Not all vaping exposures are the same: researchers reveal that device generation, flavor choices, and vaping intensity each leave distinct molecular fingerprints in the mouth's cells, offering new clues about the biological effects of e-cigarette use.
Study: Multidimensional exposure architecture shapes vaping-associated transcriptomic dysregulation in oral epithelium. Image credit: Pupsiki/Shutterstock.com
A recent study published in the journal Frontiers in Oncology investigated how vaping affects gene activity in the oral epithelium, varying with the amount vaped, device type, and flavor used.
How modern vaping evolution changes vaping effects
Vaping refers to the use of electronic cigarettes (e-cigarettes), a rising trend among young people since their introduction about 20 years ago. Most contain e-liquids with varying concentrations of nicotine, mixed with propylene glycol, glycerin, or vegetable glycerin, and various flavorings. The devices have moved from first-generation cigalike vapes to second-, third-, and fourth-generation devices that use more advanced designs, deliver more nicotine per dose, and enhance the user experience with thousands of flavor combinations, including mint, sweet, and fruit.
Vaping is widely marketed as a less harmful alternative to conventional smoking, and as a smoking cessation aid. Its widespread use among youth has triggered concerns as to whether it could increase cigarette use, especially among those who were not previously smokers. The safety and long-term health effects of vaping remain unclear at present.
Vapes produce toxic substances dubbed harmful and potentially harmful constituents (HPHCs), similar to those found in tobacco smoke, albeit at lower concentrations and in fewer numbers. Some of them are carbonyl compounds, volatile organic compounds, free radicals, and heavy metals. Many of these affect genes expressed in pathways involving immune inflammation, cancer, cardiovascular disease, and respiratory disease.
Thus, transcriptional regulation could offer clues about the potential harm of vaping. Epigenetic changes also occur in association with vaping, which is linked with disease risk. Moreover, the mouth is the first body site to be directly exposed to cigarette smoke or e-cigarette aerosol. Previous research, some by the same authors, showed that functionally important genes in the oral and other epithelia were affected by both vaping and smoking, though to different extents, producing distinctive but partly shared profiles.
The current study, therefore, examines how vape use and product characteristics independently and collectively shape gene expression profiles in the oral epithelium.
Researchers compare vapers, smokers, and non-users
The researchers analyzed oral epithelial cells from 35 e-cigarette users, 24 cigarette smokers, and 24 non-users to investigate how vaping and smoking affect gene activity. Using RNA sequencing, they measured changes across the entire transcriptome and examined how these changes related to different measures of nicotine exposure and product use.
For vapers, the team assessed lifetime e-liquid consumption, cumulative nicotine exposure from e-cigarettes, years of vaping, and plasma cotinine levels, a biomarker of recent nicotine intake. For smokers, exposure was evaluated using pack-years and plasma cotinine concentrations. The researchers also explored whether vaping device generation and e-liquid flavor influenced gene expression patterns.
Participants differed substantially in their tobacco-use histories. The median ages of vapers, smokers, and non-users were 28, 42, and 24.5 years, respectively. Vapers had used e-cigarettes for a median of three years, while smokers had smoked for a median of 23 years. Despite these differences, both vaping and smoking groups showed similarly elevated plasma cotinine levels, with median concentrations of 114 ng/mL and 122 ng/mL, respectively, compared with just 2.5 ng/mL among non-users.
Vaping alters gene expression
Corroborating previous studies, both vaping and smoking were associated with widespread changes in gene activity compared with non-users. However, the researchers found that vaping-related gene expression patterns were influenced by multiple aspects of exposure rather than by nicotine dose alone.
Among the 3,124 differentially expressed genes (DEGs) identified in vapers, only a subset remained significantly altered when the data were reanalyzed using different exposure measures. Approximately 31% of DEGs showed the same directional change when assessed against cumulative e-liquid consumption, while corresponding figures were 44% for cumulative e-nicotine exposure, 43% for years of vaping, and 51% for plasma cotinine levels. Overall, just 27% of vaping-associated DEGs were consistently linked to all exposure metrics examined.
Product characteristics also appeared to shape the transcriptomic response. When the analysis was limited to users of third-generation and multiple-generation devices, 58% of DEGs were shared between the two groups, suggesting that newer device types produce relatively similar molecular signatures. Comparable patterns were not observed for earlier-generation devices, likely because relatively few participants used them. Flavor choice also influenced gene activity, with 31% of primary DEGs remaining significant among fruit-flavor users and 64% among users who regularly used multiple flavor types.
Taken together, the findings indicate that no single vaping characteristic can fully explain the observed gene-expression changes. Instead, different dimensions of exposure, including nicotine intake, vaping duration, device generation, and flavor use, appear to contribute distinct but overlapping effects on the oral epithelium. The magnitude of these changes varied considerably across product categories, with later-generation devices and the use of multiple flavor types producing the most pronounced and consistent transcriptional alterations. This suggests that product design and formulation may play an important role in shaping the biological effects of vaping.
Overall, the results suggest that vaping exposure is more heterogeneous at the molecular level than smoking exposure. Whereas smoking-related gene expression changes followed a relatively consistent dose-response pattern, vaping-associated alterations were distributed across multiple exposure characteristics, indicating a more complex biological response to e-cigarette use.
Smoking and gene expression
Among smokers, 57% of DEGs showed concordant shifts with pack-years, and 60% when analyzed against plasma cotinine. About 54% of DEGs were common across all smoking metrics, suggesting a more uniform dose-response relationship.
Some of the DEGs overlapped between the two nicotine user categories, but not all. This indicates non-identical biological consequences of vaping versus smoking exposure.
Notably, approximately 60% of the genes altered in vapers were not altered in smokers, suggesting that vaping is associated with a substantial number of molecular changes that are distinct from those linked to combustible tobacco use.
Affected pathways
Functional pathway analyses showed that both vaping and smoking disrupt gene networks associated with cancer-related and cell-signaling processes. In particular, the RHO GTPase cycle was affected by both types of use. This pathway is key to the growth, movement, and organization of cells.
In addition to these shared effects, vaping and smoking also altered distinct biological pathways. Vaping was linked to disruptions in pathways involved in cilia formation and chromosome replication, while smoking more strongly affected pathways related to vascular signaling and neutrophil activity, suggesting that the two exposures may influence cells through partly different molecular mechanisms.
Conclusions
The findings suggest that vaping disrupts gene transcription across multiple exposure measures, including cumulative e-liquid use, cumulative e-nicotine exposure, years vaped, plasma cotinine levels, and the nature of the device (i.e., flavor type and device generation). The study also reflects differences in how cells respond at the molecular level to vaping versus smoking.
Because the study measured changes in gene expression rather than clinical disease outcomes, the findings provide molecular evidence of biological effects but do not demonstrate that vaping directly causes specific diseases.
The authors suggest that, based on this evidence, regulatory and research approaches may need to consider the health risks posed by different types of devices and flavors in the market today to improve public health and clinical practice.
The researchers also noted several limitations, including relatively small numbers of users of first- and second-generation devices and the absence of fourth-generation device users in the study population, which may affect how broadly some product-specific findings can be generalized.
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