DNA methylation at AHRR as a master predictor of smoke exposure and a biomarker for sleep and exercise

Abstract

Background: DNA methylation profiling may provide a more accurate measure of the smoking status than self-report and may be useful in guiding clinical interventions and forensic investigations. In the current study, blood DNA methylation profiles of nearly 800 Polish individuals were assayed using Illuminia EPIC and the inference of smoking from epigenetic data was explored. In addition, we focused on the role of the AHRR gene as a top marker for smoking and investigated its responsiveness to other lifestyle behaviors.

Results: We found > 450 significant CpGs associated with cigarette consumption, and overrepresented in various biological functions including cell communication, response to stress, blood vessel development, cell death, and atherosclerosis. The model consisting of cg05575921 in AHRR (p = 4.5 × 10^-32) and three additional CpGs (cg09594361, cg21322436 in CNTNAP2 and cg09842685) was able to predict smoking status with a high accuracy of AUC = 0.8 in the test set. Importantly, a gradual increase in the probability of smoking was observed, starting from occasional smokers to regular heavy smokers. Furthermore, former smokers displayed the intermediate DNA methylation profiles compared to current and never smokers, and thus our results indicate the potential reversibility of DNA methylation after smoking cessation. The AHRR played a key role in a predictive analysis, explaining 21.5% of the variation in smoking. In addition, the AHRR methylation was analyzed for association with other modifiable lifestyle factors, and showed significance for sleep and physical activity. We also showed that the epigenetic score for smoking was significantly correlated with most of the epigenetic clocks tested, except for two first-generation clocks.

Conclusions: Our study suggests that a more rapid return to never-smoker methylation levels after smoking cessation may be achievable in people who change their lifestyle in terms of physical activity and sleep duration. As cigarette smoking has been implicated in the literature as a leading cause of epigenetic aging and AHRR appears to be modifiable by multiple exogenous factors, it emerges as a promising target for intervention and investment.

Keywords: AHRR; DNA methylation; Epigenetic aging; Exercise; Lifestyle biomarkers; Sleep; Smoke exposure.

Fig. 1

Manhattan plot of EWAS for smoking adjusted for age, sex and blood cell count. Red horizontal line corresponds to FDR p < 0.05, with the top annotated markers meeting this threshold

Fig. 2

Epigenetic score (probability) for smoking for never smokers and current smokers within training and test sets, as determined by a binomial regression model

Fig. 3

Epigenetic score (probability) for smoking for different sample groups as determined by a binomial regression model. Smokers were divided into four groups based on frequency of smoking: occasional smokers, regular light smokers, regular medium smokers and regular heavy smokers

Fig. 4

Boxplots of methylation levels for 4 CpGs included in the predictive model for smoking and comparison between current smokers, former smokers and never smokers. Groups were matched for age and mean age of each group was 46.3