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PubMed2026

Accelerated Biological Aging Increases the Risk of Head and Neck Cancer: Insights From Genetic Instruments of Epigenetic Clocks.

Epigenetic clocks are robust biomarkers of biological aging and have been associated with cancer susceptibility. However, the relationship between genetically predicted epigenetic age acceleration and head and neck cancer risk remains unclear. Using a large case-control study of 2189 head and neck squamous cell carcinoma (HNSCC) cases and 2189 age- and sex-matched controls, we investigated the associations between polygenic scores (PGSs) for multiple epigenetic clocks and HNSCC risk, and evaluated their potential causal roles using two-sample Mendelian randomization (MR). Genome-wide association study (GWAS)-identified single nucleotide polymorphisms (SNPs) associated with four epigenetic clocks (HannumAge, HorvathAge, GrimAge, and PhenoAge) were used to construct clock-specific PGSs. Logistic regression models were applied to assess associations between PGSs and HNSCC risk, while MR analyses, including inverse-variance weighted (IVW), weighted median, and MR-Egger methods, were used to infer potential causal relationships. Among the 48 epigenetic clock-associated SNPs, 12 showed nominal associations with HNSCC risk, and one variant (rs2275558 in PBX1) remained significant after Bonferroni correction (OR = 0.67, 95% CI: 0.60-0.76). PGSs for all four epigenetic clocks were higher in cases than in controls. In logistic regression analyses, each standard deviation increase in HannumAge PGS was associated with a 25% higher risk of HNSCC (OR = 1.25, 95% CI: 1.10-1.41), whereas HorvathAge, GrimAge, and PhenoAge PGSs showed weaker positive associations (ORs ranging from 1.06 to 1.10). Individuals in the highest PGS quartile for all four epigenetic clocks exhibiting 14%-25% higher risk than those in the lower three quartiles. MR analyses supported potential causal effects of genetically predicted HannumAge (IVW OR = 1.24 per SD increase, 95% CI: 1.09-1.42) and GrimAge (IVW OR = 1.23 per SD increase, 95% CI: 0.98-1.56) on HNSCC risk, with consistent estimates in weighted median analyses. Our results highlight biological aging as a potential etiologic mechanism for HNSCC and suggest that epigenetic clock-related genetic profiles may improve HNSCC risk stratification.

Humans↗

PubMed2026

Assessing the influence of different alignment tools on the accuracy of a forensic epigenetic clock.

MOTIVATION: DNA methylation (DNAm) has long been a commonly investigated biomarker in biomedical research. The current gold standard for DNAm detection is bisulfite sequencing which requires dedicated alignment tools that can handle reduced sequence complexity. One commonly used application of DNAm are epigenetic clock measurements. These clocks have been adapted by many fields for their specific needs, including forensic genetics. Here, epigenetic clocks were designed to help estimate the chronological age of a biological stain donor for investigative purposes. RESULTS: In this study, data generated with a well-established forensic epigenetic clock is aligned with four different bisulfite-specific alignment tools: "Bwa-meth," "Abismal," "Bismark," and "BS-Seeker2." For each tool, we tested up to six different settings, altering parameters such as the maximum number of mismatches or the score function setting. The goal was to investigate whether the final predicted ages differed considerably between the tested alignment tools and settings. Quality controls such as read depth, precision, recall, F1 score, and alignment run time were also assessed. To allow other researchers to easily perform such methylation comparison analyses on their own data, a Shiny app called "MethylAge Explorer" was developed within this study. None of the tested settings for the three alignment tools "Abismal," "Bismark," and "BS-Seeker2" outperformed the originally used alignment tool "Bwa-meth" in terms of age prediction accuracy. However, differences in final age predictions were observed between the different alignment tools. Therefore, it is necessary to be aware of which alignment tool to use for particular epigenetic clocks. AVAILABILITY AND IMPLEMENTATION: The data underlying this article and the code for the shiny app are available on GitHub (https://github.com/charlsut/methylage_explorer).

DNA Methylation↗

PubMed2026

DNA methylation-based ageing in a deuterostome invertebrate: an epigenetic clock for the crown-of-thorns seastar (Acanthaster cf. solaris).

