Tobacco smoking is associated with methylation of genes related to coronary artery disease

An update on the cell-free DNA-derived methylome as a non-invasive biomarker for coronary artery disease

Cardiovascular diseases are the foremost contributor to global mortality, presenting a complex etiology and an expanding array of risk factors. Coronary artery disease characterized by atherosclerotic plaque build-up in the coronary arteries, imposes significant mortality and financial burdens, especially in low- and middle-income nations. The pathogenesis of coronary artery disease involves a multifaceted interplay of genetic, environmental, and epigenetic factors. Epigenetic regulation contributes to the dynamic control of gene expression without altering the underlying DNA sequence. The mounting evidence that highlights the pivotal role of epigenetic regulation in coronary artery disease development and progression, offering potential avenues for the development of novel diagnostic biomarkers and therapeutic targets. Abnormal DNA methylation patterns are linked to the modulation of gene expression involved in crucial processes like lipid metabolism, inflammation, and vascular function in the context of coronary artery disease. Cell-free DNA has become invaluable in tumor biology as a liquid biopsy, while its applications in coronary artery disease are limited, but intriguing. Atherosclerotic plaque rupture causes myocardial infarction, by depriving heart muscles of oxygen, releasing cell-free DNA from dead cardiac cells, and providing a minimally invasive source to explore tissue-specific epigenetic alterations. We discussed the methodologies for studying the global methylome and hydroxy-methylome landscape, their advantages, and limitations. It explores methylome alterations in coronary artery disease, considering risk factors and their relevance in coronary artery disease genesis. The review also details the implications of MI-derived cell-free DNA for developing minimally invasive biomarkers and associated challenges.

Atherosclerosis as the Damocles' sword of human evolution: insights from nonhuman ape-like primates, ancient human remains, and isolated modern human populations

Atherosclerosis is the leading cause of death worldwide, and the predominant risk factors are advanced age and high-circulating low-density lipoprotein cholesterol (LDL-C). However, the findings of atherosclerosis in relatively young mummified remains and a lack of atherosclerosis in chimpanzees despite high LDL-C call into question the role of traditional cardiovascular risk factors. The inflammatory theory of atherosclerosis may explain the discrepancies between traditional risk factors and observed phenomena in current literature. Following the divergence from chimpanzees several millennia ago, loss of function mutations in immune regulatory genes and changes in gene expression have resulted in an overactive human immune system. The ubiquity of atherosclerosis in the modern era may reflect a selective pressure that enhanced the innate immune response at the cost of atherogenesis and other chronic disease states. Evidence provided from the fields of genetics, evolutionary biology, and paleoanthropology demonstrates a sort of circular dependency between inflammation, immune system functioning, and evolution at both a species and cellular level. More recently, the role of proinflammatory stimuli, somatic mutations, and the gene-environment effect appear to be underappreciated elements in the development and progression of atherosclerosis. Neurobiological stress, metabolic syndrome, and traditional cardiovascular risk factors may instead function as intermediary links between inflammation and atherosclerosis. Therefore, considering evolution as a mechanistic process and atherosclerosis as part of the inertia of evolution, greater insight into future preventative and therapeutic interventions for atherosclerosis can be gained by examining the past.

Panoramic on Epigenetics in Coronary Artery Disease and the Approach of Personalized Medicine

Epigenetic modifications play a fundamental role in the progression of coronary artery disease (CAD). This panoramic review aims to provide an overview of the current understanding of the epigenetic mechanisms involved in CAD pathogenesis and highlights the potential implications for personalized medicine approaches. Epigenetics is the study of heritable changes that do not influence alterations in the DNA sequence of the genome. It has been shown that epigenetic processes, including DNA/histone methylation, acetylation, and phosphorylation, play an important role. Additionally, miRNAs, lncRNAs, and circRNAs are also involved in epigenetics, regulating gene expression patterns in response to various environmental factors and lifestyle choices. In the context of CAD, epigenetic alterations contribute to the dysregulation of genes involved in inflammation, oxidative stress, lipid metabolism, and vascular function. These epigenetic changes can occur during early developmental stages and persist throughout life, predisposing individuals to an increased risk of CAD. Furthermore, in recent years, the concept of personalized medicine has gained significant attention. Personalized medicine aims to tailor medical interventions based on an individual's unique genetic, epigenetic, environmental, and lifestyle factors. In the context of CAD, understanding the interplay between genetic variants and epigenetic modifications holds promise for the development of more precise diagnostic tools, risk stratification models, and targeted therapies. This review summarizes the current knowledge of epigenetic mechanisms in CAD and discusses the fundamental principles of personalized medicine.

Derivation and validation of an epigenetic frailty risk score in population-based cohorts of older adults

DNA methylation (DNAm) patterns in peripheral blood have been shown to be associated with aging related health outcomes. We perform an epigenome-wide screening to identify CpGs related to frailty, defined by a frailty index (FI), in a large population-based cohort of older adults from Germany, the ESTHER study. Sixty-five CpGs are identified as frailty related methylation loci. Using LASSO regression, 20 CpGs are selected to derive a DNAm based algorithm for predicting frailty, the epigenetic frailty risk score (eFRS). The eFRS exhibits strong associations with frailty at baseline and after up to five-years of follow-up independently of established frailty risk factors. These associations are confirmed in another independent population-based cohort study, the KORA-Age study, conducted in older adults. In conclusion, we identify 65 CpGs as frailty-related loci, of which 20 CpGs are used to calculate the eFRS with predictive performance for frailty over long-term follow-up.

Unlocking the potential of forensic traces: Analytical approaches to generate investigative leads

Forensic investigation involves gathering the information necessary to understand the criminal events as well as linking objects or individuals to an item, location or other individual(s) for investigative purposes. For years techniques such as presumptive chemical tests, DNA profiling or fingermark analysis have been of great value to this process. However, these techniques have their limitations, whether it is a lack of confidence in the results obtained due to cross-reactivity, subjectivity and low sensitivity; or because they are dependent on holding reference samples in a pre-existing database. There is currently a need to devise new ways to gather as much information as possible from a single trace, particularly from biological traces commonly encountered in forensic casework. This review outlines the most recent advancements in the forensic analysis of biological fluids, fingermarks and hair. Special emphasis is placed on analytical methods that can expand the information obtained from the trace beyond what is achieved in the usual practices. Special attention is paid to those methods that accurately determine the nature of the sample, as well as how long it has been at the crime scene, along with individualising information regarding the donor source of the trace.

Overview of Polyamines as Nutrients for Human Healthy Long Life and Effect of Increased Polyamine Intake on DNA Methylation

Polyamines, spermidine and spermine, are synthesized in every living cell and are therefore contained in foods, especially in those that are thought to contribute to health and longevity. They have many physiological activities similar to those of antioxidant and anti-inflammatory substances such as polyphenols. These include antioxidant and anti-inflammatory properties, cell and gene protection, and autophagy activation. We have first reported that increased polyamine intake (spermidine much more so than spermine) over a long period increased blood spermine levels and inhibited aging-associated pathologies and pro-inflammatory status in humans and mice and extended life span of mice. However, it is unlikely that the life-extending effect of polyamines is exerted by the same bioactivity as polyphenols because most studies using polyphenols and antioxidants have failed to demonstrate their life-extending effects. Recent investigations revealed that aging-associated pathologies and lifespan are closely associated with DNA methylation, a regulatory mechanism of gene expression. There is a close relationship between polyamine metabolism and DNA methylation. We have shown that the changes in polyamine metabolism affect the concentrations of substances and enzyme activities involved in DNA methylation. I consider that the increased capability of regulation of DNA methylation by spermine is a key of healthy long life of humans.

Smoking Status and Type 2 Diabetes, and Cardiovascular Disease: A Comprehensive Analysis of Shared Genetic Etiology and Causal Relationship

OBJECTIVE

This study aimed to explore shared genetic etiology and the causality between smoking status and type 2 diabetes (T2D), cardiovascular diseases (CVDs), and related metabolic traits.

