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Results for “epigenomics”

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PubMed2026

3D epigenomic remodelling mediated by Foxa1 drives gemcitabine resistance in pancreatic cancer.

Gemcitabine remains a cornerstone treatment for pancreatic ductal adenocarcinoma (PDAC), yet the emergence of resistance constitutes a major clinical challenge with poorly understood epigenomic mechanisms. Here, we identified the pioneer transcription factor Foxa1 as a master regulator of gemcitabine resistance through multi-omics analysis. Mechanistically, Foxa1 drives widespread super-enhancer (SE) reprogramming and 3D genome remodelling in resistant cells, which coordinately activates the expression of key resistance genes, notably Rrm1 and Cdadc1. This is accompanied by increased chromatin accessibility, elevated H3K27ac enrichment at SEs, and enhanced Foxa1 binding at regulatory elements. Moreover, post-translational stabilization of Foxa1 via USP7-mediated deubiquitination sustains this epigenomic program. Genetic ablation of Foxa1 or specific SE regions near Rrm1 resensitizes resistant cells to gemcitabine. Building upon this mechanism, we demonstrate that bromodomain and extraterminal (BET) inhibitors, which disrupt SE function, potently reverse resistance. Notably, the clinical-stage BET inhibitor AZD5153, in combination with gemcitabine, achieves robust tumor suppression and overcomes resistance in cell-derived xenograft (CDX) models by dismantling the Foxa1-mediated resistant transcriptome and reinvigorating drug sensitivity. Our findings establish Foxa1-orchestrated enhancer reprogramming as a fundamental mechanism of gemcitabine resistance and unveil a promising epigenetic therapy to restore treatment efficacy in PDAC.

Hepatocyte Nuclear Factor 3-alpha↗

PubMed2025

Methylation patterns of the nasal epigenome of hospitalized SARS-CoV-2 positive patients reveal insights into molecular mechanisms of COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has varied presentations from asymptomatic to death. Efforts to identify factors responsible for differential COVID-19 severity include but are not limited to genome wide association studies (GWAS) and transcriptomic analysis. More recently, variability in host epigenomic profiles have garnered attention, providing links to disease severity. However, whole epigenome analysis of the respiratory tract, the target tissue of SARS-CoV-2, remains ill-defined. RESULTS: We interrogated the nasal methylome to identify pathophysiologic drivers in COVID-19 severity through whole genome bisulfite sequencing (WGBS) of nasal samples from COVID-19 positive individuals with severe and mild presentation of disease. We noted differential DNA methylation in intergenic regions and low methylated regions (LMRs), demonstrating the importance of distal regulatory elements in gene regulation in COVID-19 illness. Additionally, we demonstrated differential methylation of pathways implicated in immune cell recruitment and function, and the inflammatory response. We found significant hypermethylation of the FUT4 promoter implicating impaired neutrophil adhesion in severe disease. We also identified hypermethylation of ELF5 binding sites suggesting downregulation of ELF5 targets in the nasal cavity as a factor in COVID-19 phenotypic variability. CONCLUSIONS: This study demonstrated DNA methylation as a marker of the immune response to SARS-CoV-2 infection, with enhancer-like elements playing significant roles. It is difficult to discern whether this differential methylation is a predisposing factor to severe COVID-19, or if methylation differences occur in response to disease severity. These differences in the nasal methylome may contribute to disease severity, or conversely, the nasal immune system may respond to severe infection through differential immune cell recruitment and immune function, and through differential regulation of the inflammatory response.

Humans↗

PubMed2003

Epigenomic replication: linking epigenetics to DNA replication.

The information contained within the linear sequence of bases (the genome) must be faithfully replicated in each cell cycle, with a balance of constancy and variation taking place over the course of evolution. Recently, it has become clear that additional information important for genetic regulation is contained within the chromatin proteins associated with DNA (the epigenome). Epigenetic information also must be faithfully duplicated in each cell cycle, with a balance of constancy and variation taking place during the course of development to achieve differentiation while maintaining identity within cell lineages. Both the genome and the epigenome are synthesized at the replication fork, so the events occurring during S-phase provide a critical window of opportunity for eliciting change or maintaining existing genetic states. Cells discriminate between different states of chromatin through the activities of proteins that selectively modify the structure of chromatin. Several recent studies report the localization of certain chromatin modifying proteins to replication forks at specific times during S-phase. Since transcriptionally active and inactive chromosome domains generally replicate at different times during S-phase, this spatiotemporal regulation of chromatin assembly proteins may be an integral part of epigenetic inheritance.