Accurate and reliable ageing tools are essential for wildlife conservation and management. While DNA methylation has emerged as a promising tool for age estimation in vertebrates, its application to invertebrates remains contested and has been limited to arthropods. Here, we develop an epigenetic clock for the Pacific crown-of-thorns seastar (CoTS; Acanthaster cf. solaris), a destructive coral predator contributing to habitat degradation across Indo-Pacific reefs. Using Oxford Nanopore Technologies, we generated whole-genome DNA methylation profiles across five age groups and identified 1910 CpG sites with methylation patterns significantly associated with age. We then fitted age prediction models using elastic net regression and evaluated predictive performance with leave-one-out cross-validation (LOOCV), achieving a mean absolute error of 0.31 ± 0.22 years, corresponding to 4-6% of the CoTS lifespan (5-8 years). This accuracy suggests the potential to differentiate annual cohorts, supporting future management-relevant inference. To facilitate practical implementation, we constructed an optimized epigenetic clock from 14 CpG sites consistently selected across LOOCV iterations. Our results demonstrate that DNA methylation-based age estimation is feasible in a deuterostome invertebrate, extending epigenetic ageing approaches beyond arthropods and establishing their potential to advance age determination and management in invertebrates that lack reliable ageing methods.

Animals↗

PubMed2026

Epigenetic Clocks of Biological Aging and Cognitively Healthy Longevity: The Women's Health Initiative Memory Study.

BACKGROUND: Little is known about whether epigenetic age acceleration (EAA) clocks are capable of predicting exceptional longevity with or without preserved cognitive function. METHODS: We examined 5844 women from the Women's Health Initiative Memory Study. Fifteen epigenetic clocks were measured at baseline (1996-1999). Longevity outcomes were defined as: 1) survival to age 90 with preserved cognition (n = 1726, 29.5%); or 2) survival to age 90 with cognitive impairment (n = 956, 16.4%); vs. 3) death before age 90 (n = 2611, 44.7%). Logistic regression models examined associations between the 15 clocks and survival to age 90 (vs. death before age 90), adjusting for covariates. Multinomial logistic regression models examined associations with survival to age 90 without cognitive impairment and survival to age 90 with cognitive impairment (each vs. death before age 90), also adjusting for covariates. RESULTS: Each standard deviation increase in EAA for the first-generation clocks was associated with 7%-18% reduced odds of survival to age 90 vs. earlier death. Stronger associations were observed for second- and third-generation clocks, including AgeAccelGrim2 (OR = 0.66; 95% CI 0.61-0.71), PCGrimAge (OR = 0.64; 95% CI 0.59-0.69), PCPhenoAge (OR = 0.73; 95% CI 0.68-0.78) and DunedinPACE (OR = 0.77; 95% CI 0.72-0.82). None of the clocks was more strongly associated with survival to age 90 with preserved cognition than with survival to age 90 with cognitive impairment, relative to death before age 90. CONCLUSION: All epigenetic clocks were associated with exceptional longevity, but none were associated with cognitive healthspan. Developing clocks that can differentiate long survival with and without preserved cognitive function is critical.

Healthspan↗

PubMed2025

Scalable screening of ternary-code DNA methylation dynamics associated with human traits.

Epigenome-wide association studies (EWASs) are transforming our understanding of the interplay between epigenetics and complex human traits. We introduce the methylation screening array (MSA) to enable scalable and quantitative screening of trait-associated DNA cytosine modifications in large human populations. The MSA integrates EWASs and cell-type-linked methylation signatures, covering diverse traits and diseases. Using the MSA to profile the ternary-code DNA methylations-dissecting 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC), and unmodified cytosine-revealed a previously unappreciated role of 5hmC in mediating human trait associations and epigenetic clocks. We demonstrated that 5hmCs complement 5mCs in defining epigenetic cell identities. In-depth analyses highlighted the cell-type context of EWAS and genome-wide association study (GWAS) hits. Targeting aging, we uncovered shared and tissue-specific 5hmC aging dynamics and tissue-specific rates of mitotic hyper- and hypomethylation. These findings chart a landscape of the complex interplay of the two forms of cytosine modifications in diverse human tissues and their roles in health and disease.

Humans↗

PubMed2026

Age and early life adversity shape heterogeneity of the epigenome across tissues in macaques.

