Metabolomic Analysis Identified Reduced Levels of Xenobiotics, Oxidative Stress, and Improved Vitamin Metabolism in Smokers Switched to Vuse Electronic Nicotine Delivery System

Abstract

Introduction

Switching to noncombustible tobacco products presents an opportunity for cigarette smokers to potentially reduce the health risks associated with smoking. Electronic Nicotine Delivery Systems (ENDS) are one such product because the vapor produced from ENDS contains far fewer toxicants than cigarette smoke. To investigate the biochemical effects of switching from smoking to an ENDS, we assessed global metabolomic profiles of smokers in a 7-day confinement clinical study.

Methods

In the first 2 days of this clinical study, the subjects used their usual brand of cigarettes and then switched to exclusive ENDS ad libitum use for 5 days. Urine and plasma samples were collected at baseline and 5 days after switching. The samples were analyzed using a mass spectrometry-based metabolomic platform.

Results

Random forest analyses of urine and plasma metabolomic data revealed excellent predictive accuracy (>97%) of a 30-metabolite signature that can differentiate smokers from 5-day ENDS switchers. In these signatures, most biomarkers are nicotine-derived metabolites or xenobiotics. They were significantly reduced in urine and plasma, suggesting a decreased xenobiotic load on subjects. Our results also show significantly decreased levels of plasma glutathione metabolites after switching, which suggests reduced levels of oxidative stress. In addition, increased urinary and plasma levels of vitamins and antioxidants were identified, suggesting enhanced bioavailability due to discontinuation of cigarette smoking and switching to Vuse ENDS use.

Conclusions

Our results suggest reduced toxicant exposure, reduced oxidative stress, and potential beneficial changes in vitamin metabolism within 5 days in smokers switching to Vuse ENDS.

Implications

Switching from smoking to exclusive ENDS use in clinical confinement settings results in significant reduction of nicotine metabolites and other cigarette-related xenobiotics in urine and plasma of subjects. Significantly decreased oxidative stress-related metabolites and increased urinary and plasma levels of vitamin metabolites and antioxidants in 5-day short-term ENDS switchers suggest less toxic physiological environment for consumers of ENDS products and potential health benefits if such changes persist.

Introduction

Smoking increases the risks of lung cancer, chronic obstructive pulmonary disease, and cardiovascular disease.^1–3 Cigarette smoke contains several thousand chemicals that are generated during the combustion process.⁴ Many of these chemicals, designated by the US FDA as harmful and potentially harmful constituents (HPHCs), have been linked to long-term adverse health effects.^5,6 A relative risk continuum across different tobacco and nicotine products has been envisioned,⁷ and under this paradigm, cigarette smoking has been recognized as the most harmful form of tobacco use.⁷ Complete smoking cessation is the best option to reduce the risk of smoking-related diseases.

Apart from cigarettes, noncombustible tobacco products exist and do not generate combustion-related toxicants. These include smokeless tobacco products such as moist snuff and chewing tobacco, Electronic Nicotine Delivery Systems (ENDS), and heated tobacco products.^8,9 For those smokers (SMK) who are unable to quit, switching to noncombustible tobacco products may significantly reduce their risk of disease.⁷ Biomarkers of exposure and biomarkers of potential harm (BoPH) are biological measures that inform of the exposure to tobacco toxicants and the potential harm from the toxicant exposure, respectively. Considering the long latency of smoking-related diseases, biomarkers are important tools to assess the potential long-term adverse health effects of tobacco use.

The inhaled, noncombustible tobacco products such as ENDS generate chemically much simpler aerosol that is devoid or contains substantially lower levels of HPHCs. The e-liquids used in ENDS, while varying from manufacturer to manufacturer, typically contain glycerin, propylene glycol, nicotine and flavors, and are not combusted during product use. Several studies have shown that ENDS use generally results in significant reductions in biomarkers indicative of exposure to several HPHCs.^10–12 Particularly, switching from SMK to exclusive use of Vuse (VS) Digital Vapor Cigarette (ENDS product marketed by R. J. Reynolds Vapor Company) results in substantial reductions in biomarkers of nicotine exposure and the biomarkers of 22 carcinogens and toxicants found in cigarette smoke.¹³ According to a 2018 report, “there is substantial evidence that—except for nicotine—exposure to potentially toxic substances from e-cigarettes is significantly lower compared with combustible cigarettes.”  ¹⁴ Furthermore, the report suggested that switching to sole use of noncombustible tobacco products, for example, ENDS, may present a significant harm-reduction opportunity to chronic smokers.¹⁴

There is limited information on the biological and potential health effects of ENDS usage relative to the adverse effects associated with chronic cigarette smoking. Due to the popularity of ENDS products, however, studies are being conducted to examine the potential human health impact of ENDS usage (reviewed elsewhere¹⁵). In the absence of strong epidemiologic data associated with the ENDS product category in general, BoPH represent valuable tools in assessing the health effects of ENDS. The generally accepted BoPH associated with cigarette smoking (such as white blood cell count and isoprostanes) require several months of smoking abstinence (or switching to alternate products such as ENDS). In a recent study, we demonstrated that select arachidonic acid metabolites are useful BoPH to assess the short-term effects of switching SMK to noncombustible tobacco products. In particular, we found that urinary leukotriene E₄ and 2,3-dinor-thromboxane B₂ levels rapidly decline in smokers who switched to VS products to levels seen in nonsmokers.¹⁶

