Modeling the Causal Role of DNA Methylation in the Association Between Cigarette Smoking and Inflammation in African Americans: A 2-Step Epigenetic Mendelian Randomization Study

Multi-omic integration reveals alterations in nasal mucosal biology that mediate air pollutant effects on allergic rhinitis

BACKGROUND

Allergic rhinitis is a common inflammatory condition of the nasal mucosa that imposes a considerable health burden. Air pollution has been observed to increase the risk of developing allergic rhinitis. We addressed the hypotheses that early life exposure to air toxics is associated with developing allergic rhinitis, and that these effects are mediated by DNA methylation and gene expression in the nasal mucosa.

METHODS

In a case-control cohort of 505 participants, we geocoded participants' early life exposure to air toxics using data from the US Environmental Protection Agency, assessed physician diagnosis of allergic rhinitis by questionnaire, and collected nasal brushings for whole-genome DNA methylation and transcriptome profiling. We then performed a series of analyses including differential expression, Mendelian randomization, and causal mediation analyses to characterize relationships between early life air toxics, nasal DNA methylation, nasal gene expression, and allergic rhinitis.

RESULTS

Among the 505 participants, 275 had allergic rhinitis. The mean age of the participants was 16.4 years (standard deviation = 9.5 years). Early life exposure to air toxics such as acrylic acid, phosphine, antimony compounds, and benzyl chloride was associated with developing allergic rhinitis. These air toxics exerted their effects by altering the nasal DNA methylation and nasal gene expression levels of genes involved in respiratory ciliary function, mast cell activation, pro-inflammatory TGF-β1 signaling, and the regulation of myeloid immune cell function.

CONCLUSIONS

Our results expand the range of air pollutants implicated in allergic rhinitis and shed light on their underlying biological mechanisms in nasal mucosa.

Molecular mechanisms of environmental exposures and human disease

A substantial proportion of disease risk for common complex disorders is attributable to environmental exposures and pollutants. An appreciation of how environmental pollutants act on our cells to produce deleterious health effects has led to advances in our understanding of the molecular mechanisms underlying the pathogenesis of chronic diseases, including cancer and cardiovascular, neurodegenerative and respiratory diseases. Here, we discuss emerging research on the interplay of environmental pollutants with the human genome and epigenome. We review evidence showing the environmental impact on gene expression through epigenetic modifications, including DNA methylation, histone modification and non-coding RNAs. We also highlight recent studies that evaluate recently discovered molecular processes through which the environment can exert its effects, including extracellular vesicles, the epitranscriptome and the mitochondrial genome. Finally, we discuss current challenges when studying the exposome - the cumulative measure of environmental influences over the lifespan - and its integration into future environmental health research.

DNA methylation pattern of hypertriglyceridemic subjects

BACKGROUND

Chylomicronemias are generally diagnosed genetically by genomic sequencing or screening for mutations in causal genes with a large phenotypic effect. This strategy has allowed to improve the characterization of these patients, but we still have 30% of the patients without a conclusive genetic diagnosis. This is why we hypothesize that by adding the epigenetic component we can improve the genetic diagnosis, and for this we have explored the degree of methylation in the DNA of hypertriglyceridemic patients.

METHODOLOGY

Blood cell DNA was obtained from 16 hypertriglyceridemic patients and from 16 age- and sex-matched control subjects. The degree of methylation in genome-wide DNA was determined using the Illumina® Infinium Methylation EPIC Array Analysis.

RESULTS

We identified 31 differentially methylated cytosines by comparing the methylation patterns presented by hypertriglyceridemic patients vs. control subjects. The cg03636183 in the F2RL3 gene was 10% hypomethylated in hypertriglyceridemic patients, and has previously been associated with an increased cardiovascular risk. Cg13824500 is 10% hypomethylated in hypertriglyceridemic patients and is located in VTI1A, which is a limiting gene in the transit of chylomicrons in the enterocyte through the endoplasmic reticulum and the Golgi apparatus. Cg26468118 in the RAB20 gene (13% hypomethylated) and cg21560722 in the SBF2 gene (33% hypermethylated) are involved in the regulation of Golgi apparatus vesicles.

CONCLUSIONS

Our results suggest that there are differentially methylated regions related to the formation of chylomicrons in hypertriglyceridemic patients.

