Applications of biomarkers of exposure and biological effects in users of new generation tobacco and nicotine products: Tentative proposals

Despite efforts to eliminate smoking, more than 1 billion people worldwide continue to use combustible cigarettes through choice or inability to quit. With an associated 8 million deaths, the provision of noncombustible tobacco and nicotine products that smokers will accept to replace combustible cigarettes can lessen harm. However, most of these products have entered the market only in the past 20 years. Therefore, particularly for some smoking-related diseases, epidemiological studies to test harm reduction potential are only now becoming feasible. For cancer and chronic obstructive pulmonary disease, around two decades of data might be required. In this article, we discuss how the use of biomarkers might be applied to supplement epidemiological research for regulators. We further discuss how health providers and insurers can keep up with the rapid changes in biomarker research and recognize these reduced risks.

Biomarkers of Electronic Nicotine Delivery Systems (ENDS) Use

This perspective summarizes available evidence on biomarkers of exposure in electronic nicotine delivery system (ENDS) users to aid the overall assessment of the health consequences of using ENDS. Identification of novel biomarkers of exposure specific to ENDS use remains challenging because chemicals emitted from ENDS devices have many familiar sources. The biomarker levels of many tobacco-related toxicants measured in biological samples collected from ENDS users did not differ significantly from non-users, except for nicotine metabolites and a small number of biomarkers of exposure to volatile organic compounds and tobacco-specific tobacco nitrosamines. Several studies have shown that while exposed to nicotine, long-term exclusive ENDS users showed significantly lower levels of toxicant biomarkers than cigarette smokers. Studies have also shown that concurrent users of ENDS and combustible cigarettes ('dual users') are not reducing overall exposure to harmful toxicants compared to exclusive cigarette smokers. Because of an absence of validated ENDS-specific biomarkers, we recommend combining several biomarkers to differentiate tobacco product user groups in population-based studies and monitor ENDS compliance in randomized controlled trials. Using a panel of biomarkers would provide a better understanding of health effects related to ENDS use.

Time trend of exposure to secondhand tobacco smoke and polycyclic aromatic hydrocarbons between 1995 and 2019 in Germany - Showcases for successful European legislation

Starting in 2002, regulations and legislative amendments in Germany focused on the non-smoker protection with several measures to reduce exposure to secondhand tobacco smoke (SHS). The present work aimed to evaluate the relationship between polycyclic aromatic hydrocarbons (PAHs) and SHS exposure and to determine to which extent enforced non-smoking regulations and smoking bans affected the exposure of the non-smoking population in Germany since their implementation in the early 2000s until today. For this purpose, cotinine and selected monohydroxylated PAHs (OH-PAHs) were analyzed by means of (UP)LC-MS/MS in 510 24-h-urine samples of the Environmental Specimen Bank collected over a time span of 24 years from 1995 to 2019. Median urinary cotinine levels were found to steadily and significantly decline by 82% from 1995 to 2019. A significant decrease of urinary 3-hydroxybenzo[a]pyrene (19%), 1-OH-pyrene (39%), 1-naphthol (66%), 1- (17%), 2- (25%), and 3-OH-phenanthrene (22%) was also observed throughout the same time span. The decline in urinary levels of cotinine and several OH-PAHs can most likely be attributed to smoking bans and regulations limiting SHS and PAH exposure. This study therefore emphasizes the relevance of human biomonitoring to investigate the exposure of humans to chemicals of concern, assess the effectiveness of regulatory measures, and help policies to enforce provisions to protect public health.

Understanding heterogeneity among individuals who smoke cigarettes and vape: assessment of biomarkers of exposure and potential harm among subpopulations from the PATH Wave 1 Data

Introduction

People who both smoke cigarettes and vape are often considered as a homogenous group even though multiple subgroups may exist. We examined biomarkers of exposure (BOE) and biomarkers of potential harm (BOPH) to differentiate between subgroups of people who smoke and vape based on PATH Study Wave 1 (2013–2014) data.

Methods

We compared people who only smoke cigarettes everyday (Group A, n = 2442) and people who only vape everyday (Group C, n = 169) against people who smoke and vape segmented into subgroups of people who frequently smoke and vape (Group B1, n = 169), frequently smoke and infrequently vape (Group B2, n = 678), frequently vape and infrequently smoke (Group B3, n = 57), and infrequently smoke and vape (Group B4, n = 66). Eighteen BOEs (representing exposure to TSNAs, nicotine, heavy metals, PAHs, and volatile organic compounds) and four BOPHs (representing inflammation and oxidative stress) were compared within the subgroups.

