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

Identification and validation of cigarette smoking-related genes in predicting prostate cancer development through bioinformatic analysis and experiments

The morbidity and mortality rates of prostate cancer (PCa) are high among elderly men worldwide. Several factors, such as heredity, obesity, and environment are associated with the occurrence of PCa. Cigarette smoking, which is also an important factor in the development of PCa, can lead to genetic alterations and consequently promote PCa development. However, the smoking-induced genetic alterations in PCa are unclear. This study aimed to identify the potential smoking-related genes associated with PCa development. The smoking-related differentially expressed genes (DEGs) were identified using the Gene Expression Omnibus (GEO) which included lots of PCa datasets. DEGs were subjected to protein-protein interaction (PPI) network analysis to identify the hub genes. The pathways in which these hub genes were enriched were identified. The Cancer Genome Atlas (TCGA) dataset was used to examine the expression of smoking-related genes in PCa samples and estimate their value in predicting tumor progression and prognosis. In total, 110 smoking-related DEGs were got from GSE68135 dataset which included microarray data of PCa patients with smoking or not and 14 smoking-related key genes associated with PCa were identified from PPI network. The expression of the following seven key genes was altered in TCGA PCa patients: EWSR1, SRSF6, COL6A3, FBLN1, DCN, CYP2J2, and PLA2G2A. EWSR1, SRSF6, FBLN1, and CYP2J2 also influenced PCa progression. Additionally, EWSR1 influenced disease-free survival. In the logistic regression model, CYP2J2, which exhibited the highest risk scores, was identified as the risk gene for PCa. We also found one of the smoking-related genes: EWSR1 was truly upregulated in clinical PCa patients and influenced PCa cells invasion and proliferation. This study identified the function of smoking-related genes involved in the progression of PCa.

Role of epigenetic mechanisms in the pathogenesis of chronic respiratory diseases and response to inhaled exposures: From basic concepts to clinical applications

Epigenetic modifications are chemical groups in our DNA (and chromatin) that determine which genes are active and which are shut off. Importantly, they integrate environmental signals to direct cellular function. Upon chronic environmental exposures, the epigenetic signature of lung cells gets altered, triggering aberrant gene expression programs that can lead to the development of chronic lung diseases. In addition to driving disease, epigenetic marks can serve as attractive lung disease biomarkers, due to early onset, disease specificity, and stability, warranting the need for more epigenetic research in the lung field. Despite substantial progress in mapping epigenetic alterations (mostly DNA methylation) in chronic lung diseases, the molecular mechanisms leading to their establishment are largely unknown. This review is meant as a guide for clinicians and lung researchers interested in epigenetic regulation with a focus on DNA methylation. It provides a short introduction to the main epigenetic mechanisms (DNA methylation, histone modifications and non-coding RNA) and the machinery responsible for their establishment and removal. It presents examples of epigenetic dysregulation across a spectrum of chronic lung diseases and discusses the current state of epigenetic therapies. Finally, it introduces the concept of epigenetic editing, an exciting novel approach to dissecting the functional role of epigenetic modifications. The promise of this emerging technology for the functional study of epigenetic mechanisms in cells and its potential future use in the clinic is further discussed.

Prenatal chemical exposures and the methylome: current evidence and opportunities for environmental epigenetics

Exposure to pollutants and chemicals during critical developmental periods in early life can impact health and disease risk across the life course. Research in environmental epigenetics has provided increasing evidence that prenatal exposures affect epigenetic markers, particularly DNA methylation. In this article, we discuss the role of DNA methylation in early life programming and review evidence linking the intrauterine environment to epigenetic modifications, with a focus on exposure to tobacco smoke, metals, and endocrine-disrupting chemicals. We also discuss challenges and novel approaches in environmental epigenetic research and explore the potential of epigenetic biomarkers in studies of pediatric populations as indicators of exposure and disease risk. Overall, we aim to highlight how advancements in environmental epigenetics may transform our understanding of early-life exposures and inform new approaches for supporting long-term health.

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.

