Pathogenic Pathways in Early-Onset Autosomal Recessive Parkinson's Disease Discovered Using Isogenic Human Dopaminergic Neurons

Tim Ahfeldt, Alban Ordureau, Christina Bell, Lily Sarrafha, Chicheng Sun, Silvia Piccinotti, Tobias Grass, Gustavo M. Parfitt, Joao A. Paulo, Fumiki Yanagawa, Takayuki Uozumi, Yasujiro Kiyota, J. Wade Harper, Lee L. Rubin

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

Parkinson's disease (PD) is a complex and highly variable neurodegenerative disease. Familial PD is caused by mutations in several genes with diverse and mostly unknown functions. It is unclear how dysregulation of these genes results in the relatively selective death of nigral dopaminergic neurons (DNs). To address this question, we modeled PD by knocking out the PD genes PARKIN (PRKN), DJ-1 (PARK7), and ATP13A2 (PARK9) in independent isogenic human pluripotent stem cell (hPSC) lines. We found increased levels of oxidative stress in all PD lines. Increased death of DNs upon differentiation was found only in the PARKIN knockout line. Using quantitative proteomics, we observed dysregulation of mitochondrial and lysosomal function in all of the lines, as well as common and distinct molecular defects caused by the different PD genes. Our results suggest that precise delineation of PD subtypes will require evaluation of molecular and clinical data. In this article, Ahfeldt, Rubin, and colleagues model Parkinson's disease (PD) in human pluripotent stem cells by knocking out PARKIN, DJ-1, or ATP13A2. They report increased levels of oxidative stress in all PD lines and death of dopaminergic neurons in the PARKIN-KO. Using transcriptomics and quantitative proteomics approaches they determine common and distinct molecular defects caused by different PD genes.

Original languageEnglish
Pages (from-to)75-90
Number of pages16
JournalStem Cell Reports
Volume14
Issue number1
DOIs
StatePublished - 14 Jan 2020

Keywords

  • ATP13A2
  • CRISPR
  • DJ1
  • Parkin
  • Parkinson's disease
  • disease modeling
  • genome editing
  • human pluripotent stem cells
  • proteomics
  • transcriptomics

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