Breathomics

Breathomics is a subfield of metabolomics that analyzes volatile organic compounds in exhaled breath to characterize physiological and pathophysiological processes. By profiling the complete set of small molecules emitted in breath, breathomics seeks to identify diagnostic, prognostic, and monitoring biomarkers for human health. Analyses focus on comprehensive VOC inventories as well as pattern-based signatures, sometimes called breathprints, rather than single compounds alone. The approach combines analytical chemistry with bioinformatics and systems medicine.

Common analytical platforms include gas chromatography–mass spectrometry (GC-MS), gas chromatography–ion mobility spectrometry (GC-IMS), proton transfer reaction–mass spectrometry (PTR-MS), selected ion flow tube–mass spectrometry (SIFT-MS), and multi-sensor electronic nose devices. Sample collection methods aim to minimize contamination and variation, but standardization remains a challenge. Data analysis relies on multivariate statistics and machine learning to identify VOC panels associated with diseases such as lung cancer, chronic obstructive pulmonary disease, asthma, pneumonia, diabetes (notably acetone), and renal or hepatic dysfunction. VOCs like isoprene, acetone, ammonia, and various aldehydes have been studied, though associations are often context-dependent.

Clinical translation is ongoing; breathomics offers a noninvasive, rapid, and potentially low-cost tool for screening and monitoring, but reproducibility, external validation, and regulatory approval are major hurdles. The field emphasizes reproducible protocols, cross-cohort validation, and integration with other clinical and omics data.