states of the human body. This approach stands out for its simplicity, cost-effectiveness, and patient-friendly nature, making it an attractive alternative to traditional diagnostic methods that often involve invasive procedures. Recent advancements in detection techniques and standardized methods for breath sample collection have significantly enhanced our understanding of the relationship between breath molecules and diseases. Furthermore, the integration of machine learning and artificial intelligence has facilitated the identification of complex associations between breath VOCs and various diseases, broadening the scope of breath analysis from gastrointestinal and respiratory diagnostics to include thoracic diseases, neurological disorders, and pharmacokinetics. Despite these advancements, there remains a need for further investigation into the mechanisms linking breath biomarkers to diseases, as well as the development of robust predictive models and validation strategies for clinical applications.

This Research Topic aims to provide a comprehensive overview of the recent advancements in breathomics, with a particular focus on exploring the association between exhaled breath VOCs and diseases. The objective is to delve deeper into the scientific underpinnings of this emerging field and to assess its potential in modern healthcare. By addressing key questions such as the mechanisms of breath biomarkers, the influence of external factors on VOC composition, and the integration of multi-omics data, this research seeks to advance our understanding of breathomics and its applications in disease diagnostics and personalized medicine.

To gather further insights in the field of breathomics, we welcome articles addressing, but not limited to, the following themes:
- Investigating the mechanism of breath biomarkers and diseases, including unique VOC signatures and potential profiles for early disease screening.
- Advancements in breath analysis technologies, focusing on novel analytical techniques and standardized protocols for sample collection and analysis.
- Machine learning and AI-driven data processing in breathomics, including predictive model development and integration with multi-omics data.
- Clinical applications of breathomics, evaluating diagnostic tools, monitoring disease progression, and exploring personalized medicine and disease screening potential.

Topic editor Meixiu Sun is employed by WIM Spirare Health Technology Limited. The other Topic Editors declare no potential conflicts of interest with regards to the Research.

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Frontiers in Molecular Biosciences

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