Trajectory-Informed Breathomics for Dynamic Mapping of Health and Disease: Toward a Health Navigation Framework
Suzuki, K. T.; Nagasaki, A.; Sakamoto, S.; Ouhara, K.; Hyogo, H.; Aikata, H.; Takemoto, T.; Tanaka, A.; Funakoshi, G.; Koyama, Y.; Ikeda, K.; Shin, W.; Sato, K.; Takata, T.; Sakumura, Y.; Miyauchi, M.
Show abstract
BackgroundMost diagnostic frameworks treat disease as static, overlooking its inherently dynamic and continuous progression. Noninvasive biomarkers capable of capturing physiological trajectories are critically needed for proactive health management. MethodsWe developed a breath-based health navigation framework using exhaled volatile organic compounds (VOCs) as integrative, real-time indicators of systemic metabolism and immunity. Breath profiles were collected from healthy individuals and patients with nonalcoholic steatohepatitis (NASH, recently redefined as metabolic dysfunction-associated steatohepatitis, MASH), hepatocellular carcinoma (HCC), and periodontitis (PD). Multidimensional analysis and trajectory-informed mapping were applied to project individual health states into a low-dimensional physiological space. ResultsRatio-normalized VOC profiles revealed disease-specific metabolic signatures across P450-derived and microbiota-derived compounds. Machine learning achieved high diagnostic accuracy for distinguishing health, NASH, HCC, and PD, while dimensionality reduction and topological analysis visualized a continuous progression from health to advanced liver disease. This approach captured preclinical shifts and transitional states often missed by static diagnostics. ConclusionsExhaled VOCs can serve as dynamic biomarkers for mapping health-disease transitions. By offering clinicians an intuitive map to locate patients within the health-disease continuum and anticipate their trajectories, this framework enables proactive decision-making and personalized intervention strategies. Collectively, our work points toward a paradigm shift in disease monitoring, with future integration into portable sensing technologies for noninvasive, continuous health-state assessment.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Metagenomics Combined with Activity-Based Proteomics Point to Gut Bacterial Enzymes that Reactivate Mycophenolate 93%
- Human gut commensal Alistipes timonensis modulates the host lipidome and delivers anti-inflammatory outer membrane vesicles to suppress colitis in an Il10-deficient mouse model 93%
- Gut Microbiota and Derived Metabolites Mediate Obstructive Sleep Apnea Induced Atherosclerosis 93%
Similar papers in this journal
- Systems analysis of gut microbiome influence on metabolic disease in HIV and high-risk populations 94%
- Metabolome-informed microbiome analysis refines metadata classifications and reveals unexpected medication transfer in captive cheetahs 94%
- Spatial metabolomics reveals localized impact of influenza virus infection on the lung tissue metabolome 93%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.