Ethnicity and Smoking-Associated DNA Methylation Changes at HIV Co-Receptor GPR15

G Protein-Coupled Receptor 15 Expression Is Associated with Myocardial Infarction

Beyond the influence of lifestyle-related risk factors for myocardial infarction (MI), the mechanisms of genetic predispositions for MI remain unclear. We sought to identify and characterize differentially expressed genes in early-onset MI in a translational approach. In an observational case−control study, transcriptomes from 112 early-onset MI individuals showed upregulated G protein-coupled receptor 15 (GPR15) expression in peripheral blood mononuclear cells compared to controls (fold change = 1.4, p = 1.87 × 10−7). GPR15 expression correlated with intima-media thickness (β = 0.8498, p = 0.111), C-reactive protein (β = 0.2238, p = 0.0052), ejection fraction (β = −0.9991, p = 0.0281) and smoking (β = 0.7259, p = 2.79 × 10−10). The relation between smoking and MI was diminished after the inclusion of GPR15 expression as mediator in mediation analysis (from 1.27 (p = 1.9 × 10−5) to 0.46 (p = 0.21)). The DNA methylation of two GPR15 sites was 1%/5% lower in early-onset MI individuals versus controls (p = 2.37 × 10−6/p = 0.0123), with site CpG3.98251219 significantly predicting risk for incident MI (hazard ratio = 0.992, p = 0.0177). The nucleotide polymorphism rs2230344 (C/T) within GPR15 was associated with early-onset MI (odds ratio = 3.61, p = 0.044). Experimental validation showed 6.3-fold increased Gpr15 expression in an ischemic mouse model (p < 0.05) and 4-fold increased Gpr15 expression in cardiomyocytes under ischemic stress (p < 0.001). After the induction of MI, Gpr15gfp/gfp mice showed lower survival (p = 0.042) and deregulated gene expression for response to hypoxia and signaling pathways. Using a translational approach, our data provide evidence that GPR15 is linked to cardiovascular diseases, mediating the adverse effects of smoking.

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

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

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

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

Additive and Interactive Genetically Contextual Effects of HbA1c on cg19693031 Methylation in Type 2 Diabetes

Type 2 diabetes mellitus (T2D) has a complex genetic and environmental architecture that underlies its development and clinical presentation. Despite the identification of well over a hundred genetic variants and CpG sites that associate with T2D, a robust biosignature that could be used to prevent or forestall clinical disease has not been developed. Based on the premise that underlying genetic variation influences DNA methylation (DNAm) independently of or in combination with environmental exposures, we assessed the ability of local and distal gene x methylation (GxMeth) interactive effects to improve cg19693031 models for predicting T2D status in an African American cohort. Using genome-wide genetic data from 506 subjects, we identified a total of 1476 GxMeth terms associated with HbA1c values. The GxMeth SNPs map to biological pathways associated with the development and complications of T2D, with genetically contextual differences in methylation observed only in diabetic subjects for two GxMeth SNPs (rs2390998 AG vs. GG, p = 4.63 × 10−11, Δβ = 13%, effect size = 0.16 [95% CI = 0.05, 0.32]; rs1074390 AA vs. GG, p = 3.93 × 10−4, Δβ = 9%, effect size = 0.38 [95% CI = 0.12, 0.56]. Using a repeated stratified k-fold cross-validation approach, a series of balanced random forest classifiers with random under-sampling were built to evaluate the addition of GxMeth terms to cg19693031 models to discriminate between normoglycemic controls versus T2D subjects. The results were compared to those obtained from models incorporating only the covariates (age, sex and BMI) and the addition of cg19693031. We found a post-pruned classifier incorporating 10 GxMeth SNPs and cg19693031 adjusted for covariates predicted the T2D status, with the AUC, sensitivity, specificity and precision of the positive target class being 0.76, 0.81, 0.70 and 0.63, respectively. Comparatively, the AUC, sensitivity, specificity and precision using the covariates and cg19693031 were only 0.71, 0.74, 0.67 and 0.59, respectively. Collectively, we demonstrate correcting for genetic confounding of cg19693031 improves its ability to detect type 2 diabetes. We conclude that an integrated genetic–epigenetic approach could inform personalized medicine programming for more effective prevention and treatment of T2D.

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.

