Unknown

Dataset Information

0

Modeling G2019S-LRRK2 Sporadic Parkinson's Disease in 3D Midbrain Organoids.


ABSTRACT: Recent advances in generating three-dimensional (3D) organoid systems from stem cells offer new possibilities for disease modeling and drug screening because organoids can recapitulate aspects of in vivo architecture and physiology. In this study, we generate isogenic 3D midbrain organoids with or without a Parkinson's disease-associated LRRK2 G2019S mutation to study the pathogenic mechanisms associated with LRRK2 mutation. We demonstrate that these organoids can recapitulate the 3D pathological hallmarks observed in patients with LRRK2-associated sporadic Parkinson's disease. Importantly, analysis of the protein-protein interaction network in mutant organoids revealed that TXNIP, a thiol-oxidoreductase, is functionally important in the development of LRRK2-associated Parkinson's disease in a 3D environment. These results provide proof of principle for the utility of 3D organoid-based modeling of sporadic Parkinson's disease in advancing therapeutic discovery.

SUBMITTER: Kim H 

PROVIDER: S-EPMC6410341 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

altmetric image

Publications

Modeling G2019S-LRRK2 Sporadic Parkinson's Disease in 3D Midbrain Organoids.

Kim Hongwon H   Park Hyeok Ju HJ   Choi Hwan H   Chang Yujung Y   Park Hanseul H   Shin Jaein J   Kim Junyeop J   Lengner Christopher J CJ   Lee Yong Kyu YK   Kim Jongpil J  

Stem cell reports 20190221 3


Recent advances in generating three-dimensional (3D) organoid systems from stem cells offer new possibilities for disease modeling and drug screening because organoids can recapitulate aspects of in vivo architecture and physiology. In this study, we generate isogenic 3D midbrain organoids with or without a Parkinson's disease-associated LRRK2 G2019S mutation to study the pathogenic mechanisms associated with LRRK2 mutation. We demonstrate that these organoids can recapitulate the 3D pathologica  ...[more]

Similar Datasets

2019-02-02 | GSE125234 | GEO
| PRJNA515615 | ENA
| S-EPMC6450999 | biostudies-literature
2020-05-01 | GSE133894 | GEO
| S-EPMC6563926 | biostudies-literature
| S-EPMC10913847 | biostudies-literature
| S-EPMC8248170 | biostudies-literature
| S-EPMC7248385 | biostudies-literature
| S-EPMC2761091 | biostudies-literature
| S-EPMC5886254 | biostudies-other