METHODS

Using summary statistics from publicly available genome-wide association studies (GWASs), we estimated genetic correlations between smoking status and T2D, 6 major CVDs, and 8 related metabolic traits with linkage disequilibrium score regression (LDSC) analysis; identified shared genetic loci with large-scale genome-wide cross-trait meta-analysis; explored potential shared biological mechanisms with a series of post-GWAS analyses; and determined causality with Mendelian randomization (MR).

RESULTS

We found significant positive genetic associations with smoking status for T2D (Rg = 0.170, p = 9.39 × 10^-22), coronary artery disease (CAD) (Rg = 0.234, p = 1.96 × 10^-27), myocardial infarction (MI) (Rg = 0.226, p = 1.08 × 10^-17), and heart failure (HF) (Rg = 0.276, p = 8.43 × 10^-20). Cross-trait meta-analysis and transcriptome-wide association analysis of smoking status identified 210 loci (32 novel loci) and 354 gene-tissue pairs jointly associated with T2D, 63 loci (12 novel loci) and 37 gene-tissue pairs with CAD, 38 loci (6 novel loci) and 17 gene-tissue pairs with MI, and 28 loci (3 novel loci) and one gene-tissue pair with HF. The shared loci were enriched in the exo-/endocrine, cardiovascular, nervous, digestive, and genital systems. Furthermore, we observed that smoking status was causally related to a higher risk of T2D (β = 0.385, p = 3.31 × 10^-3), CAD (β = 0.670, p = 7.86 × 10^-11), MI (β = 0.725, p = 2.32 × 10^-9), and HF (β = 0.520, p = 1.53 × 10^-6).

CONCLUSIONS

Our findings provide strong evidence on shared genetic etiology and causal associations between smoking status and T2D, CAD, MI, and HF, underscoring the potential shared biological mechanisms underlying the link between smoking and T2D and CVDs. This work opens up a new way of more effective and timely prevention of smoking-related T2D and CVDs.

Human beta-defensin-1 rs2738047 polymorphism is associated with shisha smoking risk among Saudi population

Human β-defensin (HBD), a member of the antimicrobial peptides, is essential for respiratory epithelial cells' microbial defense, and is affected by cigarette smoking (CS). Its expression is upregulated by stimulation from microbes or inflammation. Genetic polymorphisms in the HBD-1 gene have been implicated in the development of various smoking-related diseases, including chronic obstructive pulmonary disease and asthma. Thus, we sought to analyze possible associations between HBD-1 single-nucleotide polymorphism (SNP) in HBD-1 gene and CS in ethnic Saudi Arabian subjects. Variants rs1047031 (C/T), rs1799946 (C/T), rs2738047 (C/T), and rs11362 (C/T) were investigated by genotyping 575 blood specimens from males and females, smokers/non-smokers: 288/287. The CT and CT+TT genotypes of rs1799946 presented an ~5-fold increased correlation with CS among the female smokers, compared with the female controls (OR = 5.473, P = 0.02003; and OR = 5.211, P = 0.02028, respectively), an observation similar to rs11362 SNP in female smokers, but with protective effects in TT genotype, compared with the CC reference allele (OR = 0.143, P = 0.04368). In shisha smokers, the heterozygous CT and the CT/TT genotype of rs2738047 polymorphism showed the same results with ~3-fold increased correlation with CS (OR = 2.788; P = 0.03448), compared with the cigarette smokers category. No significant association was shown in genotypic distributions and allelic frequencies of rs1047031. Further investigations, including large study samples, are required to investigate the effects of shisha on human beta-defensin expression and protein levels.

The epigenetic etiology of cardiovascular disease in a longitudinal Swedish twin study

BACKGROUND

Studies on DNA methylation have the potential to discover mechanisms of cardiovascular disease (CVD) risk. However, the role of DNA methylation in CVD etiology remains unclear.

RESULTS

We performed an epigenome-wide association study (EWAS) on CVD in a longitudinal sample of Swedish twins (535 individuals). We selected CpGs reaching the Bonferroni-corrected significance level (2 [Formula: see text] 10-7) or the top-ranked 20 CpGs with the lowest P values if they did not reach this significance level in EWAS analysis associated with non-stroke CVD, overall stroke, and ischemic stroke, respectively. We further applied a bivariate autoregressive latent trajectory model with structured residuals (ALT-SR) to evaluate the cross-lagged effect between DNA methylation of these CpGs and cardiometabolic traits (blood lipids, blood pressure, and body mass index). Furthermore, mediation analysis was performed to evaluate whether the cross-lagged effects had causal impacts on CVD. In the EWAS models, none of the CpGs we selected reached the Bonferroni-corrected significance level. The ALT-SR model showed that DNA methylation levels were more likely to predict the subsequent level of cardiometabolic traits rather than the other way around (numbers of significant cross-lagged paths of methylation → trait/trait → methylation were 84/4, 45/6, 66/1 for the identified three CpG sets, respectively). Finally, we demonstrated significant indirect effects from DNA methylation on CVD mediated by cardiometabolic traits.

CONCLUSIONS

We present evidence for a directional association from DNA methylation on cardiometabolic traits and CVD, rather than the opposite, highlighting the role of epigenetics in CVD development.

Convergence of biomarkers and risk factor trait loci of coronary artery disease at 3p21.31 and HLA region

Here we seek to identify molecular biomarkers that mediate the effect of risk factors on coronary artery disease (CAD). We perform a SNP-based multiomics data analysis to find biomarkers (probes) causally associated with the risk of CAD within known genomic loci for its risk factors. We identify 78 biomarkers, the majority (64%) of which are methylation probes. We detect the convergence of several CNS and lifestyle trait loci and their biomarkers at the 3p21.31 and human leukocyte antigen (HLA) regions. The 3p21.31 locus was the most populated region in the convergence of biomarkers and risk factors. In this region, we noted as the BSN gene becomes methylated the level of stomatin (STOM) in blood increases and this contributes to higher risk of CAD. In the HLA locus, we identify several methylation biomarkers associated with various CAD risk factors. SNPs in the CFB gene display a trans-regulatory impact on the GRIA4 protein level. A methylation site upstream of the APOE gene is associated with a higher protein level of S100A13 which in turn leads to higher LDL-C and greater CAD risk. We find UHRF1BP1 and ILRUN mediate the effect of obesity on CAD whereas methylation sites within NOS3 and CKM mediate the effect of their associated-risk factors on CAD. This study provides further insight into the biology of CAD and identifies a list of biomarkers that mediate the impact of risk factors on CAD. A SNP-based initiative can unite data from various fields of omics into a single network of knowledge.

Effect of ABCA1 promoter methylation on premature coronary artery disease and its relationship with inflammation

BACKGROUND

ATP-binding cassette transporter A1 (ABCA1) plays a major role in high-density lipoprotein (HDL) metabolism and reverse cholesterol transport (RCT) and exerts anti-inflammatory effects. Increased ABCA1 promoter methylation level may result in the progression of coronary artery disease. Thus, the present study investigated the association between promoter methylation status of ABCA1 and inflammation in the development of premature coronary artery disease (pCAD).

METHODS

PCAD patients and healthy individuals (n = 90 each) were recruited from the Characteristic Medical Center of the Chinese People's Armed Police Force from June to December 2019. Using pyrosequencing, the levels of ABCA1 promoter methylation in their blood samples were evaluated. Serum concentrations of lipids, interleukin 1β (IL-1β), C-reactive protein (CRP), and circulating free DNA/Neutrophil extracellular traps (cfDNA/NETs) were also routinely measured and compared between the two groups. P values < 0.05 were considered statistically significant.

RESULTS

The mean ABCA1 promoter methylation levels were significantly higher in the pCAD group than in the control group (44.24% ± 3.66 vs. 36.05% ± 2.99, P < 0.001). Based on binary logistic regression analysis, ABCA1 promoter methylation level was identified as an independent risk factor for pCAD development (odds ratio = 2.878, 95% confidence interval: 1.802-4.594, P < 0.001). Furthermore, ABCA1 promoter methylation levels were negatively correlated with HDL levels (r =  - 0.488, P < 0.001) and positively correlated with the levels of CRP, cfDNA/NETs, and IL-1β (r = 0.389, 0.404, 0.385, respectively; P < 0.001). Multiple regression analysis showed that the serum levels of CRP, IL-1β, and cfDNA/NETs independently affect ABCA1 promoter methylation.

