Biology subjects

Glaser, B.

Publications and source records attributed to Glaser, B..

18 recordsLinked to original sources

bioRxiv2026

Ultrasensitive detection of neuronal DNA using genome-wide non-CG methylation patterns

Methylation-based liquid biopsies can identify the tissue origins of circulating cell-free DNA (cfDNA). A major constraint on the sensitivity of these assays is the limited number of cell-type-specific CpG markers. Here we exploit the high abundance of non-CpG (CpH) methylation in neurons to enable ultrasensitive detection of neuronal DNA. We show that neurons carry 100-fold higher CpH methylation than other tissues, in which apparent CpH methylation largely reflects experimental artifacts. Using a computational criterion to identify cfDNA molecules carrying clusters of methylated CpA sites, we detect neuronal DNA at proportions as low as 20 parts per million. Analysis of 231 samples from 163 individuals revealed minimal neuronal cfDNA in the plasma of healthy subjects; elevated levels in patients with measles or acute neurological conditions; strikingly high levels in brain-dead donors, indicating extensive ongoing neuronal death; and the highest levels in the cerebrospinal fluid of patients in a neurological intensive care unit. These findings establish genome-wide, fragment-level analysis of non-CpG methylation as an ultrasensitive approach for blood-based monitoring of brain injury and disease.

genomics↗

bioRxiv2026

Bispecific GD2xB7-H3 Antibody Improves Tumor Targeting and Reduces Toxicity while Maintaining Efficacy for Neuroblastoma

The current treatment regimen for neuroblastoma involves immunotherapy, including a monoclonal antibody that recognizes disialoganglioside (GD2), expressed at high levels on neuroblastoma. GD2 is not present on most normal tissues except for nerves. Thus, anti-GD2 antibody treatment causes substantial, dose-limiting neuropathic pain. B7-H3 is overexpressed on multiple tumor types, including neuroblastoma, and is largely absent on nerves and other normal tissues. We designed a bispecific antibody (bsAb) that requires simultaneous binding of these two tumor antigens to achieve tight binding of tumor cells. Our preclinical research shows that, compared with a monospecific anti-GD2 antibody, the GD2xB7-H3 bsAb has improved tumor specificity, comparable antitumor efficacy, and reduced nerve binding and pain-associated toxicity. Since this bsAb does not bind to nerves, it may permit more tolerable and sustained treatment schedules than are currently feasible with monospecific anti-GD2 antibodies. In addition, its enhanced tumor specificity may support future development as a targeted delivery platform for antibody-drug conjugates or other payload-based therapies, potentially improving both efficacy and quality of life for patients with neuroblastoma.

cancer biology↗

bioRxiv2025

Latent plasticity of the human pancreas across development, health, and disease.

The pancreas plays a central role in major human diseases, yet our understanding of its cellular diversity and plasticity remains incomplete. Here, we present a single-cell multiomics atlas of the human pancreas, profiling over four million cells and nuclei from 57 donors across fetal development, adult homeostasis, and type 2 diabetes (T2D). Integrating sc/snRNA-seq, snATAC-seq, VASA-seq, spatial transcriptomics (Xenium), and multiplexed proteomics (CODEX), we resolve gene expression, chromatin accessibility, and spatial organization at high resolution. We identify transcriptionally plastic centroacinar-like cells (pCACs) in adults with fetal-like features, delineate endocrine and exocrine lineage trajectories during development, and uncover HNF1A-defined beta cell epigenetic states. In T2D, we observe shifts in beta cell subtypes and altered regulatory programs. Glucose perturbation of healthy islets reveals cell-type-specific adaptation and stress responses. This atlas provides a foundational framework to understand pancreas biology and the role of cellular plasticity in regeneration and disease.

genomics↗

bioRxiv2025

Epigenetic adaptation of beta cells across lifespan and disease: age-related demethylation is advanced in type 2 diabetes