Smoking-Induced DNA Hydroxymethylation Signature Is Less Pronounced than True DNA Methylation: The Population-Based KORA Fit Cohort

Despite extensive research on 5-methylcytosine (5mC) in relation to smoking, there has been limited exploration into the interaction between smoking and 5-hydroxymethylcytosine (5hmC). In this study, total DNA methylation (5mC+5hmC), true DNA methylation (5mC) and hydroxymethylation (5hmC) levels were profiled utilizing conventional bisulphite (BS) and oxidative bisulphite (oxBS) treatment, measured with the Illumina Infinium Methylation EPIC BeadChip. An epigenome-wide association study (EWAS) of 5mC+5hmC methylation revealed a total of 38,575 differentially methylated positions (DMPs) and 2023 differentially methylated regions (DMRs) associated with current smoking, along with 82 DMPs and 76 DMRs associated with former smoking (FDR-adjusted p < 0.05). Additionally, a focused examination of 5mC identified 33 DMPs linked to current smoking and 1 DMP associated with former smoking (FDR-adjusted p < 0.05). In the 5hmC category, eight DMPs related to current smoking and two DMPs tied to former smoking were identified, each meeting a suggestive threshold (p < 1 × 10-5). The substantial number of recognized DMPs, including 5mC+5hmC (7069/38,575, 2/82), 5mC (0/33, 1/1), and 5hmC (2/8, 0/2), have not been previously reported. Our findings corroborated previously established methylation positions and revealed novel candidates linked to tobacco smoking. Moreover, the identification of hydroxymethylated CpG sites with suggestive links provides avenues for future research.

GPS2 ameliorates cigarette smoking-induced pulmonary vascular remodeling by modulating the ras-Raf-ERK axis

BACKGROUND

Mitogen-activated protein kinase (MAPK)signaling-mediated smoking-associated pulmonary vascular remodeling (PVR) plays an important role in the pathogenesis of group 3 pulmonary hypertension (PH). And G protein pathway suppressor 2 (GPS2) could suppress G-protein signaling such as Ras and MAPK, but its role in cigarette smoking -induced PVR (CS-PVR) is unclear.

METHODS

An in vivo model of smoke-exposed rats was constructed to assess the role of GPS2 in smoking-induced PH and PVR. In vitro, the effects of GPS2 overexpression and silencing on the function of human pulmonary arterial smooth cells (HPASMCs) and the underlying mechanisms were explored.

RESULTS

GPS2 expression was downregulated in rat pulmonary arteries (PAs) and HPASMCs after CS exposure. More importantly, CS-exposed rats with GPS2 overexpression had lower right ventricular systolic pressure (RVSP), right ventricular hypertrophy index (RVHI), and wall thickness (WT%) than those without. And enhanced proliferation and migration of HPASMCs induced by cigarette smoking extract (CSE) can be evidently inhibited by overexpressed GPS2. Besides, GPS2siRNA significantly enhanced the proliferation, and migration of HPASMCs as well as activated Ras and Raf/ERK signaling, while these effects were inhibited by zoledronic acid (ZOL). In addition, GPS2 promoter methylation level in rat PAs and HPASMCs was increased after CS exposure, and 5-aza-2-deoxycytidine (5-aza) inhibited CSE-induced GPS2 hypermethylation and downregulation in vitro.

CONCLUSIONS

GPS2 overexpression could improve the CS-PVR, suggesting that GPS2 might serve as a novel therapeutic target for PH-COPD in the future.

The association of cigarette smoking with DNA methylation and gene expression in human tissue samples

Cigarette smoking adversely affects many aspects of human health, and epigenetic responses to smoking may reflect mechanisms that mediate or defend against these effects. Prior studies of smoking and DNA methylation (DNAm), typically measured in leukocytes, have identified numerous smoking-associated regions (e.g., AHRR). To identify smoking-associated DNAm features in typically inaccessible tissues, we generated array-based DNAm data for 916 tissue samples from the GTEx (Genotype-Tissue Expression) project representing 9 tissue types (lung, colon, ovary, prostate, blood, breast, testis, kidney, and muscle). We identified 6,350 smoking-associated CpGs in lung tissue (n = 212) and 2,735 in colon tissue (n = 210), most not reported previously. For all 7 other tissue types (sample sizes 38-153), no clear associations were observed (false discovery rate 0.05), but some tissues showed enrichment for smoking-associated CpGs reported previously. For 1,646 loci (in lung) and 22 (in colon), smoking was associated with both DNAm and local gene expression. For loci detected in both lung and colon (e.g., AHRR, CYP1B1, CYP1A1), top CpGs often differed between tissues, but similar clusters of hyper- or hypomethylated CpGs were observed, with hypomethylation at regulatory elements corresponding to increased expression. For lung tissue, 17 hallmark gene sets were enriched for smoking-associated CpGs, including xenobiotic- and cancer-related gene sets. At least four smoking-associated regions in lung were impacted by lung methylation quantitative trait loci (QTLs) that co-localize with genome-wide association study (GWAS) signals for lung function (FEV1/FVC), suggesting epigenetic alterations can mediate the effects of smoking on lung health. Our multi-tissue approach has identified smoking-associated regions in disease-relevant tissues, including effects that are shared across tissue types.

