bioRxivPhysiologyPreprint
Mitochondrial and protein homeostasis pathways are transcriptionally impaired in islets during type 1 diabetes pathogenesis
Alexandra E. CuaycaliD, Elizabeth Ashley ButterworthiD, Scott E. StimpsoniD, Jing CheniD, Nataliya I. LenchikiD, Leigh A BarattaiD, Edward A. PhelpsiD, Scott S. GrieshaberiD, Mark A. AtkinsoniD, Weijun QianiD, Martha Campbell‐ThompsoniD, Ivan GerlingiD, Clayton E. MathewsiD
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Abstract
The decline in first-phase insulin response (FPIR) during the presymptomatic period of type 1 diabetes (T1D) is well established. In-situ functional studies with pancreas tissue slices showed that {beta}-cell loss of glucose-responsiveness was independent of T-cell infiltration into islets in recent-onset T1D cases. However, the mechanisms driving {beta}-cell dysfunction before the onset of T1D remain unclear. In pancreas tissue from donors across the natural history of T1D, we utilized an in-situ, whole-islet phenotypical and transcriptomic approach to unravel novel targets in the glucose-stimulus coupled secretion pathway that are similarly impaired in T-cell infiltrated and non-infiltrated islets. Specifically, we observed that islets from autoantibody positive (single(s) or multiple(m) AAb+) donors exhibited activation of post-transcriptional gene regulation along with reduced protein translation, processing in the endoplasmic reticulum (ER), and ER stress. Disrupted mitochondrial metabolism and bioenergetics were prominent in islets from multiple AAb+ and T1D donors with disease durations [≤]7 years. In addition, T1D islets presented reduced mitochondrial protein import, quality control, and dynamics, together with downregulated genes in insulin secretory pathways. During infiltration, these pathways remain dysregulated while immune/inflammatory transcripts were increased. These studies identified novel mechanisms of {beta}-cell dysregulation before symptomatic onset and independent of T-cell infiltration in T1D pathogenesis.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
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