Tobacco smoking is associated with DNA methylation of diabetes susceptibility genes

Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data

Integrating multi-omics data into predictive models has the potential to enhance accuracy, which is essential for precision medicine. In this study, we developed interpretable predictive models for multi-omics data by employing neural networks informed by prior biological knowledge, referred to as visible networks. These neural networks offer insights into the decision-making process and can unveil novel perspectives on the underlying biological mechanisms associated with traits and complex diseases. We tested the performance, interpretability and generalizability for inferring smoking status, subject age and LDL levels using genome-wide RNA expression and CpG methylation data from the blood of the BIOS consortium (four population cohorts, Ntotal = 2940). In a cohort-wise cross-validation setting, the consistency of the diagnostic performance and interpretation was assessed. Performance was consistently high for predicting smoking status with an overall mean AUC of 0.95 (95% CI: 0.90-1.00) and interpretation revealed the involvement of well-replicated genes such as AHRR, GPR15 and LRRN3. LDL-level predictions were only generalized in a single cohort with an R2 of 0.07 (95% CI: 0.05-0.08). Age was inferred with a mean error of 5.16 (95% CI: 3.97-6.35) years with the genes COL11A2, AFAP1, OTUD7A, PTPRN2, ADARB2 and CD34 consistently predictive. For both regression tasks, we found that using multi-omics networks improved performance, stability and generalizability compared to interpretable single omic networks. We believe that visible neural networks have great potential for multi-omics analysis; they combine multi-omic data elegantly, are interpretable, and generalize well to data from different cohorts.

Multiomics Data Analysis Identified CpG Sites That Mediate the Impact of Smoking on Cardiometabolic Traits

Understanding the epigenome paths through which smoking contributes to cardiometabolic traits is important for downstream applications. In this study, an SNP-based analytical pipeline was used to integrate several publicly available datasets in order to identify CpG sites that mediate the impact of smoking on cardiometabolic traits and to investigate the underlying molecular mechanisms. After applying stringent statistical criteria, 11 CpG sites were detected that showed significant association (p < 5 × 10-8) with cardiometabolic traits at both the discovery and replication stages. By integrating eQTL data, I found genes behind a number of these associations. cg05228408 was hypomethylated in smokers and contributed to higher blood pressure by lowering the expression of the CLCN6 gene. cg08639339 was hypermethylated in smokers and lowered the metabolic rate by increasing the expression of RAB29; furthermore, I noted TMEM120A mediated the impact of smoking-cg17325771 on LDL, and LTBP3 mediated the smoking-cg07029024 effect on heart rate. The pathway analysis identified processes through which the identified genes impact their traits. This study provides a list of CpG sites that mediates the impact of smoking on cardiometabolic traits and a framework to investigate the underlying molecular paths using publicly available data.

Mechanisms Linking COPD to Type 1 and 2 Diabetes Mellitus: Is There a Relationship between Diabetes and COPD?

Chronic obstructive pulmonary disease (COPD) patients frequently suffer from multiple comorbidities, resulting in poor outcomes for these patients. Diabetes is observed at a higher frequency in COPD patients than in the general population. Both type 1 and 2 diabetes mellitus are associated with pulmonary complications, and similar therapeutic strategies are proposed to treat these conditions. Epidemiological studies and disease models have increased our knowledge of these clinical associations. Several recent genome-wide association studies have identified positive genetic correlations between lung function and obesity, possibly due to alterations in genes linked to cell proliferation; embryo, skeletal, and tissue development; and regulation of gene expression. These studies suggest that genetic predisposition, in addition to weight gain, can influence lung function. Cigarette smoke exposure can also influence the differential methylation of CpG sites in genes linked to diabetes and COPD, and smoke-related single nucleotide polymorphisms are associated with resting heart rate and coronary artery disease. Despite the vast literature on clinical disease association, little direct mechanistic evidence is currently available demonstrating that either disease influences the progression of the other, but common pharmacological approaches could slow the progression of these diseases. Here, we review the clinical and scientific literature to discuss whether mechanisms beyond preexisting conditions, lifestyle, and weight gain contribute to the development of COPD associated with diabetes. Specifically, we outline environmental and genetic confounders linked with these diseases.

Association between olfactory pathway gene variants and obesity in Chinese Han population: A case-control study based on genetic score

BACKGROUND

Our previous bivariate genome-wide association study in dizygotic twins suggested that the olfactory transduction pathway genes were associated with obesity in Northern Han Chinese adults. In this study, we attempted to verify the associations of the olfactory transduction pathway genes score with obesity in population with the same genetic background, and to estimate the interaction between gene variants and potential environment factors.