Age and early life adversity (ELA) are key determinants of health, but whether they affect similar physiological mechanisms across tissues is unknown. We generated DNA methylation (DNAm) profiles across 14 tissues in 237 semi-free-ranging rhesus macaques with naturally occurring ELA. Age-associated DNAm was predominantly tissue dependent, yet tissue-specific epigenetic clocks showed that epigenetic aging was relatively consistent within individuals. ELA effects were adversity dependent, but each ELA exerted coordinated effects across tissues. Although ELA targeted many of the same loci as age, the directions of effects differed, which indicates that ELA does not uniformly increase epigenetic age. Instead, ELA leaves a coordinated, cross-tissue epigenetic signature that is distinct from-yet intertwined with-age-related differences, which advances our understanding of how early environments sculpt the molecular foundations of aging and disease.

Animals↗

PubMed2026

Epigenetic age acceleration is not strongly associated with cardiorespiratory fitness in heart failure: a pilot study.

BACKGROUND: In heart failure (HF), standard measures such as left ventricular ejection fraction and cardiopulmonary exercise testing incompletely capture interindividual differences in disease status or prognosis. DNA methylation (DNAm) epigenetic clocks, which estimate biological age and epigenetic age acceleration (EAA), may provide complementary insight into cardiorespiratory fitness and systemic aging in HF. RESEARCH DESIGN AND METHODS: We analyzed peripheral blood DNAm from fourteen patients enrolled in REDHART2, a clinical trial of interleukin-1 blockade following hospitalization for acute systolic HF. Genome-wide DNAm was assayed using Illumina EPIC arrays and several clocks were applied to these data. Associations between biological age or EAA and cardiorespiratory fitness measures, inflammatory markers, and clinical parameters were evaluated. RESULTS: All epigenetic clocks demonstrated moderate to strong correlations with chronological age. Biological age was consistently associated with measures of cardiorespiratory fitness, particularly oxygen consumption normalized to fat free mass (VO2_FFM). However, chronological age showed similar associations, and biological age did not significantly improve prediction of VO2 parameters beyond chronological age alone. EAA was not significantly associated with cardiorespiratory fitness for any clock. CONCLUSIONS: In this pilot study, neither biological age nor EAA provided significant predictive value beyond chronological age for cardiorespiratory fitness in patients with HF. CLINICAL TRIAL REGISTRATION NUMBER: NCT03797001.

DNA methylation↗

PubMed2025

Stochastic epigenetic mutation profiles as biomarkers of clinical activity in juvenile idiopathic arthritis: a multi-omic machine learning approach for gene prioritization.

BACKGROUND: Juvenile idiopathic arthritis (JIA) is a rare autoimmune disease arising from a complex interplay between genetic and environmental factors. Epigenetic modifications such as DNA methylation (DNAm) have been described as potential mediators in gene-environment interactions, contributing to immune system dysregulation. Emerging evidence suggests that DNAm profiles also predict therapeutic responses in autoimmune diseases. This study aims to identify epigenetic biomarkers and epigenetic-driven gene expression changes associated with JIA clinical activity. METHODS: We reanalyzed a publicly available dataset of 44 JIA patients, with whole-genome DNAm and gene expression from CD4 + T cells measured at two points: at anti-TNF therapy withdrawal (T0) and eight months later (Tend). At Tend, 30 patients maintained inactive disease (ID) while 14 did not (NO ID). We investigated differences between ID and NO ID patients in the epigenetic mutation load and various epigenetic clocks through linear regression models, and prioritized genomic regions with significantly higher number of epimutations in NO ID patients through machine learning. RESULTS: We found a higher mutation load in NO ID than ID patients, both at T0 and at Tend, with the differences at Tend reaching statistical significance (p = 0.02). In contrast, we found no evidence of association between epigenetic clocks and JIA clinical activity. Using a multi-omic approach, we identified a List of candidate epigenetically-driven differentially expressed genes, 80 up-regulated and 77 down-regulated, in NO ID patients. Finally, comparing our candidate gene list with the Connectivity Map database, we identified new candidate potential therapeutic targets. Key findings were validated in independent datasets: DNAm profiles from CD4 + T cells (56 JIA patients, 57 controls) and transcriptomic data from PBMCs of JIA patients with active or inactive disease, confirming dysregulation of pathways such as TNF-α signaling via NF-kB and TGF-β signaling among others. CONCLUSIONS: We described a significant association of epigenetic mutations with JIA clinical activity, indicating that epigenetic changes might precede clinical symptoms and may serve as biomarkers for early disease monitoring. Further, our results shed light on biomolecular mechanisms of JIA, supporting the development of more effective treatments.

