SEARCH · PubMed Health

Results for “Enhancer mapping”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2Linked to original sources

PubMed2026

Educational approaches to enhance genomics competencies among health sciences students: A scoping review with implications for nursing education.

INTRODUCTION: Genomics is increasingly recognized as essential for precision health, yet its integration into undergraduate nursing and other health sciences curricula remains limited. Persistent gaps in genomics literacy and confidence among students and professionals indicate that current educational approaches may not adequately prepare graduates for genomics-informed care and precision health. The aim of this review is to map educational approaches and methods used to enhance genomic competencies among undergraduate health sciences students and discuss implications for nursing education. METHODS: Scoping review, reported in accordance with PRISMA-ScR recommendations. Systematic search in CINAHL Ultimate, ERIC, and MEDLINE for studies published in English between January 2015 and December 2024 was undertaken. Data were charted using a standardized extraction form and synthesized descriptively and narratively, grouping interventions by educational approach, methods, strategies, techniques, and tools. RESULTS: Thirty-one studies were included, mostly from the United States, involving primarily medical and nursing students. Educational approaches centered on experiential and practice-based learning, simulation, case- and problem-based learning, flipped classrooms, collaborative or interprofessional learning, narrative and arts-based methods, and technology-enhanced strategies such as virtual labs, online modules, and digital storytelling. These approaches were associated with improvements in genomic knowledge, application to clinical scenarios, ethical awareness, engagement, and self-reported confidence, although outcomes were predominantly short-term. CONCLUSIONS: Genomics education for health sciences students is characterized by diverse, largely experiential and student-centered approaches. Integration into curricula remains fragmented and often focused on genetics rather than broader genomics and precision health. Nurse educators should prioritize integrated, authentic, and ethically informed genomics education, supported by educator development and digital technologies, including generative AI, to prepare graduates for precision nursing care.

Genomics↗

PubMed2026

An encyclopedia of human enhancer-gene regulatory interactions.

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the effect of human genetic variation on disease1-6. Here we create and evaluate a resource of more than 92 million enhancer-gene regulatory interactions across 1,458 biosamples covering 369 cell types and tissues, by integrating predictive models, chromatin states, three-dimensional contacts and large-scale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,356 element-gene pairs measured in CRISPR perturbation experiments, more than 30,000 fine-mapped expression quantitative trait loci and 569 fine-mapped genome-wide association study (GWAS) variants linked to a probable causal gene. Using this framework, we develop ENCODE-rE2G, a predictive model achieving state-of-the-art performance across several prediction tasks, demonstrating that iterative perturbations and supervised machine learning can build increasingly accurate predictive models of enhancer regulation. Using ENCODE-rE2G, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, revealing global properties of enhancer networks, identifying differences in regulatory complexity across genes and improving analyses linking noncoding variants to target genes and cell types for common complex diseases. By interpreting the model, we find that beyond enhancer activity and three-dimensional enhancer-promoter contacts, additional features that guide enhancer-promoter communication include promoter class and enhancer-enhancer synergy. These genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

Humans↗

PubMed2026

YIPFα1A expression is regulated by multilayered molecular mechanisms.

Yip domain family (YIPF) proteins are five-pass transmembrane proteins that localize primarily to the Golgi apparatus. These proteins assemble into higher-order complexes with each α-subunit pairing specifically with a β-subunit to form a dimer which then assemble into complexes with two to four dimers. Notably, β-subunit expression depends on the corresponding α-subunit partner, and conventional transient overexpression of α-subunits has been extremely inefficient, hindering deeper analysis of YIPF complexes. To identify the cause of poor exogenous expression, we examined YIPF gene features and found two properties correlated with low expression: (i) rare-codon enrichment in the CDS and (ii) extended 3' UTRs. Experimental analyses focusing on YIPFα1A revealed that rare-codon enrichment suppresses expression mainly at the mRNA level, consistent with translation-coupled mRNA decay, whereas inclusion of the native 3' UTR enhances expression by increasing mRNA abundance. Deletion mapping further showed that a proximal 3' UTR segment (51-150) is necessary and sufficient for mRNA stabilization, thereby elevating both mRNA and protein levels. Conversely, a distal 3' UTR fragment (1116-2230) increased mRNA but not protein levels, suggesting translational repression resulting in a reduced protein-to-mRNA ratio. Together, these findings explain the discrepancy between endogenous and exogenous YIPFα1A expression and propose a multilayered regulatory model in which rare codons decrease mRNA, the proximal 3' UTR stabilizes mRNA, and the distal 3' UTR reduces translation. Impact statement Our work advances YIPF biology and identifies post‑transcriptional mechanisms governing multi‑pass membrane proteins. We show rare‑codon and 3' UTR‑based control of trafficking proteins-an area largely unexplored-and introduce a new paradigm for membrane‑traffic regulation that will guide future studies of complex assembly, localization, and homeostasis.

