'; ?> geneimprint : Hot off the Press http://www.geneimprint.com/site/hot-off-the-press Daily listing of the most recent articles in epigenetics and imprinting, collected from the PubMed database. en-us Sat, 28 Mar 2026 08:23:26 EDT Sat, 28 Mar 2026 08:23:26 EDT jirtle@radonc.duke.edu james001@jirtle.com DNA methylation-mediated alterations in Copper(I/II) redox equilibrium underlie lead-induced neurotoxicity. Hu J, Wang WX
Environ Pollut (Apr 2026)

Lead (Pb), a ubiquitous environmental toxin, poses significant risks to central nervous system health, primarily by disrupting essential metal homeostasis in the brain. While epigenetic regulation and proteomic expression are significantly affected by Pb, its specific molecular impact on copper (Cu) redox states remains poorly understood. This study systematically investigated the molecular mechanisms underlying Pb-induced neurotoxicity in SH-SY5Y cells through integrated epigenomics and proteomics analysis. DNA methylation analysis revealed 141,357 differentially methylated regions (DMRs), primarily in CpG sites, with 62.6 % hypermethylated and 37.4 % hypomethylated. These DMRs were enriched in genes associated with critical processes such as metal ion binding, cell cycle regulation, and nervous system development. Promoter-specific methylation changes were notably pronounced, impacting pathways linked to neurodegenerative diseases, including Alzheimer's disease. Proteomic analysis identified 740 differentially expressed proteins (DEPs), with 366 upregulated and 374 downregulated in Pb-treated cells. Functional annotation revealed significant enrichment of DEPs in mitochondria, where Pb exposure disrupted processes related to oxidative phosphorylation, ion transport, and transmembrane processes. These proteomic changes aligned with the observed epigenetic modifications, reinforcing the role of Pb in impairing neuronal function via its effects on cellular energy metabolism and metal ion dynamics. Notably, Pb exposure disrupted Cu redox transitions between Cu(I) and Cu(II) as well as glutathione (GSH) activity, underscoring its impact on cellular metal homeostasis regulation and oxidative imbalance. In summary, this study provides a comprehensive view of how Pb exposure alters epigenetic and proteomic landscapes, disrupting key biological processes and pathways essential for neuronal health.]]> Wed, 31 Dec 1969 19:00:00 EST Introduction to the special issue on epigenetic regulation of chronic pain. Nackley AG
Pain Rep (Apr 2026)

This Special Issue features 6 articles from leaders in the field that elucidate novel epigenetic mechanisms regulating nociception, inflammation, responses to pharmacologic and integrative therapies, and pain disparities among racial/ethnic groups. Together, they highlight the expanding potential of epigenomics to inform mechanistic discovery, guide personalized pain therapeutics, and advance pain equity.]]> Wed, 31 Dec 1969 19:00:00 EST Interactions between nutrition and the epigenome: how can it be harnessed for public health? Anastasopoulou M, Dereki I, Sgourou A, Lagoumintzis G
Future Sci OA (Dec 2026)

A substantial body of evidence shows that dietary habits influence gene expression and epigenetic processes, holding significant implications for public health policies. Epigenetic modifications are increasingly associated with metabolic state, disease risk, and biological aging. Translating mechanistic results into scalable, efficient nutritional epigenetics treatments is difficult.]]> Wed, 31 Dec 1969 19:00:00 EST Synergistic integration of clinical and multi-omics data for early MCI diagnosis using an attention-based graph fusion network. Yu S, Zhao J, Ouyang J, Wang X, Kou P, Zhu K, Liu P
J Neurosci Methods (Apr 2026)

Mild cognitive impairment (MCI), a precursor to Alzheimer's disease (AD), requires precise early diagnosis. Single-omics approaches often miss disease complexity, motivating integrative and interpretable solutions.]]> Wed, 31 Dec 1969 19:00:00 EST Melatonin-enabled omics: understanding plant responses to single and combined abiotic stresses for climate-smart agriculture. Raza A, Li Y, Charagh S, Guo C, Zhao M, Hu Z
GM Crops Food (Dec 2026)

