AHRR methylation predicts smoking status and smoking intensity in both saliva and blood DNA

Objective Assessments of Smoking and Drinking Outperform Clinical Phenotypes in Predicting Variance in Epigenetic Aging

The reliability of the associations of the acceleration of epigenetic aging (EA) indices with clinical phenotypes other than for smoking and drinking is poorly understood. Furthermore, the majority of clinical phenotyping studies have been conducted using data from subjects of European ancestry. In order to address these limitations, we conducted clinical, physiologic, and epigenetic assessments of a cohort of 278 middle-aged African American adults and analyzed the associations with the recently described principal-components-trained version of GrimAge (i.e., PC-GrimAge) and with the DunedinPACE (PACE) index using regression analyses. We found that 74% of PC-GrimAge accelerated aging could be predicted by a simple baseline model consisting of age, sex, and methylation-sensitive digital PCR (MSdPCR) assessments of smoking and drinking. The addition of other serological, demographic, and medical history variables or PACE values did not meaningfully improve the prediction, although some variables did significantly improve the model fit. In contrast, clinical variables mapping to cardiometabolic syndrome did independently contribute to the prediction of PACE values beyond the baseline model. The PACE values were poorly correlated with the GrimAge values (r = 0.2), with little overlap in variance explained other than that conveyed by smoking and drinking. The results suggest that EA indices may differ in the clinical information that they provide and may have significant limitations as screening tools to guide patient care.

Inference of tobacco and alcohol consumption habits from DNA methylation analysis of blood

DNA methylation has become a biomarker of great interest in the forensic and clinical fields. In criminal investigations, the study of this epigenetic marker has allowed the development of DNA intelligence tools providing information that can be useful for investigators, such as age prediction. Following a similar trend, when the origin of a sample in a criminal scenario is unknown, the inference of an individual's lifestyle such as tobacco use and alcohol consumption could provide relevant information to help in the identification of DNA donors at the crime scene. At the same time, in the clinical domain, prediction of these trends of consumption could allow the identification of people at risk or better identification of the causes of different pathologies. In the present study, DNA methylation data from the UK AIRWAVE study was used to build two binomial logistic models for the inference of smoking and drinking status. A total of 348 individuals (116 non-smokers, 116 former smokers and 116 smokers) plus a total of 237 individuals (79 non-drinkers, 79 moderate drinkers and 79 drinkers) were used for development of tobacco and alcohol consumption prediction models, respectively. The tobacco prediction model was composed of two CpGs (cg05575921 in AHRR and cg01940273) and the alcohol prediction model three CpGs (cg06690548 in SLC7A11, cg0886875 and cg21294714 in MIR4435-2HG), providing correct classifications of 86.49% and 74.26%, respectively. Validation of the models was performed using leave-one-out cross-validation. Additionally, two independent testing sets were also assessed for tobacco and alcohol consumption. Considering that the consumption of these substances could underlie accelerated epigenetic ageing patterns, the effect of these lifestyles on the prediction of age was evaluated. To do that, a quantile regression model based on previous studies was generated, and the potential effect of tobacco and alcohol consumption with the epigenetic age was assessed. The Wilcoxon test was used to evaluate the residuals generated by the model and no significant differences were observed between the categories analyzed.

A validated restriction enzyme ddPCR cg05575921 (AHRR) assay to accurately assess smoking exposure

BACKGROUND & METHODS

In this study, a novel restriction enzyme (RE) digestion-based droplet digital polymerase chain reaction (ddPCR) assay was designed for cg005575921 within the AHRR gene body and compared with matching results obtained by bisulfite conversion (BIS) ddPCR and Illumina DNA methylation array.

RESULTS

The RE ddPCR cg05575921 assay appeared concordant with BIS ddPCR (r2 = 0.94, P < 0.0001) and, when compared with the Illumina array, had significantly better smoking status classification performance for current versus never smoked (AUC 0.96 versus 0.93, P < 0.04) and current versus ex-smoker (AUC 0.88 versus 0.83, P < 0.04) comparisons.

CONCLUSIONS

The RE ddPCR cg05575921 assay accurately predicts smoking status and could be a useful component of 'precision-medicine' chronic disease risk screening tools.

The Influence of Smoking and Occupational Risk Factors on DNA Methylation in the AHRR and F2RL3 Genes

BACKGROUND

AHRR and F2RL3 hypomethylation has been associated with lung cancer. In this study, we investigated the cross-sectional association between smoking and occupational exposures, and AHRR and F2RL3 methylation.

METHODS

A case-control study was nested in CARTaGENE to examine the association between AHRR and F2RL3 methylation and lung cancer risk (200 cases; 400 controls). A secondary analysis was conducted using the data collected from this nested study; namely, baseline information on participants' smoking behavior and longest-held job was obtained. A cumulative smoking index summarized information on the number of cigarettes smoked, duration of smoking, and time since cessation. Exposure to 13 occupational agents was estimated using the Canadian Job Exposure Matrix. In baseline blood samples, methylation ratios of 40 CpG sites in the AHRR and F2RL3 genes were measured using Sequenom EpiTYPER. Separate least squares regression models were used to estimate the associations between smoking and occupational exposures, and average AHRR and F2RL3 methylation levels, while adjusting for confounders identified from directed acyclic graphs.

RESULTS

In both genes, smoking was associated with lower average methylation levels. Occupational exposure to aromatic amines, cadmium, and formaldehyde were associated with lower AHRR methylation while, only benzene was associated with F2RL3 hypomethylation; these associations were stronger among ever smokers.

CONCLUSIONS

Our findings support that smoking and occupational exposures to some agents are associated with AHRR and F2RL3 hypomethylation.

IMPACT

Our results inform on mechanisms underlying environmental exposures in lung cancer etiology; future studies should prioritize studying joint exposures.

Aromatic Hydrocarbon Receptor Repressor (AHRR) is a biomarker of ambient air pollution exposure and Coronary Artery Disease (CAD)

Two hundred and twenty subjects were recruited while undergoing cardiac catheterization. AHRR cg05575921 methylation was shown to be significantly decreased in ever smokers compared to never smokers (Mean± SD = 64.2 ± 17.2 vs 80.1 ± 11.1 respectively; P < 0.0001). In addition, higher urinary levels of 2-OHNAP and 2-OHFLU were significantly associated with more AHRR cg05575921 hypomethylation, even after correcting for smoking (β[95%CI]= -4.161[-7.553, -0.769]; P = 0.016 and -5.190[-9.761, -0.618]; P = 0.026, respectively) but not 1-OHPYR (β[95%CI]= -3.545 [-10.935, 3.845]; P = 0.345). Additionally, hypomethylation of AHRR ROI was significantly associated with obstructive coronary artery disease (CAD) after adjusting for smoking, age, sex, diabetes and dyslipidemia (OR [95%CI] = 1.024[1.000 - 1.048]; P = 0.046). Results of this study necessitate further validation to potentially consider clinical incorporation of AHRR methylation status as an early predictive biomarker for the potential association between ambient air pollution and CAD.

Validation of an Integrated Genetic-Epigenetic Test for the Assessment of Coronary Heart Disease

BACKGROUND

Coronary heart disease (CHD) is the leading cause of death in the world. Unfortunately, many of the key diagnostic tools for CHD are insensitive, invasive, and costly; require significant specialized infrastructure investments; and do not provide information to guide postdiagnosis therapy. In prior work using data from the Framingham Heart Study, we provided in silico evidence that integrated genetic-epigenetic tools may provide a new avenue for assessing CHD.

METHODS AND RESULTS

In this communication, we use an improved machine learning approach and data from 2 additional cohorts, totaling 449 cases and 2067 controls, to develop a better model for ascertaining symptomatic CHD. Using the DNA from the 2 new cohorts, we translate and validate the in silico findings into an artificial intelligence-guided, clinically implementable method that uses input from 6 methylation-sensitive digital polymerase chain reaction and 10 genotyping assays. Using this method, the overall average area under the curve, sensitivity, and specificity in the 3 test cohorts is 82%, 79%, and 76%, respectively. Analysis of targeted cytosine-phospho-guanine loci shows that they map to key risk pathways involved in atherosclerosis that suggest specific therapeutic approaches.