METHODS

A case-control study was conducted in Qingdao, China in 2019-2021, which enrolled 301 obesity cases and 307 controls. Based on the candidate gene selection method, 29 single nucleotide polymorphisms (SNPs) in 7 olfactory pathway genes were selected. Genomic deoxyribonucleic acid (DNA) was isolated and purified from the peripheral blood leukocytes by using DNA extraction kits and was genotyped by the MassArray system. The weighted genetic score of each gene was calculated to analyze the effect of whole gene. The effect of gene scores on obesity and the gene-environment interaction were estimated by logistic regression.

RESULTS

After adjusting for age, sex, smoking, alcohol drinking, physical activity, we observed positive associations of OR4D1 (OR = 1.531, 95% CI = 1.083-2.164, P = 0.016) and OR52K1 (OR = 1.437, 95% CI = 1.055-1.957, P = 0.022) gene scores with obesity, as well as negative associations of OR2L8 (OR = 0.708, 95% CI = 0.504-0.995, P = 0.046) and CALML3 (OR = 0.601, 95% CI = 0.410-0.881, P = 0.009) gene scores with obesity. Significant multiplicative model interaction between OR4D1 and smoking (P_interaction = 0.041) as well as CALML3 and smoking (P_interaction = 0.026) on obesity were identified. Stratified analysis showed that in smokers, OR4D1 gene score was positively associated with obesity (OR = 2.673, 95% CI = 1.348-5.299, P = 0.005) and CALML3 gene score was negatively correlated with obesity (OR = 0.252, 95% CI = 0.103-0.618, P = 0.003). The relationships were not statistically significant in non-smokers (OR4D1: OR = 1.216, 95% CI = 0.806-1.836, P = 0.351; CALML3: OR = 0.764, 95% CI = 0.492-1.188, P = 0.232).

CONCLUSIONS

Genetic variations in the olfactory pathway were associated with obesity in Northern Han Chinese adults. Smoking modified the effect of OR4D1 and CALML3 gene variants on obesity.

Genome-wide evaluation of transcriptomic responses of human tissues to smoke: A systems biology study

The harmful compounds in various sources of smoke threaten human health. So far, many studies have investigated the effects of compounds of smoke on transcriptome changes in different human tissues. However, no study has been conducted on the effects of these compounds on transcriptome changes in different human tissues simultaneously. Hence, the present study was conducted to identify smoke-related genes (SRGs) and their response mechanisms to smoke in various human cells and tissues using systems biology based methods. A total of 6,484 SRGs were identified in the studied tissues, among which 4,095 SRGs were up-regulated and 2,389 SRGs were down-regulated. Totally, 459 SRGs were smoke-related transcription factors (SRTFs). Gene regulatory network analysis showed that the studied cells and tissues have different gene regulation and responses to compounds of smoke. The comparison of different tissues revealed no common SRG among the all studied tissues. However, the CYP1B1 gene was common among seven cells and tissues, and had the same expression trend. Network analysis showed that the CYP1B1 is a hub gene among SRGs in various cells and tissues. To the best of our knowledge, for the first time, our results showed that compounds of smoke induce and increase the expression of CYP1B1 key gene in all target and non-target tissues of human. Moreover, despite the specific characteristics of CYP1B1 gene and its identical expression trend in target and non-target tissues, it can be used as a biomarker for diagnosis and prognosis.

Relationship Between KCNQ1 Polymorphism and Type 2 Diabetes Risk in Northwestern China

Purpose

This study aimed to explore the relationship between KCNQ1 polymorphism and type 2 diabetes mellitus (T2DM) risk in the population of Northwest China.

Patients and Methods

Case-control strategy was used to reveal the correlation between KCNQ1 polymorphism and T2DM risk, and MDR analysis clarified the influence of KCNQ1 polymorphism interaction on T2DM risk. The related proteins, functions, and signal pathways of KCNQ1 were further explored through bioinformatics methods. PCR was used to explore the relative expression of KCNQ1 in T2DM patients and the controls.