Humans↗

PubMed2026

Cardiomyocyte-Specific Plakophilin-2 Loss Is Sufficient to Induce Aging and Senescence of Nonmyocytes: Relevance to Arrhythmogenic Cardiomyopathy.

BACKGROUND: Pathogenic variants in PKP2 are the most common cause of familial arrhythmogenic right ventricular cardiomyopathy. This study tests whether plakophilin-2 (PKP2) deficiency only in cardiomyocytes is sufficient to provoke premature aging and proinflammatory senescence in nonmyocyte, cardiac resident cells. METHODS: We studied mice with cardiomyocyte-specific, tamoxifen-activated loss of PKP2 (cardiomyocyte-specific conditional knockout of plakophilin-2) using conventional and multiplex imaging, cytokine arrays, epigenetic clocks, spatial transcriptomics, expansion and structured illumination microscopy, and correlative data analysis. We examined nonmyocytes and cardiomyocytes for premature aging and senescence. RESULTS: We observed senescence-associated heterochromatin foci in nonmyocytes, predominantly in cells positive for α-smooth muscle actin staining. Cytokines in media of nonmyocyte cells were consistent with senescence-associated secretory phenotype. Epigenetic clocks identified premature aging. Multiplex immunohistochemistry showed nonmyocyte cells in niches, intermingled with cardiomyocytes. Spatial transcriptomics showed overrepresentation of senescence-associated secretory phenotype-related transcripts, predominantly in myocyte-rich areas of the left ventricle. Senescence-associated heterochromatin foci and increased epigenetic age were not found in cardiomyocytes from cardiomyocyte-specific conditional knockout of plakophilin-2 hearts, although we observed structural features associated with premature aging. Cross-reference analysis showed correlation between the cardiomyocyte-specific conditional knockout of plakophilin-2 cardiac proteome and that of mice 5 or 6 times their chronological age, as well as transcriptional signatures of neurodegenerative diseases. CONCLUSIONS: Loss of PKP2 expression only in adult cardiac myocytes is sufficient to induce proinflammatory senescence in nonmyocytes, and overall premature cardiac aging. This is the first study to intersect cellular senescence and premature aging with desmosomal arrhythmogenic cardiomyopathies. We speculate that cell-agnostic molecular signatures, biomarkers, and pharmacology of senescence and of neurodegenerative diseases may be relevant to diagnose or treat PKP2 arrhythmogenic right ventricular cardiomyopathy.

Animals↗

PubMed2025

A SuperLearner-based pipeline for the development of DNA methylation-derived predictors of phenotypic traits.

BACKGROUND: DNA methylation (DNAm) provides a window to characterize the impacts of environmental exposures and the biological aging process. Epigenetic clocks are often trained on DNAm using penalized regression of CpG sites, but recent evidence suggests potential benefits of training epigenetic predictors on principal components. METHODOLOGY/FINDINGS: We developed a pipeline to simultaneously train three epigenetic predictors; a traditional CpG Clock, a PCA Clock, and a SuperLearner PCA Clock (SL PCA). We gathered publicly available DNAm datasets to generate i) a novel childhood epigenetic clock, ii) a reconstructed Hannum adult blood clock, and iii) as a proof of concept, a predictor of polybrominated biphenyl exposure using the three developmental methodologies. We used correlation coefficients and median absolute error to assess fit between predicted and observed measures, as well as agreement between duplicates. The SL PCA clocks improved fit with observed phenotypes relative to the PCA clocks or CpG clocks across several datasets. We found evidence for higher agreement between duplicate samples run on alternate DNAm arrays when using SL PCA clocks relative to traditional methods. Analyses examining associations between relevant exposures and epigenetic age acceleration (EAA) produced more precise effect estimates when using predictions derived from SL PCA clocks. CONCLUSIONS: We introduce a novel method for the development of DNAm-based predictors that combines the improved reliability conferred by training on principal components with advanced ensemble-based machine learning. Coupling SuperLearner with PCA in the predictor development process may be especially relevant for studies with longitudinal designs utilizing multiple array types, as well as for the development of predictors of more complex phenotypic traits.