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

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

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

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

Array-Based Epigenetic Aging Indices May Be Racially Biased

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

Cigarette and Cannabis Smoking Effects on GPR15+ Helper T Cell Levels in Peripheral Blood: Relationships with Epigenetic Biomarkers

Background: Smoking causes widespread epigenetic changes that have been linked with an increased risk of smoking-associated diseases and elevated mortality. Of particular interest are changes in the level of T cells expressing G-protein-coupled receptor 15 (GPR15), a chemokine receptor linked with multiple autoimmune diseases, including inflammatory bowel disease, multiple sclerosis and psoriasis. Accordingly, a better understanding of the mechanisms by which smoking influences variation in the GPR15+ helper T cell subpopulation is of potential interest. Methods: In the current study, we used flow cytometry and digital PCR assays to measure the GPR15+CD3+CD4+ populations in peripheral blood from a cohort of n = 62 primarily African American young adults (aged 27–35 years) with a high rate of tobacco and cannabis use. Results: We demonstrated that self-reported tobacco and cannabis smoking predict GPR15⁺CD3⁺CD4⁺ helper T cell levels using linear regression models. Further, we demonstrated that methylation of two candidate CpGs, cg19859270, located in GPR15, and cg05575921, located in the gene Aryl Hydrocarbon Receptor Repressor (AHRR), were both significant predictors of GPR15⁺CD3⁺CD4⁺ cell levels, mediating the relationship between smoking habits and increases in GPR15⁺CD3⁺CD4⁺ cells. As hypothesized, the interaction between cg05575921 and cg19859270 was also significant, indicating that low cg05575921 methylation was more strongly predictive of GPR15⁺CD3⁺CD4⁺ cell levels for those who also had lower cg19859270 methylation. Conclusions: Smoking leads changes in two CpGs, cg05575921 and cg19859270, that mediate 38.5% of the relationship between tobacco and cannabis smoking and increased GPR15⁺ T_h levels in this sample. The impact of cg19859270 in amplifying the association between cg05575921 and increased GPR15⁺ T_h levels is of potential theoretical interest given the possibility that it reflects a permissive interaction between different parts of the adaptive immune system.

Using DNA methylation to validate an electronic medical record phenotype for smoking

A validated, scalable approach to characterizing (phenotyping) smoking status is needed to facilitate genetic discovery. Using established DNA methylation sites from blood samples as a criterion standard for smoking behavior, we compare three candidate electronic medical record (EMR) smoking metrics based on longitudinal EMR text notes. With data from the Veterans Aging Cohort Study (VACS), we employed a validated algorithm to translate each smoking-related text note into current, past or never categories. We compared three alternative summary characterizations of smoking: most recent, modal and trajectories using descriptive statistics and Spearman's correlation coefficients. Logistic regression and area under the curve analyses were used to compare the associations of these phenotypes with the DNA methylation sites, cg05575921 and cg03636183, which are known to have strong associations with current smoking. DNA methylation data were available from the VACS Biomarker Cohort (VACS-BC), a sub-study of VACS. We also considered whether the associations differed by the certainty of trajectory group assignment (<0.80/≥0.80). Among 140 152 VACS participants, EMR summary smoking phenotypes varied in frequency by the metric chosen: current from 33 to 53 percent; past from 16 to 24 percent and never from 24 to 33 percent. The association between the EMR smoking pairs was highest for modal and trajectories (rho = 0.89). Among 728 individuals in the VACS-BC, both DNA methylation sites were associated with all three EMR summary metrics (p < 0.001), but the strongest association with both methylation sites was observed for trajectories (p < 0.001). Longitudinal EMR smoking data support using a summary phenotype, the validity of which is enhanced when data are integrated into statistical trajectories.

Smoking and DNA methylation: Correlation of methylation with smoking behavior and association with diseases and fetus development following prenatal exposure

Among epigenetic mechanisms, DNA methylation has been widely studied with respect to many environmental factors. Smoking is a common factor which affects both global and gene-specific DNA methylation. It is supported that smoking directly affects DNA methylation, and these effects contribute to the development and progression of various diseases, such as cancer, lung and cardiovascular diseases and male infertility. In addition, prenatal smoking influences the normal development of the fetus via DNA methylation changes. The DNA methylation profile and its smoking-induced alterations helps to distinguish current from former smokers and non-smokers and can be used to predict the risk for the development of a disease. This review summarizes the DNA methylation changes induced by smoking, their correlation with smoking behavior and their association with various diseases and fetus development.

