Epigenomics最新文献_第5页

DNA methylation in glioblastoma: insights from single-cell epigenomics. 胶质母细胞瘤中的DNA甲基化：来自单细胞表观基因组学的见解。

IF 3.1 4区医学

Epigenomics Pub Date : 2026-06-01 Epub Date: 2026-06-11 DOI: 10.1080/17501911.2026.2682246

Rana Zohreh, Nima Rezaei, Parisa Amirifar

{"title":"DNA methylation in glioblastoma: insights from single-cell epigenomics.","authors":"Rana Zohreh, Nima Rezaei, Parisa Amirifar","doi":"10.1080/17501911.2026.2682246","DOIUrl":"10.1080/17501911.2026.2682246","url":null,"abstract":"Isocitrate dehydrogenase (IDH)-wildtype glioblastoma is an aggressive brain tumor characterized by limited therapeutic options and poor survival outcomes. Beyond well-established genomic alterations, epigenetic mechanisms such as DNA methylation have gained attention for their roles in glioblastoma pathogenesis. Tumor suppressor genes are frequently silenced through promoter hypermethylation, whereas global hypomethylation of repetitive elements contributes to genomic instability and oncogenic progression. Clinically, O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation remains an important biomarker for predicting patient response to alkylating chemotherapies. Advances in single-cell epigenomic sequencing have characterized the remarkable heterogeneity of DNA methylation within glioblastoma. Techniques including single-cell bisulfite sequencing (scBS-seq) and single-cell reduced representation bisulfite sequencing (scRRBS) provide high-resolution insights into the methylation landscapes of individual tumor cells. These analyses reveal that epigenetic diversity underlies subclonal expansion, therapy resistance, and tumor recurrence. Moreover, integrating single-cell methylation data with other modalities such as transcriptomics and proteomics offers a multidimensional view of tumor evolution and microenvironmental dynamics. Despite ongoing challenges in cost, data interpretation, and large-scale integration, single-cell epigenomics has potential applications in refining glioblastoma classification and guiding personalized therapeutic strategies in the future. This review explores emerging roles of DNA methylation in glioblastoma alongside cutting-edge single-cell techniques and translational prospects.","PeriodicalId":11959,"journal":{"name":"Epigenomics","volume":" ","pages":"767-779"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13313216/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148224113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ultra-sensitive urine DNA methylation test enables early and accurate detection of bladder cancer. 超灵敏的尿液DNA甲基化检测能够早期准确检测膀胱癌。

IF 3.1 4区医学

Epigenomics Pub Date : 2026-06-01 Epub Date: 2026-06-22 DOI: 10.1080/17501911.2026.2688972

Zhichao Tong, Tianxi Yu, Zhilong Li, Fengming Zhang, Qing Shi, Jiaxi Peng, Yubo Zhao, Yaowei Li, Zhihui Xiu, Zhishuai Zhang, Benchi Li, Weijia Jiang, Hongjian Song, Zongzheng Yang, Haonan Li, Pengyu Guo, Dayong Hou, Zhihao Yin, Ziyi Liu, Qi Liu, Jianwei Wang, Peng Zhang, Peng Dai, Yuying Wang, Di Wang, Hang Su, Ziqi Wang

{"title":"Ultra-sensitive urine DNA methylation test enables early and accurate detection of bladder cancer.","authors":"Zhichao Tong, Tianxi Yu, Zhilong Li, Fengming Zhang, Qing Shi, Jiaxi Peng, Yubo Zhao, Yaowei Li, Zhihui Xiu, Zhishuai Zhang, Benchi Li, Weijia Jiang, Hongjian Song, Zongzheng Yang, Haonan Li, Pengyu Guo, Dayong Hou, Zhihao Yin, Ziyi Liu, Qi Liu, Jianwei Wang, Peng Zhang, Peng Dai, Yuying Wang, Di Wang, Hang Su, Ziqi Wang","doi":"10.1080/17501911.2026.2688972","DOIUrl":"10.1080/17501911.2026.2688972","url":null,"abstract":"Background: Early and accurate detection of bladder cancer (BCa), particularly low-grade and early-stage disease, remains challenging because current diagnostic methods are either invasive or insufficiently sensitive. We aimed to develop a noninvasive urine DNA methylation assay for BCa detection and postoperative monitoring.Research design and methods: Integrative methylation profiling across institutional and public cohorts identified PENK and NKPD1 as urothelial carcinoma-associated hypermethylation markers. A bisulfite-free methylation-sensitive restriction enzyme quantitative polymerase chain reaction (MSRE-qPCR) assay was developed using urine sediment DNA. Diagnostic performance was evaluated in a case-control cohort of 606 urine samples, including 340 pathologically confirmed BCa cases.Results: The dual-marker assay achieved areas under the curve (AUCs) of 92.52% and 93.00% in the training and validation cohorts, respectively. Sensitivity reached 87.74%, with specificity of 92.31% against benign urological diseases and 83.05% against non-urothelial malignancies. The assay outperformed urine cytology in low-grade tumors and provided complementary diagnostic value when combined with cytology. Postoperative methylation signals significantly decreased after tumor resection (p < 0.001).Conclusions: This bisulfite-free urine MSRE-qPCR assay provides a simple and scalable approach for noninvasive BCa detection and surveillance, with strong performance in early-stage and low-grade disease. Further prospective multicenter validation is warranted.","PeriodicalId":11959,"journal":{"name":"Epigenomics","volume":" ","pages":"709-721"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13313207/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148293938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Epigenetic regulation of non-coding DNA in placental development and disorders. 非编码DNA在胎盘发育和疾病中的表观遗传调控。