CONCLUSIONS

We conclude that this scalable integrated genetic-epigenetic approach is useful for the diagnosis of symptomatic CHD, performs favorably as compared with many existing methods, and may provide personalized insight to CHD therapy. Furthermore, given the dynamic nature of DNA methylation and the ease of methylation-sensitive digital polymerase chain reaction methodologies, these findings may pave a pathway for precision epigenetic approaches for monitoring CHD treatment response.

Stage 2 Registered Report: Epigenetic Intergenerational Transmission: Mothers' Adverse Childhood Experiences and DNA Methylation

OBJECTIVE

Individual differences in risk for mental disorders over the lifespan are shaped by forces acting before the individual is born-in utero, but likely even earlier, during the mother's own childhood. The environmental epigenetics hypothesis proposes that sustained effects of environmental conditions on gene expression are mediated by epigenetic mechanisms. Recent human studies have shown that adversities in childhood are correlated with DNA methylation (DNAm) in adulthood. In the current study, we tested the following pre-registered hypotheses: Mothers' adverse childhood experiences (ACEs) are correlated with DNAm in peripheral blood during pregnancy (hypothesis 1) and in cord blood samples from newborn infants (hypothesis 2), and women's depression and anxiety symptoms during pregnancy mediate the association between mothers' ACE exposure and prenatal/neonatal DNA methylation (hypothesis 3).

METHOD

Data were from the Avon Longitudinal Study of Parents and Children Accessible Resource for Integrated Epigenomic Studies substudy. Women provided retrospective self-reports during pregnancy of ACE exposure. We conducted an epigenome-wide association study testing whether mothers' ACE exposure, cumulative score (0-10), was associated with DNAm in maternal antenatal blood and infant cord blood in more than 450,000 CpG (point on DNA sequence where cytosine and guanine base pairs are linked by a phosphate, where methylation usually occurs) sites on the Illumina 450K BeadChip. Analyses for cord blood were separated by infant sex, a pre-registered analysis.

RESULTS

Hypothesis 1: In 896 mother-infant pairs with available methylation and ACE exposure data, there were no significant associations between mothers' ACE score and DNAm from antenatal peripheral blood, after controlling for covariates. Hypothesis 2: In infant cord blood, there were 5 CpG sites significantly differentially methylated in relation to mothers' ACEs (false discovery rate [FDR] < .05), but only in male offspring. Effect sizes were medium, with partial eta squared values ranging from 0.060 to 0.078. CpG sites were in genes related to mitochondrial function and neuronal development in the cerebellum. Hypothesis 3: There was no mediation by maternal anxiety/depression symptoms found between mothers' ACEs score and DNAm in the significant CpG sites in male cord blood. Mediation was not tested in antenatal peripheral blood, because no direct association between mothers' ACE score and antenatal peripheral blood was found.

CONCLUSION

Our results show that mothers' ACE exposure is associated with DNAm in male offspring, supporting the notion that DNAm could be a marker of intergenerational biological embedding of mothers' childhood adversity.

STUDY REGISTRATION INFORMATION

Epigenetic Intergenerational Transmission: Mothers' Adverse Childhood Experiences and DNA Methylation; https://doi.org/10.1016/j.jaac.2020.03.008.

Association of DNA methylation signatures with cognitive performance among smokers and ex-smokers

INTRODUCTION

Alterations in DNA methylation profiles have been associated with cancer, and can be influenced by environmental factors such as smoking. A small but growing literature indicates there are reproducible and robust differences in methylation levels among smokers, never smokers, and ex-smokers. Here, we compared differences in salivary DNA methylation levels among current and ex-smokers (at least 2 years abstinent).

METHODS

Smokers (n=26) and ex-smokers (n=30) provided detailed smoking histories, completed the Paced Auditory Serial Addition Test (PASAT), and submitted a saliva sample. Whole-genome DNA methylation from saliva was performed, and ANCOVA models and a receiver operating characteristic (ROC) curve were used for the differences between groups and the performance of significant CpG sites.

RESULTS

After controlling for race, age, and gender, smokers had significantly lower methylation levels than ex-smokers in two CpG sites: cg05575921 (AHRR) and cg21566642 (ALPPL2). Based on the ROC analyses, both CpGs had strong classification potentials (cg05575921 AUC=0.97 and cg21566642 AUC=0.93) in differentiating smoking status. Across all subjects, the percent methylation of cg05575921 (AHRR) and cg21566642 (ALPPL2) positively correlated with the length of the last quit attempt (r=0.65 and 0.64, respectively, p<0.001) and PASAT accuracy (r=0.29 and 0.30, respectively, p<0.05).

CONCLUSIONS

In spite of the small sample size and preliminary research, our results replicate previously reported differences in AHRR hypomethylation among smokers. Furthermore, we show that the duration of smoking abstinence is associated with a recovery of methylation in ex-smokers, which may be linked to a reduced risk of smoking-associated diseases. The association with cognitive performance suggests that the hypomethylation of AHRR in saliva may reflect systemic exposure to cigarette-related toxicants that negatively affect cognitive performance, and should be validated in larger studies.

Contrasting Association of Maternal Plasma Biomarkers of Smoking and 1-Carbon Micronutrients with Offspring DNA Methylation: Evidence of Aryl Hydrocarbon Receptor Repressor Gene-Smoking-Folate Interaction

BACKGROUND

Maternal prenatal smoking is known to alter offspring DNA methylation (DNAm). However, there are no effective interventions to mitigate smoking-induced DNAm alteration.

OBJECTIVES

This study investigated whether 1-carbon nutrients (folate, vitamins B6, and B12) can protect against prenatal smoking-induced offspring DNAm alterations in the aryl hydrocarbon receptor repressor (AHRR) (cg05575921), GFI1 (cg09935388), and CYP1A1 (cg05549655) genes.

METHODS

This study included mother-newborn dyads from a racially diverse US birth cohort. The cord blood DNAm at the above 3 sites were derived from a previous study using the Illumina Infinium MethylationEPIC BeadChip. Maternal smoking was assessed by self-report and plasma biomarkers (hydroxycotinine and cotinine). Maternal plasma folate, and vitamins B6 and B12 concentrations were obtained shortly after delivery. Linear regressions, Bayesian kernel machine regression, and quantile g-computation were applied to test the study hypothesis by adjusting for covariables and multiple testing.

RESULTS

The study included 834 mother-newborn dyads (16.7% of newborns exposed to maternal smoking). DNAm at cg05575921 (AHRR) and at cg09935388 (GFI1) was inversely associated with maternal smoking biomarkers in a dose-response fashion (all P < 7.01 × 10-13). In contrast, cg05549655 (CYP1A1) was positively associated with maternal smoking biomarkers (P < 2.4 × 10-6). Folate concentrations only affected DNAm levels at cg05575921 (AHRR, P = 0.014). Regression analyses showed that compared with offspring with low hydroxycotinine exposure (<0.494) and adequate maternal folate concentrations (quartiles 2-4), an offspring with high hydroxycotinine exposure (≥0.494) and low folate concentrations (quartile 1) had a significant reduction in DNAm at cg05575921 (M-value, ß ± SE = -0.801 ± 0.117, P = 1.44 × 10-11), whereas adequate folate concentrations could cut smoking-induced hypomethylation by almost half. Exposure mixture models further supported the protective role of adequate folate concentrations against smoking-induced aryl hydrocarbon receptor repressor (AHRR) hypomethylation.

CONCLUSIONS

This study found that adequate maternal folate can attenuate maternal smoking-induced offspring AHRR cg05575921 hypomethylation, which has been previously linked to a range of pediatric and adult diseases.

Defining Interactions Between the Genome, Epigenome, and the Environment in Inflammatory Bowel Disease: Progress and Prospects

Recent advances in our understanding of the pathogenesis of inflammatory bowel disease (IBD) have highlighted the complex interplay between the genome, the epigenome, and the environment. Despite the exciting advances in genomics that have enabled the identification of over 200 susceptibility loci, these only account for a small proportion of the disease variance and the estimated heritability in IBD. It is likely that gene-environment (GxE) interactions contribute to "missing heritability" and these may act through epigenetic mechanisms. Several environmental factors, such as the microbiome, nutrition, and tobacco smoking, induce alterations in the epigenome of children and adults, which may impact disease susceptibility. Other mechanisms for GxE interactions are also directly pertinent in early life. We discuss a model in which environmental factors imprint disease risk in a window of susceptibility during infancy that may contribute to later disease onset, whereas other elements of the exposome act later in life and contribute directly to the pathogenesis and course of the disease. Understanding the mechanisms underlying GxE interactions may provide the basis for new therapeutic targets or preventative strategies for IBD.