Animals↗

PubMed2026

Epigenome-wide placental methylation landscapes in relation to antenatal depressive symptoms.

Antenatal depressive symptoms (ADS) are common during pregnancy and are linked to adverse maternal and offspring neurodevelopmental outcomes. The placenta plays a central role in maternal-fetal communication and may function as an epigenetic sensor of maternal psychological stress. However, placental epigenetic signatures associated with ADS remain poorly understood. This study investigated epigenome-wide placental DNA methylation patterns associated with ADS in an Indian cohort. Placental samples were collected at delivery from women recruited in early pregnancy into the STRiDE cohort. Depressive symptoms were assessed at 24-28 weeks' gestation using the Patient Health Questionnaire-9 (PHQ-9). Participants were classified as controls (PHQ-9 ≤ 4; n = 53) or ADS (PHQ-9 > 4; n = 54). Genome-wide DNA methylation profiling was performed using the Illumina Infinium MethylationEPIC array. Epigenome-wide association analysis identified no CpG sites that remained statistically significant after Benjamini-Hochberg FDR correction. Top nominal CpGs showed medium-to-large effect sizes for ADS. Exploratory analyses of the top nominally associated CpGs annotated to genes including TAP2, LRCH1, SLITRK2, RASSF1 and IL3 implicated in immune regulation, cellular signalling and neurodevelopment. Gene enrichment analysis suggested the involvement of biological processes and pathways related to synaptic organization, ion transport, Hippo signalling, and thyroid hormone regulation. In conclusion, the study findings provide preliminary evidence of DNA methylation signatures linked to potential candidate genes and biological pathways that may be relevant to ADS, supporting the need for validation in larger independent cohorts and functional experimental studies.

Asian Indians↗

PubMed2004

Semirandom sampling to detect differentiation-related and age-related epigenome remodeling.

With completion of the human genome project, patterns of higher order chromatin structure can be easily related to other features of genome organization. A well-studied aspect of chromatin, histone H4 acetylation, is examined here on the basis of its role in setting competence for gene activation. Three applications of a new hybrid genome sampling-chromatin immunoprecipitation strategy are described. The first explores aspects of epigenome architecture in human fibroblasts. A second focuses on chromatin from HL-60 promyelocytic leukemia cells before and after differentiation into macrophage-like cells. A third application explores age-related epigenome change. In the latter, acetylation patterns are compared in human skin fibroblast chromatin from donors of various ages. Two sites are reported at which observed histone H4 acetylation differences suggest decreasing acetylation over time. The sites, located in chromosome 4p16.1 and 4q35.2 regions, appear to remodel during late fetal-early child development and from preadolescence through adult life, respectively.

Acetylation↗

PubMed2005

The Genome Health Clinic and Genome Health Nutrigenomics concepts: diagnosis and nutritional treatment of genome and epigenome damage on an individual basis.

The evidence of a direct link between increased genome/epigenome damage and elevated risk for adverse health outcomes during the various stages of life, such as infertility, foetal development and cancer is becoming increasingly stronger. The latter is briefly reviewed against a background of evidence indicating that genome and epigenome damage biomarkers, in the absence of overt exposure of genotoxins, are themselves sensitive indicators of deficiency in micronutrients required as cofactors or as components of DNA repair enzymes, for maintenance methylation of CpG sequences and prevention of DNA oxidation and/or uracil incorporation into DNA. The latter is illustrated with cross-sectional and dietary intervention data obtained using the micronucleus assay and other efficient biomarkers for diagnosing genome and/or epigenome instability. The concept of recommended dietary allowances for genome stability and how this could be achieved is discussed. The 'Genome Health Nutrigenomics' concept is also introduced to define and focus attention on the specialized research area of how diet impacts on genome stability and how genotype determines nutritional requirements for genome health maintenance. The review concludes with a vision for a paradigm shift in disease prevention strategy based on the diagnosis and nutritional treatment of genome/epigenome damage on an individual basis, i.e. The Genome Health Clinic.

