Cigarette smoking reduces DNA methylation levels at multiple genomic loci but the effect is partially reversible upon cessation

A comprehensive lifestyle index and its associations with DNA methylation and type 2 diabetes among Ghanaian adults: the rodam study

BACKGROUND

A series of modifiable lifestyle factors, such as diet quality, physical activity, alcohol intake, and smoking, may drive the rising burden of type 2 diabetes (T2DM) among sub-Saharan Africans globally. It is unclear whether epigenetic changes play a mediatory role in the associations between these lifestyle factors and T2DM. We assessed the associations between a comprehensive lifestyle index, DNA methylation and T2DM among Ghanaian adults.

METHODS

We used whole-blood Illumina 450 k DNA methylation data from 713 Ghanaians from the Research on Obesity and Diabetes among African Migrants (RODAM) study. We constructed a comprehensive lifestyle index based on established cut-offs for diet quality, physical activity, alcohol intake, and smoking status. In the T2DM-free discovery cohort (n = 457), linear models were fitted to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs) associated with the lifestyle index after adjustment for age, sex, body mass index (BMI), and technical covariates. Associations between the identified DMPs and the primary outcome (T2DM), as well as secondary outcomes (fasting blood glucose (FBG) and HbA1c), were determined via logistic and linear regression models, respectively.

RESULTS

In the present study population (mean age: 52 ± 10 years; male: 42.6%), the comprehensive lifestyle index showed a significant association with one DMP annotated to an intergenic region on chromosome 7 (false discovery rate (FDR) = 0.024). Others were annotated to ADCY7, SMARCE1, AHRR, LOXL2, and PTBP1 genes. One DMR was identified and annotated to the GFPT2 gene (familywise error rate (FWER) from bumphunter bootstrap = 0.036). None of the DMPs showed significant associations with T2DM; directions of effect were positive for the DMP in the AHRR and inverse for all the other DMPs. Higher methylation of the ADCY7 DMP was associated with higher FBG (p = 0.024); LOXL2 DMP was associated with lower FBG (p = 0.023) and HbA1c (p = 0.049); and PTBP1 DMP was associated with lower HbA1c (p = 0.002).

CONCLUSIONS

In this explorative epigenome-wide association study among Ghanaians, we identified one DMP and DMR associated with a comprehensive lifestyle index not previously associated with individual lifestyle factors. Based on our findings, we infer that lifestyle factors in combination, affect DNA methylation, thereby influencing the risk of T2DM among Ghanaian adults living in different contexts.

A comprehensive map of the aging blood methylome in humans

BACKGROUND

During aging, the human methylome undergoes both differential and variable shifts, accompanied by increased entropy. The distinction between variably methylated positions (VMPs) and differentially methylated positions (DMPs), their contribution to epigenetic age, and the role of cell type heterogeneity remain unclear.

RESULTS

We conduct a comprehensive analysis of > 32,000 human blood methylomes from 56 datasets (age range = 6-101 years). We find a significant proportion of the blood methylome that is differentially methylated with age (48% DMPs; FDR < 0.005) and variably methylated with age (37% VMPs; FDR < 0.005), with considerable overlap between the two groups (59% of DMPs are VMPs). Bivalent and Polycomb regions become increasingly methylated and divergent between individuals, while quiescent regions lose methylation more uniformly. Both chronological and biological clocks, but not pace-of-aging clocks, show a strong enrichment for CpGs undergoing both mean and variance changes during aging. The accumulation of DMPs shifting towards a methylation fraction of 50% drives the increase in entropy, smoothening the epigenetic landscape. However, approximately a quarter of DMPs exhibit anti-entropic effects, opposing this direction of change. While changes in cell type composition minimally affect DMPs, VMPs and entropy measurements are moderately sensitive to such alterations.

CONCLUSION

This study represents the largest investigation to date of genome-wide DNA methylation changes and aging in a single tissue, providing valuable insights into primary molecular changes relevant to chronological and biological aging.

Development of an epigenetic clock resistant to changes in immune cell composition

Epigenetic clocks are age predictors that use machine-learning models trained on DNA CpG methylation values to predict chronological or biological age. Increases in predicted epigenetic age relative to chronological age (epigenetic age acceleration) are connected to aging-associated pathologies, and changes in epigenetic age are linked to canonical aging hallmarks. However, epigenetic clocks rely on training data from bulk tissues whose cellular composition changes with age. Here, we found that human naive CD8+ T cells, which decrease in frequency during aging, exhibit an epigenetic age 15-20 years younger than effector memory CD8+ T cells from the same individual. Importantly, homogenous naive T cells isolated from individuals of different ages show a progressive increase in epigenetic age, indicating that current epigenetic clocks measure two independent variables, aging and immune cell composition. To isolate the age-associated cell intrinsic changes, we created an epigenetic clock, the IntrinClock, that did not change among 10 immune cell types tested. IntrinClock shows a robust predicted epigenetic age increase in a model of replicative senescence in vitro and age reversal during OSKM-mediated reprogramming.

Objective Assessments of Smoking and Drinking Outperform Clinical Phenotypes in Predicting Variance in Epigenetic Aging

The reliability of the associations of the acceleration of epigenetic aging (EA) indices with clinical phenotypes other than for smoking and drinking is poorly understood. Furthermore, the majority of clinical phenotyping studies have been conducted using data from subjects of European ancestry. In order to address these limitations, we conducted clinical, physiologic, and epigenetic assessments of a cohort of 278 middle-aged African American adults and analyzed the associations with the recently described principal-components-trained version of GrimAge (i.e., PC-GrimAge) and with the DunedinPACE (PACE) index using regression analyses. We found that 74% of PC-GrimAge accelerated aging could be predicted by a simple baseline model consisting of age, sex, and methylation-sensitive digital PCR (MSdPCR) assessments of smoking and drinking. The addition of other serological, demographic, and medical history variables or PACE values did not meaningfully improve the prediction, although some variables did significantly improve the model fit. In contrast, clinical variables mapping to cardiometabolic syndrome did independently contribute to the prediction of PACE values beyond the baseline model. The PACE values were poorly correlated with the GrimAge values (r = 0.2), with little overlap in variance explained other than that conveyed by smoking and drinking. The results suggest that EA indices may differ in the clinical information that they provide and may have significant limitations as screening tools to guide patient care.

TNF Promoter Hypomethylation Is Associated With Mucosal Inflammation in IBD and Anti-TNF Response

Background and Aims

Inflammatory bowel diseases (IBDs) are chronic inflammatory conditions influenced heavily by environmental factors. DNA methylation is a form of epigenetic regulation linking environmental stimuli to gene expression changes and inflammation. Here, we investigated how DNA methylation of the tumor necrosis factor (TNF) promoter differs between inflamed and uninflamed mucosa of IBD patients, including anti-TNF responders and nonresponders.

Methods

We obtained mucosal biopsies from 200 participants (133 IBDs and 67 controls) and analyzed TNF promoter methylation using bisulfite sequencing, comparing inflamed with uninflamed segments, in addition to paired inflamed/uninflamed samples from individual patients. We conducted similar analyses on purified intestinal epithelial cells from bowel resections. We also compared TNF methylation levels of inflamed and uninflamed mucosa from a separate cohort of 15 anti-TNF responders and 17 nonresponders. Finally, we sequenced DNA methyltransferase genes to identify rare variants in IBD patients and functionally tested them using rescue experiments in a zebrafish genetic model of DNA methylation deficiency.

Results

TNF promoter methylation levels were decreased in inflamed mucosa of IBD patients and correlated with disease severity. Isolated intestinal epithelial cells from inflamed tissue showed proportional decreases in TNF methylation. Anti-TNF nonresponders showed lower levels of TNF methylation than responders in uninflamed mucosa. Our sequencing analysis revealed 2 missense variants in DNA methyltransferase 1, 1 of which had reduced function in vivo.

Conclusion

Our study reveals an association of TNF promoter hypomethylation with mucosal inflammation, suggesting that IBD patients may be particularly sensitive to inflammatory environmental insults affecting DNA methylation. Together, our analyses indicate that TNF promoter methylation analysis may aid in the characterization of IBD status and evaluation of anti-TNF therapy response.

Aging clocks based on accumulating stochastic variation

Aging clocks have provided one of the most important recent breakthroughs in the biology of aging, and may provide indicators for the effectiveness of interventions in the aging process and preventive treatments for age-related diseases. The reproducibility of accurate aging clocks has reinvigorated the debate on whether a programmed process underlies aging. Here we show that accumulating stochastic variation in purely simulated data is sufficient to build aging clocks, and that first-generation and second-generation aging clocks are compatible with the accumulation of stochastic variation in DNA methylation or transcriptomic data. We find that accumulating stochastic variation is sufficient to predict chronological and biological age, indicated by significant prediction differences in smoking, calorie restriction, heterochronic parabiosis and partial reprogramming. Although our simulations may not explicitly rule out a programmed aging process, our results suggest that stochastically accumulating changes in any set of data that have a ground state at age zero are sufficient for generating aging clocks.