The Reversion of the Epigenetic Signature of Coronary Heart Disease in Response to Smoking Cessation

Coronary heart disease (CHD) is the leading cause of death worldwide. However, current diagnostic tools for CHD, such as coronary computed tomography angiography (CCTA), are poorly suited for monitoring treatment response. Recently, we have introduced an artificial-intelligence-guided integrated genetic-epigenetic test for CHD whose core consists of six assays that determine methylation in pathways known to moderate the pathogenesis of CHD. However, whether methylation at these six loci is sufficiently dynamic to guide CHD treatment response is unknown. To test that hypothesis, we examined the relationship of changes in these six loci to changes in cg05575921, a generally accepted marker of smoking intensity, using DNA from a cohort of 39 subjects undergoing a 90-day smoking cessation intervention and methylation-sensitive digital PCR (MSdPCR). We found that changes in epigenetic smoking intensity were significantly associated with reversion of the CHD-associated methylation signature at five of the six MSdPCR predictor sites: cg03725309, cg12586707, cg04988978, cg17901584, and cg21161138. We conclude that methylation-based approaches could be a scalable method for assessing the clinical effectiveness of CHD interventions, and that further studies to understand the responsiveness of these epigenetic measures to other forms of CHD treatment are in order.

Changing Smoking Behavior and Epigenetics: A Longitudinal Study of 4,432 Individuals From the General Population

BACKGROUND

Hypomethylation of the aryl hydrocarbon receptor repressor (AHRR) gene indicates long-term smoking exposure and might therefore be a monitor for smoking-induced disease risk. However, studies of individual longitudinal changes in AHRR methylation are sparse.

RESEARCH QUESTION

How does the recovery of AHRR methylation depend on change in smoking behaviors and demographic variables?

STUDY DESIGN AND METHODS

This study included 4,432 individuals from the Copenhagen City Heart Study, with baseline and follow-up blood samples and smoking information collected approximately 10 years apart. AHRR methylation at the cg05575921 site was measured in bisulfite-treated leukocyte DNA. Four smoking groups were defined: participants who never smoked (Never-Never), participants who formerly smoked (Former-Former), participants who quit during the study period (Current-Former), and individuals who smoked at both baseline and follow-up (Current-Current). Methylation recovery was defined as the increase in AHRR methylation between baseline and follow-up examination.

RESULTS

Methylation recovery was highest among participants who quit, with a median methylation recovery of 5.58% (interquartile range, 1.79; 9.15) vs 1.64% (interquartile range, -1.88; 4.96) in the Current-Current group (P < .0001). In individuals who quit smoking, older age was associated with lower methylation recovery (P < .0001). In participants who quit aged > 65 years, methylation recovery was 5.9% at 5.6 years after quitting; methylation recovery was 8.5% after 2.8 years for participants who quit aged < 55 years.

INTERPRETATION

AHRR methylation recovered after individuals quit smoking, and recovery was more pronounced and occurred faster in younger compared with older interim quitters.

Targeted DNA methylation analysis and prediction of smoking habits in blood based on massively parallel sequencing

Tobacco smoking is a frequent habit sustained by > 1.3 billion people in 2020 and the leading preventable factor for health risk and premature mortality worldwide. In the forensic context, predicting smoking habits from biological samples may allow broadening DNA phenotyping. In this study, we aimed to implement previously published smoking habit classification models based on blood DNA methylation at 13 CpGs. First, we developed a matching lab tool based on bisulfite conversion and multiplex PCR followed by amplification-free library preparation and targeted paired-end massively parallel sequencing (MPS). Analysis of six technical duplicates revealed high reproducibility of methylation measurements (Pearson correlation of 0.983). Artificially methylated standards uncovered marker-specific amplification bias, which we corrected via bi-exponential models. We then applied our MPS tool to 232 blood samples from Europeans of a wide age range, of which 90 were current, 71 former and 71 never smokers. On average, we obtained 189,000 reads/sample and 15,000 reads/CpG, without marker drop-out. Methylation distributions per smoking category roughly corresponded to previous microarray analysis, showcasing large inter-individual variation but with technology-driven bias. Methylation at 11 out of 13 smoking-CpGs correlated with daily cigarettes in current smokers, while solely one was weakly correlated with time since cessation in former smokers. Interestingly, eight smoking-CpGs correlated with age, and one displayed weak but significant sex-associated methylation differences. Using bias-uncorrected MPS data, smoking habits were relatively accurately predicted using both two- (current/non-current) and three- (never/former/current) category model, but bias correction resulted in worse prediction performance for both models. Finally, to account for technology-driven variation, we built new, joint models with inter-technology corrections, which resulted in improved prediction results for both models, with or without PCR bias correction (e.g. MPS cross-validation F₁-score > 0.8; 2-categories). Overall, our novel assay takes us one step closer towards the forensic application of viable smoking habit prediction from blood traces. However, future research is needed towards forensically validating the assay, especially in terms of sensitivity. We also need to further shed light on the employed biomarkers, particularly on the mechanistics, tissue specificity and putative confounders of smoking epigenetic signatures.

Differential methylation in CD44 and SEC23A is associated with time preference in older individuals

Time preference is a measure used to ascertain the level of which individuals prefer smaller, immediate rewards over larger, delayed rewards. We explored how an individual's time preference associates with their epigenetic profile. Time preferences were ascertained by asking participants of the Northern Ireland COhort for the Longitudinal study of Ageing to make a series of choices between two hypothetical income scenarios. From these, eight 'time preference' categories were derived, ranging from "patient" to "impatient" on an ordinal scale. The Infinium High Density Methylation Assay, MethylationEPIC (Illumina) was used to evaluate the status of 862,927 CpGs. Time preference and DNA methylation data were obtained for 1648 individuals. Four analyses were conducted, assessing the methylation patterns at single site resolution between patient and impatient individuals using two adjustment models. In this discovery cohort analysis, two CpG sites were identified with significantly different levels of methylation (p < 9 × 10^-8) between the individuals allocated to the patient group and the remaining population following adjustment for covariates; cg08845621 within CD44 and cg18127619 within SEC23A. Neither of these genes have previously been linked to time preference. Epigenetic modifications have not previously been linked to time preference using a population cohort but they may represent important biomarkers of accumulated, complex determinants of this trait. Further analysis is warranted of both the top-ranked results and of DNA methylation as an important link between measurable biomarkers and health behaviours.

Promising applications of human-derived saliva biomarker testing in clinical diagnostics

Saliva testing is a vital method for clinical applications, for its noninvasive features, richness in substances, and the huge amount. Due to its direct anatomical connection with oral, digestive, and endocrine systems, clinical usage of saliva testing for these diseases is promising. Furthermore, for other diseases that seeming to have no correlations with saliva, such as neurodegenerative diseases and psychological diseases, researchers also reckon saliva informative. Tremendous papers are being produced in this field. Updated summaries of recent literature give newcomers a shortcut to have a grasp of this topic. Here, we focused on recent research about saliva biomarkers that are derived from humans, not from other organisms. The review mostly addresses the proceedings from 2016 to 2022, to shed light on the promising usage of saliva testing in clinical diagnostics. We recap the recent advances following the category of different types of biomarkers, such as intracellular DNA, RNA, proteins and intercellular exosomes, cell-free DNA, to give a comprehensive impression of saliva biomarker testing.

