'; ?> 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 Fri, 06 Jun 2025 04:58:16 EDT Fri, 06 Jun 2025 04:58:16 EDT jirtle@radonc.duke.edu james001@jirtle.com Post-fertilization transcription initiation in an ancestral LTR retrotransposon drives lineage-specific genomic imprinting of . Kobayashi H, Igaki T, Kumamoto S, Tanaka K, Takashima T, Nagaoka SI, Suzuki S, Hayashi M, Renfree MB, Kawahara M, Saito S, Kobayashi T, Nagashima H, Matsunari H, Nakano K, Uchikura A, Kiyonari H, Kaneko M, Imai H, Nakabayashi K, Lorincz M, Kurimoto K
Elife (Jun 2025)

The imprinted gene is regulated through a unique mechanism involving a transient paternal transcript in early embryos, rather than persistent gametic DNA methylation. In humans and mice, this transcript- (also known as ) or the long isoform of ()-arises from the unmethylated paternal allele and initiates secondary epigenetic marks that maintain expression. Here, we investigate the evolutionary origin of this mechanism, and show that the first exon of human overlaps with a MER21C long terminal repeat (LTR), a retrotransposon subfamily specific to Boreoeutherian mammals. Comparative analyses revealed that this MER21C insertion occurred in the common ancestor of Euarchontoglires, including primates, rodents, and rabbits. Although not annotated, the first exon of mouse displays conserved features with the MER21C-overlapping exon in humans. In rabbit and nonhuman primate placentas, orthologs with LTR-embedded first exons were also identified. In contrast, in non-Euarchontoglire mammals such as cow and tammar wallaby, is biallelically expressed, suggesting absence of imprinting. These findings suggest that imprinting emerged in Euarchontoglires via MER21C insertion. Together with our prior work on LTR-driven imprinting in oocytes, our findings demonstrate that post-fertilization activation of retrotransposons can also drive lineage-specific acquisition of imprinting.]]> Wed, 31 Dec 1969 19:00:00 EST Detection of Circulating Tumor DNA Using a Tissue-Free Epigenomic Assay Is a Highly Prognostic Biomarker in Early-Stage Triple-Negative Breast Cancer. Ademuyiwa FO, Ma CX, Weilbaecher K, Suresh R, Peterson LL, Bose R, Bagegni N, Rigden CE, Frith A, Clifton K, Dustin D, Cai M, Xiong L, Chen S, Davis AA
Clin Cancer Res (Jun 2025)

Clinical tools to monitor treatment response and metastatic risk could improve early-stage triple-negative breast cancer (TNBC) care. Although molecular residual disease assays show promise, their use in the neoadjuvant setting requires rapid turnaround times. Tissue-informed approaches may be challenging for patients with limited biopsy samples. The objectives were to determine the surveillance sensitivity for detecting metastatic recurrence and evaluate the ctDNA response to neoadjuvant therapy (NAT) using a tissue-free epigenomic assay.]]> Wed, 31 Dec 1969 19:00:00 EST Advances and applications of multiomics technologies in precision diagnosis and treatment for gastric cancer. Shen K, Hu C, Zhang Y, Cheng X, Xu Z, Pan S
Biochim Biophys Acta Rev Cancer (Jul 2025)

Gastric cancer (GC), one of the most prevalent malignancies worldwide, is distinguished by extensive genetic and phenotypic heterogeneity, posing persistent challenges to conventional diagnostic and therapeutic strategies. The significant global burden of GC highlights an urgent need to unravel its complex underlying mechanisms, discover novel diagnostic and prognostic biomarkers, and develop more effective therapeutic interventions. In this context, this review comprehensively examines the transformative roles of cutting-edge technologies, including radiomics, pathomics, genomics, transcriptomics, epigenomics, proteomics, and metabolomics, in advancing precision diagnosis and treatment for GC. Multiomics data analysis not only deepens our understanding of GC pathogenesis and molecular subtypes but also identifies promising biomarkers, facilitating the creation of tailored therapeutic approaches. Additionally, integrating multiomics approaches holds immense potential for elucidating drug resistance mechanisms, predicting patient outcomes, and uncovering novel therapeutic targets, thereby laying a robust foundation for precision medicine in the comprehensive management of GC.]]> Wed, 31 Dec 1969 19:00:00 EST Precision Health: Applications for Registered Nurses. Davis SH, Himes DO, Dewell S, Dungan JR, Lucas RF
Nurs Clin North Am (Jun 2025)