A Direct Comparison of the Relationship of Epigenetic Aging and Epigenetic Substance Consumption Markers to Mortality in the Framingham Heart Study

A number of studies have examined the relationship of indices of epigenetic aging (EA) to key health outcomes. Unfortunately, our understanding of the relationship of EA to mortality and substance use-related health variables is unclear. In order to clarify these interpretations, we analyzed the relationship of the Levine EA index (LEA), as well as established epigenetic indices of cigarette (cg05575921) and alcohol consumption (cg04987734), to all-cause mortality in the Framingham Heart Study Offspring Cohort (n = 2256) Cox proportional hazards regression. We found that cg05575921 and cg04987734 had an independent effect relative to LEA and vice versa, with the model including all the predictors having better performance than models with either LEA or cg05575921 and cg04987734 alone. After correction for multiple comparisons, 195 and 327, respectively, of the 513 markers in the LEA index, as well as the overall index itself, were significantly associated with cg05575921 and cg04987734 methylation status. We conclude that the epigenetic indices of substance use have an independent effect over and above LEA, and are slightly stronger predictors of mortality in head-to-head comparisons. We also conclude that the majority of the strength of association conveyed by the LEA is secondary to smoking and drinking behaviors, and that efforts to promote healthy aging should continue to focus on addressing substance use.

Methylation of MTHFR Moderates the Effect of Smoking on Genomewide Methylation Among Middle Age African Americans

Differential methylation at MTHFR (mMTHFR) has been examined previously as a moderator of changes in methylation among nascent smokers, but the effects of mMTHFR on genomewide patterns of methylation among established smokers in middle age are unknown. In the current investigation we examined a sample of 180 African American middle-aged smokers and non-smokers to test for patterns indicative of three different potential mechanisms of impact on epigenetic remodeling in response to long-term smoking. We found that mMTHFR moderated the association between smoking and changes in methylation for more than 25% of the 909 loci previously identified as being associated with smoking at a genomewide level of significance in middle-aged African Americans. Observed patterns of effect indicated amplification of both hyper and hypo methylating responses to smoking among those with lower mMTHFR. Moderating effects were robust to controls for sex, age, diet, and cell-type variation. Implications for potential mechanisms conferring effects are discussed. Of particular potential practical importance was a strong effect of mMTHFR on hypomethylation at GPR15 in response to smoking, indicative of the differential impact of MTHFR activity on changes in a specific cell population linked to inflammatory disease in smokers.

Novel DNA Methylation Sites Influence GPR15 Expression in Relation to Smoking

Smoking is a major risk factor for cardiovascular diseases and has been implicated in the regulation of the G protein-coupled receptor 15 (GPR15) by affecting CpG methylation. The G protein-coupled receptor 15 is involved in angiogenesis and inflammation. An effect on GPR15 gene regulation has been shown for the CpG site CpG3.98251294. We aimed to analyze the effect of smoking on GPR15 expression and methylation sites spanning the GPR15 locus. DNA methylation of nine GPR15 CpG sites was measured in leukocytes from 1291 population-based individuals using the EpiTYPER. Monocytic GPR15 expression was measured by qPCR at baseline and five-years follow up. GPR15 gene expression was upregulated in smokers (beta (ß) = −2.699, p-value (p) = 1.02 × 10⁻⁷⁷) and strongly correlated with smoking exposure (ß = −0.063, p = 2.95 × 10⁻³⁴). Smoking cessation within five years reduced GPR15 expression about 19% (p = 9.65 × 10⁻⁵) with decreasing GPR15 expression over time (ß = 0.031, p = 3.81 × 10⁻⁶). Additionally, three novel CpG sites within GPR15 affected by smoking were identified. For CpG3.98251047, DNA methylation increased steadily after smoking cessation (ß = 0.123, p = 1.67 × 10⁻³) and strongly correlated with changes in GPR15 expression (ß = 0.036, p = 4.86 × 10⁻⁵). Three novel GPR15 CpG sites were identified in relation to smoking and GPR15 expression. Our results provide novel insights in the regulation of GPR15, which possibly linked smoking to inflammation and disease progression.