Polymethylation scores for prenatal maternal smoke exposure persist until age 15 and are detected in saliva in the Fragile Families and Child Wellbeing cohort

Prenatal maternal smoking is associated with low birthweight, neurological disorders, and asthma in exposed children. DNA methylation signatures can function as biomarkers of prenatal smoke exposure. However, the robustness of DNA methylation signatures across child ages, genetic ancestry groups, or tissues is not clear. Using coefficients from a meta-analysis of prenatal smoke exposure and DNA methylation in newborn cord blood, we created polymethylation scores of saliva DNA methylation from children at ages 9 and 15 in the Fragile Families and Child Wellbeing study. In the full sample at age 9 (n = 753), prenatal smoke exposure was associated with a 0.51 (95%CI: 0.35, 0.66) standard deviation higher polymethylation score. The direction and magnitude of the association was consistent in European and African genetic ancestry samples. In the full sample at age 15 (n = 747), prenatal smoke exposure was associated with a 0.48 (95%CI: 0.32, 0.63) standard deviation higher polymethylation score, and the association was attenuated among the European and Admixed-Latin genetic ancestry samples. The polymethylation score classified prenatal smoke exposure accurately (AUC age 9 = 0.77, age 15 = 0.76). Including the polymethylation score increased the AUC of base model covariates by 5 (95% CI: (2.1, 7.2)) percentage points, while including a single candidate site in the AHRR gene did not (P-value = 0.19). Polymethylation scores for prenatal smoking were portable across genetic ancestries and more accurate than an individual DNA methylation site. Polymethylation scores from saliva samples could serve as robust and practical biomarkers of prenatal smoke exposure.

Epigenetic and Proteomic Biomarkers of Elevated Alcohol Use Predict Epigenetic Aging and Cell-Type variation Better Than Self-Report

Excessive alcohol consumption (EAC) has a generally accepted effect on morbidity and mortality, outcomes thought to be reflected in measures of epigenetic aging (EA). As the association of self-reported EAC with EA has not been consistent with these expectations, underscoring the need for readily employable non-self-report tools for accurately assessing and monitoring the contribution of EAC to accelerated EA, newly developed alcohol consumption DNA methylation indices, such as the Alcohol T Score (ATS) and Methyl DetectR (MDR), may be helpful. To test that hypothesis, we used these new indices along with the carbohydrate deficient transferrin (CDT), concurrent as well as past self-reports of EAC, and well-established measures of cigarette smoking to examine the relationship of EAC to both accelerated EA and immune cell counts in a cohort of 437 young Black American adults. We found that MDR, CDT, and ATS were intercorrelated, even after controlling for gender and cotinine effects. Correlations between EA and self-reported EAC were low or non-significant, replicating prior research, whereas correlations with non-self-report indices were significant and more substantial. Comparing non-self-report indices showed that the ATS predicted more than four times as much variance in EA, CDT4 cells and B-cells as for both the MDR and CDT, and better predicted indices of accelerated EA. We conclude that each of the non-self-report indices have differing predictive capacities with respect to key alcohol-related health outcomes, and that the ATS may be particularly useful for clinicians seeking to understand and prevent accelerated EA. The results also underscore the likelihood of substantial underestimates of problematic use when self-report is used and a reduction in correlations with EA and variance in cell-types.

Longitudinal change in blood DNA epigenetic signature after smoking cessation

Cigarette smoking is associated with epigenetic changes that may be reversible following smoking cessation. Whole blood DNA methylation was evaluated in Framingham Heart Study Offspring (n = 169) and Third Generation (n = 30) cohort participants at two study visits 6 years apart and in Atherosclerosis Risk in Communities (ARIC) study (n = 222) participants at two study visits 20 years apart. Changes in DNA methylation (delta β values) at 483,565 cytosine-phosphate-guanine (CpG) sites and differentially methylated regions (DMRs) were compared between participants who were current, former, or never smokers at both visits (current-current, former-former, never-never, respectively), versus those who quit in the interim (current-former). Interim quitters had more hypermethylation at four CpGs annotated to AHRR, one CpG annotated to F2RL3, and one intergenic CpG (cg21566642) compared with current-current smokers (FDR < 0.02 for all), and two significant DMRs were identified. While there were no significant differentially methylated CpGs in the comparison of interim quitters and former-former smokers, 106 DMRs overlapping with small nucleolar RNA were identified. As compared with all non-smokers, current-current smokers additionally had more hypermethylation at two CpG sites annotated to HIVEP3 and TMEM126A, respectively, and another intergenic CpG (cg14339116). Gene transcripts associated with smoking cessation were implicated in immune responses, cell homoeostasis, and apoptosis. Smoking cessation is associated with early reversion of blood DNA methylation changes at CpG sites annotated to AHRR and F2RL3 towards those of never smokers. Associated gene expression suggests a role of longitudinal smoking-related DNA methylation changes in immune response processes.

Cognition, Aryl Hydrocarbon Receptor Repressor Methylation, and Abstinence Duration-Associated Multimodal Brain Networks in Smoking and Long-Term Smoking Cessation

Cigarette smoking and smoking cessation are associated with changes in cognition and DNA methylation; however, the neurobiological correlates of these effects have not been fully elucidated, especially in long-term cessation. Cognitive performance, percent methylation of the aryl hydrocarbon receptor repressor (AHRR) gene, and abstinence duration were used as references to supervise a multimodal fusion analysis of functional, structural, and diffusion magnetic resonance imaging (MRI) data, in order to identify associated brain networks in smokers and ex-smokers. Correlations among these networks and with smoking-related measures were performed. Cognition-, methylation-, and abstinence duration-associated networks discriminated between smokers and ex-smokers and correlated with differences in fractional amplitude of low frequency fluctuations (fALFF) values, gray matter volume (GMV), and fractional anisotropy (FA) values. Long-term smoking cessation was associated with more accurate cognitive performance, as well as lower fALFF and more GMV in the hippocampus complex. The methylation- and abstinence duration-associated networks positively correlated with smoking-related measures of abstinence duration and percent methylation, respectively, suggesting they are complementary measures. This analysis revealed structural and functional co-alterations linked to smoking abstinence and cognitive performance in brain regions including the insula, frontal gyri, and lingual gyri. Furthermore, AHRR methylation, a promising epigenetic biomarker of smoking recency, may provide an important complement to self-reported abstinence duration.

Digital methylation assessments of alcohol and cigarette consumption account for common variance in accelerated epigenetic ageing

Smoking and Heavy Alcohol Consumption (HAC) are established risk factors for myriad complex disorders of ageing. Yet many prior studies of Epigenetic Ageing (EA) have shown only modest effects of smoking and drinking on accelerated ageing. One potential reason for this conundrum might be the reliance of some prior EA studies on self-reported substance use, which may be unreliable in many samples. To test whether novel, non-self-reported indices would show a stronger association of smoking and HAC to EA, we used methylation sensitive digital PCR (MSdPCR) and data from 437 African American subjects from Wave 7 of the Family and Community Health Study Offspring Cohort to examine the effects of subjective and objective measures of smoking and HAC on 7 indices of EA. Because of limited overall correlations between the various EA indices, we examined patterns of association separately for each index. Consistent with expectations, MSdPCR assessments of smoking and HAC, but not self-reported alcohol consumption, were strongly correlated with accelerated EA. MSdPCR assessments of smoking and HAC accounted for 57% of GrimAge acceleration and the shared variance in GrimAge and DunedinPOAM accelerated EA. We conclude that MSdPCR assessments of smoking and HAC are valuable tools for understanding EA, represent directly targetable conditions for the prevention of premature ageing, and substantially improve upon self-reported assessment of smoking and HAC.

DNA methylation-based predictors of health: applications and statistical considerations

DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.

