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: 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.

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: 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-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.

DNA methylation changes accumulate with age through both regulated and stochastic processes, yet the determinants of epigenetic information loss remain poorly defined. Using genome-wide DNA methylation profiles from 1,531 healthy human samples spanning 14 tissues, we quantified epigenetic noise by Shannon entropy and corrected it for cellular and tissue heterogeneity. Adjusted entropy was consistently low in promoters, first exons and CpG islands, and high in CpG-poor and intergenic regions. Cumulative mitotic history showed a stronger association with epigenetic noise than chronological age, explaining most of its variance particularly within CpG-rich regulatory regions. By contrast, age-related, replication-independent effects predominated outside CpG islands and in low-proliferative tissues such as the brain. Moreover, biological age acceleration was largely attributable to cell division in a tissue-specific manner. Collectively, mitotic history emerges as a major determinant of epigenetic noise accumulation across human tissues, while genomic context modulates regional vulnerability to methylation information loss during aging.

BackgroundDNA methylation-based biomarkers have enabled robust estimation of biological age across tissues, and longitudinally trained measures such as DunedinPACE provide estimates of the pace of aging from blood methylomes. However, longitudinal methylation data are often unavailable, particularly for minimally invasive tissues such as buccal mucosa. Here, we developed a pseudo-longitudinal framework to estimate a buccal mucosa-derived PACE-like aging-rate score from cross-sectional methylome data. MethodsWe used a buccal biological age estimator as an internal pseudo-time axis. Methylation beta-values were transformed to M-values, and CpG-specific smooth functions of biological age were fitted in cross-validation. Local derivatives of these functions were used to project each individuals buccal methylome forward by a small time step. The projected methylome was converted back to beta-values, biological age was recalculated, and the change in biological age per unit time was defined as a pseudo-aging velocity. This raw velocity was transformed to a non-negative PACE-like score centered at 1.0. We then trained cross-fitted models to predict the derived score from buccal CpG methylation profiles. ResultsIn 151 individuals, the proposed score was reproducibly predicted from buccal methylomes in out-of-fold analysis, with a Pearson correlation of 0.706 and Spearman correlation of 0.710 between observed and predicted PACE-like scores. Sensitivity analyses across CpG selection size and regression models showed broadly consistent performance. In contrast, the proposed buccal PACE-like score showed only modest association with measured DunedinPACE, and alternative attempts to reconstruct DunedinPACE from buccal methylomes, including supervised proxy modeling and buccal-to-blood CpG imputation, showed limited sample-level performance. ConclusionsThese results support the feasibility of deriving a tissue-specific PACE-like aging-rate score from cross-sectional buccal methylome data by treating biological age as a pseudo-time axis. The proposed score should not be interpreted as a replacement for blood-derived DunedinPACE, but rather as an exploratory buccal methylome dynamics index that may capture tissue-specific aging-related variation.

Abstract. Introduction: Preterm birth drives adverse perinatal maternal and infant health outcomes through heterogeneous symptoms, severity, and etiologies. Delivery prior to reaching 37 weeks of gestation may result from medically indicated intervention for pregnancy complications or spontaneously in the absence of prior symptoms. Placental tissue collected following preterm birth exhibits differential DNA methylation compared to full-term placentas and may indicate pregnancy health during gestation. Placental DNA currently has limited utility for assessing health of ongoing pregnancy, as sampling placental tissue during gestation increases the risk of infection and miscarriage. Risks associated with placental sampling during pregnancy limit the use of DNA methylation in clinical preterm birth prediction. Assessing preterm birth risk during gestation requires non-invasive methods for characterizing placental DNA methylation. Results: We quantified genome-wide DNA methylation patterns of hypermethylated cell-free DNA in pregnant (n = 99) and non-pregnant (n = 93) plasma using cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq). In each sample, we assessed DNA methylation status in 300-bp genomic windows, examining both sequencing read counts and calculated absolute molar DNA amount. Known hypermethylated placental regions, including RASSF1, STAT5A, and ERG promoters showed significantly increased odds of detection in pregnant samples, suggesting enrichment of cell-free placental DNA. Of the 536,444 300-bp windows examined, 173,071 (32%) showed significant enrichment in pregnant plasma. Linear modeling identified 107,505 differentially methylated regions (DMRs) associated with pregnancies later diagnosed with intrauterine growth restriction (IUGR) (n = 22). Alu elements showed increased representation in these DMRs than expected, while other repetitive elements exhibited underrepresentation. Discussion: These results demonstrate cfMeDIP-seq's ability to enrich for cell-free placental DNA and characterize cell-free DNA methylation signatures of pregnancies complicated by IUGR. Enrichment of cell-free placental DNA enables non-invasive profiling of placental DNA methylation from maternal plasma. Detectable epigenetic signatures in maternal plasma may identify pregnancies at elevated risk for preterm birth before clinical symptoms appear. Our findings further highlight the potential of cell-free placental DNA for monitoring pregnancy health.

