Epigenetics

Introduction: People with HIV have disproportionately higher rates of adverse childhood experiences compared to the general population. This, in turn, is linked to long-term physical and mental health consequences. DNA methylation - a heritable, reasonably stable and quantifiable epigenetic mechanism implicated in gene silencing - may offer a useful lens that helps understand how HIV and childhood trauma become biologically embedded and affect disease risk profiles. Methods: This study aimed to identify regional and network level methylomic signatures associated with HIV and childhood maltreatment scores in South African women who bear the highest dual burden. DNA methylation profiling using the Illumina Infinium EPIC V2 kit was performed on DNA extracted from blood samples of 238 women with or without HIV with varying levels of childhood maltreatment. Regional DNA methylation analyses, composed of correlation tests on specific CpG sites and on genetic regions, were conducted for each of HIV and childhood maltreatment scores. Thereafter, a weighted gene Co-Expression Network Analysis (WGCNA) was conducted on HIV and childhood maltreatment scores to determine co-expression modules associated with the variable of interest. Finally, causal mediation analysis of the most significant network module was conducted to clarify the direction of association. Results: Neither HIV status nor childhood maltreatment was associated with DNA methylation at site-specific or regional levels. Network methylation effects were, however, observed, with three out of four network modules that were differentially methylated in HIV, implicating genes involved in immune pathways. One network module, composed of an abundance of genes relating to neurotransmitter functioning, was associated with childhood maltreatment. Both causal analyses implied that HIV and childhood maltreatment preceded the epigenetic effects. Conclusions: The findings suggest that DNA methylation in immune pathways may partially explain the immune and neurologic effects of HIV. The link between childhood maltreatment and neuronal processes warrants further investigation.

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.

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. 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.

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.

Introduction: HIV and childhood maltreatment (CM) are both chronic stressors that disproportionately affect women, with each contributing to accelerated biological aging. Whether biological aging markers are convergent and associate with HIV and CM is unclear. Methods: We studied 238 women (122 with HIV), characterised for CM severity, and assessed biological aging using absolute telomere length (aTL), mitochondrial DNA copy number (mtDNAcn), magnetic resonance imaging-based brain-predicted age difference (MRI-BPAD), and DNA methylation age (DNAmAge) clocks. CM was measured with the Childhood Trauma Questionnaire-Short Form total score. We examined intercorrelations among biological aging markers to assess convergence and conducted linear regression models to test moderation by HIV status and CM severity. Results: PWH had shorter aTL, lower MRI-BPAD, and higher Horvath age acceleration (HorvathAA), HannumAA, PhenoAA, and extrinsic epigenetic age acceleration (EEAA). CM had limited associations with biological aging markers. Absolute TL correlated weakly with mtDNAcn (p = 0.36), PhenoAA (p = -0.18), and EEAA (p = -0.18), while MRI-BPAD correlated weakly with PhenoAA (r = 0.20). DNAmAge clocks were moderately to strongly intercorrelated (r = 0.35 - 0.93). No robust two- or three-way moderation effects were observed after false discovery rate correction. Conclusion: Our findings support a multidimensional pattern of biological aging, with substantial convergence among epigenetic aging measures but limited relationships across different markers, largely independent of HIV status and CM severity. Longitudinal approaches are needed to clarify how distinct biological aging markers relate to one another and to health outcomes over time in vulnerable populations.

