Tobacco smoking leads to extensive genome-wide changes in DNA methylation

Novel DNA methylation changes in mouse lungs associated with chronic smoking

Smoking is a potent cause of asthma exacerbations, chronic obstructive pulmonary disease (COPD) and many other health defects, and changes in DNA methylation (DNAm) have been identified as a potential link between smoking and these health outcomes. However, most studies of smoking and DNAm have been done using blood and other easily accessible tissues in humans, while evidence from more directly affected tissues such as the lungs is lacking. Here, we identified DNAm patterns in the lungs that are altered by smoking. We used an established mouse model to measure the effects of chronic smoke exposure first on lung phenotype immediately after smoking and then after a period of smoking cessation. Next, we determined whether our mouse model recapitulates previous DNAm patterns observed in smoking humans, specifically measuring DNAm at a candidate gene responsive to cigarette smoke, Cyp1a1. Finally, we carried out epigenome-wide DNAm analyses using the newly released Illumina mouse methylation microarrays. Our results recapitulate some of the phenotypes and DNAm patterns observed in human studies but reveal 32 differentially methylated genes specific to the lungs which have not been previously associated with smoking. The affected genes are associated with nicotine dependency, tumorigenesis and metastasis, immune cell dysfunction, lung function decline, and COPD. This research emphasizes the need to study CS-mediated DNAm signatures in directly affected tissues like the lungs, to fully understand mechanisms underlying CS-mediated health outcomes.

Methylation marks in blood DNA reveal breast cancer risk in patients fulfilling hereditary disease criteria

Less than 15-20% of patients who meet the criteria for hereditary breast and ovarian cancer (HBOC) carry pathogenic coding genetic mutations, implying that other molecular mechanisms may contribute to the increased risk of this condition. DNA methylation in peripheral blood has been suggested as a potential epigenetic marker for the risk of breast cancer (BC). We aimed to discover methylation marks in peripheral blood associated with BC in 231 pre-treatment BC patients meeting HBOC criteria, testing negative for coding pathogenic variants, and 156 healthy controls, through methylation analysis by targeted bisulfite sequencing on 18 tumor suppressor gene promoters (330 CpG sites). We found i) hypermethylation in EPCAM (17 CpG sites; p = 0.017) and RAD51C (27 CpG sites; p = 0.048); ii) hypermethylation in 36 CpG-specific sites (FDR q < 0.05) in the BC patients; iii) four specific CpG sites were associated with a higher risk of BC (FDR q < 0.01, Bonferroni p < 0.001): cg89786999-FANCI (OR = 1.65; 95% CI:1.2-2.2), cg23652916-PALB2 (OR = 2.83; 95% CI:1.7-4.7), cg47630224-MSH2 (OR = 4.17; 95% CI:2.1-8.5), and cg47596828-EPCAM (OR = 1.84; 95% CI:1.5-2.3). Validation of cg47630224-MSH2 methylation in one Australian cohort showed an association with 3-fold increased BC risk (AUC: 0.929; 95% CI: 0.904-0.955). Our findings suggest that four DNA methylation CpG sites may be associated with a higher risk of BC, potentially serving as biomarkers in patients without detectable coding mutations.

Artificial intelligence-based epigenomic, transcriptomic and histologic signatures of tobacco use in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) biomarker studies rarely employ multi-omic biomarker strategies and pertinent clinicopathologic characteristics to predict mortality. In this study we determine for the first time a combined epigenetic, gene expression, and histology signature that differentiates between patients with different tobacco use history (heavy tobacco use with ≥10 pack years vs. no tobacco use). Using The Cancer Genome Atlas (TCGA) cohort (n = 257) and an internal cohort (n = 40), we identify 3 epigenetic markers (GPR15, GNG12, GDNF) and 13 expression markers (IGHA2, SCG5, RPL3L, NTRK1, CD96, BMP6, TFPI2, EFEMP2, RYR3, DMTN, GPD2, BAALC, and FMO3), which are dysregulated in OSCC patients who were never smokers vs. those who have a ≥ 10 pack year history. While mortality risk prediction based on smoking status and clinicopathologic covariates alone is inaccurate (c-statistic = 0.57), the combined epigenetic/expression and histologic signature has a c-statistic = 0.9409 in predicting 5-year mortality in OSCC patients.

Fast matrix completion in epigenetic methylation studies with informative covariates

DNA methylation is an important epigenetic mark that modulates gene expression through the inhibition of transcriptional proteins binding to DNA. As in many other omics experiments, the issue of missing values is an important one, and appropriate imputation techniques are important in avoiding an unnecessary sample size reduction as well as to optimally leverage the information collected. We consider the case where relatively few samples are processed via an expensive high-density whole genome bisulfite sequencing (WGBS) strategy and a larger number of samples is processed using more affordable low-density, array-based technologies. In such cases, one can impute the low-coverage (array-based) methylation data using the high-density information provided by the WGBS samples. In this paper, we propose an efficient Linear Model of Coregionalisation with informative Covariates (LMCC) to predict missing values based on observed values and covariates. Our model assumes that at each site, the methylation vector of all samples is linked to the set of fixed factors (covariates) and a set of latent factors. Furthermore, we exploit the functional nature of the data and the spatial correlation across sites by assuming some Gaussian processes on the fixed and latent coefficient vectors, respectively. Our simulations show that the use of covariates can significantly improve the accuracy of imputed values, especially in cases where missing data contain some relevant information about the explanatory variable. We also showed that our proposed model is particularly efficient when the number of columns is much greater than the number of rows-which is usually the case in methylation data analysis. Finally, we apply and compare our proposed method with alternative approaches on two real methylation datasets, showing how covariates such as cell type, tissue type or age can enhance the accuracy of imputed values.

Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis

Tobacco use is a major modifiable risk factor for adverse health outcomes, including cancer, and elicits profound epigenetic changes thought to be associated with long-term cancer risk. While electronic cigarettes (e-cigarettes) have been advocated as harm reduction alternatives to tobacco products, recent studies have revealed potential detrimental effects, highlighting the urgent need for further research into the molecular and health impacts of e-cigarettes. Here, we applied computational deconvolution methods to dissect the cell- and tissue-specific epigenetic effects of tobacco or e-cigarette use on DNA methylation (DNAme) in over 3,500 buccal/saliva, cervical, or blood samples, spanning epithelial and immune cells at directly and indirectly exposed sites. The 535 identified smoking-related DNAme loci [cytosine-phosphate-guanine sites (CpG)] clustered into four functional groups, including detoxification or growth signaling, based on cell type and anatomic site. Loci hypermethylated in buccal epithelial cells of smokers associated with NOTCH1/RUNX3/growth factor receptor signaling also exhibited elevated methylation in cancer tissue and progressing lung carcinoma in situ lesions, and hypermethylation of these sites predicted lung cancer development in buccal samples collected from smokers up to 22 years prior to diagnosis, suggesting a potential role in driving carcinogenesis. Alarmingly, these CpGs were also hypermethylated in e-cigarette users with a limited smoking history. This study sheds light on the cell type-specific changes to the epigenetic landscape induced by smoking-related products.

SIGNIFICANCE

The use of both cigarettes and e-cigarettes elicits cell- and exposure-specific epigenetic effects that are predictive of carcinogenesis, suggesting caution when broadly recommending e-cigarettes as aids for smoking cessation.

Eight Weeks of Physical Training Decreases 2 Years of DNA Methylation Age of Sedentary Women

Purpose: The acceleration of epigenetic age is a predictor of mortality and contributes to the increase in chronic diseases. Adherence to a healthy lifestyle is a strategy to reduce epigenetic age. The present study aimed to determine whether eight weeks of combined (aerobic and strength) training (CT) can influence the epigenetic age of women between 50 and 70 years old and the differences in sites and methylated regions. Methods: Eighteen women (AARLow: lower age acceleration residual, n = 10; AARHigh: higher age acceleration residual, n = 8) participated in a combined exercise training program (60 minutes, 3× a week) for eight weeks. DNA was extracted from whole blood using the salting out technique. DNA methylation was performed using the array technique (Illumina's Infinium Methylation BeadChip 850k). We used the DNA Methylation Age Calculator platform to calculate the biological epigenetic age. Two-way ANOVA followed by FISHER LSD posthoc was Applied, adopting p < .05. Results: After eight weeks of CT, there were no changes to the epigenetic age acceleration for the AARLow group (PRE: -2.3 ± 3.2 to POST: -2.3 ± 3.6). However, the AARHigh group significantly decreased the age acceleration (PRE: 3.6 ± 2.6 to POST: 2.2 ± 2.7) (group effect, p = .01; time effect, p = .31; group vs. time effect, p = .005). Conclusion: CT for eight weeks benefits the epigenetic clock of women with the most accelerated age.

