ABSTRACT Cutaneous melanoma, a highly aggressive and therapy-resistant skin cancer, is characterized by its remarkable cellular plasticity, enabling tumour cells to switch between different phenotypic states. This plasticity contributes to tumour heterogeneity and is regulated by key transcription factors. Long non-coding RNAs (lncRNAs) are emerging as crucial regulators in melanoma progression, yet much remains to be explored regarding their role in phenotype switching. In this study, we analysed long non-coding RNAs (lncRNAs) across different murine melanoma cell lines, identifying a set of lncRNAs potentially involved in regulating melanoma phenotypic state through cis-regulation of neighbouring protein-coding genes. We demonstrated that the lncRNA Dlx4os regulates genes associated with melanoma plasticity, favouring a mesenchymal-like, undifferentiated state. Dlx4os knockdown redirected melanoma cells to a more differentiated and less malignant phenotype, confirmed by differential expression of phenotypic state markers (Sox10, Mitf, Tgfβ, Sox6, Mlana), reduced their invasive and migratory potential, and delayed tumour progression in vivo. Furthermore, we identified a human orthologue of Dlx4os. Our findings highlight the potential of Dlx4os as both a biomarker and therapeutic target, capable of modulating melanoma’s phenotypic plasticity to influence treatment response and metastasis.

Heart failure arises from maladaptive remodelling driven by genetic and epigenetic networks. Using a systems genetics framework, we mapped how DNA variants and CpG methylation shape cardiac transcriptomes during beta adrenergic stress in the Hybrid Mouse Diversity Panel, a cohort of over 100 fully inbred mouse strains. Expression QTLs (eQTLs), methylation QTLs (mQTLs) and methylation-driven eQTLs (emQTLs) were generated from over 13k expressed genes and 200k hypervariable CpGs in left ventricles. We discovered hundreds of regulatory 'hotspots' that control large portions of the genome, including several that regulate over 10% of the transcriptome and/or methylome. Approximately 16% of these hotspots overlapped with prior GWAS or EWAS signals. We focus on a hotspot on chromosome 12 and identify the serpine peptidase inhibitor Serpina3n, as the most likely driver gene in this hotspot. Experimental knockdown of Serpina3n in neonatal rat ventricular cardiomyocytes blunted hypertrophy induced by a variety of hypertrophic signals, while altering predicted target expression and modulating the activity of Nppa and Nppb. Together, these findings position Serpina3n as a major regulator of stress-responsive cardiac gene programs, highlighting how integration of genetic and epigenetic signals can pinpoint key drivers of heart failure.

ABSTRACT Fetal repair of spina bifida aperta (fSBA) is an established intervention that improves neurological and neurodevelopmental outcomes. The present exploratory study examines whether molecular signatures related to stress regulation are detectable in newborns following this procedure. Specifically, we investigated DNA methylation and gene expression of two stress-regulatory genes, NR3C1 and FKBP5. Within a clinical trial (ID: NCT04027374), we analyzed postpartum saliva samples from newborns who had undergone fSBA repair (fSBA group; n = 30) and compared them with two control groups: newborns exposed to antenatal glucocorticoids for lung maturation (LMI group; n = 12) and healthy controls (HC group; n = 27). Pyrosequencing and qRT-PCR were used for epigenetic and transcriptional analyses. Significant group differences were observed in FKBP5 methylation, particularly at intron 7 CpG sites 5–7. The fSBA group showed lower methylation at site 5 but higher methylation at sites 6–7 compared to controls. No significant methylation differences were detected for NR3C1. Conversely, NR3C1 gene expression was elevated in the fSBA group, whereas FKBP5 expression did not differ between groups. These findings suggest gene- and site-specific molecular variation in newborns following fetal surgery. Given the exploratory nature of the study, the results are not suited to draw specific clinical implications but may inform future work aimed at understanding stress-related molecular alterations surrounding fetal interventions. Larger and longitudinal studies are warranted to clarify the robustness, developmental course, and potential clinical relevance of these molecular patterns.

ABSTRACT In recent years, the incidence of gestational diabetes mellitus (GDM) has been steadily increasing, posing risks to the long-term health of both mother and child. We aim to characterize blood glucose levels of pregnant women and predict the risk of GDM during early pregnancy through plasma cell-free mRNA and non-coding RNA (cfRNA). Here, we collected plasma samples from 108 pregnant women (54 with GDM and 54 controls) at around 16 weeks of gestation. Following high-throughput sequencing, we performed differentially abundant genes analysis and evaluated correlations between cfRNA profiles and blood glucose levels. Based on these findings, we developed a predictive model utilizing cf-mRNA and cf-lncRNA signatures. We found that ribosomal genes (RPL/RPS) are decreased in GDM, negatively correlated with 1hGlu and 2hGlu, and enriched in protein synthesis metabolic pathways. Additionally, placental-derived cfRNA contributed less to plasma in GDM, with placental-specific gene IGF2 significantly negatively correlated with blood glucose. Furthermore, 35 blood glucose correlated-cfRNA genes accurately predict GDM, with area under the curve of 0.84 in internal testing and 0.73 in external validation cohort. Our study reveals significant alterations in protein metabolic pathways and placenta-derived RNAs in plasma cfRNA prior to GDM diagnosis.