Global profiling technologies such as metabolomics have been used to assess BoPH and individual health effects in SMK. For example, metabolomic profiling was used to characterize biochemical changes and identify BoPH following smoking cessation or smokeless tobacco use.^17–19 In this study, we investigated global biochemical changes in SMK switching from a combustible tobacco product to either of two VS products over a 5-day period. A baseline was first established during the initial 2 days of usual brand cigarette use, with subjects switching to the exclusive use of an ENDS ad libitum for the remainder of study. The comparative analysis of plasma and urinary metabolomic profiles in SMK switched to VS products revealed a reduced xenobiotic load, lower oxidative stress, and potential beneficial changes in vitamin metabolism within 5 days of switching. Taken together, our data suggest the ability of key metabolites to differentiate combustible and noncombustible tobacco product users. As such, these metabolites might serve as useful BoPH to assess the short-term health effects of ENDS products.

Methods

Study Design

The Vuse Digital Vapor cigarettes (ENDS) are first-generation cig-alike products, and the e-liquid that used this system is composed of propylene glycol, glycerin, nicotine, flavorings, and water.¹³ Clinical study design and conduct of the product-switching study were previously described.¹³ This study, which was approved by Chesapeake Institutional Review Board (Columbia, Maryland) in November 2014, was conducted in accordance with the principles of the Declaration of Helsinki. It was registered on www.clinicaltrials.gov on December 2014, and its identifier number is NCT02323438. Generally healthy males and females, 21–60 years of age, inclusive, who reported smoking at least 10 combustible, filtered, menthol, or non-menthol cigarettes per day and reported smoking their first cigarette within 30 minutes of waking were included in the study. Written informed consent was obtained from all the subjects in the study.

Briefly, the study was a single-center, randomized, controlled, switching, open-label, parallel cohort study in which SMK were enrolled and randomized to one of three cohorts switched from 2 days of usual brand cigarette use to 5 days of ad libitum use of either VS Original flavor, nicotine gum, or VS Menthol flavor. Both VS brand styles contain approximately 600 μL of a 4.8% nicotine e-liquid or approximately 29 mg of nicotine. Nicorette nicotine polacrilex gum (GlaxoSmithKline Consumer Healthcare, LP, Philadelphia, PA) was commercially available, and a 4-mg strength nicotine gum was chosen in this study. Smokers of non-menthol cigarettes were randomized to VS Original or nicotine gum. Smokers of menthol cigarettes were randomized to VS Menthol or nicotine gum. Cigarettes per day at baseline were similar across the cohorts, ranging from means of 14.0–14.5. The mean daily amounts of e-liquid used by the VS groups increased from day 1 to day 3, and then the amounts used on days 3, 4, and 5 were relatively consistent. By day 4, the mean gram of e-liquid used was approximately 0.43 ± 0.32 for VS Original group and 0.44 ± 0.32 for VS Menthol group.

Plasma and urine samples collected from SMK who switched to ENDS products (VS Original flavor or VS Menthol flavor) were used for metabolomic profiling studies described herein. Plasma was collected at approximately 07:00 AM (before product use began each day) on study days −2 (baseline) and 5 (post-switching) after overnight fasting and abstinence from tobacco product use. Urine samples were collected for 24-hour periods starting at 07:30 PM on days −3 and 4. Plasma and urine samples were stored at −70°C while awaiting shipment to Metabolon Inc (Cary, NC) for metabolomic analysis. Samples from the subjects who had been switched to nicotine gum were not used in metabolomic profiling because the scope of post hoc analyses was limited to comparison of the effects of cigarette smoking to the usage of Vuse products.

Metabolomics

Sample processing and analysis was carried out at Metabolon Inc (Cary, NC) as previously described.²⁰ Briefly, samples were divided into five fractions for nontargeted mass spectrometry analysis using ultra-high-performance liquid chromatography–tandem mass spectrometry. Metabolites were identified by automated comparison of the ion features in the experimental samples to a reference library of chemical standard entries that included retention time, molecular weight (m/z), preferred adducts, and in-source fragments as well as associated mass spectrometry spectra and curated by visual inspection for quality control using software developed at Metabolon Inc.²¹

Statistical Analysis

The matched-pairs t-test was used to determine the statistical significance (p value) of metabolite mean differences between comparator groups (baselines and post-switching). False discovery rates, estimated by q values, were used to control the type I error. In our analysis, the significantly upregulated or downregulated metabolites were defined based on three selections including (1) p < .05 and q < .05; (2) % filled values (defined as the percentage of the metabolite detected among all the samples using Metabolon platform, eg, 10% filled value means that the metabolite was not detected among 10 samples out of 100 total) ≥ 90%; and (3) fold ratio > 1.1 or < 0.9 (the ratio of relative abundance of the identified metabolites between 5-day post-switching and baselines). Random forest analyses—a supervised classification technique based on an ensemble of decision trees²²—were performed to develop classification models. ArrayStudio version 5.0 (OmicSoft, Cary, NC) was used to perform t-test, and R program (http://cran.r-project.org/) was used to conduct random forest analysis.