Role of untargeted omics biomarkers of exposure and effect for tobacco research

Tobacco research remains a clear priority to improve individual and population health, and has recently become more complex with emerging combustible and noncombustible tobacco products. The use of omics methods in prevention and cessation studies are intended to identify new biomarkers for risk, compared risks related to other products and never use, and compliance for cessation and reinitation. to assess the relative effects of tobacco products to each other. They are important for the prediction of reinitiation of tobacco use and relapse prevention. In the research setting, both technical and clinical validation is required, which presents a number of complexities in the omics methodologies from biospecimen collection and sample preparation to data collection and analysis. When the results identify differences in omics features, networks or pathways, it is unclear if the results are toxic effects, a healthy response to a toxic exposure or neither. The use of surrogate biospecimens (e.g., urine, blood, sputum or nasal) may or may not reflect target organs such as the lung or bladder. This review describes the approaches for the use of omics in tobacco research and provides examples of prior studies, along with the strengths and limitations of the various methods. To date, there is little consistency in results, likely due to small number of studies, limitations in study size, the variability in the analytic platforms and bioinformatic pipelines, differences in biospecimen collection and/or human subject study design. Given the demonstrated value for the use of omics in clinical medicine, it is anticipated that the use in tobacco research will be similarly productive.

Prolonged indoleamine 2,3-dioxygenase-2 activity and associated cellular stress in post-acute sequelae of SARS-CoV-2 infection

BACKGROUND

Post-acute sequela of SARS-CoV-2 infection (PASC) encompass fatigue, post-exertional malaise and cognitive problems. The abundant expression of the tryptophan-catabolizing enzyme indoleamine 2,3-dioxygenase-2 (IDO2) in fatal/severe COVID-19, led us to determine, in an exploratory observational study, whether IDO2 is expressed and active in PASC, and may correlate with pathophysiology.

METHODS

Plasma or serum, and peripheral blood mononuclear cells (PBMC) were obtained from well-characterized PASC patients and SARS-CoV-2-infected individuals without PASC. We assessed tryptophan and its degradation products by UPLC-MS/MS. IDO2 activity, its potential consequences, and the involvement of the aryl hydrocarbon receptor (AHR) in IDO2 expression were determined in PBMC from another PASC cohort by immunohistochemistry (IHC) for IDO2, IDO1, AHR, kynurenine metabolites, autophagy, and apoptosis. These PBMC were also analyzed by metabolomics and for mitochondrial functioning by respirometry. IHC was also performed on autopsy brain material from two PASC patients.

FINDINGS

IDO2 is expressed and active in PBMC from PASC patients, as well as in brain tissue, long after SARS-CoV-2 infection. This is paralleled by autophagy, and in blood cells by reduced mitochondrial functioning, reduced intracellular levels of amino acids and Krebs cycle-related compounds. IDO2 expression and activity is triggered by SARS-CoV-2-infection, but the severity of SARS-CoV-2-induced pathology appears related to the generated specific kynurenine metabolites. Ex vivo, IDO2 expression and autophagy can be halted by an AHR antagonist.

INTERPRETATION

SARS-CoV-2 infection triggers long-lasting IDO2 expression, which can be halted by an AHR antagonist. The specific kynurenine catabolites may relate to SARS-CoV-2-induced symptoms and pathology.

FUNDING

None.