Methylome-wide studies of six metabolic traits

Exploring the molecular correlates of metabolic health measures may identify the shared and unique biological processes and pathways that they track. Here, we performed epigenome-wide association studies (EWASs) of six metabolic traits: body mass index (BMI), body fat percentage, waist-hip ratio (WHR), and blood-based measures of glucose, high-density lipoprotein (HDL) cholesterol, and total cholesterol. We considered blood-based DNA methylation (DNAm) from >750,000 CpG sites in over 17,000 volunteers from the Generation Scotland (GS) cohort. Linear regression analyses identified between 304 and 11,815 significant CpGs per trait at P<3.6×10-8, with 37 significant CpG sites across all six traits. Further, we performed a Bayesian EWAS that jointly models all CpGs simultaneously and conditionally on each other, as opposed to the marginal linear regression analyses. This identified between 3 and 27 CpGs with a posterior inclusion probability ≥ 0.95 across the six traits. Next, we used elastic net penalised regression to train epigenetic scores (EpiScores) of each trait in GS, which were then tested in the Lothian Birth Cohort 1936 (LBC1936; European ancestry) and Health for Life in Singapore (HELIOS; Indian-, Malay- and Chinese-ancestries). A maximum of 27.1% of the variance in BMI was explained by the BMI EpiScore in the subset of Malay-ancestry Singaporeans. Four metabolic EpiScores were associated with general cognitive function in LBC1936 in models adjusted for vascular risk factors (Standardised βrange: 0.08 - 0.12, PFDR < 0.05). EpiScores of metabolic health are applicable across ancestries and can reflect differences in brain health.

Epigenetics of the non-coding RNA nc886 across blood, adipose tissue and skeletal muscle in offspring exposed to diabetes in pregnancy

BACKGROUND

Diabetes in pregnancy is associated with increased risk of long-term metabolic disease in the offspring, potentially mediated by in utero epigenetic variation. Previously, we identified multiple differentially methylated single CpG sites in offspring of women with gestational diabetes mellitus (GDM), but whether stretches of differentially methylated regions (DMRs) can also be identified in adolescent GDM offspring is unknown. Here, we investigate which DNA regions in adolescent offspring are differentially methylated in blood by exposure to diabetes in pregnancy. The secondary aim was to characterize the RNA expression of the identified DMR, which contained the nc886 non-coding RNA.

METHODS

To identify DMRs, we employed the bump hunter method in samples from young (9-16 yr, n = 92) offspring of women with GDM (O-GDM) and control offspring (n = 94). Validation by pyrosequencing was performed in an adult offspring cohort (age 28-33 years) consisting of O-GDM (n = 82), offspring exposed to maternal type 1 diabetes (O-T1D, n = 67) and control offspring (O-BP, n = 57). RNA-expression was measured using RT-qPCR in subcutaneous adipose tissue and skeletal muscle.

RESULTS

One significant DMR represented by 10 CpGs with a bimodal methylation pattern was identified, located in the nc886/VTRNA2-1 non-coding RNA gene. Low methylation status across all CpGs of the nc886 in the young offspring was associated with maternal GDM. While low methylation degree in adult offspring in blood, adipose tissue, and skeletal muscle was not associated with maternal GDM, adipose tissue nc886 expression was increased in O-GDM compared to O-BP, but not in O-T1D. In addition, adipose tissue nc886 expression levels were positively associated with maternal pre-pregnancy BMI (p = 0.006), but not with the offspring's own adiposity.

CONCLUSIONS

Our results highlight that nc886 is a metastable epiallele, whose methylation in young offspring is negatively correlated with maternal obesity and GDM status. The physiological effect of nc886 may be more important in adipose tissue than in skeletal muscle. Further research should aim to investigate how nc886 regulation in adipose tissue by exposure to GDM may contribute to development of metabolic disease.

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.

regionalpcs: improved discovery of DNA methylation associations with complex traits

We have developed the regional principal components (rPCs) method, a novel approach for summarizing gene-level methylation. rPCs address the challenge of deciphering complex epigenetic mechanisms in diseases like Alzheimer's disease (AD). In contrast to traditional averaging, rPCs leverage principal components analysis to capture complex methylation patterns across gene regions. Our method demonstrated a 54% improvement in sensitivity over averaging in simulations, offering a robust framework for identifying subtle epigenetic variations. Applying rPCs to the AD brain methylation data in ROSMAP, combined with cell type deconvolution, we uncovered 838 differentially methylated genes associated with neuritic plaque burden-significantly outperforming conventional methods. Integrating methylation quantitative trait loci (meQTL) with genome-wide association studies (GWAS) identified 17 genes with potential causal roles in AD, including MS4A4A and PICALM. Our approach is available in the Bioconductor package regionalpcs, opening avenues for research and facilitating a deeper understanding of the epigenetic landscape in complex diseases.

Power of testing for exposure effects under incomplete mediation

Mediation analysis studies situations where an exposure may affect an outcome both directly and indirectly through intervening variables called mediators. It is frequently of interest to test for the effect of the exposure on the outcome, and the standard approach is simply to regress the latter on the former. However, it seems plausible that a more powerful test statistic could be achieved by also incorporating the mediators. This would be useful in cases where the exposure effect size might be small, which for example is common in genomics applications. Previous work has shown that this is indeed possible under complete mediation, where there is no direct effect. In most applications, however, the direct effect is likely nonzero. In this paper we study linear mediation models and find that under certain conditions, power gain is still possible under this incomplete mediation setting for testing the null hypothesis that there is neither a direct nor an indirect effect. We study a class of procedures that can achieve this performance and develop their application to both low- and high-dimensional mediators. We then illustrate their performances in simulations as well as in an analysis using DNA methylation mediators to study the effect of cigarette smoking on gene expression.

On epigenetic stochasticity, entropy and cancer risk

Epigenetic changes are known to accrue in normal cells as a result of ageing and cumulative exposure to cancer risk factors. Increasing evidence points towards age-related epigenetic changes being acquired in a quasi-stochastic manner, and that they may play a causal role in cancer development. Here, I describe the quasi-stochastic nature of DNA methylation (DNAm) changes in ageing cells as well as in normal cells at risk of neoplastic transformation, discussing the implications of this stochasticity for developing cancer risk prediction strategies, and in particular, how it may require a conceptual paradigm shift in how we select cancer risk markers. I also describe the mounting evidence that a significant proportion of DNAm changes in ageing and cancer development are related to cell proliferation, reflecting tissue-turnover and the opportunity this offers for predicting cancer risk via the development of epigenetic mitotic-like clocks. Finally, I describe how age-associated DNAm changes may be causally implicated in cancer development via an irreversible suppression of tissue-specific transcription factors that increases epigenetic and transcriptomic entropy, promoting a more plastic yet aberrant cancer stem-cell state. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

The association of cigarette smoking with DNA methylation and gene expression in human tissue samples

Cigarette smoking adversely affects many aspects of human health, and epigenetic responses to smoking may reflect mechanisms that mediate or defend against these effects. Prior studies of smoking and DNA methylation (DNAm), typically measured in leukocytes, have identified numerous smoking-associated regions (e.g., AHRR). To identify smoking-associated DNAm features in typically inaccessible tissues, we generated array-based DNAm data for 916 tissue samples from the GTEx (Genotype-Tissue Expression) project representing 9 tissue types (lung, colon, ovary, prostate, blood, breast, testis, kidney, and muscle). We identified 6,350 smoking-associated CpGs in lung tissue (n = 212) and 2,735 in colon tissue (n = 210), most not reported previously. For all 7 other tissue types (sample sizes 38-153), no clear associations were observed (false discovery rate 0.05), but some tissues showed enrichment for smoking-associated CpGs reported previously. For 1,646 loci (in lung) and 22 (in colon), smoking was associated with both DNAm and local gene expression. For loci detected in both lung and colon (e.g., AHRR, CYP1B1, CYP1A1), top CpGs often differed between tissues, but similar clusters of hyper- or hypomethylated CpGs were observed, with hypomethylation at regulatory elements corresponding to increased expression. For lung tissue, 17 hallmark gene sets were enriched for smoking-associated CpGs, including xenobiotic- and cancer-related gene sets. At least four smoking-associated regions in lung were impacted by lung methylation quantitative trait loci (QTLs) that co-localize with genome-wide association study (GWAS) signals for lung function (FEV1/FVC), suggesting epigenetic alterations can mediate the effects of smoking on lung health. Our multi-tissue approach has identified smoking-associated regions in disease-relevant tissues, including effects that are shared across tissue types.

