Epigenomics最新文献

DNA methylation (DNAm) has emerged as a powerful and dynamic biomarker for predicting health outcomes, biological aging, and disease risk. Unlike static genetic variants, DNAm is dynamic and influenced by environmental, lifestyle, and pathological factors, making it highly suitable for applications in personalized medicine. This review provides a comprehensive synthesis of recent advances in DNAm-based predictors, including epigenetic clocks, exposure biomarkers, disease risk models, and trait-specific estimators. We describe the diverse methodological frameworks underpinning these predictors, such as penalized regression, surrogate modeling and deep learning. We discuss their performance across various preprocessing strategies and study populations. Additionally, we highlight clinical and research applications, ethical considerations, and emerging challenges, such as issues of reproducibility, tissue specificity, population generalizability, and interpretability. Looking forward, we explore future directions emphasizing artificial intelligence, multiomics integration, and longitudinal modeling. By critically assessing current limitations and technological innovations, this review outlines a roadmap for advancing the development, validation, and responsible implementation of DNAm-based health predictors.

Allergic diseases are a significant global health concern. These disorders result from abnormal immune responses to environmental allergens, influenced by genetic, environmental, and epigenetic factors. Among these, histone acetylation has emerged as a key epigenetic mechanism influencing immune gene expression. Histone acetylation modulates chromatin structure and gene transcription, linking environmental exposures to immune responses. In this review, we explore how histone acetylation mechanisms regulate immune gene activation and contribute to the pathophysiology of allergic diseases and detail the role of histone acetylation in asthma, food allergy, atopic dermatitis, and other allergic conditions. Finally, we discuss therapeutic strategies targeting histone acetylation, highlighting their potential to mitigate allergic inflammation and improve patient outcomes. Understanding histone acetylation's role in allergic diseases provides a basis for developing epigenetic therapies, offering promising new approaches to managing these conditions.

Prostate cancer (PCa) is one of the most common cancers in men, distinguished by a multifaceted pathogenesis that involves substantial epigenetic modifications. This article emphasizes the critical role of chromatin remodeling in PCa advancement. Chromatin remodeling, a key epigenetic mechanism, influences gene expression by modulating the chromatin structure through the action of specialized complexes such as SWI/SNF, ISWI, CHD, & INO80, thereby regulating genes vital to tumor progression. A comprehensive literature search was conducted using PubMed, Web of Science, and Scopus databases for studies published between 2000 and 2025, focusing on chromatin remodeling, epigenetic alterations, and therapeutic strategies in PCa. The review discusses the major epigenetic changes observed in PCa, including DNA and RNA methylation, histone modifications, and non-coding RNA (ncRNA)-mediated chromatin remodeling. The evolving epigenetic landscape shaped by these alterations offers insights into novel therapeutic opportunities. The clinical relevance of targeting chromatin remodeling complexes is explored, alongside existing therapies and potential future interventions. This review also addresses challenges in studying chromatin remodeling and highlights emerging technologies that could enhance understanding of PCa epigenetics. This comprehensive exploration underscores the promise of chromatin remodeling as both a biomarker and a therapeutic target in PCa management.

DNA methylation (DNAm) is a key epigenetic modification that dynamically regulates eukaryotic development over time. DNAm has been found to influence a variety of biological processes in both normative and pathological states, such as depression. Since DNAm can serve as an interface between environmental influence and gene expression, it is a mechanism studied in the context of many pathologies, including psychiatric. Depression is a complex and heterogeneous disorder strongly influenced by puberty, as evidenced by increased rates in both sexes after sexual maturation. However, this effect is more pronounced in females, contributing to its twofold increased lifetime prevalence compared to males. Additionally, depression is consistently associated with altered DNAm at specific genomic sites. In this review, we discuss how DNAm programming can affect functional pathways during puberty and in turn, influence disease outcomes. Here, we highlight the bidirectional relationship of steroid hormone surges during this sensitive period and DNAm, adding a layer of complexity and insight into the pathophysiology of depression. Specifically, we explore the extent of DNAm change throughout puberty, how it contributes to individual and sex-specific differences in puberty, and how it may influence the risk for depression.

Background: Chronickidney disease (CKD) is a major global health burden lacking effectivetherapies. Renal interstitial fibrosis (RIF) is a key pathological driver ofCKD progression. This study aimed to identify novel diagnostic biomarkers and therapeutictargets.

Research design and methods: Weanalyzed the GEO dataset GSE137570 to identify differentially expressed genes(DEGs). Protein-protein interaction (PPI) networks were constructed to screen HubGenes. A competing endogenous RNA (ceRNA) network was predicted. Validationincluded single-cell sequencing, in vitro epithelial-mesenchymal transition(EMT) models using Transforming growth factor-β 1 (TGF-β1)-treated TCMK1 cells,clinical samples (64 CKD patients, 20 healthy controls), and dual-luciferasereporter assays (DLRA).

Results: FiveHub Genes (EGF, VCAN, CXCL1, MMP7, CCL2) were identified, with CCL2 being themost central. Enrichment analyses linked them to immune/inflammatory responses.DLRA confirmed specific targeting between miR-124-3p and both NEAT1 and CCL2,supporting the NEAT1/miR-124-3p/CCL2 axis. Clinically, serum CCL2 increasedwhile miR-124-3p and NEAT1 decreased with CKD progression; all three showedgood diagnostic accuracy for staging.