CONCLUSIONS

Our findings indicate that high methylation levels at the ABCA1 promoter are associated with low HDL cholesterol levels and an increased risk of pCAD. Inflammatory factors and NETs may be involved in the progression of pCAD by affecting ABCA1 promoter methylation levels.

Elucidation of Epigenetic Landscape in Coronary Artery Disease: A Review on Basic Concept to Personalized Medicine

Despite extensive clinical research and management protocols applied in the field of coronary artery diseases (CAD), it still holds the number 1 position in mortality worldwide. This indicates that we need to work on precision medicine to discover the diagnostic, therapeutic, and prognostic targets to improve the outcome of CAD. In precision medicine, epigenetic changes play a vital role in disease onset and progression. Epigenetics is the study of heritable changes that do not affect the alterations of DNA sequence in the genome. It comprises various covalent modifications that occur in DNA or histone proteins affecting the spatial arrangement of the DNA and histones. These multiple modifications include DNA/histone methylation, acetylation, phosphorylation, and SUMOylation. Besides these covalent modifications, non-coding RNAs-viz. miRNA, lncRNA, and circRNA are also involved in epigenetics. Smoking, alcohol, diet, environmental pollutants, obesity, and lifestyle are some of the prime factors affecting epigenetic alterations. Novel molecular techniques such as next-generation sequencing, chromatin immunoprecipitation, and mass spectrometry have been developed to identify important cross points in the epigenetic web in relation to various diseases. The studies regarding exploration of epigenetics, have led researchers to identify multiple diagnostic markers and therapeutic targets that are being used in different disease diagnosis and management. Here in this review, we will discuss various ground-breaking contributions of past and recent studies in the epigenetic field in concert with coronary artery diseases. Future prospects of epigenetics and its implication in CAD personalized medicine will also be discussed in brief.

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.

Integrated genomics analysis highlights important SNPs and genes implicated in moderate-to-severe asthma based on GWAS and eQTL datasets

Background

Severe asthma is a chronic disease contributing to disproportionate disease morbidity and mortality. From the year of 2007, many genome-wide association studies (GWAS) have documented a large number of asthma-associated genetic variants and related genes. Nevertheless, the molecular mechanism of these identified variants involved in asthma or severe asthma risk remains largely unknown.

Methods

In the current study, we systematically integrated 3 independent expression quantitative trait loci (eQTL) data (N = 1977) and a large-scale GWAS summary data of moderate-to-severe asthma (N = 30,810) by using the Sherlock Bayesian analysis to identify whether expression-related variants contribute risk to severe asthma. Furthermore, we performed various bioinformatics analyses, including pathway enrichment analysis, PPI network enrichment analysis, in silico permutation analysis, DEG analysis and co-expression analysis, to prioritize important genes associated with severe asthma.

Results

In the discovery stage, we identified 1129 significant genes associated with moderate-to-severe asthma by using the Sherlock Bayesian analysis. Two hundred twenty-eight genes were prominently replicated by using MAGMA gene-based analysis. These 228 replicated genes were enriched in 17 biological pathways including antigen processing and presentation (Corrected P = 4.30 × 10^− 6), type I diabetes mellitus (Corrected P = 7.09 × 10^− 5), and asthma (Corrected P = 1.72 × 10^− 3). With the use of a series of bioinformatics analyses, we highlighted 11 important genes such as GNGT2, TLR6, and TTC19 as authentic risk genes associated with moderate-to-severe/severe asthma. With respect to GNGT2, there were 3 eSNPs of rs17637472 (P_eQTL = 2.98 × 10^− 8 and P_GWAS = 3.40 × 10^− 8), rs11265180 (P_eQTL = 6.0 × 10^− 6 and P_GWAS = 1.99 × 10^− 3), and rs1867087 (P_eQTL = 1.0 × 10^− 4 and P_GWAS = 1.84 × 10^− 5) identified. In addition, GNGT2 is significantly expressed in severe asthma compared with mild-moderate asthma (P = 0.045), and Gngt2 shows significantly distinct expression patterns between vehicle and various glucocorticoids (Anova P = 1.55 × 10^− 6).

Conclusions

Our current study provides multiple lines of evidence to support that these 11 identified genes as important candidates implicated in the pathogenesis of severe asthma.

Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10-8 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10-8) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10-3) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.

Multiomics Screening Identifies Molecular Biomarkers Causally Associated With the Risk of Coronary Artery Disease

BACKGROUND

In this study, we aimed to investigate functional mechanisms underlying coronary artery disease (CAD) loci and find molecular biomarkers for CAD.

METHODS

We devised a multiomics data analysis approach based on Mendelian randomization and utilized it to search for molecular biomarkers causally associated with the risk of CAD within genomic regions known to be associated with CAD.

RESULTS

Through our CAD-centered multiomics data analysis approach, we identified 33 molecular biomarkers (probes) that were causally associated with the risk of CAD. The majority of these (N=19) were methylation probes; moreover, methylation was often behind the causal effect of expression/protein probes. We identified a number of novel loci that have a causal impact on CAD including C5orf38, SF3A3, DHX36, and MRPL33. Furthermore, by integrating the risk factors of CAD in our analysis, we were able to investigate the clinical pathways whereby several of our probes exert their effect. We found that the SELE protein level in the blood is under the trans-regulatory impact of methylation sites within the ABO gene and that SELE exerts its effect on CAD through immune, glycemic, and lipid metabolism, making it a candidate of interest for therapeutic interventions. We found the methylation site, cg05126514 within the BSN gene exert its effect on CAD through central nervous system-lifestyle risk factors. Finally, genes with a transcriptional regulatory role (SF3A3, ILF3, and N4BP2L2) exert their effect on CAD through height.

CONCLUSIONS

We demonstrate that multiomics data analysis is a powerful approach to unravel the functional mechanisms underlying CAD loci and to identify novel molecular biomarkers. Our results indicate epigenetic modifications are important in the pathogenesis of CAD and identifying and targeting these sites is of potential therapeutic interest to address the detrimental effects of both environmental and genetic factors.

Cadmium, Smoking, and Human Blood DNA Methylation Profiles in Adults from the Strong Heart Study

BACKGROUND

The epigenetic effects of individual environmental toxicants in tobacco remain largely unexplored. Cadmium (Cd) has been associated with smoking-related health effects, and its concentration in tobacco smoke is higher in comparison with other metals.

OBJECTIVES

We studied the association of Cd and smoking exposures with human blood DNA methylation (DNAm) profiles. We also evaluated the implication of findings to relevant methylation pathways and the potential contribution of Cd exposure from smoking to explain the association between smoking and site-specific DNAm.

METHODS

We conducted an epigenome-wide association study of urine Cd and self-reported smoking (current and former vs. never, and cumulative smoking dose) with blood DNAm in 790,026 CpGs (methylation sites) measured with the Illumina Infinium Human MethylationEPIC (Illumina Inc.) platform in 2,325 adults 45-74 years of age who participated in the Strong Heart Study in 1989-1991. In a mediation analysis, we estimated the amount of change in DNAm associated with smoking that can be independently attributed to increases in urine Cd concentrations from smoking. We also conducted enrichment analyses and in silico protein-protein interaction networks to explore the biological relevance of the findings.

RESULTS

At a false discovery rate (FDR)-corrected level of 0.05, we found 6 differentially methylated positions (DMPs) for Cd; 288 and 17, respectively, for current and former smoking status; and 77 for cigarette pack-years. Enrichment analyses of these DMPs displayed enrichment of 58 and 6 Gene Ontology and Kyoto Encyclopedia of Genes and Genomes gene sets, respectively, including biological pathways for cancer and cardiovascular disease. In in silico protein-to-protein networks, we observed key proteins in DNAm pathways directly and indirectly connected to Cd- and smoking-DMPs. Among DMPs that were significant for both Cd and current smoking (annotated to PRSS23, AHRR, F2RL3, RARA, and 2q37.1), we found statistically significant contributions of Cd to smoking-related DNAm.

