PATHOGENESIS OF DEMENTIA--A MULTI-FACTORIAL APPROACH

痴呆症的发病机制——多因素研究

• 批准号: 3790068
• 负责人: JAMES E HAMOS
• 金额: --
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/3790068
• 关键词: Alzheimer's disease; aging; amygdala; brain mapping; enzyme linked immunosorbent assay; hippocampus; histochemistry /cytochemistry; human tissue; image processing; immunocytochemistry; immunoelectron microscopy; locus coeruleus; neural degeneration; neuritic plaques; neurofibrillary tangles; neurons; pathology; postmortem; soma; substantia innominata; synapses; synapsins; temporal lobe /cortex; thalamic nuclei

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.

尽管阿尔茨海默病（AD）的典型特征是