3' Untranslated Regions↗

PubMed2026

Locus-specific stratification and prioritization unveil genetic risk mechanism underlying complex diseases.

Although genome-wide association studies have identified thousands of disease-associated loci, the mechanistic understanding and drug target discovery remain challenging, particularly for complex diseases. The multi-signal architecture of complex diseases complicates the interpretation of genetic contributions. To address this challenge, we develop an approach comprising locus-specific stratification (LSS) and gene regulatory prioritization score (GRPS), which uniquely considers multi-signals during fine-mapping and target gene identification. LSS significantly enhances the interpretability of genetic risk associated with complex diseases. For loci associated with serum urate levels, the method identifies candidate causal genes in 34.43% of loci, surpassing the performance of other methods by 5.47% to 25.14%. GRPS considers the regulatory network of LSS-variants comprehensively and successfully nominates under-explored drug targets for hyperuricemia with high confidence such as SLC17A4, which is further validated using epigenetic activation and phenotypic assays. This study introduces an approach to efficiently and comprehensively address the multi-signal challenges in complex diseases.

Humans↗

PubMed2026

The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review.

INTRODUCTION: Intimate partner violence (IPV), encompassing physical, sexual, emotional and economic abuse, remains a pervasive global health concern. Traditional prevention efforts face obstacles such as underreporting, delayed detection and limited personalised support. Emerging artificial intelligence (AI) approaches offer new opportunities to enhance IPV prevention. AIM: This systematic review maps and synthesises evidence on AI-driven tools in IPV prevention based on studies published between 2004 and 2024. METHODS: Following PRISMA 2020 guidelines and PROSPERO registration, we searched PubMed, Embase, CINAHL, PsycINFO, IEEE Xplore and Web of Science. Eligible studies explicitly evaluated AI technologies targeting IPV prediction, screening, intervention or support delivery. Study quality was appraised using the Mixed Methods Appraisal Tool (MMAT). RESULTS: Of 1304 records initially identified, 41 studies met eligibility criteria. AI applications ranged from machine learning (ML) for risk prediction and natural language processing (NLP) for IPV detection in clinical and social media data, to image analysis for forensic evaluation and chatbot-based support. Predictive modelling demonstrated strong discriminative performance, while NLP-based screening detected IPV with notable sensitivity. Chatbots showed feasibility and user acceptability, but evidence of their direct impact on reducing IPV incidence was limited, with one randomised controlled trial showing a modest reduction. Key challenges identified included algorithmic bias, data privacy risks and barriers to integration across health and social care systems. DISCUSSION: AI-informed interventions show promise for improving IPV detection, risk assessment, and scalable support, but questions remain about long-term effectiveness, ethical fairness, transparency and equitable implementation. Future interdisciplinary research should address these concerns to responsibly deploy AI in IPV prevention. RELEVANCE TO CLINICAL PRACTICE: The findings highlight the importance of trauma-informed, culturally responsive care and provider training in AI applications. Nurse-led innovation and policy advocacy will be crucial for safe, equitable integration of AI in IPV prevention.

Artificial Intelligence↗

PubMed2026

Assessment of differentially culturable tubercle bacteria assays for the detection of tuberculosis infection in asymptomatic household contacts and the implications for intra-household transmission: a longitudinal cohort study.

