Nature MetabolismBioinformaticsPeer-reviewed journal article
Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories toward type 2 diabetes
Leonore WiggeriD, Marko BaroviciD, Andreas‐David BrunneriD, Flavia MarzettaiD, Eyke SchönigeriD, Florence MehliD, Nicole Kipke, Daniela Friedland, Frédéric BurdetiD, Camille KessleriD, Mathias LescheiD, Bernard ThorensiD, Ezio E. BonifacioiD, Cristina Legido‐QuigleyiD, Pierre Barbier Saint HilaireiD, Philippe DeleriveiD, Andreas DahliD, Christian D. KloseiD, Mathias J. GerliD, Kai SimonsiD, Daniela Ellen AustiD, Jürgen WeitziD, Marius DistleriD, Anke M. Schulte, Matthias ManniD, , Michele SolimenaiD
Abstract
Existing studies do not sufficiently describe the molecular changes of pancreatic islet beta cells leading to their deficient insulin secretion in type 2 diabetes (T2D). Here we address this deficiency with a comprehensive multi-omics analysis of metabolically profiled pancreatectomized living human donors stratified along the glycemic continuum from normoglycemia to T2D. Islet pools isolated from surgical samples by laser-capture microdissection had remarkably heterogeneous transcriptomic and proteomic profiles in diabetics, but not in non-diabetic controls. Transcriptomics analysis of this unique cohort revealed islet genes already dysregulated in prediabetic individuals with impaired glucose tolerance. Our findings demonstrate a progressive but disharmonic remodeling of mature beta cells, challenging current hypotheses of linear trajectories toward precursor or trans-differentiation stages in T2D. Further, integration of islet transcriptomics and pre-operative blood plasma lipidomics data enabled us to define the relative importance of gene co-expression modules and lipids positively or negatively associated with HbA1c levels, pointing to potential prognostic markers.
- organism: human
- assay: bulk RNA-seq
- assay: metabolomics
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 162
- FWCI
- 23.46
- Field percentile
- top 1%
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