Climate change-driven single and combined abiotic stresses pose escalating threats to sustainable, climate-smart agriculture and global food security. Melatonin (MLT, a powerful plant biostimulant) has established noteworthy potential in improving stress tolerance by regulating diverse physiological, biochemical, and molecular responses. Therefore, this review delivers a comprehensive synopsis of MLT-enabled omics responses across genomics, transcriptomics, proteomics, metabolomics, miRNAomics, epigenomics, phenomics, ionomics, and microbiomics levels that collectively regulate plant adaptation to multiple abiotic stresses. We also highlight the crosstalk between these omics layers and the power of integrated multi-omics (panomics) approaches to harness the complex regulatory networks underlying MLT-enabled stress tolerance. Lastly, we argue for translating these omics insights into actionable strategies through advanced genetic engineering and synthetic biology platforms to develop MLT-enabled, stress-smart crop plants.]]> Wed, 31 Dec 1969 19:00:00 EST Multi-omics biomarkers in psychiatric disorders diagnosis and stratification. Khatami SH, Anoosheh S, Khodaparast M, Maghsoudloonejad A, Dadgostar E, Asadi A, Kaveh M, Haghighi MM
Clin Chim Acta (Apr 2026)

The precise diagnosis and stratification of psychiatric disorders remain formidable challenges in modern medicine, hindered by the absence of objective biomarkers and reliance on subjective clinical criteria. Recent advances in multi-omics technologies, including genomics, transcriptomics, proteomics, metabolomics, and epigenomics, have revolutionized our understanding of complex neuropsychiatric conditions such as schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder. This review critically evaluates the current landscape of multi-omics research in psychiatry, highlighting methodological innovations, integrative strategies, and translational potential for biomarker discovery and clinical implementation. By synthesizing data across diverse molecular layers, multi-omics approaches enable a systems-level view of psychiatric disorders as multifactorial entities shaped by molecular, cellular, environmental, and neurocircuitry interactions. Despite promising advances in diagnostic accuracy and personalized treatment, significant barriers persist, including data heterogeneity, analytical complexity, and the translational gap between molecular signatures and clinical phenotypes. This review systematically explores the contributions of individual omics domains, emerging frameworks for multimodal data integration, the role of systems biology and network-based models, and the impact of large-scale consortia in driving clinical translation.]]> Wed, 31 Dec 1969 19:00:00 EST A cell type enrichment analysis tool for brain DNA methylation data (CEAM). Müller J, Laroche VT, Imm J, Weymouth L, Harvey J, Reijnders RA, Smith AR, van den Hove D, Lunnon K, Cavill R, Pishva E
Epigenetics (Dec 2026)

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.]]> Wed, 31 Dec 1969 19:00:00 EST : a computational suite for DNA methylation sequencing data analysis. Loyfer N, Rosenski J, Kaplan T
Life Sci Alliance (Apr 2026)

Next-generation methylation-aware sequencing of DNA sheds light on the fundamental role of methylation in cellular function in health and disease, increasing the number of covered CpG sites from hundreds of thousands in previous array-based approaches to tens of millions across the whole genome. While array-based approaches are limited to single-CpG resolution, next-generation sequencing allows for a more detailed, single-molecule fragment-level analysis; however, existing tools to fully use this capability are not yet well developed. Here, we present , an extensive computational suite tailored for methylation sequencing data. allows fast access and ultracompact anonymized representation of high-throughput methylome data, obtained through various library preparation and sequencing methods, with a custom epiread file format achieving a compression factor of over 100x from the input BAM file. In addition, contains state-of-the-art algorithms for genomic segmentation, biomarker identification, genetic and epigenetic data integration, and more. offers fragment-level analysis and informative visualizations, across multiple genomic regions and samples.]]> Wed, 31 Dec 1969 19:00:00 EST TiSMeD: A tissue-specific methylation and expression database for biomarker and translational applications. Cheng J, Lin Z, Wu L, Li Q, Yin H, Wang H, Chen H, Chen X, Ji ZL
Mol Ther Nucleic Acids (Jun 2026)