Inflammatory biomarker relationships with helper T cell GPR15 expression and cannabis and tobacco smoking

OBJECTIVE

Smoking is associated with numerous inflammatory and autoimmune conditions. The goal of this study was to examine whether increased expression of G-protein-coupled receptor 15 (GPR15) on helper T cells in smokers could predispose to these conditions through its relationship with inflammatory biomarkers.

METHODS

We used flow cytometric measurement of GPR15⁺CD3⁺CD4⁺ helper T cells and serum assays for C-reactive protein (CRP) and 17 cytokines drawn from peripheral blood samples from a cohort of n = 62 primarily African American young adults (aged 27-35 years). These variables were examined cross-sectionally in conjunction with serum biomarkers of tobacco (cotinine) and cannabis (tetrahydrocannabinol) use and lifestyle factors potentially impacting immune function in correlational analyses and linear regression models.

RESULTS

Tobacco and cannabis smoking were strongly associated with increased GPR15 expression on helper T cells (p < 0.001), which was in turn was strongly associated with the ratio of pro-inflammatory to anti-inflammatory cytokines (p < 0.001). Mediation analyses indicated increased GPR15 expression accounted for roughly half of the relationship between smoking variables and pro-inflammatory to anti-inflammatory cytokine balance. CRP was not associated with cannabis or tobacco use or GPR15+ expression, but was associated with body mass index (p < 0.001). These relationships persisted after controlling for lifestyle and medical factors impacting immune function.

CONCLUSIONS

Increased expression of GPR15 by helper T cells in smokers may mediate some of the relationship between smoking and a pro-inflammatory cytokine milieu. Better understanding of this relationship may help uncover how smoking increases the risk of inflammatory diseases.

Smoking-related changes in DNA methylation and gene expression are associated with cardio-metabolic traits

BACKGROUND

Tobacco smoking is a well-known modifiable risk factor for many chronic diseases, including cardiovascular disease (CVD). One of the proposed underlying mechanism linking smoking to disease is via epigenetic modifications, which could affect the expression of disease-associated genes. Here, we conducted a three-way association study to identify the relationship between smoking-related changes in DNA methylation and gene expression and their associations with cardio-metabolic traits.

RESULTS

We selected 2549 CpG sites and 443 gene expression probes associated with current versus never smokers, from the largest epigenome-wide association study and transcriptome-wide association study to date. We examined three-way associations, including CpG versus gene expression, cardio-metabolic trait versus CpG, and cardio-metabolic trait versus gene expression, in the Rotterdam study. Subsequently, we replicated our findings in The Cooperative Health Research in the Region of Augsburg (KORA) study. After correction for multiple testing, we identified both cis- and trans-expression quantitative trait methylation (eQTM) associations in blood. Specifically, we found 1224 smoking-related CpGs associated with at least one of the 443 gene expression probes, and 200 smoking-related gene expression probes to be associated with at least one of the 2549 CpGs. Out of these, 109 CpGs and 27 genes were associated with at least one cardio-metabolic trait in the Rotterdam Study. We were able to replicate the associations with cardio-metabolic traits of 26 CpGs and 19 genes in the KORA study. Furthermore, we identified a three-way association of triglycerides with two CpGs and two genes (GZMA; CLDND1), and BMI with six CpGs and two genes (PID1; LRRN3). Finally, our results revealed the mediation effect of cg03636183 (F2RL3), cg06096336 (PSMD1), cg13708645 (KDM2B), and cg17287155 (AHRR) within the association between smoking and LRRN3 expression.

CONCLUSIONS

Our study indicates that smoking-related changes in DNA methylation and gene expression are associated with cardio-metabolic risk factors. These findings may provide additional insights into the molecular mechanisms linking smoking to the development of CVD.

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

Background

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

Methods

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

Results

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

Conclusion

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

The role of cigarette smoke-induced epigenetic alterations in inflammation

Background

Exposure to cigarette smoke (CS) is a major threat to human health worldwide. It is well established that smoking increases the risk of respiratory diseases, cardiovascular diseases and different forms of cancer, including lung, liver, and colon. CS-triggered inflammation is considered to play a central role in various pathologies by a mechanism that stimulates the release of pro-inflammatory cytokines. During this process, epigenetic alterations are known to play important roles in the specificity and duration of gene transcription.