Although the prevalence of type 2 diabetes (T2D) increases with age, most adults maintain normoglycemia despite rising insulin resistance, largely due to the adaptive capacity of pancreatic beta cells to meet increased metabolic demand. However, persistent insulin resistance can lead to beta cell dysfunction and T2D onset. Here, leveraging cell-type-specific methylome data from the Human Pancreas Analysis Program (HPAP), we investigate the epigenomic basis of beta cell adaptation by mapping genome-wide DNA methylation (DNAm) patterns across the human lifespan. In healthy donors, we identify progressive age-related demethylation enriched in cis- regulatory elements at beta cell identity and function genes, suggesting that epigenetic remodeling supports functional adaptation to metabolic demand over time. In contrast, alpha cells show the opposite trajectory, with subtle, age-related hypermethylation. In T2D beta but not alpha cells we observed further demethylation compared to healthy controls, underscoring a unique capacity of beta cells to respond to changes in metabolic demand. Together, our findings suggest that DNAm remodeling in healthy beta cells reflects a long-term adaptation to metabolic demand, which in T2D is accelerated as part of a compensatory response that ultimately fails under sustained insulin resistance.

genomics↗

bioRxiv2024

Time is encoded by methylation changes at clustered CpG sites

Age-dependent changes in DNA methylation allow chronological and biological age inference, but the underlying mechanisms remain unclear. Using ultra-deep sequencing of >300 blood samples from healthy individuals, we show that age-dependent DNA methylation changes are regional and occur at multiple adjacent CpG sites, either stochastically or in a coordinated block-like manner. Deep learning analysis of single-molecule patterns in two genomic loci achieved accurate age prediction with a median error of 1.46-1.7 years on held-out human blood samples, dramatically improving current epigenetic clocks. Factors such as gender, BMI, smoking and other measures of biological aging do not affect chronological age inference. Longitudinal 10-year samples revealed that early deviations from epigenetic age are maintained throughout life and subsequent changes faithfully record time. Lastly, the model inferred chronological age from as few as 50 DNA molecules, suggesting that age is encoded by individual cells. Overall, DNA methylation changes in clustered CpG sites illuminate the principles of time measurement by cells and tissues, and facilitate medical and forensic applications. O_FIG O_LINKSMALLFIG WIDTH=174 HEIGHT=200 SRC="FIGDIR/small/626674v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@c4dd52org.highwire.dtl.DTLVardef@9e6e62org.highwire.dtl.DTLVardef@160f8c3org.highwire.dtl.DTLVardef@16be7a3_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

Bispecific GD2 x B7-H3 Antibody Improves Tumor Targeting and Reduces Toxicity while Maintaining Efficacy for Neuroblastoma

The current treatment for neuroblastoma involves an immunotherapy regimen that includes a monoclonal antibody that recognizes disialoganglioside (GD2), expressed at high levels on neuroblastoma. GD2 is not present on most normal tissues but is expressed on nerves. Thus, anti-GD2 treatment causes substantial, dose-limiting, neuropathic pain. B7-H3 is overexpressed on multiple tumor types, including neuroblastoma, with minimal normal cell expression and is absent on nerves. We designed a bispecific antibody (bsAb) that requires simultaneous binding of these two tumor antigens to achieve tight-binding of tumor cells. Our preclinical research shows that when compared to an anti-GD2 monospecific antibody, the GD2xB7-H3 bsAb has improved tumor specificity with similar efficacy and reduced toxicity. Since this bsAb does not bind to nerves, it may be possible to administer increased or additional doses beyond the tolerable dose of monospecific anti-GD2 antibodies, which could improve therapeutic efficacy and quality of life for patients with neuroblastoma.

