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From pancreas and islet resources to diabetes insights

Chen, Sing Young ; Lekka, Christiana ; Lemvig, Jonas ; Yi, Xiaoyan ; Cnop, Miriam ; Marchetti, Piero ; Marselli, Lorella ; Xia, Jianguo ; Madsen, Jesper G.S. and Rodriguez-Calvo, Teresa , et al. (2026) In Diabetologia 69(7). p.1741-1758
Abstract

Pancreatic islets of Langerhans are central to the pathogenesis of all major forms of diabetes. The ability to study human islets ex vivo has advanced our understanding of diabetes and aided in the development of novel therapeutics. However, for decades, very few laboratories had access to this critical resource and experiments on human islets were typically underpowered. More recently, multiple consortia around the world have started to enable islet biology at scale, enriching our understanding of the intra-individual variability of islet function and disease mechanisms. This article reviews and compares existing large-scale human islet tissue and data resources, offering suggestions for their improvement and for developing new... (More)

Pancreatic islets of Langerhans are central to the pathogenesis of all major forms of diabetes. The ability to study human islets ex vivo has advanced our understanding of diabetes and aided in the development of novel therapeutics. However, for decades, very few laboratories had access to this critical resource and experiments on human islets were typically underpowered. More recently, multiple consortia around the world have started to enable islet biology at scale, enriching our understanding of the intra-individual variability of islet function and disease mechanisms. This article reviews and compares existing large-scale human islet tissue and data resources, offering suggestions for their improvement and for developing new resources.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Biobanking, Data repositories, Diabetes, Islets of Langerhans, Knowledge bases, Multi-omics, Open science, Review, Standardisation, Tissue phenotyping
in
Diabetologia
volume
69
issue
7
pages
18 pages
publisher
Springer
external identifiers
  • scopus:105037734809
  • pmid:42065736
ISSN
0012-186X
DOI
10.1007/s00125-026-06731-4
language
English
LU publication?
yes
id
d652cf65-a2d9-4f19-9071-d95ef12dd51c
date added to LUP
2026-08-27 14:57:49
date last changed
2026-08-28 03:00:02
@article{d652cf65-a2d9-4f19-9071-d95ef12dd51c,
  abstract     = {{<p>Pancreatic islets of Langerhans are central to the pathogenesis of all major forms of diabetes. The ability to study human islets ex vivo has advanced our understanding of diabetes and aided in the development of novel therapeutics. However, for decades, very few laboratories had access to this critical resource and experiments on human islets were typically underpowered. More recently, multiple consortia around the world have started to enable islet biology at scale, enriching our understanding of the intra-individual variability of islet function and disease mechanisms. This article reviews and compares existing large-scale human islet tissue and data resources, offering suggestions for their improvement and for developing new resources.</p>}},
  author       = {{Chen, Sing Young and Lekka, Christiana and Lemvig, Jonas and Yi, Xiaoyan and Cnop, Miriam and Marchetti, Piero and Marselli, Lorella and Xia, Jianguo and Madsen, Jesper G.S. and Rodriguez-Calvo, Teresa and Richardson, Sarah J. and Johnson, James D. and MacDonald, Patrick E.}},
  issn         = {{0012-186X}},
  keywords     = {{Biobanking; Data repositories; Diabetes; Islets of Langerhans; Knowledge bases; Multi-omics; Open science; Review; Standardisation; Tissue phenotyping}},
  language     = {{eng}},
  number       = {{7}},
  pages        = {{1741--1758}},
  publisher    = {{Springer}},
  series       = {{Diabetologia}},
  title        = {{From pancreas and islet resources to diabetes insights}},
  url          = {{http://dx.doi.org/10.1007/s00125-026-06731-4}},
  doi          = {{10.1007/s00125-026-06731-4}},
  volume       = {{69}},
  year         = {{2026}},
}