DNA Methylation↗

PubMed2025

Multi-omic underpinnings of heterogeneous aging across multiple organ systems.

Aging is the main determinant of chronic diseases and mortality, yet organ-specific aging trajectories vary, and the molecular basis underlying this heterogeneity remains unclear. To elucidate this, we integrated genomic, epigenomic, transcriptomic, proteomic, and metabolomic data, employing post-genome-wide association study methodologies to systematically investigate the molecular mechanisms of nine organ-specific aging clocks and four blood-based epigenetic clocks. We uncovered genetic correlations and specific phenotypic clusters among these aging-related traits, identified prioritized genetic drug targets for heterogeneous aging, and elucidated downstream proteomic and metabolomic effects mediated by heterogeneous aging. We constructed a cross-layer molecular interaction network of heterogeneous aging across multiple organ systems and characterized detectable biomarkers of this heterogeneity. Integrating these findings, we developed an R/Shiny-based framework that provides a comprehensive multi-omic molecular landscape of heterogeneous aging, thereby advancing the understanding of aging heterogeneity and informing precision medicine strategies to delay organ-specific aging and prevent or treat its associated chronic diseases.

Aging↗

PubMed2026

[Research Advances on Mechanisms and Interventions of DNA Methylation-Regulated Aging-Related Imbalance in Bone Metabolism].

Aging can induce age-related bone diseases such as osteoporosis. DNA methylation, a core epigenetic regulatory mechanism, participate in the pathological process of aging-induced bone metabolism imbalance by modulating gene expression at the epigenetic level. Using S-adenosylmethionine as a methyl donor, it exhibits characteristics of hypomethylation in genomic repetitive regions and abnormal methylation in CpG islands of promoters of key bone metabolism genes with advancing age. The "epigenetic clock" constructed based on these features can accurately predict an individual's biological age. In bone metabolism, DNA methylation disrupts the osteoblast-osteoclast balance by targeting key factors. Such abnormalities are driven by aging-related inflammation and oxidative stress, while bone loss feedback exacerbates epigenetic disorders, forming a vicious cycle. Targeted intervention strategies have demonstrated significant potential in addressing bone metabolism-related issues. Low-dose DNA methyltransferase inhibitors can improve bone metabolism; nutrients such as folate and cobalamin maintain methylation homeostasis by optimizing one-carbon metabolism pathways; while CRISPR/dCas technology enables precise regulation in the cellular and animal levels, thereby affecting bone metabolism. However, existing strategies still face challenges such as off-target effects and low delivery efficiency. Future research needs to deepen mechanistic studies, optimize intervention methods, and promote their translation into clinical prevention and treatment of osteoporosis.

DNA Methylation↗

PubMed2026

Epigenetic aging and autosomal methylation remodeling in Anderson-Fabry disease.

Anderson-Fabry disease (AFD) is a rare X-linked lysosomal storage disorder characterized by marked clinical heterogeneity and incompletely understood genotype-phenotype correlations. While X-chromosome inactivation has been extensively investigated, the contribution of autosomal epigenetic mechanisms to phenotypic variability remains poorly defined. Here, we performed an exploratory genome-wide DNA methylation analysis in 32 AFD patients (22 females and 10 males; mean age 51.7 years) recruited within a multicenter regional research project in Calabria (Italy). DNA methylation profiling was conducted using the Infinium MethylationEPIC v2.0 array. The analysis integrated two complementary approaches: differential methylation analysis and evaluation of biological aging through multiple epigenetic clocks, including Horvath, Hannum, PhenoAge, Skin & Blood, GrimAge, and DunedinPACE. Exploratory methylome-wide analysis identified a limited set of CpG loci showing nominal evidence of methylation differences between carriers of pathogenic and non-pathogenic variants; however, none remained statistically significant after correction for multiple testing. Annotation of the top-ranking nominal CpG associations highlighted genes involved in biological processes including vascular regulation, intracellular trafficking, cytoskeletal organization, immune signaling, and lipid metabolism. No significant differences between groups were observed for the conventional epigenetic age-acceleration measures examined. In contrast, carriers of pathogenic variants showed significantly higher DunedinPACE values (p = 0.0328), indicating a faster estimated pace of biological aging. This finding suggests that DunedinPACE may capture aspects of the cumulative systemic burden associated with pathogenic GLA variants, although confirmation in larger independent cohorts is required. Overall, this pilot epigenomic study provides preliminary evidence that autosomal epigenetic remodeling and biological aging acceleration may contribute to phenotypic heterogeneity in AFD.