BACKGROUND: Conventional culture methods for tuberculosis diagnosis miss differentially culturable tubercle bacteria (DCTB), which grow only in liquid assays supplemented with growth-enhancing factors. This limitation, combined with inadequate contact tracing and screening, often fails to identify asymptomatic individuals, with live bacilli detectable by enhanced culture methods. This shortfall results in undiagnosed reservoirs of bacteria, potentially fuelling ongoing transmission. In this study, we aimed to investigate whether DCTB assays provide greater sensitivity by detecting more Mycobacterium tuberculosis infections than conventional culture and whether this enhanced detection improves the resolution of intrahousehold transmission mapping. In addition, we sought to evaluate whether DCTB populations can progress to conventional culture positivity, thereby highlighting their clinical and epidemiological relevance. METHODS: In this prospective observational longitudinal cohort study, drug-susceptible or rifampicin-resistant tuberculosis index participants aged 12 years or older, were recruited from primary healthcare clinics from two South African districts. Inclusion criteria were informed consent, Xpert MTB/RIF Ultra-positive results, tuberculosis symptoms (>2 weeks), provision of baseline samples, at least one consenting household contact, and documented HIV status. Household contacts of the index patients and control households were also recruited. Sputum specimens were collected at baseline and 2, 4, 8, 12, and 16 months from the index participants and household contacts. Samples were analysed by conventional mycobacterial growth indicator tube (MGIT) culture, and colony-forming unit assays to identify viable bacteria. Enhanced culture to detect DCTB involved serial dilution of sputum in liquid culture, supplemented with M tuberculosis culture filtrate as a source of growth stimulatory factors. Whole-genome sequencing (WGS) of cultured isolates was performed to trace household transmission. FINDINGS: Between June 1, 2020, and Feb 6, 2024, 293 index participants (183 [62%] male), 701 household contacts (453 [65%] female), and 122 control participants (67 [55%] female) were enrolled. At baseline, 249 (85%) of 293 index participants and 110 (16%) of 701 household contact sputum samples were positive for M tuberculosis by MGIT conventional culture. For baseline MGIT-negative specimens, DCTB assays detected M tuberculosis in an additional 21 (7%) of 293 index participants and 26 (4%) of 701 household contacts. Over 16 months of follow-up, DCTB assays identified 61 (8·7%) of 701 additional tuberculosis-positive household contacts not detected by conventional culture. WGS-guided transmission mapping using conventional culture identified transmission in 16 (15%) of 104 households, whereas DCTB assays detected an additional 19 (18%) of 104 transmission events. No evidence of intrahousehold transmission was found in the remaining 69 (66%) of 104 tuberculosis-positive households. Over the 16-month follow-up period, conventional culture identified 233 positive household contacts, of which 195 (84%) were asymptomatic. DCTB assays detected an additional 94 cases of M tuberculosis positivity in household contacts, of which 79 (84%) were asymptomatic. In control households, tuberculosis prevalence at baseline was two (2%) of 122, with an additional three (3%) of 122 identified during follow-up. INTERPRETATION: DCTB assays provide substantial value by detecting asymptomatic individuals missed by conventional culture, revealing a potentially important reservoir of subclinical infection, which could sustain transmission. In addition, DCTB detection uncovers transmission linkages missed by conventional culture, providing a more comprehensive understanding of M tuberculosis transmission dynamics and highlighting the need to incorporate enhanced culture methods into diagnostic and surveillance strategies, to strengthen early case identification and tuberculosis control efforts. FUNDING: National Institutes of Health.

Humans↗

PubMed2026

A network of steroid receptor transcription factors regulates ovarian chromatin remodeling in the transition to ovulation.

Steroid receptors are transcription factors activated by progesterone, androgen, and glucocorticoid that bind the same canonical DNA sequence to modulate genome function in response to steroid hormones. However, the mechanisms defining unique physiological roles of these conserved receptors within the same tissue context, including the ovary, remain elusive. Here, we describe the dynamic association between each steroid receptor cistrome in the mouse ovary responding to the hormonal switch from follicle development to ovulation and generate chromatin conformation maps to define steroid receptor roles in promoter-enhancer interactions and gene transcription. Ovulatory hormones trigger progesterone receptor (PGR) and glucocorticoid receptor (NR3C1 [also known as GR]) binding to novel chromatin sites, promoting transcriptional activation of genes that are required for ovulation, whereas AR-chromatin interactions and androgen receptor (AR)-associated genes are repressed. Integration of genomic and transcriptomic data illustrates two parallel modes of PGR-mediated gene activation. Unique cooperation between PGR and GR enables their recruitment to previously inaccessible promoters, increasing histone acetylation, chromatin accessibility, and transcription activation, with PGR being the indispensable component of this transcriptional complex. Alternatively, PGR tethered to enhancers interacting with preaccessible, AR/GR-bound promoters induces gene activation. Our findings illustrate the multifaceted steroid receptor interactions that translate progressive change in steroid environments to collectively reprogram granulosa cell genome function to switch from follicle development to ovulation.