IF 3.1 4区医学

Epigenomics Pub Date : 2026-06-01 Epub Date: 2026-05-27 DOI: 10.1080/17501911.2026.2678924

Ying Hei Kan, Lin Gao, Danny Leung

{"title":"Epigenetic regulation of non-coding DNA in placental development and disorders.","authors":"Ying Hei Kan, Lin Gao, Danny Leung","doi":"10.1080/17501911.2026.2678924","DOIUrl":"10.1080/17501911.2026.2678924","url":null,"abstract":"The human placenta is an epigenetically exceptional organ that must execute rapid proliferation, lineage bifurcation, and controlled invasion while maintaining immune tolerance at the maternal-fetal interface. Trophoblast lineages operate within a developmentally programmed \"pseudo-malignant\" regulatory state, characterized by global DNA hypomethylation, large partially methylated domains, and dynamic chromatin transitions across gestation. This configuration enables transcriptional plasticity but also creates vulnerability to maternal and environmental exposures, which can leave persistent epigenetic effects associated with fetal growth restriction, preeclampsia, preterm birth, and pregnancy loss. Placental health and disease therefore cannot be understood through protein-coding genes alone. The non-coding genome, comprising promoters, enhancers, enhancer-promoter networks, and non-coding RNAs is extensively rewired in trophoblast, with retrotransposons providing a major source of regulatory innovation. Epigenetic mechanisms coordinate these elements to establish trophoblast-specific transcriptional programs, and perturbation at any layer can disrupt differentiation, invasion, endocrine signaling, and immune modulation. Maternal inflammation, hypoxia, toxins, metabolic and psychological stress reshape epigenetically labile non-coding regions, positioning the placenta as both a developmental sensor and molecular archive of the intrauterine environment. Advances in epigenomic profiling highlight the potential of non-coding epigenetic signatures as early biomarkers, while underscoring ongoing challenges in resolving cell-type-specific regulatory programs and accurately annotating repetitive elements.","PeriodicalId":11959,"journal":{"name":"Epigenomics","volume":" ","pages":"753-766"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13313205/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148028674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Epigenetic reprogramming of tissue-resident memory T cells in chronic inflammatory disorders and implications for targeted therapies. 慢性炎症性疾病中组织驻留记忆T细胞的表观遗传重编程及其靶向治疗的意义。

IF 3.1 4区医学

Epigenomics Pub Date : 2026-06-01 Epub Date: 2026-06-03 DOI: 10.1080/17501911.2026.2678920