Anderson-Fabry disease↗

PubMed2025

Genome-wide methylation biomarkers and biological aging in patients with bipolar disorder characterized for lithium response.

BACKGROUND: Epigenetic mechanisms might play a role in modulating susceptibility to bipolar disorder (BD) and response to lithium, the mainstay treatment for BD. Additionally, individuals with BD experience accelerated biological aging. METHODS: We compared blood DNA methylation profiles measured with EPIC v.2.0 arrays between patients with BD (33 lithium responders and 31 nonresponders) and nonpsychiatric controls (n = 32), as well as based on long-term lithium response. In addition, we compared cellular aging between these groups using epigenetic age, pace of aging, and, for the first time, transcriptional age acceleration based on bulk RNA sequencing in 93 patients and 56 controls. RESULTS: We identified 191 differentially methylated positions (DMPs) and 8 differentially methylated regions between patients with BD and controls, located in genes enriched for "Postsynaptic Density" (odds ratio = 6.81, p = 0.001). No DMP was significantly associated with lithium response after multiple testing correction. Patients showed a significantly higher biological age acceleration than controls based on two epigenetic clocks (GrimAge, Mann-Whitney U = 551, p = 0.0009; GrimAge2: U = 477, p = 9.0E-05) and pace of aging (DunedinPACE, t = 3.01, p = 0.003), but not on transcriptional age. While we observed no significant difference in epigenetic aging based on lithium response, lithium responders showed lower epigenetic acceleration using all clocks, with a trend observed using the PhenoAge clock (t = 1.97, p = 0.053). CONCLUSIONS: Our findings point to methylation patterns characterizing BD and support the hypothesis of accelerated cellular aging in BD.

Humans↗

PubMed2026

Characterization of DNA methylation in PBMCs and donor-matched iPSCs shows age-related methylation is reset during stem cell reprogramming.

DNA methylation is an important epigenetic mechanism that helps define and maintain cellular functions. It is influenced by many factors, including environmental exposures, genotype, cell type, sex, and aging. Since age is the primary risk factor for developing neurodegenerative diseases, it is important to determine if age-related DNA methylation is retained when cells are reprogrammed to an induced Pluripotent Stem Cell (iPSC) state. Here, we selected peripheral blood mononuclear cells (PBMCs; n = 99) from a cohort of diverse and healthy individuals enrolled in the Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing (GESTALT) study to reprogram to iPSCs. After reprogramming, the resulting iPSCs were evaluated for DNA methylation signatures to determine if they reflect the confounding factors of aging and environmental effects. Data from genome-wide DNA methylation arrays in both cell types showed that age-related methylation measured by epigenetic clocks is largely reset to an early methylation age after reprogramming of PBMCs to iPSCs. We further examined the epigenetic age of each cell type using an Epigenome-wide Association Study (EWAS) and identified a set of methylation Quantitative Trait Loci in each cell type. Our results show that age-related DNA methylation is largely reset in iPSCs, and each cell type has a unique set of methylation sites that are modified by population-level genetic variation.

DNA Methylation↗

PubMed2026

Sex-specific differences in liver DNA methylation patterns and epigenetic aging in mice.

