Refinement of cg05575921 demethylation response in nascent smoking

Epigenetic effects of cannabis: A systematic scoping review of behavioral and emotional symptoms associated with cannabis use and exocannabinoid exposure

BACKGROUND

Recent research suggests that epigenetic modifications may mediate the behavioral effects of cannabis, influencing exocannabinnoids' long term effects in cognitive function and its role in the emergence of psychotic symptoms.

BASIC PROCEDURES

In this systematic scoping review, we assessed the current evidence of epigenetic effects associated with the use of cannabis or exocannabinoid administration and their relationship with behavioral and emotional symptoms. We searched PubMed, Cochrane CENTRAL, and Web of Science, up to January 2022, using the terms "cannabis" and "epigenetics." The search yielded 178 articles, of which 43 underwent full article revision; 37 articles were included in the review.

MAIN FINDINGS

The gathered evidence included observational cross-sectional studies conducted on human subjects and experimental designs using animal models that conveyed disparity in administration dosage, methods of cannabis use assessment and targeted epigenetic mechanisms. Nine studies performed epigenome-wide analysis with identification of differentially methylated sites; most of these studies found a global hypomethylation, and enrichment in genes related to cellular survival and neurodevelopment. Other studies assessed methylation at specific genes and found that cannabis exposure was associated with reduced methylation at Cg05575921, DNMT1, DRD2, COMT, DLGAP2, Arg1, STAT3, MGMT, and PENK, while hypermethylation was found at DNMT3a/b, NCAM1, and AKT1.

CONCLUSIONS

The review found evidence of an exocannabinoid-induced epigenetic changes that modulate depressive-anxious, psychotic, and addictive behavioural phenotypes. Further studies will require dosage exposure/administration uniformization and a customized pool of genes to assess their suitability as biomarkers for psychiatric diseases.

Non-cigarette tobacco products, aryl-hydrocarbon receptor repressor gene methylation and smoking-related health outcomes

INTRODUCTION

Cigarette smoking leads to altered DNA methylation at the aryl-hydrocarbon receptor repressor (AHRR) gene. However, it remains unknown whether pipe or cigar smoking is associated with AHRR methylation. We evaluated associations of non-cigarette tobacco use with AHRR methylation and determined if AHRR methylation was associated with smoking-related health outcomes.

METHODS

Data were pooled across four population-based cohorts that enrolled participants from 1985 to 2002. Tobacco exposures were evaluated using smoking questionnaires. AHRR cg05575921 methylation was measured in peripheral blood leucocyte DNA. Spirometry and respiratory symptoms were evaluated at the time of methylation measurements and in subsequent visits. Vital status was monitored using the National Death Index.

RESULTS

Among 8252 adults (mean age 56.7±10.3 years, 58.1% women, 40.6% black), 4857 (58.9%) participants used cigarettes and 634 (7.7%) used non-cigarette tobacco products. Exclusive use of non-cigarette tobacco products was independently associated with lower AHRR methylation (-2.44 units, 95% CI -4.42 to -0.45), though to a lesser extent than exclusive use of cigarettes (-6.01 units, 95% CI -6.01 to -4.10). Among participants who exclusively used non-cigarette tobacco products, reduced AHRR methylation was associated with increased respiratory symptom burden (OR 1.60, 95% CI 1.03 to 2.68) and higher all-cause mortality (log-rank p=0.02).

CONCLUSION

Pipe and cigar smoking were independently associated with lower AHRR methylation in a multiethnic cohort of US adults. Among users of non-cigarette tobacco products, lower AHRR methylation was associated with poor respiratory health outcomes and increased mortality. AHRR methylation may identify non-cigarette tobacco users with an increased risk of adverse smoking-related health outcomes.

Epigenetic signals associated with delirium replicated across four independent cohorts

Delirium is risky and indicates poor outcomes for patients. Therefore, it is crucial to create an effective delirium detection method. However, the epigenetic pathophysiology of delirium remains largely unknown. We aimed to discover reliable and replicable epigenetic (DNA methylation: DNAm) markers that are associated with delirium including post-operative delirium (POD) in blood obtained from patients among four independent cohorts. Blood DNA from four independent cohorts (two inpatient cohorts and two surgery cohorts; 16 to 88 patients each) were analyzed using the Illumina EPIC array platform for genome-wide DNAm analysis. We examined DNAm differences in blood between patients with and without delirium including POD. When we compared top CpG sites previously identified from the initial inpatient cohort with three additional cohorts (one inpatient and two surgery cohorts), 11 of the top 13 CpG sites showed statistically significant differences in DNAm values between the delirium group and non-delirium group in the same directions as found in the initial cohort. This study demonstrated the potential value of epigenetic biomarkers as future diagnostic tools. Furthermore, our findings provide additional evidence of the potential role of epigenetics in the pathophysiology of delirium including POD.