An improved epigenetic counter to track mitotic age in normal and precancerous tissues

The cumulative number of stem cell divisions in a tissue, known as mitotic age, is thought to be a major determinant of cancer-risk. Somatic mutational and DNA methylation (DNAm) clocks are promising tools to molecularly track mitotic age, yet their relationship is underexplored and their potential for cancer risk prediction in normal tissues remains to be demonstrated. Here we build and validate an improved pan-tissue DNAm counter of total mitotic age called stemTOC. We demonstrate that stemTOC's mitotic age proxy increases with the tumor cell-of-origin fraction in each of 15 cancer-types, in precancerous lesions, and in normal tissues exposed to major cancer risk factors. Extensive benchmarking against 6 other mitotic counters shows that stemTOC compares favorably, specially in the preinvasive and normal-tissue contexts. By cross-correlating stemTOC to two clock-like somatic mutational signatures, we confirm the mitotic-like nature of only one of these. Our data points towards DNAm as a promising molecular substrate for detecting mitotic-age increases in normal tissues and precancerous lesions, and hence for developing cancer-risk prediction strategies.

Inference of tobacco and alcohol consumption habits from DNA methylation analysis of blood

DNA methylation has become a biomarker of great interest in the forensic and clinical fields. In criminal investigations, the study of this epigenetic marker has allowed the development of DNA intelligence tools providing information that can be useful for investigators, such as age prediction. Following a similar trend, when the origin of a sample in a criminal scenario is unknown, the inference of an individual's lifestyle such as tobacco use and alcohol consumption could provide relevant information to help in the identification of DNA donors at the crime scene. At the same time, in the clinical domain, prediction of these trends of consumption could allow the identification of people at risk or better identification of the causes of different pathologies. In the present study, DNA methylation data from the UK AIRWAVE study was used to build two binomial logistic models for the inference of smoking and drinking status. A total of 348 individuals (116 non-smokers, 116 former smokers and 116 smokers) plus a total of 237 individuals (79 non-drinkers, 79 moderate drinkers and 79 drinkers) were used for development of tobacco and alcohol consumption prediction models, respectively. The tobacco prediction model was composed of two CpGs (cg05575921 in AHRR and cg01940273) and the alcohol prediction model three CpGs (cg06690548 in SLC7A11, cg0886875 and cg21294714 in MIR4435-2HG), providing correct classifications of 86.49% and 74.26%, respectively. Validation of the models was performed using leave-one-out cross-validation. Additionally, two independent testing sets were also assessed for tobacco and alcohol consumption. Considering that the consumption of these substances could underlie accelerated epigenetic ageing patterns, the effect of these lifestyles on the prediction of age was evaluated. To do that, a quantile regression model based on previous studies was generated, and the potential effect of tobacco and alcohol consumption with the epigenetic age was assessed. The Wilcoxon test was used to evaluate the residuals generated by the model and no significant differences were observed between the categories analyzed.

Cigarette smoking combined with genetic variation regulates the m6A methylation of CRNKL1 and is associated with bladder cancer risk

Cigarette smoking was known to accelerate the occurrence and development of bladder cancer by regulating RNA modification. However, the association between the combination of cigarette smoking and RNA modification-related single nucleotide polymorphisms (RNAm-SNPs) and bladder cancer risk remains unclear. In this study, 1681 participants, including 580 cases and 1101 controls, were recruited for genetic association analysis. In total, 1 287 990 RNAm-SNPs involving nine RNA modifications (m6A, m1A, m6Am, 2'-O-Me, m5C, m7G, A-to-I, m5U, and pseudouridine modification) were obtained from the RMVar database. The interactive effect of cigarette smoking and RNAm-SNPs on bladder cancer risk was assessed through joint analysis. The susceptibility analysis revealed that 89 RNAm-SNPs involving m6A, m1A, and A-to-I modifications were associated with bladder cancer risk. Among them, m6A-related rs2273058 in CRNKL1 was associated with bladder cancer risk (odds ratios (OR) = 1.35, padj = 1.78 × 10-4), and CRNKL1 expression was increased in bladder cancer patients (p = 0.035). Cigarette smoking combined with the A allele of rs2273058 increased bladder cancer risk compared with nonsmokers with the G allele of rs2273058 (OR = 2.40, padj = 3.11 × 10-9). Mechanistically, the A allele of rs2273058 endowed CRNKL1 with an additional m6A motif, facilitating recognition by m6A reader IGF2BP1, thereby promoting CRNKL1 expression under cigarette smoking (r = 0.142, p = 0.017). Moreover, elevated CRNKL1 expression may accelerate cell cycle and proliferation, thereby increasing bladder cancer risk. In summary, our study demonstrated that cigarette smoking combined with RNAm-SNPs contributes to bladder cancer risk, which provides a potential target for bladder cancer prevention.

The race-based stress reduction intervention (RiSE) study on African American women in NYC and Chicago: Design and methods for complex genomic analysis

RiSE study aims to evaluate a race-based stress-reduction intervention as an effective strategy to improve coping and decrease stress-related symptoms, inflammatory burden, and modify DNA methylation of stress response-related genes in older AA women. This article will describe genomic analytic methods to be utilized in this longitudinal, randomized clinical trial of older adult AA women in Chicago and NYC that examines the effect of the RiSE intervention on DNAm pre- and post-intervention, and its overall influence on inflammatory burden. Salivary DNAm will be measured at baseline and 6 months following the intervention, using the Oragene-DNA kit. Measures of perceived stress, depressive symptoms, fatigue, sleep, inflammatory burden, and coping strategies will be assessed at 4 time points including at baseline, 4 weeks, 8 weeks, and 6 months. Genomic data analysis will include the use of pre-processed and quality-controlled methylation data expressed as beta (β) values. Association analyses will be performed to detect differentially methylated sites on the targeted candidate genes between the intervention and non-intervention groups using the Δβ (changes in methylation) with adjustment for age, health behaviors, early life adversity, hybridization batch, and top principal components of the probes as covariates. To account for multiple testing, we will use FDR adjustment with a corrected p-value of <0.05 regarded as statistically significant. To assess the relationship between inflammatory burden and Δβ among the study samples, we will repeat association analyses with the inclusion of individual inflammation protein measures. ANCOVA will be used because it is more statistically powerful to detect differences.

TNF promoter hypomethylation is associated with mucosal inflammation in IBD and anti-TNF response

Background and aims

Inflammatory Bowel Diseases (IBD) are chronic inflammatory conditions influenced heavily by environmental factors. DNA methylation is a form of epigenetic regulation linking environmental stimuli to gene expression changes and inflammation. Here, we investigated how DNA methylation of the TNF promoter differs between inflamed and uninflamed mucosa of IBD patients, including anti-TNF responders and non-responders.

Methods

We obtained mucosal biopsies from 200 participants (133 IBD and 67 controls) and analyzed TNF promoter methylation using bisulfite sequencing, comparing inflamed with uninflamed segments, in addition to paired inflamed/uninflamed samples from individual patients. We conducted similar analyses on purified intestinal epithelial cells from bowel resections. We also compared TNF methylation levels of inflamed and uninflamed mucosa from a separate cohort of 15 anti-TNF responders and 17 non-responders. Finally, we sequenced DNA methyltransferase genes to identify rare variants in IBD patients and functionally tested them using rescue experiments in a zebrafish genetic model of DNA methylation deficiency.

Results

TNF promoter methylation levels were decreased in inflamed mucosa of IBD patients and correlated with disease severity. Isolated IECs from inflamed tissue showed proportional decreases in TNF methylation. Anti-TNF non-responders showed lower levels of TNF methylation than responders in uninflamed mucosa. Our sequencing analysis revealed two missense variants in DNMT1, one of which had reduced function in vivo.

Conclusions

Our study reveals an association of TNF promoter hypomethylation with mucosal inflammation, suggesting that IBD patients may be particularly sensitive to inflammatory environmental insults affecting DNA methylation. Together, our analyses indicate that TNF promoter methylation analysis may aid in the characterization of IBD status and evaluation of anti-TNF therapy response.

Comprehensive evaluation of smoking exposures and their interactions on DNA methylation

BACKGROUND

Smoking impacts DNA methylation, but data are lacking on smoking-related differential methylation by sex or dietary intake, recent smoking cessation (<1 year), persistence of differential methylation from in utero smoking exposure, and effects of environmental tobacco smoke (ETS).