Tissue-specific methylation sites (TSMs) are important epigenetic features associated with gene regulation, tissue development, and disease pathogenesis. However, the lack of comprehensive and reliable resources for TSMs restricts advancements in epigenetic and translational research. We present TiSMeD (http://www.bio-add.org/TiSMeD/), a multi-omics database integrating 6,782 DNA methylation, 16,894 transcriptome, and 241 proteome profiles across 48 normal human tissues. Using a scoring framework based on SPM and Tscore, we identified 67,427 high-confidence TSMs, 4,607 tissue-specific genes, and 2,833 tissue-specific proteins, along with over 11 million housekeeping methylation sites. TiSMeD enables interactive exploration and data retrieval, supporting biomarker discovery and disease research. We demonstrate its utility in tracing the tissue-of-origin of cell-free DNA (cfDNA), prioritizing 1,849 cancer biomarkers from The Cancer Genome Atlas (TCGA), and constructing a multi-cancer tracing and diagnostic model achieving 95.7% accuracy. TiSMeD serves as a robust, user-friendly platform integrating multi-omics data to advance epigenetic research and biomarker translation.]]> Wed, 31 Dec 1969 19:00:00 EST Global analyses of genomic and epigenomic influences on gene expression reveal as a major regulator of cardiac gene expression in response to catecholamine challenge during heart failure. Lahue C, Ravindran S, Dalal A, Avetisyan R, Rau CD
Epigenetics (Dec 2026)

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 , as the most likely driver gene in this hotspot. Experimental knockdown of in neonatal rat ventricular cardiomyocytes blunted hypertrophy induced by a variety of hypertrophic signals, while altering predicted target expression and modulating the activity of and . Together, these findings position 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.]]> Wed, 31 Dec 1969 19:00:00 EST Long noncoding RNA H19 in liver development and disease. Montoya-Durango DE, Gobejishvili L
Cell Signal (Jun 2026)

Liver disease is a global health problem responsible for more than two million deaths annually. Metabolic dysfunction-associated steatotic liver disease (MASLD) and alcohol-associated liver disease (ALD) are major contributors to chronic liver disease-related morbidity and mortality. Factors like diet and alcohol consumption have become key drivers of liver pathologies including steatosis, fibrosis/cirrhosis, and hepatocellular carcinoma. To date very few treatments are available, hence there is a critical need for the development of novel therapies to slow down the development/progression of liver damage. The long non-coding RNA H19 gene, H19, is an imprinted gene normally expressed from the maternally inherited chromosome and epigenetically silenced in the paternal chromosome. At the embryo stage H19 controls genome-wide methylation, directs the methylation of the imprinted gene network, and regulates organ size. In the livers of neonates, H19 is important for organ maturation but remains silent in the mature organ. H19 re-expression in the adult liver drives de novo lipogenesis and fibrosis and maintains a proliferative state in tumor cells. The complexity of H19 functions in the liver is reflected in its interaction and regulation of a growing number of proteins, and coding and non-coding RNAs involved in metabolism, pro-fibrotic gene networks, cell cycle progression, and chromatin regulation. This review summarizes the findings related to the role of H19 in liver development and in diseases such as fatty liver, fibrosis, and hepatocellular carcinoma.]]> Wed, 31 Dec 1969 19:00:00 EST Hyperglycaemia-induced metabolic stress and epigenetic imprinting in the inflammatory pathogenesis of diabetic neuropathy. Razi FB, Ashraf H, Singhal S, Qamar Z, Moin S
Diabetes Res Clin Pract (Apr 2026)

