Biology subjects

Avrahami, D.

Publications and source records attributed to Avrahami, D..

4 recordsLinked to original sources

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↗

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

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↗