Epigenetic signatures of starting and stopping smoking

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.

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.

Mdivi-1: Effective but complex mitochondrial fission inhibitor

Mdivi-1, Mitochondrial DIVIsion inhibitor 1, has been widely employed in research under the assumption that it exclusively influences mitochondrial fusion, but effects other than mitochondrial dynamics have been underinvestigated. This paper provides transcriptome and DNA methylome-wide analysis for Mdivi-1 treated SH-SY5Y human neuroblastoma cells using RNA sequencing (RNA-seq) and methyl capture sequencing (MC-seq) methods. Gene ontology analysis of RNA sequences revealed that p53 transcriptional gene network and DNA replication initiation-related genes were significantly up and down-regulated, respectively, showing the correlation with the arrest cell cycle in the G1 phase. MC-seq, a powerful sequencing method for capturing DNA methylation status in CpG sites, revealed that although Mdivi-1 does not induce dramatic DNA methylation change, the subtle alterations were concentrated within the CpG island. Integrative analysis of both sequencing data disclosed that the p53 transcriptional network was activated while the Parkinson's disease pathway was halted. Next, we investigated several changes in mitochondria in response to Mdivi-1. Copy number and transcription of mitochondrial DNA were suppressed. ROS levels increased, and elevated ROS triggered mitochondrial retrograde signaling rather than inducing direct DNA damage. In this study, we could better understand the molecular network of Mdivi-1 by analyzing DNA methylation and mRNA transcription in the nucleus and further investigating various changes in mitochondria, providing inspiration for studying nuclear-mitochondrial communications.

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.

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.

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.

Association between smoking and peri-implant diseases: A retrospective study

OBJECTIVES

To determine the association between tobacco and peri-implant diseases in a sample of patients who had received implant-supported restorations in a university dental clinic. Furthermore, the study aimed to investigate patient- and implant-related variables associated with peri-implant diseases.

MATERIALS AND METHODS

The present retrospective study analyzed data from 117 patients treated with implant-supported restorations from 2001 to 2013. A total of 450 implants were evaluated. Patients were selected from an electronic database, and patient- and implant-related variables were evaluated. Detailed information regarding the smoking history (i.e., smoking status, lifetime cumulative dose, duration of exposure, intensity of the habit, and smoking cessation) was recorded. The primary study outcome was peri-implant status [i.e., health (H), peri-implant mucositis (PM) and peri-implantitis (PI)]. Univariate and multinomial regression models comparing PM and PI versus peri-implant health were conducted.

RESULTS

A total of 117 subjects [55 (47%) females and 62 (53%) males] with a mean age at examination of 64.2 years (SD 11.6) and rehabilitated with 450 implants were included. The average number of implants per patient was 4.6 (SD 3.3) with a mean time in function of 8.0 years (SD 1.9). Fifty-six patients (47.9%) were non-smokers, 42 (35.9%) were former-smokers, and 19 (16.2%) were current-smokers. Thirty-nine subjects (33.4%) were H, whereas 41 (35%) and 37 (31.6%) exhibited PM and PI, respectively. At implant level, the corresponding values were 142 (31.6%), 230 (51.1%) and 78 (17.3%). In the multinomial regression model, significant associations for peri-implant diseases were observed for the mean number of implants per patient (p = .016), function time (p = .048), implants placed simultaneously with guided bone regeneration (p = .016), implant surface (p = .020), keratinized mucosa at the buccal aspect (p = .032), and access to interproximal hygiene (p < .001). In addition, ever smokers >23 pack-years exhibited a significantly higher risk for peri-implantitis (p = .002). Finally, the multinomial regression analysis revealed that subjects who had stopped smoking more than 21 years before the last examination presented a significantly lower risk of peri-implant diseases than a smoking cessation of ≤21 years (p = .028).

CONCLUSIONS

Smoke intensity was associated with an increased risk of the development of peri-implantitis. Moreover, the risk of peri-implant diseases might be similar in those subjects who had stopped smoking for more than 21 years with respect to never-smokers.

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.

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

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

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.

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

BACKGROUND

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

RESEARCH QUESTION

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

STUDY DESIGN AND METHODS

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

RESULTS

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

INTERPRETATION

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

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

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

Involvement of epigenetics in affecting host immunity during SARS-CoV-2 infection

Coronavirus disease 19 (COVID-19) is caused by a highly contagious RNA virus Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2), originated in December 2019 in Wuhan, China. Since then, it has become a global public health concern and leads the disease table with the highest mortality rate, highlighting the necessity for a thorough understanding of its biological properties. The intricate interaction between the virus and the host immune system gives rise to diverse implications of COVID-19. RNA viruses are known to hijack the host epigenetic mechanisms of immune cells to regulate antiviral defence. Epigenetics involves processes that alter gene expression without changing the DNA sequence, leading to heritable phenotypic changes. The epigenetic landscape consists of reversible modifications like chromatin remodelling, DNA/RNA methylation, and histone methylation/acetylation that regulates gene expression. The epigenetic machinery contributes to many aspects of SARS-CoV-2 pathogenesis, like global DNA methylation and receptor angiotensin-converting enzyme 2 (ACE2) methylation determines the viral entry inside the host, viral replication, and infection efficiency. Further, it is also reported to epigenetically regulate the expression of different host cytokines affecting antiviral response. The viral proteins of SARS-CoV-2 interact with various host epigenetic enzymes like histone deacetylases (HDACs) and bromodomain-containing proteins to antagonize cellular signalling. The central role of epigenetic factors in SARS-CoV-2 pathogenesis is now exploited as promising biomarkers and therapeutic targets against COVID-19. This review article highlights the ability of SARS-CoV-2 in regulating the host epigenetic landscape during infection leading to immune evasion. It also discusses the ongoing therapeutic approaches to curtail and control the viral outbreak.

Refining epigenetic prediction of chronological and biological age

BACKGROUND

Epigenetic clocks can track both chronological age (cAge) and biological age (bAge). The latter is typically defined by physiological biomarkers and risk of adverse health outcomes, including all-cause mortality. As cohort sample sizes increase, estimates of cAge and bAge become more precise. Here, we aim to develop accurate epigenetic predictors of cAge and bAge, whilst improving our understanding of their epigenomic architecture.