Results

Levels of many BOEs/BOPHs were higher among Group B2 relative to Groups B1, B3, and B4. Compared to Group A, many BOEs were significantly lower in Groups B3 (15/18) and B4 (17/18), and some BOEs were higher among B2 (4/18). Compared to Group C, significantly lower BOEs were observed for Group B4 (2/18).

Conclusions

Overall, the levels of BOEs and BOPHs in people who smoke and vape are associated with frequency of cigarette smoking. Our findings indicate that not all people who smoke and vape are the same, and tobacco product use frequency should be considered when categorizing people who smoke and vape.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12954-022-00673-x.

Assessment of nicotine delivery and uptake in users of various tobacco/nicotine products

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Nicotine uptake doses from various products show a large overlap between each other.

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Combustible cigarettes and oral tobacco products are at the high end of the nicotine uptake doses.

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Simple models for daily amounts of nicotine intake can predict the nicotine doses for most product users.

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Larger deviations were observed for smokers and users of heated tobacco products.

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The most probable reason for these deviations are differences in parameters for puffing and inhalation and actual behavior of the users.

Today various tobacco and nicotine products are available, many of them can be regarded as potentially risk-reduced products when compared to the most frequently used product, combustible cigarettes (CCs). A commonality of these products is that they deliver nicotine, although in quite different amounts and uptake routes, the most common of which are inhalation through the lung and absorption through the oral mucosa. Product-specific nicotine delivery as well as the subject-related use patterns are important factors which determine the pharmacokinetics and achieved internal dose levels of the alkaloid. The latter two parameters are highly relevant for the long-term product loyalty and, consequently, for the implicated health risks, since the risk-reduced products will replace CCs in the long-term only when users will experience a similar level of satisfaction. We measured nicotine and its major metabolites in plasma, saliva and urine samples collected in a controlled clinical study with habitual users (10 per group) of CCs, electronic cigarettes (ECs), heated tobacco products (HTP), oral tobacco (OT), and nicotine replacement therapy (NRT). Non-users (NU) of any tobacco/nicotine products served as (negative) control group. Moderate to strong correlations were observed between the daily consumption and the urinary nicotine equivalents (comprising nicotine and its 10 major metabolites, Nic + 10) or plasma and saliva cotinine concentrations. The average daily nicotine dose as measured by the urinary excretion of Nic + 10 (reflecting approximately 95 % of the absorbed nicotine) amounted to 17 and 22 mg/24 h for smokers (CC) and OT users, respectively, while it was in the range of 6–12 mg/24 h for users of ECs, HTP and NRT products, with high inter-individual variations in each user group. The individual daily nicotine intake, which was calculated by applying product-specific models, showed none to good agreement with the corresponding internal nicotine dose measured by Nic + 10 excretion. Possible reasons for the observed deviations between calculated and objectively measured nicotine doses are discussed.

DNA methylation differentiates smoking from vaping and non-combustible tobacco use

Increasing use of non-combusted forms of nicotine such as e-cigarettes poses important public health questions regarding their specific risks relative to combusted tobacco products such as cigarettes. To fully delineate these risks, improved biomarkers that can distinguish between these forms of nicotine use are needed. Prior work has suggested that methylation status at cg05575921 may serve as a specific biomarker of combusted tobacco smoke exposure. We hypothesized combining this epigenetic biomarker with conventional metabolite assays could classify the type of nicotine product consumption. Therefore, we determined DNA methylation and serum cotinine values in samples from 112 smokers, 35 e-cigarette users, 19 smokeless tobacco users, and 269 controls, and performed mass spectroscopy analyses of urine samples from all nicotine users and 22 verified controls to determine urinary levels of putatively nicotine product-specific substances; propylene glycol, 2-cyanoethylmercapturic acid (CEMA), and anabasine. 1) Cigarette smoking was associated with a dose dependent demethylation of cg05575921 and increased urinary CEMA and anabasine levels, 2) e-cigarette use did not demethylate cg05575921, 3) smokeless tobacco use also did not demethylate cg05575921 but was positively associated with anabasine levels 4) CEMA and cg05575921 levels were highly correlated and 5) propylene glycol levels did not reliably distinguish use groups. Cg05575921 assessments distinguish exposure to tobacco smoke from smokeless sources of nicotine including e-cigarettes and smokeless tobacco, neither of which are associated with cg05575921 demethylation. A combination of methylomic and metabolite profiling may allow for accurate classification use status of a variety of nicotine containing products.