METHODS

We meta-analysed data from up to 15,014 adults across 5 cohorts with DNA methylation measured in blood using Illumina's EPIC array for current smoking (2560 exposed), quit < 1 year (500 exposed), in utero (286 exposed), and ETS exposure (676 exposed). We also evaluated the interaction of current smoking with sex or diet (fibre, folate, and vitamin C).

FINDINGS

Using false discovery rate (FDR < 0.05), 65,857 CpGs were differentially methylated in relation to current smoking, 4025 with recent quitting, 594 with in utero exposure, and 6 with ETS. Most current smoking CpGs attenuated within a year of quitting. CpGs related to in utero exposure in adults were enriched for those previously observed in newborns. Differential methylation by current smoking at 4-71 CpGs may be modified by sex or dietary intake. Nearly half (35-50%) of differentially methylated CpGs on the 450 K array were associated with blood gene expression. Current smoking and in utero smoking CpGs implicated 3049 and 1067 druggable targets, including chemotherapy drugs.

INTERPRETATION

Many smoking-related methylation sites were identified with Illumina's EPIC array. Most signals revert to levels observed in never smokers within a year of cessation. Many in utero smoking CpGs persist into adulthood. Smoking-related druggable targets may provide insights into cancer treatment response and shared mechanisms across smoking-related diseases.

FUNDING

Intramural Research Program of the National Institutes of Health, Norwegian Ministry of Health and Care Services and the Ministry of Education and Research, Chief Scientist Office of the Scottish Government Health Directorates and the Scottish Funding Council, Medical Research Council UK and the Wellcome Trust.

Traffic Density Exposure, Oxidative Stress Biomarkers and Plasma Metabolomics in a Population-Based Sample: The Hortega Study

Exposure to traffic-related air pollution (TRAP) generates oxidative stress, with downstream effects at the metabolic level. Human studies of traffic density and metabolomic markers, however, are rare. The main objective of this study was to evaluate the cross-sectional association between traffic density in the street of residence with oxidative stress and metabolomic profiles measured in a population-based sample from Spain. We also explored in silico the potential biological implications of the findings. Secondarily, we assessed the contribution of oxidative stress to the association between exposure to traffic density and variation in plasma metabolite levels. Traffic density was defined as the average daily traffic volume over an entire year within a buffer of 50 m around the participants' residence. Plasma metabolomic profiles and urine oxidative stress biomarkers were measured in samples from 1181 Hortega Study participants by nuclear magnetic resonance spectroscopy and high-performance liquid chromatography, respectively. Traffic density was associated with 7 (out of 49) plasma metabolites, including amino acids, fatty acids, products of bacterial and energy metabolism and fluid balance metabolites. Regarding urine oxidative stress biomarkers, traffic associations were positive for GSSG/GSH% and negative for MDA. A total of 12 KEGG pathways were linked to traffic-related metabolites. In a protein network from genes included in over-represented pathways and 63 redox-related candidate genes, we observed relevant proteins from the glutathione cycle. GSSG/GSH% and MDA accounted for 14.6% and 12.2% of changes in isobutyrate and the CH2CH2CO fatty acid moiety, respectively, which is attributable to traffic exposure. At the population level, exposure to traffic density was associated with specific urine oxidative stress and plasma metabolites. Although our results support a role of oxidative stress as a biological intermediary of traffic-related metabolic alterations, with potential implications for the co-bacterial and lipid metabolism, additional mechanistic and prospective studies are needed to confirm our findings.

Stability of DNA-Methylation Profiles of Biological Aging in Children and Adolescents

Background and Objectives

Methylation profile scores (MPSs) index biological aging and aging-related disease in adults and are cross-sectionally associated with social determinants of health in childhood. MPSs thus provide an opportunity to trace how aging-related biology responds to environmental changes in early life. Information regarding the stability of MPSs in early life is currently lacking.

Method

We use longitudinal data from children and adolescents ages 8-18 (N = 428, M age = 12.15 years) from the Texas Twin Project. Participants contributed two waves of salivary DNA-methylation data (mean lag = 3.94 years), which were used to construct four MPSs reflecting multi-system physiological decline and mortality risk (PhenoAgeAccel and GrimAgeAccel), pace of biological aging (DunedinPACE), and cognitive function (Epigenetic-g). Furthermore, we exploit variation among participants in whether they were exposed to the COVID-19 pandemic during the course of study participation, in order to test how a historical period characterized by environmental disruption might affect children's aging-related MPSs.

Results

All MPSs showed moderate longitudinal stability (test-retest rs = 0.42, 0.44, 0.46, 0.51 for PhenoAgeAccel, GrimAgeAccel, and Epigenetic-g, and DunedinPACE, respectively). No differences in the stability of MPSs were apparent between those whose second assessment took place after the onset of the COVID-19 pandemic vs. those for whom both assessments took place prior to the pandemic.

Conclusions

Aging-related DNA-methylation patterns are less stable in childhood than has been previously observed in adulthood. Further developmental research on the methylome is necessary to understand which environmental perturbations in childhood impact trajectories of biological aging and when children are most sensitive to those impacts.

A roadmap for social determinants of health and biological nursing research in the National Institute of Nursing Research 2022-2026 Strategic Plan: Optimizing health and advancing health equity using antiracist framing

BACKGROUND

Health equity is essential for improving the well-being of all individuals and groups, and research remains a critical element for understanding barriers to health equity. While considering how to best support research that acknowledges current health challenges, it is crucial to understand the role of social justice frameworks within health equity research and the contributions of minoritized researchers. Additionally, there should be an increased understanding of the influence of social determinants of health on biological mechanisms.

PURPOSE

Biological health equity research seeks to understand and address health disparities among historically excluded populations.

DISCUSSION

While there are examples of studies in this area led by minoritized researchers, some individuals and groups remain understudied due to underfunding. Research within minoritized populations must be prioritized to authentically achieve health equity. Furthermore, there should be increased funding from National Institutes of Health to support minoritized researchers working in this area.

DNA Methylation Patterns in Relation to Acute Severity and Duration of Anxiety and Depression

Depression and anxiety are common mental disorders that often occur together. Stress is an important risk factor for both disorders, affecting pathophysiological processes through epigenetic changes that mediate gene-environment interactions. In this study, we explored two proposed models about the dynamic nature of DNA methylation in anxiety and depression: a stable change, in which DNA methylation accumulates over time as a function of the duration of clinical symptoms of anxiety and depression, or a flexible change, in which DNA methylation correlates with the acute severity of clinical symptoms. Symptom severity was assessed using clinical questionnaires for anxiety and depression (BDI-II, IDS-C, and HAM-A), and the current episode and the total lifetime symptom duration was obtained from patients' medical records. Peripheral blood DNA methylation levels were determined for the BDNF, COMT, and SLC6A4 genes. We found a significant negative correlation between COMT_1 amplicon methylation and acute symptom scores, with BDI-II (R(22) = 0.190, p = 0.033), IDS-C (R(22) = 0.199, p = 0.029), and HAM-A (R(22) = 0.231, p = 0.018) all showing a similar degree of correlation. Our results suggest that DNA methylation follows flexible dynamics, with methylation levels closely associated with acute clinical presentation rather than with the duration of anxiety and depression. These results provide important insights into the dynamic nature of DNA methylation in anxiety and affective disorders and contribute to our understanding of the complex interplay between stress, epigenetics, and individual phenotype.

Implication of DNA methylation during lifestyle mediated weight loss

Over the past 50 years, the number of overweight/obese people increased significantly, making obesity a global public health challenge. Apart from rare monogenic forms, obesity is a multifactorial disease, most likely resulting from a concerted interaction of genetic, epigenetic and environmental factors. Although recent studies opened new avenues in elucidating the complex genetics behind obesity, the biological mechanisms contributing to individual's risk to become obese are not yet fully understood. Non-genetic factors such as eating behaviour or physical activity are strong contributing factors for the onset of obesity. These factors may interact with genetic predispositions most likely via epigenetic mechanisms. Epigenome-wide association studies or methylome-wide association studies are measuring DNA methylation at single CpGs across thousands of genes and capture associations to obesity phenotypes such as BMI. However, they only represent a snapshot in the complex biological network and cannot distinguish between causes and consequences. Intervention studies are therefore a suitable method to control for confounding factors and to avoid possible sources of bias. In particular, intervention studies documenting changes in obesity-associated epigenetic markers during lifestyle driven weight loss, make an important contribution to a better understanding of epigenetic reprogramming in obesity. To investigate the impact of lifestyle in obesity state specific DNA methylation, especially concerning the development of new strategies for prevention and individual therapy, we reviewed 19 most recent human intervention studies. In summary, this review highlights the huge potential of targeted interventions to alter disease-associated epigenetic patterns. However, there is an urgent need for further robust and larger studies to identify the specific DNA methylation biomarkers which influence obesity.

