2. Academic Validation
  3. Integrative single-cell multi-omics profiling of human pancreatic islets identifies T1D-associated genes and regulatory signals

Integrative single-cell multi-omics profiling of human pancreatic islets identifies T1D-associated genes and regulatory signals

  • Cell Rep. 2025 Aug 26;44(8):116065. doi: 10.1016/j.celrep.2025.116065.
Ricardo D'Oliveira Albanus 1,  Xiaoshan Zhang 2,  Zeping Zhao 2,  Henry J Taylor 3,  Xuming Tang 2,  Yuling Han 2,  Peter Orchard 1,  Arushi Varshney 1,  Tuo Zhang 4,  Nandini Manickam 1,  Michael R Erdos 3,  Narisu Narisu 3,  Leland Taylor 3,  Xiaxia Saavedra 5,  Xinyi Liu 2,  Aaron Zhong 6,  Bo Li 5,  Ting Zhou 6,  Ali Naji 7,  Chengyang Liu 7,  Francis S Collins 3,  Stephen C J Parker 8,  Shuibing Chen 9
Affiliations

Affiliations

  • 1 Gilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
  • 2 Department of Surgery, Weill Cornell Medicine, 1300 York Avenue, New York, NY 10065, USA; Center for Genomic Health, Weill Cornell Medicine, 1300 York Avenue, New York, NY 10065, USA.
  • 3 Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
  • 4 Genomic Resource Core Facility, Weill Cornell Medicine, New York, NY 10065, USA.
  • 5 Department of Surgery, Weill Cornell Medicine, 1300 York Avenue, New York, NY 10065, USA.
  • 6 Stem Cell Research Facility, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.
  • 7 Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA.
  • 8 Gilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA. Electronic address: scjp@umich.edu.
  • 9 Department of Surgery, Weill Cornell Medicine, 1300 York Avenue, New York, NY 10065, USA; Center for Genomic Health, Weill Cornell Medicine, 1300 York Avenue, New York, NY 10065, USA. Electronic address: shc2034@med.cornell.edu.
PMID: 40737125 DOI: 10.1016/j.celrep.2025.116065
Abstract

Genome-wide association studies (GWASs) have identified over 100 signals associated with type 1 diabetes (T1D). However, it has been challenging to translate any given T1D GWAS signal into mechanistic insights, such as causal variants, their target genes, and the specific cell types involved. Here, we present a comprehensive multi-omic integrative analysis of single-cell/nucleus resolution profiles of gene expression and chromatin accessibility in human pancreatic islets under baseline and T1D-stimulating conditions. We nominate effector cell types for all T1D GWAS signals and the regulatory elements and genes for three independent T1D signals acting through β cells at the DLK1/MEG3, RASGRP1, and TOX loci. Subsequently, we validated the functional impact of these genes and regulatory regions using isogenic human embryonic stem cells (hESCs). We found that loss of RASGRP1 or DLK1, as well as disruption of their corresponding regulatory regions, led to increased β cell Apoptosis. Furthermore, β cells derived from isogenic hESCs carrying the T1D risk allele of rs3783355 associated with DLK1 showed elevated β cell death. Through additional RNA Sequencing (RNA-seq) and assay for transposase-accessible chromatin using Sequencing (ATAC-seq) analyses, we identified five genes upregulated in both RASGRP1-/- and DLK1-/- β-like cells, four of which are near T1D GWAS signals. This integrative approach combining single-cell multi-omics, GWASs, and isogenic human pluripotent stem cell (hPSC)-derived β-like cells illuminates cell type context, genes, single nucleotide polymorphisms (SNPs), and regulatory elements underlying T1D-associated signals, providing insights into the biological functions and molecular mechanisms involved.

Keywords

CP: Genomics; CP: Metabolism; GWAS; T1D-associated signals; apoptosis; cytokine; differentiation; hPSCs; human pancreatic islets; multi-omics profiling; type 1 diabetes; β cells.

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