Background: Contemporary cardiovascular disease (CVD) risk equations may not fully capture cumulative biological aging or long-term exposure burden. DNA methylation (DNAm) biomarkers may capture aging- and exposure-related biology, but their incremental prognostic value beyond clinical risk-factor models like PREVENT remains uncertain. To our knowledge, no prior study has benchmarked DNAm-based biomarkers with PREVENT. Methods: In a population-based cohort study, we analyzed NHANES 1999-2002 participants with DNAm biomarkers and mortality follow-up. We derived a DNAmScore from candidate DNAm biomarkers using elastic-net Cox regression with repeated nested cross-validation. A PREVENT-like clinical model was defined as a Cox model fit in NHANES using PREVENT predictors. Weighted Cox models estimated the association between DNAmScore and mortality after adjustment for PREVENT-like clinical predictors. We then compared the PREVENT-like clinical model, DNAmScore alone, and a combined model (PREVENT-like clinical predictors plus DNAmScore) using cross-fitted C-index, time-dependent AUC, calibration, and Brier score. Results: Our cohort included 2,282 participants; 597 and 937 deaths occurred by 10 and 15 years, respectively. After adjustment for PREVENT-like clinical predictors, the cross-fitted DNAmScore was strongly associated with all-cause mortality (HR per 1-SD increase, 2.43; 95% CI, 1.97?2.99). At 10 years, AUCs were 0.791 for the PREVENT-like model, 0.791 for DNAmScore, and 0.803 for the combined model. At 15 years, corresponding AUCs were 0.825, 0.822, and 0.835. Compared with the PREVENT-like model, the combined model improved AUC by 0.013 (95% CI, 0.006?0.020) at 10 years and 0.010 (95% CI, 0.004?0.015) at 15 years. The combined model had lower Brier scores at all three horizons with similar calibration. DNAmScore remained associated with CVD mortality after clinical adjustment. Conclusions: DNAmScore identified residual biological risk beyond PREVENT-like clinical predictors, with strong independent mortality associations and modest, consistent improvements in cross-fitted prediction performance. These findings support development and external validation of CVD-specific DNAm biomarkers.

BackgroundPrenatal growth restriction has been associated with adverse neonatal and long- term health outcomes, yet the epigenetic mechanisms by which an adverse intrauterine environment shapes fetal immune development remain incompletely understood. Monozygotic dichorionic-diamniotic twins with selective fetal growth restriction (sFGR) provide a unique human model for investigating environmentally driven developmental programming independent of genetic variation and inter-twin placental vascular anastomoses. MethodsUmbilical cord blood buffy coat samples were collected from three sFGR and two gestational age-matched concordant control twin pairs. Bulk RNA sequencing and genome-wide DNA methylation analysis were performed, followed by differential expression, pathway enrichment, hematopoietic and immune module analyses, differential methylation, and integrative transcriptomic-epigenomic analyses. ResultsCompared with concordant control twin pairs, discordant twins exhibited broad attenuation of immune and inflammatory transcriptional programs alongside enrichment of erythroid- and hypoxia-related pathways, consistent with adaptive hematopoietic responses to intrauterine stress. Within discordant twin pairs, the growth-restricted co-twins displayed marked transcriptional asymmetry characterized by selective enrichment of cytotoxic lymphoid signatures despite global suppression of myeloid and antigen-presenting cell-associated programs. Integrated transcriptomic and epigenomic analyses further revealed coordinated epigenetic remodeling, with hypomethylated regions in growth-restricted twins enriched for immune regulatory pathways, including T cell differentiation and leukocyte activation. At selected loci, concordant hypomethylation and increased gene expression suggested a potential epigenetic basis for the observed immune remodeling. ConclusionsThese findings suggest that intrauterine growth restriction is associated with coordinated hematopoietic and immune reprogramming at birth, consistent with both compositional and cell-intrinsic alterations. In genetically identical twins, relative growth divergence was associated with polarized transcriptional states, highlighting how intrauterine environmental differences may shape early immune development independent of genetic background.

