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At least 217 records · Page 12Linked to original sources
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

Discovery of a DNA methylation episignature as a molecular biomarker for fetal alcohol syndrome.

PURPOSE: Fetal alcohol spectrum disorder (FASD) encompasses a range of clinical features and neurodevelopmental disorders in children exposed to alcohol in utero. Despite its global public health significance, FASD diagnosis remains challenging because of nonspecific clinical findings and the lack of an accurate molecular diagnostic biomarker. This study aimed to evaluate peripheral blood DNA methylation (DNAm) profiles as a potential diagnostic biomarker for fetal alcohol syndrome. METHODS: Genomic DNAm profiles from 93 individuals with suspected or confirmed FAS, including a clinically diagnosed FAS subgroup, were analyzed and compared with a large database of control and patient cohorts with previously reported DNAm episignatures. Functional analysis of these DNAm profiles was performed to identify episignatures and assess their potential diagnostic utility. RESULTS: A relatively sensitive and specific DNAm episignature for FAS was identified. Comparative epigenomic analysis revealed functional correlations between FAS and other rare genetic disorders, supporting the robustness of the identified DNAm profiles as a diagnostic tool. CONCLUSION: This study demonstrates that unique DNAm profiles provide a robust episignature biomarker for FAS. These findings contribute to the molecular understanding of FAS and hold promise for improving diagnostic accuracy for this complex disorder.

Humans↗
PubMed2026

Light-activated CRISPR/dCas9 nanomedicine for programmable control of renal fibrosis.

Renal fibrosis is the final common pathway of progressive chronic kidney disease and is maintained by spatially heterogeneous interactions among injured epithelial cells, activated fibroblasts, immune cells, extracellular matrix remodeling, metabolic stress, and persistent profibrotic transcriptional programs. Current therapies slow renal functional decline but do not directly control the regulatory circuits that stabilize maladaptive repair. Photoresponsive renal nanomedicine offers a potential strategy to add external control to anti-fibrotic intervention by combining kidney-directed delivery with light-gated release or activation of molecular payloads. This review examines the emerging interface between photoresponsive nanomaterials and CRISPR/dCas9-based gene regulation for renal fibrosis, with emphasis on upconversion nanoparticles, photoresponsive polymers, ROS- and pH-responsive matrices, optogenetic switches, and renal-compartment-directed carrier design. We argue that the most defensible therapeutic objective is not permanent genome editing or autonomous organ regeneration, but spatially confined, temporally limited, and reversible regulation of validated fibrotic or protective gene programs using CRISPRa, CRISPRi, or dCas9-based epigenome editors. The review therefore evaluates material requirements, optical-dosimetry constraints, payload architecture, renal biodistribution, target-selection logic, safety risks, and preclinical validation criteria. By defining the engineering and biological conditions required for controlled anti-fibrotic regulation, this framework positions photoresponsive renal nanomedicine as a translationally testable route toward localized modulation of fibrotic cell states rather than an overextended claim of kidney regeneration.

Anti-fibrotic gene regulation↗
PubMed2025

Ectopic expression of DNMT3L in human trophoblast stem cells restores features of the placental methylome.

The placental DNA methylation landscape is unique, with widespread partially methylated domains (PMDs). The placental "methylome" is conserved across mammals, a shared feature of many cancers, and extensively studied for links with pregnancy complications. Human trophoblast stem cells (hTSCs) offer exciting potential for functional studies to better understand this epigenetic feature; however, whether the hTSC epigenome recapitulates primary trophoblast remains unclear. We find that hTSCs exhibit an atypical methylome compared with trophectoderm and 1st trimester cytotrophoblast. Regardless of cell origin, oxygen levels, or culture conditions, hTSCs show localized DNA methylation within transcribed gene bodies and a complete loss of PMDs. Unlike early human trophoblasts, hTSCs display a notable absence of DNMT3L expression, which is necessary for PMD establishment in mouse trophoblasts. Remarkably, we demonstrate that ectopic expression of DNMT3L in hTSCs restores placental PMDs, supporting a conserved role for DNMT3L in de novo methylation in trophoblast development in human embryogenesis.

