FB2025_01 , released February 20, 2025
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Wang, Y., Wang, Y., Sui, Y., Yu, H., Shen, X., Chen, S., Pei, G., Zhao, J., Ding, J. (2015). The combination of aricept with a traditional chinese medicine formula, smart soup, may be a novel way to treat Alzheimer's disease.  J. Alzheimers Dis. 45(4): 1185--1195.
FlyBase ID
FBrf0228057
Publication Type
Research paper
Abstract
Alzheimer's disease (AD) is a common neurodegenerative disease affecting cognitive function in the elderly, which is characterized by the presence of extracellular deposits of insoluble amyloid-β plaques and neuronal loss. Modern pharmacology and drug development usually follow a single-target principle, which might contribute to the failure of most compounds in clinical trials against AD. Considering AD is a multifactorial disease, a combination therapeutic strategy that applies drugs with different mechanisms would be an alternative way. Smart Soup (SS), a Traditional Chinese Medicine formula, is composed of three herbaceous plants and has been applied in the treatment of amnesia in China for hundreds of years. In this work, we studied the clinical potency of the combination of SS and Aricept in AD therapy. In the in vivo model, both longevity and locomotive activity of AD transgenic Drosophila were improved remarkably in the combined medicine treated group. We also observed less amyloid-β deposition and retarded neuronal loss following the combined drug treatment. In the retrospective cohort study, we found the combination therapy exerted better therapeutic effect on AD patients. Our study revealed that combination therapy with multiple drug targets did have a better therapeutic outcome. It provides a new strategy to develop an optimum pharmaceutical approach against AD.
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    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    J. Alzheimers Dis.
    Title
    Journal of Alzheimer's disease : JAD
    ISBN/ISSN
    1387-2877
    Data From Reference
    Chemicals (2)
    Genes (2)
    Human Disease Models (1)