cancer biology↗

bioRxiv2024

Atlas of imprinted and allele-specific DNA methylation in the human body

Allele-specific DNA methylation, determined genetically or epigenetically, is involved in gene regulation and underlies multiple pathologies. Yet, our knowledge of this phenomenon is partial, and largely limited to blood lineages. Here, we present a comprehensive atlas of allele-specific DNA methylation, using deep whole-genome sequencing across 39 normal human cell types. We identified 325k genomic regions, covering 6% of the genome and containing 11% of all CpG sites, that show a bimodal distribution of methylated and unmethylated molecules. In 34K of these regions, genetic variations at individual alleles segregate with methylation patterns, thus validating allele-specific methylation. We also identified 460 regions showing parentally-imprinted methylation, the majority of which were not previously reported. Surprisingly, sequence-dependent and parent-dependent methylation patterns are often restricted to specific cell types, revealing unappreciated variation in the human allele-specific methylation across the human body. The atlas provides a resource for studying allele-specific methylation and regulatory mechanisms underlying imprinted expression in specific human cell types. HighlightsO_LIA comprehensive atlas of allele-specific methylation in primary human cell types C_LIO_LI325k genomic regions show a bimodal pattern of of hyper- and hypo-methylation of DNA C_LIO_LIAllele-specific methylation at 34k genomic regions C_LIO_LITissue-specific effects at known imprinting control regions (ICRs) C_LIO_LI100s of novel loci exhibiting parentally-imprinted methylation C_LIO_LIParentally-imprinting methylation is often cell-type-specific C_LI

genomics↗

bioRxiv2023

Multi-cell type deconvolution using a probabilistic model for single-molecule DNA methylation haplotypes

BackgroundDeconvolution is used to estimate the proportion of mixed cell types from tissue or blood samples based on genomic profiling. DNA methylation is commonly used because specific CpG positions reflect cell type identity and can be accurately measured at either the population or single-molecule level. Methylation sequencing techniques can profile multiple individual CpGs on a single DNA molecule, but few deconvolution models have been developed to exploit these single-molecule methylation haplotypes for cell type deconvolution. Results and ConclusionsWe used simulated whole-genome methylation data and in silico mixtures of real data to compare existing deconvolution tools with two new models developed here. We found that adapting an existing model CelFiE to incorporate methylation haplotype information improved deconvolution accuracy by [~]30% over other tools, including the original CelFiE. In addition to overall higher accuracy, our new tool CelFiE Integrated Single-molecule Haplotypes (or CelFiE-ISH) outperformed others in detecting rare cell types present at 0.1% and below. Detection of rare cell types is important for the analysis of circulating DNA, which we demonstrate using a patient-derived plasma sequencing dataset.Finally,we show that marker selection strategy has a strong effect on deconvolution accuracy, concluding that haplotype-aware deconvolution can take advantage of markers tailored for that purpose.

bioinformatics↗

bioRxiv2023

Epigenetic liquid biopsies reveal elevated vascular endothelial cell turnover and erythropoiesis in asymptomatic COVID-19 patients

The full spectrum of tissues affected by SARS-CoV-2 infection is crucial for deciphering the heterogenous clinical course of COVID-19. Here, we analyzed DNA methylation and histone modification patterns in circulating chromatin to assess cell type-specific turnover in severe and asymptomatic COVID-19 patients, in relation to clinical outcome. Patients with severe COVID-19 had a massive elevation of circulating cell-free DNA (cfDNA) levels, which originated in lung epithelial cells, cardiomyocytes, vascular endothelial cells and erythroblasts, suggesting increased cell death or turnover in these tissues. The immune response to infection was reflected by elevated B cell and monocyte/macrophage cfDNA levels, and by evidence of an interferon response in cells prior to cfDNA release. Strikingly, monocyte/macrophage cfDNA levels (but not monocyte counts), as well as lung epithelium cfDNA and vascular endothelial cfDNA, predicted clinical deterioration and duration of hospitalization. Asymptomatic patients had elevated levels of immune-derived cfDNA but did not show evidence of pulmonary or cardiac damage. Surprisingly, these patients showed elevated levels of vascular endothelial cell and erythroblast cfDNA, suggesting that sub-clinical vascular and erythrocyte turnover are universal features of COVID-19, independent of disease severity. Epigenetic liquid biopsies provide non-invasive means of monitoring COVID-19 patients, and reveal sub-clinical vascular damage and red blood cell turnover.

microbiology↗

bioRxiv2023

G6PC2 controls glucagon secretion by defining the setpoint for glucose in pancreatic α-cells