Main text

Epigenetic alterations include three major modifications: DNA modifications via methylation; various posttranslational modifications of histones, namely, methylation, acetylation, phosphorylation, and ubiquitination; and non-coding RNA sequences. These modifications work in concert to regulate gene transcription in a heritable fashion. The enzymes that regulate these epigenetic modifications can be activated by smoking, which further mediates the expression of multiple inflammatory genes. In this review, we summarize the current knowledge on the epigenetic alterations triggered by CS and assess how such alterations may affect smoking-mediated inflammatory responses.

Conclusion

The recognition of the molecular mechanisms of the epigenetic changes in abnormal inflammation is expected to contribute to the understanding of the pathophysiology of CS-related diseases such that novel epigenetic therapies may be identified in the near future.

Evidence of epigenetic alterations in thrombosis and coagulation: A systematic review

Thrombosis in the context of Cardiovascular disease (CVD) affects mainly the blood vessels supplying the heart, brain and peripheries and it is the leading cause of death worldwide. The pathophysiological thrombotic mechanisms are largely unknown. Heritability contributes to a 30% of the incidence of CVD. The remaining variation can be explained by life style factors such as smoking, dietary and exercise habits, environmental exposure to toxins, and drug usage and other comorbidities. Epigenetic variation can be acquired or inherited and constitutes an interaction between genes and the environment. Epigenetics have been implicated in atherosclerosis, ischemia/reperfusion damage and the cardiovascular response to hypoxia. Epigenetic regulators of gene expression are mainly the methylation of CpG islands, histone post translational modifications (PTMs) and microRNAs (miRNAs). These epigenetic regulators control gene expression either through activation or silencing. Epigenetic control is mostly dynamic and can potentially be manipulated to prevent or reverse the uncontrolled expression of genes, a trait that renders them putative therapeutic targets. In the current review, we systematically studied and present available data on epigenetic alterations implicated in thrombosis derived from human studies. Evidence of epigenetic alterations is observed in several thrombotic diseases such as Coronary Artery Disease and Cerebrovascular Disease, Preeclampsia and Antiphospholipid Syndrome. Differential CpG methylation and specific histone PTMs that control transcription of prothrombotic and proinflammatory genes have also been associated with predisposing factors of thrombosis and CVD, such us smoking, air pollution, hypertriglyceridemia, occupational exposure to particulate matter and comorbidities including cancer, Chronic Obstructive Pulmonary Disease and Chronic Kidney Disease. These clinical observations are further supported by in vitro experiments and indicate that epigenetic regulation affects the pathophysiology of thrombotic disorders with potential diagnostic or therapeutic utility.

Epigenetics and Inflammatory Markers: A Systematic Review of the Current Evidence

Epigenetic mechanisms have been suggested to play a role in the genetic regulation of pathways related to inflammation. Therefore, we aimed to systematically review studies investigating the association between DNA methylation and histone modifications with circulatory inflammation markers in blood. Five bibliographic databases were screened until 21 November of 2017. We included studies conducted on humans that examined the association between epigenetic marks (DNA methylation and/or histone modifications) and a comprehensive list of inflammatory markers. Of the 3,759 identified references, 24 articles were included, involving, 17,399 individuals. There was suggestive evidence for global hypomethylation but better-quality studies in the future have to confirm this. Epigenome-wide association studies (EWAS) (n=7) reported most of the identified differentially methylated genes to be hypomethylated in inflammatory processes. Candidate genes studies reported 18 differentially methylated genes related to several circulatory inflammation markers. There was no overlap in the methylated sites investigated in candidate gene studies and EWAS, except for TMEM49, which was found to be hypomethylated with higher inflammatory markers in both types of studies. The relation between histone modifications and inflammatory markers was assessed by one study only. This review supports an association between epigenetic marks and inflammation, suggesting hypomethylation of the genome. Important gaps in the quality of studies were reported such as inadequate sample size, lack of adjustment for relevant confounders, and failure to replicate the findings. While most of the studies have been focused on C-reactive protein, further efforts should investigate other inflammatory markers.

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.

