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Molecular Neurodegeneration
Published in: Molecular Neurodegeneration 1/2024

Open Access 01-12-2024 | Alzheimer's Disease | Review

Updates on mouse models of Alzheimer’s disease

Authors: Michael Z. Zhong, Thomas Peng, Mariana Lemos Duarte, Minghui Wang, Dongming Cai

Published in: Molecular Neurodegeneration | Issue 1/2024

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Abstract

Alzheimer’s disease (AD) is the most common neurodegenerative disease in the United States (US). Animal models, specifically mouse models have been developed to better elucidate disease mechanisms and test therapeutic strategies for AD. A large portion of effort in the field was focused on developing transgenic (Tg) mouse models through over-expression of genetic mutations associated with familial AD (FAD) patients. Newer generations of mouse models through knock-in (KI)/knock-out (KO) or CRISPR gene editing technologies, have been developed for both familial and sporadic AD risk genes with the hope to more accurately model proteinopathies without over-expression of human AD genes in mouse brains. In this review, we summarized the phenotypes of a few commonly used as well as newly developed mouse models in translational research laboratories including the presence or absence of key pathological features of AD such as amyloid and tau pathology, synaptic and neuronal degeneration as well as cognitive and behavior deficits. In addition, advantages and limitations of these AD mouse models have been elaborated along with discussions of any sex-specific features. More importantly, the omics data from available AD mouse models have been analyzed to categorize molecular signatures of each model reminiscent of human AD brain changes, with the hope to guide future selection of most suitable models for specific research questions to be addressed in the AD field.
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Metadata
Title
Updates on mouse models of Alzheimer’s disease
Authors
Michael Z. Zhong
Thomas Peng
Mariana Lemos Duarte
Minghui Wang
Dongming Cai
Publication date
01-12-2024
Publisher
BioMed Central
Published in
Molecular Neurodegeneration / Issue 1/2024
Electronic ISSN: 1750-1326
DOI
https://doi.org/10.1186/s13024-024-00712-0

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