Intergenerational and life-course links between a cardiovascular health-related methylation score and early vascular changes

The role of epigenetic age acceleration and social disadvantage in cardiometabolic health in southeast Louisiana women.

BACKGROUND Cardiometabolic risk factors can disrupt DNA methylation (DNAm) patterns, accelerate cellular aging, and contribute to age-related disorders, including cardiovascular disease (CVD) and diabetes. Social disadvantage may exacerbate these biological processes, yet its relationship with epigenetic aging and cardiometabolic disease across time remains incompletely understood. We examined associations between epigenetic age acceleration and both social disadvantage and cardiometabolic diseases. We assessed whether these associations differed in each study wave. RESULTS Participants were drawn from The Women and Their Children's Health (WaTCH) cohort and assessed at Wave 1 (2012-2014; N = 865) and Wave 3 (2023-2025; N = 348). At Wave 1, participants had a mean age of 46.9 ± 11.9 years and identified as Black (38.0%) or White (56.2%). Social disadvantage was assessed using an individual-level socioeconomic status (SES) index (education, income, and health insurance) and the Area Deprivation Index (ADI). DNAm was measured from blood samples to derive epigenetic age acceleration metrics (GrimAge2, PhenoAge, and DunedinPACE). Lower SES index and higher ADI were associated with greater epigenetic age acceleration and a faster pace of aging. CVD (45.2%) and diabetes (15.6%) at Wave 1 were more prevalent among participants with lower SES index, higher ADI, Black race, and higher body mass index (BMI). After adjustment for BMI, alcohol use, ADI, SES, smoking, and cell composition, both CVD and diabetes were associated with higher GrimAge2 and PhenoAge acceleration and a faster pace of aging at Wave 1. At Wave 3, diabetes was associated with all measures of epigenetic age acceleration after covariate adjustment. CONCLUSIONS CVD and diabetes were more common among socially disadvantaged women and were associated with accelerated epigenetic aging. These findings highlight the biological correlates of social disadvantage and underscore the need for targeted public health interventions addressing social drivers of health to mitigate cardiometabolic disease risk.

DNA methylation informs adult cardiovascular risk and prevention for low birthweight individuals

Background Barker’s hypothesis posits that adverse in utero exposures, often reflected by low birthweight, increase adult cardiovascular disease (CVD) risk. However, underlying mechanisms remain unclear; identifying potentially causal mediators is crucial for developing effective interventions. Emerging research suggests epigenetic modifications may influence CVD traits from early life. We aimed to identify DNA methylation (DNAm) signatures that mediate birthweight and CVD traits and to establish their biological relevance across three developmental time points using multi-omics integration. Methods We identified DNAm mediators using epigenetic Mendelian randomisation (MR). The exposures were 261 birthweight-associated CpG sites (BW-CpGs) from epigenome-wide association studies, instrumented by cis-methylation quantitative trait loci (cis-mQTLs) in European-ancestry participants from the Accessible Resource for Integrative Epigenomic Studies measured at three developmental time points: birth (mean gestational age = 40 weeks), childhood (mean age = 7.49 years), and adolescence (mean age = 17.14 years). The outcomes included adult cardiovascular events and lipid traits from genome-wide association studies (n = 98,048–547,261). Sensitivity analyses included colocalisation, Steiger’s test, Cochran’s Q, and pleiotropy-robust methods. We interrogated DNAm persisting across development using omics datasets. Results Using cis-mQTLs measured at birth, we found 230 associations between 216 BW-CpGs and CVD traits, including coronary artery disease, hypertension, stroke, cholesterol, and triglycerides (false discovery rate-corrected P < 0.05), with effect size directions consistent with Barker’s hypothesis. A total of 42 associations were robust following sensitivity analyses. Persistent DNAm changes across development were observed at ASGR1 and KDM2B. Multi-omics interrogation prioritised a promising therapeutic candidate (ASGR1). Conclusions Although Barker’s hypothesis is well-established, this is the first study to explore its causal pathway using a rigorous, multi-time-point epigenetic MR framework with multi-omic integration. This represents a major advancement over previous observational and DNAm studies. The Barker-consistent hypothesis-free discovery approach identified novel and known candidate genes that, with future validation, may serve as therapeutic targets, identify high-risk individuals, and support clinical trial recruitment.

Blood-Based DNA Methylation Models Improve Short-term Cardiovascular Risk Stratification in Individuals With Type 2 Diabetes

OBJECTIVE Cardiovascular complications are the leading cause of death in type 2 diabetes mellitus (T2DM). We investigated whether blood-based DNA methylation (DNAm) biomarkers could improve risk stratification for major adverse cardiovascular events (MACE) in individuals with T2DM. RESEARCH DESIGN AND METHODS Epigenome-wide DNAm was profiled in peripheral blood mononuclear cells obtained at baseline from 305 T2DM participants of the Thiazolidinediones Or Sulphonylureas and Cardiovascular Accidents. Intervention Trial (TOSCA.IT) study, including 81 who experienced MACE within 5 years (T2DMACE) and 224 who did not (T2D). The population was randomly divided into training and internal test sets for model development and evaluation. Differential DNAm analyses were performed under five frameworks differing by covariate adjustment. Binomial least absolute shrinkage and selection operator (LASSO) logistic regression with stability selection was used to generate DNAm-based models to stratify individuals at higher risk of incident MACE over 5 years. RESULTS Differential DNAm analysis identified 23,839, 21,529, 21,500, 12,114, and 7,101 differentially methylated CpG sites across the five analytical frameworks. LASSO logistic regression was used to develop five DNAm-based models. Stability selection retained 22–26 CpG predictors per model. When evaluated in the internal test cohort, the five models showed high discriminative performance, with receiver operating characteristic area under the curve values ranging from 0.915 to 0.937 and area under the precision-recall curve values from 0.866 to 0.940. Several CpGs were independently associated with either increased or decreased risk of MACE, including 12 CpGs identified across all of the models. CONCLUSIONS The DNAm-based models we have generated may improve risk stratification for short-term cardiovascular events in individuals with T2DM, providing a promising approach to refine identification of those at increased risk of MACE.

