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

Abstract

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.

Keywords: 2-cyanoethylmercapturic acid; AHRR; DNA methylation; anabasine; cg05575921; propylene glycol; smoking; vaping.

Figure 1.

The relationship of serum cotinine and carbon monoxide levels for the control and smoking participants (n = 366, adj-R² = 0.68 for cg05575921 and n = 368, adj-R² = 0.60 for exhaled carbon monoxide).

Figure 2.

Cubic spline fit of the relationship of self-reported daily cigarette consumption over the past week to serum cotinine and cg05575921 levels for the control and smoking participants (n = 381, adj-R² = 0.85 and n = 366, adj-R² = 0.71, respectively).

Figure 3.

The relationship of serum cotinine to urine nicotine levels. The black line is the best fit line for a linear model (N = 187, adj-R² = 0.46).