Chen Ling, Haytham F Isleem, Ghanshyam G Tejani

{"title":"Epigenetic reprogramming of tissue-resident memory T cells in chronic inflammatory disorders and implications for targeted therapies.","authors":"Chen Ling, Haytham F Isleem, Ghanshyam G Tejani","doi":"10.1080/17501911.2026.2678920","DOIUrl":"10.1080/17501911.2026.2678920","url":null,"abstract":"Background: Tissue-resident memory T (TRM) cells play a role in causing long-term tissue injury in chronic inflammatory diseases via pathological epigenetic reprogramming. Nevertheless, the epigenetic processes that cause this malfunction have not been well defined.Research design and methods: We performed integrative multi-omics analysis of TRM cells (CD3+CD8+CD69+CD103+, >92% purity, >94% viability) from 124 patients (41 rheumatoid arthritis, 43 inflammatory bowel disease, 40 psoriasis) and 35 healthy controls, employing scATAC-seq, ChIP-seq, whole-genome bisulfite sequencing, and scRNA-seq.Results: We identified 847 differentially methylated regions (p<0.001) and 1,239 altered chromatin accessibility peaks. Pathogenic programming was sustained through TET2-mediated demethylation of pro-inflammatory enhancers for IL-17A (-43.2% methylation) and TNF (-87.3% methylation). Tissue-specific defects included FOXP3 hypermethylation (+47.3%) in intestinal TRM and elevated H3K27me3 deposition (2.3-fold) in synovial TRM. Combined inhibition using the DNMT1-targeting degrader GSK-3484862 and the EZH2 inhibitor GSK126 reversed pathological programming, reducing cytokine production by >80% in ex vivo assays. Machine learning classification achieved 94.2% accuracy (95% CI: 91.3-97.1%) distinguishing pathogenic from protective TRM cells.Conclusions: This first epigenetic atlas of TRM cells in chronic inflammation reveals tissue-specific vulnerabilities, therapeutic targets (DNMT1, EZH2), and patient stratification biomarkers. Limitations include the ex vivo validation system and the need for larger multicentric biomarker validation studies.","PeriodicalId":11959,"journal":{"name":"Epigenomics","volume":" ","pages":"681-693"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13313248/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148149221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning models predict the immunotherapy response in tumors on the basis of DNA methylation. 机器学习模型在DNA甲基化的基础上预测肿瘤的免疫治疗反应。

IF 3.1 4区医学

Epigenomics Pub Date : 2026-06-01 Epub Date: 2026-06-06 DOI: 10.1080/17501911.2026.2685058

Zheng Gu, Ning Jiang, Erle Deng, Junxian Yu

{"title":"Machine learning models predict the immunotherapy response in tumors on the basis of DNA methylation.","authors":"Zheng Gu, Ning Jiang, Erle Deng, Junxian Yu","doi":"10.1080/17501911.2026.2685058","DOIUrl":"10.1080/17501911.2026.2685058","url":null,"abstract":"Background: The epigenetic control of immune responses plays a crucial role in the development and progression of cancer. The need to identify biomarkers and create new predictive models is crucial to reliably estimate response rates in patients receiving tumor immunotherapy, which are currently low.Methods: We screened for variably methylated loci associated with immunotherapy response, focusing on relevant pathways. The expression of immunotherapy-related methylation loci was analyzed in tissues, and quantitative trait locus (QTL) features were summarized. Relationships among tumor mutational Burden (TMB), neoantigen (NeoAg), programmed death-ligand 1 (PD-L1), and immunotherapy efficacy were examined. Motif analysis identified sequence preferences linked to methylation. Six machine learning models were constructed and compared to select the optimal.Due to the lack of external validation datasets, subgroup analysis was conducted.Results: The five CpG loci showing the strongest response to immunotherapy were cg00045061, cg00107488, cg00056433, cg00090974, and cg00072957. Differentially methylated sites enriched the ubiquitin-proteasome pathway, with most loci located in the N shore region of CpG islands. GO enrichment highlighted microvillus length modulation and CXCR4 chemokine receptor binding. The support vector machine (SVM) model exhibited optimal performance, with precision of 0.796, accuracy of 0.833, F1-score of 0.663, recall of 0.55 and AUC of 0.894.The optimal SVM model achieved an AUC of 0.85 for melanoma dataset and 0.75 for lung cancer dataset.Conclusion: Tumor methylation sites hold promise as predictive biomarkers for immunotherapy efficacy. The SVM model is the optimal machine learning approach for predicting methylation sites in immunotherapy.","PeriodicalId":11959,"journal":{"name":"Epigenomics","volume":" ","pages":"695-707"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13313271/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148175644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RNA modifications at the crossroads of inflammation: METTL1-mediated m⁷G methylation of Sarm1 mRNA. 炎症十字路口的RNA修饰：mettl1介导的Sarm1 mRNA的m7G甲基化。

IF 3.1 4区医学

Epigenomics Pub Date : 2026-06-01 Epub Date: 2026-05-13 DOI: 10.1080/17501911.2026.2672094

Kathrine Rallis

引用次数: 0

MicroRNA-510-3p alleviates endothelial dysfunction in a DOCA-salt rat model of hypertension by targeting phosphatase and tensin homolog and its signaling axis. MicroRNA-510-3p通过靶向磷酸酶和紧张素同源物及其信号轴缓解DOCA-salt大鼠高血压模型的内皮功能障碍。

IF 3.1 4区医学

Epigenomics Pub Date : 2026-06-01 Epub Date: 2026-05-28 DOI: 10.1080/17501911.2026.2676125

