Clinical Epigenetics

Aberrant DNA methylation is a hallmark of cancer, but its clinical interpretation remains debated. UHRF1, a key epigenetic adaptor for DNA methylation maintenance and chromatin bivalency regulation in embryonic stem cells, is frequently overexpressed yet shows context-dependent prognostic behaviour. By integrating bulk and single-cell transcriptomics, CpG-resolution methylation, developmental chromatin states, immune profiling and clinical outcomes across gastric (STAD), clear-cell renal (KIRC) and adrenal (ACC) carcinomas, we identified a four-class UHRF1-embryonic morphogenesis (UHRF1-EM) framework resolving this paradox. This axis revealed an inverse prognostic pattern: whilst across all three tumours EM-low and EM-high states mark better or worse prognosis, respectively, UHRF1-high levels associate with favourable outcome in STAD (UH-EML), and unfavourable in KIRC and ACC (UH-EMH). The classification proved reproducible and independently prognostic after adjustment for stage and molecular subtypes, outperforming existing classifiers and exceeding pathological stage in KIRC and ACC. Multivariable models incorporating UHRF1-EM yielded uniformly positive {Delta}C-indices. Hypermethylation associated with the UHRF1-EM axis was enriched at ESC bivalent developmental loci (EM and oncofoetal genes), but not at housekeeping cell-cycle sites. In STAD, this pattern was related to oncofoetal gene downregulation and best prognosis, whereas in KIRC and ACC it matched with gene-body/enhancer methylation, higher EM expression, immunosuppressive microenvironments and worst prognosis. Together, these findings establish the UHRF1-EM axis as a clinically robust molecular classifier and support a mechanistic model in which tumour-specific epigenetic engagement of developmental loci may contribute to the prognostic inversion, providing a foundation for further mechanistic experimental validation.

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.

Analyses of 3,370 normal human tissues of ectodermal, endodermal and mesodermal origins identified 12,587 regions averaging [~]585 bp with significant differences in DNA methylation levels within identical tissues. These methylation variants (MeVars) occurred in 8,037 genes enriched in neurological disorders and cancers of which, majority were tissue-specific rather than being systemic. This somatic variation was reduced by reprogramming in vitro into iPSCs and in vivo during spermatogenesis. Analysis of prefrontal cortices showed a higher incidence of MeVars in the candidate genes in controls than schizophrenia patients wherein a subset showed significantly altered transcript levels. Similar effects were observed for oral tissues and skin fibroblast cells. MeVars showed significant association with SINE1, simple and low complexity repeats, H3K27me3, H3k9me3 and H3K4me1 modifications and EZH2, SUZ12 and REST binding sites. Collectively, MeVars have postzygotic origins with an ability to reset during reprogramming, adding a new dimension in the form of epigenetic diversity and its relevance to disease susceptibility in humans.

Background: Suicide is a major public health concern and a highly complex, heterogeneous phenotype. Increasing evidence implicates epigenetic mechanisms, particularly DNA methylation (DNAm), in suicidal behavior. Methods: Building on previous epigenome-wide association studies (EWASs), we conducted the largest EWAS to date in postmortem dorsolateral prefrontal cortex (Brodmann area 9), analyzing DNAm and epigenetic aging (EA) in 199 suicide decedents (SD) and 190 age- and sex-matched non-psychiatric controls (NPC) using the Infinium MethylationEPIC BeadChip Array v2.0. Results: Bulk tissue analysis identified no significant differentially methylated positions or regions. In contrast, cell type-specific analysis using DNAm-deconvoluted cell proportions identified 605 differentially methylated cytosines in individual cell types (DMCTs) in excitatory neurons, 10 in inhibitory neurons, and 28 in oligodendrocyte precursor cells. Sex-stratified analyses identified mainly male-specific DMCTs, most of which were found in excitatory neurons, while comparison of violent and non-violent suicide identified additional DMCTs in glial cell types. Excitatory neuron DMCTs were enriched for synaptic, small GTPase signaling, and neurodevelopmental pathways, and overlapped genes previously associated with suicidal behavior, including MAD1L1. No significant differences in EA acceleration were observed overall or by sex or suicide mechanism. Conclusions: These findings indicate that suicide-associated DNAm patterns are primarily neuron-specific and may remain undetectable in bulk tissue, highlighting the importance of cell type-specific approaches to elucidate biological mechanisms underlying suicide.