Genome-wide and digital polymerase chain reaction epigenetic assessments of alcohol consumption

The lack of readily employable biomarkers of alcohol consumption is a problem for clinicians and researchers. In 2014, we published a preliminary DNA methylation signature of heavy alcohol consumption that remits as a function of abstinence. Herein, we present new genome-wide methylation findings from a cohort of additional subjects and a meta-analysis of the data. Using DNA from 47 consecutive heavy drinkers admitted for alcohol detoxification in the context of alcohol treatment and 47 abstinent controls, we replicate the 2014 results and show that 21,221 CpG residues are differentially methylated in active heavy drinkers. Meta-analysis of all data from the 448,058 probes common to the two methylation platforms shows a similarly profound signature with confirmation of findings from other groups. Principal components analyses show that genome-wide methylation changes in response to alcohol consumption load on two major factors with one component accounting at least 50% of the total variance in both smokers and nonsmoking alcoholics. Using data from the arrays, we derive a panel of five methylation probes that classifies use status with a receiver operator characteristic area under the curve (AUC) of 0.97. Finally, using droplet digital polymerase chain reaction (PCR), we convert these array-based findings to two marker assays with an AUC of 0.95 and a four marker set AUC of 0.98. We conclude that DNA methylation assessments are capable of quantifying alcohol use status and suggest that readily employable digital PCR approaches for substance consumption may find widespread use in alcohol-related research and patient care.

RNA sequencing to predict response to TNF-α inhibitors reveals possible mechanism for nonresponse in smokers

BACKGROUND

Several studies have employed microarray-based profiling to predict response to tumor necrosis factor-alpha inhibitors (TNFi) in rheumatoid arthritis (RA); yet efforts to validate these targets have failed to show predictive abilities acceptable for clinical practice.

METHODS

The eighty most extreme responders and nonresponders to TNFi therapy were selected from the observational BiOCURA cohort. RNA sequencing was performed on mRNA from peripheral blood mononuclear cells (PBMCs) collected before initiation of treatment. The expression of pathways as well as individual gene transcripts between responders and nonresponders was investigated. Promising targets were technically replicated and validated in n = 40 new patients using qPCR assays.

RESULTS

Before therapy initiation, nonresponders had lower expression of pathways related to interferon and cytokine signaling, while also showing higher levels of two genes, GPR15 and SEMA6B (p = 0.02). The two targets could be validated, however, additional analyses revealed that GPR15 and SEMA6B did not independently predict response, but were rather dose-dependent markers of smoking (p < 0.0001).

CONCLUSIONS

The study did not identify new transcripts ready to use in clinical practice, yet GPR15 and SEMA6B were recognized as candidate explanatory markers for the reduced treatment success in RA smokers.

The G protein-coupled receptor GPR34 - The past 20 years of a grownup

Research on GPR34, which was discovered in 1999 as an orphan G protein-coupled receptor of the rhodopsin-like class, disclosed its physiologic relevance only piece by piece. Being present in all recent vertebrate genomes analyzed so far it seems to improve the fitness of species although it is not essential for life and reproduction as GPR34-deficient mice demonstrate. However, closer inspection of macrophages and microglia, where it is mainly expressed, revealed its relevance in immune cell function. Recent data clearly demonstrate that GPR34 function is required to arrest microglia in the M0 homeostatic non-phagocytic phenotype. Herein, we summarize the current knowledge on its evolution, genomic and structural organization, physiology, pharmacology and relevance in human diseases including neurodegenerative diseases and cancer, which accumulated over the last 20 years.

Lung cancer early detection and health disparities: the intersection of epigenetics and ethnicity

Lung cancer is the most prominent cause of cancer-related mortality. Significant disparities in incidence and outcome characterize the disease's manifestations among ethnically and racially diverse populations. Complete surgical resection is the most effective curative treatment. However, success relies on early tumor detection. The National Lung Cancer Screening trial showed that lung cancer related mortality can be reduced by the use of low-dose CT (LDCT) screening. However, this test is plagued by a high false positive rate of 97% and the device itself is limited to designated cancer centers due to its expense and size. This restriction makes it difficult for underserved groups to access LDCT screening, the current standard of care. Highly sensitive and specific epigenetic DNA methylation-based biomarkers have the potential to work independently or in conjunction with LDCT screening to identify early-stage tumors. These tests could reduce unnecessary invasive confirmatory diagnostic tests and their associated morbidity and mortality. These tests also have the opportunity to bring lung cancer screening to the community thereby reducing unequal accessibility. However, epigenetic alterations are closely linked to the interplay between hereditary and environmental factors such as diet, lifestyle, ethnic ancestry, toxin exposure, residential segregation, and disparate community support structures. Despite this, the overwhelming number of early detection DNA methylation biomarker studies to date have either failed to control for ethnicity or have employed heavily Caucasian-biased patient cohorts. This review seeks to summarize the literature related to the early detection of lung cancer through molecular biomarkers among different ethnicities. Ethnical specific epigenetic biomarkers have the potential to be the first step towards an accessible, available personalized medicine approach to cancer through liquid biopsy.