Epigenome-wide association study and epigenetic age acceleration associated with cigarette smoking among Costa Rican adults

Smoking-associated DNA methylation (DNAm) signatures are reproducible among studies of mostly European descent, with mixed evidence if smoking accelerates epigenetic aging and its relationship to longevity. We evaluated smoking-associated DNAm signatures in the Costa Rican Study on Longevity and Healthy Aging (CRELES), including participants from the high longevity region of Nicoya. We measured genome-wide DNAm in leukocytes, tested Epigenetic Age Acceleration (EAA) from five clocks and estimates of telomere length (DNAmTL), and examined effect modification by the high longevity region. 489 participants had a mean (SD) age of 79.4 (10.8) years, and 18% were from Nicoya. Overall, 7.6% reported currently smoking, 35% were former smokers, and 57.4% never smoked. 46 CpGs and five regions (e.g. AHRR, SCARNA6/SNORD39, SNORA20, and F2RL3) were differentially methylated for current smokers. Former smokers had increased Horvath’s EAA (1.69-years; 95% CI 0.72, 2.67), Hannum’s EAA (0.77-years; 95% CI 0.01, 1.52), GrimAge (2.34-years; 95% CI1.66, 3.02), extrinsic EAA (1.27-years; 95% CI 0.34, 2.21), intrinsic EAA (1.03-years; 95% CI 0.12, 1.94) and shorter DNAmTL (− 0.04-kb; 95% CI − 0.08, − 0.01) relative to non-smokers. There was no evidence of effect modification among residents of Nicoya. Our findings recapitulate previously reported and novel smoking-associated DNAm changes in a Latino cohort.

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.

Alcohol Use Intensity Decreases in Response to Successful Smoking Cessation Therapy

Smokers frequently drink heavily. However, the effectiveness of smoking cessation therapy for those with comorbid alcohol abuse is unclear, and the content of smoking cessation programs often does not address comorbid alcohol consumption. In order to achieve a better understanding of the relationship between changes in rate of smoking to the change in intensity of alcohol consumption, and the necessity for alcohol-specific programming for dual users, we quantified cigarette and alcohol consumption in 39 subjects undergoing a 3-month contingency management smoking cessation program using recently developed DNA methylation tools. Intake alcohol consumption, as quantified by the Alcohol T Score (ATS), was highly correlated with cg05575921 smoking intensity (adjusted R² = 0.49) with 19 of the 39 subjects having ATS scores indicative of Heavy Alcohol Consumption. After 90 days of smoking cessation therapy, ATS values decreased with the change in ATS score being highly correlated with change in cg05575921 smoking intensity (adjusted R² = 0.60), regardless of whether or not the subject managed to completely quit smoking. We conclude that alcohol consumption significantly decreases in response to successful smoking cessation. Further studies to determine whether targeted therapy focused on comorbid alcohol use increases the success of smoking cessation in those with dual use should be explored.

Stabilization of Salivary Biomarkers

The use of saliva as a diagnostic biofluid has been increasing in recent years, thanks to the identification and validation of new biomarkers and improvements in test accuracy, sensitivity, and precision that enable the development of new noninvasive and cost-effective devices. However, the lack of standardized methods for sample collection, treatment, and storage contribute to the overall variability and lack of reproducibility across analytical evaluations. Furthermore, the instability of salivary biomarkers after sample collection hinders their translation into commercially available technologies for noninvasive monitoring of saliva in home settings. The present review aims to highlight the status of research on the challenges of collecting and using diagnostic salivary samples, emphasizing the methodologies used to preserve relevant proteins, hormones, genomic, and transcriptomic biomarkers during sample handling and analysis.

Epigenetic modelling of former, current and never smokers

BACKGROUND

DNA methylation (DNAm) performs excellently in the discrimination of current and former smokers from never smokers, where AUCs > 0.9 are regularly reported using a single CpG site (cg05575921; AHRR). However, there is a paucity of DNAm models which attempt to distinguish current, former and never smokers as individual classes. Derivation of a robust DNAm model that accurately distinguishes between current, former and never smokers would be particularly valuable to epidemiological research (as a more accurate smoking definition vs. self-report) and could potentially translate to clinical settings. Therefore, we appraise 4 DNAm models of ternary smoking status (that is, current, former and never smokers): methylation at cg05575921 (AHRR model), weighted scores from 13 CpGs created by Maas et al. (Maas model), weighted scores from a LASSO model of candidate smoking CpGs from the literature (candidate CpG LASSO model), and weighted scores from a LASSO model supplied with genome-wide 450K data (agnostic LASSO model). Discrimination is assessed by AUC, whilst classification accuracy is assessed by accuracy and kappa, derived from confusion matrices.

RESULTS

We find that DNAm can classify ternary smoking status with reasonable accuracy, including when applied to external data. Ternary classification using only DNAm far exceeds the classification accuracy of simply assigning all classes as the most prevalent class (63.7% vs. 36.4%). Further, we develop a DNAm classifier which performs well in discriminating current from former smokers (agnostic LASSO model AUC in external validation data: 0.744). Finally, across our DNAm models, we show evidence of enrichment for biological pathways and human phenotype ontologies relevant to smoking, such as haemostasis, molybdenum cofactor synthesis, body fatness and social behaviours, providing evidence of the generalisability of our classifiers.

CONCLUSIONS

Our findings suggest that DNAm can classify ternary smoking status with close to 65% accuracy. Both the ternary smoking status classifiers and current versus former smoking status classifiers address the present lack of former smoker classification in epigenetic literature; essential if DNAm classifiers are to adequately relate to real-world populations. To improve performance further, additional focus on improving discrimination of current from former smokers is necessary.

Novel blood-based hypomethylation of SH3BP5 is associated with very early-stage lung adenocarcinoma

BACKGROUND

Early detection is essential to improve the survival of lung cancer (LC). The quantitative measurement of specific DNA methylation changes in the peripheral blood could provide an efficient strategy for the detection of early cancer.

OBJECTIVE

We applied a candidate approach and assess the association between blood-based SH3BP5 methylation and the risk of lung adenocarcinoma (LUAD) in a case-control cohort.

METHODS

The methylation level of four CpG sites in the promoter of SH3BP5 gene was quantitatively determined by mass spectrometry in 171 very early-stage LUAD patients (93.6% LUAD at stage I) and 190 age and gender-matched controls. The logistic regression and non-parametric tests were used for the statistical analyses.

RESULTS

We observed a significant association between decreased methylation of SH3BP5_CpG_4 in the peripheral blood and increased risk of LUAD (odds ratio (OR) per-10% methylation = 1.51, P = 0.006, FDR = 0.024), and even for the LUAD at stage I (OR per-10% methylation = 1.53, P = 0.006, FDR = 0.024). Moreover, the lower quartile of SH3BP5_CpG_4 methylation was correlated with increased risk for LUAD with a P trend of 0.011. Further investigation disclosed that the hypomethylation of SH3BP5_CpG_4 was mostly associated with LUAD in younger subjects (OR per-10% methylation = 2.02, P = 0.010, age < 55 years old) and probably could be enhanced by advance stage.

CONCLUSION

Our study revealed an association between blood-based SH3BP5 hypomethylation and very early-stage LUAD, which provides a novel support for the blood-based methylation signatures as a potential marker for the evaluation of cancer risk.

The relationship of smoking to cg05575921 methylation in blood and saliva DNA samples from several studies

Numerous studies have shown that cg05575921 methylation decreases in response to smoking. However, secondary to methodological issues, the magnitude and dose dependency of that response is as of yet unclear. This lack of certainty is a barrier to the use of DNA methylation clinically to assess and monitor smoking status. To better define this relationship, we conducted a joint analysis of methylation sensitive PCR digital (MSdPCR) assessments of cg05575921 methylation in whole blood and/or saliva DNA to smoking using samples from 421 smokers and 423 biochemically confirmed non-smokers from 4 previously published studies. We found that cg05575921 methylation manifested a curvilinear dose dependent decrease in response to increasing cigarette consumption. In whole blood DNA, the Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) of cg05575921 methylation for predicting daily smoking status was 0.98. In saliva DNA, the gross AUC was 0.91 with correction for cellular heterogeneity improving the AUC to 0.94. Methylation status was significantly associated with the Fagerstrom Test for Nicotine Dependence score, but with significant sampling heterogeneity. We conclude that MSdPCR assessments of cg05575921 methylation are a potentially powerful, clinically implementable tool for the assessment and management of smoking.

An investigation into DNA methylation patterns associated with risk preference in older individuals

Risk preference is a complex trait governed by psycho-social, environmental and genetic determinants. We aimed to examine how an individual’s risk preference associates with their epigenetic profile.

Risk preferences were ascertained by asking participants of the Northern Ireland COhort for the Longitudinal study of Ageing to make a series of choices between hypothetical income scenarios. From these, four risk preference categories were derived, ranging from risk-averse to risk-seeking. Illumina’s Infinium High-Density Methylation Assay was used to evaluate the status of 862,927 CpGs.