Results

Studies showed that rs163177, rs163184, rs2237895 and rs2283228 on the KCNQ1 gene are closely related to the risk of T2DM in Northwest China. MDR results showed that the three-locus model is the best model for T2DM risk assessment, which increases the risk of T2DM. The bioinformatics results showed that KCNQ1 closely-acted proteins are mainly involved in signal pathways such as gastric acid secretion and renin secretion. The PCR results showed that, compared with the controls, the expression of KCNQ1 was up-regulated in T2DM patients.

Conclusion

The results revealed that KCNQ1 polymorphism is related to the risk of T2DM in the population of Northwest China and provide a scientific basis for the early screening and prevention of T2DM high-risk populations.

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.

Association between secondhand smoke exposure and diabetes mellitus in 131 724 Korean never smokers using self-reported questionnaires and cotinine levels: Gender differences

OBJECTIVE

The aim of this study is to compare the gender-different associations between secondhand smoke (SHS) exposure and diabetes in self-reported never smokers verified by cotinine.

METHODS

Self-reported never smokers verified by cotinine levels (<50 ng/mL) enrolled in the Kangbuk Samsung Health Study between April 2011 and December 2016 were included for this study. SHS exposure was defined as current exposure to passive smoke indoors at home or workplace. The gender-specific association between SHS exposure and diabetes was assessed using multivariable regression analyses.

RESULTS

Of the total 131 724 individuals (mean age 35 years, SD 7.1 years), 66.8% were female, and the prevalence of SHS exposure in the entire population was 22.9%. The prevalence of diabetes in the group exposed to SHS was higher than that in the group unexposed to SHS only in females (1.8% vs 1.2%, P < .001 for females; 2.2% vs 2.2%, P = .956 for males). A significant gender interaction existed for the relationships between SHS exposure and diabetes (P for interaction <.001). The multivariate regression model showed that SHS exposure was significantly associated with diabetes only in females (odds ratio [95% CI], 1.40 [1.20, 1.65] for females; 1.00 [0.85, 1.19] for males). In particular, females with SHS exposure ≥1 hour/day, ≥3 times/week, and ≥10 years showed an increased risk of diabetes by more than 50% compared to those without SHS exposure.

CONCLUSIONS

SHS exposure was significantly associated with diabetes in female never smokers with dose-dependent relationship. However, further longitudinal studies are needed to elucidate the gender difference in the incidence of diabetes associated with SHS exposure.

Active Cigarette Smoking Is Associated With an Exacerbation of Genetic Susceptibility to Diabetes

The heritability levels of two traits for diabetes diagnosis, serum fasting glucose (FG) and glycated hemoglobin (HbA_1c), were estimated to be 51-62%. Studies have shown that cigarette smoking is a modifiable risk factor for diabetes. It is important to uncover whether smoking may modify the genetic risk of diabetes. This study included unrelated Taiwan Biobank subjects in a discovery cohort (TWB1) of 25,460 subjects and a replication cohort (TWB2) of 58,774 subjects. Genetic risk score (GRS) of each TWB2 subject was calculated with weights retrieved from the TWB1 analyses. We then assessed the significance of GRS-smoking interactions on FG, HbA_1c, and diabetes while adjusting for covariates. A total of five smoking measurements were investigated, including active smoking status, pack-years, years as a smoker, packs smoked per day, and hours as a passive smoker per week. Except for passive smoking, all smoking measurements were associated with FG, HbA_1c, and diabetes (P < 0.0033) and were associated with an exacerbation of the genetic risk of FG and HbA_1c (P _Interaction < 0.0033). For example, each 1 SD increase in GRS is associated with a 1.68% higher FG in subjects consuming one more pack of cigarettes per day (P _Interaction = 1.9 × 10^-7). Smoking cessation is especially important for people who are more genetically predisposed to diabetes.

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.

Association of smoking habits with TXNIP DNA methylation levels in leukocytes among general Japanese population

Thioredoxin-interacting protein (TXNIP) inhibits the activity of thioredoxin (TXN), leading to increased oxidative stress. Expression of the TXNIP gene is regulated by DNA methylation. However, no study has reported the influence of lifestyle factors on TXNIP DNA methylation. Our goal was to determine the association between smoking habits and TXNIP DNA methylation levels in a Japanese population. We conducted a cross-sectional study of 417 subjects (180 males and 237 females) participating in a health examination. We used a pyrosequencing assay to determine TXNIP DNA methylation levels in leukocytes. The mean TXNIP DNA methylation level in current smokers (75.3%) was significantly lower than that in never and ex-smokers (never: 78.1%, p < 0.001; ex: 76.9%, p = 0.013). Multivariable logistic regression analyses showed that the OR for TXNIP DNA hypomethylation was significantly higher in current smokers than that in never smokers, and significantly higher in current smokers with years of smoking ≥ 35 and Brinkman Index ≥ 600 compared to that in non-smokers. In conclusion, we found that current smokers had TXNIP DNA hypomethylation compared to never and ex-smokers. Moreover, long-term smoking and high smoking exposure also were associated with TXNIP DNA hypomethylation.