A meta-analysis of immune-cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes

BACKGROUND

Changes in cell-type composition of tissues are associated with a wide range of diseases and environmental risk factors and may be causally implicated in disease development and progression. However, these shifts in cell-type fractions are often of a low magnitude, or involve similar cell subtypes, making their reliable identification challenging. DNA methylation profiling in a tissue like blood is a promising approach to discover shifts in cell-type abundance, yet studies have only been performed at a relatively low cellular resolution and in isolation, limiting their power to detect shifts in tissue composition.

METHODS

Here we derive a DNA methylation reference matrix for 12 immune-cell types in human blood and extensively validate it with flow-cytometric count data and in whole-genome bisulfite sequencing data of sorted cells. Using this reference matrix, we perform a directional Stouffer and fixed effects meta-analysis comprising 23,053 blood samples from 22 different cohorts, to comprehensively map associations between the 12 immune-cell fractions and common phenotypes. In a separate cohort of 4386 blood samples, we assess associations between immune-cell fractions and health outcomes.

RESULTS

Our meta-analysis reveals many associations of cell-type fractions with age, sex, smoking and obesity, many of which we validate with single-cell RNA sequencing. We discover that naïve and regulatory T-cell subsets are higher in women compared to men, while the reverse is true for monocyte, natural killer, basophil, and eosinophil fractions. Decreased natural killer counts associated with smoking, obesity, and stress levels, while an increased count correlates with exercise and sleep. Analysis of health outcomes revealed that increased naïve CD4 + T-cell and N-cell fractions associated with a reduced risk of all-cause mortality independently of all major epidemiological risk factors and baseline co-morbidity. A machine learning predictor built only with immune-cell fractions achieved a C-index value for all-cause mortality of 0.69 (95%CI 0.67-0.72), which increased to 0.83 (0.80-0.86) upon inclusion of epidemiological risk factors and baseline co-morbidity.

CONCLUSIONS

This work contributes an extensively validated high-resolution DNAm reference matrix for blood, which is made freely available, and uses it to generate a comprehensive map of associations between immune-cell fractions and common phenotypes, including health outcomes.

Short-term smoking cessation leads to a universal decrease in whole blood genomic DNA methylation in patients with a smoking history

BACKGROUND

Epigenetics is involved in various human diseases. Smoking is one of the most common environmental factors causing epigenetic changes. The DNA methylation changes and mechanisms after quitting smoking have yet to be defined. The present study examined the changes in DNA methylation levels before and after short-term smoking cessation and explored the potential mechanism.

METHODS

Whole blood and clinical data were collected from 8 patients before and after short-term smoking cessation, DNA methylation was assessed, and differentially methylated sites were analyzed, followed by a comprehensive analysis of the differentially methylated sites with clinical data. GO/KEGG enrichment and protein-protein interaction (PPI) network analyses identified the hub genes. The differentially methylated sites between former and current smokers in GSE50660 from the GEO database were detected by GEO2R. Then, a Venn analysis was carried out using the differentially methylated sites. GO/KEGG enrichment analysis was performed on the genes corresponding to the common DNA methylation sites, the PPI network was constructed, and hub genes were predicted. The enriched genes associated with the cell cycle were selected, and the pan-cancer gene expression and clinical significance in lung cancer were analyzed based on the TCGA database.

RESULTS

Most genes showed decreased DNA methylation levels after short-term smoking cessation; 694 upregulated methylation CpG sites and 3184 downregulated methylation CpG sites were identified. The DNA methylation levels were altered according to the clinical data (body weight, expiratory, and tobacco dependence score). Enrichment analysis, construction of the PPI network, and pan-cancer analysis suggested that smoking cessation may affect various biological processes.

CONCLUSIONS

Smoking cessation leads to epigenetic changes, mainly decreased in the decline of most DNA methylation levels. Bioinformatics further identified the biologically relevant changes after short-term smoking cessation.

Defining Interactions Between the Genome, Epigenome, and the Environment in Inflammatory Bowel Disease: Progress and Prospects

Recent advances in our understanding of the pathogenesis of inflammatory bowel disease (IBD) have highlighted the complex interplay between the genome, the epigenome, and the environment. Despite the exciting advances in genomics that have enabled the identification of over 200 susceptibility loci, these only account for a small proportion of the disease variance and the estimated heritability in IBD. It is likely that gene-environment (GxE) interactions contribute to "missing heritability" and these may act through epigenetic mechanisms. Several environmental factors, such as the microbiome, nutrition, and tobacco smoking, induce alterations in the epigenome of children and adults, which may impact disease susceptibility. Other mechanisms for GxE interactions are also directly pertinent in early life. We discuss a model in which environmental factors imprint disease risk in a window of susceptibility during infancy that may contribute to later disease onset, whereas other elements of the exposome act later in life and contribute directly to the pathogenesis and course of the disease. Understanding the mechanisms underlying GxE interactions may provide the basis for new therapeutic targets or preventative strategies for IBD.

Stress, diet, exercise: Common environmental factors and their impact on epigenetic age

Epigenetic aging clocks have gained significant attention as a tool for predicting age-related health conditions in clinical and research settings. They have enabled geroscientists to study the underlying mechanisms of aging and assess the effectiveness of anti-aging therapies, including diet, exercise and environmental exposures. This review explores the effects of modifiable lifestyle factors' on the global DNA methylation landscape, as seen by aging clocks. We also discuss the underlying mechanisms through which these factors contribute to biological aging and provide comments on what these findings mean for people willing to build an evidence-based pro-longevity lifestyle.

Emerging roles of a chemoattractant receptor GPR15 and ligands in pathophysiology

Chemokine receptors play a central role in the maintenance of immune homeostasis and development of inflammation by directing leukocyte migration to tissues. GPR15 is a G protein-coupled receptor (GPCR) that was initially known as a co-receptor for human immunodeficiency virus (HIV) and simian immunodeficiency virus (SIV), with structural similarity to other members of the chemoattractant receptor family. Since the discovery of its novel function as a colon-homing receptor of T cells in mice a decade ago, GPR15 has been rapidly gaining attention for its involvement in a variety of inflammatory and immune disorders. The recent identification of its natural ligand C10orf99, a chemokine-like polypeptide strongly expressed in gastrointestinal tissues, has established that GPR15-C10orf99 is a novel signaling axis that controls intestinal homeostasis and inflammation through the migration of immune cells. In addition, it has been demonstrated that C10orf99-independent functions of GPR15 and GPR15-independent activities of C10orf99 also play significant roles in the pathophysiology. Therefore, GPR15 and its ligands are potential therapeutic targets. To provide a basis for the future development of GPR15- or GPR15 ligand-targeted therapeutics, we have summarized the latest advances in the role of GPR15 and its ligands in human diseases as well as the molecular mechanisms that regulate GPR15 expression and functions.

Genome-Wide Methylation Profiling in 229 Patients With Crohn's Disease Requiring Intestinal Resection: Epigenetic Analysis of the Trial of Prevention of Post-operative Crohn's Disease (TOPPIC)

BACKGROUND & AIMS

DNA methylation alterations may provide important insights into gene-environment interaction in cancer, aging, and complex diseases, such as inflammatory bowel disease (IBD). We aim first to determine whether the circulating DNA methylome in patients requiring surgery may predict Crohn's disease (CD) recurrence following intestinal resection; and second to compare the circulating methylome seen in patients with established CD with that we had reported in a series of inception cohorts.

METHODS

TOPPIC was a placebo-controlled, randomized controlled trial of 6-mercaptopurine at 29 UK centers in patients with CD undergoing ileocolic resection between 2008 and 2012. Genomic DNA was extracted from whole blood samples from 229 of the 240 patients taken before intestinal surgery and analyzed using 450KHumanMethylation and Infinium Omni Express Exome arrays (Illumina, San Diego, CA). Coprimary objectives were to determine whether methylation alterations may predict clinical disease recurrence; and to assess whether the epigenetic alterations previously reported in newly diagnosed IBD were present in the patients with CD recruited into the TOPPIC study. Differential methylation and variance analysis was performed comparing patients with and without clinical evidence of recurrence. Secondary analyses included investigation of methylation associations with smoking, genotype (MeQTLs), and chronologic age. Validation of our previously published case-control observation of the methylome was performed using historical control data (CD, n = 123; Control, n = 198).