CONCLUSIONS

Beyond replicating well-known smoking epigenetic signatures, we found novel DMPs related to smoking. Moreover, increases in smoking-related Cd exposure were associated with differential DNAm. Our integrative analysis supports a biological link for Cd and smoking-associated health effects, including the possibility that Cd is partly responsible for smoking toxicity through epigenetic changes. https://doi.org/10.1289/EHP6345.

5-Aza-2'-deoxycytidine advances the epithelial-mesenchymal transition of breast cancer cells by demethylating Sipa1 promoter-proximal elements

Human breast cancer cells exhibit considerable diversity in the methylation status of genomic DNA CpGs that regulate metastatic transcriptome networks. In this study, we identified human Sipa1 promoter-proximal elements that contained a CpG island and demonstrated that the methylation status of the CpG island was inversely correlated with SIPA1 protein expression in cancer cells. 5-Aza-2′-deoxycytidine (5-Aza-CdR), a DNA methyltransferase inhibitor, promoted the expression of Sipa1 in the MCF7 breast cancer cells with a low level of SIPA1 expression. On the contrary, in MDA-MB-231 breast cancer cells with high SIPA1 expression levels, hypermethylation of the CpG island negatively regulated the transcription of Sipa1. In addition, the epithelial–mesenchymal transition (EMT) was reversed after knocking down Sipa1 in MDA-MB-231 cells. However, the EMT was promoted in MCF7 cells with over-expression of SIPA1 or treated with 5-Aza-CdR. Taken together, hypomethylation of the CpG island in Sipa1 promoter-proximal elements could enhance SIPA1 expression in breast cancer cells, which could facilitate EMT of cancer cells, possibly increasing a risk of cancer cell metastasis in individuals treated with 5-Aza-CdR.

Summary: Hypomethylation by 5-Aza-CdR upregulates the SIPA1 expression and promotes epithelial–mesenchymal transition in breast cancer cells, possibly increasing the risk of cancer cell metastasis.

Epigenetic Link Between Statin Therapy and Type 2 Diabetes

OBJECTIVE

To investigate the role of epigenetics in statins' diabetogenic effect comparing DNA methylation (DNAm) between statin users and nonusers in an epigenome-wide association study in blood.

RESEARCH DESIGN AND METHODS

Five cohort studies' participants (n = 8,270) were classified as statin users when they were on statin therapy at the time of DNAm assessment with Illumina 450K or EPIC array or noncurrent users otherwise. Associations of DNAm with various outcomes like incident type 2 diabetes, plasma glucose, insulin, and insulin resistance (HOMA of insulin resistance [HOMA-IR]) as well as with gene expression were investigated.

RESULTS

Discovery (n = 6,820) and replication (n = 1,450) phases associated five DNAm sites with statin use: cg17901584 (1.12 × 10-25 [DHCR24]), cg10177197 (3.94 × 10-08 [DHCR24]), cg06500161 (2.67 × 10-23 [ABCG1]), cg27243685 (6.01 × 10-09 [ABCG1]), and cg05119988 (7.26 × 10-12 [SC4MOL]). Two sites were associated with at least one glycemic trait or type 2 diabetes. Higher cg06500161 methylation was associated with higher fasting glucose, insulin, HOMA-IR, and type 2 diabetes (odds ratio 1.34 [95% CI 1.22, 1.47]). Mediation analyses suggested that ABCG1 methylation partially mediates the effect of statins on high insulin and HOMA-IR. Gene expression analyses showed that statin exposure and ABCG1 methylation were associated with ABCG1 downregulation, suggesting epigenetic regulation of ABCG1 expression. Further, outcomes insulin and HOMA-IR were significantly associated with ABCG1 expression.

CONCLUSIONS

This study sheds light on potential mechanisms linking statins with type 2 diabetes risk, providing evidence on DNAm partially mediating statins' effects on insulin traits. Further efforts shall disentangle the molecular mechanisms through which statins may induce DNAm changes, potentially leading to ABCG1 epigenetic regulation.

Metabolic reprogramming by tobacco-specific nitrosamines (TSNAs) in cancer

Metabolic reprogramming is a hallmark of cancer and the link between oncogenes activation, tumor supressors inactivation and bioenergetics modulation is well established. However, numerous carcinogenic environmental factors are responsible for early cancer initiation and their impact on metabolic reprogramming just starts to be deciphered. For instance, it was recently shown that UVB irradiation triggers metabolic reprogramming at the pre-cancer stage with implication for skin cancer detection and therapy. These observations foster the need to study the early changes in tissue metabolism following exposure to other carcinogenic events. According to the International Agency for Research on Cancer (IARC), tobacco smoke is a major class I-carcinogenic environmental factor that contains different carcinogens, but little is known on the impact of tobacco smoke on tissue metabolism and its participation to cancer initiation. In particular, tobacco-specific nitrosamines (TSNAs) play a central role in tobacco-smoke mediated cancer initiation. Here we describe the recent advances that have led to a new hypothesis regarding the link between nitrosamines signaling and metabolic reprogramming in cancer.

Epigenetic signatures of smoking associate with cognitive function, brain structure, and mental and physical health outcomes in the Lothian Birth Cohort 1936

Recent advances in genome-wide DNA methylation (DNAm) profiling for smoking behaviour have given rise to a new, molecular biomarker of smoking exposure. It is unclear whether a smoking-associated DNAm (epigenetic) score has predictive value for ageing-related health outcomes which is independent of contributions from self-reported (phenotypic) smoking measures. Blood DNA methylation levels were measured in 895 adults aged 70 years in the Lothian Birth Cohort 1936 (LBC1936) study using the Illumina 450K assay. A DNA methylation score based on 230 CpGs was used as a proxy for smoking exposure. Associations between smoking variables and health outcomes at age 70 were modelled using general linear modelling (ANCOVA) and logistic regression. Additional analyses of smoking with brain MRI measures at age 73 (n = 532) were performed. Smoking-DNAm scores were positively associated with self-reported smoking status (P < 0.001, eta-squared ɳ2 = 0.63) and smoking pack years (r = 0.69, P < 0.001). Higher smoking DNAm scores were associated with variables related to poorer cognitive function, structural brain integrity, physical health, and psychosocial health. Compared with phenotypic smoking, the methylation marker provided stronger associations with all of the cognitive function scores, especially visuospatial ability (P < 0.001, partial eta-squared ɳp2 = 0.022) and processing speed (P < 0.001, ɳp2 = 0.030); inflammatory markers (all P < 0.001, ranges from ɳp2 = 0.021 to 0.030); dietary patterns (healthy diet (P < 0.001, ɳp2 = 0.052) and traditional diet (P < 0.001, ɳp2 = 0.032); stroke (P = 0.006, OR 1.48, 95% CI 1.12, 1.96); mortality (P < 0.001, OR 1.59, 95% CI 1.42, 1.79), and at age 73; with MRI volumetric measures (all P < 0.001, ranges from ɳp2 = 0.030 to 0.052). Additionally, education was the most important life-course predictor of lifetime smoking tested. Our results suggest that a smoking-associated methylation biomarker typically explains a greater proportion of the variance in some smoking-related morbidities in older adults, than phenotypic measures of smoking exposure, with some of the accounted-for variance being independent of phenotypic smoking status.