APOBEC shapes tumor evolution and age at onset of lung cancer in smokers

APOBEC enzymes are part of the innate immunity and are responsible for restricting viruses and retroelements by deaminating cytosine residues1,2. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B)3-6. However, how APOBEC3A/B enzymes shape the tumor evolution in the presence of exogenous mutagenic processes is largely unknown. Here, by combining deep whole-genome sequencing with multi-omics profiling of 309 lung cancers from smokers with detailed tobacco smoking information, we identify two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations, whereas HAS for A3A-like mutagenesis and TP53 mutations. Unlike APOBEC3A, APOBEC3B expression is strongly associated with an upregulation of the base excision repair pathway. Hypermutation by unrepaired A3A and tobacco smoking mutagenesis combined with TP53-induced genomic instability can trigger senescence7, apoptosis8, and cell regeneration9, as indicated by high expression of pulmonary healing signaling pathway, stemness markers and distal cell-of-origin in HAS. The expected association of tobacco smoking variables (e.g., time to first cigarette) with genomic/epigenomic changes are not observed in HAS, a plausible consequence of frequent cell senescence or apoptosis. HAS have more neoantigens, slower clonal expansion, and older age at onset compared to LAS, particularly in heavy smokers, consistent with high proportions of newly generated, unmutated cells and frequent immuno-editing. These findings show how heterogeneity in mutational burden across co-occurring mutational processes and cell types contributes to tumor development, with important clinical implications.

Alteration of DNA Methylation and Epigenetic Scores Associated With Features of Schizophrenia and Common Variant Genetic Risk

BACKGROUND

Unpacking molecular perturbations associated with features of schizophrenia is a critical step toward understanding phenotypic heterogeneity in this disorder. Recent epigenome-wide association studies have uncovered pervasive dysregulation of DNA methylation in schizophrenia; however, clinical features of the disorder that account for a large proportion of phenotypic variability are relatively underexplored.

METHODS

We comprehensively analyzed patterns of DNA methylation in a cohort of 381 individuals with schizophrenia from the deeply phenotyped Australian Schizophrenia Research Bank. Epigenetic changes were investigated in association with cognitive status, age of onset, treatment resistance, Global Assessment of Functioning scores, and common variant polygenic risk scores for schizophrenia. We subsequently explored alterations within genes previously associated with psychiatric illness, phenome-wide epigenetic covariance, and epigenetic scores.

RESULTS

Epigenome-wide association studies of the 5 primary traits identified 662 suggestively significant (p < 6.72 × 10-5) differentially methylated probes, with a further 432 revealed after controlling for schizophrenia polygenic risk on the remaining 4 traits. Interestingly, we uncovered many probes within genes associated with a variety of psychiatric conditions as well as significant epigenetic covariance with phenotypes and exposures including acute myocardial infarction, C-reactive protein, and lung cancer. Epigenetic scores for treatment-resistant schizophrenia strikingly exhibited association with clozapine administration, while epigenetic proxies of plasma protein expression, such as CCL17, MMP10, and PRG2, were associated with several features of schizophrenia.

CONCLUSIONS

Our findings collectively provide novel evidence suggesting that several features of schizophrenia are associated with alteration of DNA methylation, which may contribute to interindividual phenotypic variation in affected individuals.

Sex effects on DNA methylation affect discovery in epigenome-wide association study of schizophrenia

Sex differences in the epidemiology and clinical characteristics of schizophrenia are well-known; however, the molecular mechanisms underlying these differences remain unclear. Further, the potential advantages of sex-stratified meta-analyses of epigenome-wide association studies (EWAS) of schizophrenia have not been investigated. Here, we performed sex-stratified EWAS meta-analyses to investigate whether sex stratification improves discovery, and to identify differentially methylated regions (DMRs) in schizophrenia. Peripheral blood-derived DNA methylation data from 1519 cases of schizophrenia (male n = 989, female n = 530) and 1723 controls (male n = 997, female n = 726) from three publicly available datasets, and the TOP cohort were meta-analyzed to compare sex-specific, sex-stratified, and sex-adjusted EWAS. The predictive power of each model was assessed by polymethylation score (PMS). The number of schizophrenia-associated differentially methylated positions identified was higher for the sex-stratified model than for the sex-adjusted one. We identified 20 schizophrenia-associated DMRs in the sex-stratified analysis. PMS from sex-stratified analysis outperformed that from sex-adjusted analysis in predicting schizophrenia. Notably, PMSs from the sex-stratified and female-only analyses, but not those from sex-adjusted or the male-only analyses, significantly predicted schizophrenia in males. The findings suggest that sex-stratified EWAS meta-analyses improve the identification of schizophrenia-associated epigenetic changes and highlight an interaction between sex and schizophrenia status on DNA methylation. Sex-specific DNA methylation may have potential implications for precision psychiatry and the development of stratified treatments for schizophrenia.

Unlocking the potential of tumor-derived DNA in urine for cancer detection: methodological challenges and opportunities

High cancer mortality rates and the rising cancer burden worldwide drive the development of innovative methods in order to advance cancer diagnostics. Urine contains a viable source of tumor material and allows for self-collection from home. Biomarker testing in this liquid biopsy represents a novel approach that is convenient for patients and can be effective in detecting cancer at a curable stage. Here, we set out to provide a detailed overview of the rationale behind urine-based cancer detection, with a focus on non-urological cancers, and its potential for cancer diagnostics. Moreover, evolving methodological challenges and untapped opportunities for urine biomarker testing are discussed, particularly emphasizing DNA methylation of tumor-derived cell-free DNA. We also provide future recommendations for technical advancements in urine-based cancer detection and elaborate on potential mechanisms involved in the transrenal transport of cell-free DNA.

Epigenome-wide association study of total nicotine equivalents in multiethnic current smokers from three prospective cohorts

The impact of tobacco exposure on health varies by race and ethnicity and is closely tied to internal nicotine dose, a marker of carcinogen uptake. DNA methylation is strongly responsive to smoking status and may mediate health effects, but study of associations with internal dose is limited. We performed a blood leukocyte epigenome-wide association study (EWAS) of urinary total nicotine equivalents (TNEs; a measure of nicotine uptake) and DNA methylation measured using the MethylationEPIC v1.0 BeadChip (EPIC) in six racial and ethnic groups across three cohort studies. In the Multiethnic Cohort Study (discovery, n = 1994), TNEs were associated with differential methylation at 408 CpG sites across >250 genomic regions (p < 9 × 10-8). The top significant sites were annotated to AHRR, F2RL3, RARA, GPR15, PRSS23, and 2q37.1, all of which had decreasing methylation with increasing TNEs. We identified 45 novel CpG sites, of which 42 were unique to the EPIC array and eight annotated to genes not previously linked with smoking-related DNA methylation. The most significant signal in a novel gene was cg03748458 in MIR383;SGCZ. Fifty-one of the 408 discovery sites were validated in the Singapore Chinese Health Study (n = 340) and the Southern Community Cohort Study (n = 394) (Bonferroni corrected p < 1.23 × 10-4). Significant heterogeneity by race and ethnicity was detected for CpG sites in MYO1G and CYTH1. Furthermore, TNEs significantly mediated the association between cigarettes per day and DNA methylation at 15 sites (average 22.5%-44.3% proportion mediated). Our multiethnic study highlights the transethnic and ethnic-specific methylation associations with internal nicotine dose, a strong predictor of smoking-related morbidities.

Multimodal Associations of FKBP5 Methylation with Emotion-Regulatory Brain Circuits

BACKGROUND

Understanding the biological processes underlying individual differences in emotion regulation and stress responsivity is a key challenge for translational neuroscience. The gene FKBP5 is a core regulator in molecular stress signaling that is implicated in the development of psychiatric disorders. Yet it remains unclear how FKBP5 DNA methylation (DNAm) in peripheral blood relates to individual differences in measures of neural structure and function, and their relevance to daily-life stress responsivity.

METHODS

Here, we characterize multimodal correlates of FKBP5 DNAm by combining epigenetic data with neuroimaging and Ambulatory Assessment in a sample of 395 healthy individuals.

RESULTS

First, we show that FKBP5 demethylation as a psychiatric risk factor relates to an anxiety-associated reduction of gray matter volume in the ventromedial prefrontal cortex (vmPFC), a brain area that is involved in emotion regulation and mental health risk and resilience. This effect of epigenetic upregulation of FKBP5 on neuronal structure is more pronounced where FKBP5 is epigenetically downregulated at baseline. Leveraging 208 functional MRI scans during a well-established emotion processing task we find that FKBP5 DNAm in peripheral blood is associated with functional difference of prefrontal-limbic circuits modulating affective responsivity to daily stressors, which we measured using ecological momentary assessment in daily life.

CONCLUSIONS

Overall, we demonstrate how FKBP5 contributes to interindividual differences in neural and real-life affect regulation via structural and functional changes in prefrontal-limbic brain circuits.

