Animal models of Alzheimer's disease: Applications, evaluation, and perspectives

• Published in: Dōngwùxué yánjiū 2022-11, Vol.43 (6), p.1026-1040
• Main Authors: Chen, Zhi-Ya, Zhang, Yan
• Format: Article
• Language: English
• Subjects: Age; Alzheimer's disease; Animal cognition; Animal diseases; Animal models; Animals; Biomarkers; Brain research; Cognitive ability; Dementia; Dementia disorders; Diseases; Environmental factors; Genetic engineering; Memory; Mutation; Natural phenomena; Neurodegenerative diseases; Neuropathology; Pathogenesis; Pathology; Vertebrates; Yeasts
• ISSN: 0254-5853
• DOI: 10.24272/j.issn.2095-8137.2022.289

Although great advances in elucidating the molecular basis and pathogenesis of Alzheimer's disease (AD) have been made and multifarious novel therapeutic approaches have been developed, AD remains an incurable disease. Evidence shows that AD neuropathology occurs decades before clinical presentation. AD is divided into three stages: preclinical stage, mild cognitive impairment (MCI), and AD dementia. In the natural world, some animals, such as non-human primates (NHPs) and canines, can develop spontaneous AD-like dementia. However, most animals do not develop AD. With the development of transgenic techniques, both invertebrate and vertebrate animals have been employed to uncover the mechanisms of AD and study treatment methods. Most AD research focuses on early-onset familial AD (FAD) because FAD is associated with specific genetic mutations. However, there are no well-established late-onset sporadic AD (SAD) animal models because SAD is not directly linked to any genetic mutation, and multiple environmental factors are involved. Moreover, the widely used animal models are not able to sufficiently recapitulate the pathological events that occur in the MCI or preclinical stages. This review summarizes the common models used to study AD, from yeast to NHP models, and discusses the different applications, evaluation methods, and challenges related to AD animal models, as well as prospects for the evolution of future studies.