Risk preference and DNA methylation data were obtained for 1,656 individuals. The distribution of single-site DNA methylation levels between risk-averse and risk-seeking individuals was assessed whilst adjusting for age, sex and peripheral white cell counts. In this discovery cohort, 55 CpGs were identified with significantly different levels of methylation (p≤x10⁻⁵) between risk-averse and risk-seeking individuals when adjusting for the maximum number of covariates. No CpGs were significantly differentially methylated in any of the risk preference groups at an epigenome-wide association level (p<9x10⁻⁸) following covariate adjustment.

Protein-coding genes NWD1 and LRP1 were among the genes in which the top-ranked dmCpGs were located for all analyses conducted. Mutations in these genes have previously been linked to neurological conditions.

Epigenetic modifications have not previously been linked to risk-aversion using a population cohort, but may represent important biomarkers of accumulated, complex determinants of this trait. Several striking results from this study support further analysis of DNA methylation as an important link between measurable biomarkers and health behaviours.

Investigating the DNA methylation profile of e-cigarette use

BACKGROUND

Little evidence exists on the health effects of e-cigarette use. DNA methylation may serve as a biomarker for exposure and could be predictive of future health risk. We aimed to investigate the DNA methylation profile of e-cigarette use.

RESULTS

Among 117 smokers, 117 non-smokers and 116 non-smoking vapers, we evaluated associations between e-cigarette use and epigenome-wide methylation from saliva. DNA methylation at 7 cytosine-phosphate-guanine sites (CpGs) was associated with e-cigarette use at p < 1 × 10-5 and none at p < 5.91 × 10-8. 13 CpGs were associated with smoking at p < 1 × 10-5 and one at p < 5.91 × 10-8. CpGs associated with e-cigarette use were largely distinct from those associated with smoking. There was strong enrichment of known smoking-related CpGs in the smokers but not the vapers. We also tested associations between e-cigarette use and methylation scores known to predict smoking and biological ageing. Methylation scores for smoking and biological ageing were similar between vapers and non-smokers. Higher levels of all smoking scores and a biological ageing score (GrimAge) were observed in smokers. A methylation score for e-cigarette use showed poor prediction internally (AUC 0.55, 0.41-0.69) and externally (AUC 0.57, 0.36-0.74) compared with a smoking score (AUCs 0.80) and was less able to discriminate lung squamous cell carcinoma from adjacent normal tissue (AUC 0.64, 0.52-0.76 versus AUC 0.73, 0.61-0.85).

CONCLUSIONS

The DNA methylation profile for e-cigarette use is largely distinct from that of cigarette smoking, did not replicate in independent samples, and was unable to discriminate lung cancer from normal tissue. The extent to which methylation related to long-term e-cigarette use translates into chronic effects requires further investigation.

Epigenetic Analyses of Alcohol Consumption in Combustible and Non-Combustible Nicotine Product Users

Alcohol and tobacco use are highly comorbid and exacerbate the associated morbidity and mortality of either substance alone. However, the relationship of alcohol consumption to the various forms of nicotine-containing products is not well understood. To improve this understanding, we examined the relationship of alcohol consumption to nicotine product use using self-report, cotinine, and two epigenetic biomarkers specific for smoking (cg05575921) and drinking (Alcohol T Scores (ATS)) in n = 424 subjects. Cigarette users had significantly higher ATS values than the other groups (p < 2.2 × 10⁻¹⁶). Using the objective biomarkers, the intensity of nicotine and alcohol consumption was correlated in both the cigarette and smokeless users (R = −0.66, p = 3.1 × 10⁻¹⁴; R² = 0.61, p = 1.97 × 10⁻⁴). Building upon this idea, we used the objective nicotine biomarkers and age to build and test a Balanced Random Forest classification model for heavy alcohol consumption (ATS > 2.35). The model performed well with an AUC of 0.962, 89.3% sensitivity, and 85% specificity. We conclude that those who use non-combustible nicotine products drink significantly less than smokers, and cigarette and smokeless users drink more with heavier nicotine use. These findings further highlight the lack of informativeness of self-reported alcohol consumption and suggest given the public and private health burden of alcoholism, further research into whether using non-combustible nicotine products as a mode of treatment for dual users should be considered.

Hypomethylation of AHRR (cg05575921) Is Related to Smoking Status in the Mexican Mestizo Population

Tobacco smoking results in a multifactorial disease involving environmental and genetic factors; epigenome-wide association studies (EWAS) show changes in DNA methylation levels due to cigarette consumption, partially reversible upon tobacco smoking cessation. Therefore, methylation levels could predict smoking status. This study aimed to evaluate the DNA methylation level of cg05575921 (AHRR) and cg23771366 (PRSS23) and their correlation with lung function variables, cigarette consumption, and nicotine addiction in the Mexican smoking population. We included 114 non-smokers (NS) and 102 current tobacco smokers (TS); we then further subclassified them as heavy smokers (HS) (n = 53) and light smokers (LS) (n = 49). We used restriction enzymes (MspI/HpaII) and qPCR to determine the DNA methylation level. We observed significant hypomethylation of cg05575921 in smokers compared to NS (p = 0.003); further analysis found a difference between HS and NS (p = 0.02). We did not observe differences between other groups or a positive correlation between methylation levels and age, BMI, cigarette consumption, nicotine addiction, or lung function. In conclusion, the cg05575921 site of AHRR is significantly hypomethylated in Mexican smokers, especially in HS (≥20 cigarettes per day).

External validation of integrated genetic-epigenetic biomarkers for predicting incident coronary heart disease

Aim: The Framingham Risk Score (FRS) and atherosclerotic cardiovascular disease (ASCVD) Pooled Cohort Equation (PCE) for predicting risk for incident coronary heart disease (CHD) work poorly. To improve risk stratification for CHD, we developed a novel integrated genetic-epigenetic tool. Materials & methods: Using machine learning techniques and datasets from the Framingham Heart Study (FHS) and Intermountain Healthcare (IM), we developed and validated an integrated genetic-epigenetic model for predicting 3-year incident CHD. Results: Our approach was more sensitive than FRS and PCE and had high generalizability across cohorts. It performed with sensitivity/specificity of 79/75% in the FHS test set and 75/72% in the IM set. The sensitivity/specificity was 15/93% in FHS and 31/89% in IM for FRS, and sensitivity/specificity was 41/74% in FHS and 69/55% in IM for PCE. Conclusion: The use of our tool in a clinical setting could better identify patients at high risk for a heart attack.

DNA Methylation in Babies Born to Nonsmoking Mothers Exposed to Secondhand Smoke during Pregnancy: An Epigenome-Wide Association Study

BACKGROUND

Maternal smoking during pregnancy is related to altered DNA methylation in infant umbilical cord blood. The extent to which low levels of smoke exposure among nonsmoking pregnant women relates to offspring DNA methylation is unknown.

OBJECTIVE

This study sought to evaluate relationships between maternal prenatal plasma cotinine levels and DNA methylation in umbilical cord blood in newborns using the Infinium HumanMethylation 450K BeadChip.

METHODS

Participants from the Newborn Epigenetics Study cohort who reported not smoking during pregnancy had verified low levels of cotinine from maternal prenatal plasma (0 ng / mL to < 4  ng / mL ), and offspring epigenetic data from umbilical cord blood were included in this study (n = 79 ). Multivariable linear regression models were fit to the data, controlling for cell proportions, age, race, education, and parity. Estimates represent changes in response to any 1 -ng / mL unit increase in exposure.

RESULTS

Multivariable linear regression models yielded 29,049 CpGs that were differentially methylated in relation to increases in cotinine at a 5% false discovery rate. Top CpGs were within or near genes involved in neuronal functioning (PRKG1, DLGAP2, BSG), carcinogenesis (FHIT, HSPC157) and inflammation (AGER). Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses suggest cotinine was related to methylation of gene pathways controlling neuronal signaling, metabolic regulation, cell signaling and regulation, and cancer. Further, enhancers associated with transcription start sites were enriched in altered CpGs. Using an independent sample from the same study population (n = 115 ), bisulfite pyrosequencing was performed with infant cord blood DNA for two genes within our top 20 hits (AGER and PRKG1). Results from pyrosequencing replicated epigenome results for PRKG1 (cg17079497, estimate = - 1.09 , standard error  ( SE ) = 0.45 , p = 0.018 ) but not for AGER (cg09199225; estimate = - 0.16 , SE = 0.21 , p = 0.44 ).

