Not all vapor exposures are the same: researchers reveal that device manufacturing, flavor choices and vaping intensity leave distinct molecular imprints on oral cells, offering new clues to the biological effects of e-cigarette use.
Study: Multidimensional exposure architecture modulates vaping-associated transcriptional 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, which varies with the amount of vaping, the type of device and the flavor used.
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Vaping refers to the use of electronic cigarettes (e-cigarettes), a growing 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 flavors. Devices have moved from first-generation cigalike vapors 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 young people has raised concerns about whether it could increase cigarette use, especially among those who were not previously smokers. The long-term safety and health effects of vaping remain unclear at this time.
Vapors produce toxic substances called harmful and potentially harmful constituents (HPHCs), similar to those found in cigarette smoke, although in lower concentrations and in fewer numbers. Some of these are carbonyl compounds, volatile organic compounds, free radicals and heavy metals. Many of these affect genes expressed in pathways that include immune inflammation, cancer, cardiovascular disease and respiratory disease.
Thus, transcriptional regulation could provide clues about potential vaping damage. Epigenetic changes also occur in association with vaping, which is linked to disease risk. In addition, the mouth is the first part of the body directly exposed to cigarette smoke or e-cigarette aerosol. Previous research, some by the same authors, showed that functionally important genes in oral and other epithelia were affected by both vaping and smoking, albeit to different degrees, creating distinct but partially shared profiles.
The current study therefore examines how vapor use and product characteristics independently and collectively modulate 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 in 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 assessed using pack years and plasma cotinine concentrations. The researchers also investigated whether vaping device production and e-liquid flavor affected gene expression patterns.
Participants differed substantially in their history of tobacco use. The median age of vapers, smokers and non-users was 28, 42 and 24.5 years, respectively. Vapers had used e-cigarettes for an average of three years, while smokers had smoked for an average of 23 years. Despite these differences, both the vaping and smoking groups showed similarly elevated plasma cotinine levels, with median concentrations of 114 ng/mL and 122 ng/mL, respectively, compared with only 2.5 ng/mL among nonusers.
Vaping changes gene expression
Confirming previous studies, both vaping and smoking were associated with extensive changes in gene activity compared to non-users. However, the researchers found that gene expression patterns associated with vaping were influenced by multiple aspects of exposure, not 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 measures of exposure. About 31% of DEGs showed the same change in direction when assessed in relation to cumulative e-liquid consumption, while the corresponding figures were 44% for cumulative e-nicotine exposure, 43% for years of vaping, and 51% for plasma cotinine levels. Overall, only 27% of vaping-related DEGs were consistently associated with all exposure metrics examined.
Product characteristics also appeared to modulate the transcriptional response. When the analysis was restricted to users of third- and multi-generation devices, 58% of DEGs were shared between the two groups, suggesting that newer types of devices produce relatively similar molecular signatures. No comparable patterns were observed for older generation devices, likely because relatively few participants used them. Flavor choice also affected gene activity, with 31% of primary DEGs remaining significant among fruit flavor users and 64% among users who regularly used multiple flavor types.
Overall, the findings indicate that no single smoking trait can fully explain the observed gene expression changes. In contrast, 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 significantly between product classes, with newer generation devices and the use of multiple flavor types producing the most pronounced and consistent transcriptional alterations. This suggests that product design and composition 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. While smoking-related gene expression changes followed a relatively consistent dose-response pattern, vaping-related changes 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 corresponding shifts with pack years and 60% when analyzed against plasma cotinine. About 54% of DEGs were common across all smoking measures, suggesting a more uniform dose–response relationship.
Some of the DEGs overlapped between the two categories of nicotine users, but not all. This indicates non-identical biological consequences of exposure to vaping versus smoking.
Notably, about 60% of the genes altered in vapers were not altered in smokers, suggesting that vaping is associated with a significant number of molecular changes that are distinct from those associated with tobacco fuel use.
Pathways affected
Functional pathway analyzes showed that both vaping and smoking disrupt gene networks associated with cancer-related processes and cell signaling. Specifically, the RHO GTPase cycle was affected by both types of use. This pathway is key to cell growth, movement and organization.
In addition to these shared effects, vaping and smoking also altered different 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 affect cells through partly different molecular mechanisms.
conclusions
Findings indicate that vaping disrupts gene transcription across multiple measures of exposure, including cumulative e-liquid use, cumulative e-nicotine exposure, years of vaping, plasma cotinine levels, and device nature (eg, flavor type and device build). 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 outcome, the findings provide molecular evidence of biological effects, but do not prove 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 on the market today to improve public health and clinical practice.
The researchers also noted several limitations, including the relatively small number of first- and second-generation device users and the absence of fourth-generation device users in the study population, which may affect how generalizable some findings are to specific products.