Systemic biomarkers of exposure associated with ENDS use: a scoping review

OBJECTIVE

This scoping review provides an overview of the existing literature on biomarkers of exposure from electronic nicotine delivery systems (ENDS) use and identifies gaps in existing knowledge.

DATA SOURCES

We searched two international databases (PubMed and Web of Science) to identify relevant studies published from August 2013 to February 2021.

DATA SELECTION

Studies were included if they assessed and compared biomarkers of exposure between exclusive ENDS users, non-users, exclusive cigarette smokers, dual users of ENDS and cigarettes or cigarette smokers who switch to ENDS.

DATA EXTRACTION AND SYNTHESIS

Of the 5074 studies identified, 188 studies met criteria and were selected for full-text screening. Of these, 27 studies were selected for inclusion and data extraction.

CONCLUSIONS

Consistent, although limited, evidence shows that exclusive ENDS users have elevated levels of biomarkers of certain volatile organic compounds (VOCs; eg, acrylamide and acrylonitrile), metals (eg, cadmium and selenium) and propylene glycol compared with non-users; however, evidence for biomarkers of other toxicants (eg, acrolein, benzene and chromium) is mixed. Biomarkers of most VOCs are lower in ENDS users compared with cigarette smokers, and cigarette smokers who switch to ENDS consistently show reductions in VOC biomarkers. Evidence comparing metal exposures from exclusive ENDS use, cigarette smoking and dual use is mixed and depends on the metal. ENDS and e-liquid characteristics as well as use patterns may be associated with elevated exposure to VOCs and metals. Additional rigorous, controlled studies can assess biomarker exposures from ENDS use and inform the overall risk-benefit of ENDS use for different user populations.

1,2-Propylene Glycol: A Biomarker of Exposure Specific to e-Cigarette Consumption

Over the past decade, new emerging tobacco and nicotine-delivery products have changed the tobacco landscape. Especially, electronic cigarettes (ECs) have been suggested to be considered for tobacco harm reduction, reinforcing the need to identify novel biomarkers of exposure (BoE) specific to the EC use as this would complement exposure assessment and product compliance monitoring. Therefore, a sensitive LC-MS/MS method for the quantification of 1,2-propylene glycol (PG) and glycerol (G), the main e-liquid constituents, was established. PG and G were analyzed in plasma and urine samples from a clinical study comparing five nicotine product user groups, users of combustible cigarettes (CC), electronic cigarettes (EC), heated tobacco products (HTP), oral tobacco (OT), and oral/dermal nicotine delivery products (used for nicotine replacement therapy, NRT) with a control group of non-users (NU). Data demonstrate significantly elevated PG levels in urine and plasma in EC users compared to users of CC, HTP, NRT, OT as well as NU. In addition, PG in plasma and urine of vapers significantly correlated with nicotine (plasma) and total nicotine equivalents (urine), biomarkers reflecting product consumption, emphasizing the high specificity of PG as a BoE for EC consumption. We therefore suggest the use of PG as BoE in urine and/or plasma in order to monitor EC use compliance in exposure assessments.

Assessment of the potential vaping-related exposure to carbonyls and epoxides using stable isotope-labeled precursors in the e-liquid

The formation of carbonyls and epoxides in e-cigarette (EC) aerosol is possible due to heating of the liquid constituents. However, high background levels of these compounds have inhibited a clear assessment of exposure during use of ECs. An EC containing an e-liquid replaced with 10% of ¹³C-labeled propylene glycol and glycerol was used in a controlled use clinical study with 20 EC users. In addition, five smokers smoked cigarettes spiked with the described e-liquid. Seven carbonyls (formaldehyde, acetaldehyde, acrolein, acetone, crotonaldehyde, methacrolein, propionaldehyde) were measured in the aerosol and the mainstream smoke. Corresponding biomarkers of exposure were determined in the user’s urine samples. ¹³C-labeled formaldehyde, acetaldehyde and acrolein were found in EC aerosol, while all seven labeled carbonyls were detected in smoke. The labeled biomarkers of exposure to formaldehyde (¹³C-thiazolidine carboxylic acid and ¹³C-N-(1,3-thiazolidine-4-carbonyl)glycine), acrolein (¹³C₃-3-hydroxypropylmercapturic acid) and glycidol (¹³C₃-dihydroxypropylmercapturic acid) were present in the urine of vapers indicating an EC use-specific exposure to these toxicants. However, other sources than vaping contribute to a much higher extent by several orders of magnitude to the overall exposure of these toxicants. Comparing data for the native (unlabeled) and the labeled (exposure-specific) biomarkers revealed vaping as a minor source of user’s exposure to these toxicants while other carbonyls and epoxides were not detectable in the EC aerosol.

