Journal
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
Volume 21, Issue 2, Pages -Publisher
MDPI
DOI: 10.3390/ijms21020493
Keywords
Alzheimer's disease; quercetin; neuroprotective effects; animal AD models
Funding
- Science and Technology Development Fund, Macau SAR [FDCT-0110/2018/A3, FDCT-024-2017-AMJ, FDCT-092-2015-A3]
- China Natural Science Foundation of China, NSFC [NSFC-31500831]
- University of Macau [MYRG2016-0019-ICMS-QRCM, MYRG2019-00129-ICMS]
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Alzheimer's disease (AD) is the leading cause of dementia worldwide. It involves progressive impairment of cognitive function. A growing number of neuroprotective compounds have been identified with potential anti-AD properties through in vitro and in vivo models of AD. Quercetin, a natural flavonoid contained in a wide range of plant species, is repeatedly reported to exert neuroprotective effects in experimental animal AD models. However, a systematic analysis of methodological rigor and the comparison between different studies is still lacking. A systematic review uses a methodical approach to minimize the bias in each independent study, providing a less biased, comprehensive understanding of research findings and an objective judgement of the strength of evidence and the reliability of conclusions. In this review, we identified 14 studies describing the therapeutic efficacy of quercetin on animal AD models by electronic and manual retrieval. Some of the results of the studies included were meta-analyzed by forest plot, and the methodological quality of each preclinical trial was assessed with SYRCLE's risk of bias tool. Our results demonstrated the consistent neuroprotective effects of quercetin on different AD models, and the pharmacological mechanisms of quercetin on AD models are summarized. This information eliminated the bias of each individual study, providing guidance for future tests and supporting evidence for further implementation of quercetin into clinical trials. However, the limitations of some studies, such as the absence of sample size calculations and low method quality, should also be noted.
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