Results

Global Metabolomic Alterations in Smokers Switched to ENDS

Metabolic profiling was performed using plasma and urine collected from SMK at baseline and 5 days after switching to the ENDS products to characterize the global metabolomic changes in SMK switched to VS products. A total of 698 and 846 metabolites were identified in urine and plasma, respectively (mass-normalized data are included in Supplementary Files S1 and S2). In SMK switched to VS Original, 78 metabolites were significantly upregulated and 48 were downregulated in urine (Supplementary Table S1). In plasma, 72 metabolites were significantly upregulated and 63 were downregulated. In SMK switched to VS Menthol, 96 metabolites were significantly upregulated, whereas 69 metabolites were downregulated in urine. In plasma, 91 metabolites were significantly upregulated, and 62 metabolites were downregulated. These differentiating metabolites belong to amino acid, carbohydrate, cofactors and vitamins, energy, lipid, nucleotide, and peptide metabolic pathways. In addition, many metabolites were mapped to xenobiotic metabolic pathways (Supplementary Table S1).

Random forest classification showed excellent predictions of VS product usage based on the baseline (smoking) and post-switch (ENDS use) metabolomic profiles in both urine and plasma. For VS Original, 36 of 37 (36/37) smoking and 37/37 ENDS use urine samples were accurately identified with 98.65% accuracy and 1.35% out-of-bag error rates using top 30 differentiating metabolites (Table 1, Supplementary Figure S1A). For VS Menthol, 36/38 smoking and 38/38 ENDS use samples were accurately predicted in urine (Supplementary Figure S1B). The corresponding out-of-bag error rate and accuracy for VS Menthol are 2.63% and 97.37%, respectively. Similarly, random forest models were highly predictive for plasma metabolite data for VS Original and VS Menthol (Supplementary Figure S2). Random forest importance plots identified 30 similar metabolites as key contributors to differentiate ENDS use from smoking in urine and plasma (Table 1 for VS Original and Supplementary Table S2 for VS Menthol), with sulfated and nicotine-derived metabolites exerting highest influence on classification regardless of cohort or matrix. We excluded nicotine and its metabolites from the data sets from urine and plasma and repeated the random forest analyses. These analyses led to similar highly predictive models with prediction accuracy > 98% and most of top 30 metabolites were sulfated metabolites, that is, xenobiotics (Table 1, Supplementary Table S2, and Supplementary Figures S1 and S2).

Table 1.

Top 30 Differentiating Metabolites Identified From Random Forest Analyses in Urine and Plasma of Non-menthol Smokers Switched to VS Original Product