Identification of biomarkers specific to five different nicotine product user groups: Study protocol of a controlled clinical trial

Background

Assessing biomarker profiles in various body fluids is of large value to discern between the sole use of nicotine products. In particular, the assessment of the product compliance is required for long-term clinical studies. The objective of this study was the identification of biomarkers and biomarker patterns in body fluids, to distinguish between combustibles, heated tobacco products, electronic cigarettes, oral tobacco and oral/dermal nicotine products used for nicotine replacement therapy (NRT), as well as a control group of non-users.

Methods

A controlled, single-center study was conducted with 60 healthy subjects, divided into 6 groups (5 nicotine product user groups and one non-user group) based on their sole use of the products of choice. The subjects were confined for 76 h, during which, free and uncontrolled use of the products was provided. Sample collections were performed according to the study time schedule provided in Table 2. The primary outcome will be validated through analysis of the collected biospecimens (urine, blood, saliva, exhaled breath and exhaled breath condensate) by means of untargeted omics approaches (i.e. exposomics, breathomics and adductomics). Secondary outcome will include established biomarker quantification methods to allow for the identification of typical biomarker patterns. Statistical analysis tools will be used to specifically discriminate different product use categories.

Results/Conclusions

The clinical trial was successfully completed in May 2020, resulting in sample management and preparations for the quantitative and qualitative analyses. This work will serve as a solid basis to discern between biomarker profiles of different nicotine product user groups. The knowledge collected during this research will be required to develop prototype diagnostic tools that can reliably assess the differences and evaluate possible health risks of various nicotine products.

Electronic nicotine delivery system-induced alterations in oral health via saliva assessment

IMPACT STATEMENT

The use of traditional tobacco products is a known risk factor for the development of diseases including periodontal disease. To date, the potential oral health effects related to electronic nicotine delivery systems (ENDS) use is unknown. This study collected saliva from ENDS users and never tobacco users to examine differences in the oral cavity of inflammatory cytokines and metabolites. The identification and measurement of these ENDS-related changes provide insight into disease pathways potentially associated with ENDS use. The utilization of saliva samples collected from human participates enhances the application of the findings compared to the majority of studies using cell culture and animal models. In addition, these foundational findings can inform future studies to examining specific pathways identified, interventional approaches, and application of translatable biomarkers of ENDS use.

A novel quantification method for sulfur-containing biomarkers of formaldehyde and acetaldehyde exposure in human urine and plasma samples

A novel method for the quantification of the sulfur-containing metabolites of formaldehyde (thiazolidine carboxylic acid (TCA) and thiazolidine carbonyl glycine (TCG)) and acetaldehyde (methyl thiazolidine carboxylic acid (MTCA) and methyl thiazolidine carbonyl glycine (MTCG)) was developed and validated for human urine and plasma samples. Targeting the sulfur-containing metabolites of formaldehyde and acetaldehyde in contrast to the commonly used biomarkers formate and acetate overcomes the high intra- and inter-individual variance. Due to their involvement in various endogenous processes, formate and acetate lack the required specificity for assessing the exposure to formaldehyde and acetaldehyde, respectively. Validation was successfully performed according to FDA's Guideline for Bioanalytical Method Validation (2018), showing excellent performance with regard to accuracy, precision, and limits of quantification (LLOQ). TCA, TCG, and MTCG proved to be stable under all investigated conditions, whereas MTCA showed a depletion after 21 months. The method was applied to a set of pilot samples derived from smokers who consumed unfiltered cigarettes spiked with ¹³C-labeled propylene glycol and ¹³C-labeled glycerol. These compounds were used as potential precursors for the formation of ¹³C-formaldehyde and ¹³C-acetaldehyde during combustion. Plasma concentrations were significantly lower as compared to urine, suggesting urine as suitable matrix for a biomonitoring. A smoking-related increase of unlabeled biomarker concentrations could not be shown due to the ubiquitous distribution in the environment. While the metabolites of ¹³C-acetaldehyde were not detected, the described method allowed for the quantification of ¹³C-formaldehyde uptake from cigarette smoking by targeting the biomarkers ¹³C-TCA and ¹³C-TCG in urine.Graphical abstract.