Validated inference of smoking habits from blood with a finite DNA methylation marker set

Inferring a person’s smoking habit and history from blood is relevant for complementing or replacing self-reports in epidemiological and public health research, and for forensic applications. However, a finite DNA methylation marker set and a validated statistical model based on a large dataset are not yet available. Employing 14 epigenome-wide association studies for marker discovery, and using data from six population-based cohorts (N = 3764) for model building, we identified 13 CpGs most suitable for inferring smoking versus non-smoking status from blood with a cumulative Area Under the Curve (AUC) of 0.901. Internal fivefold cross-validation yielded an average AUC of 0.897 ± 0.137, while external model validation in an independent population-based cohort (N = 1608) achieved an AUC of 0.911. These 13 CpGs also provided accurate inference of current (average AUC_{crossvalidation} 0.925 ± 0.021, AUC_{externalvalidation}0.914), former (0.766 ± 0.023, 0.699) and never smoking (0.830 ± 0.019, 0.781) status, allowed inferring pack-years in current smokers (10 pack-years 0.800 ± 0.068, 0.796; 15 pack-years 0.767 ± 0.102, 0.752) and inferring smoking cessation time in former smokers (5 years 0.774 ± 0.024, 0.760; 10 years 0.766 ± 0.033, 0.764; 15 years 0.767 ± 0.020, 0.754). Model application to children revealed highly accurate inference of the true non-smoking status (6 years of age: accuracy 0.994, N = 355; 10 years: 0.994, N = 309), suggesting prenatal and passive smoking exposure having no impact on model applications in adults. The finite set of DNA methylation markers allow accurate inference of smoking habit, with comparable accuracy as plasma cotinine use, and smoking history from blood, which we envision becoming useful in epidemiology and public health research, and in medical and forensic applications.

TSLP and TSLP receptors variants are associated with smoking

Background

To search for new prevention markers for early detection of the diseases caused by tobacco, we aimed to investigate the polymorphisms in TSLP and TSLPRs associated with cigarette smoking in the Saudi population.

Materials and methods

Samples were collected from 177 smokers and 126 healthy controls. Three TSLP SNPs [rs3806933, rs2289276, and rs10043985], three TSLPR SNPs [rs36133495, rs36177645, and rs36139698], and two IL7R SNPs rs1053496 and rs12516866 were analyzed by genotyping.

Results

Two TSLP SNPs (rs10043985 and rs3806933) and one TSLPR SNP (rs36139698) showed significant correlations with smoking behavior, but not IL7R rs12516866 and rs1053496. rs10043985 showed a clear association with long‐term smoking regardless of daily cigarette consumption. rs2289276 was associated with short‐term smoking but not with daily cigarette consumption. rs3806933 was highly associated with different smoker subgroups. Rs36139698 was highly associated with long‐term smokers who consumed ≥20 cigarettes/day, and the “T” allele was associated only with individuals who smoked ≤20 cigarettes/day. Rs36139698 corresponds to a P195L substitution and produces a TSLPR mutant with a predicted ΔΔG increase of 2.15 kcal/mol and has a more stable structure than the wild‐type variant.

Conclusions

Investigating TSLP and TSLPR polymorphisms is crucial for elucidating the mechanisms underlying tobacco‐induced diseases.

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.

MicroRNAs and their target mRNAs as potential biomarkers among smokers and non-smokers with lung adenocarcinoma

Lung adenocarcinoma is one of the major causes of mortality. Current methods of diagnosis can be improved through identification of disease specific biomarkers. MicroRNAs are small non-coding regulators of gene expression, which can be potential biomarkers in various diseases. Thus, the main objective of this study was to gain mechanistic insights into genetic abnormalities occurring in lung adenocarcinoma by implementing an integrative analysis of miRNAs and mRNAs expression profiles in the case of both smokers and non-smokers. Differential expression was analysed by comparing publicly available lung adenocarcinoma samples with controls. Furthermore, weighted gene co-expression network analysis is performed which revealed mRNAs and miRNAs significantly correlated with lung adenocarcinoma. Moreover, an integrative analysis resulted in identification of several miRNA-mRNA pairs which were significantly dysregulated in non-smokers with lung adenocarcinoma. Also two pairs (miR-133b/Protein Kinase C Zeta (PRKCZ) and miR-557/STEAP3) were found specifically dysregulated in smokers. Pathway analysis further revealed their role in important signalling pathways including cell cycle. This analysis has not only increased the authors' understanding about lung adenocarcinoma but also proposed potential biomarkers. However, further wet laboratory studies are required for the validation of these potential biomarkers which can be used to diagnose lung adenocarcinoma.

Varinostat Alters Gene Expression Profiles in Aortic Tissues from ApoE-/- Mice

Atherosclerosis (AS) is a complex, chronic inflammatory disease that is characterized by plaque buildup within arterial vessel walls. Preclinical trials have suggested that vorinostat, a pan-histone deacetylase inhibitor (HDACi), reduces vascular inflammation and AS, but the underlying protective mechanism has not been fully elucidated. The present study aimed to identify altered gene expression profiles in aortic tissues from ApoE^-/- mice after vorinostat treatment. Male ApoE-/- mice fed a high-fat diet were treated with either vorinostat or vehicle, and the aortic plaque area was quantified 8 weeks after treatment. Aortic tissues were collected from both the vorinostat group (n = 3) and vehicle group (n = 3) for deep sequencing of the cDNA to construct sRNA libraries. Oral administration of vorinostat significantly reduced plaque size in the ApoE^-/- mice (p < 0.05). In total, 1,550 differentially expressed mRNAs, 56 differentially expressed miRNAs, and 381 differentially expressed lncRNAs were identified in the vorinostat group compared to the vehicle group. Subsequently, a global lncRNA-miRNA-mRNA triple network was constructed based on the competitive endogenous RNA (ceRNA) theory. The hepatitis C signaling pathway was significantly enriched among the differentially expressed mRNAs from the ceRNA network, which suggests that vorinostat has anti-inflammatory properties. Importantly, the identified target pair of mmu-miR-3075-5p/lncRNA-A330023F24Rik/Ldlr may regulate drug response. Upregulation of low-density lipid receptor (Ldlr) and lncRNA-A330023F24Rik and downregulation of mmu-miR-3075-5p were further verified by quantitative real-time polymerase chain reaction. To conclude, vorinostat reduced AS in ApoE^-/- mice. Differentially expressed mRNA, lncRNAs, and miRNAs, as well as their interactions and pathways, were identified, which partially explain vorinostat's anti-atherosclerotic effects.

Polyamine Metabolism and Gene Methylation in Conjunction with One-Carbon Metabolism

Recent investigations have revealed that changes in DNA methylation status play an important role in aging-associated pathologies and lifespan. The methylation of DNA is regulated by DNA methyltransferases (DNMT1, DNMT3a, and DNMT3b) in the presence of S-adenosylmethionine (SAM), which serves as a methyl group donor. Increased availability of SAM enhances DNMT activity, while its metabolites, S-adenosyl-l-homocysteine (SAH) and decarboxylated S-adenosylmethionine (dcSAM), act to inhibit DNMT activity. SAH, which is converted from SAM by adding a methyl group to cytosine residues in DNA, is an intermediate precursor of homocysteine. dcSAM, converted from SAM by the enzymatic activity of adenosylmethionine decarboxylase, provides an aminopropyl group to synthesize the polyamines spermine and spermidine. Increased homocysteine levels are a significant risk factor for the development of a wide range of conditions, including cardiovascular diseases. However, successful homocysteine-lowering treatment by vitamins (B6, B12, and folate) failed to improve these conditions. Long-term increased polyamine intake elevated blood spermine levels and inhibited aging-associated pathologies in mice and humans. Spermine reversed changes (increased dcSAM, decreased DNMT activity, aberrant DNA methylation, and proinflammatory status) induced by the inhibition of ornithine decarboxylase. The relation between polyamine metabolism, one-carbon metabolism, DNA methylation, and the biological mechanism of spermine-induced lifespan extension is discussed.