Background: Epigenetic clocks are markers of biological aging that may vary in their sensitivity to environmental stressors and lifestyle modifiers. To evaluate the utility of these biomarkers as sensors of the human exposome, we investigated how they respond to two powerful and opposing exposures: smoking, a source of oxidative stress, and the antioxidant-rich Mediterranean diet. Objectives: We assessed the sensitivity of eleven epigenetic clocks to diet and smoking and evaluated whether Mediterranean diet adherence modifies associations between smoking and epigenetic aging. Methods: We analysed 928 participants (mean age 41 years, 59% male) from the Airwave Health Monitoring Study. Linear regression models assessed associations between Mediterranean Diet Score (MDS) and epigenetic age acceleration (EAA), alongside smoking status and blood cotinine. Interaction terms between smoking status and MDS were included to detect dietary attenuation of smoking-related EAA. Models were adjusted for demographic, socioeconomic, lifestyle, and psychological covariates. Results: Higher MDS was associated with lower EAA for GrimAge ({beta} = -0.07 SD; 95% CI: -0.13, -0.01) and Bernabeu ({beta} = -0.08 SD; 95% CI: -0.14, -0.02) after false discovery rate correction. Smoking was strongly associated with increased EAA, particularly for GrimAge, Bernabeu, and DunedinPACE. Among current smokers, effect sizes were greater in those with lower dietary adherence (e.g. GrimAge: 1.79 SD, 95% CI: 1.54, 2.04) compared with those with higher adherence (1.35 SD, 95% CI: 1.01, 1.68; P_interaction < 0.001). Similar attenuation patterns were observed for Bernabeu. Higher intake of fruits, vegetables, and whole grains contributed most to the attenuation of smoking-related EAA. Conclusions: Our findings indicate that certain epigenetic clocks effectively capture the tension between harmful and protective exposures within the exposome. Rather than suggesting that diet neutralises the risks of tobacco, these results demonstrate that specific clocks are sensitive enough to monitor how lifestyle factors modify molecular responses to environmental toxins. This highlights the value of second-generation clocks in quantifying biological resilience.

Abstract Background: Peripheral artery disease (PAD) is a common atherosclerotic condition with incompletely understood molecular drivers. DNA methylation is a key epigenetic regulator influenced by smoking, aging, and metabolic risk factors, yet genome-wide methylation patterns specifically associated with PAD remain understudied. Objective: To characterize genome-wide DNA methylation patterns associated with peripheral artery disease (PAD) using the Infinium Methylation EPIC v2.0 platform. Design: Single-center pilot epigenome-wide association study using pooled whole blood genomic DNA and pool-level bioinformatic analysis. Setting: Academic medical center. Patients: Ten adults patients diagnosed with PAD and 22 healthy controls. Interventions: None. Methods: In this prospective single-center pilot study, we performed genome-wide DNA methylation profiling on blood DNA from 10 clinically diagnosed patients with PAD (mean age 72.7 {+/-} 11.2 years; 50% female) and 22 age- and sex ratio-matched controls (mean age 74.6 {+/-} 7.8) using the Illumina Infinium MethylationEPIC v2.0 BeadChip (>935,000 CpG sites). Data was processed with the SeSAMe pipeline. Differentially methylated loci (DMLs) and regions (DMRs) were identified at FDR [&le;] 0.01 and |{Delta}{beta}| [&ge;] 0.10. Enrichment analysis of associated genes was performed using clusterProfiler (Gene Ontology, GO, and Kyoto Encyclopedia of Genes and Genomes, KEGG, computational methods). Results: Following quality control, 933,942 probes were analyzed. We observed that a majority of significant DMLs exhibited hypomethylation in PAD. Intersection of DML- and DMR-supported genes yielded 16,854 high-confidence genes. GO analysis revealed a strong enrichment for muscle system processes, regulation of membrane potential, embryonic organ development, DNA-binding transcription activator activity, actin binding, and metal ion transmembrane transporter activity. Cellular component terms highlighted cell leading edge, focal adhesion, and cell cortex. KEGG pathways were dominated by calcium signaling, cadherin signaling, MAPK signaling, and cytoskeleton in muscle cells. Conclusions: Blood DNA methylation patterns in a cohort of PAD patients are enriched in developmental vascular, muscle, and cell-motility programs that are characteristically reactivated in adult vascular pathology (endothelial dysfunction, vascular smooth muscle cell (VSMC) phenotypic switching, pathological angiogenesis). These findings generate a hypothesis for biomarker development and epigenetic therapeutic targeting in PAD. Larger longitudinal and multi-ethnic validation studies are warranted.