Biomarkers of Exposure and Effect in the Lungs of Smokers, Nonsmokers, and Electronic Cigarette Users

BACKGROUND

Nicotine-containing electronic cigarette (e-cig) use has become widespread. However, understanding the biological impact of e-cigs compared with smoking on the lung is needed. There are major gaps in knowledge for chronic effects and for an etiology to recent acute lung toxicity leading to death among vapers.

METHODS

We conducted bronchoscopies in a cross-sectional study of 73 subjects (42 never-smokers, 15 e-cig users, and 16 smokers). Using bronchoalveolar lavage and brushings, we examined lung inflammation by cell counts, cytokines, genome-wide gene expression, and DNA methylation.

RESULTS

There were statistically significant differences among never-smokers, e-cig users, and smokers for inflammatory cell counts and cytokines (FDR q < 0.1). The e-cig users had values intermediate between smokers and never-smokers, with levels for most of the biomarkers more similar to never-smokers. For differential gene expression and DNA methylation, e-cig users also more like never-smokers; many of these genes corresponded to smoking-related pathways, including those for xenobiotic metabolism, aryl hydrocarbon receptor signaling, and oxidative stress. Differentially methylated genes were correlated with changes in gene expression, providing evidence for biological effects of the methylation associations.

CONCLUSIONS

These data indicate that e-cigs are associated with less toxicity than cigarettes for smoking-related pathways. What is unknown may be unique effects for e-cigs not measured herein, and a comparison of smokers completely switching to e-cigs compared with former smokers. Clinical trials for smokers switching to e-cigs who undergo serial bronchoscopy and larger cross-sectional studies of former smokers with and without e-cig use, and for e-cigs who relapse back to smoking, are needed.

IMPACT

These data can be used for product regulation and for informing tobacco users considering or using e-cigs. What is unknown may be unique effects for e-cigs not measured herein, and clinical trials with serial bronchoscopy underway can demonstrate a direct relationship for changes in lung biomarkers.

Short halt in vaping modifies cardiorespiratory parameters and urine metabolome: a randomized trial

Propylene glycol and glycerol are e-cigarette constituents that facilitate liquid vaporization and nicotine transport. As these small hydrophilic molecules quickly cross the lung epithelium, we hypothesized that short-term cessation of vaping in regular users would completely clear aerosol deposit from the lungs and reverse vaping-induced cardiorespiratory toxicity. We aimed to assess the acute effects of vaping and their reversibility on biological/clinical cardiorespiratory parameters [serum/urine pneumoproteins, hemodynamic parameters, lung-function test and diffusing capacities, transcutaneous gas tensions (primary outcome), and skin microcirculatory blood flow]. Regular e-cigarette users were enrolled in this randomized, investigator-blinded, three-period crossover study. The periods consisted of nicotine-vaping (nicotine-session), nicotine-free vaping (nicotine-free-session), and complete cessation of vaping (stop-session), all maintained for 5 days before the session began. Multiparametric metabolomic analyses were used to verify subjects' protocol compliance. Biological/clinical cardiorespiratory parameters were assessed at the beginning of each session (baseline) and after acute vaping exposure. Compared with the nicotine- and nicotine-free-sessions, a specific metabolomic signature characterized the stop-session. Baseline serum club cell protein-16 was higher during the stop-session than the other sessions (P < 0.01), and heart rate was higher in the nicotine-session (P < 0.001). Compared with acute sham-vaping in the stop-session, acute nicotine-vaping (nicotine-session) and acute nicotine-free vaping (nicotine-free-session) slightly decreased skin oxygen tension (P < 0.05). In regular e-cigarette-users, short-term vaping cessation seemed to shift baseline urine metabolome and increased serum club cell protein-16 concentration, suggesting a decrease in lung inflammation. Additionally, acute vaping with and without nicotine decreased slightly transcutaneous oxygen tension, likely as a result of lung gas exchanges disturbances.