Precision health care requires the treatment of individuals, families, communities, and populations based on their genomic, biological, behavioral, and environmental characteristics. Nurses are key factors in identifying health risk factors and coordinating treatment plans." to "Nurses are essential healthcare professionals who identify health risk factors and coordinate treatment plans. Genomics-informed nurses can improve patient outcomes by advocating for appropriate care plans or riskprevention strategies at the individual, family, community, and population levels. Social determinants of health and the resulting epigenomic modifications are important factors to integrate into care plans. Genomics-informed nursing care incorporates genetic and genomic knowledge in the nursing process to promote optimal outcomes through precision health care.]]> Wed, 31 Dec 1969 19:00:00 EST Histone modifications as molecular drivers of cardiac aging: Metabolic alterations, epigenetic mechanisms, and emerging therapeutic strategies. Alrumaihi F, Al-Doaiss AA, Ullah F, Alwanian WM, Alharbi HO, Alassaf FA, Alfifi SM, Alshabrmi FM, Aba Alkhay FF, Alatawi EA
Curr Probl Cardiol (Jul 2025)

Cardiac aging represents a complex pathophysiological process characterized by progressive metabolic recombination and functional dedifferentiation of cardiac cellular components. Despite advancements in cardiovascular medicine, a critical research gap persists in understanding the precise epigenetic mechanisms that drive age-related cardiac dysfunction. This comprehensive review elucidates the pivotal role of histone modifications-including methylation, acetylation, and phosphorylation-in orchestrating the molecular landscape of cardiac aging. Significant gaps remain in our understanding of site-specific histone modification impacts on cardiac function, the intricate crosstalk between different histone marks, and their integration with metabolic alterations that characterize the aging myocardium. Current evidence reveals a dynamic epigenetic signature in aged cardiac tissue, typically featuring increased transcriptional activation markers alongside decreased repressive marks, though context-dependent variations exist. This review explores how histone modifications influence critical pathways governing mitochondrial dysfunction, DNA damage repair, inflammation, and fibrosis in aging hearts. Innovative therapeutic approaches targeting specific histone-modifying enzymes promise to mitigate age-related cardiac deterioration, potentially revolutionizing treatment paradigms for cardiovascular diseases in aging populations. Addressing these knowledge gaps requires multidimensional approaches that integrate epigenomics with functional assessment of cardiac performance.]]> Wed, 31 Dec 1969 19:00:00 EST Cell-cell communication-mediated cell-type-specific parent-of-origin effects in mammals. Wu JJ, Zheng E, Liu L, Quan J, Ruan D, Yao Z, Yang J, Li X, Wang S, Yang M, Zhang Z, Lin M, Xu Z, Li Z, Cai G, Yang J, Wu Z
Nat Commun (Jun 2025)