Diabetic neuropathy (DN), a major microvascular complication of diabetes mellitus, results from a complex interplay among oxidative stress, inflammation, and persistent epigenetic modifications. Hyperglycemia-induced mitochondrial dysfunction increases reactive oxygen species (ROS), which activate redox-sensitive inflammatory cascades, including NF-κB, JAK/STAT, and the NLRP3 inflammasome. These pathways amplify cytokine release and neuronal sensitisation, while reciprocal feedback between ROS and inflammation mediated by Nrf2 suppression further perpetuates nerve damage. Damage-associated molecular patterns (DAMPs), including HMGB1, S100A8/A9, mitochondrial DNA, and extracellular ATP, act as key amplifiers of neuroinflammation. By engaging receptors such as RAGE, Toll-like receptors (TLRs), and NOD-like receptors (NLRs), particularly NLRP3, these DAMPs trigger glial activation and nociceptive signalling, contributing to axonal degeneration and pain hypersensitivity in DN. Epigenetic dysregulation, including DNA methylation drift, histone modification imbalance, and aberrant non-coding RNA expression, constitutes a critical mechanism underlying metabolic memory, wherein prior hyperglycemic exposure leaves lasting molecular imprints. Persistent histone acetylation (H3K9ac), altered methylation (H3K4me1/Set7, H3K9me3/SUV39H1), and stable 5-methylcytosine patterns sustain inflammatory and oxidative pathways, even after glucose normalisation. Therapeutically, DNMT and HDAC inhibitors, miRNA modulators, and agents targeting RAGE/TLR4/NLRP3 pathways show promise in reversing these molecular imprints. Antioxidants and anti-inflammatory compounds with epigenetic effects further represent potential disease-modifying strategies. Future research must focus on longitudinal human studies, nerve-specific epigenomics, and multi-omics integration to enable personalised, mechanism-based therapy for DN. Understanding the interdependence of ROS, DAMPs, and epigenetic memory is key to breaking the cycle of chronic neuroinflammation and neuronal injury.]]> Wed, 31 Dec 1969 19:00:00 EST Multi‑omics and their integration in psoriasis research (Review). Zhang H, Li D, Zhu L, Yan H, Yang L, Yang X, Zhou Y
Mol Med Rep (May 2026)

Psoriasis is a chronic, immune‑mediated skin disorder characterized by keratinocyte hyperproliferation, inflammatory infiltrates and systemic comorbidities. While genetic predisposition and immune dysregulation are established contributors, recent advancements in high‑throughput omics technologies have provided deeper insights into the molecular complexity of psoriasis. The present review synthesized findings from various omics layers, genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiomics, to elucidate their roles in psoriasis pathogenesis. Large‑scale genome‑wide association studies have identified both common and region‑specific susceptibility loci. Epigenetic factors and transcription factors regulate psoriasis‑related genes by modulating chromatin accessibility, DNA methylation, non‑coding RNAs and direct gene activation/inactivation, thereby reshaping the transcriptome. Genetic and epigenetic influences also drive significant alterations in the proteome and metabolome, both in the skin and plasma, shedding light on disease mechanisms and offering potential for biomarker discovery. While microbiome research in psoriasis remains in its early stages, shifts in skin and gut microbial communities have been observed, suggesting their involvement in disease pathogenesis. Together, the multi‑layered insights underscore the future potential of integrated systems approaches to unravel disease mechanisms and support the discovery of clinically actionable biomarkers and therapeutic targets, paving the way for more precise diagnosis and targeted therapeutic development in psoriasis.]]> Wed, 31 Dec 1969 19:00:00 EST Rising Star: Single Cell Omics Technologies: When Whole Omics Analysis Meets Single Cell Resolution. Tang F
J Mol Biol (Apr 2026)