ADHD genetic burden associates with older epigenetic age: mediating roles of education, behavioral and sociodemographic factors among older adults

BACKGROUND

Shortened lifespans are associated with having Attention Deficit Hyperactivity Disorder (ADHD), which is likely mediated by related behavioral and sociodemographic factors that are also associated with accelerated physiological aging. Such factors include exhibiting more depressive symptoms, more cigarette smoking, higher body mass index, lower educational attainment, lower income in adulthood, and more challenges with cognitive processes compared to the general population. A higher polygenic score for ADHD (ADHD-PGS) is associated with having more characteristic features of ADHD. The degree to which (1) the ADHD-PGS associates with an epigenetic biomarker developed to predict accelerated aging and earlier mortality is unknown, as are whether (2) an association would be mediated by behavioral and sociodemographic correlates of ADHD, or (3) an association would be mediated first by educational attainment, then by behavioral and sociodemographic correlates. We evaluated these relationships in a population-based sample from the US Health and Retirement Study, among N = 2311 adults age 50 and older, of European-ancestry, with blood-based epigenetic and genetic data. The ADHD-PGS was calculated from a prior genomewide meta-analysis. Epigenome-wide DNA methylation levels that index biological aging and earlier age of mortality were quantified by a blood-based biomarker called GrimAge. We used a structural equation modeling approach to test associations with single and multi-mediation effects of behavioral and contextual indicators on GrimAge, adjusted for covariates.

RESULTS

The ADHD-PGS was significantly and directly associated with GrimAge when adjusting for covariates. In single mediation models, the effect of the ADHD-PGS on GrimAge was partially mediated via smoking, depressive symptoms, and education. In multi-mediation models, the effect of the ADHD-PGS on GrimAge was mediated first through education, then smoking, depressive symptoms, BMI, and income.

CONCLUSIONS

Findings have implications for geroscience research in elucidating lifecourse pathways through which ADHD genetic burden and symptoms can alter risks for accelerated aging and shortened lifespans, when indexed by an epigenetic biomarker. More education appears to play a central role in attenuating negative effects on epigenetic aging from behavioral and sociodemographic risk factors related to ADHD. We discuss implications for the potential behavioral and sociodemographic mediators that may attenuate negative biological system effects.

A variability in response of osteoclasts to zoledronic acid is mediated by smoking-associated modification in the DNA methylome

BACKGROUND

Clinical trials have shown zoledronic acid as a potent bisphosphonate in preventing bone loss, but with varying potency between patients. Human osteoclasts ex vivo reportedly displayed a variable sensitivity to zoledronic acid > 200-fold, determined by the half-maximal inhibitory concentration (IC50), with cigarette smoking as one of the reported contributors to this variation. To reveal the molecular basis of the smoking-mediated variation on treatment sensitivity, we performed a DNA methylome profiling on whole blood cells from 34 healthy female blood donors. Multiple regression models were fitted to associate DNA methylation with ex vivo determined IC50 values, smoking, and their interaction adjusting for age and cell compositions.

RESULTS

We identified 59 CpGs displaying genome-wide significance (p < 1e-08) with a false discovery rate (FDR) < 0.05 for the smoking-dependent association with IC50. Among them, 3 CpGs have p < 1e-08 and FDR < 2e-03. By comparing with genome-wide association studies, 15 significant CpGs were locally enriched (within < 50,000 bp) by SNPs associated with bone and body size measures. Furthermore, through a replication analysis using data from a published multi-omics association study on bone mineral density (BMD), we could validate that 29 out of the 59 CpGs were in close vicinity of genomic sites significantly associated with BMD. Gene Ontology (GO) analysis on genes linked to the 59 CpGs displaying smoking-dependent association with IC50, detected 18 significant GO terms including cation:cation antiporter activity, extracellular matrix conferring tensile strength, ligand-gated ion channel activity, etc. CONCLUSIONS: Our results suggest that smoking mediates individual sensitivity to zoledronic acid treatment through epigenetic regulation. Our novel findings could have important clinical implications since DNA methylation analysis may enable personalized zoledronic acid treatment.