Humans↗
PubMed2025

Self-organization of mouse embryonic stem cells into reproducible pre-gastrulation embryo models via CRISPRa programming.

Embryonic stem cells (ESCs) can self-organize into structures with spatial and molecular similarities to natural embryos. During development, embryonic and extraembryonic cells differentiate through activation of endogenous regulatory elements while co-developing via cell-cell interactions. However, engineering regulatory elements to self-organize ESCs into embryo models remains underexplored. Here, we demonstrate that CRISPR activation (CRISPRa) of two regulatory elements near Gata6 and Cdx2 generates embryonic patterns resembling pre-gastrulation mouse embryos. Live single-cell imaging revealed that self-patterning occurs through orchestrated collective movement driven by cell-intrinsic fate induction. In 3D, CRISPRa-programmed embryo models (CPEMs) exhibit morphological and transcriptomic similarity to pre-gastrulation mouse embryos. CPEMs allow versatile perturbations, including dual Cdx2-Elf5 activation to enhance trophoblast differentiation and lineage-specific activation of laminin and matrix metalloproteinases, uncovering their roles in basement membrane remodeling and embryo model morphology. Our findings demonstrate that minimal intrinsic epigenome editing can self-organize ESCs into programmable pre-gastrulation embryo models with robust lineage-specific perturbation capabilities.

Animals↗
PubMed2026

Omics in hereditary optic neuropathies: A systematic review of clinical studies with an integrated point of view.

Hereditary optic neuropathies are characterized by bilateral visual loss due to the degeneration of retinal ganglion cells, resulting in optic nerve degeneration and atrophy. Although the genetic origin of the main isolated and syndromic hereditary optic neuropathies has been characterized, the clinical phenotypes exhibit significant and poorly understood variability in both penetrance and expressivity. Additionally, the genetic and environmental factors that influence the onset of these optic neuropathies remain poorly understood, with limited biomarkers to predict disease progression or as readouts for therapeutic trials. Data-driven omics strategies allow deep phenotyping to improve our understanding of pathophysiological mechanisms and to search for new biomarkers and therapeutic targets. We explore whether the omics strategies applied to patients with hereditary optic neuropathies have provided such new insights. MEDLINE, Web of Science and EMBASE databases were screened for studies with terms relating to hereditary optic neuropathies, transcriptomics, epigenomics, proteomics, metabolomics and lipidomics in clinical studies exploring patients' samples. Out of 1244 references identified, 22 articles were included after double-masked data curation. These articles focused only on the 3 main forms of hereditary optic neuropathies, namely, OPA1-related dominant optic atrophy (n = 4), Leber hereditary optic neuropathy (n = 13), and Wolfram syndrome (n = 5). While the methodological designs and results of these studies were highly heterogeneous, they revealed molecular alterations that we have attempted to discuss at the integrated multi-omics level. This data integration highlighted several common pathophysiological mechanisms such as energetic impairment, endoplasmic reticulum stress, proteotoxic and oxidative stresses, lipid remodeling and altered amino acid and purine metabolisms, while suggesting potential new biomarkers and therapeutic targets. These findings underscore the potential of integrated multi-omics approaches to deepen our understanding of the phenotypic complexity of hereditary optic neuropathies and to support the development of innovative diagnostic and therapeutic strategies.

Humans↗
PubMed2025

Ternary-code DNA methylation dynamics: A new era for scalable mapping.

The preview discusses the scalable platform for methylation-based trait mapping published in Cell Genomics by Goldberg et al.1 This work represents not only a methodological advance but also marks a conceptual shift toward scalable and high-throughput functional, targeted, and context-sensitive epigenomic screening.

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

Seeing and Feeling DNA Methylation: Single-Molecule Biophysics Meets Machine Learning.