Genomic imprinting is manifested as monoallelic expression of genes according to parental origin, which is closely linked to mammalian placentation and human diseases. Yet, it is unclear how genomic imprinting evolves in different cell types. Here we generate a single-nucleus transcriptomic landscape of mammalian placental development, identifying 5 major cell types and 14 trophoblast subtypes. By developing a framework for integrating the datasets of single-nucleus transcriptome and whole-genome variations from reciprocal crosses of the genetically distinct Duroc and Lulai pig breeds, we construct a cell-type-specific genomic imprinting landscape, uncovering 118 candidate imprinted genes. We expand the mammalian imprinting gene catalog by identifying 97 previously uncharacterized imprinted candidates. Nearly 75% of imprinted candidates exhibit a cell-type- and developmental-stage-dependent manner. Through cross-species analysis, we show that cell-cell communication, especially the integration and modification of signaling pathways into a cell-type-specific autocrine network, drives biased allelic expression of imprinted genes in pigs, mice, and humans. Our findings provide genetic and molecular insights into parent-of-origin effects on gene expression, offering an in-depth understanding of genomic imprinting in mammals.]]> Wed, 31 Dec 1969 19:00:00 EST Broadening the Nicotiana benthamiana research toolbox through the generation of dicer-like mutants using CRISPR/Cas9 approaches. Bardani E, Katsarou K, Mitta E, Andronis C, Å tefková M, Wassenegger M, Kalantidis K
Plant Sci (Jul 2025)

RNA silencing in plants plays a pivotal role in various biological processes, including development, epigenetic modifications and stress response. Key components of this network are Dicer-like (DCL) proteins. Nicotiana benthamiana encodes four DCLs, each responsible for the generation of distinct small RNA (sRNA) populations, which regulate different functions. However, elucidating the precise role of each DCL has been proven challenging, as overlapping functions exist within DCLs. In our present study, we have successfully generated dcl2, dcl3 and dcl4 homozygous mutants, employing two different CRISPR/Cas9 approaches. The first approach is based on a transgene-mediated delivery of the single-guide RNA (sgRNA), while the second approach employs a viral vector for sgRNA delivery. By utilizing a suite of screening techniques, including polymerase chain reaction (PCR), T7 endonuclease I (T7E1) assay, high-resolution melt analysis (HRMA) and DNA sequencing, we successfully generated dcl2, dcl3 and dcl4 homozygous mutants harboring identical mutations in every allele. To evaluate these dcl mutants, we examined their sRNA profiles and phenotypes. We further have indications that homozygous mutations of a gene do not always lead to the desired loss-of-function, highlighting the importance of mutant evaluation. dcl mutants represent invaluable tools to explore how overlapping silencing pathways are connected to essential plant functions, including development, stress responses and pathogen defense. Additionally, they hold potential for biotechnological applications, such as crop improvement and gene silencing tools. We anticipate that our study will make significant contributions to enhance understanding of the role of DCLs in plants.]]> Wed, 31 Dec 1969 19:00:00 EST Resolving sequencing-based HIV-1 epitranscriptomics. Bosmeny MS, Mamede JI, Gagnon KT
Epigenomics (Jun 2025)

The collection of HIV-1 RNA chemical modifications and their functional consequences in viral gene expression, host interactions, and the viral life cycle, referred to as HIV-1 epitranscriptomics, remain incompletely understood. While the field is evolving, diverse modification discovery methods, cell lines, HIV-1 sequences, and bioinformatics methods make a consensus view of the HIV-1 epitranscriptome difficult to resolve. Here, we review methods for identifying and interpreting N-methyladenosine (mA), 5-methylcytosine (mC), pseudouridine (Ψ), 2´--methylation (N), and N-acetylcytidine (acC) modifications in HIV-1, including antibody-based selection methods, chemical-treatment-based selection methods, and detection by nanopore direct RNA sequencing. We recommend the adoption of the latter as a standardized sequencing strategy to enable better benchmarking across diverse studies and help resolve HIV-1 epitranscriptomics.]]> Wed, 31 Dec 1969 19:00:00 EST Development and validation of a machine learning prognostic model based on an epigenomic signature in patients with pancreatic ductal adenocarcinoma. Zaccaria GM, Altini N, Mongelli V, Marino F, Bevilacqua V
Int J Med Inform (Jul 2025)