Concept Formation↗

PubMed2004

DNA methylation profiling of the human major histocompatibility complex: a pilot study for the human epigenome project.

The Human Epigenome Project aims to identify, catalogue, and interpret genome-wide DNA methylation phenomena. Occurring naturally on cytosine bases at cytosine-guanine dinucleotides, DNA methylation is intimately involved in diverse biological processes and the aetiology of many diseases. Differentially methylated cytosines give rise to distinct profiles, thought to be specific for gene activity, tissue type, and disease state. The identification of such methylation variable positions will significantly improve our understanding of genome biology and our ability to diagnose disease. Here, we report the results of the pilot study for the Human Epigenome Project entailing the methylation analysis of the human major histocompatibility complex. This study involved the development of an integrated pipeline for high-throughput methylation analysis using bisulphite DNA sequencing, discovery of methylation variable positions, epigenotyping by matrix-assisted laser desorption/ionisation mass spectrometry, and development of an integrated public database available at http://www.epigenome.org. Our analysis of DNA methylation levels within the major histocompatibility complex, including regulatory exonic and intronic regions associated with 90 genes in multiple tissues and individuals, reveals a bimodal distribution of methylation profiles (i.e., the vast majority of the analysed regions were either hypo- or hypermethylated), tissue specificity, inter-individual variation, and correlation with independent gene expression data.

CpG Islands↗

PubMed2004

Future potential of the Human Epigenome Project.

Deciphering the information encoded in the human genome is key for the further understanding of human biology, physiology and evolution. With the draft sequence of the human genome completed, elucidation of the epigenetic information layer of the human genome becomes accessible. Epigenetic mechanisms are mediated by either chemical modifications of the DNA itself or by modifications of proteins that are closely associated with DNA. Defects of the epigenetic regulation involved in processes such as imprinting, X chromosome inactivation, transcriptional control of genes, as well as mutations affecting DNA methylation enzymes, contribute fundamentally to the etiology of many human diseases. Headed by the Human Epigenome Consortium, the Human Epigenome Project is a joint effort by an international collaboration that aims to identify, catalog and interpret genome-wide DNA methylation patterns of all human genes in all major tissues. Methylation variable positions are thought to reflect gene activity, tissue type and disease state, and are useful epigenetic markers revealing the dynamic state of the genome. Like single nucleotide polymorphisms, methylation variable positions will greatly advance our ability to elucidate and diagnose the molecular basis of human diseases.

CpG Islands↗

PubMed2025

Activation of the imprinted Prader-Willi syndrome locus by CRISPR-based epigenome editing.

Epigenome editing with DNA-targeting technologies such as CRISPR-dCas9 can be used to dissect gene regulatory mechanisms and potentially treat associated disorders. For example, Prader-Willi syndrome (PWS) results from loss of paternally expressed imprinted genes on chromosome 15q11.2-q13.3, although the maternal allele is intact but epigenetically silenced. Using CRISPR repression and activation screens in human induced pluripotent stem cells (iPSCs), we identified genomic elements that control the expression of the PWS gene SNRPN from the paternal and maternal chromosomes. We showed that either targeted transcriptional activation or DNA demethylation can activate the silenced maternal SNRPN and downstream PWS transcripts. However, these two approaches function at unique regions, preferentially activating different transcript variants and involving distinct epigenetic reprogramming mechanisms. Remarkably, transient expression of the targeted demethylase leads to stable, long-term maternal SNRPN expression in PWS iPSCs. This work uncovers targeted epigenetic manipulations to reprogram a disease-associated imprinted locus and suggests possible therapeutic interventions.

Prader-Willi Syndrome↗

PubMed2025

CRISPR tools for T cells: targeting the genome, epigenome, and transcriptome.

T cell therapy has curative potential for many cancers. Despite impressive clinical efficacy in hematological malignancies, current T cell therapy still faces challenges related to sustaining responses, antigen escape, cytotoxicity, limited accessibility, and difficulties in treating solid tumors. The advent of CRISPR (clustered regularly interspaced short palindromic repeats) technologies provides a promising solution to these challenges. CRISPR technologies have grown from merely tools for gene knockout to sophisticated tools that can engineer cells at various levels of the genome, epigenome, and transcriptome. In this review we discuss recent technological advancements and how their application to T cells has the potential to steer the next generation of cellular therapy. We highlight emerging applications and current technological limitations that future tool development aims to overcome.