Association of common gene-smoking interactions with elevated plasma apolipoprotein B concentration

Background

Increased apolipoprotein (apo) B level (hyperapoB) is a strong predictor of cardiovascular disease (CVD), even in patients who achieve recommended LDL-Cholesterol (LDL-C) goals. ApoB level, an important correlate of metabolic syndrome (MetS), is influenced by several gene-environment interactions. Some of them are rare and can explain a large proportion of apoB variance, whereas others more common have variable effects. The aim of this study was to evaluate the association of interaction between smoking and common hyperapoB gene variants (PPARα-L162V, lipoprotein lipase loss-of function mutation, apo e4 allele or apo E2/2 genotype) with plasma apoB concentrations, according to the expression of MetS.

Methods

This study was performed among 1798 subjects. Smoking was defined as non/mild smokers vs. moderate-to-heavy smokers. ApoB levels were determined using nephelometry. Logistic regression models were used to document interactions between smoking habits and the presence of hyperapoB gene variants on the relative odds to exhibit increased plasma apoB concentrations.

Results

Around 29% of individuals with a low-risk lipid profile without MetS component had hyperapoB. Smoking and the presence of hyperapoB gene variants tended to be associated with higher plasma apoB levels even in presence of low-LDL-C. There was a significant interaction (P = 0.04) between the presence of ≥1 gene variants and smoking on the risk to exhibit hyperapoB among subjects with low risk profile in primary prevention.

Conclusions

Combination of life habits assessment and some common genes variants may detect a significant proportion of patients with increased apoB levels, and therefore a higher risk of CVD, who could have been initially perceived as low-risk.

Objectives, design and main findings until 2020 from the Rotterdam Study

The Rotterdam Study is an ongoing prospective cohort study that started in 1990 in the city of Rotterdam, The Netherlands. The study aims to unravel etiology, preclinical course, natural history and potential targets for intervention for chronic diseases in mid-life and late-life. The study focuses on cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1700 research articles and reports. This article provides an update on the rationale and design of the study. It also presents a summary of the major findings from the preceding 3 years and outlines developments for the coming period.

Multi-Omics Analysis Reveals MicroRNAs Associated With Cardiometabolic Traits

MicroRNAs (miRNAs) are non-coding RNA molecules that regulate gene expression. Extensive research has explored the role of miRNAs in the risk for type 2 diabetes (T2D) and coronary heart disease (CHD) using single-omics data, but much less by leveraging population-based omics data. Here we aimed to conduct a multi-omics analysis to identify miRNAs associated with cardiometabolic risk factors and diseases. First, we used publicly available summary statistics from large-scale genome-wide association studies to find genetic variants in miRNA-related sequences associated with various cardiometabolic traits, including lipid and obesity-related traits, glycemic indices, blood pressure, and disease prevalence of T2D and CHD. Then, we used DNA methylation and miRNA expression data from participants of the Rotterdam Study to further investigate the link between associated miRNAs and cardiometabolic traits. After correcting for multiple testing, 180 genetic variants annotated to 67 independent miRNAs were associated with the studied traits. Alterations in DNA methylation levels of CpG sites annotated to 38 of these miRNAs were associated with the same trait(s). Moreover, we found that plasma expression levels of 8 of the 67 identified miRNAs were also associated with the same trait. Integrating the results of different omics data showed miR-10b-5p, miR-148a-3p, miR-125b-5p, and miR-100-5p to be strongly linked to lipid traits. Collectively, our multi-omics analysis revealed multiple miRNAs that could be considered as potential biomarkers for early diagnosis and progression of cardiometabolic diseases.

Pleiotropic Effects of a KCNQ1 Variant on Lipid Profiles and Type 2 Diabetes: A Family-Based Study in China

OBJECTIVE

The genetic variant rs2237895, located in the Potassium Voltage-Gated Channel Subfamily Q Member 1 (KCNQ1) gene, has been replicated to be associated with type 2 diabetes mellitus (T2DM) susceptibility, but the relationship with lipids is conflicting. Furthermore, the common genetic predisposition to T2DM and lipids was not fully detected.