Vaccine responses vary across individuals due to differences in ageing and health status. Using transcriptomic profiling, we analyzed early gene expression profiles after influenza (QIV) followed by pneumococcal (PCV13) vaccination in 148 participants spanning young, middle-aged, and older adults. The two vaccines induced distinct immune signatures: QIV elicited innate and interferon immune activation, while PCV13 triggered inflammation-based responses. Older adults showed weaker but similar transcriptomic profiles compared to young adults. Among older adults, frailty, in addition to age, was strongly associated with reduced innate responses. In addition, we identified associations between early-stage transcriptomic profiles and later-stage antibody responses for QIV; however, no such associations were observed for PCV13. Importantly, observed group differences arose not from altered immune modules but from differences in the magnitude of gene expression, paving the way for immune-boosting interventions to enhance early gene expression in at-risk populations.

Ageing and cytomegalovirus (CMV) infection drive major alterations to T-cell immunity. Age is also associated with an increased risk of cancers including melanoma, which is treated with T-cell modifying immune checkpoint blockade (ICB). However, the extent to which age, CMV, and treatment-induced immune changes interact to shape clinical outcomes remains poorly understood. We investigated this through flow cytometric evaluation of pre- and early on-treatment blood samples of 79 advanced melanoma patients. Age and CMV infection were associated with significant and largely distinct changes to T cell phenotype pre-treatment but had no impact on clinical outcome. Older patients ([&ge;]65 years) had fewer CD8+ Tnaive, CD4+ Tcm, TFH, and B cells, and increased CD8+ TemRA, but similar cytokine and inhibitory marker expression. Conversely, CMV drove expansion of CD8+ and CD4+ TemRA cells with enhanced effector function without reducing naive populations. One cycle of PD-1 and CTLA-4 ICB induced immune cell expansion and phenotype changes of greater magnitude and partially distinct from those seen during PD-1 with or without LAG-3 ICB, but these effects were largely independent of age or CMV serostatus. Hence, neither ageing nor CMV were associated with clinical outcome or immunological response to ICB in advanced melanoma patients.

Despite extensive epigenetic reprogramming, induced pluripotent stem cells (iPSC) from schizophrenia patients (SZ) retain several molecular and functional features of this disease. Transcriptomic and epigenomic analyses were performed in iPSC of SZ and healthy control subjects (HC). Transcriptional profiles were largely similar between SZ and HC iPSC, whereas pronounced differences emerged following neural differentiation, with SZ NSC exhibiting dysregulation of genes involved in neurodevelopment and synaptic function. ZNF5c0 was identified as a uniquely and consistently upregulated gene in SZ iPSC, robustly discriminating SZ from HC iPSC. Epigenomic profiling revealed increased chromatin accessibility and reduced DNA methylation at the ZNF5c0 promoter in SZ iPSC. ChIP-seq data suggested that ZNF560 can bind to promoters of genes implicated in synaptic signaling and neuronal development. Moreover, a subset of these genes was found to be differentially expressed in SZ neural stem cells. Together, our results identify ZNF5c0 as a reprogramming-resistant epigenetic marker of schizophrenia and suggest an altered KRAB-ZNF-mediated regulation in early neurodevelopmental pathways underlying this disorder.