	Urine				Plasma
	Random forest of all identified metabolomic data		Random forest of all metabolomic data excluding nicotine and its metabolites		Random forest of all identified metabolomic data		Random forest of all metabolomic data excluding nicotine and its metabolites
No.	Metabolite	MDAa	Metabolite	MDA	Metabolite	MDA	Metabolite	MDA
1	2-Ethylphenylsulfate	72.6	2-Ethylphenylsulfate	73.7	2-Ethylphenylsulfsate	69.3	2-Ethylphenylsulfate	69.9
2	o-Cresol sulfate	71.2	o-Cresol sulfate	72.5	o-Cresol sulfate	64.0	o-Cresol sulfate	64.5
3	S-(3-Hydroxypropyl)- mercaptunic acid	64.9	S-(3-Hydroxypropyl)- mercaptunic acid	66.8	Isoeugenol sulfate	62.0	Isoeugenol sulfate	62.2
4	Isoeugenol sulfate	56.3	Isoeugenol sulfate	57.7	Methylnaphthyl sulfate (2)	57.4	Methylnaphthyl sulfate (2)	57.9
5	Syringol sulfate	52.3	Syringol sulfate	53.0	Methylnaphthyl sulfate (1)	52.3	Methylnaphthyl sulfate (1)	52.4
6	2,3-Dihydroxyisovalerate	49.5	2,3-Dihydroxyisovalerate	51.0	Homocitrulline	46.0	Homocitrulline	46.6
7	Umbelliferone sulfate	48.1	Umbelliferone sulfate	49.6	4-Hydroxycoumarin	38.7	4-Hydroxycoumarin	39.3
8	Cotinine N-oxide	41.7	Argininate	34.5	4-Hydroxyphenyl acetylglutamine	37.9	4-Hydroxyphenyl acetylglutamine	38.5
9	Nornicotine	40.5	4-Hydroxycoumarin	33.7	5-Hydroxylysine	37.2	5-Hydroxylysine	37.5
10	Hydroxycotinine	40.3	Galactosylglycerol	31.5	Cotinine N-oxide	30.9	Octadecanedioylcarnitine (C18-DC)	28.7
11	Norcotinine	34.2	Mandelate	30.7	Cotinine	28.8	Trimethylamine N-oxide	28.0
12	Argininate	33.1	Cytosine	30.3	Octadecanedioylcarnitine (C18-DC)	28.2	2,3-Dihydroxyisovalerate	25.8
13	Cotinine	31.9	Uridine	28.5	Trimethylamine N-oxide	27.7	Daidzein sulfate (2)	25.0
14	4-Hydroxycoumarin	31.6	4-Ethylphenol glucuronide	28.4	2,3-Dihydroxyisovalerate	25.3	S-Methylcysteine	24.8
15	Mandelate	30.0	S-(2-Carboxyethyl)-mercapturic acid	28.4	Daidzein sulfate (2)	24.2	Linoleoylcarnitine (C18:2)	23.1
16	Galactosylglycerol	29.5	4-Ethylphenyl sulfate	23.5	S-Methylcysteine	23.8	Mannitol/sorbitol	22.3
17	Cytosine	28.1	N-Methylalanine	22.7	Linoleoylcarnitine (C18:2)	23.3	2-Aminoheptanoate	21.6
18	Uridine	27.7	Succinylglutamine	22.7	2-Aminoheptanoate	22.0	Umbelliferone sulfate	20.8
19	S-(2-Carboxyethyl)-mercapturic acid	27.2	Naringenin 7-glucuronide	22.6	Mannitol/sorbitol	21.8	5-Oxoproline	20.7
20	3-Hydroxycotinine glucuronide	26.8	Anserine	21.8	Alliin	20.2	Alliin	20.5
21	4-Ethylphenol gucuronide	26.6	7-Hydroxyindole sulfate	21.0	Umbelliferone sulfate	20.1	4-Ethylphenyl sulfate	18.9
22	4-Ethylphenyl sulfate	22.8	2-Isopropylmalate	20.9	5-Oxoproline	19.9	1-(1-Enyl-palmitoyl)-2-palmitoyl- GPC (P-16:0/18.2)	18.7
23	Succinylglutamine	21.3	4-Vinylphenol sulfate	20.5	4-Ethylphenyl sulfate	18.7	3-Methyl catechol sulfate (2)	18.1
24	N-Methylalanine	20.9	N-Octanoylglutamine	18.2	1-(1-Enyl-palmitoyl)-2-palmitoyl- GPC	18.1	3-Methyl catechol sulfate (1)	18.0
25	4-Vinylphenol sulfate	20.9	Hexanoylglutamine	17.7	3-Methyl catechol sulfate (2)	17.5	Piperine	16.5
26	Naringenin 7-glucuronide	20.7	N-Acetylalliin	17.4	3-Methyl catechol sulfate (1)	17.3	Genistein sulfate	16.5
27	Anserine	20.3	4-Acetylphenol sulfate	17.1	Genistein sulfate	16.4	2-Oxoarginine	16.4
28	2-Isopropylmalate	19.5	N1-Methyl-2-pyridone-5- carboxamide	17.1	Piperine	16.2	3-Methoxytyramine sulfate	15.7
29	7-Hydroxyindole sulfate	19.5	Daidzein	16.0	2-Oxoarginine	16.0	2-Aminooctanoate	15.4
30	Hexanoylglutamine	18.8	Furnaeol sulfate	15.8	3-Methoxytyramine sulfate	15.6	4-Vinylphenol sulfate	15.3

^aMDA is the mean decrease in accuracy computed from random forest analysis. The larger MDA is, the more important the variable is for classification of the data.

Biochemical Pathways Affected in Smokers Switched to ENDS

As described above, global metabolomic profiling identified a large number of statistically significant metabolites in SMK who had switched to VS Original and VS Menthol products. In the following sections, we present differences in specific biochemical pathways indicative of exposure (nicotine and other exposures) to the VS products and potential biological effects from switching to VS products.

Exposure to Nicotine and Its Metabolites

Metabolomic profiling detected nicotine and six nicotine metabolites in urine (Table 2). A significant reduction in levels of nicotine and its metabolites was observed in the urine of SMK switched to either VS Original or VS Menthol for 5 days. Relative declines ranged from 35% to 67% in urinary cotinine, hydroxycotinine, cotinine N-oxide, 3-hydroxycotinine glucuronide, norcotinine, nornicotine, and nicotine. Consistent with urinary changes, alterations in nicotine metabolism were observed in the plasma of SMK switched to either VS Original or VS Menthol. Specifically, plasma levels of nicotine metabolites (cotinine, hydroxycotinine, cotinine N-oxide, 3-hydroxycotinine glucuronide) significantly decreased (24%–43%) in SMK switched to either VS Original or VS Menthol. However, nicotine and two nicotine metabolites (nornicotine and norcotinine) were undetectable in plasma.

Table 2.