Genome-wide DNA methylation analysis of cannabis use disorder in a veteran cohort enriched for posttraumatic stress disorder

Cannabis use has been increasing over the past decade, not only in the general US population, but particularly among military veterans. With this rise in use has come a concomitant increase in cannabis use disorder (CUD) among veterans. Here, we performed an epigenome-wide association study for lifetime CUD in an Iraq/Afghanistan era veteran cohort enriched for posttraumatic stress disorder (PTSD) comprising 2,310 total subjects (1,109 non-Hispanic black and 1,201 non-Hispanic white). We also investigated CUD interactions with current PTSD status and examined potential indirect effects of DNA methylation (DNAm) on the relationship between CUD and psychiatric diagnoses. Four CpGs were associated with lifetime CUD, even after controlling for the effects of current smoking (AHRR cg05575921, LINC00299 cg23079012, VWA7 cg22112841, and FAM70A cg08760398). Importantly, cg05575921, a CpG strongly linked to smoking, remained associated with lifetime CUD even when restricting the analysis to veterans who reported never smoking cigarettes. Moreover, CUD interacted with current PTSD to affect cg05575921 and cg23079012 such that those with both CUD and PTSD displayed significantly lower DNAm compared to the other groups. Finally, we provide preliminary evidence that AHRR cg05575921 helps explain the association between CUD and any psychiatric diagnoses, specifically mood disorders.

Mitochondrial DNA copy number reduction via in vitro TFAM knockout remodels the nuclear epigenome and transcriptome

Mitochondrial DNA copy number (mtDNA-CN) is associated with several age-related chronic diseases and is a predictor of all-cause mortality. Here, we examine site-specific differential nuclear DNA (nDNA) methylation and differential gene expression resulting from in vitro reduction of mtDNA-CN to uncover shared genes and biological pathways mediating the effect of mtDNA-CN on disease. Epigenome and transcriptome profiles were generated for three independent human embryonic kidney (HEK293T) cell lines harbouring a mitochondrial transcription factor A (TFAM) heterozygous knockout generated via CRISPR-Cas9, and matched control lines. We identified 4,242 differentially methylated sites, 228 differentially methylated regions, and 179 differentially expressed genes associated with mtDNA-CN. Integrated analysis uncovered 381 Gene-CpG pairs. GABAA receptor genes and related pathways, the neuroactive ligand receptor interaction pathway, ABCD1/2 gene activity, and cell signalling processes were overrepresented, providing insight into the underlying biological mechanisms facilitating these associations. We also report evidence implicating chromatin state regulatory mechanisms as modulators of mtDNA-CN effect on gene expression. We demonstrate that mitochondrial DNA variation signals to the nuclear DNA epigenome and transcriptome and may lead to nuclear remodelling relevant to development, aging, and complex disease.

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.

Comprehensive evaluation of smoking exposures and their interactions on DNA methylation

BACKGROUND

Smoking impacts DNA methylation, but data are lacking on smoking-related differential methylation by sex or dietary intake, recent smoking cessation (<1 year), persistence of differential methylation from in utero smoking exposure, and effects of environmental tobacco smoke (ETS).

METHODS

We meta-analysed data from up to 15,014 adults across 5 cohorts with DNA methylation measured in blood using Illumina's EPIC array for current smoking (2560 exposed), quit < 1 year (500 exposed), in utero (286 exposed), and ETS exposure (676 exposed). We also evaluated the interaction of current smoking with sex or diet (fibre, folate, and vitamin C).

FINDINGS

Using false discovery rate (FDR < 0.05), 65,857 CpGs were differentially methylated in relation to current smoking, 4025 with recent quitting, 594 with in utero exposure, and 6 with ETS. Most current smoking CpGs attenuated within a year of quitting. CpGs related to in utero exposure in adults were enriched for those previously observed in newborns. Differential methylation by current smoking at 4-71 CpGs may be modified by sex or dietary intake. Nearly half (35-50%) of differentially methylated CpGs on the 450 K array were associated with blood gene expression. Current smoking and in utero smoking CpGs implicated 3049 and 1067 druggable targets, including chemotherapy drugs.

INTERPRETATION

Many smoking-related methylation sites were identified with Illumina's EPIC array. Most signals revert to levels observed in never smokers within a year of cessation. Many in utero smoking CpGs persist into adulthood. Smoking-related druggable targets may provide insights into cancer treatment response and shared mechanisms across smoking-related diseases.

FUNDING

Intramural Research Program of the National Institutes of Health, Norwegian Ministry of Health and Care Services and the Ministry of Education and Research, Chief Scientist Office of the Scottish Government Health Directorates and the Scottish Funding Council, Medical Research Council UK and the Wellcome Trust.

Altered DNA methylation within DNMT3A, AHRR, LTA/TNF loci mediates the effect of smoking on inflammatory bowel disease

This work aims to investigate how smoking exerts effect on the development of inflammatory bowel disease (IBD). A prospective cohort study and a Mendelian randomization study are first conducted to evaluate the association between smoking behaviors, smoking-related DNA methylation and the risks of Crohn's disease (CD) and ulcerative colitis (UC). We then perform both genome-wide methylation analysis and co-localization analysis to validate the observed associations. Compared to never smoking, current and previous smoking habits are associated with increased CD (P = 7.09 × 10-10) and UC (P < 2 × 10-16) risk, respectively. DNA methylation alteration at cg17742416 [DNMT3A] is linked to both CD (P = 7.30 × 10-8) and UC (P = 1.04 × 10-4) risk, while cg03599224 [LTA/TNF] is associated with CD risk (P = 1.91 × 10-6), and cg14647125 [AHRR] and cg23916896 [AHRR] are linked to UC risk (P = 0.001 and 0.002, respectively). Our study identifies biological mechanisms and pathways involved in the effects of smoking on the pathogenesis of IBD.

Alcohol Use Disorder-Associated DNA Methylation in the Nucleus Accumbens and Dorsolateral Prefrontal Cortex

Background

Alcohol use disorder (AUD) has a profound public health impact. However, understanding of the molecular mechanisms underlying the development and progression of AUD remain limited. Here, we interrogate AUD-associated DNA methylation (DNAm) changes within and across addiction-relevant brain regions: the nucleus accumbens (NAc) and dorsolateral prefrontal cortex (DLPFC).

Methods

Illumina HumanMethylation EPIC array data from 119 decedents of European ancestry (61 cases, 58 controls) were analyzed using robust linear regression, with adjustment for technical and biological variables. Associations were characterized using integrative analyses of public gene regulatory data and published genetic and epigenetic studies. We additionally tested for brain region-shared and -specific associations using mixed effects modeling and assessed implications of these results using public gene expression data.

Results

At a false discovery rate ≤ 0.05, we identified 53 CpGs significantly associated with AUD status for NAc and 31 CpGs for DLPFC. In a meta-analysis across the regions, we identified an additional 21 CpGs associated with AUD, for a total of 105 unique AUD-associated CpGs (120 genes). AUD-associated CpGs were enriched in histone marks that tag active promoters and our strongest signals were specific to a single brain region. Of the 120 genes, 23 overlapped with previous genetic associations for substance use behaviors; all others represent novel associations.

Conclusions

Our findings identify AUD-associated methylation signals, the majority of which are specific within NAc or DLPFC. Some signals may constitute predisposing genetic and epigenetic variation, though more work is needed to further disentangle the neurobiological gene regulatory differences associated with AUD.

Kinetic Referencing Allows Identification of Epigenetic Cytosine Modifications by Single-Molecule Hybridization Kinetics and Superresolution DNA-PAINT Microscopy

We develop a DNA origami-based internal kinetic referencing system with a colocalized reference and target molecule to provide increased sensitivity and robustness for transient binding kinetics. To showcase this, we investigate the subtle changes in binding strength of DNA oligonucleotide hybrids induced by cytosine modifications. These cytosine modifications, especially 5-methylcytosine but also its oxidized derivatives, have been increasingly studied in the context of epigenetics. Recently revealed correlations of epigenetic modifications and disease also render them interesting biomarkers for early diagnosis. Internal kinetic referencing allows us to probe and compare the influence of the different epigenetic cytosine modifications on the strengths of 7-nucleotide long DNA hybrids with one or two modified nucleotides by single-molecule imaging of their transient binding, revealing subtle differences in binding times. Interestingly, the influence of epigenetic modifications depends on their position in the DNA strand, and in the case of two modifications, effects are additive. The sensitivity of the assay indicates its potential for the direct detection of epigenetic disease markers.