METHODS

First, we perform large-scale (N = 18,413) epigenome-wide association studies (EWAS) of chronological age and all-cause mortality. Next, to create a cAge predictor, we use methylation data from 24,674 participants from the Generation Scotland study, the Lothian Birth Cohorts (LBC) of 1921 and 1936, and 8 other cohorts with publicly available data. In addition, we train a predictor of time to all-cause mortality as a proxy for bAge using the Generation Scotland cohort (1214 observed deaths). For this purpose, we use epigenetic surrogates (EpiScores) for 109 plasma proteins and the 8 component parts of GrimAge, one of the current best epigenetic predictors of survival. We test this bAge predictor in four external cohorts (LBC1921, LBC1936, the Framingham Heart Study and the Women's Health Initiative study).

RESULTS

Through the inclusion of linear and non-linear age-CpG associations from the EWAS, feature pre-selection in advance of elastic net regression, and a leave-one-cohort-out (LOCO) cross-validation framework, we obtain cAge prediction with a median absolute error equal to 2.3 years. Our bAge predictor was found to slightly outperform GrimAge in terms of the strength of its association to survival (HRGrimAge = 1.47 [1.40, 1.54] with p = 1.08 × 10-52, and HRbAge = 1.52 [1.44, 1.59] with p = 2.20 × 10-60). Finally, we introduce MethylBrowsR, an online tool to visualise epigenome-wide CpG-age associations.

CONCLUSIONS

The integration of multiple large datasets, EpiScores, non-linear DNAm effects, and new approaches to feature selection has facilitated improvements to the blood-based epigenetic prediction of biological and chronological age.

Dissecting the epigenomic differences between smoking and nicotine dependence in a veteran cohort

Smoking is a serious public health issue linked to more than 8 million deaths per year worldwide and may lead to nicotine dependence (ND). Although the epigenomic literature on smoking is well established, studies evaluating the role of epigenetics in ND are limited. In this study, we examined the epigenomic signatures of ND and how these differ from smoking exposure to identify biomarkers specific to ND. We investigated the peripheral epigenetic profile of smoking status (SS) and ND in a US male veteran cohort. DNA from saliva was collected from 1135 European American (EA) male US military veterans. DNAm was assessed using the Illumina Infinium Human MethylationEPIC BeadChip array. SS was evaluated as current smokers (n = 137; 12.1%) and non-current smokers (never and former; n = 998; 87.9%). NDFTND was assessed as a continuous variable using the Fagerström Test for ND (FTND; n = 1135; mean = 2.54 ± 2.29). Epigenome-wide association studies (EWAS) and co-methylation analyses were conducted for SS and NDFTND . A total of 450 and 22 genome-wide significant differentially methylated sites (DMS) were associated with SS and NDFTND , respectively (15 overlapped DMS). We identified 97 DMS (43 genes) in SS-EWAS previously reported in the literature, including AHRR and F2RL3 genes (p-value: 1.95 × 10-83 to 4.55 × 10-33 ). NDFTND novel DMS mapped to NEUROG1, ANPEP, and SLC29A1. Co-methylation analysis identified 386 modules (11 SS-related and 19 NDFTND -related). SS-related modules showed enrichment for alcoholism, while NDFTND -related modules were enriched for nicotine addiction. This study confirms previous findings associated with SS and identifies novel and-potentially specific-epigenetic biomarkers of ND that may inform prognosis and novel treatment strategies.

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.

A comparison of blood and brain-derived ageing and inflammation-related DNA methylation signatures and their association with microglial burdens

Inflammation and ageing-related DNA methylation patterns in the blood have been linked to a variety of morbidities, including cognitive decline and neurodegenerative disease. However, it is unclear how these blood-based patterns relate to patterns within the brain and how each associates with central cellular profiles. In this study, we profiled DNA methylation in both the blood and in five post mortem brain regions (BA17, BA20/21, BA24, BA46 and hippocampus) in 14 individuals from the Lothian Birth Cohort 1936. Microglial burdens were additionally quantified in the same brain regions. DNA methylation signatures of five epigenetic ageing biomarkers ('epigenetic clocks'), and two inflammatory biomarkers (methylation proxies for C-reactive protein and interleukin-6) were compared across tissues and regions. Divergent associations between the inflammation and ageing signatures in the blood and brain were identified, depending on region assessed. Four out of the five assessed epigenetic age acceleration measures were found to be highest in the hippocampus (β range = 0.83-1.14, p ≤ 0.02). The inflammation-related DNA methylation signatures showed no clear variation across brain regions. Reactive microglial burdens were found to be highest in the hippocampus (β = 1.32, p = 5 × 10-4 ); however, the only association identified between the blood- and brain-based methylation signatures and microglia was a significant positive association with acceleration of one epigenetic clock (termed DNAm PhenoAge) averaged over all five brain regions (β = 0.40, p = 0.002). This work highlights a potential vulnerability of the hippocampus to epigenetic ageing and provides preliminary evidence of a relationship between DNA methylation signatures in the brain and differences in microglial burdens.

Longitudinal change in blood DNA epigenetic signature after smoking cessation

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

Nicotine dose-dependent epigenomic-wide DNA methylation changes in the mice with long-term electronic cigarette exposure

Epigenomic-wide DNA methylation profiling holds the potential to reflect both electronic cigarette exposure-associated risks and individual poor health outcomes. However, a systemic study in animals or humans is still lacking. Using the Infinium Mouse Methylation BeadChip, we examined the DNA methylation status of white blood cells in male ApoE-/- mice after 14 weeks of electronic cigarette exposure with the InExpose system (2 hr/day, 5 days/week, 50% PG and 50% VG) with low (6 mg/ml) and high (36 mg/ml) nicotine concentrations. Our results indicate that electronic cigarette aerosol inhalation induces significant alteration of 8,985 CpGs in a dose-dependent manner (FDR<0.05); 7,389 (82.2%) of the CpG sites are annotated with known genes. Among the top 6 significant CpG sites (P-value<1e-8), 4 CpG sites are located in the known genes, and most (3/5) of these genes have been related to cigarette smoking. The other two CpGs are close to/associated with the Phc2 gene that was recently linked to smoking in a transcriptome-wide associations study. Furthermore, the gene set enrichment analysis highlights the activation of MAPK and 4 cardiomyocyte/cardiomyopathy-related signaling pathways (including adrenergic signaling in cardiomyocytes and arrhythmogenic right ventricular cardiomyopathy) following repeated electronic cigarette use. The MAPK pathway activation correlates well with our finding of increased cytokine mRNA expression after electronic cigarette exposure in the same batch of mice. Interestingly, two pathways related to mitochondrial activities, namely mitochondrial gene expression and mitochondrial translation, are also activated after electronic cigarette exposure. Elucidating the relationship between these pathways and the increased circulating mitochondrial DNA observed here will provide further insight into the cell-damaging effects of prolonged inhalation of e-cigarette aerosols.