K Auxzilia Preethi, Sushmaa Chandralekha Selvakumar, Thangavel Muthusamy, Durairaj Sekar

{"title":"MicroRNA-510-3p alleviates endothelial dysfunction in a DOCA-salt rat model of hypertension by targeting phosphatase and tensin homolog and its signaling axis.","authors":"K Auxzilia Preethi, Sushmaa Chandralekha Selvakumar, Thangavel Muthusamy, Durairaj Sekar","doi":"10.1080/17501911.2026.2676125","DOIUrl":"10.1080/17501911.2026.2676125","url":null,"abstract":"Essential hypertension, characterized by persistent elevation of blood pressure, is often associated with endothelial dysfunction (ED), marked by impaired endothelial activity. Despite advancements, the molecular mechanisms underlying ED in hypertension remain unclear. This study aimed to investigate the role of microRNA-510-3p (miR-510-3p) in regulating endothelial function through the PTEN/PI3K/AKT/eNOS signaling pathway and to evaluate its potential as a biomarker and potential therapeutic target for DOCA-salt-induced experimental hypertension. Bioinformatic and luciferase analysis suggest PTEN as a potential direct target of miR-510-3p. Human umbilical vein endothelial cells (HUVECs) were employed to assess proliferation, migration, apoptosis, and dual-luciferase activity. The expression levels of miR-510-3p, PTEN, PI3K, AKT, and eNOS were quantified using qRT-PCR in both HUVECs and rat tissues. Hypertensive DOCA-salt-induced rats exhibited significantly increased systolic and diastolic pressures with evident vascular hypertrophy. Both mRNA expression analyses revealed elevated miR-510-3p, PI3K, AKT, and eNOS levels and a marked decrease in PTEN expression in HUVECs and hypertensive DOCA-salt-induced rats. miR-510-3p is associated with changes in endothelial function and PTEN expression, potentially involving the PI3K/AKT/eNOS signaling pathway. Taken together, miR-510-3p may represent a candidate biomarker and potential therapeutic target, warranting further validation. However, as the DOCA-salt model primarily reflects a low-renin, volume-dependent form of hypertension, these findings may not fully represent the complexity of human essential hypertension.","PeriodicalId":11959,"journal":{"name":"Epigenomics","volume":" ","pages":"667-680"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13313270/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148041510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Interplay of the 3D genome and epigenome in androgen-driven prostate cancer. 三维基因组和表观基因组在雄激素驱动的前列腺癌中的相互作用。

IF 3.1 4区医学

Epigenomics Pub Date : 2026-06-01 Epub Date: 2026-05-22 DOI: 10.1080/17501911.2026.2676129

Elyssa M Campbell, Dayna Challis, Susan J Clark, Joanna Achinger-Kawecka

{"title":"Interplay of the 3D genome and epigenome in androgen-driven prostate cancer.","authors":"Elyssa M Campbell, Dayna Challis, Susan J Clark, Joanna Achinger-Kawecka","doi":"10.1080/17501911.2026.2676129","DOIUrl":"10.1080/17501911.2026.2676129","url":null,"abstract":"Understanding of the therapeutic landscape for androgen-driven prostate cancer has undergone significant evolution, yet treatment resistance remains an ongoing challenge. The androgen receptor (AR) plays a central role in androgen-dependent prostate tumor growth, and therapeutic agents targeting AR represent the main treatment modality for prostate cancer. AR transcriptional activity is tightly regulated by coregulatory transcription factors and their DNA binding and activity. However, the precise interactions between AR and three-dimensional (3D) chromatin structure and its dynamic remodeling represent a critical yet underexploited therapeutic frontier. Here, we present a perspective on how the spatial architecture of the epigenome, including 3D chromatin structure and dynamics, orchestrates dysregulation of transcription factor networks that help to drive disease progression in androgen-driven prostate cancer. We argue that successful therapeutic intervention requires moving beyond linear epigenetic marks toward a three-dimensional understanding of the epigenetic landscape. Such a shift is essential to capture the complex enhancer-promoter communications and chromatin state transitions that define the disease. Drawing on recent advances in prostate cancer biology and technological developments, we propose a unique integrated framework centered on patient-specific 3D epigenomic vulnerabilities for next-generation epigenetic therapies designed to disrupt oncogenic transcriptional programs by specifically targeting chromatin topology.","PeriodicalId":11959,"journal":{"name":"Epigenomics","volume":" ","pages":"739-751"},"PeriodicalIF":3.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13313260/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147987011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning-driven integration of multi-omics data uncovers methylation-dependent molecular signatures for luminal A and B breast cancer subtypes. 机器学习驱动的多组学数据集成揭示了luminal A和B乳腺癌亚型的甲基化依赖分子特征。