RESULTS

CD recurrence in patients following surgery is associated with 5 differentially methylated positions (Holm P < .05), including probes mapping to WHSC1 (P = 4.1 × 10-9, Holm P = .002) and EFNA3 (P = 4.9 × 10-8, Holm P = .02). Five differentially variable positions are demonstrated in the group of patients with evidence of disease recurrence including a probe mapping to MAD1L1 (P = 6.4 × 10-5). DNA methylation clock analyses demonstrated significant age acceleration in CD compared with control subjects (GrimAge + 2 years; 95% confidence interval, 1.2-2.7 years), with some evidence for accelerated aging in patients with CD with disease recurrence following surgery (GrimAge +1.04 years; 95% confidence interval, -0.04 to 2.22). Significant methylation differences between CD cases and control subjects were seen by comparing this cohort in conjunction with previously published control data, including validation of our previously described differentially methylated positions (RPS6KA2 P = 1.2 × 10-19, SBNO2 = 1.2 × 10-11) and regions (TXK [false discovery rate, P = 3.6 × 10-14], WRAP73 [false discovery rate, P = 1.9 × 10-9], VMP1 [false discovery rate, P = 1.7 × 10-7], and ITGB2 [false discovery rate, P = 1.4 × 10-7]).

CONCLUSIONS

We demonstrate differential methylation and differentially variable methylation in patients developing clinical recurrence within 3 years of surgery. Moreover, we report replication of the CD-associated methylome, previously characterized only in adult and pediatric inception cohorts, in patients with medically refractory disease needing surgery.

Epigenetic biomarkers for smoking cessation

Cigarette smoking has been associated with epigenetic alterations that may be reversible upon cessation. As the most-studied epigenetic modification, DNA methylation is strongly associated with smoking exposure, providing a potential mechanism that links smoking to adverse health outcomes. Here, we reviewed the reversibility of DNA methylation in accessible peripheral tissues, mainly blood, in relation to cigarette smoking cessation and the utility of DNA methylation as a biomarker signature to differentiate current, former, and never smokers and to quantify time since cessation. We summarized thousands of differentially methylated Cytosine-Guanine (CpG) dinucleotides and regions associated with smoking cessation from candidate gene and epigenome-wide association studies, as well as the prediction accuracy of the multi-CpG predictors for smoking status. Overall, there is robust evidence for DNA methylation signature of cigarette smoking cessation. However, there are still gaps to fill, including (1) cell-type heterogeneity in measuring blood DNA methylation; (2) underrepresentation of non-European ancestry populations; (3) limited longitudinal data to quantitatively measure DNA methylation after smoking cessation over time; and (4) limited data to study the impact of smoking cessation on other epigenetic features, noncoding RNAs, and histone modifications. Epigenetic machinery provides promising biomarkers that can improve success in smoking cessation in the clinical setting. To achieve this goal, larger and more-diverse samples with longitudinal measures of a broader spectrum of epigenetic marks will be essential to developing a robust DNA methylation biomarker assay, followed by meeting validation requirements for the assay before being implemented as a clinically useful tool.

Epigenomic profiling of isolated blood cell types reveals highly specific B cell smoking signatures and links to disease risk

BACKGROUND

Tobacco smoking alters the DNA methylation profiles of immune cells which may underpin some of the pathogenesis of smoking-associated diseases. To link smoking-driven epigenetic effects in specific immune cell types with disease risk, we isolated six leukocyte subtypes, CD14+ monocytes, CD15+ granulocytes, CD19+ B cells, CD4+ T cells, CD8+ T cells, and CD56+ natural killer cells, from whole blood of 67 healthy adult smokers and 74 nonsmokers for epigenome-wide association study (EWAS) using Illumina 450k and EPIC methylation arrays.

RESULTS

Numbers of smoking-associated differentially methylated sites (smCpGs) at genome-wide significance (p < 1.2 × 10-7) varied widely across cell types, from 5 smCpGs in CD8+ T cells to 111 smCpGs in CD19+ B cells. We found unique smoking effects in each cell type, some of which were not apparent in whole blood. Methylation-based deconvolution to estimate B cell subtypes revealed that smokers had 7.2% (p = 0.033) less naïve B cells. Adjusting for naïve and memory B cell proportions in EWAS and RNA-seq allowed the identification of genes enriched for B cell activation-related cytokine signaling pathways, Th1/Th2 responses, and hematopoietic cancers. Integrating with large-scale public datasets, 62 smCpGs were among CpGs associated with health-relevant EWASs. Furthermore, 74 smCpGs had reproducible methylation quantitative trait loci single nucleotide polymorphisms (SNPs) that were in complete linkage disequilibrium with genome-wide association study SNPs, associating with lung function, disease risks, and other traits.

CONCLUSIONS

We observed blood cell-type-specific smCpGs, a naïve-to-memory shift among B cells, and by integrating genome-wide datasets, we identified their potential links to disease risks and health traits.

Analysis of Systemic Epigenetic Alterations in Inflammatory Bowel Disease: Defining Geographical, Genetic and Immune-Inflammatory influences on the Circulating Methylome

BACKGROUND

Epigenetic alterations may provide valuable insights into gene-environment interactions in the pathogenesis of inflammatory bowel disease [IBD].

METHODS

Genome-wide methylation was measured from peripheral blood using the Illumina 450k platform in a case-control study in an inception cohort (295 controls, 154 Crohn's disease [CD], 161 ulcerative colitis [UC], 28 IBD unclassified [IBD-U)] with covariates of age, sex and cell counts, deconvoluted by the Houseman method. Genotyping was performed using Illumina HumanOmniExpressExome-8 BeadChips and gene expression using the Ion AmpliSeq Human Gene Expression Core Panel. Treatment escalation was characterized by the need for biological agents or surgery after initial disease remission.

RESULTS

A total of 137 differentially methylated positions [DMPs] were identified in IBD, including VMP1/MIR21 [p = 9.11 × 10-15] and RPS6KA2 [6.43 × 10-13], with consistency seen across Scandinavia and the UK. Dysregulated loci demonstrate strong genetic influence, notably VMP1 [p = 1.53 × 10-15]. Age acceleration is seen in IBD [coefficient 0.94, p < 2.2 × 10-16]. Several immuno-active genes demonstrated highly significant correlations between methylation and gene expression in IBD, in particular OSM: IBD r = -0.32, p = 3.64 × 10-7 vs non-IBD r = -0.14, p = 0.77]. Multi-omic integration of the methylome, genome and transcriptome also implicated specific pathways that associate with immune activation, response and regulation at disease inception. At follow-up, a signature of three DMPs [TAP1, TESPA1, RPTOR] were associated with treatment escalation to biological agents or surgery (hazard ratio of 5.19 [CI: 2.14-12.56], logrank p = 9.70 × 10-4).

CONCLUSION

These data demonstrate consistent epigenetic alterations at diagnosis in European patients with IBD, providing insights into the pathogenetic importance and translational potential of epigenetic mapping in complex disease.

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.

Association between passive smoking and the risk of rheumatoid arthritis: a systematic review and meta-analysis

In order to provide a basis for the prevention of RA, this systematic review and meta-analysis evaluated the association between passive smoking and the risk of developing RA. We searched electronic databases, including PubMed, Cochrane Central Register of Controlled Trials, Web of Science, and Embase, for published literature from the establishment to March 2022. Then we included subject-related cohort studies and case-control studies, and two researchers independently screened and extracted relevant data. Finally, we performed a meta-analysis, cumulative meta-analysis, and dose-response meta-analysis using the Stata software and evaluated the included literature for the level of evidence. This meta-analysis included three case-control and three cohort studies. There was only a small amount of statistical heterogeneity among the studies (I² = 34.9%). According to the study results, the risk of RA was 12% higher in passive smokers than in unexposed individuals. In subgroup analysis, a 12% increase in the prevalence of RA was observed in those exposed to passive smoking in adulthood. The developing RA rate was 34% higher in individuals exposed to passive smoking during childhood than in unexposed individuals. As time progressed and with the inclusion of extensive sample studies in the cumulative meta-analysis, the precision of the overall incidence effect values gradually increased. A dose-response meta-analysis showed no statistical significance that the risk of RA increased with the number of passive smoking years. Passive smoking may relate to the risk of RA, especially in childhood exposures.