The prenatal exposome and genome in predictive modelling of DNA methylation

Effects of maternal and paternal smoking on offspring cardiometabolic risk factors in adulthood: a multi-method intergenerational Mendelian randomization study

Parental smoking has been linked to several adverse offspring cardiometabolic outcomes; however, evidence is conflicting regarding the causal and long-term nature of these associations. We investigated the effects of maternal and paternal smoking, capturing exposure before, during, and after pregnancy, on eleven offspring cardiometabolic risk factors related to body composition, blood pressure, glucose, and lipid levels in adulthood. We applied a multi-method intergenerational Mendelian randomization (MR) framework, combining two-sample MR (outcome GWAS, n = up to 564,160) and one-sample MR analyses (n = up to 17,484 genotyped mother-father-offspring trios with offspring cardiometabolic risk factors) from the HUNT cohort, Norway, and the UK Biobank and ALSPAC cohorts in the United Kingdom. Smoking behaviour was instrumented using genome-wide significant variants for smoking initiation and heaviness from large genome-wide association studies (2019 and 2022), with additional analyses of the CHRNA5 variant rs16969968. Using the two-sample MR approach, we found an average change in adult offspring waist-hip ratio (WHR) per one standard deviation (SD) increase in maternal cigarettes smoked per day of 0.25 SD (95% CI: 0.13, 0.38; 2019 GWAS), 0.19 SD (95% CI: 0.08, 0.31; 2022 GWAS) and 0.27 SD (95% CI: 0.07, 0.47; CHRNA5 rs16969968). We also found tentative evidence of comparable effects on offspring body mass index and C-reactive protein. One-sample MR analyses using CHRNA5 rs16969968, restricted to maternal ever-smokers, provided supporting evidence consistent with the primary findings for maternal smoking heaviness on offspring WHR. We found little evidence that maternal smoking initiation affected WHR, and little evidence that maternal smoking heaviness affected the remaining cardiometabolic risk factors; paternal smoking showed no clear effect on any outcome. Results from sensitivity analyses were consistent with these main findings. Adult offspring of mothers with a propensity to heavier smoking exhibited greater central adiposity, a phenotype associated with increased cardiometabolic risk. These findings are consistent with a causal influence of maternal smoking heaviness across the preconception, perinatal, and postnatal periods on later-life offspring body fat distribution. Further triangulation using alternative causal approaches is warranted.

Stress-Related Methylation Risk Scores Predict Coronary Heart Disease

Background: Psychosocial stress is a key risk factor for coronary heart disease (CHD), particularly in postmenopausal women who face both a high stress burden and elevated cardiovascular risk. DNA methylation (DNAm), a critical epigenetic modification bridging environment and health, remains understudied as a contributor to stress-related CHD. Methods: We conducted an epigenome-wide association study (EWAS) of stress in the Women's Health Initiative (WHI), an ancestrally diverse cohort of postmenopausal women (n=3,857). At screening visit, participants completed a questionnaire assessing stressful life events and provided whole blood for DNAm. Incident CHD was then longitudinally ascertained (follow-up mean/SD: 16.7/8.4 years), and DNAm signatures were evaluated as CHD predictors using Cox regression. Predictive models were independently validated in the Jackson Heart Study (JHS; n=3,053) and Multi-Ethnic Study of Atherosclerosis (MESA; n=870). The bulk-level DNAm associations were computationally deconvolved at the cell-type-specific level using tensor composition analysis (TCA). Results: The EWAS in WHI identified 841 stress-related DNAm sites (99 hypermethylated, 742 hypomethylated with stress) after FDR correction, with 13 significant after Bonferroni correction, including sites located on immune and CHD-related genes (e.g., TNF, ALDH2). Methylation risk scores (MRSs) integrating the 841 FDR-significant sites (MRS841) and 13 Bonferroni-significant sites (MRS13) predicted incident CHD (HR=1.33-1.37; p[≤]0.0008) and mediated 16.5-17.7% of the association between stress and CHD. In JHS and MESA, MRS13 independently predicted CHD (HR=1.34; p=0.036), whereas MRS841 was suggestively associated with CHD (HR=1.27; p=0.087). TCA indicated that the greatest number of stress-related sites predictive of CHD was specifically in monocytes (133 total), with directions consistent with bulk-level associations (9 hypermethylated, 124 hypomethylated with stress). Conclusion: Our study supports methylation risk scores as novel biomarkers of stress-related CHD and uncovers epigenetic regulation in monocytes as a potential underlying mechanism. These findings highlight biological pathways linking stress and disease and may promote personalized interventions in high-risk populations.