I got my PhD degree under the supervision of Prof. Kegang Shang in 2003. And I did my postdoc research in Azim Surani's lab. Then I set up my own lab in Biomedical Pioneering Innovation Center at Peking University in 2010. My research has focused on developing single-cell omics sequencing technologies and employing these powerful tools to dissect the gene regulation networks in human germline cell development under both physiological and pathological conditions. My lab systematically developed a serial of single-cell omics sequencing technologies, including the first single-cell DNA methylome sequencing technology in 2013, which was considered to pioneer the single-cell epigenome field. In recent years, my lab has focused on developing single-cell omics long-read sequencing technologies based on single-molecule sequencing platforms, which can reveal critical features of the repetitive elements. The repetitive elements are considered as 'dark matter', which account for over half of our genome and play important roles for both normal development and numerous diseases. The research in my lab revealed critical features of the epigenetic reprogramming of human germline cells, deepening our understanding of these cells, which are fundamental to the transgenerational immortality of the human species.]]> Wed, 31 Dec 1969 19:00:00 EST Limitations and opportunities in multi-omics integration for neurodevelopmental, neurodegenerative and psychiatric disorders: A systematic review. Behrens LMP, Fernandes GDS, Gonçalves GF, Nunes FVM, Weimer RD, Moreira JCF, Dorn M
Neuroscience (Apr 2026)

Recent advances in high-throughput technologies have led to an increased generation of biological data across genomics, transcriptomics, proteomics, epigenomics, and metabolomics. However, a major challenge remains: effectively integrating these multi-omics datasets to allow a more holistic understanding of the complex, interconnected mechanisms underlying human diseases. Neurodevelopmental, neurodegenerative, and psychiatric disorders are particularly multifactorial and heterogeneous, making them candidates for multi-omics approaches. In this context, this systematic review assesses the current state of multi-omics integration in neurological research. Records retrieved from five major databases were processed, and 156 studies were included for further analysis. The most frequently studied conditions were Alzheimer's Disease, Depressive Disorder and Parkinson's Disease, with epigenomics-transcriptomics and metagenomics-metabolomics emerging as the most common omics pairings. The field remains dominated by studies integrating pairs of omics layers. Only a limited number of computational tools are currently being applied to the integration of more than two omics layers, highlighting a gap in comprehensive multi-omics modeling. Despite progress, key challenges persist, including data accessibility and the need for standardized frameworks to allow cross-study comparisons. Moreover, most computational findings lack experimental validation in wet-laboratory settings. Future research should address these challenges, develop scalable algorithms for integrating multi-omics data, and leverage large, open-access datasets. Integrating computational predictions with experimental validation could help researchers prioritize high-confidence biomarkers relevant to clinical applications. Collaborative efforts among bioinformaticians, clinicians, and experimentalists will be essential to translating these advances into clinically actionable solutions.]]> Wed, 31 Dec 1969 19:00:00 EST Artificial intelligence and multi-omics convergence in breast cancer: Revolutionizing diagnosis, prognostication, and precision oncology. Jiang B, Wu Y, Chen X, Jian C, Wang W
Crit Rev Oncol Hematol (Apr 2026)

Breast cancer (BC) is a highly heterogeneous malignancy and remains a major cause of cancer-related mortality among women worldwide. Advances in multi-omics profiling spanning genomics, transcriptomics, epigenomics, proteomics, and metabolomics have enabled finer subtype stratification and more comprehensive characterisation of tumour biology, thereby accelerating the discovery of diagnostic and prognostic biomarkers and actionable therapeutic targets. Nonetheless, translating multi-layer molecular signals into clinically robust decision support remains challenging because of the high dimensionality and heterogeneity of omics data, cross-cohort and cross-platform variability, and the fragmentation inherent to single-modality analyses. This review summarises how multi-omics studies have refined BC subtype definitions and advanced biomarker and target identification, and then synthesises recent progress in artificial intelligence, particularly deep learning, for integrating multi-omics with imaging, pathology, and clinical variables to improve diagnosis, risk stratification, prognosis prediction, and treatment response assessment. We critically examine representative multimodal integration frameworks and emerging deep learning architectures that learn both shared and modality-specific representations, which in many settings enable more accurate patient-level prediction than unimodal baselines. We further delineate key barriers to clinical translation, including cross-centre heterogeneity and inconsistent endpoint definitions, structural missingness of modalities in real-world workflows, inadequate cross-platform normalisation, limited interpretability and auditability, and a lack of prospective validation. Finally, we propose realistic next steps, including standardised and auditable preprocessing pipelines, missingness-aware fusion strategies, explainable and uncertainty-aware modelling, privacy-preserving multi-centre learning, and prospective, workflow-based evaluation. Collectively, these perspectives provide a roadmap for advancing multimodal AI-multi-omics integration toward reliable clinical deployment in BC management.]]> Wed, 31 Dec 1969 19:00:00 EST DNA methylation as a predictor of pituitary neuroendocrine tumour behaviour: A systematic review. van der Groef R, Mulugeta E, Neggers S, Refardt J
J Neuroendocrinol (Apr 2026)