Genome-wide DNA methylation risk scores for schizophrenia derived from blood and brain tissues further explain the genetic risk in patients stratified by polygenic risk scores for schizophrenia and bipolar disorder

BACKGROUND

Genetic and environmental factors contribute to the pathogenesis of schizophrenia (SZ) and bipolar disorder (BD). Among genetic risk groups stratified by combinations of Polygenic Risk Score (PRS) deciles for SZ, BD and SZ versus BD, genetic SZ risk groups had high SZ risk and prominent cognitive impairments. Furthermore, epigenetic alterations are implicated in these disorders. However, it was unclear whether DNA Methylation Risk Scores (MRSs) for SZ risk derived from blood and brain tissues were associated with SZ risk, particularly the PRS-stratified genetic SZ risk group.

METHODS

Epigenome-wide association studies (EWASs) of SZ risk in whole blood were preliminarily conducted between 66 SZ patients and 30 healthy controls (HCs) and among genetic risk groups (individuals with low genetic risk for SZ and BD in HCs (n=30) and in SZ patients (n=11), genetic BD risk in SZ patients (n=25) and genetic SZ risk in SZ patients (n=30)) stratified by combinations of PRSs for SZ, BD and SZ versus BD. Next, differences in MRSs based on independent EWASs of SZ risk in whole blood, postmortem frontal cortex (FC) and superior temporal gyrus (STG) were investigated among our case‒control and PRS-stratified genetic risk status groups.

RESULTS

Among case‒control and genetic risk status groups, 33 and 351 genome-wide significant differentially methylated positions (DMPs) associated with SZ were identified, respectively, many of which were hypermethylated. Compared with the low genetic risk in HCs group, the genetic SZ risk in SZ group had 39 genome-wide significant DMPs, while the genetic BD risk in SZ group had only six genome-wide significant DMPs. The MRSs for SZ risk derived from whole blood, FC and STG were higher in our SZ patients than in HCs in whole blood and were particularly higher in the genetic SZ risk in SZ group than in the low genetic risk in HCs and genetic BD risk in SZ groups. Conversely, the MRSs for SZ risk based on our whole-blood EWASs among genetic risk groups were also associated with SZ in the FC and STG. There were no correlations between the MRSs and PRSs.

CONCLUSIONS

These findings suggest that the MRS is a potential genetic marker in understanding SZ, particularly in patients with a genetic SZ risk.

Association between lifestyle and dietary preference factors and conventional adenomas and serrated polyps

Introduction

Both conventional adenoma (AD) and serrated polyp (SP) were known precursor lesions of colorectal cancer (CRC). Modifiable lifestyle factors were significantly associated with CRC risk, but whether these factors were related to the risk of different precursors of CRC needed to be clarified. This study aimed to evaluate the risks of AD and SP caused by lifestyle factors and compare the risk differences between AD and SP.

Methods

The study population was from the CRC screening cohort in Hangzhou, China. A total of 458,457 eligible individuals volunteered to undergo initial screening including the fecal immunochemical test (FIT) and the CRC risk assessment. Finally, 13,993 participants who had undergone colonoscopy tests and had been diagnosed at designated hospitals were selected in this study. All participants were required to fill out a questionnaire during the initial screening for collecting their information. The generalized estimate equation (GEE) model was used to assess the association between lifestyle factors/dietary preferences and AD/SP.

Results

The body mass index (BMI) and smoking were positively associated with the risks of only SP (BMI: OR = 1.50, 95%CI: 1.23-1.84; smoking: OR = 1.29, 95%CI: 1.07-1.55), only AD (BMI: OR = 1.53, 95%CI: 1.28-1.82; OR = 1.24, 95%CI: 1.11-1.39), and synchronous SP and AD (BMI: OR = 1.97, 95%CI: 1.40-2.75; smoking: OR = 1.53, 95%CI: 1.27-1.85). In the case-group comparison, smoking was more strongly associated with the risk of synchronous SP and AD than only AD. Alcohol drinking was positively associated with the risk of AD (OR = 1.28, 95%CI: 1.14-1.44), but no statistically significant difference was observed in risks in the case-group comparison. Furthermore, whole-grain intake was associated with a decreased risk of only AD (OR = 0.78, 95%CI: 0.65-0.93). However, white meat intake was positively associated with risks of only SP when compared with AD cases (OR = 1.60, 95%CI: 1.15-2.23).

Conclusion

The current study identified common risk factors such as BMI and smoking as well as different risks of certain factors (e.g., alcohol drinking and whole-grain intake) for SP and AD. However, there were still some factors, especially diet-related factors, that have not been fully elucidated in their association with the two lesions. Further research is needed in future to confirm and develop prevention strategies for different lesions.

Identification of an association between coronary heart disease and ITGB2 methylation in peripheral blood by a case-control study

BACKGROUND

Blood DNA methylation was associated with coronary heart disease (CHD) risk in Caucasians. We investigated the association between DNA methylation in peripheral blood at the reported loci and CHD in the Chinese population.

METHODS

The integrin subunit beta 2 (ITGB2) gene was identified in 196 CHD cases and 184 controls, and its methylation level was determined by mass spectrometry. Logistic regression was used to assess the association.

RESULTS

Hypomethylation of ITGB2 was significantly associated with heart failure CHD and NYHA Ⅰ&Ⅱ CHD patients with minor to medium cardiac function impairment (ITGB2_CpG_11/cg08422803, OR per -10 % methylation = 1.15 and 1.16; p = 0.012 and 0.018 by Bonferroni correction, respectively). Hypomethylation of ITGB2_CpG_11/cg08422803 was a risk factor for CHD in people < 65 years and males (p < 0.05 after Bonferroni correction). The combination of ITGB2 methylation and conventional CHD risk factors could efficiently discriminate CHD, heart failure CHD, NYHA I&II CHD, and myocardial infarction CHD patients from controls (AUC = 0.78, 0.81, 0.80, and 0.81, respectively).

CONCLUSION

Blood-based ITGB2 methylation has the potential as a biomarker for CHD. The combination of ITGB2 methylation and conventional CHD risk factors may improve the risk assessment and detection of CHD.

Longitudinal changes and variation in human DNA methylation analysed with the Illumina MethylationEPIC BeadChip assay and their implications on forensic age prediction

DNA methylation, a pivotal epigenetic modification, plays a crucial role in regulating gene expression and is known to undergo dynamic changes with age. The present study investigated epigenome-wide methylation profiles in 64 individuals over two time points, 15 years apart, using the Illumina EPIC850k arrays. A mixed-effects model identified 2821 age-associated differentially methylated CpG positions (aDMPs) with a median rate of change of 0.18% per year, consistent with a 10-15% change during a human lifespan. Significant variation in the baseline DNA methylation levels between individuals of similar ages as well as inconsistent direction of change with time across individuals were observed for all the aDMPs. Twenty-three of the 2821 aDMPs were previously incorporated into forensic age prediction models. These markers displayed larger changes in DNA methylation with age compared to all the aDMPs and less variation among individuals. Nevertheless, the forensic aDMPs also showed inter-individual variations in the direction of DNA methylation changes. Only cg16867657 in ELOVL2 exhibited a uniform direction of the age-related change among the investigated individuals, which supports the current knowledge that CpG sites in ELOVL2 are the best markers for age prediction.

Waterpipe and cigarette epigenome analysis reveals markers implicated in addiction and smoking type inference

Waterpipe smoking is frequent in the Middle East and Africa with emerging prevalence worldwide. The epigenome acts as a molecular sensor to exposures and a crucial driver in several diseases. With the widespread use of waterpipe smoking, it is timely to investigate its epigenomic markers and their role in addiction, as a central player in disease prevention and therapeutic strategies. DNA methylome-wide profiling was performed on an exposure-rich population from the Middle East, constituting of 216 blood samples split equally between never, cigarette-only and waterpipe-only smokers. Waterpipe smokers showed predominantly distinct epigenetic markers from cigarette smokers, even though both smoking forms are tobacco-based. Moreover, each smoking form could be accurately (∼90 %) inferred from the DNA methylome using machine learning. Top markers showed dose-response relationship with extent of smoking and were validated using independent technologies and additional samples (total N = 284). Smoking markers were enriched in regulatory regions and several biological pathways, primarily addiction. The epigenetically altered genes were not associated with genetic etiology of tobacco use, and the methylation levels of addiction genes, in particular, were more likely to reverse after smoking cessation. In contrast, other epigenetic markers continued to feature smoking exposure after cessation, which may explain long-term health effects observed in former smokers. This study reports, for the first time, blood epigenome-wide markers of waterpipe smokers and reveals new markers of cigarette smoking, with implications in mechanisms of addiction and the capacity to discriminate between different smoking types. These markers may offer actionable targets to reverse the epigenetic memory of addiction and can guide future prevention strategies for tobacco smoking as the most preventable cause of illnesses worldwide.