Long term associations of early life experiences with later life DNA methylation are understudied. In the U.S. Health and Retirement Study, participants self-reported early life experiences, including years in school, smoking during childhood, growing up in a rural area, and living with a grandparent. Later life DNA methylation was measured in blood for participants with a mean age of 69.6 years at 731,474 sites. We tested for associations between each early life experience with DNA methylation age acceleration, global and site-specific methylation, and enriched biological pathways. We compared results across early life experiences. Participants (N = 3,562) were 58.8% female and 68.1% non-Hispanic White. They reported 13 mean years in school, 18.3% smoked during childhood, 42.7% grew up in a rural area, and 26.8% lived with a grandparent. Fewer years in school (0.10, 95% CI: 0.06, 0.14) and smoking during childhood (0.65, 95% CI: 0.32, 0.97) were associated with accelerated GrimAge in later life, while living in a rural area and living with a grandparent were not associated. Early life experiences were associated (p<1x10-4) with distinct DNA methylation sites, specifically 574 sites for years in school, 20 for smoking during childhood, 49 for growing up in a rural area, and 23 for living with a grandparent. For example, one fewer year in school was associated with 0.47 (p-value = 4.61x10-15) lower percent methylation at cg07318158 in OTUD7B. Sites associated with our early life exposures were enriched for unique pathways. Years in school was enriched for embryonic development and cell structure pathways, smoking during childhood was enriched for nervous system development, exocytosis, and cell adhesion and structure pathways, growing up in a rural area was enriched for cell and vesicle processing pathways, and living with a grandparent was enriched for hormone regulation and protein breakdown pathways. Findings suggest our early life exposures are associated with unique DNA methylation patterns in later life, which can potentially allow for separate biomarker opportunities aimed at early intervention of adverse later life outcomes associated with these exposures.

IntroductionFetal development represents a critical window during which genetic and environmental influences shape lifelong health. DNA methylation (DNAm) is a candidate underlying mechanism. While individual prenatal exposures have been related to DNAm, no studies have investigated the broader prenatal exposome, nor incorporated genetics with the exposome. Here, we integrated the prenatal exposome and genetics as predictors of DNAm at birth. MethodsWe used data from the Dutch Generation R (n=2282) and English Avon Longitudinal Study of Parents and Children (ALSPAC; n=809) cohorts. We performed epigenome-wide elastic net regression, using Generation R for model development/internal validation and ALSPAC for external validation, to predict DNAm at each CpG site. We used three models: Model 1 included 42 prenatal exposures, Model 2 additionally included child sex, gestational age and birth weight, and Model 3 further included meQTLs. ResultsIn Model 1, the prenatal exposome explained on average 0.7% of DNAm variation across 347 validated CpGs (0.1% of tested CpGs). This increased to 40,044 CpGs (10.2%) with 1.3% of variation explained in Model 2, and 91,305 CpGs (23.2%) with 3.0% of variation explained in Model 3. In Model 1, prenatal smoking was the largest predictor, followed by delivery characteristics, among which meconium-stained amniotic fluid was a novel finding. In Model 3, typically both SNPs and multiple prenatal exposures were selected. DiscussionWe find that genomic associations with cord blood DNAm are stronger and more widespread than prenatal exposures, although typically, the prenatal exposome explains additional variation in DNAm beyond genetic influences.