Integrated genetic and epigenetic prediction of coronary heart disease in the Framingham Heart Study

An improved method for detecting coronary heart disease (CHD) could have substantial clinical impact. Building on the idea that systemic effects of CHD risk factors are a conglomeration of genetic and environmental factors, we use machine learning techniques and integrate genetic, epigenetic and phenotype data from the Framingham Heart Study to build and test a Random Forest classification model for symptomatic CHD. Our classifier was trained on n = 1,545 individuals and consisted of four DNA methylation sites, two SNPs, age and gender. The methylation sites and SNPs were selected during the training phase. The final trained model was then tested on n = 142 individuals. The test data comprised of individuals removed based on relatedness to those in the training dataset. This integrated classifier was capable of classifying symptomatic CHD status of those in the test set with an accuracy, sensitivity and specificity of 78%, 0.75 and 0.80, respectively. In contrast, a model using only conventional CHD risk factors as predictors had an accuracy and sensitivity of only 65% and 0.42, respectively, but with a specificity of 0.89 in the test set. Regression analyses of the methylation signatures illustrate our ability to map these signatures to known risk factors in CHD pathogenesis. These results demonstrate the capability of an integrated approach to effectively model symptomatic CHD status. These results also suggest that future studies of biomaterial collected from longitudinally informative cohorts that are specifically characterized for cardiac disease at follow-up could lead to the introduction of sensitive, readily employable integrated genetic-epigenetic algorithms for predicting onset of future symptomatic CHD.

MTHFR methylation moderates the impact of smoking on DNA methylation at AHRR for African American young adults

Smoking has been shown to have a large, reliable, and rapid effect on demethylation of AHRR, particularly at cg05575921, suggesting that methylation may be used as an index of cigarette consumption. Because the availability of methyl donors may also influence the degree of demethylation in response to smoking, factors that affect the activity of methylene tetrahydrofolate reductase (MTHFR), a key regulator of methyl group availability, may be of interest. In the current investigation, we examined the extent to which individual differences in methylation of MTHFR moderated the association between smoking and demethylation at cg05575921 as well as at other loci on AHRR associated with a main effect of smoking. Using a discovery sample (AIM, N = 293), and a confirmatory sample (SHAPE, N = 368) of young adult African Americans, degree of methylation of loci in the first exon of MTHFR was associated with amplification of the association between smoking and AHRR demethylation at cg05575921. However, genetic variation at a commonly studied MTHFR variant, C677T, did not influence cg05575921 methylation. The significant interaction between MTHFR methylation and the smoking-induced response at cg05575921 suggests a role for individual differences in methyl cycle regulation in understanding the effects of cigarette consumption on genome wide DNA methylation.

Genetically contextual effects of smoking on genome wide DNA methylation

Smoking is the leading cause of death in the United States. It exerts its effects by increasing susceptibility to a variety of complex disorders among those who smoke, and if pregnant, to their unborn children. In prior efforts to understand the epigenetic mechanisms through which this increased vulnerability is conveyed, a number of investigators have conducted genome wide methylation analyses. Unfortunately, secondary to methodological limitations, these studies were unable to examine methylation in gene regions with significant amounts of genetic variation. Using genome wide genetic and epigenetic data from the Framingham Heart Study, we re-examined the relationship of smoking status to genome wide methylation status. When only methylation status is considered, smoking was significantly associated with differential methylation in 310 genes that map to a variety of biological process and cellular differentiation pathways. However, when SNP effects on the magnitude of smoking associated methylation changes are also considered, cis and trans-interaction effects were noted at a total of 266 and 4353 genes with no marked enrichment for any biological pathways. Furthermore, the SNP variation participating in the significant interaction effects is enriched for loci previously associated with complex medical illnesses. The enlarged scope of the methylome shown to be affected by smoking may better explicate the mediational pathways linking smoking with a myriad of smoking related complex syndromes. Additionally, these results strongly suggest that combined epigenetic and genetic data analyses may be critical for a more complete understanding of the relationship between environmental variables, such as smoking, and pathophysiological outcomes.

