Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories towards type 2 diabetes.
Détails
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Accès restreint UNIL
Etat: Public
Version: de l'auteur⸱e
Licence: Non spécifiée
Accès restreint UNIL
Etat: Public
Version: de l'auteur⸱e
Licence: Non spécifiée
ID Serval
serval:BIB_CE60701C01FB
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories towards type 2 diabetes.
Périodique
Nature metabolism
ISSN
2522-5812 (Electronic)
ISSN-L
2522-5812
Statut éditorial
Publié
Date de publication
07/2021
Peer-reviewed
Oui
Volume
3
Numéro
7
Pages
1017-1031
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Publication Status: ppublish
Résumé
Most research on human pancreatic islets is conducted on samples obtained from normoglycaemic or diseased brain-dead donors and thus cannot accurately describe the molecular changes of pancreatic islet beta cells as they progress towards a state of deficient insulin secretion in type 2 diabetes (T2D). Here, we conduct a comprehensive multi-omics analysis of pancreatic islets obtained from metabolically profiled pancreatectomized living human donors stratified along the glycemic continuum, from normoglycemia to T2D. We find that islet pools isolated from surgical samples by laser-capture microdissection display remarkably more heterogeneous transcriptomic and proteomic profiles in patients with diabetes than in non-diabetic controls. The differential regulation of islet gene expression is already observed in prediabetic individuals with impaired glucose tolerance. Our findings demonstrate a progressive, but disharmonic, remodelling of mature beta cells, challenging current hypotheses of linear trajectories toward precursor or transdifferentiation stages in T2D. Furthermore, through integration of islet transcriptomics with preoperative blood plasma lipidomics, we define the relative importance of gene coexpression modules and lipids that are positively or negatively associated with HbA1c levels, pointing to potential prognostic markers.
Mots-clé
Biomarkers, Blood Glucose, Diabetes Mellitus, Type 2/etiology, Diabetes Mellitus, Type 2/metabolism, Disease Susceptibility, Energy Metabolism, Gene Expression Profiling, Gene Expression Regulation, Humans, Insulin/metabolism, Insulin-Secreting Cells/metabolism, Islets of Langerhans/metabolism, Living Donors, Metabolomics, Proteomics
Pubmed
Web of science
Création de la notice
06/07/2021 10:30
Dernière modification de la notice
25/02/2022 6:37