Spontaneous and familial models of Alzheimer's disease: Challenges and advances in preclinical research

疾病 神经科学 病因学 医学 临床试验 阿尔茨海默病 转化研究 生物信息学 心理学 生物 病理
作者
Suryapriya Ulaganathan,Arunkumar Pitchaimani
出处
期刊:Life Sciences [Elsevier BV]
卷期号:328: 121918-121918 被引量:9
标识
DOI:10.1016/j.lfs.2023.121918
摘要

Alzheimer's disease (AD) is a debilitating neurodegenerative disorder that is progressive and irreversible in nature. Even after decades of dedicated research and paradigm-shifting hypotheses of AD etiology, very few well-founded credible improvements have been foreseen in understanding the actual underlying mechanisms involved in the development of the disorder. As for any disease to be well-comprehended, AD also requires optimal modelling strategies, which will then pave way for effective therapeutic interventions. Most of the clinical trials and research towards better treatment of AD fail in translation, due to the inefficacy of explored animal models to mimic the actual AD pathology precisely. The majority of the existing AD models are developed based on the mutations found in the familial form of AD (fAD) which accounts for less than 5 % of the incidence of AD. Further, the investigations also face more challenges due to the additional complexities and lacunae found in etiology of sporadic form of AD (sAD), which accounts for 95 % of total AD. This review illustrates the gaps found in different models of AD, both sporadic and familial variants with additional focus on recent avenues for accurate simulation of AD pathology using in vitro and chimeric AD models.
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