DNA methylation at 5-methylcytosine (5mC) is crucial for embryonic development and cellular function, while aberrant patterns strongly drive disease onset and progression. Its reversible nature offers substantial therapeutic potential, emphasizing the need for precise, context-specific genome wide 5mC mapping. Conventional techniques such as bisulfite sequencing and ensemble biosensor assays are hindered by DNA degradation, amplification bias, high cost, and inability to resolve single-molecule structural and mechanical effects of methylation. This review examines advances in single-molecule biophysical methods (nanopore sensing, smFRET, optical/magnetic tweezers, and AFM) that provide direct, label-free/minimally invasive 5mC detection, along with quantitative insights into DNA conformation, mechanics, and protein-DNA interactions. These techniques complement traditional methylome mapping by linking genomic localization to molecular mechanisms. Emerging machine-learning approaches are revolutionizing analysis, particularly in nanopore sensing, while promising applications in smFRET, tweezers, and AFM address throughput and reproducibility challenges. Their convergence promises scalable, high-resolution epigenetic profiling, advancing precision epigenomics toward clinical application.

DNA Methylation↗
PubMed2021

Epigenetic mechanisms in breast cancer therapy and resistance.

The majority of breast cancers express the estrogen receptor (ERα) and agents targeting this pathway represent the main treatment modality. Endocrine therapy has proven successful in the treatment of hormone-responsive breast cancer since its early adoption in the 1940s as an ablative therapy. Unfortunately, therapeutic resistance arises, leading to disease recurrence and relapse. Recent studies increased our understanding in how changes to the chromatin landscape and deregulation of epigenetic factors orchestrate the resistant phenotype. Here, we will discuss how the epigenome is an integral determinant in hormone therapy response and why epigenetic factors are promising targets for overcoming clinical resistance.

Antineoplastic Agents, Hormonal↗
PubMed2026

Scalable, generalizable and uncertainty-aware integration of spatial multiomics across diverse modalities and platforms with SCIGMA.

Recent advances in spatial omics technologies have enabled simultaneous profiling of transcriptomic, proteomic, epigenomic, metabolomic and imaging data at high spatial resolution, offering unprecedented opportunities to dissect tissue complexity. However, integrating these diverse and large-scale spatial multimodal datasets remains a major computational challenge. We present SCIGMA, a scalable and generalizable deep learning framework for spatial multiomics integration. SCIGMA introduces an uncertainty-aware contrastive learning objective and multiview graph neural networks to preserve modality-specific signals while learning biologically meaningful joint representations. Unlike previous methods, SCIGMA provides spatially resolved uncertainty estimates, interpretably identifying regions of biological or technical heterogeneity. SCIGMA supports integration of up to five modalities, and its modular framework is extensible to future technologies with even more modalities. It also scales to more than 1 million spatial locations, enabling analysis of high-resolution datasets such as Visium HD and Xenium Prime. We evaluated SCIGMA across 19 datasets spanning 8 modalities, 10 tissues and 9 platforms. On benchmarkable datasets, SCIGMA outperformed other methods in spatial domain detection, modality preservation, feature reconstruction and reproducibility. SCIGMA identifies biologically meaningful structures, refined spatial domains and modality-specific regulatory programs, providing a robust, flexible and future-ready solution for scalable spatial multimodal integration.

Multiomics↗
PubMed2026

Regulation of immune signal integration and memory by inflammation-induced chromosome conformation.

Three-dimensional (3D) genome conformation is central to gene expression regulation, yet our understanding of its contribution to rapid transcriptional responses, signal integration, and memory in immune cells is limited. Here, we study the molecular regulation of the inflammatory response in primary macrophages using integrated transcriptomic, epigenomic, and chromosome conformation data, including base pair-resolution Micro Capture-C. We demonstrate that interleukin-4 (IL-4) primes the inflammatory response in macrophages by stably rewiring 3D genome conformation, juxtaposing endotoxin-, interferon-gamma-, and dexamethasone-responsive enhancers to their cognate gene promoters. CRISPR-based perturbations of enhancer-promoter contacts or CCCTC-binding factor (CTCF) boundary elements show that IL-4-driven conformation changes are required for enhanced and synergistic endotoxin-induced transcriptional responses, as well as transcriptional memory following stimulus removal. Moreover, transcriptional memory mediated by changes in chromosome conformation can occur in the absence of changes in chromatin accessibility or histone modifications. Collectively, these findings demonstrate that rapid and memory transcriptional responses to immunological stimuli are encoded in the 3D genome.