In Pancreatic Ductal Adenocarcinoma (PDAC), current prognostic scores are unable to fully capture the biological heterogeneity of the disease. While some approaches investigating the role of multi-omics in PDAC are emerging, the analysis of methylation data is under exploited.]]> Wed, 31 Dec 1969 19:00:00 EST Host-microbe multi-omics and succinotype profiling have prognostic value for future relapse in patients with inflammatory bowel disease. O'Sullivan J, Patel S, Leventhal GE, Fitzgerald RS, Laserna-Mendieta EJ, Huseyin CE, Konstantinidou N, Rutherford E, Lavelle A, Dabbagh K, DeSantis TZ, Shanahan F, Temko A, Iwai S, Claesson MJ
Gut Microbes (Dec 2025)

Crohn's disease (CD) and ulcerative colitis (UC) are chronic relapsing inflammatory bowel disorders (IBD), the pathogenesis of which is uncertain but includes genetic susceptibility factors, immune-mediated tissue injury and environmental influences, most of which appear to act via the gut microbiome. We hypothesized that host-microbe alterations could be used to prognostically stratify patients experiencing relapses up to four years after endoscopy. We therefore examined multiple omics data, including published and new datasets, generated from paired inflamed and non-inflamed mucosal biopsies from 142 patients with IBD (54 CD; 88 UC) and from 34 control (non-diseased) biopsies. The relapse-predictive potential of 16S rRNA gene and transcript amplicons (standing and active microbiota) were investigated along with host transcriptomics, epigenomics and genetics. While standard single-omics analysis could not distinguish between patients who relapsed and those that remained in remission within four years of colonoscopy, we did find an association between the number of flares and a patient's succinotype. Our multi-omics machine learning approach was also able to predict relapse when combining features from the microbiome and human host. Therefore multi-omics, rather than single omics, better predicts relapse within 4 years of colonoscopy, while a patient's succinotype is associated with a higher frequency of relapses.]]> Wed, 31 Dec 1969 19:00:00 EST Intervention of machine learning in bladder cancer research using multi-omics datasets: systematic review on biomarker identification. Kiruba B, Narayan PSA, Raj B, Raj SR, Mathew SG, Lulu SS, Sundararajan V
Discov Oncol (Jun 2025)

Bladder cancer (BC) is one of the most prevalent types of cancer in developed countries. BC is characterized by its highly heterogeneous and dynamic nature, with significantly higher morbidity and mortality rates in men compared to women. Diagnosing BC requires traditional methods, such as cystoscopy, which can be invasive and costly. Recent research has heavily focused on multi-omics analysis, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, for biomarker identification. However, challenges such as computational complexity and data integration prevent these methods from achieving robust diagnostic capabilities. Hence, machine learning (ML), with its ability to process high-dimensional data and identify complex patterns, offers a promising patient outcome. By exploiting genomics, epigenomics, transcriptomics, proteomics, and metabolomics data, these models facilitate the discovery of reliable biomarkers, which are critical for early detection, prognosis, and risk stratification of the disease. Integrated models combining computational techniques with large multi-omics datasets have gained significant attention, enabling the identification of significant BC biomarkers that include genes coding for diverse cellular functions, differentially expressed genes, proteins, and metabolites. A substantial amount of multi-omics data collected from clinics and laboratories are utilized to train powerful ML models such as Support Vector Machines (SVM), random forests (RF), decision trees (DT), and gradient boosting methods (e.g., XGBoost) to perform complex tasks, including biomarker discovery, classification of subtypes and feature selection. This comprehensive review highlights the essence of integrated multiomics-ML approaches for the improvement of prognosis and diagnosis of BC.]]> Wed, 31 Dec 1969 19:00:00 EST Divergent combinations of enhancers encode spatial gene expression. Hong D, Shu M, Liu J, Liu L, Cheng H, Zhu M, Du Y, Xu B, Hu D, Liu Z, Zhao Y, Dai J, Lu F, Huang J
Nat Commun (Jun 2025)