Humans↗

PubMed2026

Novel epigenetic loci identified from an epigenome-wide association study underlying brain structural changes in bipolar disorder.

BACKGROUND: DNA methylation influences gene-environment interactions and brain development in bipolar disorder (BD). We aimed to identify BD-associated epigenetic loci and examine their associations with brain structural variation. METHODS: We conducted an epigenome-wide association study (BD group, n = 90; healthy controls group, n = 161) to identify BD-associated DNA methylation loci, and we additionally performed copy number alteration and functional enrichment analyses. The correlations between epigenetic loci and cortical thickness (CT) were assessed using Pearson's partial correlation analysis, and the co-methylation effect of the epigenetic loci identified in the neuroimaging-epigenetic analysis was investigated. FINDINGS: A total of 156 differentially methylated positions (DMPs) and 7 differentially methylated regions were identified, and the genes associated with them were observed to be enriched in biological processes related to muscle hypertrophy and neuronal activity. Significant correlations between the methylation levels of 13 DMPs associated with three genes (miR886, PLEC1, and ICAM5) and the CT of the right postcentral gyrus and inferior frontal gyrus were identified. Specifically, 10 DMPs associated with the CpG island in the upstream region of the miR886 gene showed negative correlations with the right postcentral gyrus CT, implicating miR886-associated CpG-island methylation in regional cortical thinning. CONCLUSION: Epigenetic changes might play an important role in brain structural changes in BD. These multimodal findings nominate miR886-related methylation as a candidate molecular correlate of cortical thinning and warrant replication and mechanistic follow-up in larger, state-diverse cohorts.

Humans↗

PubMed2026

Estimating population structure using epigenome-wide methylation data.

Population stratification is one of the source of inflation in epigenome-wide association studies (EWAS) when not properly accounted for. To address this, we developed methylation population scores (MPSs) to predict genetic principal components (GPCs) using a feature selection approach. We used multi-ethnic DNA methylation data from Illumina EPIC arrays across five cohorts, including MESA (n = 929), CARDIA (n = 1123), JHS (n = 1365), ARIC (n = 2338), and HCHS/SOL (n = 1475), randomly splitting participants into training (85%) and test (15%) sets. Within each cohort, associations between GPCs and CpG sites were estimated using linear regression adjusting for age, sex, smoking and alcohol use, race/ethnicity, body mass index, and cell type proportions, followed by meta-analysis and selection of CpGs with FDR <0.05. We then applied a two-stage weighted least squares Lasso regression to construct MPSs, adjusting for the aforementioned covariates. In the test dataset, MPSs showed strong correlation with GPCs, with R² ranging from 0.27 (MPS7 vs. GPC7) to 0.98 (MPS1 vs. GPC1). Visualization demonstrated that MPSs recapitulated the pattern shown by GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups and outperformed methylation-based principal components constructed using alternative published methods. Additionally, MPSs showed comparable performance to GPCs in reducing inflation in EWAS. Overall, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations, and provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent.

Humans↗

PubMed2025

Detection of cell-type-specific differentially methylated regions in epigenome-wide association studies.

MOTIVATION: DNA methylation at cytosine-phosphate-guanine (CpG) sites is one of the most important epigenetic markers. Therefore, epidemiologists are interested in investigating DNA methylation in large cohorts through epigenome-wide association studies (EWAS). However, the observed EWAS data are bulk data with signals aggregated from distinct cell types. Deconvolution of cell-type-specific signals from EWAS data is challenging because phenotypes can affect both cell-type proportions and cell-type-specific methylation levels. Recently, there has been active research on detecting cell-type-specific risk CpG sites for EWAS data. However, existing methods all assume that the methylation levels of different CpG sites are independent and perform association detection for each CpG site separately. Although these methods significantly improve the detection at the aggregated-level-identifying a CpG site as a risk CpG site as long as it is associated with the phenotype in any cell type, they have low power in detecting cell-type-specific associations for EWAS with typical sample sizes. RESULTS: Here, we develop a new method, Fine-scale inference for Differentially Methylated Regions (FineDMR), to borrow strengths of nearby CpG sites to improve the cell-type-specific association detection. Via a Bayesian hierarchical model built upon Gaussian process functional regression, FineDMR takes advantage of the spatial dependencies between CpG sites. FineDMR can provide cell-type-specific association detection as well as output subject-specific and cell-type-specific methylation profiles for each subject. Simulation studies and real data analysis show that FineDMR substantially improves the power in detecting cell-type-specific associations for EWAS data. AVAILABILITY AND IMPLEMENTATION: FineDMR is freely available at https://github.com/JiaRuofan/Detection-of-Cell-type-specific-DMRs-in-EWAS.