METHODS

In total, 5839 individuals (2220 were T2DM patients) across 2885 families were included. The effect of rs2237895 on T2DM and lipids was estimated using linear regression and logistic regression models after adjustment for multiple covariates. Mediation analysis was then used to test whether KCNQ1 participated in T2DM pathogenesis via lipid-mediated pathways.

RESULTS

Per allele-C of rs2237895 was associated with 17% (11-23%, P < 0.001) increased T2DM risk. Moreover, it was correlated with 5% (1-9%, P < 0.001) increased T2DM risk. Moreover, it was correlated with 5% (1-9%, P < 0.001) increased T2DM risk. Moreover, it was correlated with 5% (1-9%, P < 0.001) increased T2DM risk. Moreover, it was correlated with 5% (1-9%, P < 0.001) increased T2DM risk. Moreover, it was correlated with 5% (1-9%, P < 0.001) increased T2DM risk. Moreover, it was correlated with 5% (1-9%.

CONCLUSION

KCNQ1 had pleiotropic effects on lipids and T2DM, and the unexpected genetic effect on association of HDL-C with T2DM was observed, indicating the different pathways to lipids and T2DM. Further research studies are needed to verify potential biological mechanisms.

DNA methylation is associated with lung function in never smokers

BACKGROUND

Active smoking is the main risk factor for COPD. Here, epigenetic mechanisms may play a role, since cigarette smoking is associated with differential DNA methylation in whole blood. So far, it is unclear whether epigenetics also play a role in subjects with COPD who never smoked. Therefore, we aimed to identify differential DNA methylation associated with lung function in never smokers.

METHODS

We determined epigenome-wide DNA methylation levels of 396,243 CpG-sites (Illumina 450 K) in blood of never smokers in four independent cohorts, LifeLines COPD&C (N = 903), LifeLines DEEP (N = 166), Rotterdam Study (RS)-III (N = 150) and RS-BIOS (N = 206). We meta-analyzed the cohort-specific methylation results to identify differentially methylated CpG-sites with FEV₁/FVC. Expression Quantitative Trait Methylation (eQTM) analysis was performed in the Biobank-based Integrative Omics Studies (BIOS).

RESULTS

A total of 36 CpG-sites were associated with FEV₁/FVC in never smokers at p-value< 0.0001, but the meta-analysis did not reveal any epigenome-wide significant CpG-sites. Of interest, 35 of these 36 CpG-sites have not been associated with lung function before in studies including subjects irrespective of smoking history. Among the top hits were cg10012512, cg02885771, annotated to the gene LTV1 Ribosome Biogenesis factor (LTV1), and cg25105536, annotated to Kelch Like Family Member 32 (KLHL32). Moreover, a total of 11 eQTMS were identified.

CONCLUSIONS

With the identification of 35 CpG-sites that are unique for never smokers, our study shows that DNA methylation is also associated with FEV₁/FVC in subjects that never smoked and therefore not merely related to smoking.

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.

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.

Occupational exposure to gases/fumes and mineral dust affect DNA methylation levels of genes regulating expression

Many workers are daily exposed to occupational agents like gases/fumes, mineral dust or biological dust, which could induce adverse health effects. Epigenetic mechanisms, such as DNA methylation, have been suggested to play a role. We therefore aimed to identify differentially methylated regions (DMRs) upon occupational exposures in never-smokers and investigated if these DMRs associated with gene expression levels. To determine the effects of occupational exposures independent of smoking, 903 never-smokers of the LifeLines cohort study were included. We performed three genome-wide methylation analyses (Illumina 450 K), one per occupational exposure being gases/fumes, mineral dust and biological dust, using robust linear regression adjusted for appropriate confounders. DMRs were identified using comb-p in Python. Results were validated in the Rotterdam Study (233 never-smokers) and methylation-expression associations were assessed using Biobank-based Integrative Omics Study data (n = 2802). Of the total 21 significant DMRs, 14 DMRs were associated with gases/fumes and 7 with mineral dust. Three of these DMRs were associated with both exposures (RPLP1 and LINC02169 (2×)) and 11 DMRs were located within transcript start sites of gene expression regulating genes. We replicated two DMRs with gases/fumes (VTRNA2-1 and GNAS) and one with mineral dust (CCDC144NL). In addition, nine gases/fumes DMRs and six mineral dust DMRs significantly associated with gene expression levels. Our data suggest that occupational exposures may induce differential methylation of gene expression regulating genes and thereby may induce adverse health effects. Given the millions of workers that are exposed daily to occupational exposures, further studies on this epigenetic mechanism and health outcomes are warranted.