Preterm birth is strongly linked to systemic inflammation and encephalopathy of prematurity, which underlies subsequent cognitive impairment. T-cell immunity contributes to brain-immune crosstalk across the life course but its role in the pathogenesis of encephalopathy of prematurity is unknown. Protein epigenetic scores are DNA methylation (DNAm)-based proxies of circulating proteins. We tested the hypothesis that T-cell dysregulation has a specific role in child neurodevelopment following preterm birth. Multimodal data were collected from 144 preterm infants (median gestational age at birth 29+5 weeks [range 23+3 to 32+6]) recruited to a prospective cohort study: saliva DNAm for protein epigenetic score derivation and brain MRI, both at term-equivalent age, and the Mullen Scales of Early Learning Composite score at 5 years from a subset. We investigated associations of the epigenetic scores for cytotoxic and regulatory T cell-associated molecule (DNAm CRTAM) and C-reactive protein (DNAm CRP; a non-specific marker of inflammation) with MRI metrics of encephalopathy of prematurity: global and regional brain volumes, and general factors of diffusion tensor imaging and neurite orientation dispersion and density imaging metrics averaged across 42 white matter tracts. We tested whether DNAm CRTAM explains more variance than DNAm CRP in MRI metrics of the encephalopathy of prematurity and cognitive scores in childhood. Higher neonatal DNAm CRTAM was associated with lower general factor of fractional anisotropy ({beta} = -0.252, q = 0.011) and higher general factors of radial diffusivity ({beta} = 0.215, q = 0.039), mean diffusivity ({beta} = 0.198, q = 0.047) and orientation dispersion index ({beta} = 0.201, q = 0.048), independent of inflammatory morbidities and other biological covariates after false discovery rate correction. DNAm CRTAM explained more variance than DNAm CRP (maximum incremental R2 = 4.2% vs 1.5%) in diffusion MRI metrics. Higher neonatal DNAm CRTAM was associated with lower cognitive scores at 5 years, independent of DNAm CRP and other covariates ({beta} = -0.332, P = 0.008), and explained more variance in cognitive scores than DNAm CRP (incremental R2 = 9.4% vs 1.2%). An epigenetic proxy of CRTAM in preterm infants is associated with both encephalopathy of prematurity in the neonatal period and lower cognitive performance at 5 years, explaining greater incremental variance than a non-specific marker of inflammation. The data implicate T-cell dysregulation in the pathophysiology of atypical neurodevelopment following preterm birth.

Chromatin profiling methods, such as ChIP-seq (chromatin immunoprecipitation followed by sequencing), are used to characterize the genomic localization of DNA-associated proteins. While ChIP and ChIP-seq have been used for decades, an orthogonal approach, CUT&Tag (Cleavage Under Targets and Tagmentation), is gaining popularity as an efficient and cost-effective alternative. Although previous comparative studies note discrepancies in signal-to-noise ratios and detection bias at certain genomic regions, many differences between ChIP-seq and CUT&Tag results remain largely unreconciled. Here, we systematically investigate the disagreeing signals captured by these two methods across well annotated genomic regions. We assess multiple histone mark profiles generated by different groups in two cell lines (K562 and MCF-7). Overall, our analysis indicates that compared to ChIP-seq, CUT&Tag may have limited sensitivity in low-GC environments and, as previously observed, increased signal in hyper-accessible chromatin. Notably, within GC-poor regions of active gene bodies and Polycomb-repressed domains, CUT&Tag exhibits a loss of H3K36me3 and H3K27me3 signal, respectively, where occupancy of these histone marks is otherwise expected. Further, active promoters with discrepant H3K4me3 and H3K27ac signal between the two assays differ systematically in GC content and chromatin accessibility. Promoters differentially enriched for CUT&Tag signal relative to ChIP-seq generally show higher, broader GC-content profiles and higher DNase-seq and ATAC-seq signal, while promoters enriched for ChIP-seq signal harbor the opposite characteristics. A local bias for high GC content and/or chromatin accessibility in CUT&Tag may also explain its differing signal patterns at nucleosome-depleted regions (NDRs) compared to ChIP-seq and MNase-seq promoter profiles. Altogether, our results highlight that studies focused on profiling the intensity and structure of histone modification occupancy can be sensitive to potential biases of CUT&Tag to GC content and chromatin accessibility. These characteristics should be accounted for when selecting a chromatin profiling approach, analyzing and interpreting data as well as drawing biological conclusions.

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.

