PATHOGENESIS OF DEMENTIA--A MULTI-FACTORIAL APPROACH

尽管阿尔茨海默病(AD)的典型特征是 痴呆症与各种神经病理特征有关，它是 很可能没有一个单独的病理变化是基础 对于认知和行为障碍。在这项提案中，我们 假设痴呆症的发病机制包括 数量和可变的神经元胞体和突触损失 在多个大脑结构中同时发生以达到某个阈值 导致痴呆症的损失，特别是当与 老化过程。为了证实痴呆症的多因素病因，我们 将确定在被诊断为 通过将它们与阿尔茨海默病患者的大脑进行比较，得出阿尔茨海默病患者的痴呆 认知正常的老年受试者。 连续的一系列组织切片将由神经元制备 已知的涉及认知和行为功能的区域， 包括海马复合体、杏仁核、部分额叶和 颞叶和Meynert基底核。作为…的标志 突触终末，我们将验证和扩大抗体的使用 突触素。使用这些免疫组织化学方法和标准 组织化学技术，我们将确定损失的数量和/或 突触终末和神经元胞体的密度。要确定 神经丧失的程度是产生痴呆症的必要条件和充分条件， 我们将量化AD患者与对照组相比的缺陷，使用 图像分析系统。从第2年开始，我们将与 其他MADRC实验室通过量化来扩展数据集 阿尔茨海默病的药理和生化损失。我们将在统计上 使用多变量方法分析积累的数据 表征导致的多个位点的累积神经损失 在AD的痴呆症中。

Although Alzheimer's Disease (AD) is characterized classically by dementia associated with a variety of neuropathologic features, it is likely that there is no single pathologic change that alone is the basis for the cognitive and behavioral impairment. In this proposal, we hypothesize that the pathogenetic mechanism for dementia involves quantitative and variable neuronal cell body and synaptic losses occurring concurrently in multiple brain structures to reach a threshold of loss that results in dementia, especially when combined with the aging process. To substantiate multifactorial origins of dementia, we will identify losses that occur in the brains of patients diagnosed as having dementia due to AD by comparing them with the brains of cognitively normal aged subjects. Consecutive series of tissue sections will be prepared form neuronal regions known to be involved in cognitive and behavioral function, including the hippocampal complex, amygdala, portions of the frontal and temporal lobes, and the nucleus basalis of Meynert. As a marker of synaptic terminals, we will validate and extend the use of antibodies to synapsin. Using these immunohistochemical methods and standard histochemical techniques, we will identify losses in the number and/or density of synaptic terminals and neuronal cell bodies. To determine the extent of neural loss necessary and sufficient to produce dementia, we will quantify deficits in AD patients compared to controls using an image analysis system. Starting in year 2, we will collaborate with other MADRC laboratories to expand the data set by quantifying pharmacologic and biochemical losses in AD. We will statistically analyze the accumulated data with a multivariate approach to characterize the cumulative neural losses in multiple loci that result in the dementia of AD.