Genetic Regulatory Mechanisms of Smooth Muscle Cells Map to Coronary Artery Disease Risk Loci

Coronary artery disease (CAD) is the leading cause of death globally. Genome-wide association studies (GWASs) have identified more than 95 independent loci that influence CAD risk, most of which reside in non-coding regions of the genome. To interpret these loci, we generated transcriptome and whole-genome datasets using human coronary artery smooth muscle cells (HCASMCs) from 52 unrelated donors, as well as epigenomic datasets using ATAC-seq on a subset of 8 donors. Through systematic comparison with publicly available datasets from GTEx and ENCODE projects, we identified transcriptomic, epigenetic, and genetic regulatory mechanisms specific to HCASMCs. We assessed the relevance of HCASMCs to CAD risk using transcriptomic and epigenomic level analyses. By jointly modeling eQTL and GWAS datasets, we identified five genes (SIPA1, TCF21, SMAD3, FES, and PDGFRA) that may modulate CAD risk through HCASMCs, all of which have relevant functional roles in vascular remodeling. Comparison with GTEx data suggests that SIPA1 and PDGFRA influence CAD risk predominantly through HCASMCs, while other annotated genes may have multiple cell and tissue targets. Together, these results provide tissue-specific and mechanistic insights into the regulation of a critical vascular cell type associated with CAD in human populations.

A systematic analysis highlights multiple long non-coding RNAs associated with cardiometabolic disorders

Genome-wide association studies (GWAS) have identified many susceptibility loci for cardiometabolic disorders. Most of the associated variants reside in non-coding regions of the genome including long non-coding RNAs (lncRNAs), which are thought to play critical roles in diverse biological processes. Here, we leveraged data from the available GWAS meta-analyses on lipid and obesity-related traits, blood pressure, type 2 diabetes, and coronary artery disease and identified 179 associated single-nucleotide polymorphisms (SNPs) in 102 lncRNAs (p-value < 2.3 × 10^-7). Of these, 55 SNPs, either the lead SNP or in strong linkage disequilibrium with the lead SNP in the related loci, were selected for further investigations. Our in silico predictions and functional annotations of the SNPs as well as expression and DNA methylation analysis of their lncRNAs demonstrated several lncRNAs that fulfilled predefined criteria for being potential functional targets. In particular, we found evidence suggesting that LOC157273 (at 8p23.1) is involved in regulating serum lipid-cholesterol. Our results showed that rs4841132 in the second exon and cg17371580 in the promoter region of LOC157273 are associated with lipids; the lncRNA is expressed in liver and associates with the expression of its nearby coding gene, PPP1R3B. Collectively, we highlight a number of loci associated with cardiometabolic disorders for which the association may act through lncRNAs.

Tobacco smoking and methylation of genes related to lung cancer development

Lung cancer is a leading cause of cancer-related mortality worldwide, and cigarette smoking is the major environmental hazard for its development. This study intended to examine whether smoking could alter methylation of genes at lung cancer risk loci identified by genome-wide association studies (GWASs). By systematic literature review, we selected 75 genomic candidate regions based on 120 single-nucleotide polymorphisms (SNPs). DNA methylation levels of 2854 corresponding cytosine-phosphate-guanine (CpG) candidates in whole blood samples were measured by the Illumina Infinium Human Methylation450 Beadchip array in two independent subsamples of the ESTHER study. After correction for multiple testing, we successfully confirmed associations with smoking for one previously identified CpG site within the KLF6 gene and identified 12 novel sites located in 7 genes: STK32A, TERT, MSH5, ACTA2, GATA3, VTI1A and CHRNA5 (FDR <0.05). Current smoking was linked to a 0.74% to 2.4% decrease of DNA methylation compared to never smoking in 11 loci, and all but one showed significant associations (FDR <0.05) with life-time cumulative smoking (pack-years). In conclusion, our study demonstrates the impact of tobacco smoking on DNA methylation of lung cancer related genes, which may indicate that lung cancer susceptibility genes might be regulated by methylation changes in response to smoking. Nevertheless, this mechanism warrants further exploration in future epigenetic and biomarker studies.

Polygenic Risk Score for Coronary Heart Disease Modifies the Elevated Risk by Cigarette Smoking for Disease Incidence

BACKGROUND

Coronary heart disease (CHD) is a multifactorial disease with both genetic and environmental components. Smoking is the most important modifiable risk factor for CHD. Our aim was to test whether the increased CHD incidence by smoking is modified by genetic predisposition to CHD.

METHODS AND RESULTS

Our study included 24 443 individuals from the MDCS (Malmö Diet and Cancer Study). A weighted polygenic risk score (PRS) was created by summing the number of risk alleles for 50 single-nucleotide polymorphisms associated with CHD. Individuals were classified as current, former, or never smokers. Interactions were primarily tested between smoking status and PRS and secondarily with individual single-nucleotide polymorphisms. Then, the predictive use of PRS for CHD incidence was tested among different smoking categories. During a median follow-up time of 19.4 years, 3217 incident CHD cases were recorded. The association between smoking and CHD was modified by the PRS (P_interaction=0.005). The magnitude of increased incidence of CHD by smoking was highest among individuals in the lowest tertile of PRS (odds ratio, 1.42; 95% confidence interval, 1.29-1.56 per smoking risk category) compared with the highest tertile (odds ratio, 1.20; 95% confidence interval, 1.11-1.30 per smoking risk category). This interaction was stronger among men (P_interaction=0.001) compared with women (P_interaction=0.44). The PRS provided a significantly better net reclassification and discrimination on top of traditional risk factors among never smokers compared with current smokers (P<0.001).

CONCLUSIONS

Genetic predisposition to CHD modifies the associated increased CHD risk by smoking. The PRS has a better predictive use among never smokers compared with smokers.

From forensic epigenetics to forensic epigenomics: broadening DNA investigative intelligence

Human genetic variation is a major resource in forensics, but does not allow all forensically relevant questions to be answered. Some questions may instead be addressable via epigenomics, as the epigenome acts as an interphase between the fixed genome and the dynamic environment. We envision future forensic applications of DNA methylation analysis that will broaden DNA-based forensic intelligence. Together with genetic prediction of appearance and biogeographic ancestry, epigenomic lifestyle prediction is expected to increase the ability of police to find unknown perpetrators of crime who are not identifiable using current forensic DNA profiling.

Redundancy analysis allows improved detection of methylation changes in large genomic regions

BACKGROUND

DNA methylation is an epigenetic process that regulates gene expression. Methylation can be modified by environmental exposures and changes in the methylation patterns have been associated with diseases. Methylation microarrays measure methylation levels at more than 450,000 CpGs in a single experiment, and the most common analysis strategy is to perform a single probe analysis to find methylation probes associated with the outcome of interest. However, methylation changes usually occur at the regional level: for example, genomic structural variants can affect methylation patterns in regions up to several megabases in length. Existing DMR methods provide lists of Differentially Methylated Regions (DMRs) of up to only few kilobases in length, and cannot check if a target region is differentially methylated. Therefore, these methods are not suitable to evaluate methylation changes in large regions. To address these limitations, we developed a new DMR approach based on redundancy analysis (RDA) that assesses whether a target region is differentially methylated.

RESULTS

Using simulated and real datasets, we compared our approach to three common DMR detection methods (Bumphunter, blockFinder, and DMRcate). We found that Bumphunter underestimated methylation changes and blockFinder showed poor performance. DMRcate showed poor power in the simulated datasets and low specificity in the real data analysis. Our method showed very high performance in all simulation settings, even with small sample sizes and subtle methylation changes, while controlling type I error. Other advantages of our method are: 1) it estimates the degree of association between the DMR and the outcome; 2) it can analyze a targeted or region of interest; and 3) it can evaluate the simultaneous effects of different variables. The proposed methodology is implemented in MEAL, a Bioconductor package designed to facilitate the analysis of methylation data.

CONCLUSIONS

We propose a multivariate approach to decipher whether an outcome of interest alters the methylation pattern of a region of interest. The method is designed to analyze large target genomic regions and outperforms the three most popular methods for detecting DMRs. Our method can evaluate factors with more than two levels or the simultaneous effect of more than one continuous variable, which is not possible with the state-of-the-art methods.