Impact of tobacco, alcohol, and marijuana on genome-wide DNA methylation and its relationship with hypertension

Tobacco, alcohol, and marijuana consumption is an important public health problem because of their high use worldwide and their association with the risk of mortality and many health conditions, such as hypertension, which is the commonest risk factor for death throughout the world. A likely pathway of action of substance consumption leading to persistent hypertension is DNA methylation. Here, we evaluated the effects of tobacco, alcohol, and marijuana on DNA methylation in the same cohort (N = 3,424). Three epigenome-wide association studies (EWAS) were assessed in whole blood using the InfiniumHumanMethylationEPIC BeadChip. We also evaluated the mediation of the top CpG sites in the association between substance consumption and hypertension. Our analyses showed 2,569 CpG sites differentially methylated by alcohol drinking and 528 by tobacco smoking. We did not find significant associations with marijuana consumption after correcting for multiple comparisons. We found 61 genes overlapping between alcohol and tobacco that were enriched in biological processes involved in the nervous and cardiovascular systems. In the mediation analysis, we found 66 CpG sites that significantly mediated the effect of alcohol consumption on hypertension. The top alcohol-related CpG site (cg06690548, P-value = 5.9·10^-83) mapped to SLC7A11 strongly mediated 70.5% of the effect of alcohol consumption on hypertension (P-value = 0.006). Our findings suggest that DNA methylation should be considered for new targets in hypertension prevention and management, particularly concerning alcohol consumption. Our data also encourage further research into the use of methylation in blood to study the neurological and cardiovascular effects of substance consumption.

Molecular Mechanism Biomarkers Predict Diagnosis in Schizophrenia and Schizoaffective Psychosis, with Implications for Treatment

Diagnostic uncertainty and relapse rates in schizophrenia and schizoaffective disorder are relatively high, indicating the potential involvement of other pathological mechanisms that could serve as diagnostic indicators to be targeted for adjunctive treatment. This study aimed to seek objective evidence of methylenetetrahydrofolate reductase MTHFR C677T genotype-related bio markers in blood and urine. Vitamin and mineral cofactors related to methylation and indolamine-catecholamine metabolism were investigated. Biomarker status for 67 symptomatically well-defined cases and 67 asymptomatic control participants was determined using receiver operating characteristics, Spearman's correlation, and logistic regression. The 5.2%-prevalent MTHFR 677 TT genotype demonstrated a 100% sensitive and specific case-predictive biomarkers of increased riboflavin (vitamin B2) excretion. This was accompanied by low plasma zinc and indicators of a shift from low methylation to high methylation state. The 48.5% prevalent MTHFR 677 CC genotype model demonstrated a low-methylation phenotype with 93% sensitivity and 92% specificity and a negative predictive value of 100%. This model related to lower vitamin cofactors, high histamine, and HPLC urine indicators of lower vitamin B2 and restricted indole-catecholamine metabolism. The 46.3%-prevalent CT genotype achieved high predictive strength for a mixed methylation phenotype. Determination of MTHFR C677T genotype dependent functional biomarker phenotypes can advance diagnostic certainty and inform therapeutic intervention.

Molecular Mechanisms Provide a Landscape for Biomarker Selection for Schizophrenia and Schizoaffective Psychosis

Research evaluating the role of the 5,10-methylenetetrahydrofolate reductase (MTHFR C677T) gene in schizophrenia has not yet provided an extended understanding of the proximal pathways contributing to the 5-10-methylenetetrahydrofolate reductase (MTHFR) enzyme's activity and the distal pathways being affected by its activity. This review investigates these pathways, describing mechanisms relevant to riboflavin availability, trace mineral interactions, and the 5-methyltetrahydrofolate (5-MTHF) product of the MTHFR enzyme. These factors remotely influence vitamin cofactor activation, histamine metabolism, catecholamine metabolism, serotonin metabolism, the oxidative stress response, DNA methylation, and nicotinamide synthesis. These biochemical components form a broad interactive landscape from which candidate markers can be drawn for research inquiry into schizophrenia and other forms of mental illness. Candidate markers drawn from this functional biochemical background have been found to have biomarker status with greater than 90% specificity and sensitivity for achieving diagnostic certainty in schizophrenia and schizoaffective psychosis. This has implications for achieving targeted treatments for serious mental illness.

Accelerated epigenetic age, inflammation, and gene expression in lung: comparisons of smokers and vapers with non-smokers

BACKGROUND

Cigarette smoking and aging are the main risk factors for pulmonary diseases, including cancer. Epigenetic aging may explain the relationship between smoking, electronic cigarette vaping, and pulmonary health. No study has examined smoking and vaping-related epigenetic aging in relation to lung biomarkers.

METHODS

Lung epigenetic aging measured by DNA methylation (mAge) and its acceleration (mAA) was assessed in young (age 21-30) electronic cigarette vapers (EC, n = 14, including 3 never-smoking EC), smokers (SM, n = 16), and non-EC/non-SM (NS, n = 39). We investigated relationships of mAge estimates with chronological age (Horvath-mAge), lifespan/mortality (Grim-mAge), telomere length (TL-mAge), smoking/EC history, urinary biomarkers, lung cytokines, and transcriptome.

RESULTS

Compared to NS, EC and SM had significantly older Grim-mAge, shorter TL-mAge, significantly accelerated Grim-mAge and decelerated TL-mAge. Among SM, Grim-mAA was associated with nicotine intake and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL). For EC, Horvath-mAA was significantly correlated with puffs per day. Overall, cytokines (IL-1β, IL-6, and IL-8) and 759 transcripts (651 unique genes) were significantly associated with Grim-mAA. Grim-mAA-associated genes were highly enriched in immune-related pathways and genes that play a role in the morphology and structures of cells/tissues.

CONCLUSIONS

Faster lung mAge for SM is consistent with prior studies of blood. Faster lung mAge for EC compared to NS indicates possible adverse pulmonary effects of EC on biological aging. Our findings support further research, particularly on epigenetic markers, on effects of smoking and vaping on pulmonary health. Given that most EC are former smokers, further study is needed to understand unique effects of electronic cigarettes on biological aging.

AHRR Hypomethylation mediates the association between maternal smoking and metabolic profiles in children

BACKGROUND

Tobacco smoking during pregnancy is associated with metabolic dysfunction in children, but mechanistic insights remain limited. Hypomethylation of cg05575921 in the aryl hydrocarbon receptor repressor (AHRR) gene is associated with in utero tobacco smoke exposure. In this study, we evaluated whether AHRR hypomethylation mediates the association between maternal smoking and metabolic dysfunction in children.

METHODS

We assessed metabolic dysfunction using liver fat content (LFC), serum, and clinical data in children aged 7-12 years (n=78) followed since birth. Maternal smoking was self-reported at 12 weeks gestation. Methylation was measured by means of pyrosequencing at 3 sequential CpG sites, including cg05575921, at birth and at ages 7-12. Regression models were used to evaluate whether AHRR methylation mediated the association between maternal smoking and child metabolic dysfunction.

RESULTS

Average AHRR methylation at birth was significantly higher among children of nonsmoking mothers compared with children of mothers who smoked (69.8% ± 4.4% vs. 63.5% ± 5.5, p=0.0006). AHRR hypomethylation at birth was associated with higher liver fat content (p=0.01), triglycerides (p=0.01), and alanine aminotransferase levels (p=0.03), and lower HDL cholesterol (p=0.01) in childhood. AHRR hypomethylation significantly mediated associations between maternal smoking and liver fat content (indirect effect=0.213, p=0.018), triglycerides (indirect effect=0.297, p=0.044), and HDL cholesterol (indirect effect = -0.413, p=0.007). AHRR methylation in childhood (n=78) was no longer significantly associated with prenatal smoke exposure or child metabolic parameters (p>0.05).

CONCLUSIONS

AHRR hypomethylation significantly mediates the association between prenatal tobacco smoke exposure and features of childhood metabolic dysfunction, despite the lack of persistent hypomethylation of AHRR into childhood. Further studies are needed to replicate these findings and to explore their causal and long-term significance.

NCAE: data-driven representations using a deep network-coherent DNA methylation autoencoder identify robust disease and risk factor signatures

Precision medicine relies on the identification of robust disease and risk factor signatures from omics data. However, current knowledge-driven approaches may overlook novel or unexpected phenomena due to the inherent biases in biological knowledge. In this study, we present a data-driven signature discovery workflow for DNA methylation analysis utilizing network-coherent autoencoders (NCAEs) with biologically relevant latent embeddings. First, we explored the architecture space of autoencoders trained on a large-scale pan-tissue compendium (n = 75 272) of human epigenome-wide association studies. We observed the emergence of co-localized patterns in the deep autoencoder latent space representations that corresponded to biological network modules. We determined the NCAE configuration with the strongest co-localization and centrality signals in the human protein interactome. Leveraging the NCAE embeddings, we then trained interpretable deep neural networks for risk factor (aging, smoking) and disease (systemic lupus erythematosus) prediction and classification tasks. Remarkably, our NCAE embedding-based models outperformed existing predictors, revealing novel DNA methylation signatures enriched in gene sets and pathways associated with the studied condition in each case. Our data-driven biomarker discovery workflow provides a generally applicable pipeline to capture relevant risk factor and disease information. By surpassing the limitations of knowledge-driven methods, our approach enhances the understanding of complex epigenetic processes, facilitating the development of more effective diagnostic and therapeutic strategies.

