Insulin resistance compromises midbrain organoid neuronal activity and metabolic efficiency predisposing to Parkinson's disease pathology

Alise Zagare, Jānis Kurlovičs, Catarina Almeida, Daniele Ferrante, Daniela Frangenberg, Armelle Vitali, Gemma Gomez-Giro, Christian Jäger, Paul Antony, Rashi Halder, Rejko Krüger, Enrico Glaab, Egils Stalidzāns, Giuseppe Arena, Jens C Schwamborn (Corresponding Author)

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
18 Downloads (Pure)

Abstract

Growing evidence indicates that type 2 diabetes (T2D) is associated with an increased risk of developing Parkinson's disease (PD) through shared disease mechanisms. Studies show that insulin resistance, which is the driving pathophysiological mechanism of T2D plays a major role in neurodegeneration by impairing neuronal functionality, metabolism and survival. To investigate insulin resistance caused pathological changes in the human midbrain, which could predispose a healthy midbrain to PD development, we exposed iPSC-derived human midbrain organoids from healthy individuals to either high insulin concentration, promoting insulin resistance, or to more physiological insulin concentration restoring insulin signalling function. We combined experimental methods with metabolic modelling to identify the most insulin resistance-dependent pathogenic processes. We demonstrate that insulin resistance compromises organoid metabolic efficiency, leading to increased levels of oxidative stress. Additionally, insulin-resistant midbrain organoids showed decreased neuronal activity and reduced amount of dopaminergic neurons, highlighting insulin resistance as a significant target in PD prevention.

Original languageEnglish
Pages (from-to)1-19
JournalJournal of Tissue Engineering
Volume16
DOIs
Publication statusPublished - 1 Jan 2025

Keywords*

  • Organoids
  • brain organoids
  • Parkinsons disease
  • diabetes
  • metabolism

Field of Science*

  • 3.3 Health sciences
  • 3.2 Clinical medicine
  • 1.6 Biological sciences

Publication Type*

  • 1.1. Scientific article indexed in Web of Science and/or Scopus database

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