Epigenetic biomarkers for smoking cessation

Cigarette smoking has been associated with epigenetic alterations that may be reversible upon cessation. As the most-studied epigenetic modification, DNA methylation is strongly associated with smoking exposure, providing a potential mechanism that links smoking to adverse health outcomes. Here, we reviewed the reversibility of DNA methylation in accessible peripheral tissues, mainly blood, in relation to cigarette smoking cessation and the utility of DNA methylation as a biomarker signature to differentiate current, former, and never smokers and to quantify time since cessation. We summarized thousands of differentially methylated Cytosine-Guanine (CpG) dinucleotides and regions associated with smoking cessation from candidate gene and epigenome-wide association studies, as well as the prediction accuracy of the multi-CpG predictors for smoking status. Overall, there is robust evidence for DNA methylation signature of cigarette smoking cessation. However, there are still gaps to fill, including (1) cell-type heterogeneity in measuring blood DNA methylation; (2) underrepresentation of non-European ancestry populations; (3) limited longitudinal data to quantitatively measure DNA methylation after smoking cessation over time; and (4) limited data to study the impact of smoking cessation on other epigenetic features, noncoding RNAs, and histone modifications. Epigenetic machinery provides promising biomarkers that can improve success in smoking cessation in the clinical setting. To achieve this goal, larger and more-diverse samples with longitudinal measures of a broader spectrum of epigenetic marks will be essential to developing a robust DNA methylation biomarker assay, followed by meeting validation requirements for the assay before being implemented as a clinically useful tool.

Predictors of Smoking in Older Adults and an Epigenetic Validation of Self-Report

There are several established predictors of smoking, but it is unknown if these predictors operate similarly for young and old smokers. We examined clinical data from the National Lung Screening Trial (NLST) to determine the predictive ability of gender, body mass index (BMI), marital status, and race on smoking behavior, with emphasis on gender interactions. In addition, we validated the self-report of smoking behaviors for a subgroup that had available epigenetic data in the form of cg05575921 methylation. Participants were N=9572 current or former smokers from the NLST biofluids database, age 55-74, minimum of 30 pack years, and mostly White. A subgroup of N=3084 who had DNA were used for the self-report validation analysis. The predictor analysis was based on the larger group and used penalized logistic regression to predict the self-report of being a former or current smoker at baseline. Cg05575921 methylation showed a moderate ability to discriminate among former and current smokers, AUC = 0.85 (95% confidence interval = [0.83, 0.86]). The final selected variables for the prediction model were BMI, gender, BMI by gender, age, divorced (vs. married), education, and race. The gender by BMI interaction was such that males had a higher probability of current smoking for lower BMI, but this switched to females having higher current smoking for overweight to obese. There is evidence that the self-reported smoking behavior in NLST is moderately accurate. The results of the primary analysis are consistent with the general smoking literature, and our results provide additional specificity regarding the gender by BMI interaction. Body weight issues might play a role in smoking cessation for older established smokers in a similar manner as younger smokers. It could be that women have less success with cessation when their BMI increases.

Using Cg05575921 methylation to predict lung cancer risk: a potentially bias-free precision epigenetics approach

The decision to engage in lung cancer screening (LCS) necessitates weighing benefits versus harms. Previously, clinicians in the United States have used the PLCOM2012 algorithm to guide LCS decision-making. However, that formula contains race and gender-based variables. Previously, using data from a European study, Bojesen and colleagues have suggested that cg05575921 methylation could guide decision-making. To test this hypothesis in a more diverse American population, we examined DNA and clinical data from 3081 subjects from the National Lung Screening Trial (NLST) study. Using survival analysis, we found a simple linear predictor consisting of age, pack-year consumption and cg05575921, to have the best predictive power among several alternatives (AUC = 0.66). Results showed that the highest quartile of risk was more than 2-fold more likely to develop lung cancer than those in the lowest quartile. Race, ethnicity, and gender had no effect on prediction with both cg05575921 and pack years contributing equally (both p < 0.003) to risk prediction. Current smokers had considerably lower methylation than former smokers (46% vs 67%; p < 0.001) with the average methylation of those who quit approaching 80% after 25 years of cessation. Finally, current male smokers had lower mean cg05575921 percentage than female smokers (46% vs 49%; p < 0.001). We conclude that cg05575921 (along with age and pack years) can be used to guide LCS decision-making, and additional studies might focus on how best to use methylation to inform decision-making.

Blood DNA methylation signatures of lifestyle exposures: tobacco and alcohol consumption

BACKGROUND

Smoking and alcohol consumption may compromise health by way of epigenetic modifications. Epigenetic signatures of alcohol and tobacco consumption could provide insights into the reversibility of phenotypic changes incurred with differing levels of lifestyle exposures. This study describes and validates two novel epigenetic signatures of tobacco (EpiTob) and alcohol (EpiAlc) consumption and investigates their association with disease outcomes.

METHODS

The epigenetic signatures, EpiTob and EpiAlc, were developed using data from the Swiss Kidney Project on Genes in Hypertension (SKIPOGH) (N = 689). Epigenetic and phenotypic data available from the 1921 (N = 550) and 1936 (N = 1091) Lothian Birth Cohort (LBC) studies, and two publicly available datasets on GEO Accession (GSE50660, N = 464; and GSE110043, N = 94) were used to validate the signatures. A multivariable logistic regression model, adjusting for age and sex, was used to assess the association between self-reported tobacco or alcohol consumption and the respective epigenetic signature, as well as to estimate the association between CVD and epigenetic signatures. A Cox proportional hazard model was used to estimate the risk of mortality in association with the EpiTob and EpiAlc signatures.