IF 3.1 4区医学

Epigenomics Pub Date : 2026-05-01 Epub Date: 2026-05-16 DOI: 10.1080/17501911.2026.2675550

Mohamed Elsisi, Mohamad Maged, Mohamed Elhwary, Kamal Abdallah, Hamza Alaa-Eldin, Assem K Elsherif

{"title":"Machine learning-driven integration of multi-omics data uncovers methylation-dependent molecular signatures for luminal A and B breast cancer subtypes.","authors":"Mohamed Elsisi, Mohamad Maged, Mohamed Elhwary, Kamal Abdallah, Hamza Alaa-Eldin, Assem K Elsherif","doi":"10.1080/17501911.2026.2675550","DOIUrl":"10.1080/17501911.2026.2675550","url":null,"abstract":"Background: Breast cancer is the most common malignancy in women and includes molecular subtypes with distinct clinical outcomes, such as luminal A and luminal B. Although luminal tumors account for most cases, the epigenetic mechanisms differentiating luminal A from the more aggressive luminal B subtype remain unclear. We developed an interpretable machine learning pipeline to reduce genomic noise and identify methylation-dependent regulatory signatures by distinguishing these subtypes.Methods: The INTEND algorithm was trained on 4,441 paired RNA-seq and DNA methylation samples from 14 cancer types, excluding breast cancer, to prevent data leakage. This training generated an epigenetic filter identifying genes whose expression is predictable from methylation. The filter was applied to 537 TCGA-BRCA luminal samples to predict expression and extract CpG-level regulatory signals.Results: The model identified 2,670 high-confidence genes (R2 ≥ 0.6) and achieved strong predictive accuracy (average R2 = 0.76). Subtype-specific genes were identified through differential expression of the filtered dataset and removal of shared genes, yielding 30 methylation-driven biomarkers unified by strong methylation-expression coupling and distinct subtype-specific expression patterns.Conclusion: This framework identifies potential methylation-controlled genes underlying luminal breast cancer differentiation, reducing transcriptional noise while revealing CpG regulatory mechanisms.","PeriodicalId":11959,"journal":{"name":"Epigenomics","volume":" ","pages":"591-602"},"PeriodicalIF":3.1,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13215307/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147959737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Altered HDAC expression is associated with CYP24A1-mediated vitamin D deficiency in gestational diabetes mellitus. 妊娠期糖尿病患者HDAC表达改变与cyp24a1介导的维生素D缺乏有关。

IF 3.1 4区医学

Epigenomics Pub Date : 2026-05-01 Epub Date: 2026-05-06 DOI: 10.1080/17501911.2026.2667346

K L Milan, M Anuradha, K M Ramkumar

{"title":"Altered HDAC expression is associated with CYP24A1-mediated vitamin D deficiency in gestational diabetes mellitus.","authors":"K L Milan, M Anuradha, K M Ramkumar","doi":"10.1080/17501911.2026.2667346","DOIUrl":"10.1080/17501911.2026.2667346","url":null,"abstract":"Background: Low vitamin D levels during pregnancy are associated with an increased risk of Gestational Diabetes Mellitus (GDM), potentially mediated by altered vitamin D metabolism. Cytochrome P450 family 24 subfamily A member 1 (CYP24A1) plays a key role in vitamin D catabolism, but its epigenetic regulation in GDM remains unclear.Research design and methods: This cross-sectional study included 150 pregnant women [normoglycemic (NGDM, n = 50), early GDM (eGDM, n = 50), and GDM (n = 50)] and 40 placental samples (NGDM, n = 20; GDM, n = 20). Gene expression of histone deacetylases (HDACs), sirtuins (SIRTs), and CYP24A1 was analyzed using real-time PCR. In vitro experiments using BeWo cells assessed the effects of high glucose and trichostatin A (TSA).Results: CYP24A1 expression was significantly increased in GDM participants. Distinct alterations in HDAC and SIRT expression were observed, with HDAC3, HDAC4, and HDAC7 negatively correlated and SIRT7 positively correlated with CYP24A1. HDAC modulation using TSA regulated CYP24A1 expression under hyperglycemic conditions.Conclusions: These findings offer insights into the association of multiple HDACs regulating CYP24A1-mediated vitamin D deficiency in the pathophysiology of GDM. However, further mechanistic and longitudinal studies are required to elucidate the precise mechanism.","PeriodicalId":11959,"journal":{"name":"Epigenomics","volume":" ","pages":"551-564"},"PeriodicalIF":3.1,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13215315/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147835314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0