Relative Levels of Nicotine and Its Metabolites in Smokers Switched to VS Original and VS Menthol Products

	Non-menthol smokers switched to VS Original				Menthol smokers switched to VS Menthol
	Urine		Plasma		Urine		Plasma
Biochemical name	Adjusted p	Percentage change from baseline	Adjusted p	Percentage change from baseline	Adjusted p	Percentage change from baseline	Adjusted p	Percentage change from baseline
Cotinine	<.001	−36.2	<.001	−33.8	<.001	−38.2	<.001	−33.4
Hydroxycotinine	<.001	−45.3	<.001	−24.1	<.001	−49.1	<.001	−27.9
Cotinine N-oxide	<.001	−35.4	<.001	−38.3	<.001	−47.8	<.001	−42.9
3-Hydroxycotinine glucuronide	<.001	−42.6	<.001	−29.3	<.001	−48.2	<.001	−23.6
Norcotinine	<.001	−48.6	NA	NA	<.001	−67.0	NA	NA
Nornicotine	<.001	−46.2	NA	NA	<.001	−55.4	NA	NA
Nicotine	.023	−18.5	NA	NA	<.001	−39.9	NA	NA

NA = not applicable because some metabolites were not identified in plasma samples that were collected following overnight abstinence from tobacco product use by metabolomic profiling.

Xenobiotic Metabolites Are Decreased in Smokers Switched to VS Products

We examined the impact of short-term switching from combustible to VS ENDS products on the plasma and urinary levels of non-nicotine xenobiotic-derived metabolites. We found that switching SMK to VS for 5 days resulted in significant alterations in the levels of a number of metabolites that were derived from cigarette smoke. Also, given that many of the parent compounds of the differentiating metabolites exist in food or produced through microbial metabolism, the differences in the metabolite levels could reflect those sources as well.

The levels of the biomarkers of tobacco exposure, S-(3-hydroxypropyl) mercapturic acid (S-3-HPMA) and S-(2-carboxyethyl) mercapturic acid (metabolites of acrolein), were significantly reduced (67% and 45%, respectively) in the urine of VS Original users after switching. The decrease in HPMA levels was also substantially lower in the urine of VS Menthol users (72% and 55%, respectively). The levels of several benzoate metabolites and plant-derived metabolites showed declines upon switching SMK to VS products (Table 3). Significant declines in 2-ethylphenylsulfate (>90%), o-cresol sulfate (>80%), isoeugenol sulfate (>70%), and 4-hydroxycoumarin (>25%) were detected in urine and plasma of VS Original and VS Menthol users at 5 days of product use, relative to the baseline. Several of the benzoate and plant-derived metabolites showed consistent decreases in plasma samples from baseline to 5 days of VS product use, consistent with the urine data.

Table 3.

Relative Levels of Non-nicotine-Derived Xenobiotic Metabolites in Smokers Switched to VS Original and VS Menthol Products

		Non-menthol smokers switched to VS Original				Menthol Smokers switched to VS Menthol
		Urine		Plasma		Urine		Plasma
Biochemical name	Metabolic pathway	Adjusted p	Percentage change from baseline	Adjusted p	Percentage change from baseline	Adjusted p	Percentage change from baseline	Adjusted p	Percentage change from baseline
2-Ethylphenylsulfate	Benzoate metabolism	<.001	−93.6	<.001	−90.7	<.001	−95.1	<.001	−90.7
o-Cresol sulfate	Benzoate metabolism	<.001	−80.1	<.001	−81.4	<.001	−84.8	<.001	−87.8
Isoeugenol sulfate	Food component/ plant	<.001	−74.5	<.001	−80.5	<.001	−70.7	<.001	−74.7
Umbelliferone sulfate	Food component/plant	<.001	−56.9	.006	−2.9	<.001	−55.1	.096	29.6
2,3-Dihydroxyisovalerate	Food component/plant	<.001	−41.0	<.001	−25.3	<.001	−20.0	.039	−1.6
3-Methyl catechol sulfate (2)	Benzoate Metabolism	<.001	−36.2	<.001	−38.9	<.001	−55.5	<.001	−48.7
3-Methyl catechol sulfate (1)	Benzoate metabolism	<.001	−33.5	<.001	−40.1	<.001	−49.8	<.001	−55.1
4-Hydroxycoumarin	Tobacco smoke metabolism	<.001	−27.2	<.001	−53.6	<.001	−42.9	<.001	−40.0
4-Allylphenol sulfate	Other xenobiotic	<.001	−24.8	.312	5.4	<.001	−22.2	.26	13.1
4-Vinylguaiacol sulfate	Other xenobiotic	.001	−22.4	<.001	−25.6	.002	−7.5	.005	18.1
Pyrraline	Other xenobiotic	.003	−15.9	.295	22.5	<.001	−18.5	.29	20.0
Thymol sulfate	Other xenobiotic	.003	−12.5	.025	1134.6	<.001	−37.2	.46	110.7
2,8-Quinolinediol sulfate	Other xenobiotic	.017	−12.2	.306	33.6	.028	−7.8	.41	31.3
3-Hydroxypyridine sulfate	Chemical	.019	−9.8	<.001	−26.0	<.001	−26.3	<.001	−21.6
3-Methoxycatechol sulfate (2)	Benzoate metabolism	.021	−6.7	.015	−7.8	<.001	−26.9	.029	−9.7
2,3-Dihydroxypyridine	Other xenobiotic	.024	2.4	.007	−13.3	<.001	−24.3	.012	−11.5
4-Vinylphenol sulfate	Benzoate metabolism	.055	3.7	.236	33.9	<.001	−27.6	.003	5.5
Hydroquinone sulfate	Topical agents	.256	4.5	.049	8.4	.043	−3.9	.014	15.4
3-(3-Hydroxyphenyl)propionate sulfate	Benzoate metabolism	.033	84.8	.378	71.9	.003	94.2	.45	103.5
3-Acetylphenol sulfate	Other xenobiotic	.095	161.4	.011	−9.9	.155	64.8	<.001	−25.1
S-(3-Hydroxypropyl)mercapturic acid	Tobacco smoke	<.001	−67	NA	NA	0	−72	NA	NA
S-(2-Carboxyethyl)mercapturic acid	Tobacco smoke	<.001	−45	NA	NA	<.001	−55	NA	NA