Making Sense of the Epigenome Using Data Integration Approaches

Epigenetic research involves examining the mitotically heritable processes that regulate gene expression, independent of changes in the DNA sequence. Recent technical advances such as whole-genome bisulfite sequencing and affordable epigenomic array-based technologies, allow researchers to measure epigenetic profiles of large cohorts at a genome-wide level, generating comprehensive high-dimensional datasets that may contain important information for disease development and treatment opportunities. The epigenomic profile for a certain disease is often a result of the complex interplay between multiple genetic and environmental factors, which poses an enormous challenge to visualize and interpret these data. Furthermore, due to the dynamic nature of the epigenome, it is critical to determine causal relationships from the many correlated associations. In this review we provide an overview of recent data analysis approaches to integrate various omics layers to understand epigenetic mechanisms of complex diseases, such as obesity and cancer. We discuss the following topics: (i) advantages and limitations of major epigenetic profiling techniques, (ii) resources for standardization, annotation and harmonization of epigenetic data, and (iii) statistical methods and machine learning methods for establishing data-driven hypotheses of key regulatory mechanisms. Finally, we discuss the future directions for data integration that shall facilitate the discovery of epigenetic-based biomarkers and therapies.

Machine learning selected smoking-associated DNA methylation signatures that predict HIV prognosis and mortality

Background

The effects of tobacco smoking on epigenome-wide methylation signatures in white blood cells (WBCs) collected from persons living with HIV may have important implications for their immune-related outcomes, including frailty and mortality. The application of a machine learning approach to the analysis of CpG methylation in the epigenome enables the selection of phenotypically relevant features from high-dimensional data. Using this approach, we now report that a set of smoking-associated DNA-methylated CpGs predicts HIV prognosis and mortality in an HIV-positive veteran population.

Results

We first identified 137 epigenome-wide significant CpGs for smoking in WBCs from 1137 HIV-positive individuals (p < 1.70E−07). To examine whether smoking-associated CpGs were predictive of HIV frailty and mortality, we applied ensemble-based machine learning to build a model in a training sample employing 408,583 CpGs. A set of 698 CpGs was selected and predictive of high HIV frailty in a testing sample [(area under curve (AUC) = 0.73, 95%CI 0.63~0.83)] and was replicated in an independent sample [(AUC = 0.78, 95%CI 0.73~0.83)]. We further found an association of a DNA methylation index constructed from the 698 CpGs that were associated with a 5-year survival rate [HR = 1.46; 95%CI 1.06~2.02, p = 0.02]. Interestingly, the 698 CpGs located on 445 genes were enriched on the integrin signaling pathway (p = 9.55E−05, false discovery rate = 0.036), which is responsible for the regulation of the cell cycle, differentiation, and adhesion.

Conclusion

We demonstrated that smoking-associated DNA methylation features in white blood cells predict HIV infection-related clinical outcomes in a population living with HIV.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0591-z) contains supplementary material, which is available to authorized users.

Causal effect of smoking on DNA methylation in peripheral blood: a twin and family study

Background

Smoking has been reported to be associated with peripheral blood DNA methylation, but the causal aspects of the association have rarely been investigated. We aimed to investigate the association and underlying causation between smoking and blood methylation.

Methods

The methylation profile of DNA from the peripheral blood, collected as dried blood spots stored on Guthrie cards, was measured for 479 Australian women including 66 monozygotic twin pairs, 66 dizygotic twin pairs, and 215 sisters of twins from 130 twin families using the Infinium HumanMethylation450K BeadChip array. Linear regression was used to estimate associations between methylation at ~ 410,000 cytosine-guanine dinucleotides (CpGs) and smoking status. A regression-based methodology for twins, Inference about Causation through Examination of Familial Confounding (ICE FALCON), was used to assess putative causation.

Results

At a 5% false discovery rate, 39 CpGs located at 27 loci, including previously reported AHRR, F2RL3, 2q37.1 and 6p21.33, were found to be differentially methylated across never, former and current smokers. For all 39 CpG sites, current smokers had the lowest methylation level. Our study provides the first replication for two previously reported CpG sites, cg06226150 (SLC2A4RG) and cg21733098 (12q24.32). From the ICE FALCON analysis with smoking status as the predictor and methylation score as the outcome, a woman’s methylation score was associated with her co-twin’s smoking status, and the association attenuated towards the null conditioning on her own smoking status, consistent with smoking status causing changes in methylation. To the contrary, using methylation score as the predictor and smoking status as the outcome, a woman’s smoking status was not associated with her co-twin’s methylation score, consistent with changes in methylation not causing smoking status.

Conclusions

For middle-aged women, peripheral blood DNA methylation at several genomic locations is associated with smoking. Our study suggests that smoking has a causal effect on peripheral blood DNA methylation, but not vice versa.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0452-9) contains supplementary material, which is available to authorized users.