Nat Metab. 2021 Jun 28. doi: 10.1038/s42255-021-00420-9. Online ahead of print.
Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories towards type 2 diabetes
Leonore Wigger # 1, Marko Barovic # 2 3 4, Andreas-David Brunner # 5, Flavia Marzetta 1, Eyke Schöniger 2 3 4, Florence Mehl 1, Nicole Kipke 2 3 4, Daniela Friedland 2 3 4, Frederic Burdet 1, Camille Kessler 1, Mathias Lesche 6, Bernard Thorens 7, Ezio Bonifacio 3 4 8, Cristina Legido-Quigley 9 10, Pierre Barbier Saint Hilaire 11, Philippe Delerive 12, Andreas Dahl 6, Christian Klose 13, Mathias J Gerl 13, Kai Simons 13, Daniela Aust 14 15, Jürgen Weitz 16, Marius Distler 16, Anke M Schulte 17, Matthias Mann 18, Mark Ibberson 19, Michele Solimena 20 21 22
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.
- PMID: 34183850
- DOI: 10.1038/s42255-021-00420-9