NA = not applicable because the metabolite is not identified in urine or plasma.

Among the metabolites that showed significant increases upon switching to VS products was plasma thymol sulfate in non-menthol SMK (but not in menthol SMK), which is derived from thymol used as a food additive. Interestingly, its increase in plasma is accompanied by significant decrease in urinary levels. In addition, significant increase in urinary levels of 3-(3-hydroxyphenyl) propionate sulfate (HMDB ID: 0000375), which is a plant-derived metabolite, was observed in the SMK who were switched to VS products.

BoPH Changes in Vitamin Metabolism and Oxidative Stress Metabolism

Cigarette smoking is associated with depletion of micronutrients, eg, vitamins and free-radical scavenging metabolites essential to the body’s antioxidant defense mechanisms.^23–25 Examination of plasma metabolome following product-switching revealed alterations in circulating levels of several micronutrients (Table 4). For example, the metabolomic profile in SMK switched to VS Original indicated increased urinary levels of vitamin B₂, vitamin C (dehydroascorbate and oxalate), and vitamin B₆ (pyridoxate). Plasma metabolomic profiles of VS Original users and VS Menthol users also showed increases in vitamin C (threonate) and vitamin A (retinol and carotene diols) levels. Improvements in plasma glutathione metabolism and purine metabolism (hypoxanthine and urate) were also evident in the VS Original users relative to baseline smoking.

Table 4.

Relative Levels of Metabolites Involved in Vitamin Metabolism and Oxidative Stress in Smokers Switched to VS Original and VS Menthol Products

		Non-menthol smokers switched to VS Original				Menthol smokers switched to VS Menthol
		Urine		Plasma		Urine		Plasma
Metabolic pathway	Biochemical name	Adjusted p	Percentage change from baseline	Adjusted p	Percentage change from baseline	Adjusted p	Percentage change from baseline	Adjusted p	Percentage change from baseline
Riboflavin metabolism	Riboflavin (Vitamin B2)	<.001	108.0	NA	NA	<.001	117.0	NA	NA
Ascorbate and aldarate metabolism	Ascorbate (Vitamin C)	.32	1168.0	NA	NA	.121	1688.0	NA	NA
	Dehydroascorbate	.008	311.0	NA	NA	.003	1048.0	NA	NA
	Oxalate (ethanedioate)	.035	65.0	.195	107.0	.013	53.0	.03	21.0
	Threonate	.36	4.0	.023	21.0	.407	2.0	<.001	32.0
Vitamin B6 metabolism	Pyridoxate	.025	34.0	.213	13.0	.029	34.0	.207	22.0
Vitamin A metabolism	Retinol (vitamin A)	NA	NA	.042	7.0	NA	NA	<.001	13.0
	Carotene diol (1)	NA	NA	<.001	18.0	NA	NA	<.001	25.0
	Carotene diol (2)	NA	NA	.246	4.0	NA	NA	.046	13.0
	Carotene diol (3)	NA	NA	<.001	130.0	NA	NA	<.001	31.0
Glutathione metabolism	2-Aminobutyrate	NA	NA	.016	−9.0	NA	NA	.008	−10.0
	Cysteinylglycine	.265	62.0	.055	−6.0	.17	18.0	.001	−15.0
	5-Oxoproline	.337	1.0	<.001	−14.0	.093	−4.0	.027	−6.0
	Cysteine-glutathione disulfide	.265	62.0	.012	−9.0	.127	18.0	.008	−15.0
Y-Glutamyl amino acid	Y-Glutamylglutamate	NA	NA	.027	−8.0	NA	NA	.089	−4.0
	Y-Glutamylglutamine	NA	NA	.011	−7.0	NA	NA	.004	−7.0
	Y-Glutamylglycine	.080	−4.0	<.001	−12.0	.131	−2.0	<.001	−10.0
Purine metabolism	Hypoxanthine	.012	33.0	.002	−17.0	.087	18.0	<.001	−23.0
	Urate	.007	11.0	<.001	7.0	.057	8.0	.004	6.0

NA = not applicable because the metabolite is not identified in urine or plasma.