DNA Methylation↗

PubMed2024

Epigenome-wide Association Study Shows Differential DNA Methylation of MDC1, KLF9, and CUTA in Autoimmune Thyroid Disease.

CONTEXT: Autoimmune thyroid disease (AITD) includes Graves disease (GD) and Hashimoto disease (HD), which often run in the same family. AITD etiology is incompletely understood: Genetic factors may account for up to 75% of phenotypic variance, whereas epigenetic effects (including DNA methylation [DNAm]) may contribute to the remaining variance (eg, why some individuals develop GD and others HD). OBJECTIVE: This work aimed to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs) comparing GD to HD. METHODS: Whole-blood DNAm was measured across the genome using the Infinium MethylationEPIC array in 32 Australian patients with GD and 30 with HD (discovery cohort) and 32 Danish patients with GD and 32 with HD (replication cohort). Linear mixed models were used to test for differences in quantile-normalized β values of DNAm between GD and HD and data were later meta-analyzed. Comb-p software was used to identify DMRs. RESULTS: We identified epigenome-wide significant differences (P < 9E-8) and replicated (P < .05) 2 DMPs between GD and HD (cg06315208 within MDC1 and cg00049440 within KLF9). We identified and replicated a DMR within CUTA (5 CpGs at 6p21.32). We also identified 64 DMPs and 137 DMRs in the meta-analysis. CONCLUSION: Our study reveals differences in DNAm between GD and HD, which may help explain why some people develop GD and others HD and provide a link to environmental risk factors. Additional research is needed to advance understanding of the role of DNAm in AITD and investigate its prognostic and therapeutic potential.

Humans↗

PubMed2024

An epigenome-wide study of selenium status and DNA methylation in the Strong Heart Study.

BACKGROUND: Selenium (Se) is an essential nutrient linked to adverse health endpoints at low and high levels. The mechanisms behind these relationships remain unclear and there is a need to further understand the epigenetic impacts of Se and their relationship to disease. We investigated the association between urinary Se levels and DNA methylation (DNAm) in the Strong Heart Study (SHS), a prospective study of cardiovascular disease (CVD) among American Indians adults. METHODS: Selenium concentrations were measured in urine (collected in 1989-1991) using inductively coupled plasma mass spectrometry among 1,357 participants free of CVD and diabetes. DNAm in whole blood was measured cross-sectionally using the Illumina MethylationEPIC BeadChip (850 K) Array. We used epigenome-wide robust linear regressions and elastic net to identify differentially methylated cytosine-guanine dinucleotide (CpG) sites associated with urinary Se levels. RESULTS: The mean (standard deviation) urinary Se concentration was 51.8 (25.1) μg/g creatinine. Across 788,368 CpG sites, five differentially methylated positions (DMP) (hypermethylated: cg00163554, cg18212762, cg11270656, and hypomethylated: cg25194720, cg00886293) were significantly associated with Se in linear regressions after accounting for multiple comparisons (false discovery rate p-value: 0.10). The top hypermethylated DMP (cg00163554) was annotated to the Disco Interacting Protein 2 Homolog C (DIP2C) gene, which relates to transcription factor binding. Elastic net models selected 425 hypo- and hyper-methylated DMPs associated with urinary Se, including three sites (cg00163554 [DIP2C], cg18212762 [MAP4K2], cg11270656 [GPIHBP1]) identified in linear regressions. CONCLUSIONS: Urinary Se was associated with minimal changes in DNAm in adults from American Indian communities across the Southwest and the Great Plains in the United States, suggesting that other mechanisms may be driving health impacts. Future analyses should explore other mechanistic biomarkers in human populations, determine these relationships prospectively, and investigate the potential role of differentially methylated sites with disease endpoints.