ABSTRACT DNA methylation (DNAm), capturing chronological gestational age (GA) and epigenetic gestational age acceleration (EGAA), can be modified by environmental exposures. The Asthma&Allergy array is a new DNAm array developed with content focused on asthma and allergy loci. The association between content on the Asthma&Allergy array and chronological GA and EGAA has not been evaluated alone or in the context of prenatal/perinatal exposures. We performed an epigenome wide association study (EWAS) chronological GA at single CpG sites and regions in cord blood from 391 newborn children from a Detroit-based birth cohort. We further constructed a multi-CpG site methylation model to predict chronological GA. Also, associations between prenatal/perinatal environmental factors with GA, epigenetic gestational age (EGA), and EGAA were assessed. We identified 2,435 CpG sites associated with chronological GA, and CpGs within the HLA class II locus (HLA-DRB1, HLA-DQB1, HLA-DRB6) were among the most significantly associated with chronological GA. Our multi-CpG site model attained higher predictive accuracy (R2 = 0.88) comparable to other published methods. Using genes implicated in region-based analyses (n = 395 regions), the pathways most significantly enriched with chronological GA-associated CpGs included T helper 1(Th1) and 2(Th2) activation, B-cell development, and IL-10 signaling, which were also enriched in at least one of the other published epigenetic GA clocks. In multi-exposure models, infant’s first-born status and maternal parity were associated with EGAA. Our findings highlight enrichment for T cell modulated pathways and antigen presentation as biological processes associated with chronological GA, as well as prenatal/perinatal factors that may affect EGAA.

ABSTRACT DNA methylation (DNAm) signatures are highly cell type-specific, yet most epigenome-wide association studies (EWAS) are performed on bulk tissue, potentially obscuring critical cell type-specific patterns. Existing computational tools for detecting cell type-specific DNAm changes are often limited by the accuracy of cell type deconvolution algorithms. Here, we introduce CEAM (Cell-type Enrichment Analysis for Methylation), a robust and interpretable framework for cell type enrichment analysis in DNA methylation data. CEAM applies over-representation analysis with cell type-specific CpG panels from Illumina EPIC arrays derived from nuclei-sorted cortical post-mortem brains from neurologically healthy aged individuals. The constructed CpG panels were systematically evaluated using both simulated datasets and published EWAS results from Alzheimer’s disease, Lewy body disease, and multiple sclerosis. CEAM demonstrated resilience to shifts in cell type composition, a common confounder in EWAS, and remained robust across a wide range of differentially methylated positions, when upstream modeling of cell type composition was modeled with sufficient accuracy. Application to existing EWAS findings generated in neurodegenerative diseases revealed enrichment patterns concordant with established disease biology, confirming CEAM’s biological relevance. The workflow is publicly available as an interactive Shiny app (https://um-dementia-systems-biology.shinyapps.io/CEAM/) enabling rapid, interpretable analysis of cell type-specific DNAm changes from bulk EWAS.

ABSTRACT Paternal influence on the offspring epigenome is difficult to interpret in observational human studies due to heterogeneous designs, causing varying susceptibility to bias and non-causal explanations. We conducted a systematic review (CRD42022302695) of paternal exposures before or during pregnancy in relation to the offspring epigenome, focusing on characteristics affecting causal interpretation and reproducibility. We searched three electronic databases for human studies published between 2003 and 2023. Eligible studies assessed paternal factors before or during pregnancy as exposures, and epigenetic mechanisms as outcomes. Risk of bias (RoB) was evaluated using ROBINS-E. The most frequently studied paternal factors were BMI/obesity (7), age (7), smoking (5), and socioeconomic status (SES) (4). All 28 studies assessed DNA methylation; two additionally explored miRNA expression. Most studies were rated ‘high’ or ‘very high’ RoB, primarily due to unclear exposure measurement and confounding. Findings showed limited overlap in CpG sites and genomic regions across studies. However, exposures that were stable (e.g. SES) or had clearly defined timing produced more consistent results. Notably, studies with clearly defined timing of paternal smoking suggested preconception exposure may influence offspring epigenetic pathways related to innate immunity but not pregnancy exposure. In contrast, paternal factors with poorly defined experimental analogues, such as BMI, provided inconsistent results. Aligning study design more closely with clinical trials or animal models, by clearly defining populations and exposures, may result in more reliable and replicable findings. Frameworks like ‘target trial emulation,’ offer a promising approach to improve reproducibility and interpretability of future research on paternal effects on offspring epigenome.

