(Multiomics OR Omics) AND (Pancreatic)
Single-cell multiome and spatial profiling reveals pancreas cell type-specific gene regulatory programs of type 1 diabetes progression Rebecca Melton · Sara Jimenez · Weston Elison · Luca Tucciarone · Abigail Howell · Gaowei Wang · Denise Berti · Elisha Beebe · Michael Miller · Chun Zeng · Carolyn McGrail · Kennedy VanderStel · Katha Korgaonkar · Ruth Elgamal · Hannah Mummey · Joshua Chiou · Emily Griffin · Irina Kusmartseva · Mark Atkinson · Sebastian Preissl · Fabian J Theis · Maike Sander · Kyle J Gaulton
Sci Adv. 2025 Sep 12;11(37):eady0080. doi: 10.1126/sciadv.ady0080. Epub 2025 Sep 10.ABSTRACTCell type-specific regulatory programs that drive type 1 diabetes (T1D) in the pancreas are poorly understood. Here, we performed single-nucleus multiomics and spatial transcriptomics in up to 32 nondiabetic (ND), autoantibody-positive (AAB+), and T1D pancreas donors. Genomic profiles from 853,005 cells mapped to 12 pancreatic cell types, including multiple exocrine subtypes. β, Acinar, and other cell typ
10 September 2025 at 18:00

Single-cell multiome and spatial profiling reveals pancreas cell type-specific gene regulatory programs of type 1 diabetes progression

By: Rebecca Melton · Sara Jimenez · Weston Elison · Luca Tucciarone · Abigail Howell · Gaowei Wang · Denise Berti · Elisha Beebe · Michael Miller · Chun Zeng · Carolyn McGrail · Kennedy VanderStel · Katha Korgaonkar · Ruth Elgamal · Hannah Mummey · Joshua Chiou · Emily Griffin · Irina Kusmartseva · Mark Atkinson · Sebastian Preissl · Fabian J Theis · Maike Sander · Kyle J Gaulton

10 September 2025 at 18:00

Sci Adv. 2025 Sep 12;11(37):eady0080. doi: 10.1126/sciadv.ady0080. Epub 2025 Sep 10.

ABSTRACT

Cell type-specific regulatory programs that drive type 1 diabetes (T1D) in the pancreas are poorly understood. Here, we performed single-nucleus multiomics and spatial transcriptomics in up to 32 nondiabetic (ND), autoantibody-positive (AAB⁺), and T1D pancreas donors. Genomic profiles from 853,005 cells mapped to 12 pancreatic cell types, including multiple exocrine subtypes. β, Acinar, and other cell types, and related cellular niches, had altered abundance and gene activity in T1D progression, including distinct pathways altered in AAB⁺ compared to T1D. We identified epigenomic drivers of gene activity in T1D and AAB⁺ which, combined with genetic association, revealed causal pathways of T1D risk including antigen presentation in β cells. Last, single-cell and spatial profiles together revealed widespread changes in cell-cell signaling in T1D including signals affecting β cell regulation. Overall, these results revealed drivers of T1D in the pancreas, which form the basis for therapeutic targets for disease prevention.

PMID:40929272 | PMC:PMC12422192 | DOI:10.1126/sciadv.ady0080

(Multiomics OR Omics) AND (Pancreatic)
Single-cell multiome and spatial profiling reveals pancreas cell type-specific gene regulatory programs driving type 1 diabetes progression Rebecca Melton · Sara Jimenez · Weston Elison · Luca Tucciarone · Abigail Howell · Gaowei Wang · Denise Berti · Elisha Beebe · Michael Miller · Chun Zeng · Carolyn McGrail · Kennedy VanderStel · Katha Korgaonkar · Ruth Elgamal · Hannah Mummey · Joshua Chiou · Emily Griffin · Irina Kusmartseva · Mark Atkinson · Sebastian Preissl · Fabian J Theis · Maike Sander · Kyle J Gaulton
bioRxiv [Preprint]. 2025 Feb 17:2025.02.13.637721. doi: 10.1101/2025.02.13.637721.ABSTRACTCell type-specific regulatory programs that drive type 1 diabetes (T1D) in the pancreas are poorly understood. Here we performed single nucleus multiomics and spatial transcriptomics in up to 32 non-diabetic (ND), autoantibody-positive (AAB+), and T1D pancreas donors. Genomic profiles from 853,005 cells mapped to 12 pancreatic cell types, including multiple exocrine sub-types. Beta, acinar, and other cell t
3 March 2025 at 19:00