Background. DNA methylation patterns in cord blood are robustly associated with birthweight in the general population. However, it remains unknown whether these associations extend to clinically relevant populations, such as preterm neonates or those born small for gestational age, and whether they directly reflect birthweight or are driven indirectly by genetic, familial, maternal, and obstetric factors. Methods. We calculated a birthweight methylation profile score (MPSBW) using weights of 835 CpGs previously associated with birthweight in the general population and evaluated its association with birthweight in 67 monochorionic (MC) twin pairs including 134 neonates (97% born preterm) from the Twinlife study. MC twin pairs are identical twins sharing a single placenta, often unequally, which can result in unequal resource distribution and differential fetal growth. Results. We examined the association between within-pair differences in birthweight and MPSBW, thereby estimating the association independent of factors shared equally by co-twins. A 500-gram increase in birthweight was associated with a 0.256 SD increase in MPSBW (p<0.005) in this population of preterm neonates. Adjustment for polygenic score for birthweight (PGSBW) confirmed that the observed epigenetic associations were not driven by common genetic variation underlying birthweight. Interestingly, a similar effect size (0.226 SD per 500 g birthweight increase; p<0.05) was observed in the within-pair analysis, which controls for all shared influences within a twin pair. Conclusion DNA methylation is associated with individual differences in birthweight in a high-risk clinical population of MC twins, independent of shared genetic, familial or maternal influences.

Prostate cancer remains one of the most common cancers among men globally. While significant strides have been made in diagnosis and treatment, understanding the complex genetic and epigenetic underpinnings of the disease remains crucial for guiding intervention and developing more personalized and effective therapies. The importance of DNA methylation in prostate cancer has been known for some time, but important facets of the modulation of the epigenome during carcinogenesis remain obscure, partly because the bulk of cancer methylation data have been produced using microarray technologies. Here we utilise the TruSeq methyl capture method (EPICseq) to profile the, previously defined, UK Prostate ICGC cohort of well-annotated primary prostate cancers. To this we add methylation sequencing of benign tissue from the same men. These data allow us to identify differentially methylated regions distinguishing cancerous and non-cancerous prostate tissue, while identifying numerous genes whose methylation profiles can perform that task as well as distinguishing between classes of prostate cancer. We describe a describe a methylation-based control mechanism for prostate-cancer-associated SNPs, and show that this seems a likely mechanism of action for a SNP near the MMP7 gene. We describe three novel molecular signatures that arise from different aspects of the biology of prostate cancer revealed by sequencing. Each is shown to be an independent classifier of cancers into groups with different expected times to relapse. These consist of patterns in driver gene methylation, strand-specific methylation, and signal arising in mitochondrial reads. We show that these signatures, combined with existing molecular tools, provide a powerful predictor of time to recurrence. By substantially enhancing understanding of prostate cancer risk, detection, and prognosis, we pave the way for the development of clinical practices that will benefit patients and improve outcomes.

Background: DNA methylation (DNAm) may capture cumulative genetic, environmental, and lifestyle influences on cardiovascular health. Composite DNAm score based on the American Heart Association Life's Essential 8 (LE8) framework have been linked to clinical events, but their association with early vascular changes and intergenerational effects is unclear. Methods: We studied up to 1432 participants from the multigenerational Young Finns Study (YFS-3G), including parents (G0) and adult offspring (G1). DNAm was measured using Illumina EPIC arrays in 2011 and/or 2018, and carotid intima--media thickness (cIMT) was assessed in 2018. The LE8 DNAm score was calculated as a weighted sum of methylation levels. Associations with cIMT were evaluated in intergenerational, prospective, and cross-sectional settings, adjusting for demographic, technical, and biological covariates and conventional cardiovascular risk factors. Results: Higher parental LE8 DNAm score was associated with lower offspring cIMT ({beta} = -0.022 mm/SD; p-value = 0.02), although the association was attenuated after adjustment for parental cardiovascular risk factors. In G1, a higher baseline DNAm score was associated with lower cIMT measured seven years later ({beta} = -0.030 mm/SD; p-value = 1.1 x 10-5). This association remained significant after adjustment for follow-up cardiovascular risk factors (p-value=0.009) but not after additional adjustment for prior cIMT. Cross-sectionally, higher DNAm score was associated with lower cIMT in both generations, with attenuation after risk factor adjustment in G1 but not G0. Associations with carotid plaque were not significant. Genes associated with the DNAm score were enriched for immune and inflammatory pathways. Conclusions: An LE8-derived DNAm score was associated with lower cIMT across the life course and, to a lesser extent, across generations. These findings suggest that blood DNAm reflects cumulative cardiovascular health and vascular burden and may complement conventional cardiovascular risk assessment.