Impaired glucose suppression of glucagon secretion (GSGS) is a hallmark of type 2 diabetes. A critical role for -cell intrinsic mechanisms in regulating glucagon secretion was previously established through genetic manipulation of the glycolytic enzyme glucokinase (GCK) in mice. Genetic variation at the G6PC2 locus, encoding an enzyme that opposes GCK, has been reproducibly associated with fasting blood glucose and hemoglobin A1c levels. Here, we find that trait-associated variants in the G6PC2 promoter are located in open chromatin not just in {beta}- but also in -cells, and document allele-specific G6PC2 expression of linked variants in human - cells. Using -cell specific gene ablation of G6pc2 in mice, we show that this gene plays a critical role in controlling glucagon secretion independent of alterations in insulin output, islet hormone content, or islet morphology; findings we confirmed in primary human -cells. Collectively, our data demonstrate that G6PC2 impacts glycemic control via its action in -cells and suggest that G6PC2 inhibitors could help control blood glucose through a novel, bi-hormonal mechanism.

genetics↗

bioRxiv2023

Accurate age prediction from blood using of small set of DNA methylation sites and a cohort-based machine learning algorithm

Chronological age prediction from DNA methylation sheds light on human aging, indicates poor health and predicts lifespan. Current clocks are mostly based on linear models from hundreds of methylation sites, and are not suitable for sequencing-based data. We present GP-age, an epigenetic clock for blood, that uses a non-linear cohort-based model of 11,910 blood methylomes. Using 30 CpG sites alone, GP-age outperforms state-of-the-art models, with a median accuracy of ~2 years on held-out blood samples, for both array and sequencing-based data. We show that aging-related changes occur at multiple neighboring CpGs, with far-reaching implications on aging research at the cellular level. By training three independent clocks, we show consistent deviations between predicted and actual age, suggesting individual rates of biological aging. Overall, we provide a compact yet accurate alternative to array-based clocks for blood, with future applications in longitudinal aging research, forensic profiling, and monitoring epigenetic processes in transplantation medicine and cancer. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=158 HEIGHT=200 SRC="FIGDIR/small/524874v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@14eb626org.highwire.dtl.DTLVardef@98aecdorg.highwire.dtl.DTLVardef@1fc2ca1org.highwire.dtl.DTLVardef@d6138f_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIMachine learning analysis of a large cohort (~12K) of DNA methylomes from blood C_LIO_LIA 30-CpG regression model achieves a 2.1-year median error in predicting age C_LIO_LIImproved accuracy ([≥]1.75 years) from sequencing data, using neighboring CpGs C_LIO_LIPaves the way for easy and accurate age prediction from blood, using NGS data C_LI MotivationEpigenetic clocks that predict age from DNA methylation are a valuable tool in the research of human aging, with additional applications in forensic profiling, disease monitoring, and lifespan prediction. Most existing epigenetic clocks are based on linear models and require hundreds of methylation sites. Here, we present a compact epigenetic clock for blood, which outperforms state-of-the-art models using only 30 CpG sites. Finally, we demonstrate the applicability of our clock to sequencing-based data, with far reaching implications for a better understanding of epigenetic aging.

bioinformatics↗

bioRxiv2022

Disrupted RNA editing in beta cells mimics early stage type 1 diabetes

A major hypothesis for the etiology of type 1 diabetes (T1D) postulates initiation by viral infection, leading to double-stranded RNA (dsRNA)-mediated interferon response; however, a causal virus has not been identified. Here we use a mouse model, corroborated with human data, to demonstrate that endogenous dsRNA in beta-cells can lead to a diabetogenic immune response, thus identifying a virus-independent mechanism for T1D initiation. We found that disruption of the RNA editing enzyme ADAR in beta-cells triggers a massive interferon response, islet inflammation and beta-cell failure, with features bearing striking similarity to early-stage human T1D. Glycolysis via calcium enhances the interferon response, suggesting an actionable vicious cycle of inflammation and increased beta-cell workload. One sentence summaryAdar inactivation in beta-cells triggers a glucose-dependent interferon response causing insulitis and diabetes