These BoPH also showed marked improvements in VS Menthol users compared with the levels found at baseline smoking (Table 4). Urinary levels of vitamin B₂ and the vitamin C metabolites, ascorbate and oxalate, were higher upon switching to VS Menthol. Plasma levels of oxalate and threonate (ascorbate metabolism) were higher in VS Menthol users, whereas the plasma levels of glutathione metabolism and purine metabolism were lower compared with baseline smoking.

By comparison, urinary levels of vitamin B₂ (riboflavin), vitamin C-related metabolites (dehydroascorbate and oxalate), and the vitamin B₆-associated metabolite (pyridoxate) were higher following product switching to either VS Original or VS Menthol. Moreover, switching to either VS product culminated in reduced urinary levels of hypoxanthine and urate (purine metabolites), which exhibit free-radical scavenging activity.

Discussion

ENDS are a diverse and relatively new category of tobacco products, and there is limited information on the biological/health effects of their use by consumers. In this study, we have used metabolomic profiling to differentiate the effects of short-term use of two VS ENDS products (VS Original and VS Menthol) from chronic cigarette smoking. Key findings from these analyses are as follows: (1) reduced exposure to nicotine and its metabolites, (2) reduced xenobiotic exposure to other cigarette smoke constituents, and (3) improved vitamin metabolism and reduced oxidative stress.

Global urine and plasma profiles revealed several statistically significant changes upon switching SMK to VS products (Supplementary Table 1). These differentiating metabolites were able to differentiate smoking from VS use in random forest analyses (Table 1, Supplementary Table S2, and Supplementary Figures S1 and S2). Metabolomic profiling detected nicotine and six of its metabolites in urine and four metabolites were detected in plasma, reflecting their short half-lives and fasting conditions under which blood collections were made (Table 2). Significant declines in nicotine and its metabolites were observed in VS Original and VS Menthol use, relative to baseline smoking. These results are consistent with the quantitative measurements of nicotine exposure from a previous study.¹³

Several investigators also have reported significant declines in HPHC biomarkers in SMK who switched to ENDS use.^11,12,26 Consistent with these results, metabolomic profiling also revealed that metabolites of several cigarette smoke constituents/toxicants also decreased after 5 days of VS use. These included metabolites of acrolein, 4-hydroxycoumarin, and other smoke constituents. Although a majority of the metabolites declined following 5 days of VS product use, two compounds—thymol sulfate and 3-(3-hydroxyphenyl) propionate sulfate—increased significantly (Table 3). Thymol is a natural compound and food additive, whereas 3-(3-hydroxyphenl) propionate sulfate is a metabolite derived from 3-(3-hydroxyphenyl) propanoic acid (HMDB ID: 0000375) (a metabolite of caffeic acid, present in coffee, vegetables, and fruits). Pyrraline (HMDB ID: 0033143), which appears to be food-derived product, also declined following VS usage. Thus, metabolomic profiling demonstrates declines in several xenobiotic-derived metabolites in short-term switching SMK to VS products. Targeted analyses of biomarkers of exposure revealed that switching SMK to the VS products significantly reduces HPHC exposure.¹³ Collectively, our findings indicate an overall reduced toxicant/xenobiotic exposure in VS Original and VS Menthol users.

The differentiating metabolites between baseline smoking and 5-day usage of VS products belonged to several different classes of biochemicals (Supplementary Table 1). In addition to xenobiotics, several lipid metabolites including glycerophoshphocholines and acyl carnitines were also important in differentiating the effects of smoking and ENDS use in Random Forest analyses (Table 1 and Supplementary Table 2). Carnitine plays a central role in transport of fatty acids to mitochondria for β-oxidation²⁷ and increased levels of acyl carnitines are reported to be associated with increased risk of cardiovascular death and other diseases.²⁸ Lipidomic analyses also have revealed differences in lung tissue lipid profiles in mice exposed to different tobacco products,²⁹ and serum of current smokers, former smokers, and chronic obstructive pulmonary disease patients.³⁰

Chronic cigarette smoking has been shown to cause depletion of micronutrients such as vitamins, which contributes to increased oxidative stress in SMK. Metabolomic profiling of chronic SMK, moist snuff consumers, and nonsmokers also revealed differences in vitamin levels and select metabolites indicative of oxidative stress status.¹⁸

Vitamin C, a key antioxidant micronutrient, is consistently reduced in SMK compared with nonsmokers.³¹ In the current study, there was an increase in circulating and excreted levels of vitamin C-related metabolites. Specifically, plasma threonate and oxalate levels were elevated in SMK switched to VS Menthol, and plasma threonate levels were increased in SMK switched to VS Original. Urinary dehydroascorbate and oxalate were increased in SMK switched to either VS Original or VS Menthol.