Background: DNA methylation is an epigenetic modification that regulates gene expression in response to environmental exposures. We measured differential DNA methylation levels in blood before after general anesthesia and surgery in participants with and without postoperative delirium (POD) and postoperative neurocognitive disorder (PNCD). Methods: Blood sampling, delirium assessment and cognitive testing were prospectively performed at baseline before non-cardiac, non-neurologic surgery, and at 24 hours (24h) and 6 weeks (6wk) thereafter in 94 participants comprising 13 with POD and 81 without POD, and 40 with PNCD and 54 without PNCD 6wk after surgery who were matched for age and sex in the INTUIT and MADCO cohorts. DNA methylation was assessed using the Illumina Infinium MethylationEPIC Beadchip. Results: 132 differentially methylated positions (DMPs) annotated to 198 differentially methylated genes (DMGs) were identified in 94 participants 24h after surgery compared to baseline with a local false discovery rate (LFDR) <0.05 including CHRNB1, LGALS1, SMAD4, RYR2, CHST11, CDC25B, OBSCN, ABHD16A. No DMPs were identified between samples collected at baseline compared to 6wk after surgery. In baseline samples, 8 DMPs annotated to 12 DMGs were identified between participants who did and did not develop POD including MBTD1, BID, PPAN, ANGPTL6, PHF21B, and RBM5. In 24h samples, 87 DMPs annotated to 91 DMGs were identified between participants with and without POD including CLEC19A, FILIP1, ERICH1, PSENEN, SLC6A3, and TMEM196. In 6wk samples, 1 DMP annotated to FILIP1 and LOC124901509 in participants with and without POD. No DMPs in baseline, 24h or 6wk blood samples were identified between patients with and without PNCD at 6k after surgery. Conclusions: Differential DNA methylation levels are present throughout the genome 24h after anesthesia and surgery. Differential DNA methylation levels before surgery and at 24h after surgery distinguishes patients with and without POD. Differential DNA methylation levels were not identified between baseline and 6wk after surgery in the entire cohort, or between patients with and without PNCD at 6 weeks.

Background: Human aging does not follow a single trajectory. Epigenetic changes offer insight into the heterogeneity in aging by reflecting the combined influence of genetic, environmental, and lifestyle factors on the timing and progression of age-related changes beyond what chronological age alone can explain. Recent studies in cancer and aging underscore the importance of methylation variability as a marker of biological dysregulation. Methods: We investigated the role of DNA methylation in aging heterogeneity by performing epigenome-wide differential methylation and variance association analyses in blood samples from 1,445 Canadians aged 45 to 85 from the Canadian Longitudinal Study on Aging. Results: We identified 448 differentially methylated regions and 488 differentially variable regions associated with health decline as measured by the health deficit accumulation Frailty Index, cognitive function, and physical function. These two classes of regions showed minimal overlap, with distinct gene coverage, suggesting that variability contributes a complementary signal to aging heterogeneity. Genes overlapped by differentially methylated regions were enriched for immune and inflammation-related pathways, whereas differentially variable regions highlighted additional localized, CpG-island-enriched signals shared across health domains, consistent with regionally structured rather than diffuse dysregulation. By integrating significant CpGs from both analyses, we constructed an epigenetic biomarker. The biomarker was associated with all-cause mortality and showed higher discrimination than biomarkers constructed from differential methylation or variability alone, with a similar pattern reproduced in the Baltimore Longitudinal Study of Aging. Conclusions: These findings suggest that DNA methylation variability may provide a complementary dimension of epigenetic aging and support further evaluation in larger cohorts with more mortality events.