cell biology↗

bioRxiv2022

Megakaryocyte and erythroblast DNA in plasma and platelets

Circulating cell-free DNA (cfDNA) fragments are a biological analyte with extensive utility in diagnostic medicine. Understanding the source of cfDNA and mechanisms of release is crucial for designing and interpreting cfDNA-based liquid biopsy assays. Using cell type-specific methylation markers as well as genome-wide methylation analysis, we determined that megakaryocytes, the precursors of anuclear platelets, are major contributors to cfDNA ([~]26%), while erythroblasts contribute 1-4% of cfDNA in healthy individuals. Surprisingly, we discovered that platelets contain genomic DNA fragments originating in megakaryocytes, contrary to the general understanding that platelets lack genomic DNA. Megakaryocyte-derived cfDNA is increased in pathologies involving increased platelet production (Essential Thrombocythemia, Idiopathic Thrombocytopenic Purpura) and decreased upon reduced platelet production due to chemotherapy-induced bone marrow suppression. Similarly, erythroblast cfDNA is reflective of erythrocyte production and is elevated in patients with Thalassemia. Megakaryocyte- and erythroblast-specific DNA methylation patterns can thus serve as novel biomarkers for pathologies involving increased or decreased thrombopoiesis and erythropoiesis, which can aid in determining the etiology of aberrant levels of erythrocytes and platelets. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/510502v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@164e8borg.highwire.dtl.DTLVardef@7eb5e1org.highwire.dtl.DTLVardef@d6ff73org.highwire.dtl.DTLVardef@11cf846_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2021

Remote immune processes revealed by immune-derived circulating cell-free DNA

Blood cell counts often fail to report on immune processes occurring in remote tissues. Here we use immune cell type-specific methylation patterns in circulating cell-free DNA (cfDNA) for studying human immune cell dynamics. We characterized cfDNA released from specific immune cell types in healthy individuals (N=242), cross sectionally and longitudinally. Immune cfDNA levels had no individual steady state as opposed to blood cell counts, suggesting that cfDNA concentration reflects adjustment of cell survival to maintain homeostatic cell numbers. We also observed selective elevation of immune-derived cfDNA upon perturbations of immune homeostasis. Following influenza vaccination (N=92), B-cell-derived cfDNA levels increased prior to elevated B-cell counts and predicted efficacy of antibody production. Patients with Eosinophilic Esophagitis (N=21) and B-cell lymphoma (N=27) showed selective elevation of eosinophil and B-cell cfDNA respectively, which were undetectable by cell counts in blood. Immune-derived cfDNA provides a novel biomarker for monitoring immune responses to physiological and pathological processes that are not accessible using conventional methods.

genomics↗

bioRxiv2019

ChIP-seq of plasma cell-free nucleosomes identifies cell-of-origin gene expression programs

AbstractGenomic DNA is packed by histone proteins that carry a multitude of post-translational modifications that reflect cellular transcriptional state. Cell-free DNA (cfDNA) is derived from fragmented chromatin in dying cells, and as such it retains the histones markings present in the cells of origin. Here, we pioneer chromatin immunoprecipitation followed by sequencing of cell-free nucleosomes (cfChIP-seq) carrying active chromatin marks. Our results show that cfChIP-seq provides multidimensional epigenetic information that recapitulates the epigenetic and transcriptional landscape in the cells of origin. We applied cfChIP-seq to 268 samples including samples from patients with heart and liver pathologies, and 135 samples from 56 metastatic CRC patients. We show that cfChIP-seq can detect pathology-related transcriptional changes at the site of the disease, beyond the information on tissue of origin. In CRC patients we detect clinically-relevant, and patient-specific information, including transcriptionally active HER2 amplifications. cfChIP-seq provides genome-wide information and requires low sequencing depth. Altogether, we establish cell-free chromatin immunoprecipitation as an exciting modality with potential for diagnosis and interrogation of physiological and pathological processes using a simple blood test. One Sentence SummaryChIP-seq of plasma-circulating nucleosomes (cfChIP-seq) from a simple blood test provides detailed information about gene expression programs in human organs, and cancer.

