Parkinson's Disease Phenotypes in Patient Neuronal Cultures and Brain Organoids Improved by 2-Hydroxypropyl-ß-Cyclodextrin Treatment.

BACKGROUND: The etiology of Parkinson's disease (PD) is only partially understood despite the fact that environmental causes, risk factors, and specific gene mutations are contributors to the disease. Biallelic mutations in the phosphatase and tensin homolog (PTEN)-induced putative kinase 1 (PINK1) gene involved in mitochondrial homeostasis, vesicle trafficking, and autophagy are sufficient to cause PD. OBJECTIVES: We sought to evaluate the difference between controls' and PINK1 patients' derived neurons in their transition from neuroepithelial stem cells to neurons, allowing us to identify potential pathways to target with repurposed compounds. METHODS: Using two-dimensional and three-dimensional models of patients' derived neurons we recapitulated PD-related phenotypes. We introduced the usage of midbrain organoids for testing compounds. Using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated protein 9 (Cas9), we corrected the point mutations of three patients' derived cells. We evaluated the effect of the selected compound in a mouse model. RESULTS: PD patient-derived cells presented differences in their energetic profile, imbalanced proliferation, apoptosis, mitophagy, and a reduced differentiation efficiency to tyrosine hydroxylase positive (TH+) neurons compared to controls' cells. Correction of a patient's point mutation ameliorated the metabolic properties and neuronal firing rates as well as reversing the differentiation phenotype, and reducing the increased astrocytic levels. Treatment with 2-hydroxypropyl-ß-cyclodextrin increased the autophagy and mitophagy capacity of neurons concomitant with an improved dopaminergic differentiation of patient-specific neurons in midbrain organoids and ameliorated neurotoxicity in a mouse model. CONCLUSION: We show that treatment with a repurposed compound is sufficient for restoring the impaired dopaminergic differentiation of PD patient-derived cells. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Impaired neuron differentiation in GBA-associated Parkinson's disease is linked to cell cycle defects in organoids.

The mechanisms underlying Parkinson's disease (PD) etiology are only partially understood despite intensive research conducted in the field. Recent evidence suggests that early neurodevelopmental defects might play a role in cellular susceptibility to neurodegeneration. To study the early developmental contribution of GBA mutations in PD we used patient-derived iPSCs carrying a heterozygous N370S mutation in the GBA gene. Patient-specific midbrain organoids displayed GBA-PD relevant phenotypes such as reduction of GCase activity, autophagy impairment, and mitochondrial dysfunction. Genome-scale metabolic (GEM) modeling predicted changes in lipid metabolism which were validated with lipidomics analysis, showing significant differences in the lipidome of GBA-PD. In addition, patient-specific midbrain organoids exhibited a decrease in the number and complexity of dopaminergic neurons. This was accompanied by an increase in the neural progenitor population showing signs of oxidative stress-induced damage and premature cellular senescence. These results provide insights into how GBA mutations may lead to neurodevelopmental defects thereby predisposing to PD pathology.

Machine learning-assisted neurotoxicity prediction in human midbrain organoids.

INTRODUCTION: Brain organoids are highly complex multi-cellular tissue proxies, which have recently risen as novel tools to study neurodegenerative diseases such as Parkinson's disease (PD). However, with increasing complexity of the system, usage of quantitative tools becomes challenging. OBJECTIVES: The primary objective of this study was to develop a neurotoxin-induced PD organoid model and to assess the neurotoxic effect on dopaminergic neurons using microscopy-based phenotyping in a high-content fashion. METHODS: We describe a pipeline for a machine learning-based analytical method, allowing for detailed image-based cell profiling and toxicity prediction in brain organoids treated with the neurotoxic compound 6-hydroxydopamine (6-OHDA). RESULTS: We quantified features such as dopaminergic neuron count and neuronal complexity and built a machine learning classifier with the data to optimize data processing strategies and to discriminate between different treatment conditions. We validated the approach with high content imaging data from PD patient derived midbrain organoids. CONCLUSIONS: The here described model is a valuable tool for advanced in vitro PD modeling and to test putative neurotoxic compounds.