DNA methylation is a key epigenetic mechanism regulating the expression of genes involved in numerous developmental and pathological processes. However, the contribution of DNA methylation of microRNA genes to atherosclerosis remains poorly understood. In this study, we profiled DNA methylation patterns of both the regulatory elements and gene bodies of five microRNA genes (MIR10B, MIR21, MIR100, MIR127, and MIR143) in vascular tissues and paired peripheral blood cells (PBC) of 92 patients with advanced carotid atherosclerosis and 32 PBC of control participants by targeted bisulfite sequencing. We identified distinct tissue-specific DNA methylation patterns for all five microRNA genes in patients with advanced carotid atherosclerosis. The regulatory regions of MIR10B, MIR127, and MIR100 were moderately hypomethylated in carotid atherosclerotic plaques compared with intact vascular tissues. We further integrated our findings with lab-internal and publicly available epigenome-wide methylation datasets and evaluated the influence of vascular and blood cell composition using computational deconvolution approaches. After adjustment for cellular heterogeneity in vascular tissues, DNA methylation at CpG sites in MIR100 and MIR127 remained independently associated with atherosclerosis. Increased DNA methylation at a single CpG site (chr11:122025143, GRCh37/hg19) located within the MIR100 E-box region was associated with metabolic syndrome. Moreover, DNA methylation levels of MIR10B, MIR21, and MIR127 in atherosclerotic plaques were linked with indicators of histological instability and history of acute cerebrovascular events. In peripheral blood, we observed moderate hypomethylation of the regulatory regions of MIR10B, MIR21, and the MIR100 E-box region in patients compared with the control group. However, only the MIR10B remained robust against blood cell composition. In blood, MIR10B and MIR143 methylation correlated with lipid metabolism and carotid stenosis, while the MIR21 CpG island showed strong blood-plaque concordance, confirming its potential as a surrogate biomarker. Overall, advanced carotid atherosclerosis is characterized by specific tissue-altering DNA methylation patterns of microRNA genes, where alterations mainly occur in the regulatory regions, predominantly featuring hypomethylation. The results underscore the complex, cell- and tissue-specific nature of DNA methylation of microRNA genes in both the regulatory elements and gene bodies in vascular tissue and blood, highlighting the critical need to decipher these intricate epigenetic landscapes to identify reliable, robust biomarkers for assessing plaque instability and cardiovascular risk.

BackgroundAdversity during pregnancy is associated with alterations in offspring brain development. DNA methylation (DNAm) is a type of epigenetic modification is a putative mechanism for the intergenerational transfer of prenatal adversity on developmental outcomes. We examined the effects of prenatal social disadvantage (PSD) and prenatal psychosocial stress (PSS) on offspring epigenome-wide DNAm at four time points from infancy to age 4, and tested whether persistent DNAm signals mediated associations between PSD, PSS, and child psychopathology at ages 4-6. MethodsLongitudinal DNAm data (birth, Y1, Y2, Y3) was derived from salivary tissue of 281 infants (43.7% female) in the eLABE study. We examined epigenome-wide associations between DNAm and PSD and PSS. Linear models were adjusted for age, child sex, child race, maternal tobacco smoking, cell type composition, and batch effects. Mediation analyses tested whether birth DNAm mediated associations between prenatal exposures and internalizing and externalizing symptoms at ages 4-6. ResultsPSD was associated with 47 FDR-significant CpGs at birth and 3 at year 1. PSS was associated with 3 FDR-significant CpGs at birth. Thirteen CpGs showed PSD-associated significance across all four timepoints, including two CpGs associated with genes involved with neuronal maturation (BCL11B) and one CpG associated with a gene implicated in brain vascular health (ZNF474). Exploratory mediation analyses revealed an indirect effect of methylation at ZNF474 (cg19980369; p=0.028; pFDR=0.360) on the association between PSD and year 4-6 externalizing symptoms. ConclusionsPSD was associated with epigenetic signatures at birth, with a subset of associations persisting across early childhood and converging on cellular stress response biology. PSS showed minimal epigenetic associations, suggesting differential biological embedding of structural versus psychological dimensions of adversity.

DNA methylation-based epigenetic clocks estimate biological age from methylation profiles, and the difference between predicted biological age and chronological age is commonly described as age acceleration (AA). We compared AA across eight cancer types, lung, colorectal, breast, thyroid, bone marrow and blood, kidney, uterus, and head and neck, using seven epigenetic clocks and 5,528 publicly available samples. Across the 56 cancer type clock combinations, tumor tissues showed higher average AA than normal tissues in 44 comparisons. The uterus cohort showed the clearest deviation from this overall trend, with normal samples exhibiting higher AA for six of seven clocks. Analyses of paired normal and tumor samples generally showed higher predicted ages and greater variability in tumor samples. We additionally examined age-associated methylation changes and the ability of clock CpGs to distinguish tumor from normal tissue. Several discriminatory CpGs were shared across cancer types and frequently showed tumor-associated hypermethylation at cancer-related loci. Small subsets of top-ranked CpGs captured substantial discriminatory information. Age-stratified subsampling preserved the main AA patterns, suggesting that chronological-age differences did not explain the observed tumor-normal differences. Overall, these findings highlight broad cancer-associated alterations in epigenetic aging together with substantial cancer type- and clock-specific heterogeneity.

