Department of Neuroscience, Psychology, Drug Research, and Child Health (NEUROFARBA), University of Florence, Florence, Italy.
IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
Physiol Rev. 2021 Jul 1;101(3):1047-1081. doi: 10.1152/physrev.00015.2020. Epub 2021 Jan 21.
The history of Alzheimer's disease (AD) started in 1907, but we needed to wait until the end of the century to identify the components of pathological hallmarks and genetic subtypes and to formulate the first pathogenic hypothesis. Thanks to biomarkers and new technologies, the concept of AD then rapidly changed from a static view of an amnestic dementia of the presenium to a biological entity that could be clinically manifested as normal cognition or dementia of different types. What is clearly emerging from studies is that AD is heterogeneous in each aspect, such as amyloid composition, tau distribution, relation between amyloid and tau, clinical symptoms, and genetic background, and thus it is probably impossible to explain AD with a single pathological process. The scientific approach to AD suffers from chronological mismatches between clinical, pathological, and technological data, causing difficulty in conceiving diagnostic gold standards and in creating models for drug discovery and screening. A recent mathematical computer-based approach offers the opportunity to study AD in real life and to provide a new point of view and the final missing pieces of the AD puzzle.
阿尔茨海默病（AD）的历史可以追溯到 1907 年，但我们需要等到世纪末才能确定病理特征和遗传亚型的组成部分，并提出第一个致病假说。由于生物标志物和新技术的出现，AD 的概念迅速从一种关于早老期遗忘型痴呆的静态观点转变为一种可以在临床上表现为不同类型的正常认知或痴呆的生物学实体。从研究中明显出现的是，AD 在各个方面都是异质的，如淀粉样蛋白组成、tau 分布、淀粉样蛋白与 tau 之间的关系、临床症状和遗传背景，因此，用单一的病理过程来解释 AD 可能是不可能的。AD 的科学研究方法受到临床、病理和技术数据在时间上不匹配的影响，这使得难以构思出诊断的金标准，并为药物发现和筛选创建模型。最近一种基于数学计算机的方法为在现实生活中研究 AD 提供了机会，并为 AD 拼图提供了一个新的视角和最后缺失的部分。
