In vitro and in silico genetic toxicity screening of flavor compounds and other ingredients in tobacco products with emphasis on ENDS

Abstract

Electronic nicotine delivery systems (ENDS) are regulated tobacco products and often contain flavor compounds. Given the concern of increased use and the appeal of ENDS by young people, evaluating the potential of flavors to induce DNA damage is important for health hazard identification. In this study, alternative methods were used as prioritization tools to study the genotoxic mode of action (MoA) of 150 flavor compounds. In particular, clastogen-sensitive (γH2AX and p53) and aneugensensitive (p-H3 and polyploidy) biomarkers of DNA damage in human TK6 cells were aggregated through a supervised three-pronged ensemble machine learning prediction model to prioritize chemicals based on genotoxicity. In addition, in silico quantitative structure-activity relationship (QSAR) models were used to predict genotoxicity and carcinogenic potential. The in vitro assay identified 25 flavors as positive for genotoxicity: 15 clastogenic, eight aneugenic and two with a mixed MoA (clastogenic and aneugenic). Twenty-three of these 25 flavors predicted to induce DNA damage in vitro are documented in public literature to be in e-liquid or in the aerosols produced by ENDS products with youth-appealing flavors and names. QSAR models predicted 46 (31%) of 150 compounds having at least one positive call for mutagenicity, clastogenicity or rodent carcinogenicity, 49 (33%) compounds were predicted negative for all three endpoints, and remaining compounds had no prediction call. The parallel use of these predictive technologies to elucidate MoAs for potential genetic damage, hold utility as a screening strategy. This study is the first high-content and high-throughput genotoxicity screening study with an emphasis on flavors in ENDS products.

Lung Damage Caused by Heated Tobacco Products and Electronic Nicotine Delivery Systems: A Systematic Review

“…Currently, there are over 15,000 different e-liquid flavors on the market [ 33 ]. The Flavor and Extract Manufacturers Association (FEMA) has identified over 1000 flavorings commonly used in e-liquids that may pose a respiratory hazard due to possible volatility and irritant properties.…”

“…Most studies have identified that aliphatic aldehydes (in fruity flavors), aromatic aldehydes (in sweet and spicy flavors), and non-phenolic terpenes (floral and citric flavors) generate more lung damage [ 34 , 35 , 36 ]. Another study identified two cinnamaldehyde flavor compounds, ethyl maltol, maltol, and propylene glycol, found in the flavors, as potentially genotoxic [ 33 ]. E-liquid without nicotine produced high levels of carbonyl [ 5 ].…”

“…Evaluation of ENDS and HTPs in different models has demonstrated involvement in pathways related to chronic pulmonary diseases [ 65 , 71 , 72 ]. As described above, these devices share common pathways of damage and impairment with conventional cigarettes; however, they present with newer damage mechanisms related to the additives, flavors, and metal nanoparticles [ 31 , 32 , 33 , 34 ].…”

A Computational Approach for Respiratory Hazard Identification of Flavor Chemicals in Tobacco Products

“…Such predictive methods are time- and resource- efficient compared to conventional in vitro and in vivo testing methods . Recently, FDA-CTP applied computational methods to assess the ability of tobacco flavor chemicals to form DNA adducts and to assess genotoxic and mutagenic potential. , Computational methods can be used as a science-based approach to search for functional groups or “structural alerts” that contribute to the chemical’s reactivity. − These structural alerts commonly include Michael acceptors, acylating and alkylating agents, aldehydes and ketones, cyanates and cyanides, and thioesters. Computational methods can be used to identify generalized chemical substructures of toxicological concern for the toxicity end points .…”

“…12 Recently, FDA-CTP applied computational methods to assess the ability of tobacco flavor chemicals to form DNA adducts 13 and to assess genotoxic and mutagenic potential. 14,15 Computational methods can be used as a science-based approach to search for functional groups or "structural alerts" that contribute to the chemical's reactivity. 16−18 These structural alerts commonly include Michael acceptors, acylating and alkylating agents, aldehydes and ketones, cyanates and cyanides, and thioesters.…”