Journal Article↗

PubMed2024

A research synthesis of humans, animals, and environmental compartments exposed to PFAS: A systematic evidence map and bibliometric analysis of secondary literature.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are a class of widely used anthropogenic chemicals. Concerns regarding their persistence and potential adverse effects have led to multiple secondary research publications. Here, we aim to assess the resulting evidence base in the systematic secondary literature by examining research gaps, evaluating the quality of reviews, and exploring interdisciplinary connections. METHODS: This study employed a systematic evidence-mapping approach to assess the secondary literature on the biological, environmental, and medical aspects of exposure to 35 fluorinated compounds. The inclusion criteria encompassed systematic reviews published in peer-reviewed journals, pre-prints, and theses. Comprehensive searches across electronic databases and grey literature identified relevant reviews. Data extraction and synthesis involved mapping literature content and narrative descriptions. We employed a modified version of the AMSTAR2 checklist to evaluate the methodological rigour of the reviews. A bibliometric data analysis uncovered patterns and trends in the academic literature. A research protocol for this study was previously pre-registered (osf.io/2tpn8) and published (Vendl et al., Environment International 158 (2022) 106973). The database is freely accessible through the interactive and user-friendly web application of this systematic evidence map at https://hi-this-is-lorenzo.shinyapps.io/PFAS_SEM_Shiny_App/. RESULTS: Our map includes a total of 175 systematic reviews. Over the years, there has been a steady increase in the annual number of publications, with a notable surge in 2021. Most reviews focused on human exposure, whereas environmental and animal-related reviews were fewer and often lacked a rigorous systematic approach to literature search and screening. Review outcomes were predominantly associated with human health, particularly with reproductive and children's developmental health. Animal reviews primarily focused on studies conducted in controlled laboratory settings, and wildlife reviews were characterised by an over-representation of birds and fish species. Recent reviews increasingly incorporated quantitative synthesis methodologies. The methodological strengths of the reviews included detailed descriptions of study selection processes and disclosure of potential conflicts of interest. However, weaknesses were observed in the critical lack of detail in reporting methods. A bibliometric analysis revealed that the most productive authors collaborate within their own country, leading to limited and clustered international collaborations. CONCLUSIONS: In this overview of the available systematic secondary literature, we map literature content, assess reviews' methodological quality, highlight data gaps, and draw research network clusters. We aim to facilitate literature reviews, guide future research initiatives, and enhance opportunities for cross-country collaboration. Furthermore, we discuss how this systematic evidence map and its publicly available database benefit scientists, regulatory agencies, and other stakeholders by providing access to current systematic secondary literature on PFAS exposure.

Bibliometrics↗

PubMed2026

Journey Mapping of the Patient Experience from Diagnosis to End of Life in Lung Cancer: A Qualitative Meta-Synthesis.

OBJECTIVES: This study aimed to systematically synthesize the lived experiences and journey narratives of lung cancer patients across disease stages, and identify key tasks and pain points during the disease course through patient journey mapping, providing evidence for comprehensive disease management throughout the patient journey. METHODS: Ten databases, including PubMed, Embase, Web of Science, Scopus, PsycINFO, CINAHL, Cochrane Library, CNKI, Wanfang, and SinoMed, were systematically searched, with a search period from database inception to August 15, 2025. The JBI Critical Appraisal Tool for qualitative studies was used to evaluate the quality of studies, and the results were integrated using a meta-aggregative approach. RESULTS: Thirteen studies were included. Based on the patient journey mapping, the lung cancer patient journey comprises four potential stages: evaluation and diagnosis, initial treatment, maintenance therapy, and end-of-life. A total of 30 themes emerged within three dimensions: tasks, emotions, and pain points. Each dimension of each stage consists of 2-3 themes. CONCLUSION: The journey of lung cancer patients is protracted and complex, characterized by stage-specific needs and challenges. Future management strategies should be tailored to these distinct phases, providing precision supportive care to optimize treatment outcomes and enhance patients' quality of life. IMPLICATIONS FOR NURSING PRACTICE: This Patient Journey Map integrates routine clinical pathways with patients' lived experiences across each stage, revealing stage-specific challenges and providing targets for tailored nursing interventions. The framework promotes multidisciplinary, digitally enabled supportive care and indicates the importance of including patients' social circles to enhance patient-centered outcomes.

Humans↗

PubMed2026

Analysis of deep-resequencing data of 984 soybean accessions reveals structural variations underlying agronomic traits.