Single-cell multiome and spatial profiling reveals pancreas cell type-specific gene regulatory programs driving type 1 diabetes progression

(Multiomics OR Omics) AND (Pancreatic)

By: Rebecca Melton · Sara Jimenez · Weston Elison · Luca Tucciarone · Abigail Howell · Gaowei Wang · Denise Berti · Elisha Beebe · Michael Miller · Chun Zeng · Carolyn McGrail · Kennedy VanderStel · Katha Korgaonkar · Ruth Elgamal · Hannah Mummey · Joshua Chiou · Emily Griffin · Irina Kusmartseva · Mark Atkinson · Sebastian Preissl · Fabian J Theis · Maike Sander · Kyle J Gaulton

3 March 2025 at 19:00

bioRxiv [Preprint]. 2025 Feb 17:2025.02.13.637721. doi: 10.1101/2025.02.13.637721.

ABSTRACT

Cell type-specific regulatory programs that drive type 1 diabetes (T1D) in the pancreas are poorly understood. Here we performed single nucleus multiomics and spatial transcriptomics in up to 32 non-diabetic (ND), autoantibody-positive (AAB+), and T1D pancreas donors. Genomic profiles from 853,005 cells mapped to 12 pancreatic cell types, including multiple exocrine sub-types. Beta, acinar, and other cell types, and related cellular niches, had altered abundance and gene activity in T1D progression, including distinct pathways altered in AAB+ compared to T1D. We identified epigenomic drivers of gene activity in T1D and AAB+ which, combined with genetic association, revealed causal pathways of T1D risk including antigen presentation in beta cells. Finally, single cell and spatial profiles together revealed widespread changes in cell-cell signaling in T1D including signals affecting beta cell regulation. Overall, these results revealed drivers of T1D progression in the pancreas, which form the basis for therapeutic targets for disease prevention.

PMID:40027657 | PMC:PMC11870426 | DOI:10.1101/2025.02.13.637721

Nature - Issue - nature.com science feeds
Plasma proteomic associations with genetics and health in the UK Biobank Benjamin B. Sun · Joshua Chiou · Matthew Traylor · Christian Benner · Yi-Hsiang Hsu · Tom G. Richardson · Praveen Surendran · Anubha Mahajan · Chloe Robins · Steven G. Vasquez-Grinnell · Liping Hou · Erika M. Kvikstad · Oliver S. Burren · Jonathan Davitte · Kyle L. Fe
Nature, Published online: 04 October 2023; doi:10.1038/s41586-023-06592-6The Pharma Proteomics Project generates the largest open-access plasma proteomics dataset to date, offering insights into trans protein quantitative trait loci across multiple biological domains, and highlighting genetic influences on ligand–receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks.
4 October 2023 at 08:00

Plasma proteomic associations with genetics and health in the UK Biobank

Nature - Issue - nature.com science feeds

By: Benjamin B. Sun · Joshua Chiou · Matthew Traylor · Christian Benner · Yi-Hsiang Hsu · Tom G. Richardson · Praveen Surendran · Anubha Mahajan · Chloe Robins · Steven G. Vasquez-Grinnell · Liping Hou · Erika M. Kvikstad · Oliver S. Burren · Jonathan Davitte · Kyle L. Fe

4 October 2023 at 08:00

Nature, Published online: 04 October 2023; doi:10.1038/s41586-023-06592-6

The Pharma Proteomics Project generates the largest open-access plasma proteomics dataset to date, offering insights into trans protein quantitative trait loci across multiple biological domains, and highlighting genetic influences on ligand–receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks.

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