Spatial transcriptomics and epigenomics have enabled mapping gene regulation in the tissue context. However, it remains poorly understood how spatial gene expression patterns are orchestrated by enhancers. Here we build eSpatial, a computational framework that deciphers spatially resolved enhancer regulation of gene expression by integrating spatial profiles of gene expression and chromatin accessibility. Applying eSpatial to diverse spatial datasets, including mouse embryo and brain, as well as human melanoma and breast cancer, we reveal a "spatial enhancer code", in which divergent combinations of enhancers regulate the same gene in spatially segregated domains. We validate the spatial enhancer code using public spatial datasets such as VISTA, Allen in situ hybridization (ISH), and H3K27ac MERFISH. Moreover, we conduct transgenic reporter assays and in vivo CRISPR/Cas9-mediated perturbation experiments to confirm the Atoh1 spatial enhancer code in determining Atoh1 spatial expression in mouse embryonic spinal cord and brain. Our study establishes the spatial enhancer code concept, revealing how combinations of enhancers dynamically shape gene expression across diverse biological contexts, providing insights into tissue-specific regulatory mechanisms and tumor heterogeneity.]]> Wed, 31 Dec 1969 19:00:00 EST Monoallelic gene expression in developing cells increases genetic noise and Shannon entropy. Wolff R, Balzani E, Gelli E, Polito A, Serani A, Tucci V
Commun Biol (Jun 2025)

Monoallelic gene expression is a pivotal phenomenon in developmental biology, notably through the influence of imprinted genes. Our model predicts that monoallelic expression generates expression variability, which we assess by measuring genetic noise and entropy within Shannon's information theory framework. Analyzing single-cell allele-specific expression across human and mouse datasets, we consistently observe increased expression variability due to monoallelic expression, affecting both imprinted and co-expressed non-imprinted genes. Moreover, we find decreasing variability in developing neurons and increasing variability in glial cells. The discovery of distinct noise patterns in over 80% of analyzed genes between glial and neuronal populations highlights the importance of differential noise in neurodevelopmental processes. Given the critical role of imprinted genes in biological processes such as growth and brain development, disruptions in their expression might contribute to various disorders. Understanding the stochastic nature of monoallelic expression and its genome-wide impact offers new insights into the mechanisms underlying these pathologies.]]> Wed, 31 Dec 1969 19:00:00 EST AD-GCN: A novel graph convolutional network integrating multi-omics data for enhanced Alzheimer's disease diagnosis. Li Z, Li Q, Li X, Luo W, Guo H, Zhao C, Yang C, Xie A, Hu K, Guo Y
PLoS One (2025)

Alzheimer's disease (AD) etiology is complex, influenced by demographic risk factors such as age, sex, and educational level, alongside multi-omics factors derived from genomics, transcriptomics, and epigenomics. Advancements in multi-omics technology present both challenges and opportunities for AD diagnosis, enabling a more comprehensive understanding of the complex interactions among contributing factors, with the goal of improving diagnostic accuracy. To address this challenge, we propose a novel feature fusion approach in this study, AD-GCN, which integrates multi-omics data and their interaction networks to achieve more precise diagnosis and analysis of AD. In this study, we applied polygenic risk score and random forest algorithms for feature selection on genetic variation and methylation data. We then developed an AD-GCN for both multi-omics and single-omics classification tasks and compared its performance with that of machine learning ensemble methods. The experimental results demonstrated that multi-omics classification significantly outperformed single-omics classification, with AD-GCN surpassing the machine-learning ensembles. These findings highlight AD-GCN's strong potential to enhance AD diagnosis and improve accuracy in differentiating disease stages by integrating interactions across omics data, laying a solid foundation for the development of more precise and personalized AD diagnostic models.]]> Wed, 31 Dec 1969 19:00:00 EST Targeting SLC7A11-mediated cysteine metabolism for the treatment of trastuzumab-resistant HER2-positive breast cancer. Hua Y, Duan N, Sun C, Yang F, Tian M, Sun Y, Zhao S, Gong J, Liu Q, Huang X, Liang Y, Fu Z, Li W, Yin Y
Elife (Jun 2025)