Epigenome-Wide Association Study Reveals CpG Sites Associated with Thyroid Function and Regulatory Effects on KLF9

Background: Thyroid hormones play a key role in differentiation and metabolism and are known regulators of gene expression through both genomic and epigenetic processes including DNA methylation. The aim of this study was to examine associations between thyroid hormones and DNA methylation. Methods: We carried out a fixed-effect meta-analysis of epigenome-wide association study (EWAS) of blood DNA methylation sites from 8 cohorts from the ThyroidOmics Consortium, incorporating up to 7073 participants of both European and African ancestry, implementing a discovery and replication stage. Statistical analyses were conducted using normalized beta CpG values as dependent and log-transformed thyrotropin (TSH), free thyroxine, and free triiodothyronine levels, respectively, as independent variable in a linear model. The replicated findings were correlated with gene expression levels in whole blood and tested for causal influence of TSH and free thyroxine by two-sample Mendelian randomization (MR). Results: Epigenome-wide significant associations (p-value <1.1E-7) of three CpGs for free thyroxine, five for free triiodothyronine, and two for TSH concentrations were discovered and replicated (combined p-values = 1.5E-9 to 4.3E-28). The associations included CpG sites annotated to KLF9 (cg00049440) and DOT1L (cg04173586) that overlap with all three traits, consistent with hypothalamic-pituitary-thyroid axis physiology. Significant associations were also found for CpGs in FKBP5 for free thyroxine, and at CSNK1D/LINCO1970 and LRRC8D for free triiodothyronine. MR analyses supported a causal effect of thyroid status on DNA methylation of KLF9. DNA methylation of cg00049440 in KLF9 was inversely correlated with KLF9 gene expression in blood. The CpG at CSNK1D/LINC01970 overlapped with thyroid hormone receptor alpha binding peaks in liver cells. The total additive heritability of the methylation levels of the six significant CpG sites was between 25% and 57%. Significant methylation QTLs were identified for CpGs at KLF9, FKBP5, LRRC8D, and CSNK1D/LINC01970. Conclusions: We report novel associations between TSH, thyroid hormones, and blood-based DNA methylation. This study advances our understanding of thyroid hormone action particularly related to KLF9 and serves as a proof-of-concept that integrations of EWAS with other -omics data can provide a valuable tool for unraveling thyroid hormone signaling in humans by complementing and feeding classical in vitro and animal studies.

Select Early-Life Environmental Exposures and DNA Methylation in the Placenta

PURPOSE OF REVIEW

To summarize recent literature relating early-life environmental exposures on DNA methylation in the placenta, to identify how variation in placental methylation is regulated in an exposure-specific manner, and to encourage additional work in this area.

RECENT FINDINGS

Multiple studies have evaluated associations between prenatal environmental exposures and placental methylation in both gene-specific and epigenome-wide frameworks. Specific exposures lead to unique variability in methylation, and cross-exposure assessments have uncovered certain genes that demonstrate consistency in differential placental methylation. Exposure studies that assess methylation effects in a trimester-specific approach tend to find larger effects during the 1st trimester exposure. Earlier studies have more targeted gene-specific approaches to methylation, while later studies have shifted towards epigenome-wide, array-based approaches. Studies focusing on exposures such as air pollution, maternal smoking, environmental contaminants, and trace metals appear to be more abundant, while studies of socioeconomic adversity and circadian disruption are scarce but demonstrate remarkable effects. Understanding the impacts of early-life environmental exposures on placental methylation is critical to establishing the link between the maternal environment, epigenetic variation, and long-term health. Future studies into this field should incorporate repeated measures of exposure throughout pregnancy, in order to determine the critical windows in which placental methylation is most heavily affected. Additionally, the use of methylation-based scores and sequencing technology could provide important insights into epigenetic gestational age and uncovering more genomic regions where methylation is affected. Studies examining the impact of other exposures on methylation, including pesticides, alcohol, and other chemicals are also warranted.

DNA-Methylation Signatures of Tobacco Smoking in a High Cardiovascular Risk Population: Modulation by the Mediterranean Diet

Biomarkers based on DNA methylation are relevant in the field of environmental health for precision health. Although tobacco smoking is one of the factors with a strong and consistent impact on DNA methylation, there are very few studies analyzing its methylation signature in southern European populations and none examining its modulation by the Mediterranean diet at the epigenome-wide level. We examined blood methylation smoking signatures on the EPIC 850 K array in this population (n = 414 high cardiovascular risk subjects). Epigenome-wide methylation studies (EWASs) were performed analyzing differential methylation CpG sites by smoking status (never, former, and current smokers) and the modulation by adherence to a Mediterranean diet score was explored. Gene-set enrichment analysis was performed for biological and functional interpretation. The predictive value of the top differentially methylated CpGs was analyzed using receiver operative curves. We characterized the DNA methylation signature of smoking in this Mediterranean population by identifying 46 differentially methylated CpGs at the EWAS level in the whole population. The strongest association was observed at the cg21566642 (p = 2.2 × 10-32) in the 2q37.1 region. We also detected other CpGs that have been consistently reported in prior research and discovered some novel differentially methylated CpG sites in subgroup analyses. In addition, we found distinct methylation profiles based on the adherence to the Mediterranean diet. Particularly, we obtained a significant interaction between smoking and diet modulating the cg5575921 methylation in the AHRR gene. In conclusion, we have characterized biomarkers of the methylation signature of tobacco smoking in this population, and suggest that the Mediterranean diet can increase methylation of certain hypomethylated sites.

Machine Learning Approximations to Predict Epigenetic Age Acceleration in Stroke Patients

Age acceleration (Age-A) is a useful tool that is able to predict a broad range of health outcomes. It is necessary to determine DNA methylation levels to estimate it, and it is known that Age-A is influenced by environmental, lifestyle, and vascular risk factors (VRF). The aim of this study is to estimate the contribution of these easily measurable factors to Age-A in patients with cerebrovascular disease (CVD), using different machine learning (ML) approximations, and try to find a more accessible model able to predict Age-A. We studied a CVD cohort of 952 patients with information about VRF, lifestyle habits, and target organ damage. We estimated Age-A using Hannum's epigenetic clock, and trained six different models to predict Age-A: a conventional linear regression model, four ML models (elastic net regression (EN), K-Nearest neighbors, random forest, and support vector machine models), and one deep learning approximation (multilayer perceptron (MLP) model). The best-performing models were EN and MLP; although, the predictive capability was modest (R² 0.358 and 0.378, respectively). In conclusion, our results support the influence of these factors on Age-A; although, they were not enough to explain most of its variability.

Blood DNA methylation signatures of lifestyle exposures: tobacco and alcohol consumption

BACKGROUND

Smoking and alcohol consumption may compromise health by way of epigenetic modifications. Epigenetic signatures of alcohol and tobacco consumption could provide insights into the reversibility of phenotypic changes incurred with differing levels of lifestyle exposures. This study describes and validates two novel epigenetic signatures of tobacco (EpiTob) and alcohol (EpiAlc) consumption and investigates their association with disease outcomes.

METHODS

The epigenetic signatures, EpiTob and EpiAlc, were developed using data from the Swiss Kidney Project on Genes in Hypertension (SKIPOGH) (N = 689). Epigenetic and phenotypic data available from the 1921 (N = 550) and 1936 (N = 1091) Lothian Birth Cohort (LBC) studies, and two publicly available datasets on GEO Accession (GSE50660, N = 464; and GSE110043, N = 94) were used to validate the signatures. A multivariable logistic regression model, adjusting for age and sex, was used to assess the association between self-reported tobacco or alcohol consumption and the respective epigenetic signature, as well as to estimate the association between CVD and epigenetic signatures. A Cox proportional hazard model was used to estimate the risk of mortality in association with the EpiTob and EpiAlc signatures.

RESULTS

The EpiTob signature was positively associated with self-reported tobacco consumption for current or never smokers with explained variance ranging from 0.49 (LBC1921) to 0.72 (LBC1936) (pseudo-R2). In the SKIPOGH, LBC1921 and LBC1936 cohorts, the epigenetic signature for alcohol consumption explained limited variance in association with self-reported alcohol status [i.e., non-drinker, moderate drinker, and heavy drinker] (pseudo-R2 = 0.05, 0.03 and 0.03, respectively), although this improved considerably when measuring self-reported alcohol consumption with standardized units consumed per week (SKIPOGH R2 = 0.21; LBC1921 R2 = 0.31; LBC1936 R2 = 0.41). Both signatures were associated with history of CVD in SKIPOGH and LBC1936, but not in LBC1921. The EpiTob signature was associated with increased risk of all-cause and lung-cancer specific mortality in the 1936 and 1921 LBC cohorts.

CONCLUSIONS

This study found the EpiTob and EpiAlc signatures to be well-correlated with self-reported exposure status and associated with long-term health outcomes. Epigenetic signatures of lifestyle exposures may reduce measurement issues and biases and could aid in risk stratification for informing early-stage targeted interventions.

The Mutagenic Consequences of DNA Methylation within and across Generations

DNA methylation is an epigenetic modification with wide-ranging consequences across the life of an organism. This modification can be stable, persisting through development despite changing environmental conditions. However, in other contexts, DNA methylation can also be flexible, underlying organismal phenotypic plasticity. One underappreciated aspect of DNA methylation is that it is a potent mutagen; methylated cytosines mutate at a much faster rate than other genetic motifs. This mutagenic property of DNA methylation has been largely ignored in eco-evolutionary literature, despite its prevalence. Here, we explore how DNA methylation induced by environmental and other factors could promote mutation and lead to evolutionary change at a more rapid rate and in a more directed manner than through stochastic genetic mutations alone. We argue for future research on the evolutionary implications of DNA methylation driven mutations both within the lifetime of organisms, as well as across timescales.

