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Patient-derived iPSC models of Friedreich ataxia: a new frontier for understanding disease mechanisms and therapeutic application

Abstract:
Abstract Friedreich ataxia (FRDA) is a rare genetic multisystem disorder caused by a pathological GAA trinucleotide repeat expansion in the FXN gene. The numerous drawbacks of historical cellular and rodent models of FRDA have caused difficulty in performing effective mechanistic and translational studies to investigate the disease. The recent discovery and subsequent development of induced pluripotent stem cell (iPSC) technology provides an exciting platform to enable enhanced disease modelling for studies of rare genetic diseases. Utilising iPSCs, researchers have created phenotypically relevant and previously inaccessible cellular models of FRDA. These models enable studies of the molecular mechanisms underlying GAA-induced pathology, as well as providing an exciting tool for the screening and testing of novel disease-modifying therapies. This review explores how the use of iPSCs to study FRDA has developed over the past decade, as well as discussing the enormous therapeutic potentials of iPSC-derived models, their current limitations and their future direction within the field of FRDA research. Graphical abstrac
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1186/s40035-023-00376-8

Authors

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Institution:
University of Oxford
Role:
Author
ORCID:
0000-0002-4691-2916
More by this author
Institution:
University of Oxford
Role:
Author
ORCID:
0000-0003-0110-5894
More by this author
Institution:
University of Oxford
Role:
Author
ORCID:
0000-0001-6691-580X


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Funder identifier:
10.13039/100012357
Grant:
10312
More from this funder
Funder identifier:
10.13039/501100000346


Publisher:
BioMed Central
Journal:
Translational Neurodegeneration More from this journal
Volume:
12
Issue:
1
Pages:
45-45
Article number:
45
Publication date:
2023-09-20
DOI:
EISSN:
2047-9158
ISSN:
2047-9158


Language:
English
Keywords:
Pubs id:
1536316
Local pid:
pubs:1536316
Source identifiers:
W4386877684
Deposit date:
2026-05-17
ARK identifier:
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