Humans↗

PubMed2025

Development and validation of a machine learning prognostic model based on an epigenomic signature in patients with pancreatic ductal adenocarcinoma.

BACKGROUND: 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. MATERIALS AND METHODS: We analyzed CpG sites from two publicly available datasets, the TCGA-PAAD used as discovery set and the CPTAC-PDA as external test set. Single mutations and co-mutation of KRAS and TP53 genes were identified as targets, and differentially methylated CpG sites (DMC) were detected accordingly. We trained and validated Random Forest (RF) models to predict each target. Area Under the Receiver Operating Characteristic curve (AUROC) and Area Under the Precision-Recall curve (AUPRC) were used as performance metrics. Then, we performed consensus clustering from the DMCs to identify novel patients' profiles. Finally, we trained and validated a combination of eXtreme Gradient Boosting (XGB) and tree models to select an epigenomic prognostic determinant. RESULTS: From 598 DMCs extracted, an RF model predicted KRAS and TP53 co-mutation on the external test set with AUROC of 0.77 and AUPRC of 0.87. The consensus clustering allowed us to identify 4 clusters (C1, C2, C3, and C4) of patients. The C4 cluster captured a subgroup of patients with favorable Overall Survival (OS) with respect to others. The XGB model perfectly predicted C4 vs other clusters on the discovery set. In both cohorts, patients were stratified into two risk groups according to methylation levels of cg16854533, individuated as the most important CpG site. CONCLUSION: We analyzed methylation data to develop a classifier for the TP53 and KRAS mutational status. Four prognostic clusters were pointed out and a prognostic model using a CpG site was validated in an independent cohort. Our results evidence that the proposed use of methylation data facilitates risk stratification for PDAC.

Humans↗

PubMed2026

Nanopore-based epigenomic profiling reveals the absence of widespread CpG methylation in the African swine fever virus genome.

DNA methylation is a critical epigenetic mechanism implicated in regulating replication and transcription in DNA viruses. However, the epigenetic landscape of African swine fever virus (ASFV), a large double-stranded DNA virus infecting pigs, remains controversial. Here, we systematically profiled the DNA methylome of the first ASFV strain isolated in Hong Kong (HK_NT_202103) using Oxford Nanopore Technologies (ONT) R10.4.1 sequencing. We employed a paired design: native whole-genome sequencing (WGS) against a methylation-free whole-genome amplification (WGA) control. Using conservative thresholds, we found no evidence of 5-methylcytosine (5mC), especially typical CpG methylation, across the viral genome. Importantly, clear CpG methylation signals were successfully detected in the host genome from WGS data, confirming the functionality of the workflow to detect 5mC at CG sites. While widespread 5mC seems absent, a small number of putative N6-methyladenine (6mA) loci were identified. A specific 6mA candidate exhibited raw ionic current disruptions and gene-level intersection with another ASFV isolate (CAS19-01/2019), although it lacked single-base consensus across different methylation callers or between the two isolates. Although our biological findings are restricted to a single isolate under specific experimental conditions, this study introduces a novel, highly rigorous ONT framework for viral epigenomics research. Furthermore, the absence of ASFV CpG methylation indicates that host CpG-depletion remains a viable strategy for viral metagenomic enrichment. Ultimately, our work offers a critical methodological baseline for ASFV surveillance and highlights the necessity of targeted experimental validation for rare viral modifications.

African Swine Fever Virus↗

PubMed2026

Disentangling covariate effects on single-cell-resolved epigenomes with DeepDive.

Understanding the effects of individual biological factors from single-cell-resolved epigenomic data is hindered by multicollinearity, particularly in human cohorts. We introduce DeepDive, a deep-learning framework designed to systematically disentangle known and unknown sources of variation in single-nucleus ATAC-seq data. DeepDive accurately reconstructs chromatin accessibility, outperforms state-of-the-art methods with incomplete covariate information, and robustly recovers true biological signals from even highly entangled covariates, unlocking counterfactual, "what-if," analyses. Applying DeepDive to pancreatic islet cells, we perform counterfactual analyses to prioritize covariates associated with a type 2 diabetes-linked beta-cell subtype and nominate transcription regulators. DeepDive offers a powerful and unbiased tool for mechanistic discovery in complex human disease cohorts.

disentanglement↗