Trastuzumab resistance remains a challenge for HER2-positive breast cancer treatment. Targeting metabolic reprogramming would provide novel insights for therapeutic strategies. Here, we integrated metabolomics, transcriptomics, and epigenomics data of trastuzumab-sensitive and primary-resistant HER2-positive breast cancer to identify metabolic alterations. Aberrant cysteine metabolism was discovered in trastuzumab primary-resistant breast cancer at both circulating and intracellular levels. The inhibition of SLC7A11 and cysteine starvation could synergize with trastuzumab to induce ferroptosis. Mechanistically, increased H3K4me3 and decreased DNA methylation enhanced SLC7A11 transcription and cystine uptake in trastuzumab-resistant breast cancer. The regulation of epigenetic modifications modulated cysteine metabolism and ferroptosis sensitivity. These results revealed an innovative approach for overcoming trastuzumab resistance by targeting specific amino acid metabolism.]]> Wed, 31 Dec 1969 19:00:00 EST Methyl-Micro-C: simultaneous characterization of chromatin accessibility, interactions, and DNA methylation. Gonzalez-Smith L, Stevens C, Cao H, Wu Z, Rhie SK
NAR Genom Bioinform (Jun 2025)

Epigenomes, characterized by patterns of different signatures such as chromatin accessibility, chromatin interactions, and DNA methylation, vary across cell types and play a pivotal role in regulating gene expression. By mapping these signatures, the underlying mechanisms of development and diseases can be uncovered. However, many canonical epigenetic methods focus on mapping only one signature. Simultaneous measurement of epigenetic signatures from the same cell or tissue provides significant benefits for research, especially when resources are limited, and precise analysis is essential. Here, we report a technique called Methyl-Micro-C (MMC), which simultaneously profiles chromatin accessibility, chromatin interactions, and DNA methylation in the same sample. MMC enhances the resolution of chromatin interactions and the coverage of CpGs by combining MNase-mediated fragmentation with enzymatic conversion. This technique allows for the profiling of three-dimensional epigenomes, capturing consistent chromatin accessibility, chromatin interactions, and DNA methylation signals in an efficient manner. It is also relatively straightforward, allowing researchers to implement and apply it easily.]]> Wed, 31 Dec 1969 19:00:00 EST Epigenetic effects of paternal environmental exposures and experiences on offspring phenotypes. Liao H, Lu D, Reisinger SN, Mehrabadi MR, Gubert C, Hannan AJ
Trends Genet (Jun 2025)

Recent decades have revealed increasing evidence for epigenetic inheritance through paternal environmental exposures and experiences, affecting offspring health outcomes across diverse species. Key epigenetic mediators in sperm may include DNA methylation, chromatin modifications, as well as small and long non-coding (nc)RNAs. Identified environmental influences extend beyond lifestyle factors (e.g., exercise, diet, alcohol, and nicotine use) to include stress, infections, pollutants, and other toxins. Evidence from humans, rodents, and other species suggests that various paternal exposures before conception substantially shape the phenotypes in offspring, via developmental modulation, including changes to brain and behavior, metabolism, endocrinology, and physiology. These findings raise concerns regarding human epigenetic inheritance, because the relevant environmental exposures have changed significantly in recent decades, potentially increasing the risk of future generations for various disorders ('transgenerational epigenopathy'). Here, we integrate evidence for paternal environmental exposures affecting offspring phenotypes, and associated epigenetic mechanisms, critically discussing potential implications for medicine and other scientific fields.]]> Wed, 31 Dec 1969 19:00:00 EST The predictive power of profiling the DNA methylome in human health and disease. Christofidou P, Bell CG
Epigenomics (Jun 2025)