molecular biology↗

bioRxiv2018

Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease

Methylation patterns of circulating cell-free DNA (cfDNA) contain rich information about recent cell death events in the body. Here, we present an approach for unbiased determination of the tissue origins of cfDNA, using a reference methylation atlas of 25 human tissues and cell types. The method is validated using in silico simulations as well as in vitro mixes of DNA from different tissue sources at known proportions. We show that plasma cfDNA of healthy donors originates from white blood cells (55%), erythrocyte progenitors (30%), vascular endothelial cells (10%) and hepatocytes (1%). Deconvolution of cfDNA from patients reveals tissue contributions that agree with clinical findings in sepsis, islet transplantation, cancer of the colon, lung, breast and prostate, and cancer of unknown primary. We propose a procedure which can be easily adapted to study the cellular contributors to cfDNA in many settings, opening a broad window into healthy and pathologic human tissue dynamics.

molecular biology↗

bioRxiv2018

Specific detection of cell-free DNA derived from intestinal epithelial cells using methylation patterns

Epithelial cells of the intestine undergo rapid turnover and are thought to be cleared via stool. Disruption of tissue architecture, as occurs in colorectal cancer (CRC), results in the release of material from dying intestinal epithelial cells to blood. This phenomenon could be utilized for diagnosis and monitoring of intestinal diseases, if circulating cell-free DNA (cfDNA) derived from intestinal cells could be specifically identified. Here we describe two genomic loci that are unmethylated specifically in intestinal epithelial cells, allowing for sensitive and specific detection of DNA derived from such cells. As expected, intestinal DNA is found in stool, but not in plasma, of healthy individuals. Patients with inflammatory bowel disease (IBD) have minimal amounts of intestinal cfDNA in the plasma, whereas patients with advanced CRC show a strong signal. The intestinal markers are not elevated in plasma samples from patients with pancreatic ductal adenocarcinoma (PDAC), and a combination of intestine- and pancreas-specific markers allowed for robust differentiation between plasma cfDNA derived from CRC and PDAC patients. Intestinal DNA markers provide a mutation-independent tool for monitoring intestinal dynamics in health and disease.

developmental biology↗

bioRxiv2018

Clustering of Type 2 Diabetes Genetic Loci by Multi-Trait Associations Identifies Disease Mechanisms and Subtypes

BackgroundType 2 diabetes (T2D) is a heterogeneous disease for which 1) disease-causing pathways are incompletely understood and 2) sub-classification may improve patient management. Unlike other biomarkers, germline genetic markers do not change with disease progression or treatment. In this paper we test whether a germline genetic approach informed by physiology can be used to deconstruct T2D heterogeneity. First, we aimed to categorize genetic loci into groups representing likely disease mechanistic pathways. Second, we asked whether the novel clusters of genetic loci we identified have any broad clinical consequence, as assessed in four independent cohorts of individuals with T2D.\n\nMethods and FindingsIn an effort to identify mechanistic pathways driven by established T2D genetic loci, we applied Bayesian nonnegative matrix factorization clustering to genome-wide association results for 94 independent T2D genetic loci and 47 diabetes-related traits. We identified five robust clusters of T2D loci and traits, each with distinct tissue-specific enhancer enrichment based on analysis of epigenomic data from 28 cell types. Two clusters contained variant-trait associations indicative of reduced beta-cell function, differing from each other by high vs. low proinsulin levels. The three other clusters displayed features of insulin resistance: obesity-mediated (high BMI, waist circumference), \"lipodystrophy-like\" fat distribution (low BMI, adiponectin, HDL-cholesterol, and high triglycerides), and disrupted liver lipid metabolism (low triglycerides). Increased cluster GRSs were associated with distinct clinical outcomes, including increased blood pressure, coronary artery disease, and stroke risk. We evaluated the potential for clinical impact of these clusters in four studies containing participants with T2D (METSIM, N=487; Ashkenazi, N=509; Partners Biobank, N=2,065; UK Biobank N=14,813). Individuals with T2D in the top genetic risk score decile for each cluster reproducibly exhibited the predicted cluster-associated phenotypes, with ~30% of all participants assigned to just one cluster top decile.\n\nConclusionOur approach identifies salient T2D genetically anchored and physiologically informed pathways, and supports use of genetics to deconstruct T2D heterogeneity. Classification of patients by these genetic pathways may offer a step toward genetically informed T2D patient management.

genetics↗