ABSTRACT Investigating the role of DNA methylation in the development of pancreatic cancer (PC) may facilitate identification of potential targets for both diagnosis and treatment. We carried out a comprehensive epigenome-wide Mendelian randomization (EWMR) analysis to investigate the correlation of genetically predicted blood CpG sites with PC. Following this, we conducted various sensitivity analyses and repeated analyses using different selection criteria for instrumental variables and conditional Bayesian colocalization to guarantee the reliability of the results. External validation and a meta-analysis were then performed to further validate these results. Next, we conducted CpG site enrichment analysis, overlap with phenome-wide association studies (PheWAS) catalog analysis, overlap with epigenome-wide association studies (EWAS) Toolkit analysis, and drug target analysis to explore the enrichment, biological functions, and potential therapeutic targets associated with these sites. Finally, we used the SMR-IVW software to perform mediation analysis, aiming to uncover potential tumorigenesis pathways of PC at the transcriptional level from three distinct perspectives. Results showed 253 CpG sites passing sensitivity analysis were significantly associated with PC and 159 CpG sites were validated in at least one replication. After meta-analysis, 38 CpG sites were retained, and all 253 CpG sites were classified into three tiers. Among these, cg26373071 (CLPTM1L), cg14271713, cg11652496 (PSTPIP1), and cg20575191 (PSTPIP1) were placed in tier 1 with strong support. Finally, this study identified genetic susceptibility linked to 253 PC-related CpG sites. This study provides insights into the disease’s origins and underscores potential targets for future research.

ABSTRACT DNA methylation is among the most promising biomarkers for age prediction, enabling the development of epigenetic clocks that correlate methylation profiles with chronological age. In this study, we investigated the relationship between ageing and disease susceptibility, focusing on both nuclear and mitochondrial DNA methylation in dairy cows. Genome-wide DNA methylation profiling was performed using enzymatic methyl-seq, covering 53 million CpG sites. The dataset included 96 cows with different phenotypes, sampled cross-sectionally and ranging from 2 to 9 years of age. We applied elastic net regression to identify the most predictive CpG sites for age estimation, achieving a mean absolute error of 111 days with a strong correlation to chronological age r = 0.97. Beyond chronological age prediction, we assessed the impact of disease status on epigenetic ageing. Our results revealed accelerated epigenetic ageing in cows susceptible to diseases, suggesting a link between health-related stress and disrupted DNA methylation dynamics. We further identified age-associated promoter methylation changes, particularly in MAB21L1, which may play a role in molecular ageing mechanisms. Additionally, we observed a decline in mitochondrial DNA methylation with age, notably in genes encoding Cytochrome c oxidase (COX), indicating a possible connection between mitochondrial dysfunction and epigenetic regulation. An inverse correlation between D-loop methylation and mtDNA copy number was also observed. This study demonstrates the potential of epigenetic models for biological age prediction in livestock, while recognizing that their accuracy may vary among species with different lifespans.

ABSTRACT This review explores how anesthetic agents influence epigenetic mechanisms such as DNA methylation, histone modifications, and non-coding RNA expression, and their lasting clinical effects. Common anesthetics, including propofol, isoflurane, sevoflurane, and local or regional agents, trigger epigenetic alterations. Preclinical research, especially in developing and aging brains, ties these changes to neurodevelopmental delays, cognitive decline, and shifts in immune and metabolic processes. While clinical studies are ongoing, accumulating evidence reveals that anesthesia triggers both transient and persistent epigenetic modifications, with potential links to postoperative cognitive dysfunction, prolonged inflammation, and altered developmental trajectories. Pediatric and elderly patients show heightened susceptibility due to brain plasticity or diminished resilience. Leveraging epigenetic knowledge could pave the way for tailored anesthesia approaches, reducing long-term risks. Moreover, emerging evidence suggests intergenerational transmission of these epigenetic changes via germline reprogramming, potentially affecting neurodevelopment and disease susceptibility in offspring. Future studies should prioritize large-scale human trials, detailed mechanistic insights, and identification of epigenetic biomarkers to guide safer anesthetic development. This review highlights anesthesia’s broader systemic consequences, extending beyond immediate cognitive impacts, and underscores its relevance to personalized medicine.