Early and accurate diagnosis significantly improves the chances of disease survival. DNA methylation (5mC), the major DNA modification in the human genome, is now recognized as a biomarker of immense clinical potential. This is due to its ability to delineate precisely cell-type, quantitate both internal and external exposures, as well as tracking chronological and biological components of the aging process. Here, we survey the current state of DNA methylation as a biomarker and predictor of traits and disease. This includes Epigenome-wide association study (EWAS) findings that inform Methylation Risk Scores (MRS), EpiScore long-term estimators of plasma protein levels, and machine learning (ML) derived DNA methylation clocks. These all highlight the significant benefits of accessible peripheral blood DNA methylation as a surrogate measure. However, detailed DNA methylation biopsy analysis in real-time is also empowering pathological diagnosis. Furthermore, moving forward, in this multi-omic and biobank scale era, novel insights will be enabled by the amplified power of increasing sample sizes and data integration.]]> Wed, 31 Dec 1969 19:00:00 EST Sequence and parent-of-origin dependent mA contribute to allele-specific gene expression. Zhang Y, Zhang ZY, Chen HX, Liu C, Liu BD, Lan YL, Xie YY, Chen T, Chen S, Feng G, Zhang Z, Li W, Cao N, Wang XJ, Luo GZ
EMBO J (Jun 2025)

Multiple regulatory layers influence allele-specific expression (ASE), particularly through sequence-dependent and parent-of-origin-dependent mechanisms at the transcriptional level. However, little is known about ASE regulation at the post-transcriptional level. The most prevalent post-transcriptional mRNA modification, N-methyladenosine (mA), plays important roles in regulating gene expression. Here, we conduct transcriptome-wide analysis of allele-specific mA in mice. Using early postnatal tissues from reciprocal crosses of two divergent mouse strains, we measured allelic mA differences at single-base resolution. Our study reveals widespread sequence-dependent allelic imbalance in mA methylation, identifying thousands of allele-specific mA (ASmA) sites with statistically significant and reproducible allelic methylation differences. We find evidence of potential cis-regulatory variants within 50-nt flanking regions of ASmAs. Intriguingly, we detect parental effects on allelic methylation across mAs exhibiting parent-of-origin-dependent ASE. For both sequence- and parent-of-origin-dependent mAs, we observe opposing allelic preferences between methylation and expression, suggesting a potential role of ASmA in regulating ASE through negative effects on gene expression. Overall, our findings reveal that both cis-acting and parent-of-origin effects influence ASmA, offering new insights into post-transcriptional mechanisms of ASE regulation.]]> Wed, 31 Dec 1969 19:00:00 EST Transcriptomic and epigenomic signatures of liver metabolism and insulin sensitivity in aging mice. González JT, Scharfman OH, Zhu W, Kasamoto J, Gould V, Perry RJ, Higgins-Chen AT
Mech Ageing Dev (Jun 2025)

Age-related declines in insulin sensitivity and glucose metabolism contribute to metabolic disease. Despite the liver's central role in glucose homeostasis, a comprehensive phenotypic characterization and concurrent molecular analysis of insulin resistance and metabolic dysfunction in the aging liver is lacking. We characterized hepatic insulin resistance and mitochondrial metabolic defects through metabolic cage, hyperinsulinemic-euglycemic clamp, and tracer studies paired with transcriptomic and DNA methylation analyses in young and aged male mice. Aged mice exhibited benchmark measures of whole body and liver insulin resistance. Aged mice showed lower pyruvate dehydrogenase flux, decreased fatty acid oxidation and citrate synthase fluxes, and increased pyruvate carboxylase flux under insulin-stimulated conditions. Molecular analysis revealed age-related changes in metabolic genes Pck1, Socs3, Tbc1d4, and Enpp1. Unsupervised network analysis identified an intercorrelated phenotype module (ME-Glucose), RNA module, and DNA methylation module. The DNA methylation module was enriched for lipid metabolism pathways and TCF-1 binding, while the RNA module was enriched for MZF-1 binding and regulation by miR-155-5p. Protein-protein interaction network analysis revealed interactions between module genes and canonical metabolic pathways, highlighting genes including Ets1, Ppp1r3b, and Enpp3. This study reveals novel genes underlying age-related hepatic insulin resistance as potential targets for metabolic interventions to promote healthy aging.]]> Wed, 31 Dec 1969 19:00:00 EST