Trained immunity and clonal hematopoiesis are two newly identified immunological phenomena that contribute to the pathophysiology of atherosclerotic cardiovascular disease. These two phenomena share some convergent molecular mechanisms, such as IL-1{beta} being a central regulator and involvement of epigenetic enzymes. Therefore, we hypothesize that presence of clonal hematopoiesis driver mutations (CHDMs) can predispose to an increased capacity to build trained immunity. We previously characterized how the presence of CHDMs relates to immune cell function and vasculometabolic complications in a cohort of older individuals with overweight and obesity. From this cohort we now selected 17 individuals with CH due to DNMT3A mutations and 15 without any known CHDMs. We performed in depth immune characterization via flow cytometry, functional assays with monocytes and neutrophils, and we measured the capacity to build trained immunity using {beta}-glucan and oxLDL as stimuli. We corroborated our previous findings of lower ex vivo cytokine production capacity of PBMCs from individuals with DNMT3A mutations. Importantly, presence of DNMT3A CHDMs associated with higher trained immunity response. Moreover, we demonstrated that individuals with DNMT3A mutations were characterized with higher CD10+ mature neutrophils and a lower neutrophil MPO release upon TLR2 stimulation. In conclusion, presence of DNMT3A CHDMs is associated with increased susceptibility to build a hyperresponsive trained monocyte phenotype. The exact molecular mechanisms behind this phenomena requires further investigation.

Background: Fragile X-associated Tremor/Ataxia Syndrome (FXTAS) is a late-onset neurodegenerative disorder caused by FMR1 premutation CGG repeat expansions (55-200 repeats). The epigenetic landscape of the FXTAS brain remains uncharacterized. We performed genome-wide DNA methylation profiling of postmortem prefrontal cortex tissue to identify differentially methylated positions (DMPs) and candidate genes, and sought protein-level support for a neuroinflammatory signal. Methods: DNA methylation was profiled in postmortem prefrontal cortex (Brodmann area 9) from 27 male FXTAS cases and 29 male controls using the Illumina MethylationEPIC array (EPICv1 and EPICv2 platforms), merging 721,802 common probes. Surrogate variable analysis (SVA) controlled for confounders. DMPs were defined by p-value and FDR < 0.05; exploratory Reactome 2024 pathway analysis was performed on the DMP-associated gene list. Targeted proteomic profiling was performed in the same brain region using the Olink (proximity extension assay) Inflammation panel in 9 FXTAS cases and 12 controls, with SVA-adjusted differential abundance analysis, and concordance assessment against a prior mass spectrometry dataset. Results: We identified 108 significant cg-type DMPs mapping to 80 genes (50 hypermethylated, 58 hypomethylated in FXTAS). The strongest signal was CYP2E1 (7 concordant hypomethylated DMPs), an oxidative stress gene also implicated in Parkinsons disease. FTCD, a one-carbon cycle enzyme, carried 5 hypermethylated DMPs. A cluster of DMP-associated genes with established roles in innate immune and NF-kB signaling, TRAF3 (the single most significant DMP among the inflammation genes, hypermethylated), BATF, RCOR1, and MSI2; they pointed toward neuroinflammatory dysregulation. Additional genes included LINGO1 (myelination inhibitor), SYT3 (synaptic vesicle), and SLC39A4 (zinc transporter). Exploratory Reactome enrichment using the DMP-associated gene set nominated themes including neuroinflammation resolution, axonal growth inhibition, zinc homeostasis, and CYP2E1 metabolism at nominal significance (p<0.05); however, the gene-to-pathway mapping rate was low and no pathway survived correction for multiple testing. Olink proteomic analysis independently identified 60 significantly altered inflammation proteins (59 downregulated), including CXCL8, CXCL10, IL6, IL15, IL18, TLR3, IRAK1/4, and complement C1QA, which were directionally concordant with prior mass spectrometry data. Conclusions: This integrated study reveals a genome-wide epigenetic signature in the FXTAS prefrontal cortex implicating oxidative stress, myelination failure, zinc dysregulation, one-carbon cycle disruption, and most notably a coordinated set of epigenetically altered genes governing innate immune and NF-kB signaling. Convergence of TRAF3 hypermethylation with independent downregulation of TLR3 and NF-kB-pathway proteins at the protein level supports a coherent, cross-platform model of dysregulated neuroinflammatory signaling in FXTAS, identified here through individual gene- and protein-level convergence rather than formal pathway enrichment. FTCD hypermethylation proposes a self-reinforcing epigenetic loop via SAM depletion. These multi-omic findings establish FXTAS as a disorder of pervasive epigenetic reprogramming and nominate candidate genes for future mechanistic and therapeutic investigation.