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.

Cumulative lifetime maternal stress and epigenome-wide placental DNA methylation in the PRISM cohort

Evolving evidence links maternal stress exposure to changes in placental DNA methylation of specific genes regulating placental function that may have implications for the programming of a host of chronic disorders. Few studies have implemented an epigenome-wide approach. Using the Infinium HumanMethylation450 BeadChip (450K), we investigated epigenome-wide placental DNA methylation in relation to maternal experiences of traumatic and non-traumatic stressors over her lifetime assessed using the Life Stressor Checklist-Revised (LSC-R) survey (n = 207). We found differential DNA methylation at epigenome-wide statistical significance (FDR = 0.05) for 112 CpGs. Additionally, we observed three clusters that exhibited differential methylation in response to high maternal lifetime stress. Enrichment analyses, conducted at an FDR = 0.20, revealed lysine degradation to be the most significant pathway associated with maternal lifetimes stress exposure. Targeted enrichment analyses of the three largest clusters of probes, identified using the gap statistic, were enriched for genes associated with endocytosis (i.e., SMAP1, ANKFY1), tight junctions (i.e., EPB41L4B), and metabolic pathways (i.e., INPP5E, EEF1B2). These pathways, also identified in the top 10 KEGG pathways associated with maternal lifetime stress exposure, play important roles in multiple physiological functions necessary for proper fetal development. Further, two genes were identified to exhibit multiple probes associated with maternal lifetime stress (i.e., ANKFY1, TM6SF1). The methylation status of the probes belonging to each cluster and/or genes exhibiting multiple hits, may play a role in the pathogenesis of adverse health outcomes in children born to mothers with increased lifetime stress exposure.

An integrated -omics analysis of the epigenetic landscape of gene expression in human blood cells

Background

Gene expression can be influenced by DNA methylation 1) distally, at regulatory elements such as enhancers, as well as 2) proximally, at promoters. Our current understanding of the influence of distal DNA methylation changes on gene expression patterns is incomplete. Here, we characterize genome-wide methylation and expression patterns for ~ 13 k genes to explore how DNA methylation interacts with gene expression, throughout the genome.

Results

We used a linear mixed model framework to assess the correlation of DNA methylation at ~ 400 k CpGs with gene expression changes at ~ 13 k transcripts in two independent datasets from human blood cells. Among CpGs at which methylation significantly associates with transcription (eCpGs), > 50% are distal (> 50 kb) or trans (different chromosome) to the correlated gene. Many eCpG-transcript pairs are consistent between studies and ~ 90% of neighboring eCpGs associate with the same gene, within studies. We find that enhancers (P < 5e-18) and microRNA genes (P = 9e-3) are overrepresented among trans eCpGs, and insulators and long intergenic non-coding RNAs are enriched among cis and distal eCpGs. Intragenic-eCpG-transcript correlations are negative in 60–70% of occurrences and are enriched for annotated gene promoters and enhancers (P < 0.002), highlighting the importance of intragenic regulation. Gene Ontology analysis indicates that trans eCpGs are enriched for transcription factor genes and chromatin modifiers, suggesting that some trans eCpGs represent the influence of gene networks and higher-order transcriptional control.

Conclusions

This work sheds new light on the interplay between epigenetic changes and gene expression, and provides useful data for mining biologically-relevant results from epigenome-wide association studies.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4842-3) contains supplementary material, which is available to authorized users.

Understanding the role of the chromosome 15q25.1 in COPD through epigenetics and transcriptomics