Life factors acting on systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a highly heterogeneous autoimmune disease that primarily affects women. Currently, in the search for the mechanisms of SLE pathogenesis, the association of lifestyle factors such as diet, cigarette smoking, ultraviolet radiation exposure, alcohol and caffeine-rich beverage consumption with SLE susceptibility has been systematically investigated. The cellular and molecular mechanisms mediating lifestyle effects on SLE occurrence, including interactions between genetic risk loci and environment, epigenetic changes, immune dysfunction, hyper-inflammatory response, and cytotoxicity, have been proposed. In the present review of the reports published in reputable peer-reviewed journals and government websites, we consider the current knowledge about the relationships between lifestyle factors and SLE incidence and outline directions of future research in this area. Formulation of practical measures with regard to the lifestyle in the future will benefit SLE patients and may provide potential therapy strategies.

AhRR methylation contributes to disease progression in urothelial bladder cancer

BACKGROUND

Bladder Cancer (BCa) is the tenth most incidental malignancy worldwide. BCa is mostly attributed to environmental exposure and lifestyle, particularly tobacco smoking. The Aryl Hydrocarbon Receptor Repressor (AhRR) participates in the induction of many enzymes involved in metabolizing carcinogens, including tobacco smoke components. Additionally, studies have shown that smoking demethylates the (AhRR) gene in blood, suggesting AhRR demethylation as a specific serum smoking biomarker.

OBJECTIVE

This study aimed to validate AhRR demethylation as a smoking biomarker in the target tissue and investigate its contribution to bladder carcinogenesis.

METHODS

AhRR percent methylation was tested for its association with patient smoking status and oncogenic outcome indicators, particularly p53, RB1, and FGFR3 activating mutations, muscle-invasiveness, and tumor grade, in 180 BCa tissue-based DNA.

RESULTS

Results showed significantly higher AhRR percent methylation in muscle-invasive compared to non-muscle invasive tumors (42.86% vs. 33.98%; p= 0.011), while lower AhRR methylation was significantly associated with FGFR3 Codon 248 mutant genotype compared to wild-type (28.11% ± 9.44 vs. 37.87% ± 22.53; p= 0.036). All other tested associations were non-statistically significant.

CONCLUSIONS

Although AhRR methylation did not predict smoking status in BCa tumors, it seems to play a role in carcinogenesis and disease progression. Our findings make a basis for further research.

The potential of DNA methylation as a biomarker for obesity and smoking

DNA methylation is an epigenetic modification that has consistently been shown to be linked with a variety of human traits and diseases. Because DNA methylation is dynamic and potentially reversible in nature and can reflect environmental exposures and predict the onset of diseases, it has piqued interest as a potential disease biomarker. DNA methylation patterns are more stable than transcriptomic or proteomic patterns, and they are relatively easy to measure to track exposure to different environments and risk factors. Importantly, technologies for DNA methylation quantification have become increasingly cost effective-accelerating new research in the field-and have enabled the development of novel DNA methylation biomarkers. Quite a few DNA methylation-based predictors for a number of traits and diseases already exist. Such predictors show potential for being more accurate than self-reported or measured phenotypes (such as smoking behavior and body mass index) and may even hold potential for applications in clinics. In this review, we will first discuss the advantages and challenges of DNA methylation biomarkers in general. We will then review the current state and future potential of DNA methylation biomarkers in two human traits that show rather consistent alterations in methylome-obesity and smoking. Lastly, we will briefly speculate about the future prospects of DNA methylation biomarkers, and possible ways to achieve them.

Can epigenetics shine a light on the biological pathways underlying major mental disorders?

A significant proportion of the global burden of disease can be attributed to mental illness. Despite important advances in identifying risk factors for mental health conditions, the biological processing underlying causal pathways to disease onset remain poorly understood. This represents a limitation to implement effective prevention and the development of novel pharmacological treatments. Epigenetic mechanisms have emerged as mediators of environmental and genetic risk factors which might play a role in disease onset, including childhood adversity (CA) and cannabis use (CU). Particularly, human research exploring DNA methylation has provided new and promising insights into the role of biological pathways implicated in the aetio-pathogenesis of psychiatric conditions, including: monoaminergic (Serotonin and Dopamine), GABAergic, glutamatergic, neurogenesis, inflammatory and immune response and oxidative stress. While these epigenetic changes have been often studied as disease-specific, similarly to the investigation of environmental risk factors, they are often transdiagnostic. Therefore, we aim to review the existing literature on DNA methylation from human studies of psychiatric diseases (i) to identify epigenetic modifications mapping onto biological pathways either transdiagnostically or specifically related to psychiatric diseases such as Eating Disorders, Post-traumatic Stress Disorder, Bipolar and Psychotic Disorder, Depression, Autism Spectrum Disorder and Anxiety Disorder, and (ii) to investigate a convergence between some of these epigenetic modifications and the exposure to known risk factors for psychiatric disorders such as CA and CU, as well as to other epigenetic confounders in psychiatry research.

CpG site-specific methylation as epi-biomarkers for the prediction of health risk in PAHs-exposed populations

Environmental insults can lead to alteration in DNA methylation of specific genes. To address the role of altered DNA methylation in prediction of polycyclic aromatic hydrocarbons (PAHs) exposure-induced genetic damage, we recruited two populations, including diesel engine exhausts (low-level) and coke oven emissions (high-level) exposed subjects. The positive correlation was observed between the internal exposure marker (1-hydroxypyrene) and the extents of DNA damage (P < 0.05). The methylation of representative genes, including TRIM36, RASSF1a, and MGMT in peripheral blood lymphocytes was quantitatively examined by bisulfite-pyrosequencing assay. The DNA methylation of these three genes in response to PAHs exposure were changed in a CpG-site-specific manner. The identified hot CpG site-specific methylation of three genes exhibited higher predictive power for DNA damage than the respective single genes in both populations. Furthermore, the dose-response relationship analysis revealed a nonlinear U-shape curve of TRIM36 or RASSF1a methylation in combined population, which led to determination of the threshold of health risk. Furthermore, we established a prediction model for genetic damage based on the unidirectional-alteration MGMT methylation levels. In conclusion, this study provides new insight into the application of multiple epi-biomarkers for health risk assessment upon PAHs exposure.

Epigenome-wide association analyses of active injection drug use

BACKGROUND

Injection drug use (IDU) is prevalent in the US and is associated with substantial risk of blood-borne infections, morbidity, and mortality. However, the spectrum of its biologic effects on DNA methylation in blood is not well characterized.

METHODS

401 participants (M_age = 47.9; 68% male; 90% African American) over several timepoints (1054 visits) were drawn from a longitudinal cohort of people who inject drugs. DNA methylation was measured among buffy coat samples from the 1054 visits. Compared to samples collected after ≥ 6 months of abstinence, separate EWAS were conducted for active injecting of any drug, quantitative injection frequency, injecting of heroin and injecting of cocaine. Linear mixed effect models were used and analyses were adjusted for repeated measurements and key technical, biological, and sociodemographic characteristics.

RESULTS

We found epigenome-wide significant CpG sites associated with active injection (cg10636246, AIM2, p = 2.33 × 10^-8) and injection intensity (cg13117953, p = 4.30 × 10^-8). We found converging evidence that cg10636246 (AIM2), cg23110600 (PRKCH), cg03546163 (FKBP5), cg04590956 (GMCL1), and cg16317961 (MAPRE2) were among the top 0.1% significantly differentially methylated CpG sites shared across the five EWAS. Top ranked CpGs among the five EWAS were enriched (p < 0.0001) in AIM2 inflammasome complex, T cell migration, insulin regulation and epinephrine synthesis pathways. During periods of active injection, samples had 0.46 years of epigenetic age acceleration relative to the abstinence period, within the same subject (p = 0.03).

CONCLUSIONS

Findings from this study demonstrate modest, common, and specific effects on DNA methylation during a relatively short time between periods of active drug injection and abstinence.

