Cardiovascular Risk Factor and Disease Measures from the Population Assessment of Tobacco and Health (PATH) Study.

BACKGROUND: Cardiovascular disease is a key health condition associated with tobacco use; however, clinical measures are not typically possible in population-based studies. In this paper, we assess the reliability and validity of self-reported cardiovascular risk factors and diseases in a large nationally representative study of tobacco use and health outcomes. METHODS: This paper analyzes self-reported cardiovascular risk factors and disease among adults age 40 years and older based on U.S. nationally representative data from the Population Assessment of Tobacco and Health (PATH) Study. Prevalence of cardiovascular risk factors (self-reported high blood pressure, high cholesterol, diabetes and family history of premature heart disease, BMI ≥ 35, and tobacco use) and cardiovascular disease (self-reported heart attack, stroke and/or congestive heart failure (CHF)) were considered along with ratings of physical functioning, fatigue, and general health. RESULTS: Self-reported cardiovascular disease was found to be associated with functional health measures (walking up a flight of stairs) and general ratings of health. Prospective analyses found strong correlations between sequential data collection waves for history of hypertension, elevated cholesterol and CHF, while more modest correlations were noted for stroke and heart attack. The overall prevalence of cardiovascular disease and hypertension was comparable to those from the National Health and Nutrition Examination Survey (NHANES). CONCLUSIONS: These analyses suggest reliability and concurrent validity regarding self-reported cardiovascular risk factors and disease assessed in the PATH Study.

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

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 aneugen-sensitive (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.

Investigating DNA adduct formation by flavor chemicals and tobacco byproducts in electronic nicotine delivery system (ENDS) using in silico approaches.

The presence of flavors is one of the commonly cited reasons for use of e-cigarettes by youth; however, the potential harms from inhaling these chemicals and byproducts have not been extensively studied. One mechanism of interest is DNA adduct formation, which may lead to carcinogenesis. We identified two chemical classes of flavors found in tobacco products and byproducts, alkenylbenzenes and aldehydes, documented to form DNA adducts. Using in silico toxicology approaches, we identified structural analogs to these chemicals without DNA adduct information. We conducted a structural similarity analysis and also generated in silico model predictions of these chemicals for genotoxicity, mutagenicity, carcinogenicity, and skin sensitization. The empirical and in silico data were compared, and we identified strengths and limitations of these models. Good concordance (80-100%) was observed between DNA adduct formation and models predicting mammalian mutagenicity (mouse lymphoma sassy L5178Y) and skin sensitization for both chemical classes. On the other hand, different prediction profiles were observed for the two chemical classes for the modeled endpoints, unscheduled DNA synthesis and bacterial mutagenicity. These results are likely due to the different mode of action between the two chemical classes, as aldehydes are direct acting agents, while alkenylbenzenes require bioactivation to form electrophilic intermediates, which form DNA adducts. The results of this study suggest that an in silico prediction for the mouse lymphoma assay L5178Y, may serve as a surrogate endpoint to help predict DNA adduct formation for chemicals found in tobacco products such as flavors and byproducts.