Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories towards type 2 diabetes

L Wigger, M Barovic, AD Brunner, F Marzetta… - Nature …, 2021 - nature.com
L Wigger, M Barovic, AD Brunner, F Marzetta, E Schöniger, F Mehl, N Kipke, D Friedland…
Nature Metabolism, 2021nature.com
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 …
Abstract
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.
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