Integrated methylome and phenome study of the circulating proteome reveals markers pertinent to brain health

Characterising associations between the methylome, proteome and phenome may provide insight into biological pathways governing brain health. Here, we report an integrated DNA methylation and phenotypic study of the circulating proteome in relation to brain health. Methylome-wide association studies of 4058 plasma proteins are performed (N = 774), identifying 2928 CpG-protein associations after adjustment for multiple testing. These are independent of known genetic protein quantitative trait loci (pQTLs) and common lifestyle effects. Phenome-wide association studies of each protein are then performed in relation to 15 neurological traits (N = 1,065), identifying 405 associations between the levels of 191 proteins and cognitive scores, brain imaging measures or APOE e4 status. We uncover 35 previously unreported DNA methylation signatures for 17 protein markers of brain health. The epigenetic and proteomic markers we identify are pertinent to understanding and stratifying brain health.

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

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

Smoke-induced SAV1 Gene Promoter Hypermethylation Disrupts YAP Negative Feedback and Promotes Malignant Progression of Non-small Cell Lung Cancer

YAP (gene symbol YAP1) as a potential oncoprotein, is positively correlated with the malignancy of various tumors. However, overexpression of YAP alone in multiple normal tissue cells has failed to induce tumor formation and the underlying mechanism is poorly understood. Herein, we show that YAP activation directly induces transcription of its negative regulator, SAV1, to constitute a negative feedback loop, which plays a vital role in maintaining lung epithelial cell homeostasis and was dysregulated in non-small cell lung cancer (NSCLC). Notably, smoking promotes the hypermethylation of the SAV1 promoter region, which disrupts YAP negative feedback by inactivating the Hippo pathway. Besides, exogenous overexpression of SAV1 can act as a traffic protein, activating the Hippo signaling and concurrently inhibiting the WNT pathway to decrease cancer cell growth. Furthermore, using the lung cancer organoids, we found that lentivirus-mediated SAV1 gene transfer combined with methylation inhibitor and YAP-TEAD inhibitor is a potential feasible clinical medication regimen for the lung cancer patient, especially among the smoking population. Thus, this SAV1 mediated feedback loop provides an efficient mechanism to establish the robustness and homeostasis of YAP regulation and as a potential target of gene therapy for the smoking NSCLC population.

Impact of the Exposome on the Epigenome in Inflammatory Bowel Disease Patients and Animal Models

Inflammatory bowel diseases (IBD) are chronic inflammatory disorders of the gastrointestinal tract that encompass two main phenotypes, namely Crohn's disease and ulcerative colitis. These conditions occur in genetically predisposed individuals in response to environmental factors. Epigenetics, acting by DNA methylation, post-translational histones modifications or by non-coding RNAs, could explain how the exposome (or all environmental influences over the life course, from conception to death) could influence the gene expression to contribute to intestinal inflammation. We performed a scoping search using Medline to identify all the elements of the exposome that may play a role in intestinal inflammation through epigenetic modifications, as well as the underlying mechanisms. The environmental factors epigenetically influencing the occurrence of intestinal inflammation are the maternal lifestyle (mainly diet, the occurrence of infection during pregnancy and smoking); breastfeeding; microbiota; diet (including a low-fiber diet, high-fat diet and deficiency in micronutrients); smoking habits, vitamin D and drugs (e.g., IBD treatments, antibiotics and probiotics). Influenced by both microbiota and diet, short-chain fatty acids are gut microbiota-derived metabolites resulting from the anaerobic fermentation of non-digestible dietary fibers, playing an epigenetically mediated role in the integrity of the epithelial barrier and in the defense against invading microorganisms. Although the impact of some environmental factors has been identified, the exposome-induced epimutations in IBD remain a largely underexplored field. How these environmental exposures induce epigenetic modifications (in terms of duration, frequency and the timing at which they occur) and how other environmental factors associated with IBD modulate epigenetics deserve to be further investigated.

Epigenetic mechanisms regulate sex-specific bias in disease manifestations

Abstract

Sex presents a vital determinant of a person’s physiology, anatomy, and development. Recent clinical studies indicate that sex is also involved in the differential manifestation of various diseases, affecting both clinical outcome as well as response to therapy. Genetic and epigenetic changes are implicated in sex bias and regulate disease onset, including the inactivation of the X chromosome as well as sex chromosome aneuploidy. The differential expression of X-linked genes, along with the presence of sex-specific hormones, exhibits a significant impact on immune system function. Several studies have revealed differences between the two sexes in response to infections, including respiratory diseases and COVID-19 infection, autoimmune disorders, liver fibrosis, neuropsychiatric diseases, and cancer susceptibility, which can be explained by sex-biased immune responses. In the present review, we explore the input of genetic and epigenetic interplay in the sex bias underlying disease manifestation and discuss their effects along with sex hormones on disease development and progression, aiming to reveal potential new therapeutic targets.

Key messages

Sex is involved in the differential manifestation of various diseases.

Epigenetic modifications influence X-linked gene expression, affecting immune response to infections, including COVID-19.

Epigenetic mechanisms are responsible for the sex bias observed in several respiratory and autoimmune disorders, liver fibrosis, neuropsychiatric diseases, and cancer.