Evaluation of nanopore sequencing for epigenetic epidemiology: a comparison with DNA methylation microarrays

Most epigenetic epidemiology to date has utilized microarrays to identify positions in the genome where variation in DNA methylation is associated with environmental exposures or disease. However, these profile less than 3% of DNA methylation sites in the human genome, potentially missing affected loci and preventing the discovery of disrupted biological pathways. Third generation sequencing technologies, including Nanopore sequencing, have the potential to revolutionise the generation of epigenetic data, not only by providing genuine genome-wide coverage but profiling epigenetic modifications direct from native DNA. Here we assess the viability of using Nanopore sequencing for epidemiology by performing a comparison with DNA methylation quantified using the most comprehensive microarray available, the Illumina EPIC array. We implemented a CRISPR-Cas9 targeted sequencing approach in concert with Nanopore sequencing to profile DNA methylation in three genomic regions to attempt to rediscover genomic positions that existing technologies have shown are differentially methylated in tobacco smokers. Using Nanopore sequencing reads, DNA methylation was quantified at 1779 CpGs across three regions, providing a finer resolution of DNA methylation patterns compared to the EPIC array. The correlation of estimated levels of DNA methylation between platforms was high. Furthermore, we identified 12 CpGs where hypomethylation was significantly associated with smoking status, including 10 within the AHRR gene. In summary, Nanopore sequencing is a valid option for identifying genomic loci where large differences in DNAm are associated with a phenotype and has the potential to advance our understanding of the role differential methylation plays in the aetiology of complex disease.

Making sense of the ageing methylome

Over time, the human DNA methylation landscape accrues substantial damage, which has been associated with a broad range of age-related diseases, including cardiovascular disease and cancer. Various age-related DNA methylation changes have been described, including at the level of individual CpGs, such as differential and variable methylation, and at the level of the whole methylome, including entropy and correlation networks. Here, we review these changes in the ageing methylome as well as the statistical tools that can be used to quantify them. We detail the evidence linking DNA methylation to ageing phenotypes and the longevity strategies aimed at altering both DNA methylation patterns and machinery to extend healthspan and lifespan. Lastly, we discuss theories on the mechanistic causes of epigenetic ageing.

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

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

Age Prediction by DNA Methylation in Neural Networks

Aging is traditionally thought to be caused by complex and interacting factors such as DNA methylation. The traditional formula of DNA methylation aging is based on linear models and little work has explored the effectiveness of neural networks, which can learn non-linear relationships. DNA methylation data typically consists of hundreds of thousands of feature space and a much less number of biological samples. This leads to overfitting and a poor generalization of neural networks. We propose Correlation Pre-Filtered Neural Network (CPFNN) that uses Spearman Correlation to pre-filter the input features before feeding them into neural networks. We compare CPFNN with the statistical regressions (i.e., Horvath's and Hannum's formulas), the neural networks with LASSO regularization and elastic net regularization, and the Dropout Neural Networks. CPFNN outperforms these models by at least 1 year in term of Mean Absolute Error (MAE), with a MAE of 2.7 years. We also test for association between the epigenetic age with Schizophrenia and Down Syndrome ( p=0.024 and , respectively). We discover that for a large number of candidate features, such as genome-wide DNA methylation data, a key factor in improving prediction accuracy is to appropriately weight features that are highly correlated with the outcome of interest.

High-Dimensional DNA Methylation Mediates the Effect of Smoking on Crohn's Disease

Epigenome-wide mediation analysis aims to identify high-dimensional DNA methylation at cytosine-phosphate-guanine (CpG) sites that mediate the causal effect of linking smoking with Crohn's disease (CD) outcome. Studies have shown that smoking has significant detrimental effects on the course of CD. So we assessed whether DNA methylation mediates the association between smoking and CD. Among 103 CD cases and 174 controls, we estimated whether the effects of smoking on CD are mediated through DNA methylation CpG sites, which we referred to as causal mediation effect. Based on the causal diagram, we first implemented sure independence screening (SIS) to reduce the pool of potential mediator CpGs from a very large to a moderate number; then, we implemented variable selection with de-sparsifying the LASSO regression. Finally, we carried out a comprehensive mediation analysis and conducted sensitivity analysis, which was adjusted for potential confounders of age, sex, and blood cell type proportions to estimate the mediation effects. Smoking was significantly associated with CD under odds ratio (OR) of 2.319 (95% CI: 1.603, 3.485, p < 0.001) after adjustment for confounders. Ninety-nine mediator CpGs were selected from SIS, and then, seven candidate CpGs were obtained by de-sparsifying the LASSO regression. Four of these CpGs showed statistical significance, and the average causal mediation effects (ACME) were attenuated from 0.066 to 0.126. Notably, three significant mediator CpGs had absolute sensitivity parameters of 0.40, indicating that these mediation effects were robust even when the assumptions were slightly violated. Genes (BCL3 and FKBP5) harboring these four CpGs were related to CD. These findings suggest that changes in methylation are involved in the mechanism by which smoking increases risk of CD.

A robust mean and variance test with application to high-dimensional phenotypes

Most studies of continuous health-related outcomes examine differences in mean levels (location) of the outcome by exposure. However, identifying effects on the variability (scale) of an outcome, and combining tests of mean and variability (location-and-scale), could provide additional insights into biological mechanisms. A joint test could improve power for studies of high-dimensional phenotypes, such as epigenome-wide association studies of DNA methylation at CpG sites. One possible cause of heterogeneity of variance is a variable interacting with exposure in its effect on outcome, so a joint test of mean and variability could help in the identification of effect modifiers. Here, we review a scale test, based on the Brown-Forsythe test, for analysing variability of a continuous outcome with respect to both categorical and continuous exposures, and develop a novel joint location-and-scale score (JLSsc) test. These tests were compared to alternatives in simulations and used to test associations of mean and variability of DNA methylation with gender and gestational age using data from the Accessible Resource for Integrated Epigenomics Studies (ARIES). In simulations, the Brown-Forsythe and JLSsc tests retained correct type I error rates when the outcome was not normally distributed in contrast to the other approaches tested which all had inflated type I error rates. These tests also identified > 7500 CpG sites for which either mean or variability in cord blood methylation differed according to gender or gestational age. The Brown-Forsythe test and JLSsc are robust tests that can be used to detect associations not solely driven by a mean effect.

Associations between smoking and accelerated brain ageing

Smoking accelerates the ageing of multiple organs. However, few studies have quantified the association between smoking, especially smoking cessation, and brain ageing. Using structural magnetic resonance imaging data from the UK Biobank (n = 33,293), a brain age predictor was trained using a machine learning technique in the non-smoker group (n = 14,667) and then tested in the smoker group (n = 18,626) to determine the relationships between BrainAge Gap (predicted age - true age) and smoking parameters. Further, we examined whether smoking was associated with poorer cognition and whether this relationship was mediated by brain age. The predictor achieved an appreciable performance in training data (r = 0.712, mean-absolute-error [MAE] = 4.220) and test data (r = 0.725, MAE = 4.160). On average, smokers showed a larger BrainAge Gap (+0.304 years, Cohens'd = 0.083) than controls, more explicitly, the extents vary depending on their smoking characteristic that active regular smokers had the largest BrainAge Gap (+1.190 years, Cohens'd = 0.321), and light smokers had a moderate BrainAge Gap (+0.478, Cohens'd = 0.129). The increased smoking amount was associated with a larger BrainAge Gap (β = 0.035, p = 1.72 × 10^-20) while a longer duration of quitting smoking in ex-smokers was associated with a smaller BrainAge Gap (β = -0.015, p = 2.14 × 10^-05). Furthermore, smoking was associated with poorer cognition, and this relationship was partially mediated by BrainAge Gap. The study provides insight into the association between smoking, brain ageing, and cognition, which provide more publicly acceptable propaganda against smoking.

Genome-wide DNA methylation profiling identifies epigenetic changes in CD4+ and CD14+ cells of multiple sclerosis patients

Multiple sclerosis (MS) is a chronic autoimmune and degenerative disease of the central nervous system, which develops in genetically predisposed individuals upon exposure to environmental influences. Environmental triggers of MS, such as viral infections or smoking, were demonstrated to affect DNA methylation, and thus to involve this important epigenetic mechanism in the development of pathological process. To identify MS-associated DNA methylation hallmarks, we performed genome-wide DNA methylation profiling of two cell populations (CD4+ T-lymphocytes and CD14+ monocytes), collected from the same treatment-naive relapsing-remitting MS patients and healthy subjects, using Illumina 450 K methylation arrays. We revealed significant changes in DNA methylation for both cell populations in MS. In CD4+ cells of MS patients the majority of differentially methylated positions (DMPs) were shown to be hypomethylated, while in CD14+ cells - hypermethylated. Differential methylation of HLA-DRB1 gene in CD4+ and CD14+ cells was associated with carriage of DRB1*15 allele independently from the disease status. Besides, about 20% of identified DMPs were shared between two cell populations and had the same direction of methylation changes; they may be involved in basic epigenetic processes occuring in MS. These findings suggest that the epigenetic mechanism of DNA methylation in immune cells contributes to MS; further studies are now required to validate these results and understand their functional significance.