Pituitary neuroendocrine tumours (PitNETs) range from slow-growing to highly aggressive tumours; however, traditional prognostic markers often fail to predict clinical outcomes reliably. DNA methylation has recently emerged as a promising biomarker for assessing tumour behaviour. This systematic review evaluates its predictive value in PitNETs. To systematically assess the clinical applicability of DNA methylation profiles in predicting behaviour of PitNETs. Systematic review. A comprehensive search was conducted in Medline, Embase, Web of Science, and Cochrane CENTRAL on December 13, 2024, with an update on October 17, 2025. The search included studies on adult PitNET patients, specifically examining tumour behaviour in relation to DNA methylation. Excluded were studies that focused on cell-free DNA, investigated a single gene with no established relevance to tumour behaviour, or assessed tumour size only. Data were extracted from 20 eligible studies by four independent reviewers. The risk of bias was assessed using the QUIPS tool. Due to methodological differences across studies, the findings were summarised narratively. Twelve studies investigated tumour invasiveness, two examined tumour aggressiveness and five examined PitNET regrowth, recurrence and re-intervention. The majority of studies concentrated on non-functioning PitNETs and used Illumina arrays or PCR-based methods. These analyses identified several differentially methylated genes linked to invasiveness (e.g., PHYHD1, WNT4, STAT6, CDH1, CDH13), aggressive behaviour (e.g., AIP, PDCD1, LINE-1), and tumour regrowth (e.g., TERT, FAM90A1, ING2). DNA methylation profiling shows potential for predicting PitNET behaviour, but methodological inconsistencies limit its clinical application. Standardized methods and prospective validation are needed for clinical integration.]]> Wed, 31 Dec 1969 19:00:00 EST Emerging multi-omics biomarkers in glioblastoma: Integrative insights from genomics to metabolomics. Kakde GS, Dakal TC, Maurya PK
Biochim Biophys Acta Rev Cancer (Apr 2026)

Glioblastoma (GBM) is the most malignant form of primary brain tumor in adults, described by profound molecular heterogeneity, rapid progression, and limited therapeutic response. Despite advances in chemotherapy (TMZ), radiotherapy, and surgery, patient outcomes remain poor, with a median survival of 12-15 months. Traditional single-omics studies have identified critical biomarkers such as IDH mutations, MGMT promoter methylation, and EGFR alterations; however, these provide only partial insight into the disease's complexity. Recent integrative multi-omics approaches encompassing genomics, transcriptomics, epigenomics, proteomics, metabolomics, and non-coding RNAs have transformed the landscape of biomarker discovery in GBM. Genomic profiling has revealed recurrent mutations and subtype-specific aberrations, while transcriptomic analyses refine molecular classification and uncover alternative splicing and fusion events. Epigenomic markers, particularly MGMT methylation and G-CIMP status, are now central to prognosis and therapy stratification. Proteomic and metabolomic studies highlight dysregulated pathways, metabolic vulnerabilities, and non-invasive biomarkers in cerebrospinal fluid and plasma. Integrating multi-omics data not only improves diagnostic and prognostic accuracy but also unveils therapeutic targets, offering opportunities for precision oncology. Furthermore, liquid biopsy and single-cell/spatial omics enhance real-time monitoring of disease progression and treatment response, addressing challenges posed by intratumoral heterogeneity. This review synthesizes recent advances in GBM biomarker research across multiple omics layers, emphasizing their complementary roles in unravelling tumor biology, guiding personalized treatment, and shaping future therapeutic strategies.]]> Wed, 31 Dec 1969 19:00:00 EST An Epigenetic Clock for Accurate Age Prediction in Atlantic Cod Populations for Improved Fisheries Management. Anastasiadi D, Kasmi Y, Stransky C, Casas L, Eschbach E, Piferrer F
Mol Ecol Resour (Apr 2026)