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

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

Pathogenesis of chronic obstructive pulmonary disease: understanding the contributions of gene-environment interactions across the lifespan

The traditional view of chronic obstructive pulmonary disease (COPD) as a self-inflicted disease caused by tobacco smoking in genetically susceptible individuals has been challenged by recent research findings. COPD can instead be understood as the potential end result of the accumulation of gene-environment interactions encountered by an individual over the life course. Integration of a time axis in pathogenic models of COPD is necessary because the biological responses to and clinical consequences of different exposures might vary according to both the age of an individual at which a given gene-environment interaction occurs and the cumulative history of previous gene-environment interactions. Future research should aim to understand the effects of dynamic interactions between genes (G) and the environment (E) by integrating information from basic omics (eg, genomics, epigenomics, proteomics) and clinical omics (eg, phenomics, physiomics, radiomics) with exposures (the exposome) over time (T)-an approach that we refer to as GETomics. In the context of this approach, we argue that COPD should be viewed not as a single disease, but as a clinical syndrome characterised by a recognisable pattern of chronic symptoms and structural or functional impairments due to gene-environment interactions across the lifespan that influence normal lung development and ageing.

An epigenetic association analysis of childhood trauma in psychosis reveals possible overlap with methylation changes associated with PTSD

Patients with a severe mental disorder report significantly higher levels of childhood trauma (CT) than healthy individuals. Studies have suggested that CT may affect brain plasticity through epigenetic mechanisms and contribute to developing various psychiatric disorders. We performed a blood-based epigenome-wide association study using the Childhood Trauma Questionnaire-short form in 602 patients with a current severe mental illness, investigating DNA methylation association separately for five trauma subtypes and the total trauma score. The median trauma score was set as the predefined cutoff for determining whether the trauma was present or not. Additionally, we compared our genome-wide results with methylation probes annotated to candidate genes previously associated with CT. Of the patients, 83.2% reported CT above the cutoff in one or more trauma subtypes, and emotional neglect was the trauma subtype most frequently reported. We identified one significant differently methylated position associated with the gene TANGO6 for physical neglect. Seventeen differentially methylated regions (DMRs) were associated with different trauma categories. Several of these DMRs were annotated to genes previously associated with neuropsychiatric disorders such as post-traumatic stress disorder and cognitive impairments. Our results support a biomolecular association between CT and severe mental disorders. Genes that were previously identified as differentially methylated in CT-exposed subjects with and without psychosis did not show methylation differences in our analysis. We discuss this inconsistency, the relevance of our findings, and the limitations of our study.

The genetic and epigenetic profile of serum S100β in the Lothian Birth Cohort 1936 and its relationship to Alzheimer’s disease

Background: Circulating S100 calcium-binding protein (S100β) is a marker of brain inflammation that has been associated with a range of neurological conditions. To provide insight into the molecular regulation of S100β and its potential causal associations with Alzheimer’s disease, we carried out genome- and epigenome-wide association studies (GWAS/EWAS) of serum S100β levels in older adults and performed Mendelian randomisation with Alzheimer’s disease. Methods: GWAS (N=769, mean age 72.5 years, sd = 0.7) and EWAS (N=722, mean age 72.5 years, sd = 0.7) of S100β levels were performed in participants from the Lothian Birth Cohort 1936. Conditional and joint analysis (COJO) was used to identify independent loci. Expression quantitative trait locus (eQTL) analyses were performed for lead loci that had genome-wide significant associations with S100β. Bidirectional, two-sample Mendelian randomisation was used to test for causal associations between S100β and Alzheimer’s disease. Colocalisation between S100β and Alzheimer’s disease GWAS loci was also examined. Results: We identified 154 SNPs from chromosome 21 that associated (P<5x10-8) with S100β protein levels. The lead variant was located in the S100β gene (rs8128872, P=5.0x10-17). We found evidence that two independent causal variants existed for both transcription of S100β and S100β protein levels in our eQTL analyses. No CpG sites were associated with S100β levels at the epigenome-wide significant level (P<3.6x10-8); the lead probe was cg06833709 (P=5.8x10-6), which mapped to the LGI1 gene. There was no evidence of a causal association between S100β levels and Alzheimer’s disease or vice versa and no evidence for colocalisation between S100β and Alzheimer’s disease loci. Conclusions: These data provide insight into the molecular regulators of S100β levels. This context may aid in understanding the role of S100β in brain inflammation and neurological disease.

The genetic and epigenetic profile of serum S100β in the Lothian Birth Cohort 1936 and its relationship to Alzheimer's disease

Background: Circulating S100 calcium-binding protein (S100β) is a marker of brain inflammation that has been associated with a range of neurological conditions. To provide insight into the molecular regulation of S100β and its potential causal associations with Alzheimer's disease, we carried out genome- and epigenome-wide association studies (GWAS/EWAS) of serum S100β levels in older adults and performed Mendelian randomisation with Alzheimer's disease. Methods: GWAS (N=769, mean age 72.5 years, sd = 0.7) and EWAS (N=722, mean age 72.5 years, sd = 0.7) of S100β levels were performed in participants from the Lothian Birth Cohort 1936. Conditional and joint analysis (COJO) was used to identify independent loci. Expression quantitative trait locus (eQTL) analyses were performed for lead loci that had genome-wide significant associations with S100β. Bidirectional, two-sample Mendelian randomisation was used to test for causal associations between S100β and Alzheimer's disease. Colocalisation between S100β and Alzheimer's disease GWAS loci was also examined. Results: We identified 154 SNPs from chromosome 21 that associated (P<5x10 ^-8) with S100β protein levels. The lead variant was located in the S100β gene (rs8128872, P=5.0x10 ^-17). We found evidence that two independent causal variants existed for both transcription of S100β and S100β protein levels in our eQTL analyses . No CpG sites were associated with S100β levels at the epigenome-wide significant level (P<3.6x10 ^-8); the lead probe was cg06833709 (P=5.8x10 ^-6), which mapped to the LGI1 gene. There was no evidence of a causal association between S100β levels and Alzheimer's disease or vice versa and no evidence for colocalisation between S100β and Alzheimer's disease loci. Conclusions: These data provide insight into the molecular regulators of S100β levels. This context may aid in understanding the role of S100β in brain inflammation and neurological disease.