Epigenetic ageing and tumor progression have each been studied extensively using DNA methylation, yet their relationship remains poorly understood. Here we integrate DNA methylation age estimation with phyloepigenetic reconstruction across 20 solid cancer spanning 1710 samples from The Cancer Genome Atlas to assess age acceleration in tumor tissue compared to matched normal tissue. MethodsDNA methylation age was estimated for 544 patients with matched normal and tumor samples using Horvaths epigenetic clock, with linear regression used to assess correspondence to chronological age and Wilcoxon signed-rank tests evaluated whether tumor-normal age differences deviated significantly from zero. Tumor evolutionary architecture was reconstructed via UPGMA clustering of genome-wide methylation divergence into phyloepigenetic trees, from which trunk and private methylation events were classified and their chromosomal distribution compared descriptively across cancer types. ResultsApplying Horvaths epigenetic clock to normal tissue yielded a mean absolute error of 17.6 years, substantially exceeding expectations. Contrary to previous reports of pronounced tumor age acceleration any ubiquitous pattern of acceleration did not emerge at the cohort level across all tumor types when tumor age was compared directly against matched normal tissue. Acceleration and deceleration instead varied often consistently by cancer types, with significant positive differences observed in endometrial, lung squamous, head and neck, and prostate cancers, and significant negative differences in renal and thyroid cancers. Phyloepigenetic reconstruction revealed that methylation events arose predominantly through private, subclonal branching rather than early clonal events. The X chromosome was found overrepresented among methylation events across nearly all solid cancers. ConclusionEpigenetic aging in cancer is not uniform or consistently accelerated but reflects tissue-specific and often opposing patterns of change. The predominance of subclonal events suggest ongoing epigenetic diversification throughout tumor evolution, while the consistent overrepresentation of X-chromosome events indicates a distinct chromosome-level vulnerability.

Sex differences influence the incidence, timing, clinical presentation, and outcomes of cardiovascular disease (CVD), yet the molecular programs through which aging interacts with biological sex remain insufficiently understood. To address this gap, we integrated basal gene expression profiles from multiomics data across 981 donors and 17 CVD-relevant tissues with regulatory, genetic, network, disease-expression, and druggability information to characterize sex-dimorphic aging patterns in 1,176 candidate CVD genes. Using a two-step expression analysis, we identified 4,404 genes with significant age-associated expression trends (BH-FDR < 0.05), including 2,718 male-specific, 202 female-specific, and 742 shared trends. Concordant evidence across complementary statistical approaches highlighted 35 high-confidence sex-dimorphic genes, including REN, APOE, GUCY1A2, and SRD5A2. Regulatory analysis showed that most CVD genes were influenced by nearby genetic variants, with 96.2 Network-based analyses further suggested that CVD genes are organized within hierarchical biological structures, with curated protein-interaction data showing stronger geometric organization than broader interaction resources. Integration with Open Targets identified 289 genes already linked to approved drugs and 48 of the top 50 biomarker candidates supported by GWAS-eQTL colocalisation evidence. A final composite ranking prioritized NTRK1, TUBB4A, PTGS2, IL6, and PDE5A, and identified 19 actionable biomarkers supported by convergent expression, regulatory, genetic, and therapeutic evidence. Among these, a dedicated sex-specific evidence score nominated GUCY1A2, CACNA1D, PGR, PDE5A, and LEPR as the strongest candidates for sex-stratified validation, with GUCY1A2 and PDE5A converging on a nitric oxide-cGMP signaling axis. This study provides an integrative framework for discovering sex-dependent molecular signatures of cardiovascular aging and for prioritizing biologically supported, potentially actionable targets for precision cardiovascular medicine.