DISCUSSION

Secondhand smoke exposure among nonsmoking women may alter DNA methylation in regions involved in development, carcinogenesis, and neuronal functioning. These novel findings suggest that even low levels of smoke exposure during pregnancy may be sufficient to alter DNA methylation in distinct sites of mixed umbilical cord blood leukocytes in pathways that are known to be altered in cord blood from pregnant active smokers. https://doi.org/10.1289/EHP8099.

Perspectives on Epigenetics Alterations Associated with Smoking and Vaping

Epigenetic alterations, including DNA methylation, microRNA, and long noncoding RNA, play important roles in the pathogenesis of numerous respiratory health conditions and diseases. Exposure to tobacco smoking has been found to be associated with epigenetic changes in the respiratory tract. Marketed as a less harmful alternative to combustible cigarettes, electronic cigarette (e-cigarette) has rapidly gained popularity in recent years, especially among youth and young adults. Accumulative evidence from both animal and human studies has shown that e-cigarette use (vaping) is also linked to similar respiratory health conditions as observed with cigarette smoking, including wheezing, asthma, and COPD. This review aims to provide an overview of current studies on associations of smoking and vaping with epigenetic alterations in respiratory cells and provide future research directions in epigenetic studies related to vaping.

The Reversion of DNA Methylation at Coronary Heart Disease Risk Loci in Response to Prevention Therapy

Coronary heart disease (CHD) is preventable, but the methods for assessing risk and monitoring response rely on imprecise lipid-based assessments. Recently, we have shown that an integrated genetic–epigenetic test that includes three methylation-sensitive digital PCR assays predicts 3-year risk for incident CHD better than lipid-based methods. However, whether methylation sites change in response to therapies that alter CHD risk is not known. Therefore, we assessed methylation at these three incident CHD-related sites in DNA from 39 subjects before and after three months of biochemically verified smoking cessation, then analyzed the relationship between change in methylation at each of the sites to the change in smoking intensity as assessed by cg05575921 methylation. We found that, in those who quit smoking, methylation change at one CHD risk marker (cg00300879) was significantly associated with change in cg05575921 methylation (p < 0.04). We conclude that changes in incident CHD-related methylation occur within three months of cessation of smoking, a major risk factor for CHD. This suggests that the effectiveness of treatment of other CHD risk factors, such as high cholesterol, may be similarly quantifiable using epigenetic approaches. Further studies to determine the relationship of changes of methylation status in response to treatment of other CHD risk factors are indicated.

Comparison of DNA methylation clocks in Black South African men

Aims: DNA methylation clocks are widely used to estimate biological age, although limited data are available on non-European ethnicities. This manuscript characterizes the behavior of five DNA methylation clocks in 120 older Black South African men. Methods: The age estimation accuracy of the Horvath, Hannum and skin and blood clocks and the relative age-related mortality risk and predicted time to death portrayed by the PhenoAge and GrimAge biomarkers are investigated, respectively. Results: The results confirm the tendency of DNA methylation clocks to underestimate the biological age of older individuals. GrimAge more accurately characterizes biological decline in this African cohort compared with PhenoAge owing to the unique inclusion of smoking-related damage in the GrimAge estimate. Conclusions: Each clock provides a different fraction of information regarding the aging body. It is essential to continue studying under-represented population groups to ensure methylation-derived indicators are robust and useful in all populations.

Cost-utility analysis of an integrated genetic/epigenetic test for assessing risk for coronary heart disease

Aim: New epigenetically based methods for assessing risk for coronary heart disease may be more sensitive but are generally more costly than current methods. To understand their potential impact on healthcare spending, we conducted a cost-utility analysis. Methods: We compared costs using the new Epi + Gen CHD™ test with those of existing tests using a cohort Markov simulation model. Results: We found that use of the new test was associated with both better survival and highly competitive negative incremental cost-effectiveness ratios ranging from -$42,000 to -$8000 per quality-adjusted life year for models with and without a secondary test. Conclusion: The new integrated genetic/epigenetic test will save money and lives under most real-world scenarios. Similar advantages may be seen for other epigenetic tests.

Cigarette smoke-induced alterations in blood: A review of research on DNA methylation and gene expression

Worldwide, smoking remains a threat to public health, causing preventable diseases and premature mortality. Cigarette smoke is a powerful inducer of DNA methylation and gene expression alterations, which have been associated with negative health consequences. Here, we review the current knowledge on smoking-related changes in DNA methylation and gene expression in human blood samples. We identified 30 studies focused on the association between active smoking, DNA methylation modifications, and gene expression alterations. Overall, we identified 1,758 genes with differentially methylated sites (DMS) and differentially expressed genes (DEG) between smokers and nonsmokers, of which 261 were detected in multiple studies (≥4). The most frequently (≥10 studies) reported genes were AHRR, GPR15, GFI1, and RARA. Functional enrichment analysis of the 261 genes identified the aryl hydrocarbon receptor repressor and T cell pathways (T helpers 1 and 2) as influenced by smoking status. These results highlight specific genes for future mechanistic and translational research that may be associated with cigarette smoke exposure and smoking-related diseases. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

DNA Methylation-Based Biomarkers of Environmental Exposures for Human Population Studies

PURPOSE OF REVIEW

This manuscript orients the reader to the underlying motivations of environmental biomarker development for human population studies and provides the foundation for applying these novel biomarkers in future research. In this review, we focus our attention on the DNA methylation-based biomarkers of (i) smoking, among adults and pregnant women, (ii) lifetime cannabis use, (iii) alcohol consumption, and (iv) cumulative exposure to lead.

RECENT FINDINGS

Prior environmental exposures and lifestyle modulate DNA methylation levels. Exposure-related DNA methylation changes can either be persistent or reversible once the exposure is no longer present, and this combination of both persistent and reversible changes has essential value for biomarker development. Here, we present available biomarkers representing past and cumulative exposures using individual DNA methylation profiles. In the present work, we describe how the field of environmental epigenetics can leverage machine learning algorithms to develop exposure biomarkers and reduce problems of misreporting exposures or limited access technology. We emphasize the crucial role of the individual DNA methylation profiles in those predictions, providing a summary of each biomarker, and highlighting their advantages, and limitations. Future research can cautiously leverage these DNA methylation-based biomarkers to understand the onset and progression of diseases.

The Reversion of cg05575921 Methylation in Smoking Cessation: A Potential Tool for Incentivizing Healthy Aging

Smoking is the largest preventable cause of mortality and the largest environmental driver of epigenetic aging. Contingency management-based strategies can be used to treat smoking but require objective methods of verifying quitting status. Prior studies have suggested that cg05575921 methylation reverts as a function of smoking cessation, but that it can be used to verify the success of smoking cessation has not been unequivocally demonstrated. To test whether methylation can be used to verify cessation, we determined monthly cg05575921 levels in a group of 67 self-reported smokers undergoing biochemically monitored contingency management-based smoking cessation therapy, as part of a lung imaging protocol. A total of 20 subjects in this protocol completed three months of cotinine verified smoking cessation. In these 20 quitters, the reversion of cg05575921 methylation was dependent on their initial smoking intensity, with methylation levels in the heaviest smokers reverting to an average of 0.12% per day over the 3-month treatment period. In addition, we found suggestive evidence that some individuals may have embellished their smoking history to gain entry to the study. Given the prominent effect of smoking on longevity, we conclude that DNA methylation may be a useful tool for guiding and incentivizing contingency management-based approaches for smoking cessation.