Blood Leukocyte AHRR Methylation and Risk of Non-smoking-associated Cancer: A Case-cohort Study of Non-Hodgkin Lymphoma

Aryl-hydrocarbon receptor repressor (AHRR) hypomethylation in peripheral blood is tightly linked with tobacco smoking and lung cancer. Here, we investigated AHRR methylation in non-Hodgkin lymphoma (NHL), a non-smoking-associated cancer. In a case-cohort study within the population-based Danish Diet, Cancer and Health cohort, we measured AHRR (cg23576855) methylation in prediagnostic blood from 161 participants who developed NHL within 13.4 years of follow-up (median: 8.5 years), with a comparison group of 164 randomly chosen participants. We measured DNA-methylation levels using bisulfite pyrosequencing and estimated incidence rate ratios (IRR) using Cox proportional hazards models with adjustment for baseline age, sex, educational level, smoking status, body mass index, alcohol intake, physical activity, and diet score. Global DNA-methylation levels were assessed by long interspersed nucleotide element 1 (LINE-1) analysis. Overall, the IRR for AHRR hypomethylation (lowest vs. other quartiles) was 2.52 [95% confidence interval (CI), 1.24-5.15]. When stratified according to time between blood draw and diagnosis, low AHRR methylation levels were associated with a future diagnosis of NHL [IRR: 4.50 (95% CI, 1.62-12.50) at 0-<5 years, 7.04 (95% CI, 2.36-21.02) at 5-<10 years, and 0.56 (95% CI, 0.21-1.45) at ≥10 years]. There was no association between global DNA-methylation levels and risk of NHL. Our results show that AHRR hypomethylation in blood leukocytes is associated with a higher risk of NHL in a time-dependent manner, suggesting that it occurs as a response to tumor development.

Significance

Our population-based study demonstrated that lower AHRR methylation levels in peripheral blood leukocytes were associated with an increased risk of NHL. This association was independent of tobacco smoking, sex, and lifestyle characteristics, but was highly dependent on time to diagnosis. These findings highlight the potential of AHRR methylation as a biomarker for NHL risk, effective up to 10 years after blood draw.

A Review of the Epigenetic Clock: Emerging Biomarkers for Asthma and Allergic Disease

DNA methylation (DNAm) is a dynamic, age-dependent epigenetic modification that can be used to study interactions between genetic and environmental factors. Environmental exposures during critical periods of growth and development may alter DNAm patterns, leading to increased susceptibility to diseases such as asthma and allergies. One method to study the role of DNAm is the epigenetic clock-an algorithm that uses DNAm levels at select age-informative Cytosine-phosphate-Guanine (CpG) dinucleotides to predict epigenetic age (EA). The difference between EA and calendar age (CA) is termed epigenetic age acceleration (EAA) and reveals information about the biological capacity of an individual. Associations between EAA and disease susceptibility have been demonstrated for a variety of age-related conditions and, more recently, phenotypes such as asthma and allergic diseases, which often begin in childhood and progress throughout the lifespan. In this review, we explore different epigenetic clocks and how they have been applied, particularly as related to childhood asthma. We delve into how in utero and early life exposures (e.g., smoking, air pollution, maternal BMI) result in methylation changes. Furthermore, we explore the potential for EAA to be used as a biomarker for asthma and allergic diseases and identify areas for further study.

Linking environmental risk factors with epigenetic mechanisms in Parkinson's disease

Sporadic Parkinson's disease (PD) is a progressive neurodegenerative disease, with a complex risk structure thought to be influenced by interactions between genetic variants and environmental exposures, although the full aetiology is unknown. Environmental factors, including pesticides, have been reported to increase the risk of developing the disease. Growing evidence suggests epigenetic changes are key mechanisms by which these environmental factors act upon gene regulation, in disease-relevant cell types. We present a systematic review critically appraising and summarising the current body of evidence of the relationship between epigenetic mechanisms and environmental risk factors in PD to inform future research in this area. Epigenetic studies of relevant environmental risk factors in animal and cell models have yielded promising results, however, research in humans is just emerging. While published studies in humans are currently relatively limited, the importance of the field for the elucidation of molecular mechanisms of pathogenesis opens clear and promising avenues for the future of PD research. Carefully designed epidemiological studies carried out in PD patients hold great potential to uncover disease-relevant gene regulatory mechanisms. Therefore, to advance this burgeoning field, we recommend broadening the scope of investigations to include more environmental exposures, increasing sample sizes, focusing on disease-relevant cell types, and recruiting more diverse cohorts.

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.

Implication of DNA methylation during lifestyle mediated weight loss

Over the past 50 years, the number of overweight/obese people increased significantly, making obesity a global public health challenge. Apart from rare monogenic forms, obesity is a multifactorial disease, most likely resulting from a concerted interaction of genetic, epigenetic and environmental factors. Although recent studies opened new avenues in elucidating the complex genetics behind obesity, the biological mechanisms contributing to individual's risk to become obese are not yet fully understood. Non-genetic factors such as eating behaviour or physical activity are strong contributing factors for the onset of obesity. These factors may interact with genetic predispositions most likely via epigenetic mechanisms. Epigenome-wide association studies or methylome-wide association studies are measuring DNA methylation at single CpGs across thousands of genes and capture associations to obesity phenotypes such as BMI. However, they only represent a snapshot in the complex biological network and cannot distinguish between causes and consequences. Intervention studies are therefore a suitable method to control for confounding factors and to avoid possible sources of bias. In particular, intervention studies documenting changes in obesity-associated epigenetic markers during lifestyle driven weight loss, make an important contribution to a better understanding of epigenetic reprogramming in obesity. To investigate the impact of lifestyle in obesity state specific DNA methylation, especially concerning the development of new strategies for prevention and individual therapy, we reviewed 19 most recent human intervention studies. In summary, this review highlights the huge potential of targeted interventions to alter disease-associated epigenetic patterns. However, there is an urgent need for further robust and larger studies to identify the specific DNA methylation biomarkers which influence obesity.

Precision epigenetics provides a scalable pathway for improving coronary heart disease care globally

Coronary heart disease (CHD) is the world's leading cause of death. Up to 90% of all CHD deaths are preventable, but effective prevention of this mortality requires more scalable, precise methods for assessing CHD status and monitoring treatment response. Unfortunately, current diagnostic methods have barriers to implementation, particularly in rural areas and lower-income countries. This gap may be bridged by highly scalable advances in DNA methylation testing methods and artificial intelligence. Herein, we review prior studies of CHD related to methylation alone and in combination with other biovariables. We compare these new methods with established methods for diagnosing CHD. Finally, we outline pathways through which methylation-based testing methods may allow the democratization of improved methods for assessing CHD globally.

Short-term smoking cessation leads to a universal decrease in whole blood genomic DNA methylation in patients with a smoking history

BACKGROUND

Epigenetics is involved in various human diseases. Smoking is one of the most common environmental factors causing epigenetic changes. The DNA methylation changes and mechanisms after quitting smoking have yet to be defined. The present study examined the changes in DNA methylation levels before and after short-term smoking cessation and explored the potential mechanism.

METHODS

Whole blood and clinical data were collected from 8 patients before and after short-term smoking cessation, DNA methylation was assessed, and differentially methylated sites were analyzed, followed by a comprehensive analysis of the differentially methylated sites with clinical data. GO/KEGG enrichment and protein-protein interaction (PPI) network analyses identified the hub genes. The differentially methylated sites between former and current smokers in GSE50660 from the GEO database were detected by GEO2R. Then, a Venn analysis was carried out using the differentially methylated sites. GO/KEGG enrichment analysis was performed on the genes corresponding to the common DNA methylation sites, the PPI network was constructed, and hub genes were predicted. The enriched genes associated with the cell cycle were selected, and the pan-cancer gene expression and clinical significance in lung cancer were analyzed based on the TCGA database.

RESULTS

Most genes showed decreased DNA methylation levels after short-term smoking cessation; 694 upregulated methylation CpG sites and 3184 downregulated methylation CpG sites were identified. The DNA methylation levels were altered according to the clinical data (body weight, expiratory, and tobacco dependence score). Enrichment analysis, construction of the PPI network, and pan-cancer analysis suggested that smoking cessation may affect various biological processes.