Conclusions: EGF,VCAN, CXCL1, MMP7, and particularly CCL2 are potential CKDbiomarkers/therapeutic targets. The NEAT1/miR-124-3p/CCL2 axis is a keyregulatory pathway in CKD. Key limitations include the moderate sample sizes inbioinformatics and clinical cohorts.

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.

Breast cancer (BCa) is one of the most commonly diagnosed malignancies worldwide and is clinically heterogenous. BCa is classified into distinct histopathological and molecular subtypes that inform diagnosis, treatment, and prognosis. Although therapeutic advances, particularly targeted therapies, have improved outcomes, metastatic BCa remains an unmet clinical need. In addition, treatment options remain limited especially for triple negative BCa (TNBC). There is an urgent need to develop novel approaches that can prevent, delay, or reverse disease progression in these patients. The roles of genetic and epigenetic alterations in BCa are well established. Emerging evidence highlights the dysregulation of epitranscriptomic mechanisms involving covalent RNA modifications as a contributing factor in BCa pathogenesis. Notably, recent evidence supports functional crosstalk between epigenetic and epitranscriptomic processes with potential clinical and therapeutic relevance. This review explores key epitranscriptomic RNA modifications, m⁶A, m⁶A_m, m⁵C, m⁷G, and m¹A in the context of BCa. The functional consequences of the epitranscriptomic regulators ("writers," "erasers", and "readers") are discussed alongside the accumulating evidence of their contribution to cancer development and progression. This review considers how RNA modifications and their regulators might serve as biomarkers or therapeutic targets and offers new directions for translational research and clinical intervention in BCa.

Cancer treatment is an ongoing challenge, as directly targeting oncogenic drivers is often unfeasible in many patients due to the lack of druggable targets. This has led to the exploration of alternative strategies, such as exploiting synthetic lethality (SL) relationships between genes. SL facilitates the indirect targeting of oncogenic drivers, as exemplified by the clinical success of PARP inhibitors against BRCA-mutated tumors. Advances in high-throughput perturbation screens and multi-omics technologies have deepened our understanding of SL relationships, while computational models enhance SL predictions to better reflect biological complexity. However, while numerous experimental and computational methods have been developed to identify SL interactions, difficulties remain in translating these findings into clinical applications.This review combines recent progress on SL relationships in cancer with emerging insights into epigenetic regulation, highlighting how epigenetic drugs (epidrugs) can provide new opportunities for targeted interventions, offering a way to minimize off-target effects and enhance therapeutic precision. To advance SL-based therapies, efforts must focus not only on identifying new SL interactions but also on consolidating existing knowledge and integrating experimental and computational approaches to characterize the vulnerabilities of cancer cells. Strengthening this foundation will be critical for the effective development of SL-based cancer treatments.

Background: Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder lacking objective biomarkers for early diagnosis. DNA methylation is a promising epigenetic marker, and machine learning offers a data-driven classification approach. However, few studies have examined whole-blood, genome-wide DNA methylation profiles for ASD diagnosis in school-aged children.

Methods: We analyzed genome-wide DNA methylation data from GEO dataset GSE113967, including 52 children with ASD and 48 typically developing (TD) controls. Differentially methylated positions (DMPs) were identified, and feature selection was performed using support vector machine-recursive feature elimination with cross-validation (SVM-RFECV). Classification models were developed using random forest (RF), extreme gradient boosting (XGBoost), and decision tree (DT) classifiers. A nomogram visualized feature contributions.

Results: A total of 138 DMPs differentiated ASD from TD children. Eleven CpG sites selected by SVM-RFECV formed the basis for model construction. RF and XGBoost achieved the highest accuracy (75%), with DT reaching 70%. Functional annotation indicated enrichment in cell adhesion and immune-related pathways.

Conclusions: This exploratory study demonstrates the feasibility of integrating peripheral blood DNA methylation data with machine learning to distinguish children with ASD. While limited by sample size and moderate accuracy, this study provides methodological insights into the feasibility of integrating epigenetic and computational approaches for ASD-related biomarker exploration.

Introduction: Neuroblastoma, a highly aggressive pediatric cancer, presents significant treatment challenges due to its rapid proliferation, and resistance to conventional therapies. Growing evidence emphasizes the critical role of epigenetic modifications in tumor progression.

Research design and methods: In this study, we explored the therapeutic potential of the MDM2 inhibitor RG-7388 alongside the DNMT inhibitors CM-272 and SGI-1027 in SK-N-SH and IMR-32 neuroblastoma cells. We hypothesized that RG-7388, CM-272, and SGI-1027 would induce p21 upregulation, leading to cell cycle arrest and activation of cell death pathways.

Results: Cells treated with the above listed drug exhibited significant cell death, as determined by cell viability and caspase-3/7 activation assays. qRT-PCR and Western blot analyses revealed increased expression of p21 and pro-apoptotic BAX, along with decreased levels of the anti-apoptotic protein BCL-XL. Notably, RG-7388 treatment induced substantial PARP cleavage, consistent with activation of apoptosis.These findings suggest that MDM2 and DNMT1 inhibition promotes apoptosis through a p21-driven mechanism. Importantly, DNMT1 inhibition could provide a therapeutic alternative for neuroblastomas with p53 mutations, where p53 dependent mechanism is ineffective.

Conclusion: Our results suggest that, if validated further, RG-7388, CM-272, and SGI-1027 could become effective therapeutic agents for treating aggressive neuroblastoma that may become resistant to first or second line of treatment.