Endometriosis is a chronic inflammatory disease associated with pelvic pain, infertility, and delayed diagnosis. Growing evidence suggests that altered DNA methylation contributes to disease development and could serve as a biomarker for disease. We developed a leakage-safe machine learning pipeline to classify endometriosis case-control status and menstrual cycle phase using genome-wide DNA methylation data from eutopic endometrial tissue. The dataset consisted of 984 samples profiled using the Illumina Infinium MethylationEPIC array, with measurements across approximately 759,000 CpG sites. Technical variation was corrected using SmartSVA batch correction. Ridge logistic regression models were trained using stratified 80/20 train-test splits, with regularization strength selected via stratified cross-validation. Feature selection approaches included ridge coefficient ranking, per-CpG t-tests, and univariate logistic regression with FDR correction. Model validity was evaluated using label-shuffling analyses. Menstrual cycle phase classification showed strong performance (mean cross-validation AUROC: 0.971, held-out test AUROC: 0.989), reflecting genome-wide hormonally driven methylation. Ridge regression produced lower but meaningful performance for endometriosis classification (mean cross-validation AUROC: 0.854, held-out test AUROC: 0.875). Ridge coefficient-based feature selection identified compact predictive CpG sets, supporting the hypothesis that endometriosis-associated methylation signal is distributed across many loci rather than a few highly predictive CpGs. Pathway enrichment analyses identified substantial enrichment for menstrual cycle phase but limited enrichment for disease status following FDR correction, consistent with a diffuse endometriosis-associated signal. These findings demonstrate that ridge regression can detect methylation patterns associated with both endometriosis and menstrual cycle phase, highlighting the importance of accounting for cycle-related epigenetic variation in endometrial DNA methylation studies.

Background DNA methylation (DNAm) based age acceleration is an indicator of biological ageing. However, it is unclear how age acceleration is linked to mental health in adolescents. We examined the longitudinal associations between DNAm age acceleration and depression and anxiety in adolescents. We also triangulated the evidence using Mendelian Randomisation (MR). Methods We analysed a subsample of adolescents (n=261) from a London-based adolescent cohort study. DNAm profile was generated from saliva samples collected at ages 11-12 years. DNAm age acceleration measures were derived from Horvath, PhenoAge, and PedBE clocks. Depressive and anxiety symptoms were measured at ages 13-15 years, using the Patient Health Questionnaire and Generalised Anxiety Disorder scale, respectively. The associations between DNAm age acceleration and depressive and anxiety symptoms were assessed using logistic regression. We also conducted a two-sample MR to investigate the potential causal relationship between Horvath and PhenoAge acceleration and depression and anxiety. Results We found that PhenoAge age acceleration was associated with higher severity levels of depressive symptoms (OR=1.04, 95% CI 1.01, 1.08) and clinically significant depressive symptoms (OR=1.05, 95% CI 1.01, 1.10). None of these three clocks was associated with anxiety outcomes. MR suggested a potential causal relationship between PhenoAge age acceleration and depression (Inverse variance weighted OR = 1.01, 95% CI 1.00, 1.02). Conclusions PhenoAge acceleration at ages 11-12 years was associated with depressive symptoms at ages 13-15 years. The association patterns are consistent between longitudinal and MR analyses. PhenoAge acceleration may represent a potential early biomarker for subsequent depressive symptoms in adolescents.

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.

