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Electronic nicotine delivery systems use is associated with multi-omic biomarkers and prospective cardiopulmonary health outcomes

Gregory, A.; Xu, Z.; Pratte, K.; Berman, S.; Lu, R.; Suryadevara, R.; Chase, R.; Yun, J. H.; Saferali, A.; Hersh, C. P.; Silverman, E. K.; Bowler, R. P.; Crotty-Alexander, L.; Boueiz, A.; Castaldi, P. J.

2022-09-21 respiratory medicine
10.1101/2022.09.19.22280093 medRxiv
Show abstract

BackgroundElectronic nicotine delivery systems (ENDS) are driving an epidemic of vaping. Identifying biomarkers of vaping and dual use (concurrent vaping and smoking) will facilitate studies of the health effects of vaping. To identify putative biomarkers of vaping and dual use, we performed association analysis in an observational cohort of 3,892 COPDGene study participants with blood transcriptomics and/or plasma proteomics data and self-reported current vaping and smoking behavior. MethodsBiomarkers of vaping and dual use were identified through differential expression analysis and related to prospective health events over six years of follow-up. To assess the predictive accuracy of multi-biomarker panels, we constructed predictive models for vaping and smoking categories and prospective health outcomes. ResultsWe identified three transcriptomic and three proteomic associations with vaping, and 90 transcriptomic and 100 proteomic associations to dual use. Many of these vaping or dual use biomarkers were significantly associated with prospective health outcomes, such as FEV1 decline (three transcripts and 62 proteins), overall mortality (18 transcripts and 73 proteins), respiratory mortality (two transcripts and 23 proteins), respiratory exacerbations (13 proteins) and incident cardiovascular disease (24 proteins). Multimarker models showed good performance discriminating between vaping and smoking behavior and produced informative, modestly powerful predictions of future FEV1 decline, mortality, and respiratory exacerbations. ConclusionsIn summary, vaping and dual use are associated with RNA and protein blood-based biomarkers that are also associated with adverse health outcomes.

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