Epigenetic scores for the circulating proteome as tools for disease prediction

Protein biomarkers have been identified across many age-related morbidities. However, characterising epigenetic influences could further inform disease predictions. Here, we leverage epigenome-wide data to study links between the DNA methylation (DNAm) signatures of the circulating proteome and incident diseases. Using data from four cohorts, we trained and tested epigenetic scores (EpiScores) for 953 plasma proteins, identifying 109 scores that explained between 1% and 58% of the variance in protein levels after adjusting for known protein quantitative trait loci (pQTL) genetic effects. By projecting these EpiScores into an independent sample (Generation Scotland; n = 9537) and relating them to incident morbidities over a follow-up of 14 years, we uncovered 137 EpiScore-disease associations. These associations were largely independent of immune cell proportions, common lifestyle and health factors, and biological aging. Notably, we found that our diabetes-associated EpiScores highlighted previous top biomarker associations from proteome-wide assessments of diabetes. These EpiScores for protein levels can therefore be a valuable resource for disease prediction and risk stratification.

Smoking and Incidence of Colorectal Cancer Subclassified by Tumor-Associated Macrophage Infiltrates

BACKGROUND

Biological evidence indicates that smoking can influence macrophage functions and polarization, thereby promoting tumor evolution. We hypothesized that the association of smoking with colorectal cancer incidence might differ by macrophage infiltrates.

METHODS

Using the Nurses' Health Study and the Health Professionals Follow-up Study, we examined the association of smoking with incidence of colorectal cancer subclassified by macrophage counts. Multiplexed immunofluorescence (for CD68, CD86, IRF5, MAF, and MRC1 [CD206]) combined with digital image analysis and machine learning was used to identify overall, M1-polarized, and M2-polarized macrophages in tumor. We used inverse-probability-weighted multivariable Cox proportional hazards regression models to control for potential confounders and selection bias because of tissue data availability. All statistical tests were 2-sided.

RESULTS

During follow-up of 131 144 participants (3 648 370 person-years), we documented 3092 incident colorectal cancer cases, including 871 cases with available macrophage data. The association of pack-years smoked with colorectal cancer incidence differed by stromal macrophage densities (Pheterogeneity = .003). Compared with never smoking, multivariable-adjusted hazard ratios (95% confidence interval) for tumors with low macrophage densities were 1.32 (0.97 to 1.79) for 1-19 pack-years, 1.31 (0.92 to 1.85) for 20-39 pack-years, and 1.74 (1.26 to 2.41) for 40 or more pack-years (Ptrend = .004). In contrast, pack-years smoked was not statistically significantly associated with the incidence of tumors having intermediate or high macrophage densities (Ptrend > .009, with an α level of .005). No statistically significant differential association was found for colorectal cancer subclassified by M1-like or M2-like macrophages.

CONCLUSIONS

The association of smoking with colorectal cancer incidence is stronger for tumors with lower stromal macrophage counts. Our findings suggest an interplay of smoking and macrophages in colorectal carcinogenesis.

Epigenetic modelling of former, current and never smokers

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

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.

Epigenome-wide analysis of DNA methylation and coronary heart disease: a nested case-control study

Background

Identifying environmentally responsive genetic loci where DNA methylation is associated with coronary heart disease (CHD) may reveal novel pathways or therapeutic targets for CHD. We conducted the first prospective epigenome-wide analysis of DNA methylation in relation to incident CHD in the Asian population.

Methods

We did a nested case-control study comprising incident CHD cases and 1:1 matched controls who were identified from the 10 year follow-up of the China Kadoorie Biobank. Methylation level of baseline blood leukocyte DNA was measured by Infinium Methylation EPIC BeadChip. We performed the single cytosine-phosphate-guanine (CpG) site association analysis and network approach to identify CHD-associated CpG sites and co-methylation gene module.

Results

After quality control, 982 participants (mean age 50.1 years) were retained. Methylation level at 25 CpG sites across the genome was associated with incident CHD (genome-wide false discovery rate [FDR] < 0.05 or module-specific FDR < 0.01). One SD increase in methylation level of identified CpGs was associated with differences in CHD risk, ranging from a 47 % decrease to a 118 % increase. Mediation analyses revealed 28.5 % of the excessed CHD risk associated with smoking was mediated by methylation level at the promoter region of ANKS1A gene (P for mediation effect = 0.036). Methylation level at the promoter region of SNX30 was associated with blood pressure and subsequent risk of CHD, with the mediating proportion to be 7.7 % (P = 0.003) via systolic blood pressure and 6.4 % (P = 0.006) via diastolic blood pressure. Network analysis revealed a co-methylation module associated with CHD.

Conclusions

We identified novel blood methylation alterations associated with incident CHD in the Asian population and provided evidence of the possible role of epigenetic regulations in the smoking- and blood pressure-related pathways to CHD risk.

Funding

This work was supported by National Natural Science Foundation of China (81390544 and 91846303). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (202922/Z/16/Z, 088158/Z/09/Z, 104085/Z/14/Z), grant (2016YFC0900500, 2016YFC0900501, 2016YFC0900504, 2016YFC1303904) from the National Key R&D Program of China, and Chinese Ministry of Science and Technology (2011BAI09B01).

Epigenetic prediction of major depressive disorder

Variation in DNA methylation (DNAm) is associated with lifestyle factors such as smoking and body mass index (BMI) but there has been little research exploring its ability to identify individuals with major depressive disorder (MDD). Using penalised regression on genome-wide CpG methylation, we tested whether DNAm risk scores (MRS), trained on 1223 MDD cases and 1824 controls, could discriminate between cases (n = 363) and controls (n = 1417) in an independent sample, comparing their predictive accuracy to polygenic risk scores (PRS). The MRS explained 1.75% of the variance in MDD (β = 0.338, p = 1.17 × 10-7) and remained associated after adjustment for lifestyle factors (β = 0.219, p = 0.001, R2 = 0.68%). When modelled alongside PRS (β = 0.384, p = 4.69 × 10-9) the MRS remained associated with MDD (β = 0.327, p = 5.66 × 10-7). The MRS was also associated with incident cases of MDD who were well at recruitment but went on to develop MDD at a later assessment (β = 0.193, p = 0.016, R2 = 0.52%). Heritability analyses found additive genetic effects explained 22% of variance in the MRS, with a further 19% explained by pedigree-associated genetic effects and 16% by the shared couple environment. Smoking status was also strongly associated with MRS (β = 0.440, p ≤ 2 × 10-16). After removing smokers from the training set, the MRS strongly associated with BMI (β = 0.053, p = 0.021). We tested the association of MRS with 61 behavioural phenotypes and found that whilst PRS were associated with psychosocial and mental health phenotypes, MRS were more strongly associated with lifestyle and sociodemographic factors. DNAm-based risk scores of MDD significantly discriminated MDD cases from controls in an independent dataset and may represent an archive of exposures to lifestyle factors that are relevant to the prediction of MDD.

