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Gene Therapy Using Efficient Direct Lineage Reprogramming Technology for Neurological Diseases

Authors :
Yujung Chang
Sungwoo Lee
Jieun Kim
Chunggoo Kim
Hyun Soo Shim
Seung Eun Lee
Hyeok Ju Park
Jeongwon Kim
Soohyun Lee
Yong Kyu Lee
Sungho Park
Junsang Yoo
Source :
Nanomaterials, Vol 13, Iss 10, p 1680 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Gene therapy is an innovative approach in the field of regenerative medicine. This therapy entails the transfer of genetic material into a patient’s cells to treat diseases. In particular, gene therapy for neurological diseases has recently achieved significant progress, with numerous studies investigating the use of adeno-associated viruses for the targeted delivery of therapeutic genetic fragments. This approach has potential applications for treating incurable diseases, including paralysis and motor impairment caused by spinal cord injury and Parkinson’s disease, and it is characterized by dopaminergic neuron degeneration. Recently, several studies have explored the potential of direct lineage reprogramming (DLR) for treating incurable diseases, and highlighted the advantages of DLR over conventional stem cell therapy. However, application of DLR technology in clinical practice is hindered by its low efficiency compared with cell therapy using stem cell differentiation. To overcome this limitation, researchers have explored various strategies such as the efficiency of DLR. In this study, we focused on innovative strategies, including the use of a nanoporous particle-based gene delivery system to improve the reprogramming efficiency of DLR-induced neurons. We believe that discussing these approaches can facilitate the development of more effective gene therapies for neurological disorders.

Details

Language :
English
ISSN :
20794991
Volume :
13
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Nanomaterials
Publication Type :
Academic Journal
Accession number :
edsdoj.65f150bd79ff4c7c9a5c473841551e8d
Document Type :
article
Full Text :
https://doi.org/10.3390/nano13101680