Distinguishing smoke exposure from emerging pathology: temporal metabolomic profiling in a rat model of cigarette smoke-induced lung injury

Background COPD is a prevalent, progressive respiratory disorder for which cigarette smoking represents the predominant modifiable risk factor. To distinguish metabolites merely indicative of tobacco exposure from those specifically associated with incipient COPD-related pathological changes, we employed untargeted ultra-high-performance liquid chromatography–mass spectrometry to comprehensively profile serum and urine metabolomes in a time-stratified rat model of chronic cigarette smoke exposure. This approach enabled systematic characterization of dynamic, time-dependent metabolic perturbations and facilitated the identification of candidate metabolites linked both to smoke exposure and to early-stage lung injury. Methods We set up four groups of rat models treated with smoking method at different times to evaluate and understand the development process of COPD from the onset to the stable stage. The animal models were verified by pathological experiments, and the serum and urine of rats were analyzed by mass spectrometry to compare the changes of urine and serum metabolites in different periods of smoking. As a first step toward identifying exposure markers and candidate pathology-related metabolites in at-risk smokers, we sought to identify metabolites associated with cigarette smoke exposure and early smoke-induced pulmonary changes. Results Four candidate metabolites were identified by non-targeted metabolomic analysis, and receiver work characteristics analysis showed that all types of metabolomic data had high predictive power, with area under the curve values exceeding 0.75. These results suggest that the identified metabolites can distinguish cigarette smoke exposure from unexposed conditions and may be associated with COPD-like pulmonary pathology. Conclusion This study profiled serum and urine metabolites in a time-stratified rat model of cigarette smoke-induced lung injury. Using multivariate and univariate analyses with correction for multiple testing, we identified four metabolites associated with smoke exposure and with emerging smoke-induced lung pathology.