Animals↗
PubMed2025

Novel approaches and applications in identifying DNA methylation markers of cardio-kidney-metabolic disease.

Cardio-kidney-metabolic (CKM) diseases represent a major public health challenge, accounting for a large proportion of global burden of morbidity and mortality. These conditions share risk factors, including genetic predisposition, environmental exposures, and lifestyle influences, which collectively drive disease development and progression. Epigenetic modifications, particularly DNA methylation (DNAm), serve as key mediators and biomarkers between these risk factors and disease phenotypes by regulating gene expression without altering the DNA sequence. Epigenome-wide association studies have identified DNAm markers associated with CKM diseases and related phenotypes, highlighting both shared pathways and disease-specific epigenetic signatures in inflammation, metabolic dysfunction, and aging-related processes. Longitudinal studies further demonstrate the dynamic nature of DNAm changes over time, offering insights into disease trajectories. Additionally, methylation risk scores integrating multiple epigenetic markers show promise in improving disease prediction and risk stratification beyond traditional clinical factors. To synthesize the current evidence, we conducted a targeted literature search in PubMed for English-language, peer-reviewed articles published between 2014 and the present. Future research leveraging large, well-phenotyped cohorts, advanced statistical methods, and innovative study designs will be critical for uncovering novel biomarkers, refining risk prediction models, and developing targeted epigenetic therapies to mitigate the global burden.

Humans↗
PubMed2025

Tracing regulatory element networks using epigenetic traits to identify key transcription factors: TENET R/Bioconductor package.

SUMMARY: There is a lack of publicly available bioinformatic tools that can be widely used by researchers to identify transcription factors (TFs) that regulate cell type-specific regulatory elements (REs). To address this, we developed the Tracing regulatory Element Networks using Epigenetic Traits (TENET) R/Bioconductor package. By collecting hundreds of histone mark and open chromatin datasets from a variety of cell lines, primary cells, and tissues, and comparing these features along with matched DNA methylation and gene expression data, TENET identifies TFs and REs linked to a specific cell type. Moreover, we developed methods to interrogate findings using motifs, clinical information, and other genomic and chromatin conformation capture datasets, and applied them to pan-cancer data, highlighting TFs and REs associated with ten different cancer types. TENET enables researchers to better characterize the 3D epigenomes of cell types of interest for future clinical applications. AVAILABILITY AND IMPLEMENTATION: TENET is available at http://bioconductor.org/packages/TENET. Curated functional genomic datasets utilized by TENET are available at http://bioconductor.org/packages/TENET.AnnotationHub. Example datasets are available at http://bioconductor.org/packages/TENET.ExperimentHub.

Transcription Factors↗
PubMed2025

Immediate and durable effects of maternal tobacco consumption on placental DNA methylation: a replication and discovery study.

An increasing number of epigenome-wide association studies report tobacco smoking-associated DNA methylation levels. However, comprehensive replication studies remain scarce, particularly in placenta, despite their crucial interest in such a large-scale context. Using DNA methylation data from the EPIC array of 341 new placentas (85 smokers, 219 non-smokers, and 37 former smokers) from the EDEN cohort, we used a candidate approach to replicate maternal smoking-associated CpGs and regions previously identified using the 450K array, and an exploratory approach to discover new associations within EPIC-specific CpGs. Smoking-associated changes in DNA methylation in CpGs and regions were classified as either transient or persistent (indicating epigenetic memory), depending on the stability of their association with smoking status. Among candidate loci, 38% of probes and 9% of regions were replicated, providing robust evidence of effects of prenatal smoke exposure on methylation patterns of these loci. LEKR1 was the top hit in both the initial and replication studies. Most of the replicated loci were transient CpGs (i.e. current smokers), while persistent CpGs (i.e. former smokers) remained scarce and somewhat inconsistent with previous findings. The additional exploratory analysis identified 733 novel probes and 75 novel regions, including 18% and 30% of transient loci, respectively. Results suggested that most of the effects were related to in utero exposure only, supporting pregnant women's efforts to quit smoking. This replication study also evidences the importance of reproducible work in omic investigations to provide a more in-depth and robust understanding of the effects of environmental exposures on health biomarkers..