A simple, rapid, interpretable, actionable and implementable digital PCR based mortality index

Mortality assessments are conducted for both civil and commercial purposes. Recent advances in epigenetics have resulted in DNA methylation tools to assess risk and aid in this task. However, widely available array-based algorithms are not readily translatable into clinical tools and do not provide a good foundation for clinical recommendations. Further, recent work shows evidence of heritability and possible racial bias in these indices. Using a publicly available array data set, the Framingham Heart Study (FHS), we develop and test a five-locus mortality-risk algorithm using only previously validated methylation biomarkers that have been shown to be free of racial bias, and that provide specific assessments of smoking, alcohol consumption, diabetes and heart disease. We show that a model using age, sex and methylation measurements at these five loci outperforms the 513 probe Levine index and approximates the predictive power of the 1030 probe GrimAge index. We then show each of the five loci in our algorithm can be assessed using a more powerful, reference-free digital PCR approach, further demonstrating that it is readily clinically translatable. Finally, we show the loci do not reflect ethnically specific variation. We conclude that this algorithm is a simple, yet powerful tool for assessing mortality risk. We further suggest that the output from this or similarly derived algorithms using either array or digital PCR can be used to provide powerful feedback to patients, guide recommendations for additional medical assessments, and help monitor the effect of public health prevention interventions.

A Comparison of the Predictive Power of DNA Methylation with Carbohydrate Deficient Transferrin for Heavy Alcohol Consumption

Currently, the most commonly used biomarker of alcohol consumption patterns is carbohydrate-deficient transferrin (CDT). However, the CDT has limited sensitivity and requires the use of blood. Recently, we have shown that digital DNA methylation techniques can both sensitively and specifically detect heavy alcohol consumption (HAC) using DNA from blood or saliva. In order to better understand the relative performance characteristics of these two tests, we compared an Alcohol T-Score (ATS) derived from our prior study and serum CDT levels in 313 (182 controls and 131 HAC cases) subjects discordant for HAC. Overall, the Receiver Operating Characteristic (ROC) area under the curve (AUC) analyses showed that DNA methylation predicted HAC status better than CDT with AUCs of 0.96 and 0.87, respectively (p < 0.0001). The performance of the CDT was affected by gender while the ATS was not, while both were affected by age. We conclude that DNA methylation is a promising method for quantifying HAC and that further studies to better refine its strengths and limitations are in order.

AHRR cg05575921 methylation in relation to smoking and PM2.5 exposure among Taiwanese men and women

Background

Polycyclic aromatic hydrocarbon (PAH)-rich substances like cigarette smoke and PM_2.5 induce aryl hydrocarbon receptor (AHR)-mediated aryl hydrocarbon receptor repressor (AHRR) methylation. AHRR cg05575921 and coagulation factor II (thrombin) receptor-like 3 (F2RL3) cg03636183 methylation patterns are well-established biomarkers for smoking. Even though AHRR cg05575921 methylation has recently been associated with PM_2.5, the interaction between smoking and PM_2.5 on AHRR methylation is yet to be fully explored. We evaluated AHRR and F2RL3 CpG sites to identify potential significant markers in relation to PM_2.5 and smoking in Taiwanese adults.

Methods

DNA methylation and smoking data of 948 participants aged 30–70 years were obtained from the Taiwan Biobank Database (2008–2015), while PM_2.5 data were obtained from the Air Quality Monitoring Database (2006–2011).

Results

Smoking and PM_2.5 were independently associated with hypomethylation (lower levels) of AHRR cg05575921, AHRR cg23576855, F2RL3 cg03636183, and F2LR3 cg21911711 after multiple-comparison correction (Bonferroni P < 0.00028409). Cg05575921 was the most hypomethylated AHRR CpG site, while cg03636183 was the most hypomethylated F2RL3 CpG site. Overall, cg05575921 was the most hypomethylated CpG site: β = − 0.03909, P < 0.0001; − 0.17536, P < 0.0001 for former and current smoking, respectively (P-trend_smoking < 0.0001) and − 0.00141, P < 0.0001 for PM_2.5. After adjusting for F2RL3 cg03636183, smoking and PM_2.5 remained significantly associated with cg05575921 hypomethylation: β − 0.02221, P < 0.0001; − 0.11578, P < 0.0001 for former and current smoking, respectively (P-trend_smoking < 0.0001) and − 0.0070, P = 0.0120 for PM_2.5. After stratification by sex, smoking and PM_2.5 remained associated (P < 0.05) with cg05575921 hypomethylation in both men (β = − 0.04274, − 0.17700, and − 0.00163 for former smoking, current smoking, and PM_2.5, respectively) and women (β = − 0.01937, − 0.17255, and − 0.00105 for former smoking, current smoking, and PM_2.5, respectively). After stratification by residential area, former and current smoking remained associated (P < 0.05) with cg05575921 hypomethylation: β = − 0.03918 and − 0.17536, respectively (P-trend_smoking < 0.0001). Living in the central and southern areas was also associated (P < 0.05) with cg05575921 hypomethylation: β = − 0.01356 and − 0.01970, respectively (P-trend_area < 0.0001).

Conclusion

Smoking and PM_2.5 were independently associated with hypomethylation of cg05575921, cg23576855, cg03636183, and cg21911711. The most hypomethylated CpG site was cg05575921 and its association with smoking and PM_2.5 was dose-dependent.

Refinement of cg05575921 demethylation response in nascent smoking

The initiation of adolescent smoking is difficult to detect using carbon monoxide or cotinine assays. Previously, we and others have shown that the methylation of cg05575921 is an accurate predictor of adult smoking status. But the dose and time dependency of the demethylation response to smoking initiation in adolescents is not yet well understood. To this end, we conducted three consecutive annual in-person interviews and biological samplings of 448 high school students (wave 1 (W1)-wave 3 (W3)). At W1 (n = 448), 62 subjects reported using tobacco and 72 subjects reported using cannabis at least once in their life-time with 38 and 20 subjects having a positive cotinine and cannabinoid levels, respectively, at W1 intake. At W3 (n = 383), 67 subjects reported using tobacco and 60 subjects reported using cannabis at least once with 75 and 60 subjects having positive cotinine and cannabinoid levels, respectively, at W3. Subjects with undetectable cotinine levels at all three-time waves had stable levels of cg05575921 methylation throughout the study (88.7% at W1 and 88.8% at W3, n = 149), while subjects with positive cotinine levels at all 3 time points manifested a steady decrease in cg05575921 methylation (81.8% at W1 and 71.3% at the W3, n = 12). In those subjects with an affirmative smoking self-report at W3 (n = 17), the amount of demethylation at cg05575921 was correlated with time and intensity of smoking. We conclude that cg05575921 methylation is a sensitive, dose-dependent indicator of early stages of smoking, and may help to identify smokers in the early stages of smoking.

Array-Based Epigenetic Aging Indices May Be Racially Biased

Epigenetic aging (EA) indices are frequently used as predictors of mortality and other important health outcomes. However, each of the commonly used array-based indices has significant heritable components which could tag ethnicity and potentially confound comparisons across racial and ethnic groups. To determine if this was possible, we examined the relationship of DNA methylation in cord blood from 203 newborns (112 African American (AA) and 91 White) at the 513 probes from the Levine PhenoAge Epigenetic Aging index to ethnicity. Then, we examined all sites significantly associated with race in the newborn sample to determine if they were also associated with an index of ethnic genetic heritage in a cohort of 505 AA adults. After Bonferroni correction, methylation at 50 CpG sites was significantly associated with ethnicity in the newborn cohort. The five most significant sites predicted ancestry with a receiver operator characteristic area under the curve of 0.97. Examination of the top 50 sites in the AA adult cohort showed that methylation status at 11 of those sites was also associated with percentage European ancestry. We conclude that the Levine PhenoAge Index is influenced by cryptic ethnic-specific genetic influences. This influence may extend to similarly constructed EA indices and bias cross-race comparisons.

Epigenetic Biomarkers for Environmental Exposures and Personalized Breast Cancer Prevention

Environmental and lifestyle factors are believed to account for >80% of breast cancers; however, it is not well understood how and when these factors affect risk and which exposed individuals will actually develop the disease. While alcohol consumption, obesity, and hormone therapy are some known risk factors for breast cancer, other exposures associated with breast cancer risk have not yet been identified or well characterized. In this paper, it is proposed that the identification of blood epigenetic markers for personal, in utero, and ancestral environmental exposures can help researchers better understand known and potential relationships between exposures and breast cancer risk and may enable personalized prevention strategies.