Short-Term Molecular Assessment of Peripheral Blood Transcriptomics and Urinary Metabolomics After Switching From Cigarettes to Heated Tobacco Products Using Machine Learning and Bayesian Network Modeling

Background Omics approaches can provide mechanistic insights into biological changes after changes in smoking behavior. However, data on short-term molecular changes after changes in tobacco product use are limited. Objectives To compare 5-day molecular changes in peripheral blood gene expression and urinary metabolites among participants who continued smoking combustible cigarettes (CS), switched to heated tobacco products (HTPs; DT3.0a or THS), or stopped smoking (SS) and to explore probabilistic relationships among molecular features using machine learning and Bayesian networks. Design We performed a secondary analysis of specimens collected from a randomized, controlled, inpatient, parallel-group intervention trial in which participants underwent a 5-day intervention. Methods Peripheral blood transcriptomics (mRNA and miRNA) were measured at baseline (Day 1) and at the end of intervention (Day 6). Urinary metabolomics were measured on Day 6. Differential expression screening used exploratory thresholds without adjustment for multiple testing. Machine learning was used for feature selection and classification of CS vs SS signatures; Bayesian network models represented conditional probabilistic dependencies among molecular features and downstream events under explicit modeling assumptions. Results Compared with the CS group, both HTP groups and the SS group showed shifts in blood transcriptomic signatures and urinary metabolites consistent with reduced oxidative stress and inflammatory signaling during the 5-day intervention. Classification models tended to place HTP profiles closer to those of the SS group than the CS group for modeled processes, while plaque-related outputs remained less conclusive. Conclusion Over 5 days, switching from smoking to HTPs was associated with molecular changes in peripheral blood gene expression and urinary metabolites that partially resembled those observed with smoking cessation. These exploratory findings do not establish long-term physiological status and should be interpreted within the measured matrices and the study’s limited duration and sample size. Further studies to confirm these findings in an external cohort are required.