Identification of Smoking-Associated Transcriptome Aberration in Blood with Machine Learning Methods

Long-term cigarette smoking causes various human diseases, including respiratory disease, cancer, and gastrointestinal (GI) disorders. Alterations in gene expression and variable splicing processes induced by smoking are associated with the development of diseases. This study applied advanced machine learning methods to identify the isoforms with important roles in distinguishing smokers from former smokers based on the expression profile of isoforms from current and former smokers collected in one previous study. These isoforms were deemed as features, which were first analyzed by the Boruta to select features highly correlated with the target variables. Then, the selected features were evaluated by four feature ranking algorithms, resulting in four feature lists. The incremental feature selection method was applied to each list for obtaining the optimal feature subsets and building high-performance classification models. Furthermore, a series of classification rules were accessed by decision tree with the highest performance. Eventually, the rationality of the mined isoforms (features) and classification rules was verified by reviewing previous research. Features such as isoforms ENST00000464835 (expressed by LRRN3), ENST00000622663 (expressed by SASH1), and ENST00000284311 (expressed by GPR15), and pathways (cytotoxicity mediated by natural killer cell and cytokine-cytokine receptor interaction) revealed by the enrichment analysis, were highly relevant to smoking response, suggesting the robustness of our analysis pipeline.

Induction mechanism of cigarette smoke components (CSCs) on dyslipidemia and hepatic steatosis in rats

Objective

The purpose of this study was to explore the effect of cigarette smoke component (CSC) exposure on serum lipid levels in rats and the underlying molecular mechanism.

Methods

Male SPF-grade SD rats were randomly divided into a control group and a CSC exposure group, with the CSC group being exposed to CSC for 6 weeks. RT–PCR and Western blotting methods were used to detect lipid metabolism gene expression in rats, and 16S RNA gene sequencing was used to detect the gut microbiota in the rat cecum. Rat serum exosomes were prepared and identified, and the interaction of exosomal miR-291a-3p and miR-126a-5p with AMPK and CYP7A1 was detected by a dual luciferase reporter gene assay (DLRG).

Results

Serum indicators, including cholesterol levels and trimethylamine oxide (TMAO) content, were significantly affected in the CSC exposure group compared with the control group (P < 0.05), and the expression levels of adenylate-activated protein kinase (AMPK), acetyl-coenzyme A carboxylase (ACC) and HMG-CoA reductase (HMG-CoAR) genes were significantly increased (P < 0.05) in the liver, while the expression level of cholesterol 7α-hydroxylase (CYP7A1) was markedly decreased (P < 0.01). 16S rRNA gene sequencing of the gut microbiota in the rat cecum showed that the abundance of Firmicutes in the CSC group increased significantly at the phylum level, while the abundances of Bacteroidota and Spirochaetota were reduced significantly (P < 0.01). The relative abundance of Romboutsia, Turicibacter, and Clostridium sensu stricto increased significantly (P < 0.01), and the relative abundance of Prevotella, Muribaculaceae_norank, Lachnospiraceae NK4A136 group, Roseburia, Treponema, and Ruminococcus significantly decreased (P < 0.01) at the genus level. In addition, the exosome miR-291a-3p and miR-126a-5p levels were markedly regulated by CSC exposure (P < 0.01). The interactions of miR-291a-3p and miR-126a-5p with AMPK and CYP7A1 mRNA were also validated by the DLRG method.

Conclusions

In summary, the rat dyslipidemia induced by CSC exposure may be related to the interference of gut microbiota structure and interaction of miRNAs from serum exosomes with target mRNAs, which further regulated AMPK-ACC/CYP7A1 signaling in rats.

Association between the Extent of Peripheral Blood DNA Methylation of HIF3A and Accumulation of Adiposity in community-dwelling Women: The Yakumo Study

INTRODUCTION

DNA methylation in the CpG sites of intron 1 of HIF3A is associated with body mass index (BMI). This cross-sectional study investigated correlations between DNA methylation of HIF3A and BMI or adiposity parameters in the Japanese population.

METHOD

DNA methylation of HIF3A was quantified via pyrosequencing.

RESULT

DNA methylation of HIF3A differed only in women; DNA methylation level at cg27146050 was associated with visceral adipose tissue thickness and correlated with BMI and percent (%) body fat after excluding smokers.

CONCLUSION

Peripheral blood DNA methylation at the CpG site (cg27146050) of HIF3A correlated with VAT thickness in Japanese women.