Chronic obstructive pulmonary disease (COPD) is a major health burden in adults and cigarette smoking is considered the most important environmental risk factor of COPD. Chromosome 15q25.1 locus is associated with both COPD and smoking. Our study aims at understanding the mechanism underlying the association of chromosome 15q25.1 with COPD through epigenetic and transcriptional variation in a population-based setting. To assess if COPD-associated variants in 15q25.1 are methylation quantitative trait loci, epigenome-wide association analysis of four genetic variants, previously associated with COPD (P < 5 × 10-8) in the 15q25.1 locus (rs12914385:C>T-CHRNA3, rs8034191:T>C-HYKK, rs13180:C>T-IREB2 and rs8042238:C>T-IREB2), was performed in the Rotterdam study (n = 1489). All four variants were significantly associated (P < 1.4 × 10-6) with blood DNA methylation of IREB2, CHRNA3 and PSMA4, of which two, including IREB2 and PSMA4, were also differentially methylated in COPD cases and controls (P < 0.04). Further additive and multiplicative effects of smoking were evaluated and no significant effect was observed. To evaluate if these four genetic variants are expression quantitative trait loci, transcriptome-wide association analysis was performed in 1087 lung samples. All four variants were also significantly associated with differential expression of the IREB2 3'UTR in lung tissues (P < 5.4 × 10-95). We conclude that regulatory mechanisms affecting the expression of IREB2 gene, such as DNA methylation, may explain the association between genetic variants in chromosome 15q25.1 and COPD, largely independent of smoking.

Epigenome-wide association study of smoking and DNA methylation in non-small cell lung neoplasms

Tobacco smoke is a well-established lung cancer carcinogen. We hypothesize that epigenetic processes underlie carcinogenesis. The objective of this study is to examine the effects of smoke exposure on DNA methylation to search for novel susceptibility loci. We obtained epigenome-wide DNA methylation data from lung adenocarcinoma (LUAD) and lung squamous cell (LUSC) tissues in The Cancer Genome Atlas (TCGA). We performed a two-stage discovery (n = 326) and validation (n = 185) analysis to investigate the association of epigenetic DNA methylation level with cigarette smoking pack-years. We also externally validated our findings in an independent dataset. Linear model with least square estimator and spline regression were performed to examine the association between DNA methylation and smoking. We identified five CpG sites highly associated with pack-years of cigarette smoking. Smoking was negatively associated with methylation levels in cg25771041 (WWTR1, p = 3.6 × 10⁻⁹), cg16200496 (NFIX, p = 3.4 × 10⁻¹²), cg22515201 (PLA2G6, p = 1.0 × 10⁻⁹) and cg24823993 (NHP2L1, p = 5.1 × 10⁻⁸) and positively associated with the methylation level in cg11875268 (SMUG1, p = 4.3 × 10⁻⁸). The CpG-smoking association was stronger in LUSC than LUAD. Of the five loci, smoking explained the most variation in cg16200496 (R² = 0.098 [both types] and 0.144 [LUSC]). We identified 5 novel CpG candidates that demonstrate differential methylation patterns associated with smoke exposure in lung neoplasms.

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.

Interactions between genetic polymorphisms of glucose metabolizing genes and smoking and alcohol consumption in the risk of type 2 diabetes mellitus

The impact of gene-environment interaction on diabetes remains largely unknown. We aimed to investigate if interaction between glucose metabolizing genes and lifestyle factors is associated with type 2 diabetes mellitus (T2DM). Interactions between genotypes of 4 glucose metabolizing genes (MTNR1B, KCNQ1, KLF14, and GCKR) and lifestyle factors were estimated in 722 T2DM patients and 759 controls, using multiple logistic regression. No significant associations with T2DM were detected for the single nucleotide polymorphisms of MTNR1B, KLF14 and GCKR. However, rs151290 (KCNQ1) polymorphisms were found to be associated with risk of T2DM. Compared with AA, the odds ratios (ORs) of AC or CC genotypes for developing T2DM were 1.545 (P = 0.0489) and 1.603 (P = 0.0383), respectively. In stratified analyses, the associations were stronger in smokers with CC than smokers with AA (OR = 3.668, P = 0.013); drinkers with AC (OR = 5.518, P = 0.036), CC (OR = 8.691, P = 0.0095), and AC+CC (OR = 6.764, P = 0.016) than drinkers with AA. Compared with nondrinkers with AA, drinkers who carry AC and CC had 12.072-fold (P = 0.0007) and 8.147-fold (P = 0.0052) higher risk of developing T2DM. In conclusions, rs151290 (KCNQ1) polymorphisms are associated with increased risk of T2DM, alone and especially in interaction with smoking and alcohol.

Cigarette Smoking, Diabetes, and Diabetes Complications: Call for Urgent Action

PURPOSE OF REVIEW

This review aimed to examine the latest evidence linking cigarette smoking and cessation to risk of incident diabetes and its complications.

