PREDICTING COGNITIVE DECLINE IN NONDEMENTED ELDER SUBJECTS

阿尔茨海默病（AD）是老年人最常见的痴呆性疾病， 晚年的生活和生产力。未来的药物治疗可能能够减缓 疾病的进展或甚至预防其临床表现，并且当这种治疗 一旦有了新的技术，就需要有能力在疾病的最早阶段发现疾病， 其中该项目的总体目标是进一步开发和测试结构磁 共振扫描和计算神经解剖学来区分具有临床和 无病老年人的临床前AD。为此，将开展进一步研究， 通过启动对AD患者成年子女的研究，提高对非常轻度DAT受试者和非痴呆对照者的区分度。本项目的具体目标是：1）通过对海马、海马旁回和海马回的联合分析，提高对阿尔茨海默型极轻度痴呆（DAT）受试者和年龄匹配的健康对照者的区分度（包括内嗅皮层）和扣带回，2）确定神经形态测量变量是否显示出区分患有非常轻度痴呆和健康年龄的受试者-匹配的对照将预测健康老年对照中认知能力下降的速率，其中至少一些人将具有临床前形式的AD，和3）试图将AD患者的成年子女与年龄和性别匹配的对照区分开，再次使用神经形态测量学变量，显示出区分非常轻微的DAT受试者和健康的年龄匹配的对照。为了实现这些目标，将在基线和两年后使用高分辨率T1加权序列对60名患有极轻度DAT（CDR 0.5）的受试者和60名年龄匹配的非痴呆受试者（CDR 0）进行扫描。在基线和未来四年的每年，将使用一系列临床和认知测量来评估这些受试者，以确定痴呆症状和认知缺陷的存在和严重程度。AD患者及其对照的成年儿童将进行类似的评估，尽管评估之间的间隔将根据受试者的年龄而变化。神经解剖学特征，包括体积、厚度和3D构象（即，形状）将使用专门设计用于评估所选脑结构的计算机化算法进行量化。

Alzheimer's disease (AD) is the most common dementing illness of late life, and robs persons of vigorous activity and productivity in their later years. Future drug treatments may be capable of slowing the progression of the disease or even preventing the its clinical appearance, and when such treatments become available, the ability to detect the illness in its earliest stages will be needed to take full advantage of them. The overall goal of this project is to further develop and test the use of structural magnetic resonance scanning and computational neuroanatomy to distinguish subjects with both clinical and preclinical AD from elders without disease. This will be accomplished by conducting further studies to improve the discrimination of subjects with very mild DAT and nondemented controls and by initiating studies of the adult children of AD patients. The specific aims of the project are to 1) improve the discrimination of subjects with very mild dementia of the Alzheimer type (DAT) and healthy age-matched controls via the combined analysis of the hippocampus, parahippocampal gyrus (including the entorhinal cortex), and cingulate gyrus, 2) determine whether neuromorphometric variables shown to discriminate between subjects with very mild dementia and healthy age-matched controls will predict the rate of cognitive decline in the healthy elder controls, at least some of whom will have preclinical forms of AD, and 3) attempt to discriminate the adult children of AD patients from age- and gender-matched controls, again using neuromorphometric variables shown to discriminate between the very mild DAT subject and healthy age-matched controls. To accomplish these aims, 60 subjects with very mild DAT (CDR 0.5) and 60 nondemented, age-matched subjects (CDR 0) will be scanned at baseline and two years later using a high-resolution, T1-weighted sequence. At baseline and yearly for the next four years, these subjects will be assessed using a battery of clinical and cognitive measures to determine the presence and severity of dementia symptoms and cognitive deficits. Adult children of AD patients and their controls will be similarly assessed, although the intervals between assessments will vary depending upon the age of the subjects. Neuroanatomical features, including volume, thickness, and 3D conformation (i.e., shape) will be quantified using computerized algorithms specifically designed for the evaluation of the selected brain structures.