Predicting risk of lung function impairment and all-cause mortality using a DNA methylation-based classifier of tobacco smoke exposure

BACKGROUND

The Epigenetic Smoking Status Estimator (EpiSmokEr) predicts smoking phenotypes based on DNA methylation at 121 CpG sites.

OBJECTIVE

Evaluate associations of EpiSmokEr-predicted versus self-reported smoking phenotypes with lung function and all-cause mortality in a cohort of older adults.

METHODS

The prospective Normative Aging Study collected DNA methylation measurements from 1999 to 2012 with follow-up through 2016. The R package EpiSmokEr derived predicted smoking phenotypes based on DNA methylation levels assayed by the Illumina HumanMethylation450 Beadchip. Spirometry was collected every 3-5 years. Airflow limitation was defined as forced expiratory volume in 1 s/forced vital capacity <0.7. Vital status was monitored through periodic mailings.

RESULTS

Among 784 participants contributing 5414 person-years of follow-up, the EpiSmokEr-predicted smoking phenotypes matched the self-reported phenotypes for 228 (97%) never smokers and 22 (71%) current smokers. In contrast, EpiSmokEr classified 407 (79%) self-reported former smokers as never smokers. Nonetheless, the EpiSmokEr-predicted former smoking phenotype was more strongly associated with incident airflow limitation (hazard ratio [HR] = 3.15, 95% confidence interval [CI] = 1.50-6.59) and mortality (HR = 2.11, 95% CI = 1.56-2.85) compared to the self-reported former smoking phenotype (airflow limitation: HR = 2.21, 95% CI = 1.13-4.33; mortality: HR = 1.08, 95% CI = 0.86-1.36). Risk of airflow limitation and death did not differ among self-reported never smokers and former smokers who were classified as never smokers. The discriminative accuracy of EpiSmokEr-predicted phenotypes for incident airflow limitation and mortality was improved compared to self-reported phenotypes.

CONCLUSIONS

The DNA methylation-based EpiSmokEr classifier may be a useful surrogate of smoking-induced lung damage and may identify former smokers most at risk of adverse smoking-related health effects.

Early life adversity and age acceleration at mid-life and older ages indexed using the next-generation GrimAge and Pace of Aging epigenetic clocks

OBJECTIVE

This retrospective cross-sectional study was designed to explore whether the experience of childhood adversity was associated with epigenetic age acceleration in mid-life and older ages using the next generation GrimAge and Pace of Aging DNA methylation clocks.

METHOD

The study involved a sub-sample of 490 individuals aged 50-87 years of age participating in the Irish Longitudinal Study on Aging (TILDA); a large nationally representative prospective cohort study of aging in Ireland. Childhood adversity was ascertained via self-report using 5-items that were deemed to indicate potentially nefarious childhood exposures, including growing up poor, death of a parent, parental substance abuse in the family, childhood physical abuse, and childhood sexual abuse.

RESULTS

Only childhood poverty was associated with significant epigenetic age acceleration according to the GrimAge and Pace of Aging clocks, hastening biological aging by 2.04 years [CI= 1.07, 3.00; p < 0.001] and 1.16 years [CI= 0.11, 2.21; p = 0.030] respectively. Analysis of the dose-response pattern revealed each additional adversity was associated with 0.69 years of age acceleration [CI= 0.23, 1.15; p = 0.004] according to the GrimAge clock. Mediation analysis suggested that lifetime smoking explains a substantial portion (>50%) of the excess risk of age acceleration amongst those who experienced childhood poverty.

CONCLUSIONS

This study adds to the growing body of evidence which implicates early life adversity, particularly deprivation as a potential precipitant of earlier biological aging, and implicates smoking-related changes to DNA methylation processes as a candidate pathway and mechanism through which the social environment gets transduced at a biological level to hasten the aging process.

DNA Methylation Abnormalities and Altered Whole Transcriptome Profiles after Switching from Combustible Tobacco Smoking to Heated Tobacco Products

BACKGROUND

The use of heated tobacco products (HTP) has increased exponentially in Japan since 2016; however, their effects on health remain a major concern.