Environmental exposures can induce epigenetic modifications that persist across generations, potentially contributing to the transmission of environmentally-induced phenotypes. However, the extent to which such persistence of molecular changes are maintained independently of genetic mechanisms remains unclear. In this study, we investigated the evolution and genetic determinism of DNA methylation (DNAm) variation across three successive generations of Japanese quails (G0 to G2) belonging to two epilines, defined according to whether their female ancestor had received genistein supplementation (epi+) or not (epi-). Using reduced representation bisulfite sequencing (RRBS), we characterised CpG methylation patterns and identified differentially methylated cytosines (DMCs) and regions (DMRs) between control and genistein-supplemented epilines. Out of 112,745 CpG sites analysed, no DMCs or DMRs were detected between epilines in the first generation following exposure (G0), whereas 621 DMCs (36 DMRs) were identified in G1, and 1,381 DMCs (101 DMRs) in G2. Despite this progressive increase of differential methylation sites, mean differences in methylation rate between epilines were globally small. Similarly, genome-wide genetic differentiation between epilines was very limited. Overall, SNP-based heritability of DNA methylation was 0.19 indicating that genetic variation accounted for only a small part of the global variation of DNAm levels. By contrast, DNAm at differentially methylated CpG sites was extensively under genetic control, with a mean SNP-based heritability > 0.5, and meQTL analysis further identified significant associations between SNPs and methylation levels. Together, these results indicate that local DNAm differentiation in quail is under substantial genetic regulation, while the limited genetic differentiation between groups suggests that genetic variation alone can not fully explain the progressive accumulation of methylation differences following an ancestral exposure to genistein. These results support DNAm as a plausible molecular candidate mechanism in the multigenerational response to environmental exposure and highlight the complex interplay between genetic and epigenetic regulations in the inheritance of phenotypes.

Mammalian preimplantation development requires precisely coordinated lineage decisions to establish the trophectoderm (TE), inner cell mass (ICM), epiblast (EPI), and primitive endoderm (PrE). Glucose metabolism and epigenetic regulation are increasingly recognised as key determinants of lineage specification during preimplantation development. However, how glucose-dependent metabolic cues interface with epigenetic mechanisms to regulate embryonic cell fate remains poorly understood. Here, we investigated the role of glucose in regulating protein methylation by protein arginine methyltransferases (PRMT) in bovine preimplantation development. PRMT1 and its associated histone mark H4R3me2a were detected throughout bovine oocyte maturation and embryo development. Pharmacological inhibition of Type I PRMTs using two structurally distinct inhibitors, GSK3368715 and MS023, markedly reduced global protein asymmetric dimethylarginine (ADMA) and H4R3me2a levels. PRMT inhibition impaired blastocyst cell proliferation, reduced total cell number, and disrupted both first and second lineage decisions, as demonstrated by decreased CDX2- and SOX2-positive TE and ICM cells and reduced NANOG- and GATA6-positive EPI and PrE cell allocation. Mechanistically, Type I PRMT inhibition downregulated key components of the Hippo-associated TE programme, including YAP, TEAD4, and TFAP2C. Consistent effects were observed in mouse embryos, where MS023 treatment reduced ADMA, CDX2, YAP, and TFAP2C expression and impaired TE and ICM allocation. Collectively, our findings identify Type I PRMT-mediated ADMA as an essential epigenetic regulator of early mammalian lineage specification and support a conserved ADMA-Hippo regulatory axis linking arginine methylation to embryonic cell fate decisions. In briefType I protein arginine methyltransferase (PRMT)-mediated asymmetric dimethylarginine (ADMA) is required for proper lineage specification during mammalian preimplantation development. ADMA depletion disrupts Hippo signalling, cell proliferation, and trophectoderm and inner cell mass allocation in bovine and mouse embryos.

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.

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.

Quantifying the differentiation state of cells is an important task in regenerative medicine, cellular reprogramming and in elucidating how differentiation hierarchies are altered in aging and disease. For DNA methylation data (DNAm) there is however an accute shortage of methods for quantifying differentiation state. Here we use machine learning to build EpiDiff, a predictor of differentiation that yields a continuous absolute differentiation index (DI) when applied to a DNAm sample. We extensively validate EpiDiff in single-cells, sorted cells and bulk tissue, as well as in in-vitro differentiation, organoid, reprogramming and cellular rejuvenation experiments. In mixed samples, EpiDiff measures the extent of differentiation across all cellular lineages. In sorted cell populations, we find that DI increases with age and, underpinning this increase, we discover that many cell-types undergo a developmental epigenetic drift that is most prominent towards the mesenchymal lineage. When applied to normal-tissues, EpiDiff is predictive of carcinogenic exposure and cancer risk. In summary, EpiDiff is a unique, general and versatile tool that can accurately quantify the global differentiation state of a DNAm sample with broad applicability to many disciplines.