Surrounding Greenness and Biological Aging Based on DNA Methylation: A Twin and Family Study in Australia

BACKGROUND

High surrounding greenness has many health benefits and might contribute to slower biological aging. However, very few studies have evaluated this from the perspective of epigenetics.

OBJECTIVES

We aimed to evaluate the association between surrounding greenness and biological aging based on DNA methylation.

METHODS

We derived Horvath's DNA methylation age (DNAmAge), Hannum's DNAmAge, PhenoAge, and GrimAge based on DNA methylation measured in peripheral blood samples from 479 Australian women in 130 families. Measures of DNAmAge acceleration (DNAmAgeAC) were derived from the residuals after regressing each DNAmAge metric on chronological age. Greenness was represented by satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) metrics within 300-, 500-, 1,000-, and 2,000-m buffers surrounding participant addresses. Greenness-DNAmAgeAC associations were estimated using a within-sibship design fitted by linear mixed effect models, adjusting for familial clustering and important covariates.

RESULTS

Greenness metrics were associated with significantly lower DNAmAgeAC based on GrimAge acceleration, suggesting slower biological aging with higher greenness based on both NDVI and EVI in 300-2,000m buffer areas. For example, each interquartile range increase in NDVI within 1,000m was associated with a 0.59 (95% CI: 0.18, 1.01)-year decrease in GrimAge acceleration. Greenness was also inversely associated with three of the eight components of GrimAge, specifically, DNA methylation-based surrogates of serum cystatin-C, serum growth differentiation factor 15, and smoking pack years. Associations between greenness and biological aging measured by Horvath's and Hannum's DNAmAgeAC were less consistent, and depended on neighborhood socioeconomic status. No significant associations were estimated for PhenoAge acceleration.

DISCUSSION

Higher surrounding greenness was associated with slower biological aging, as indicated by GrimAge age acceleration, in Australian women. Associations were also evident for three individual components of GrimAge, but were inconsistent for other measures of biological aging. Additional studies are needed to confirm our results. https://doi.org/10.1289/EHP8793.

Drugs and Epigenetic Molecular Functions. A Pharmacological Data Scientometric Analysis

Interactions of drugs with the classical epigenetic mechanism of DNA methylation or histone modification are increasingly being elucidated mechanistically and used to develop novel classes of epigenetic therapeutics. A data science approach is used to synthesize current knowledge on the pharmacological implications of epigenetic regulation of gene expression. Computer-aided knowledge discovery for epigenetic implications of current approved or investigational drugs was performed by querying information from multiple publicly available gold-standard sources to (i) identify enzymes involved in classical epigenetic processes, (ii) screen original biomedical scientific publications including bibliometric analyses, (iii) identify drugs that interact with epigenetic enzymes, including their additional non-epigenetic targets, and (iv) analyze computational functional genomics of drugs with epigenetic interactions. PubMed database search yielded 3051 hits on epigenetics and drugs, starting in 1992 and peaking in 2016. Annual citations increased to a plateau in 2000 and show a downward trend since 2008. Approved and investigational drugs in the DrugBank database included 122 compounds that interacted with 68 unique epigenetic enzymes. Additional molecular functions modulated by these drugs included other enzyme interactions, whereas modulation of ion channels or G-protein-coupled receptors were underrepresented. Epigenetic interactions included (i) drug-induced modulation of DNA methylation, (ii) drug-induced modulation of histone conformations, and (iii) epigenetic modulation of drug effects by interference with pharmacokinetics or pharmacodynamics. Interactions of epigenetic molecular functions and drugs are mutual. Recent research activities on the discovery and development of novel epigenetic therapeutics have passed successfully, whereas epigenetic effects of non-epigenetic drugs or epigenetically induced changes in the targets of common drugs have not yet received the necessary systematic attention in the context of pharmacological plasticity.

Nature Versus Nurture: What Can be Learned from the Oldest-Old's Claims About Longevity?

Beneficial genetic or environmental factors that influence the length and quality of life can be evaluated while studying supercentenarians. The oldest-old can withstand serious/fatal illnesses more than their peers and/or their aging rate is decreased. Supercentenarians are an interesting group of individuals whose lifestyle is not particularly healthy according to the common guidelines, namely some of them seem to have similar harmful behaviors, but still manage to stay healthier for longer, and while eventually dying from the same degenerative diseases as the general population, they develop symptoms 20-30 years later. As there are not many supercentenarians by definition, it is worthwhile to diligently collect their data to enable future meta-analyses on larger samples; much can be learned from supercentenarians' habits and lifestyle choices about the aging process. Contributions of genetics, lifestyle choices, and epigenetics to their extended life span are discussed here.

LINE-1 methylation mediates the inverse association between body mass index and breast cancer risk: A pilot study in the Lebanese population

INTRODUCTION

Lebanon is among the top countries worldwide in combined incidence and mortality of breast cancer, which raises concern about risk factors peculiar to this country. The underlying molecular mechanisms of breast cancer require elucidation, particularly epigenetics, which is recognized as a molecular sensor to environmental exposures.

PURPOSE

We aim to explore whether DNA methylation levels of AHRR (marker of cigarette smoking), SLC1A5 and TXLNA (markers of alcohol consumption), and LINE-1 (a genome-wide repetitive retrotransposon) can act as molecular mediators underlying putative associations between breast cancer risk and pertinent extrinsic (tobacco smoking and alcohol consumption) and intrinsic factors [age and body mass index (BMI)].