Genomic structural variants (SVs) are major sources of genetic variation and have profound impacts on phenotypic traits. However, their functional effects remain largely unexplored in soybean. Here, we resequence 940 soybean accessions. Together with 44 publicly available datasets, we identify 602,281 SVs. Using a graph-based genome, we detect an additional 58,760 presence/absence variations (PAVs) that broadly affect gene expression. Population genomic analyses reveal that SVs serve as a core driving force for soybean domestication and improvement. Integrating SVs with QTLs for oil and protein content, and performing GWAS on 27 traits, we identify key functional SVs. These include transposable element insertions altering seed coat color, multiple insertions within a cytochrome P450 gene modifying flower and hypocotyl color, and a GmMATE1 deletion enhancing seed size. Together, our study establishes a comprehensive SV map of soybean, offering a valuable resource for dissecting the genetic basis of complex traits to accelerate molecular breeding.

Glycine max↗

PubMed2026

Transposable element-driven expansion of enhancer RNA repertoires underlies regulatory innovation and polyploid adaptation in cereal crops.

Cereal genomes have undergone repeated polyploidization and transposable element (TE) proliferation, collectively generating complex regulatory landscapes. However, the evolutionary trajectories and functional implications of these landscapes remain largely unexplored. Using chromatin-bound RNA sequencing across seven cereal species, we systematically mapped 45,952 regulatory element transcripts (RETs), including 32,867 distal RETs corresponding to enhancer RNAs (eRNAs). Our analysis revealed that 56% of lineage-specific eRNAs originated from TE expansions, indicating that TEs serve as major reservoirs of species-specific regulatory innovation in cereals. Notably, we identified remarkable conservation in defense-related functions, root-specific expression, and TE-derived origins of eRNAs across both ancient and recent evolutionary layers of Triticeae, suggesting recurrent recruitment of TE-derived, root-associated regulatory elements throughout Triticeae evolution. Furthermore, we found that young eRNA pairs in hexaploid wheat with high sequence similarity, many originating from RLG_famc8.3 and DTC_famc4.3, exhibited pronounced root specificity and coordinated expression, suggesting targeted amplification and refinement of successful ancestral regulatory strategies established after Triticeae divergence. To facilitate community access, we developed Cereal-eRNAdb (http://bioinfo.cemps.ac.cn/Cereal-eRNAdb/), a comprehensive database integrating 69,426 eRNAs with functional annotations across 296 samples. Our findings suggest that TE-mediated innovation of root-specific eRNAs may contribute to Triticeae adaptation and provide a foundational resource for exploiting regulatory variation in cereal crop breeding.

Enhancer RNAs↗

PubMed2025

dbscATAC: a resource of single-cell super-enhancers/enhancers and gene markers derived from scATAC-seq data.

MOTIVATION: scATAC-seq enables high-resolution mapping of cis-regulatory elements. It has been widely applied to uncover cell-type-specific regulatory networks and complement scRNA-seq analysis in numerous studies. However, a large number of datasets generated by scATAC-seq remain underutilized due to limited exploration of super-enhancers/typical enhancers and gene markers. A comprehensive resource enabling cell-type-specific annotation of cis-regulatory elements and their dynamic enhancer-gene linkages remains an urgent unmet need for scATAC-seq. RESULTS: We present dbscATAC, a specialized single-cell database for annotating super-enhancers, gene markers, and enhancer-gene interactions derived from scATAC-seq data. Using improved machine learning algorithms, we identified 213 835 super-enhancers across 520 tissue/cell types from three species, as well as 347 484 gene markers, 13 470 526 enhancers, and 10 402 346 enhancer-gene interactions derived from 1 668 076 single cells spanning 1028 tissue/cell types in 13 species. An easy-to-use online platform with multiple analytic modules and hierarchical query options was developed for searching, browsing and visualizing single-cell super-enhancers, enhancers, and gene markers. dbscATAC provides a comprehensive resource to facilitate the exploration of enhancer landscapes, gene regulation, and cell-type-specific characteristics in single-cell epigenomics. AVAILABILITY AND IMPLEMENTATION: The database with all the super-enhancer/enhancer annotation data is available at http://singlecelldb.com/dbscATAC/index.php. And the source code of dbscATAC for prediction of SEs, enhancers, and gene markers are available at https://github.com/EvansGao/dbscATAC. The source code, tissue/cell type description, and data summary can be downloaded at DOI: 10.6084/m9.figshare.28706414.scATAC-seq, Database, Super-enhancers/enhancers, Gene markers.