Biological sex has been shown to influence aging outcomes, contributing to distinct trajectories in disease susceptibility and lifespan. DNA methylation patterns provide a quantitative measure of biological aging. This study investigated whether aged male and female mice display distinct liver DNA methylation patterns and differences in epigenetic aging. Liver samples were collected from 17 aged c57BL/6 mice (6 males, 11 females). Genomic DNA was extracted and bisulfite-converted before targeted enrichment of 2,045 murine age-associated CpG loci. Biological age (DNAge) was estimated using a previously developed DNA methylation-based predictor generated through elastic net regression. The difference (ΔDNAge) between DNAge and chronological age was computed. Sex-specific differences were assessed by comparing site-specific methylation ratios, ΔDNAge values, and through principal component analysis (PCA) and multiple linear regression. Twelve CpG sites across six genes (Fam84b, Zswim6, Hsf4, Mn1, Qprt, and Rapgefl1) showed significant sex-associated differences in methylation. Fam84b demonstrated the largest and most consistent sex-associated effect, with all three associated CpG sites showing higher methylation in males (regression coefficients: -0.204, -0.281, and -0.294). Zswim6 exhibited consistent lower methylation ratios in females, whereas the other genes showed higher methylation in females. There were no sex differences in biological age or ΔDNAge (P = 0.596). Although the epigenetic clock did not reveal differences between sexes in aging, aged mice did exhibit sex-specific liver methylation patterns different from those reported in younger mice, suggesting that sex-dependent epigenetic changes may emerge later in life and may reflect sexual dimorphism in liver function with age.NEW & NOTEWORTHY Males and females are known to age differently and develop certain diseases at different rates. Here, we examined the livers of aged male and female mice to see if they show different DNA methylation patterns. We found that aged male and female mice had distinct DNA methylation patterns at specific genes. Interestingly, most of these methylation differences were not present in younger mice, suggesting that sex differences in the genome may change with age.

Animals↗

PubMed2025

DNA Methylation Analysis by Bisulfite Pyrosequencing of Mouse Embryonic Fibroblasts with Reprogramming Enhanced by Thyroid Hormones.

DNA methylation is a widely studied epigenetic mark which in mammals involves the incorporation of a methyl group to the fifth carbon of cytosines, mainly those belonging to CpG dinucleotides. It has been linked to context-dependent regulatory functions ranging from gene and repetitive DNA silencing to gene body transcriptional activity. Because of its important roles during embryonic development and cell differentiation, DNA methylation can be used to track cell reprogramming by measuring the methylation levels of pluripotency-associated factors. In this scenario, bisulfite pyrosequencing is a simple, robust, and widely used technique which allows for the quantification of DNA methylation levels at small, specific regions of the genome. It involves the amplification and biotin tagging of bisulfite-converted DNA. Single amplified strands are then purified using streptavidin and finally pyrosequenced using a sequencing primer. Thus, it is an ideal method for the quantitative profiling of specific genomic regions, with applications ranging from biomarker discovery and epigenetic clock tracking to omic validation studies.

Animals↗

PubMed2025

Prenatal organophosphate ester exposure and epigenetic changes at birth: a characterization of the methylome in the ECHO cohort.

BACKGROUND: Prenatal exposure to organophosphate esters (OPEs) affects multiple child health domains. Alterations to the DNA methylome are a plausible mechanism through which these changes occur. This study characterized DNA methylation signatures at birth associated with prenatal OPE biomarkers. METHODS: We included 736 mother-infant pairs from 7 sites in the Environmental influences on Child Health Outcomes (ECHO) Cohort. Five OPE biomarkers were quantified in maternal urine samples collected during the second and third trimesters and modeled as log2-transformed continuous variables. Using covariate-adjusted linear regression, we tested associations between OPE biomarkers and locus-specific, regional, and global cord blood DNA methylation changes measured by Illumina 450 K and EPIC arrays, and gestational epigenetic age measured by the Knight gestational age epigenetic clock generated with measures from the 27 K, 450 K, and EPIC arrays. When feasible, we examined relationships by sex. FINDINGS: Global hypomethylation at multiple regions was associated with BDCPP concentrations (p = 0.003 to 0.02, coef = -0.002). Differentially methylated regions annotated to PCDHGB1 and SLC43A2 were associated with BDCPP and DPHP concentrations, respectively (FDR q < 0.05). In sex-specific analyses, global hypomethylation was associated with prenatal BDCPP (p = 0.006 to 0.03, coef = -0.0003 to -0.0002) and DBUP_DIBP (p = 0.01, coef = -0.0007 to -0.0006) concentrations in females; and global hypermethylation was associated with DBUP_DIBP concentrations in males (p < 0.05, coef = 0.0004). BCETP concentrations were significantly associated with decelerated epigenetic aging at birth in females (p < 0.05, coef = -0.05). INTERPRETATION: Prenatal exposure to OPEs impacts child methylation at birth, suggesting a potential mechanism for the association between prenatal OPE exposure and child health outcomes.

Humans↗