RECENT FINDINGS

Abundant evidence has demonstrated that smoking is associated with increased risk of type 2 diabetes and cardiovascular disease among diabetic patients, while its relationship with microvascular complications is more limited to diabetic nephropathy and neuropathy in type 1 diabetes. In addition, diabetes risk remains high in the short term after smoking cessation, while it reduces gradually in the long term. Risk of cardiovascular complications also substantially decreases after quitting smoking, but results for microvascular complications are not consistent. Smoking is associated with increased risks of incident diabetes in the general population and cardiovascular complications among diabetic patients. Although the short-term post-cessation diabetes risk needs to be acknowledged, this review calls for urgent action to implement population-wide policies and individual pharmaceutical and lifestyle interventions (if evidence accumulated in future) to aid smoking cessation and prevent diabetes and its complications.

The Rotterdam Study: 2018 update on objectives, design and main results

The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1500 research articles and reports (see www.erasmus-epidemiology.nl/rotterdamstudy ). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods.

Role of DNA Methylation in Type 2 Diabetes Etiology: Using Genotype as a Causal Anchor

Several studies have investigated the relationship between genetic variation and DNA methylation with respect to type 2 diabetes, but it is unknown if DNA methylation is a mediator in the disease pathway or if it is altered in response to disease state. This study uses genotypic information as a causal anchor to help decipher the likely role of DNA methylation measured in peripheral blood in the etiology of type 2 diabetes. Illumina HumanMethylation450 BeadChip data were generated on 1,018 young individuals from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. In stage 1, 118 unique associations between published type 2 diabetes single nucleotide polymorphisms (SNPs) and genome-wide methylation (methylation quantitative trait loci [mQTLs]) were identified. In stage 2, a further 226 mQTLs were identified between 202 additional independent non-type 2 diabetes SNPs and CpGs identified in stage 1. Where possible, associations were replicated in independent cohorts of similar age. We discovered that around half of known type 2 diabetes SNPs are associated with variation in DNA methylation and postulated that methylation could either be on a causal pathway to future disease or could be a noncausal biomarker. For one locus (KCNQ1), we were able to provide further evidence that methylation is likely to be on the causal pathway to disease in later life.

Smoking and the risk of type 2 diabetes

Despite accumulating evidence demonstrating strong epidemiologic and mechanistic associations between cigarette smoking, hyperglycemia, and the development of type 2 diabetes, tobacco abuse has not been uniformly recognized as a modifiable risk factor in diabetes prevention or screening strategies. In this review, we highlight population-based studies that have linked cigarette smoking with an increased risk of type 2 diabetes and summarize clinical and preclinical studies offering insight into mechanisms through which cigarette smoking and nicotine exposure impact body composition, insulin sensitivity, and pancreatic β cell function. Key questions for future studies are identified and strategies for smoking cessation as a means to decrease diabetes risk are discussed.

Genetic and epigenetic mechanisms underlying arsenic-associated diabetes mellitus: a perspective of the current evidence

Chronic exposure to arsenic has been associated with the development of diabetes mellitus (DM), a disease characterized by hyperglycemia resulting from dysregulation of glucose homeostasis. This review summarizes four major mechanisms by which arsenic induces diabetes, namely inhibition of insulin-dependent glucose uptake, pancreatic β-cell damage, pancreatic β-cell dysfunction and stimulation of liver gluconeogenesis that are supported by both in vivo and in vitro studies. Additionally, the role of polymorphic variants associated with arsenic toxicity and disease susceptibility, as well as epigenetic modifications associated with arsenic exposure, are considered in the context of arsenic-associated DM. Taken together, in vitro, in vivo and human genetic/epigenetic studies support that arsenic has the potential to induce DM phenotypes and impair key pathways involved in the regulation of glucose homeostasis.

Tobacco and diabetes: clinical relevance and approach to smoking cessation in diabetic smokers

Smoking is, together with diabetes mellitus, one of the main risk factors for cardiovascular disease. Diabetic patients have unique features and characteristics, some of which are not well known, that cause smoking to aggravate the effects of diabetes and impose difficulties in the smoking cessation process, for which a specificand more intensive approach with stricter controls is required. This review details all aspects with a known influence on the interaction between smoking and diabetes, both as regards the increased risk of macrovascular and microvascular complications of diabetes and the factors with an impact on the results of smoking cessation programs. The treatment guidelines for these smokers, including the algorithms and drug treatment patterns which have proved most useful based on scientific evidence, are also discussed.

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.