CONCLUSIONS

Smoking cessation leads to epigenetic changes, mainly decreased in the decline of most DNA methylation levels. Bioinformatics further identified the biologically relevant changes after short-term smoking cessation.

Epigenetic age acceleration mediates the association between smoking and diabetes-related outcomes

BACKGROUND

Smoking can lead to the deterioration of lung function and susceptibility to diabetes. Recently, smoking was found to induce DNA methylation (DNAm) changes in some cytosine-phosphate-guanine sites (CpGs). As linear combinations of DNAm levels of aging-related CpGs, five measures of epigenetic age acceleration (EAA) have received extensive attention: HannumEAA, IEAA, PhenoEAA, GrimEAA, and DunedinPACE. It is of interest to explore whether some measures of EAA can mediate the associations of smoking with diabetes-related outcomes and indices of ventilatory lung function.

METHODS AND RESULTS

In this study, we included self-reported smoking variables (smoking status, the number of pack-years, and years since smoking cessation), seven DNAm markers (HannumEAA, IEAA, PhenoEAA, GrimEAA, DNAm-based smoking pack-years, DNAm plasminogen activator inhibitor 1 [PAI-1] levels, and DunedinPACE), and four health outcomes (fasting glucose, hemoglobin A1C, forced expiratory volume in 1.0 s [FEV1], and forced vital capacity [FVC]) from 2474 Taiwan Biobank participants. Mediation analyses were conducted while adjusting for chronological age, sex, body mass index, drinking status, regular exercise status, educational attainment, and five cell-type proportions. We demonstrated that GrimEAA, DNAm-based smoking pack-years, DNAm PAI-1 levels, DunedinPACE, and PhenoEAA mediated smoking associations with diabetes-related outcomes. Moreover, current and former smoking both had an adverse indirect effect on FVC through DNAm PAI-1 levels. For former smokers, a long time since smoking cessation had a positive indirect impact on FVC through GrimEAA and on FEV1 through PhenoEAA.

CONCLUSIONS

This is one of the first studies to comprehensively investigate the role of five measures of EAA in mediating the associations of smoking with the health outcomes of an Asian population. The results showed that the second-generation epigenetic clocks (GrimEAA, DunedinPACE, and PhenoEAA) significantly mediated the associations between smoking and diabetes-related outcomes. In contrast, the first-generation epigenetic clocks (HannumEAA and IEAA) did not significantly mediate any associations of smoking variables with the four health outcomes. Cigarette smoking can, directly and indirectly, deteriorate human health through DNAm changes in aging-related CpG sites.

Genome-wide DNA methylation association study of recent and cumulative marijuana use in middle aged adults

Marijuana is a widely used psychoactive substance in the US and medical and recreational legalization has risen over the past decade. Despite the growing number of individuals using marijuana, studies investigating the association between epigenetic factors and recent and cumulative marijuana use remain limited. We therefore investigated the association between recent and cumulative marijuana use and DNA methylation levels. Participants from the Coronary Artery Risk Development in Young Adults Study with whole blood collected at examination years (Y) 15 and Y20 were randomly selected to undergo DNA methylation profiling at both timepoints using the Illumina MethylationEPIC BeadChip. Recent use of marijuana was queried at each examination and used to estimate cumulative marijuana use from Y0 to Y15 and Y20. At Y15 (n = 1023), we observed 22 and 31 methylation markers associated (FDR P ≤ 0.05) with recent and cumulative marijuana use and 132 and 16 methylation markers at Y20 (n = 883), respectively. We replicated 8 previously reported methylation markers associated with marijuana use. We further identified 640 cis-meQTLs and 198 DMRs associated with recent and cumulative use at Y15 and Y20. Differentially methylated genes were statistically overrepresented in pathways relating to cellular proliferation, hormone signaling, and infections as well as schizophrenia, bipolar disorder, and substance-related disorders. We identified numerous methylation markers, pathways, and diseases associated with recent and cumulative marijuana use in middle-aged adults, providing additional insight into the association between marijuana use and the epigenome. These results provide novel insights into the role marijuana has on the epigenome and related health conditions.

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.

Prediction of chronological age and its applications in forensic casework: methods, current practices, and future perspectives

Estimating an individual's age can be relevant in several areas primarily related to the clinical and forensic fields. In the latter, estimation of an individual's chronological age from biological material left by the perpetrator at a crime scene may provide helpful information for police investigation. Estimation of age is also beneficial in immigration cases, where age can affect the person's protection status under the law, or in disaster victim identification to narrow the list of potential missing persons. In the last decade, research has focused on establishing new approaches for age prediction in the forensic field. From the first forensic age estimations based on morphological inspections of macroscopic changes in bone and teeth, the focus has shifted to molecular methods for age estimation. These methods allow the use of samples from human biological material that does not contain morphological age features and can, in theory, be investigated in traces containing only small amounts of biological material. Molecular methods involving DNA analyses are the primary choice and estimation of DNA methylation levels at specific sites in the genome is the most promising tool. This review aims to provide an overview of the status of forensic age prediction using molecular methods, with particular focus in DNA methylation. The frequent challenges that impact forensic age prediction model development will be addressed, together with the importance of validation efforts within the forensic community.

Epigenomic profiling of isolated blood cell types reveals highly specific B cell smoking signatures and links to disease risk

BACKGROUND

Tobacco smoking alters the DNA methylation profiles of immune cells which may underpin some of the pathogenesis of smoking-associated diseases. To link smoking-driven epigenetic effects in specific immune cell types with disease risk, we isolated six leukocyte subtypes, CD14+ monocytes, CD15+ granulocytes, CD19+ B cells, CD4+ T cells, CD8+ T cells, and CD56+ natural killer cells, from whole blood of 67 healthy adult smokers and 74 nonsmokers for epigenome-wide association study (EWAS) using Illumina 450k and EPIC methylation arrays.

RESULTS

Numbers of smoking-associated differentially methylated sites (smCpGs) at genome-wide significance (p < 1.2 × 10-7) varied widely across cell types, from 5 smCpGs in CD8+ T cells to 111 smCpGs in CD19+ B cells. We found unique smoking effects in each cell type, some of which were not apparent in whole blood. Methylation-based deconvolution to estimate B cell subtypes revealed that smokers had 7.2% (p = 0.033) less naïve B cells. Adjusting for naïve and memory B cell proportions in EWAS and RNA-seq allowed the identification of genes enriched for B cell activation-related cytokine signaling pathways, Th1/Th2 responses, and hematopoietic cancers. Integrating with large-scale public datasets, 62 smCpGs were among CpGs associated with health-relevant EWASs. Furthermore, 74 smCpGs had reproducible methylation quantitative trait loci single nucleotide polymorphisms (SNPs) that were in complete linkage disequilibrium with genome-wide association study SNPs, associating with lung function, disease risks, and other traits.

CONCLUSIONS

We observed blood cell-type-specific smCpGs, a naïve-to-memory shift among B cells, and by integrating genome-wide datasets, we identified their potential links to disease risks and health traits.

Gene Set Based Integrated Methylome and Transcriptome Analysis Reveals Potential Molecular Mechanisms Linking Cigarette Smoking and Related Diseases

Advanced integrative analysis of DNA methylation and transcriptomics data may provide deeper insights into smoke-induced epigenetic alterations, their effects on gene expression and related biological processes, linking cigarette smoking and related diseases. We hypothesize that accumulation of DNA methylation changes in CpG sites across genomic locations of different genes might have biological significance. We tested the hypothesis by performing gene set based integrative analysis of blood DNA methylation and transcriptomics data to identify potential transcriptomic consequences of smoking via changes in DNA methylation in the Young Finns Study (YFS) participants (n = 1114, aged 34-49 years, women: 54%, men: 46%). First, we performed epigenome-wide association study (EWAS) of smoking. We then defined sets of genes based on DNA methylation status within their genomic regions, for example, sets of genes containing hyper- or hypomethylated CpG sites in their body or promoter regions. Gene set analysis was performed using transcriptomics data from the same participants. Two sets of genes, one containing 49 genes with hypomethylated CpG sites in their body region and the other containing 33 genes with hypomethylated CpG sites in their promoter region, were differentially expressed among the smokers. Genes in the two gene sets are involved in bone formation, metal ion transport, cell death, peptidyl-serine phosphorylation, and cerebral cortex development process, revealing epigenetic-transcriptomic pathways to smoking-related diseases such as osteoporosis, atherosclerosis, and cognitive impairment. These findings contribute to a deeper understanding of the pathophysiology of smoking-related diseases and may provide potential therapeutic targets.