METHODS

Tsuruoka Metabolome Cohort Study participants (n = 11,002) were grouped on the basis of their smoking habits as never smokers (NS), past smokers (PS), combustible tobacco smokers (CS), and HTP users for <2 years. Peripheral blood mononuclear cells were collected from 52 participants per group matched to HTP users using propensity scores, and DNA and RNA were purified from the samples. DNA methylation (DNAm) analysis of the 17 smoking-associated DNAm biomarker genes (such as AHRR, F2RL3, LRRN3, and GPR15), as well as whole transcriptome analysis, was performed.

RESULTS

Ten of the 17 genes were significantly hypomethylated in CS and HTP users compared with NS, among which AHRR, F2RL3, and RARA showed intermediate characteristics between CS and NS; nonetheless, AHRR expression was significantly higher in CS than in the other three groups. Conversely, LRRN3 and GPR15 were more hypomethylated in HTP users than in NS, and GPR15 expression was markedly upregulated in all the groups when compared with that in NS.

CONCLUSIONS

HTP users (switched from CS <2 years) display abnormal DNAm and transcriptome profiles, albeit to a lesser extent than the CS. However, because the molecular genetic effects of long-term HTP use are still unknown, long-term molecular epidemiologic studies are needed.

IMPACT

This study provides new insights into the molecular genetic effects on DNAm and transcriptome profiles in HTP users who switched from CS.

DNA methylation in genes associated with the evolution of ageing and disease: A critical review

Ageing is characterised by a physical decline in biological functioning which results in a progressive risk of mortality with time. As a biological phenomenon, it is underpinned by the dysregulation of a myriad of complex processes. Recently, however, ever-increasing evidence has associated epigenetic mechanisms, such as DNA methylation (DNAm) with age-onset pathologies, including cancer, cardiovascular disease, and Alzheimer's disease. These diseases compromise healthspan. Consequently, there is a medical imperative to understand the link between epigenetic ageing, and healthspan. Evolutionary theory provides a unique way to gain new insights into epigenetic ageing and health. This review will: (1) provide a brief overview of the main evolutionary theories of ageing; (2) discuss recent genetic evidence which has revealed alleles that have pleiotropic effects on fitness at different ages in humans; (3) consider the effects of DNAm on pleiotropic alleles, which are associated with age related disease; (4) discuss how age related DNAm changes resonate with the mutation accumulation, disposable soma and programmed theories of ageing; (5) discuss how DNAm changes associated with caloric restriction intersect with the evolution of ageing; and (6) conclude by discussing how evolutionary theory can be used to inform investigations which quantify age-related DNAm changes which are linked to age onset pathology.

Smoking, DNA Methylation, and Breast Cancer: A Mendelian Randomization Study

Background

Smoking was strongly associated with breast cancer in previous studies. Whether smoking promotes breast cancer through DNA methylation remains unknown.

Methods

Two-sample Mendelian randomization (MR) analyses were conducted to assess the causal effect of smoking-related DNA methylation on breast cancer risk. We used 436 smoking-related CpG sites extracted from 846 middle-aged women in the ARIES project as exposure data. We collected summary data of breast cancer from one of the largest meta-analyses, including 69,501 cases for ER+ breast cancer and 21,468 cases for ER- breast cancer. A total of 485 single-nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs) for smoking-related DNA methylation. We further performed an MR Steiger test to estimate the likely direction of causal estimate between DNA methylation and breast cancer. We also conducted colocalization analysis to evaluate whether smoking-related CpG sites shared a common genetic causal SNP with breast cancer in a given region.

Results

We established four significant associations after multiple testing correction: the CpG sites of cg2583948 [OR = 0.94, 95% CI (0.91-0.97)], cg0760265 [OR = 1.07, 95% CI (1.03-1.11)], cg0420946 [OR = 0.95, 95% CI (0.93-0.98)], and cg2037583 [OR =1.09, 95% CI (1.04-1.15)] were associated with the risk of ER+ breast cancer. All the four smoking-related CpG sites had a larger variance than that in ER+ breast cancer (all p < 1.83 × 10^-11) in the MR Steiger test. Further colocalization analysis showed that there was strong evidence (based on PPH4 > 0.8) supporting a common genetic causal SNP between the CpG site of cg2583948 [with IMP3 expression (PPH4 = 0.958)] and ER+ breast cancer. There were no causal associations between smoking-related DNA methylation and ER- breast cancer.