Changes in DNA methylation induced by multi-walled carbon nanotube exposure in the workplace

This study was designed to assess the epigenetic alterations in blood cells, induced by occupational exposure to multi-wall carbon nanotubes (MWCNT). The study population comprised of MWCNT-exposed workers (n=24) and unexposed controls (n=43) from the same workplace. We measured global DNA methylation/hydroxymethylation levels on the 5th cytosine residues using a validated liquid chromatography tandem-mass spectrometry (LC-MS/MS) method. Sequence-specific methylation of LINE1 retrotransposable element 1 (L1RE1) elements, and promoter regions of functionally important genes associated with epigenetic regulation [DNA methyltransferase-1 (DNMT1) and histone deacetylase 4 (HDAC4)], DNA damage/repair and cell cycle pathways [nuclear protein, coactivator of histone transcription/ATM serine/threonine kinase (NPAT/ATM)], and a potential transforming growth factor beta (TGF-β) repressor [SKI proto-oncogene (SKI)] were studied using bisulfite pyrosequencing. Analysis of global DNA methylation levels and hydroxymethylation did not reveal significant difference between the MWCNT-exposed and control groups. No significant changes in Cytosine-phosphate-Guanine (CpG) site methylation were observed for the LINE1 (L1RE1) elements. Further analysis of gene-specific DNA methylation showed a significant change in methylation for DNMT1, ATM, SKI, and HDAC4 promoter CpGs in MWCNT-exposed workers. Since DNA methylation plays an important role in silencing/regulation of the genes, and many of these genes have been associated with occupational and smoking-induced diseases and cancer (risk), aberrant methylation of these genes might have a potential effect in MWCNT-exposed workers.

Association of genetic polymorphisms with erythrocyte traits: Verification of SNPs reported in a previous GWAS in a Japanese population

Erythrocyte count and volume are the commonly used hematological indices for anemia that change in various diseases. To date, however, only one study ever exists that addressed erythrocyte trait-associated single nucleotide polymorphisms (SNPs) in a Japanese population. Because that study was performed in patients with various diseases, we confirmed the reported associations in a general population. Participants in the current study were from the Shizuoka component of the Japan Multi-Institutional Collaborative Cohort Study, which included 4971 men and women aged 35 to 69years who were recruited between 2006 and 2007. We analyzed the association of seven selected SNPs with the following erythrocyte traits: red blood cell count, hemoglobin (Hb) and hematocrit (Ht) levels, mean corpuscular volume, mean corpuscular hemoglobin, and mean corpuscular hemoglobin concentration. The erythrocyte traits were regressed on a number of minor alleles of selected SNPs. Then we compared our findings with those from a genome-wide association study performed in a Japanese population. We replicated the association of ABO rs495828, PDGFRA-KIT rs218237, USP49-MED20-BSYL-CCND3 rs3218097, C6orf182-CD164 rs11966072, TERT rs2736100, and TMPRSS6 rs5756504 with erythrocyte traits in our independent Japanese population. In addition, we found a significant interaction between TERT rs2736100 and smoking habit that affected Hb and Ht levels.

Cigarette smoke induces mitochondrial metabolic reprogramming in lung cells

Cellular transformation owing to cigarette smoking is due to chronic exposure and not acute. However, systematic studies to understand the molecular alterations in lung cells due to cigarette smoke are lacking. To understand these molecular alterations induced by chronic cigarette smoke exposure, we carried out tandem mass tag (TMT) based temporal proteomic profiling of lung cells exposed to cigarette smoke for upto 12months. We identified 2620 proteins in total, of which 671 proteins were differentially expressed (1.5-fold) after 12months of exposure. Prolonged exposure of lung cells to smoke for 12months revealed dysregulation of oxidative phosphorylation and overexpression of enzymes involved in TCA cycle. In addition, we also observed overexpression of enzymes involved in glutamine metabolism, fatty acid degradation and lactate synthesis. This could possibly explain the availability of alternative source of carbon to TCA cycle apart from glycolytic pyruvate. Our data indicates that chronic exposure to cigarette smoke induces mitochondrial metabolic reprogramming in cells to support growth and survival.

From sperm to offspring: Assessing the heritable genetic consequences of paternal smoking and potential public health impacts

Individuals who smoke generally do so with the knowledge of potential consequences to their own health. What is rarely considered are the effects of smoking on their future children. The objective of this work was to review the scientific literature on the effects of paternal smoking on sperm and assess the consequences to offspring. A literature search identified over 200 studies with relevant data in humans and animal models. The available data were reviewed to assess the weight of evidence that tobacco smoke is a human germ cell mutagen and estimate effect sizes. These results were used to model the potential increase in genetic disease burden in offspring caused by paternal smoking, with specific focus on aneuploid syndromes and intellectual disability, and the socioeconomic impacts of such an effect. The review revealed strong evidence that tobacco smoking is associated with impaired male fertility, and increases in DNA damage, aneuploidies, and mutations in sperm. Studies support that these effects are heritable and adversely impact the offspring. Our model estimates that, with even a modest 25% increase in sperm mutation frequency caused by smoke-exposure, for each generation across the global population there will be millions of smoking-induced de novo mutations transmitted from fathers to offspring. Furthermore, paternal smoking is estimated to contribute to 1.3 million extra cases of aneuploid pregnancies per generation. Thus, the available evidence makes a compelling case that tobacco smoke is a human germ cell mutagen with serious public health and socio-economic implications. Increased public education should be encouraged to promote abstinence from smoking, well in advance of reproduction, to minimize the transmission of harmful mutations to the next-generation.

Epigenetics and Health Disparities

PURPOSE OF REVIEW

African Americans disproportionately suffer from leading causes of morbidity and mortality including cardiovascular disease (CVD), cancer, and preterm birth. Disparities can arise from multiple social and environmental exposures, but how the human body responds to these exposures to result in pathophysiologic states is incompletely understood.

RECENT FINDINGS

Epigenetic mechanisms, particularly DNA methylation, can be altered in response to exposures such as air pollution, psychosocial stress, and smoking. Each of these exposures has been linked to the above health states (CVD, cancer, and preterm birth) with striking racial disparities in exposure levels. DNA methylation patterns have also been shown to be associated with each of these health outcomes.

SUMMARY

Whether DNA methylation mediates exposure-disease relationships and can help explain racial disparities in health is not known. However, because many environmental and adverse social exposures disproportionately affect minorities, understanding the role that epigenetics plays in the human response to these exposures that often result in disease, is critical to reducing disparities in morbidity and mortality.

Two SNPs in the promoter region of Toll-like receptor 4 gene are not associated with smoking in Saudi Arabia

Defects in the innate immune system, particularly in Toll-like receptors (TLRs), have been reported in several cigarette smoke-promoted diseases. The aim of this study was to examine the impact of tobacco smoke on allelic frequencies of TLR4 single-nucleotide polymorphisms (SNPs) and to compare the genotypic distribution of these SNPs in a Saudi Arabian population with that in previously studied populations. DNA was extracted from 303 saliva samples collected from smokers and nonsmokers. Two transitional SNPs in the promoter region of TLR4 were selected, rs2770150 (T/C) and rs10759931 (G/A). Genotype frequencies were determined using quantitative polymerase chain reaction. Our results showed a slight effect of smoking on the distribution of rs2770150 and rs10759931. However, the differences were not significant. Thus, we conclude that the SNPs selected for this study were independent of smoking and may not be related to smoking-induced diseases.

Epigenome-wide association study (EWAS) on lipids: the Rotterdam Study

BACKGROUND

DNA methylation is a key epigenetic mechanism that is suggested to be associated with blood lipid levels. We aimed to identify CpG sites at which DNA methylation levels are associated with blood levels of triglycerides, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and total cholesterol in 725 participants of the Rotterdam Study, a population-based cohort study. Subsequently, we sought replication in a non-overlapping set of 760 participants.