Global incidence and outcomes of glioma have been found to vary significantly by region, however research into the disease continues to lack diversity. Here we investigated epigenetic patterns in glioma subtypes from cohorts collected from China and the USA. We retrospectively analysed the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets following reclassification of glioma subtypes based on the WHO 2021 central nervous system (CNS) tumour classification. We used DNA methylation and transcriptomics data to identify methylation-driven cancer genes in the CGGA cohort, assessed their prognostic value and compared against the non-Hispanic White cohort in the TCGA database to consider ethnic influence. Furthermore, we used machine learning classification and clustering techniques to identify methylation patterns in glioma subgroups. Here, we showed that DNA methylation profiles of CGGA glioblastomas have a methylation signature more similar to TCGA high-grade astrocytomas: 58.1% of CGGA glioblastomas were identified as high-grade astrocytomas using classification modelling. Assessment of survival revealed that CGGA glioblastoma patients had a significantly better survival rate than non-Hispanic White glioblastoma patients (p = 0.037). Four key methylation-driven genes were identified in the CGGA glioblastoma samples: GLDN, PRKDC, S100A1 and NCAPH. Hypermethylation of GLDN significantly suppressed gene expression in all glioma subtypes in only the East Asian cohort; a gene that has not been previously described as a driver in gliomas. Together these data suggest alternative epigenetic mechanisms occurring in glioma subtypes of different ethnic populations, which is important for our understanding of glioma and strategies for personalized treatment.

Hyperglycaemia is a hallmark of diabetes and a major risk factor for diabetic kidney disease (DKD). However, the molecular consequences of long-term cumulative hyperglycaemia (CH) remain unclear. As a stable epigenetic modification, DNA methylation may capture past glycaemic exposure. Here, we assessed CH-associated DNA methylation in 1,245 participants with type 1 diabetes (T1D) from Finland and the United Kingdom-Republic of Ireland cohorts. We identified 17 CH-associated CpGs, with the strongest association at cg19693031 (TXNIP). Longitudinal analyses demonstrate that these CH-associated DNA methylation levels remain stable despite short-term glycaemic fluctuations, suggesting lasting epigenetic imprints of earlier metabolic control. Integrative analyses combining genomic, epigenetic, and proteomic data characterized these CpGs and potential target proteins. Mendelian randomization suggested a causal association between cg20853880 (KLF11) and DKD, supported by chromatin accessibility and kidney KLF11 expression. Our findings suggest that epigenetic changes contribute to metabolic memory and may mediate the effects of hyperglycaemia on DKD.

Background Hypertension is a major global health challenge with well-established cardiovascular risks, yet its relationship with bone mineral density and the skeletal relevance of antihypertensive-related targets remain unclear. Methods Based on individual-level data from 366,443 European-ancestry participants in the UK Biobank, this study adopted restricted cubic spline models to explore linear and nonlinear associations between systolic/diastolic blood pressure (SBP/DBP) and heel estimated bone mineral density (BMD). We stratified participants by median DBP to conduct systematic biomarker analyses covering renal, endocrine, inflammatory and metabolic indicators. Drug-target Mendelian randomization (MR) combined with colocalization and mediation analyses was further performed to identify and validate causal antihypertensive-related target genes associated with BMD. Results A significant inverted U-shaped association was identified between DBP and BMD (P non-linear=3.23e-9), with peak BMD observed at a DBP of 80-90 mmHg, while SBP showed a trend of nonlinear correlation. Biomarker analyses revealed that renal biomarker cystatin C and endocrine biomarker IGF-1 exhibited DBP-dependent associations with BMD, mediating the nonlinear DBP-bone density relationship. Drug-target MR demonstrated that genetically proxied MMP9 expression (ACE inhibitor-related) was negatively correlated with BMD (beta=-0.036, P=5.29e-6), whereas CACNA1G expression (T-type calcium channel blocker target) was positively associated with BMD (beta=0.042, P=1.57e-9). Conclusion The inverted U-shaped association between blood pressure and bone mass might partly reflected by renal dysfunction. Antihypertensive pathways mediated by MMP9 and CACNA1G exert opposing effects on bone mass, implying that skeletal health should be considered when selecting antihypertensive agents for vulnerable older populations.