DNA methylation↗
PubMed2025

RESTRICT-seq enables time-gated CRISPR screens and uncovers novel epigenetic dependencies of SCC resistance.

Cancer cell evasion of therapy is a highly adaptive process that undermines the efficacy of many treatment strategies. A significant milestone in the study of these mechanisms has been the advent of pooled CRISPR knockout screens, which enable high-throughput, genome-wide interrogations of tumor dependencies and synthetic lethal interactions, advancing our understanding of how cancer cells adapt to and evade therapies. However, the utility of this approach diminishes when applied to dynamic biological contexts, where processes are transient and sensitivity to routine cell culture manipulations that introduce noise and limit meaningful discoveries. To overcome these limitations, we present RESTRICT-seq, a next-generation pooled screening methodology that restricts Cas9 nuclear activation in controlled, repeated cycles. By confining Cas9 catalytic activity to strict temporal windows, RESTRICT-seq mitigates undesired fitness penalties that routinely accumulate throughout pooled screens. When benchmarked against conventional pooled screens and standard inducible protocols, RESTRICT-seq revealed significantly fewer divergent cell clones and increased signal-to-noise ratio, overcoming a key limitation of traditional methods. Leveraging RESTRICT-seq, we conducted a comprehensive functional survey of the druggable mammalian epigenome, uncovering several elusive epigenetic drivers of treatment resistance in cutaneous squamous cell carcinoma (cSCC). This revealed PAK1 as a previously unrecognized mediator of cSCC resistance in human and mouse SCC, offering new insights into a prognostic marker and therapeutic target of high clinical significance. Our findings establish RESTRICT-seq as a powerful tool for extending the applicability of pooled CRISPR screens to dynamic and previously intractable biological contexts.

Allosterically-regulated Cas9 (arCas9)↗
PubMed2025

Omics in Nonsteroidal Anti-Inflammatory Drugs-Exacerbated Respiratory Disease: Current Evidence From the Upper and Lower Airways.

Nonsteroidal anti-inflammatory drugs (NSAID)-exacerbated respiratory disease (N-ERD) is a mainly type 2 inflammatory condition that combines asthma, nasal polyps, and hypersensitivity to NSAIDs. Its pathogenesis involves both upper and lower airways, yet most studies to date have examined these compartments separately. It remains unclear whether the molecular mechanisms in the nose, sinuses, and lungs are distinct or overlapping-an important gap, given that clinical manifestations of N-ERD involve both sites. In this review, we summarize available omics studies-transcriptomics, proteomics, metabolomics, and epigenomics-performed on upper and lower airways in patients with N-ERD. While omics approaches have revealed new molecular insights, comparisons across studies are limited by heterogeneity in design, controls, and methodology. We emphasize the need for integrated multi-omics analyses and standardized frameworks to better characterize the disease across airways. Such efforts are essential for identifying robust biomarkers and therapeutic targets and for moving toward a systems-level understanding of N-ERD.

Humans↗
PubMed2026

Spatial multiomics in biomedical research: advances beyond transcriptomics.

Coordinated changes in gene expression, epigenetic regulation, protein and metabolic activities together drive disease progression and determine clinical outcomes. While spatially resolved transcriptomics has been widely adopted across biomedical fields, it offers an incomplete picture limited to transcriptomic levels. Here, we survey the latest developments in spatial multiomics technologies, with particular emphasis on platforms that extend beyond conventional transcriptomics and profile genomics, epigenomics, proteomics, or metabolomics within intact tissues. These approaches are rapidly becoming commercialized, and here we highlight major technical breakthroughs, enhanced sample compatibility, emerging applications, and computational tools for data analysis. This Review aims to equip researchers with a clear understanding of the current technological landscape and to accelerate the adoption of spatial multiomics methods in biomedical research.

Humans↗