Assessing the therapeutic potential of Graptopetalum paraguayense on Alzheimer's disease using patient iPSC-derived neurons

使用患者 iPSC 衍生的神经元评估 Graptopetalum paraguayense 对阿尔茨海默病的治疗潜力

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作者:Pei-Chun Wu, Ming-Ji Fann, Tu Thanh Tran, Shu-Cian Chen, Tania Devina, Irene Han-Juo Cheng, Cheng-Chang Lien, Lung-Sen Kao, Shuu-Jiun Wang, Jong-Ling Fuh, Tsai-Teng Tzeng, Chi-Ying Huang, Young-Ji Shiao, Yu-Hui Wong

Abstract

Alzheimer's disease (AD) is the most common type of dementia and also one of the leading causes of death worldwide. However, the underlying mechanisms remain unclear, and currently there is no drug treatment that can prevent or cure AD. Here, we have applied the advantages of using induced pluripotent stem cell (iPSC)-derived neurons (iNs) from AD patients, which are able to offer human-specific drug responsiveness, in order to evaluate therapeutic candidates for AD. Using approach involving an inducible neurogenin-2 transgene, we have established a robust and reproducible protocol for differentiating human iPSCs into glutamatergic neurons. The AD-iN cultures that result have mature phenotypic and physiological properties, together with AD-like biochemical features that include extracellular β-amyloid (Aβ) accumulation and Tau protein phosphorylation. By screening using a gene set enrichment analysis (GSEA) approach, Graptopetalum paraguayense (GP) has been identified as a potential therapeutic agent for AD from among a range of Chinese herbal medicines. We found that administration of a GP extract caused a significantly reduction in the AD-associated phenotypes of the iNs, including decreased levels of extracellular Aβ40 and Aβ42, as well as reduced Tau protein phosphorylation at positions Ser214 and Ser396. Additionally, the effect of GP was more prominent in AD-iNs compared to non-diseased controls. These findings provide valuable information that suggests moving extracts of GP toward drug development, either for treating AD or as a health supplement to prevent AD. Furthermore, our human iN-based platform promises to be a useful strategy when it is used for AD drug discovery.

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