METHODS

This is a cross-sectional pilot study which includes breast cancer cases (N = 65) and controls (N = 54). DNA methylation levels were measured using bisulfite pyrosequencing on available peripheral blood samples (N = 119), and Multivariate Imputation by Chained Equations (MICE) was used to impute missing DNA methylation values in remaining samples. Multiple mediation analysis was performed to assess direct and indirect (via DNA methylation) effects of intrinsic and extrinsic factors on breast cancer risk.

RESULTS

In relation to exposure, AHRR hypo-methylation was associated with cigarette but not waterpipe smoking, suggesting potentially different biomarkers of these two forms of tobacco use; SLC1A5 and TXLNA methylation were not associated with alcohol consumption; LINE-1 methylation was inversely associated with BMI (β-value [95% confidence interval (CI)] = -0.04 [-0.07, -0.02]), which remained significant after adjustment for age, smoking and alcohol consumption. In relation to breast cancer, there was no detectable association between AHRR, SLC1A5 or TXLNA methylation and cancer risk, but LINE-1 methylation was significantly higher in breast cancer cases when compared to controls (mean ± SD: 72.00 ± 0.66 versus 70.89 ± 0.73, P = 4.67 × 10-14). This difference remained significant after adjustment for confounders (odds ratio (OR) [95% CI] = 9.75[3.74, 25.39]). Moreover, LINE-1 hypo-methylation mediated 83% of the inverse effect of BMI on breast cancer risk.

CONCLUSION

This pilot study demonstrates that alterations in blood LINE-1 methylation mediate the inverse effect of BMI on breast cancer risk. This warrants large scale studies and stratification based on clinic-pathological types of breast cancer.

Sex-specific associations with DNA methylation in lung tissue demonstrate smoking interactions

Cigarette smoking impacts DNA methylation, but the investigation of sex-specific features of lung tissue DNA methylation in smokers has been limited. Women appear more susceptible to cigarette smoke, and often develop more severe lung disease at an earlier age with less smoke exposure. We aimed to analyse whether there are sex differences in DNA methylation in lung tissue and whether these DNA methylation marks interact with smoking. We collected lung tissue samples from former smokers who underwent lung tissue resection. One hundred thirty samples from white subjects were included for this analysis. Regression models for sex as a predictor of methylation were adjusted for age, presence of COPD, smoking variables and technical batch variables revealed 710 associated sites. 294 sites demonstrated robust sex-specific methylation associations in foetal lung tissue. Pathway analysis identified 6 nominally significant pathways including the mitophagy pathway. Three CpG sites demonstrated a suggested interaction between sex and pack-years of smoking: GPR132, ANKRD44 and C19orf60. All of them were nominally significant in both male- and female-specific models, and the effect estimates were in opposite directions for male and female; GPR132 demonstrated significant association between DNA methylation and gene expression in lung tissue (P < 0.05). Sex-specific associations with DNA methylation in lung tissue are wide-spread and may reveal genes and pathways relevant to sex differences for lung damaging effects of cigarette smoking.

Creating and validating a DNA methylation-based proxy for interleukin-6

Background

Studies evaluating the relationship between chronic inflammation and cognitive functioning have produced heterogeneous results. A potential reason for this is the variability of inflammatory mediators which could lead to misclassifications of individuals’ persisting levels of inflammation. DNA methylation (DNAm) has shown utility in indexing environmental exposures and could be leveraged to provide proxy signatures of chronic inflammation.

Method

We conducted an elastic net regression of interleukin-6 (IL-6) in a cohort of 875 older adults (Lothian Birth Cohort 1936; mean age: 70 years) to develop a DNAm-based predictor. The predictor was tested in an independent cohort (Generation Scotland; N = 7028 [417 with measured IL-6], mean age: 51 years).

Results

A weighted score from 35 CpG sites optimally predicted IL-6 in the independent test set (Generation Scotland; R² = 4.4%, p = 2.1 × 10⁻⁵). In the independent test cohort, both measured IL-6 and the DNAm proxy increased with age (serum IL-6: n = 417, β = 0.02, SE = 0.004, p = 1.3 × 10⁻⁷; DNAm IL-6 score: N = 7028, β = 0.02, SE = 0.0009, p < 2 × 10⁻¹⁶). Serum IL-6 did not associate with cognitive ability (n = 417, β = −0.06, SE = 0.05, p = .19); however, an inverse association was identified between the DNAm score and cognitive functioning (N = 7028, β = −0.16, SE = 0.02, p_FDR < 2 × 10⁻¹⁶).

Conclusions

These results suggest methylation-based predictors can be used as proxies for inflammatory markers, potentially allowing for further insight into the relationship between inflammation and pertinent health outcomes.

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

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

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

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

Epigenetic mechanisms influencing COVID-19

The COVID-19 pandemic is one of the most significant public health threats in recent history and has impacted the lives of almost everyone worldwide. Epigenetic mechanisms contribute to many aspects of the SARS-CoV-2 replication cycle, including expression levels of viral receptor ACE2, expression of cytokine genes as part of the host immune response, and the implication of various histone modifications in several aspects of COVID-19. SARS-CoV-2 proteins physically associate with many different host proteins over the course of infection, and notably there are several interactions between viral proteins and epigenetic enzymes such as HDACs and bromodomain-containing proteins as shown by correlation-based studies. The many contributions of epigenetic mechanisms to the viral life cycle and the host immune response to infection have resulted in epigenetic factors being identified as emerging biomarkers for COVID-19, and project epigenetic modifiers as promising therapeutic targets to combat COVID-19. This review article highlights the major epigenetic pathways at play during COVID-19 disease and discusses ongoing clinical trials that will hopefully contribute to slowing the spread of SARS-CoV-2.