Enhancer Elements, Genetic↗

PubMed2025

Multidimensional OMICs reveal ARID1A orchestrated control of DNA damage, splicing, and cell cycle in normal-like and malignant urothelial cells.

Epigenetic regulators, such as the SWI/SNF complex, with important roles in tissue development and homeostasis, are frequently mutated in cancer. ARID1A, a subunit of the SWI/SNF complex, is mutated in approximately 20% of all bladder tumors; however, the consequences of this remain poorly understood. Finding truncations to be the most common mutation, we generated loss- and gain-of-function models to conduct RNA-Seq, interactome analyses, Omni-ATAC-Seq, and functional studies to characterize ARID1A-affected pathways potentially suitable for the treatment of ARID1A-deficient bladder cancers. We observed decreased cell proliferation and deregulation of stress-regulated pathways, including DNA repair, in ARID1A-deficient cells. Furthermore, ARID1A was linked to alternative splicing and translational regulation on RNA and interactome levels. ARID1A deficiency drastically reduced the accessibility of chromatin, especially around introns and distal enhancers, in a functional enrichment analysis. Less accessible chromatin areas were mapped to pathways such as cell proliferation and DNA damage response. Indeed, the G2/M checkpoint appeared impaired after DNA damage in ARID1A-deficient cells. Together, our data highlight the broad impact of ARID1A loss and the possibility of targeting proliferative and DNA repair pathways for treatment.

Transcription Factors↗

PubMed2027

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗

PubMed2014

Epigenomic analysis of primary human T cells reveals enhancers associated with TH2 memory cell differentiation and asthma susceptibility.

A characteristic feature of asthma is the aberrant accumulation, differentiation or function of memory CD4(+) T cells that produce type 2 cytokines (TH2 cells). By mapping genome-wide histone modification profiles for subsets of T cells isolated from peripheral blood of healthy and asthmatic individuals, we identified enhancers with known and potential roles in the normal differentiation of human TH1 cells and TH2 cells. We discovered disease-specific enhancers in T cells that differ between healthy and asthmatic individuals. Enhancers that gained the histone H3 Lys4 dimethyl (H3K4me2) mark during TH2 cell development showed the highest enrichment for asthma-associated single nucleotide polymorphisms (SNPs), which supported a pathogenic role for TH2 cells in asthma. In silico analysis of cell-specific enhancers revealed transcription factors, microRNAs and genes potentially linked to human TH2 cell differentiation. Our results establish the feasibility and utility of enhancer profiling in well-defined populations of specialized cell types involved in disease pathogenesis.

Adolescent↗

PubMed2026

Diffusion MRI radiomics in meningiomas: imaging correlates of tumor grade and intraoperative consistency.

OBJECTIVE: Despite advancements in imaging studies, the preoperative prediction of the biological behavior and intraoperative consistency of intracranial meningiomas remains limited. This study evaluated the association of volumetric diffusion-based and texture-derived radiomic features extracted from routine MRI with histopathological aggressiveness and intraoperative tumor consistency. METHODS: Ninety-seven intracranial meningiomas resected at two tertiary centers were retrospectively analyzed. Volumetric segmentation was performed on contrast-enhanced T1-weighted MRI and coregistered to apparent diffusion coefficient (ADC) maps. Data on first-order diffusion metrics and selected texture features were collected. The associations between World Health Organization (WHO) grade and Ki-67 index were assessed using nonparametric tests and Spearman correlation analysis. Independent factors associated with intraoperative tumor consistency (Zada grades 1-5) were evaluated via multivariate ordinal logistic regression analysis that adjusted for tumor volume, skull base location, calcification status, and WHO grade. Secondary receiver operating characteristic (ROC) curve analyses were performed to differentiate solid (Zada grades 4-5) from soft (Zada grades 1-2) tumors. ROC analyses were performed within the study cohort and were intended as exploratory assessments of discriminative performance. RESULTS: The mean ADC (ADCmean) and the 10th percentile of the ADC decreased significantly with increasing WHO grade (p < 0.001). ADCmean had a moderate inverse correlation with the Ki-67 index (r = -0.42, p < 0.001) and intraoperative tumor consistency (r = -0.45, p < 0.001). In the multivariate analysis, the ADCmean remained independently associated with increasing tumor firmness. Each 0.1 × 10-3 mm2/sec increase corresponded to a 38% reduction in the odds of belonging to a higher consistency category (OR 0.62, 95% CI 0.51-0.74, p < 0.001). The ROC analysis showed good discrimination for solid tumors (area under the curve 0.847, 95% CI 0.742-0.953) and soft tumors (area under the curve 0.824, 95% CI 0.714-0.935). Texture features had weaker associations with intraoperative tumor consistency. CONCLUSIONS: Volumetric diffusion-derived metrics, particularly ADCmean, are associated with both histopathological aggressiveness and intraoperative tumor firmness in meningiomas. Diffusion imaging may reflect a graded microstructural continuum rather than a purely dichotomous property, providing complementary preoperative insights into surgical complexity.