RESULTS

The EpiTob signature was positively associated with self-reported tobacco consumption for current or never smokers with explained variance ranging from 0.49 (LBC1921) to 0.72 (LBC1936) (pseudo-R2). In the SKIPOGH, LBC1921 and LBC1936 cohorts, the epigenetic signature for alcohol consumption explained limited variance in association with self-reported alcohol status [i.e., non-drinker, moderate drinker, and heavy drinker] (pseudo-R2 = 0.05, 0.03 and 0.03, respectively), although this improved considerably when measuring self-reported alcohol consumption with standardized units consumed per week (SKIPOGH R2 = 0.21; LBC1921 R2 = 0.31; LBC1936 R2 = 0.41). Both signatures were associated with history of CVD in SKIPOGH and LBC1936, but not in LBC1921. The EpiTob signature was associated with increased risk of all-cause and lung-cancer specific mortality in the 1936 and 1921 LBC cohorts.

CONCLUSIONS

This study found the EpiTob and EpiAlc signatures to be well-correlated with self-reported exposure status and associated with long-term health outcomes. Epigenetic signatures of lifestyle exposures may reduce measurement issues and biases and could aid in risk stratification for informing early-stage targeted interventions.

AhRR methylation contributes to disease progression in urothelial bladder cancer

BACKGROUND

Bladder Cancer (BCa) is the tenth most incidental malignancy worldwide. BCa is mostly attributed to environmental exposure and lifestyle, particularly tobacco smoking. The Aryl Hydrocarbon Receptor Repressor (AhRR) participates in the induction of many enzymes involved in metabolizing carcinogens, including tobacco smoke components. Additionally, studies have shown that smoking demethylates the (AhRR) gene in blood, suggesting AhRR demethylation as a specific serum smoking biomarker.

OBJECTIVE

This study aimed to validate AhRR demethylation as a smoking biomarker in the target tissue and investigate its contribution to bladder carcinogenesis.

METHODS

AhRR percent methylation was tested for its association with patient smoking status and oncogenic outcome indicators, particularly p53, RB1, and FGFR3 activating mutations, muscle-invasiveness, and tumor grade, in 180 BCa tissue-based DNA.

RESULTS

Results showed significantly higher AhRR percent methylation in muscle-invasive compared to non-muscle invasive tumors (42.86% vs. 33.98%; p= 0.011), while lower AhRR methylation was significantly associated with FGFR3 Codon 248 mutant genotype compared to wild-type (28.11% ± 9.44 vs. 37.87% ± 22.53; p= 0.036). All other tested associations were non-statistically significant.

CONCLUSIONS

Although AhRR methylation did not predict smoking status in BCa tumors, it seems to play a role in carcinogenesis and disease progression. Our findings make a basis for further research.

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.

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.

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.

An Examination of Risk Factors for Tobacco and Cannabis Smoke Exposure in Adolescents Using an Epigenetic Biomarker

Objective: Evolving patterns of nicotine and cannabis use by adolescents require new tools to understand the changing epidemiology of these substances. Here we describe the use of a novel epigenetic biomarker sensitive to both tobacco and cannabis smoke in a longitudinal sample of high-risk adolescents. We examine risk factors for positivity for this epigenetic biomarker in comparison to positivity for conventional serum biomarkers of nicotine and cannabis use. Method: Eastern Iowa 10th graders who had a friend or family member who smoked were eligible to participate in a longitudinal study over 10-12th grades. Subjects provided self-report data on nicotine, tobacco, and cannabis use patterns as well as blood samples that were used for serum cotinine and THC assays. DNA was prepared for analysis of methylation at the CpG cg05575921, a sensitive indicator of smoke exposure. Relationships between positivity for each these biomarkers and a variety of risk factors, including demographics, family and peer relationships, psychopathology, willingness to smoke, and perceptions of typical cigarette and cannabis users, were examined at the 10th (n = 442), 11th (n = 376), and 12th (n = 366) grade timepoints. Results: A increasing proportion of subjects were positive for cotinine (5-16%), THC (3-10%), and cg05575921 methylation (5-7%) across timepoints, with some overlap. Self-reported combusted tobacco and cannabis use was strongly correlated with all biomarkers, whereas cg05575921 methylation was not correlated with reported e-cigarette use. Dual users, defined as those positive for nicotine and THC in the 12th grade showed the greatest cumulative smoke exposure, indicated by cg05575921 methylation. Subjects reported more positive attitudes toward cannabis users than cigarette smokers, and willingness to smoke and positive perceptions of tobacco and cannabis smokers were significant risk factors for biomarker positivity across timepoints. Conclusion: We conclude that measurement of cg05575921 methylation in adolescents is a useful tool in detecting tobacco smoking in adolescents, and may be a novel tool for the detection of cannabis smoking and cannabis and tobacco co-use, though non-combusted forms of nicotine use do not appear to be detectable by this method.

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).

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.