Activation of GPR15 and its involvement in the biological effects of smoking

Smoking is one of the most significant modifiable environmental risk factors for many diseases. Smoking causes excessive mortality worldwide. Despite decades of long research, there has not been a clear understanding regarding the molecular mechanism that makes smoking harmful to health. Some recent studies have found that smoking influences most significantly the expression and methylation of GPR15. GPR15 is an orphan receptor that is involved in the regulation of the innate immunity and the T-cell trafficking in the intestinal epithelium. Further studies have confirmed that GPR15 is very strongly involved in smoking and smoking-induced molecular changes. Therefore, the altered expression and epigenetic regulation of GPR15 could have a significant role in the health impact of smoking. Impact statement The review describes an orphan receptor GPR15 that has recently been found to be influenced by smoking. This makes GPR15 very sensitive and adequate biomarker for smoking and smoking studies. Also, activation of GPR15 by smoking could help to explain its effects on health.

Comparison and combination of blood DNA methylation at smoking-associated genes and at lung cancer-related genes in prediction of lung cancer mortality

Epigenome-wide association studies have established methylation patterns related to smoking, the major risk factor of lung cancer (LC), which are distinct from methylation profiles disclosed in LC patients. This study simultaneously investigated associations of smoking-associated and LC-related methylation markers with LC mortality. DNA methylation was determined by HM450K assay in baseline blood samples of 1,565 older adults in a population-based case-cohort study. The associations of 151 smoking-associated CpGs (smoCpGs) and 3,806 LC-related CpGs (caCpGs) with LC mortality were assessed by weighted Cox regression models, controlling for potential confounders. Multi-loci methylation scores were separately constructed based on smoCpGs and caCpGs. During a median follow-up of 13.8 years, 60 participants who had a first diagnosis of LC died from LC. The average time between sample collection and LC diagnosis was 5.8 years. Hypomethylation at 77 smoCpGs and 121 caCpGs, and hypermethylation at 4 smoCpGs and 66 caCpGs were associated with LC mortality. The associations were much stronger for smoCpGs than for caCpGs. Hazard ratios (95% CI) were 7.82 (2.91-21.00) and 2.27 (0.75-6.85), respectively, for participants in highest quartile of Score I (based on 81 smoCpGs) and Score II (based on 187 caCpGs), compared with participants in the corresponding lower three quartiles. Score I outperformed Score II, with an optimism-corrected C-index of 0.87 vs. 0.77. In conclusion, although methylation changes of both smoking-associated and LC-related genes are associated with LC mortality, only smoking-associated methylation markers predict LC mortality with high accuracy, and may thus serve as promising candidates to identify high risk populations for LC screening.

DNA methylation changes of whole blood cells in response to active smoking exposure in adults: a systematic review of DNA methylation studies

Active smoking is a major preventable public health problem and an established critical factor for epigenetic modification. In this systematic review, we identified 17 studies addressing the association of active smoking exposure with methylation modifications in blood DNA, including 14 recent epigenome-wide association studies (EWASs) and 3 gene-specific methylation studies (GSMSs) on the gene regions identified by EWASs. Overall, 1460 smoking-associated CpG sites were identified in the EWASs, of which 62 sites were detected in multiple (≥3) studies. The three most frequently reported CpG sites (genes) in whole blood samples were cg05575921 (AHRR), cg03636183 (F2RL3), and cg19859270 (GPR15), followed by other loci within intergenic regions 2q37.1 and 6p21.33. These significant smoking-related genes were further assessed by specific methylation assays in three GSMSs and reflected not only current but also lifetime or long-term exposure to active smoking. In conclusion, this review summarizes the evidences for the use of blood DNA methylation patterns as biomarkers of smoking exposure for research and clinical practice. In particular, it provides a reservoir for constructing a smoking exposure index score which could be used to more precisely quantify long-term smoking exposure and evaluate the risks of smoking-induced diseases.