Humans↗

PubMed2026

Survival prediction for clear cell renal cell carcinoma based on deep multimodal synergistic survival network.

Objective.To propose a deep multimodal synergistic survival analysis framework (Deep Multimodal Synergistic Survival Network, DMSSN) to achieve accurate prognostic analysis for clear cell renal cell carcinoma (ccRCC).Methods.This study (DMSSN) utilized matched multimodal data from the Cancer Genome Atlas-KIRC database, including CT imaging data, whole slide images, copy number variation (CNV) features, and clinical data. Deep Canonical Correlation Analysis was employed to map heterogeneous modalities into a shared latent space. Contrastive learning was introduced to enhance semantic consistency across multimodal features, and a gating network was utilized for the adaptive fusion of multimodal information to achieve precise survival risk prediction for patients.Results.Experimental results demonstrated that DMSSN achieved a Concordance Index (C-index) of 0.8153 ± 0.0994, with a Log-rank testp-value of 1.6553×10-11. DMSSN exhibited significant performance advantages over traditional statistical methods like Log-rank-Cox (0.7055 ± 0.0670) and machine learning methods such as Random Survival Forest (RSF) (0.6836 ± 0.1048). Furthermore, in comparison with similar deep learning approaches, DMSSN outperformed late fusion strategies (0.7493 ± 0.1211) and discrete-time survival models such as DeepHit (0.7655 ± 0.1041) and Nnet-surv (0.7694 ± 0.0635). Notably, DMSSN still achieved the best predictive performance when compared to the classic deep survival model DeepSurv (0.7919 ± 0.0978) and advanced state-of-the-art multimodal fusion frameworks like Context-Aware Transformer (0.7735 ± 0.0818) and Multimodal Co-Attention Transformer (0.8102 ± 0.0972). Ablation studies showed that removing any single modality led to a decline in performance, with the largest numerical decrease occurring after removing CT imaging features (C-index decreased to 0.7327), validating the complementarity of multimodal data and the pivotal role of radiomic features in prognostic assessment. Module ablation experiments further confirmed the effectiveness of the core components.Conclusion:By effectively integrating imaging, pathology, genomic, and clinical features, the DMSSN framework demonstrates superior performance and robustness in the survival prediction of ccRCC.

Carcinoma, Renal Cell↗

PubMed2025

The Fire Ant Social Chromosome Exerts a Major Influence on Genome Regulation.

Supergenes underlying complex trait polymorphisms ensure that sets of coadapted alleles remain genetically linked. Despite their prevalence in nature, the mechanisms of supergene effects on genome regulation are poorly understood. In the fire ant Solenopsis invicta, a supergene containing over 500 individual genes influences trait variation in multiple castes to collectively underpin a colony level social polymorphism. Here, we present results of an integrative investigation of supergene effects on gene regulation. We present analyses of ATAC-seq data to investigate variation in chromatin accessibility by supergene genotype and STARR-seq data to characterize enhancer activity by supergene haplotype. Integration with gene co-expression analyses, newly mapped intact transposable elements (TEs), and previously identified copy number variants (CNVs) collectively reveals widespread effects of the supergene on chromatin structure, gene transcription, and regulatory element activity, with a genome-wide bias for open chromatin and increased expression in the presence of the derived supergene haplotype, particularly in regions that harbor intact TEs. Integrated consideration of CNVs and regulatory element divergence suggests each evolved in concert to shape the expression of supergene encoded factors, including several transcription factors that may directly contribute to the trans-regulatory footprint of a heteromorphic social chromosome. Overall, we show how genome structure in the form of a supergene has wide-reaching effects on gene regulation and gene expression.

Animals↗