Conclusions

These findings highlight potential targets for the prevention of ER+ breast cancer. Tissue-specific epigenetic data are required to confirm these results.

The Role of GPR15 Function in Blood and Vasculature

Since the first prominent description of the orphan G protein-coupled receptor 15 (GPR15) on lymphocytes as a co-receptor for the human immunodeficiency virus (HIV) type 1 and 2 and the first report about the GPR15-triggered cytoprotective effect on vascular endothelial cells by recombinant human thrombomodulin, several decades passed before the GPR15 has been recently deorphanized. Because of new findings on GPR15, this review will summarize the consequences of GPR15 signaling considering the variety of GPR15-expressing cell types and of GPR15 ligands, with a focus on blood and vasculature.

Epigenetic Alterations of Maternal Tobacco Smoking during Pregnancy: A Narrative Review

In utero exposure to maternal tobacco smoking is the leading cause of birth complications in addition to being associated with later impairment in child's development. Epigenetic alterations, such as DNA methylation (DNAm), miRNAs expression, and histone modifications, belong to possible underlying mechanisms linking maternal tobacco smoking during pregnancy and adverse birth outcomes and later child's development. The aims of this review were to provide an update on (1) the main results of epidemiological studies on the impact of in utero exposure to maternal tobacco smoking on epigenetic mechanisms, and (2) the technical issues and methods used in such studies. In contrast with miRNA and histone modifications, DNAm has been the most extensively studied epigenetic mechanism with regard to in utero exposure to maternal tobacco smoking. Most studies relied on cord blood and children's blood, but placenta is increasingly recognized as a powerful tool, especially for markers of pregnancy exposures. Some recent studies suggest reversibility in DNAm in certain genomic regions as well as memory of smoking exposure in DNAm in other regions, upon smoking cessation before or during pregnancy. Furthermore, reversibility could be more pronounced in miRNA expression compared to DNAm. Increasing evidence based on longitudinal data shows that maternal smoking-associated DNAm changes persist during childhood. In this review, we also discuss some issues related to cell heterogeneity as well as downstream statistical analyses used to relate maternal tobacco smoking during pregnancy and epigenetics. The epigenetic effects of maternal smoking during pregnancy have been among the most widely investigated in the epigenetic epidemiology field. However, there are still huge gaps to fill in, including on the impact on miRNA expression and histone modifications to get a better view of the whole epigenetic machinery. The consistency of maternal tobacco smoking effects across epigenetic marks and across tissues will also provide crucial information for future studies. Advancement in bioinformatic and biostatistics approaches is key to develop a comprehensive analysis of these biological systems.

Biomarkers for Heart Failure Prognosis: Proteins, Genetic Scores and Non-coding RNAs

Heart failure (HF) is a complex disease in which cardiomyocyte injury leads to a cascade of inflammatory and fibrosis pathway activation, thereby causing decrease in cardiac function. As a result, several biomolecules are released which can be identified easily in circulating body fluids. The complex biological processes involved in the development and worsening of HF require an early treatment strategy to stop deterioration of cardiac function. Circulating biomarkers provide not only an ideal platform to detect subclinical changes, their clinical application also offers the opportunity to monitor disease treatment. Many of these biomarkers can be quantified with high sensitivity; allowing their clinical application to be evaluated beyond diagnostic purposes as potential tools for HF prognosis. Though the field of biomarkers is dominated by protein molecules, non-coding RNAs (microRNAs, long non-coding RNAs, and circular RNAs) are novel and promising biomarker candidates that encompass several ideal characteristics required in the biomarker field. The application of genetic biomarkers as genetic risk scores in disease prognosis, albeit in its infancy, holds promise to improve disease risk estimation. Despite the multitude of biomarkers that have been available and identified, the majority of novel biomarker candidates are not cardiac-specific, and instead may simply be a readout of systemic inflammation or other pathological processes. Thus, the true value of novel biomarker candidates in HF prognostication remains unclear. In this article, we discuss the current state of application of protein, genetic as well as non-coding RNA biomarkers in HF risk prognosis.