RESULTS

Genome-wide methylation levels were measured in whole blood using the Illumina Methylation 450 array. Associations between lipid levels and DNA methylation beta values were examined using linear mixed-effect models. All models were adjusted for sex, age, smoking, white blood cell proportions, array number, and position on array. A Bonferroni-corrected p value lower than 1.08 × 10^-7 was considered statistically significant. Five CpG sites annotated to genes including DHCR24, CPT1A, ABCG1, and SREBF1 were identified and replicated. Four CpG sites were associated with triglycerides, including CpG sites annotated to CPT1A (cg00574958 and cg17058475), ABCG1 (cg06500161), and SREBF1 (cg11024682). Two CpG sites were associated with HDL-C, including ABCG1 (cg06500161) and DHCR24 (cg17901584). No significant associations were observed with LDL-C or total cholesterol.

CONCLUSIONS

We report an association of HDL-C levels with methylation of a CpG site near DHCR24, a protein-coding gene involved in cholesterol biosynthesis, which has previously been reported to be associated with other metabolic traits. Furthermore, we confirmed previously reported associations of methylation of CpG sites within CPT1A, ABCG1, and SREBF1 and lipids. These results provide insight in the mechanisms that are involved in lipid metabolism.

Effects of a parental exposure to diuron on Pacific oyster spat methylome

Environmental epigenetic is an emerging field that studies the cause-effect relationship between environmental factors and heritable trait via an alteration in epigenetic marks. This field has received much attentions since the impact of environmental factors on different epigenetic marks have been shown to be associated with a broad range of phenotypic disorders in natural ecosystems. Chemical pollutants have been shown to affect immediate epigenetic information carriers of several aquatic species but the heritability of the chromatin marks and the consequences for long term adaptation remain open questions. In this work, we investigated the impact of the diuron herbicide on the DNA methylation pattern of spat from exposed Crassotrea gigas genitors. This oyster is one of the most important mollusk species produced worldwide and a key coastal economic resource in France. The whole genome bisulfite sequencing (WGBS, BS-Seq) was applied to obtain a methylome at single nucleotide resolution on DNA extracted from spat issued from diuron exposed genitors comparatively to control spat. We showed that the parental diuron exposure has an impact on the DNA methylation pattern of its progeny. Most of the differentially methylated regions occurred within coding sequences and we showed that this change in methylation level correlates with RNA level only in a very small group of genes. Although the DNA methylation profile is variable between individuals, we showed conserved DNA methylation patterns in response to parental diuron exposure. This relevant result opens perspectives for the setting of new markers based on epimutations as early indicators of marine pollutions.

Effect of smoking on the genetic makeup of toll-like receptors 2 and 6

Background

Cigarette smoking is a major risk factor for lung cancer, asthma, and oral cancer, and is central to the altered innate immune responsiveness to infection. Many hypotheses have provided evidence that cigarette smoking induces more genetic changes in genes involved in the development of many cigarette-related diseases. This alteration may be from single-nucleotide polymorphisms (SNPs) in innate immunity genes, especially the toll-like receptors (TLRs).

Objective

In this study, the genotype frequencies of TLR2 and TLR6 in smoking and nonsmoking population were examined.

Methods

Saliva samples were collected from 177 smokers and 126 nonsmokers. The SNPs used were rs3804100 (1350 T/C, Ser450Ser) and rs3804099 (597 T/C, Asn199Asn) for TLR2 and rs3796508 (979 G/A, Val327Met) and rs5743810 (745 T/C, Ser249Pro) for TLR6.

Results

Results showed that TLR2 rs3804100 has a significant effect in short-term smokers (OR =2.63; P=0.04), and this effect is not observed in long-term smokers (>5 years of smoking). Therefore, this early mutation may be repaired by the DNA repair system. For TLR2 rs3804099, the variation in genotype frequencies between the smokers and control patients was due to a late mutation, and its protective role appears only in long-term smokers (OR =0.40, P=0.018). In TLR6 rs5743810, the TT genotype is significantly higher in smokers than in nonsmokers (OR =6.90). The effect of this SNP is observed in long-term smokers, regardless of the smoking regime per day.

Conclusion

TLR2 (rs3804100 and rs3804099) and TLR6 (rs5743810) can be used as a potential index in the diagnosis and prevention of more diseases caused by smoking.

Tobacco smoking is associated with DNA methylation of diabetes susceptibility genes

AIMS/HYPOTHESIS

Tobacco smoking, a risk factor for diabetes, is an established modifier of DNA methylation. We hypothesised that tobacco smoking modifies DNA methylation of genes previously identified for diabetes.

METHODS

We annotated CpG sites available on the Illumina Human Methylation 450K array to diabetes genes previously identified by genome-wide association studies (GWAS), and investigated them for an association with smoking by comparing current to never smokers. The discovery study consisted of 630 individuals (Bonferroni-corrected p = 1.4 × 10(-5)), and we sought replication in an independent sample of 674 individuals. The replicated sites were tested for association with nearby genetic variants and gene expression and fasting glucose and insulin levels.

RESULTS

We annotated 3,620 CpG sites to the genes identified in the GWAS on type 2 diabetes. Comparing current smokers to never smokers, we found 12 differentially methylated CpG sites, of which five replicated: cg23161492 within ANPEP (p = 1.3 × 10(-12)); cg26963277 (p = 1.2 × 10(-9)), cg01744331 (p = 8.0 × 10(-6)) and cg16556677 (p = 1.2 × 10(-5)) within KCNQ1 and cg03450842 (p = 3.1 × 10(-8)) within ZMIZ1. The effect of smoking on DNA methylation at the replicated CpG sites attenuated after smoking cessation. Increased DNA methylation at cg23161492 was associated with decreased gene expression levels of ANPEP (p = 8.9 × 10(-5)). rs231356-T, which was associated with hypomethylation of cg26963277 (KCNQ1), was associated with a higher odds of diabetes (OR 1.06, p = 1.3 × 10(-5)). Additionally, hypomethylation of cg26963277 was associated with lower fasting insulin levels (p = 0.04).

CONCLUSIONS/INTERPRETATION

Tobacco smoking is associated with differential DNA methylation of the diabetes risk genes ANPEP, KCNQ1 and ZMIZ1. Our study highlights potential biological mechanisms connecting tobacco smoking to excess risk of type 2 diabetes.

Epigenetics of Aging

The best-known phenomenon exemplifying epigenetic drift (the alteration of epigenetic patterns during aging) is the gradual decrease of global DNA methylation. Aging cells, different tissue types, as well as a variety of human diseases possess their own distinct DNA methylation profiles, although the functional impact of these is not always clear. DNA methylation appears to be a dynamic tool of transcriptional regulation, with an extra layer of complexity due to the recent discovery of the conversion of 5-methylcytosine into 5-hydroxymethylcytosine. This age-related DNA demethylation is associated with changes in histone modification patterns and, furthermore, we now know that ncRNAs have evolved in eukaryotes as epigenetic regulators of gene expression. In this review, we will discuss current knowledge on how all these epigenetic phenomena are implicated in human aging, and their links with external, internal and stochastic factors which can affect human age-related diseases onset.

Epigenetic Mechanisms of the Aging Human Retina

Degenerative retinal diseases, such as glaucoma, age-related macular degeneration, and diabetic retinopathy, have complex etiologies with environmental, genetic, and epigenetic contributions to disease pathology. Much effort has gone into elucidating both the genetic and the environmental risk factors for these retinal diseases. However, little is known about how these genetic and environmental risk factors bring about molecular changes that lead to pathology. Epigenetic mechanisms have received extensive attention of late for their promise of bridging the gap between environmental exposures and disease development via their influence on gene expression. Recent studies have identified epigenetic changes that associate with the incidence and/or progression of each of these retinal diseases. Therefore, these epigenetic modifications may be involved in the underlying pathological mechanisms leading to blindness. Further genome-wide epigenetic studies that incorporate well-characterized tissue samples, consider challenges similar to those relevant to gene expression studies, and combine the genome-wide epigenetic data with genome-wide genetic and expression data to identify additional potentially causative agents of disease are needed. Such studies will allow researchers to create much-needed therapeutics to prevent and/or intervene in disease progression. Improved therapeutics will greatly enhance the quality of life and reduce the burden of disease management for millions of patients living with these potentially blinding conditions.

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.