Linked patterns of biological and environmental covariation with brain structure in adolescence: a population-based longitudinal study

Adolescence is a period of major brain reorganization shaped by biologically timed and by environmental factors. We sought to discover linked patterns of covariation between brain structural development and a wide array of these factors by leveraging data from the IMAGEN study, a longitudinal population-based cohort of adolescents. Brain structural measures and a comprehensive array of non-imaging features (relating to demographic, anthropometric, and psychosocial characteristics) were available on 1476 IMAGEN participants aged 14 years and from a subsample reassessed at age 19 years (n = 714). We applied sparse canonical correlation analyses (sCCA) to the cross-sectional and longitudinal data to extract modes with maximum covariation between neuroimaging and non-imaging measures. Separate sCCAs for cortical thickness, cortical surface area and subcortical volumes confirmed that each imaging phenotype was correlated with non-imaging features (sCCA r range: 0.30-0.65, all P_FDR < 0.001). Total intracranial volume and global measures of cortical thickness and surface area had the highest canonical cross-loadings (|ρ| = 0.31-0.61). Age, physical growth and sex had the highest association with adolescent brain structure (|ρ| = 0.24-0.62); at baseline, further significant positive associations were noted for cognitive measures while negative associations were observed at both time points for prenatal parental smoking, life events, and negative affect and substance use in youth (|ρ| = 0.10-0.23). Sex, physical growth and age are the dominant influences on adolescent brain development. We highlight the persistent negative influences of prenatal parental smoking and youth substance use as they are modifiable and of relevance for public health initiatives.

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.

DNA methylation alterations and their potential influence on macrophage in periodontitis

OBJECTIVES

To explore how various methylation mechanisms function and affect macrophages in periodontitis, with an aim of getting a comprehensive understanding of pathogenesis of the disease.

SUBJECT

Alterations in DNA methylation are associated with different periodontitis susceptible factors and disrupt immunity homeostasis. The host's immune response to stimulus plays a vital role in the progression of periodontitis. Macrophages are key immune cells of immune system. They act as critical regulators in maintaining issue homeostasis with their nature of high plasticity. The altered methylation status of genes may cause abnormal expression of proteins in the progress of periodontitis, thus, exert potential influence on macrophages.

RESULTS

Certain genes are selectively activated or silenced due to the changes in the methylation status, which causes the alteration of the expression level of cytokines/chemokines, signal molecules, extracellular matrix molecules, leads to the change in local microenvironment, affects activation states of immune cells including macrophages, thus influences the host immune response during periodontitis.. This results in differential susceptibility and therapeutic outcome.

CONCLUSION

DNA methylation alteration may cause aberrant expression level of genes associated with periodontal diseases, thus results in deregulation of macrophages, which supports the prospect of using DNA methylation-related parameter as a new biomarker for the diagnosis and treatment of periodontitis.

AHRR methylation in heavy smokers: associations with smoking, lung cancer risk, and lung cancer mortality

BACKGROUND

A low level of methylation at cg05575921 in the aryl-hydrocarbon receptor repressor (AHRR) gene is robustly associated with smoking, and some studies have observed associations between cg05575921 methylation and increased lung cancer risk and mortality. To prospectively examine whether decreased methylation at cg05575921 may identify high risk subpopulations for lung cancer screening among heavy smokers, and mortality in cases, we evaluated associations between cg05575921 methylation and lung cancer risk and mortality, by histotype, in heavy smokers.

METHODS

The β-Carotene and Retinol Efficacy Trial (CARET) included enrollees ages 45-69 with ≥ 20 pack-year smoking histories and/or occupational asbestos exposure. A subset of CARET participants had cg05575921 methylation available from HumanMethylationEPIC assays of blood collected on average 4.3 years prior to lung cancer diagnosis in cases. Cg05575921 methylation β-values were treated continuously for a 10% methylation decrease and as quintiles, where quintile 1 (Q1, referent) represents high methylation and Q5, low methylation. We used conditional logistic regression models to examine lung cancer risk overall and by histotype in a nested case-control study including 316 lung cancer cases (diagnosed through 2005) and 316 lung cancer-free controls matched on age (±5 years), sex, race/ethnicity, enrollment year, current/former smoking, asbestos exposure, and follow-up time. Mortality analyses included 372 lung cancer cases diagnosed between 1985 and 2013 with available methylation data. We used Cox proportional hazards models to examine mortality overall and by histotype.

RESULTS

Decreased cg05575921 methylation was strongly associated with smoking, even in our population of heavy smokers. We did not observe associations between decreased pre-diagnosis cg05575921 methylation and increased lung cancer risk, overall or by histotype. We observed linear increasing trends for lung cancer-specific mortality across decreasing cg05575921 methylation quintiles for adenocarcinoma and small cell carcinoma (P-trends = 0.01 and 0.04, respectively).

CONCLUSIONS

In our study of heavy smokers, decreased cg05575921 methylation was strongly associated with smoking but not increased lung cancer risk. The observed association between cg05575921 methylation and increased mortality in adenocarcinoma and small cell histotypes requires further examination. Our results do not support using decreased cg05575921 methylation as a biomarker for lung cancer screening risk stratification.

Epigenome-450K-wide methylation signatures of active cigarette smoking: The Young Finns Study

Smoking as a major risk factor for morbidity affects numerous regulatory systems of the human body including DNA methylation. Most of the previous studies with genome-wide methylation data are based on conventional association analysis and earliest threshold-based gene set analysis that lacks sensitivity to be able to reveal all the relevant effects of smoking. The aim of the present study was to investigate the impact of active smoking on DNA methylation at three biological levels: 5'-C-phosphate-G-3' (CpG) sites, genes and functionally related genes (gene sets). Gene set analysis was done with mGSZ, a modern threshold-free method previously developed by us that utilizes all the genes in the experiment and their differential methylation scores. Application of such method in DNA methylation study is novel. Epigenome-wide methylation levels were profiled from Young Finns Study (YFS) participants' whole blood from 2011 follow-up using Illumina Infinium HumanMethylation450 BeadChips. We identified three novel smoking related CpG sites and replicated 57 of the previously identified ones. We found that smoking is associated with hypomethylation in shore (genomic regions 0-2 kilobases from CpG island). We identified smoking related methylation changes in 13 gene sets with false discovery rate (FDR) ≤ 0.05, among which is olfactory receptor activity, the flagship novel finding of the present study. Overall, we extended the current knowledge by identifying: (i) three novel smoking related CpG sites, (ii) similar effects as aging on average methylation in shore, and (iii) a novel finding that olfactory receptor activity pathway responds to tobacco smoke and toxin exposure through epigenetic mechanisms.