Fisheries management relies on accurate stock assessments, which in turn depend on precise age information. Recent molecular tools called 'epigenetic clocks' harness age-related DNA methylation changes to build accurate and precise age-prediction models. However, the influences of intrinsic and extrinsic factors on clock performance remain uncertain. In this study, we examined Atlantic cod aged 0 to 7 years, sampled from various locations across the North Sea, and developed an epigenetic clock using DNA methylation data of 73 CpG sites from fin clips obtained by bisulfite restriction-site associated DNA sequencing (bis-RAD-seq). This clock predicted age with 97.5% accuracy and a precision of 2.8 months and generalised well in unseen data. Further, we addressed critical variables such as sex and maturity status, which are often overlooked, and we showed that clock performance was unaffected by sex-specific differences in growth, and it was lower in advanced sexually mature individuals, reflecting a slight bias towards younger fish. A key finding of our study is the discovery of a latitudinal cline in global DNA methylation patterns. We found that DNA methylation varied with latitude, despite the absence of genetic differences, while our clock maintained consistent performance across geographic locations. This resolves a major question regarding how generalizable epigenetic clocks are within the distribution of a species. Our clock demonstrates extensive applicability and enhanced practicality for real-world fisheries management. It provides accurate and precise age prediction for Atlantic cod irrespective of intrinsic differences or environmental influences associated with geographic locations.]]> Wed, 31 Dec 1969 19:00:00 EST Epigenetic Age Acceleration and Frailty Among People with HIV. Oursler KK, Sun YV, Lozano AJ, Xu K, So-Armah KA, Montano M, Justice AC, Marconi VC
AIDS Res Hum Retroviruses (Apr 2026)

DNA methylation is a hallmark of aging; yet, our understanding of epigenetic age acceleration (EAA) in relationship to frailty in people with HIV (PWH) is poor. We conducted an observational study among PWH from the Veterans Aging Cohort Study (VACS) to test the hypothesis that EAA markers were associated with frailty. Epigenome-wide DNA methylation data from blood samples were used to derive EAA markers based on four established epigenetic clocks: Horvath, Hannum, PhenoAge, and GrimAge. Frailty was defined using a previously studied VACS frailty-related phenotype based on ≥1 survey item characterizing frailty factors: exhaustion, slowness, low physical activity, or weight loss. Logistic regression tested the association of participant characteristics and EAA markers with frailty. Adjusted models included each EAA marker as the independent variable, with significant participant characteristics as covariates. Among 1,076 PWH, frailty was evident in 397 (36.9%) individuals. The characteristics associated with frailty included chronological age, CD4 T-cell count, HIV-1 RNA viral load, smoking, and age-related comorbid conditions. GrimAge acceleration (GrimAA), PhenoAge acceleration (PhenoAA), and HannumAge acceleration (HannumAA) were associated with frailty, but HorvathAge acceleration (HorvathAA) was not. The strength of the association was attenuated with adjustment for characteristics but remained significant for the three markers. Age acceleration based on GrimAA (values >0) was independently associated with a 45% increased odds of frailty (OR: 1.45, 95% CI, 1.10, 1.93). In analyses, only GrimAA was associated with exercise frequency. In conclusion, select EAA markers were associated with frailty, independently of the traditional predictors of frailty. GrimAA, in particular, may be useful in future research to develop treatment strategies for frailty tailored to PWH.]]> Wed, 31 Dec 1969 19:00:00 EST