Vitamin B family members with antioxidant activity—folic acid, vitamin B2 (riboflavin), and vitamin B6 (pyridoxine)—are reduced in SMK compared with nonsmokers.^32,33 In this study, urinary levels of Vitamin B2- and B6-associated metabolite (pyridoxate) were increased following product switching to either VS Original or VS Menthol. Vitamin B2 acts as a cofactor for glutathione (GSH) reductase.³⁴ In addition, Vitamin B6 contributes to cellular antioxidant defense as a cofactor for enzymes that convert homocysteine to cysteine, the rate-limiting substrate for GSH synthesis.³⁵ SMK switched to either VS Original or VS Menthol were found to have reduced levels of circulating GSH metabolites. These data are consistent with the finding that GSH-related urinary metabolites, which are markers of oxidative stress, are reduced in SMK switched to ENDS products. Carotenoids, which are precursors of Vitamin A, are also depleted in cigarette smokers.³⁶ In SMK switched to VS Original and VS Menthol products, we found increased plasma levels of Vitamin A (retinol) and its carotene diol metabolites; however, no differences in urinary levels were detected.

Currently, there is limited information on the BoPH for ENDS use. A recent publication evaluated BoPH in the lungs of ENDS users, conventional combusted cigarette smokers and never tobacco users in a cross-sectional study.³⁷ Using bronchioalveolar lavage and brushings, lung BoPH were assessed by cell counts, cytokines, transcriptomics, and global methylation. Overall, the authors concluded that e-cigarettes are associated with less toxicity than cigarettes for smoking-related pathways.

The strengths of this study are the assessment of global plasma and urine metabolomic changes within subjects at baseline and after exclusive use of VS products. Global profiling results are consistent and reveal reductions in the levels of select HPHC and several other cigarette smoke toxicants upon switching to the ENDS products, and are consistent with the findings from previous work.¹³

This study also has several limitations. First, this study lacks a comparator group of a smoking abstinence cohort, which is necessary to determine whether smoking abstinence and product switching would lead to qualitatively and quantitatively similar changes. Second, the short duration of Vuse ENDS use, following switching from smoking, needs to be considered while interpreting the metabolomic data, as the smokers adapt to using the Vuse products. And, a comprehensive diet history of study subjects prior to enrollment (baseline smoking) was not available, and additionally, diet was not controlled in the study; subjects were provided non-mutagenic diet during the clinical confinement. In this article, because we considered only those metabolites with ≥90% fill (metabolites detected in 90% or more of the study subjects), it is less likely that diet history would be a major factor in confounding metabolite profiles reported herein.

Given the diversity of ENDS products, some have reported increased inflammation in ENDS users, relative to nontobacco users.³⁸ Furthermore, there was an outbreak of e-cigarette, or vaping, product use-associated lung injury, which was largely associated with the use of tetrahydocannabinol.³⁹ It is important to emphasize that our findings are specific to the investigated study products, and generalization across the ENDS category requires careful consideration of the product characteristics.

In conclusion, short-term switching of SMK to VS Original and VS Menthol was characterized by reduced toxicant/xenobiotic load and potential improvement in vitamin metabolism and antioxidant defense pathways.

Supplementary Material

A Contributorship Form detailing each author’s specific involvement with this content, as well as any supplementary data, are available online at https://academic.oup.com/ntr.

Supplementary Table S1. Summary of significantly different metabolites identified in urine and plasma of smokers switched to VS Original and VS Menthols products.

Supplementary Table S2. Top 30 differentiating metabolites identified from random forest analyses in urine and plasma of menthol smokers switched to VS Menthol product.

Supplementary Figure S1. Random forest analysis of urinary metabolomics profiles upon switching from smoking to ENDS use. The predictive accuracy of the random forest model built on the metabolomics data with (A) or exclusion of nicotine and its metabolites (C) for those switched to VS Original product. The predictive accuracy unchanged with the inclusion or exclusion of nicotine metabolites. The predictive accuracy for VS Menthol with (B) and without nicotine and its metabolites (D) is comparable.

Supplementary Figure S2. Random forest analysis of plasma metabolomics profiles upon switching from smoking to ENDS use. The predictive accuracy of the random forest models built on plasma metabolomics with (A) or without nicotine and its metabolites (C) for VS Original users. The predictive accuracy for VS Menthol users remains comparable with (B) or without (D) the inclusion of nicotine and its metabolites in the analyses.

Supplementary File S1. List of all identified metabolites and their intensity data in urine samples collected from 5-day Vuse switching studies.

Supplementary File S2. List of all identified metabolites and their intensity data in plasma samples collected from 5-day Vuse switching studies.

Acknowledgments

We thank Megan Whelen, Dr. Jeffery Smith, and Dr. Kyung Jason Hong for their careful edits and comments to the manuscript. We also thank Herman Krebs for helping shipping urine and plasma samples to Metabolon Inc.

Funding

The study and the manuscript preparation were funded by RAI Services Company, a wholly owned subsidiary of Reynolds American Inc., which is a wholly owned subsidiary of British American Tobacco plc.

Declaration of Interests

CJL and GLP are full-time employees of RAI Services Company. GL is a former employee of RAI Services Company. CRY is a full-time employee of Quinn Pharms. None of the authors have any other conflict of interest to declare.