Background: The placenta has a unique transcriptomic profile, including microRNAs that are secreted into maternal circulation throughout pregnancy. MicroRNAs are small, non-coding RNA that post-transcriptionally regulate gene expression. Spontaneous preterm birth (sPTB) is associated with substantial differences in both placental pathophysiology and placental gene expression compared to term birth. We aimed to generate microRNA signatures of sPTB and map them to target genes using a microRNA-mRNA network. Methods: This study was conducted within the Conditions Affecting Neurocognitive Development and Learning in Early childhood (CANDLE) study. Placental samples were collected at delivery, and RNA was isolated for mRNA and microRNA sequencing. To investigate sPTB, this study excluded placental samples of participants with iatrogenic indications for PTB or induced labor. We examined differences in microRNA expression in participants who delivered before 37 weeks (N=35) compared to term participants (N=404) in a series of covariate-adjusted linear regression models. We used paired placental microRNA and mRNA expression data from this cohort to validate associations between computationally predicted microRNA-mRNA pairs and establish a microRNA-mRNA network. Results: Expression of 7 microRNAs were increased in sPTB (FDR<0.05) and were inversely correlated with sPTB-associated genes involved in immune signaling. Expression of 12 microRNAs were decreased in sPTB, including 4 members of the maternally expressed chromosome 14 microRNA cluster (miR-376a-3p, miR-376c-3p, miR-377-3p, and miR-381-3p). These microRNAs were predicted to negatively regulate oxidative phosphorylation genes that were increased in sPTB. The associations between miR-376c-3p and miR-377-3p and oxidative phosphorylation were confirmed in microRNA knockdown experiments. Conclusions: This study highlights potential biological mechanisms by which placental microRNA dysfunction might contribute to sPTB and highlights putative sPTB biomarkers that may be detectable in maternal circulation.

Accurate epigenetic age prediction from DNA methylation profiles is intrinsically high-dimensional, creating a need for parsimonious models that preserve predictive performance while reducing the number of assayed cytosine-phosphate-guanine (CpG) loci. This study introduces MOSurvivor, a population-based multi-objective search framework that jointly optimizes a weight-threshold CpG selector and eight XGBoost hyperparameters. Experiments used the GSE40279 whole-blood cohort (656 individuals profiled on the Illumina HumanMethylation450 platform). After retaining 1,000 age-correlated CpGs, five strategies were evaluated on the same 30 seeded 80:20 train/test splits: fixed-parameter XGBoost using all 1,000 CpGs, random search, a genetic algorithm, particle swarm optimization, and MOSurvivor. Internal fitness was estimated using three-fold cross-validation on each training set. Across the 30 held-out test sets, MOSurvivor achieved a mean absolute error (MAE) of 4.149 {+/-} 0.300 years, root mean squared error of 5.545 {+/-} 0.392 years, and R2 of 0.855{+/-} 0.027 while retaining 211.6 {+/-} 54.8 CpGs. Relative to full-feature XGBoost (MAE 4.095 {+/-} 0.285 years), MOSurvivor reduced the feature set by 78.8% at an MAE increase of only 0.054 years (1.3%). Paired Wilcoxon tests found no significant accuracy difference between MOSurvivor and any comparator (all unadjusted p > 0.05; all Holm-adjusted p [&ge;] 0.476). The most recurrent locus, cg16867657, appeared in 29 runs, whereas mean pairwise Jaccard similarity was 0.124, indicating a small stable core embedded in multiple near-equivalent feature subsets. MOSurvivor thus offers a competitive accuracy-parsimony trade-off rather than superior absolute accuracy. External validation and leakage-free nested feature preselection remain necessary before biological or clinical translation. Keywords: epigenetic clock, DNA methylation, feature selection, multi-objective optimization, XGBoost, metaheuristics, biological aging.