Epidemiology of Dementia in the Framingham Study

描述（由申请人提供）：自1989年以来由NIA资助，痴呆流行病学研究的重点是在大型前瞻性社区Framingham研究中识别痴呆事件病例并确定与临床痴呆相关的危险因素，特别是阿尔茨海默病（AD）。从1976年至1978年建立无痴呆队列开始，本研究记录了600名痴呆患者，主要来自1948年招募的原始队列。近年来，随着原始队列（及其配偶）的子女年龄的增长，这些第2代受试者中的许多人已经被记录为认知能力下降，并且MRI标记为脑损伤以及轻度认知障碍（MCI）和痴呆。我们提供了以社区为基础的阿尔茨海默病的发病率和终生风险、中风后痴呆风险的估计，并确定了一些生活方式、血管、新型生物标志物和最近的阿尔茨海默病遗传风险因素。通过1995年建立的一项正在进行的大脑捐赠计划，我们对大约140个大脑进行了详细的神经病理学检查。在本应用中，我们将通过加强监测来识别可能患有轻度认知障碍的受试者，并将对他们进行年度评估，从而重点识别患有亚临床疾病的人。我们将把之前收集的大量风险因素与阿尔茨海默病和全痴呆的风险、阿尔茨海默病的内表型以及从轻度认知障碍到临床阿尔茨海默病的转化风险联系起来。这些风险因素包括遗传（全基因组、候选基因和基因表达）和环境（中年以来反复收集的生活方式、血管、代谢测量）数据、循环生物标志物水平和基线成像数据。对于这一系列假定的风险标记，我们建议增加：(1)一个关键的生物标记，循环β -淀粉样蛋白（A240和A242）水平；(2)第三轮定量脑MRI和NP测试，以更精确地记录变化，并区分那些具有一致的脑萎缩和认知能力下降迹象，并有最高风险过渡到MCI和/或痴呆；(3)对先前和新获得的MRI图像中的其他感兴趣区域进行详细的后处理MR分析，以增强对大脑形态随时间变化的细微变化的检测。目标是将这些新的和现有的数据纳入阿尔茨海默病和痴呆症的风险预测评分，并在独立的流行病学队列中进行验证。该风险概况的目的是确定患AD风险最高的人群，从而允许有针对性的预防和治疗干预，包括招募易感受试者进行有希望的治疗方法的临床试验。

DESCRIPTION (provided by applicant): Funded by NIA since 1989, the Epidemiology of Dementia Study has focused on identifying incident cases of dementia and determining the risk factors associated with clinical dementia, particularly Alzheimer's disease (AD) in the large prospective community-based Framingham Study. Beginning with the establishment of a dementia-free cohort in 1976-78, this study has documented >600 subjects with incident dementia, largely from the Original cohort recruited in 1948. In recent years, with the aging of the children of the Original cohort (and their spouses), a number of these Generation 2 subjects have been documented to have cognitive decline, and MRI markers of brain injury as well as Mild Cognitive Impairment (MCI) and dementia. We have provided community-based estimates of incidence and lifetime risk of AD, the risk of dementia following stroke, and have identified a number of lifestyle, vascular, novel biomarker and more recently genetic risk factors for AD. Through an ongoing brain donation program established in 1995, we have performed detailed neuropathologic examination of approximately 140 brains. In this application we will focus on identifying persons with subclinical disease by intensifying surveillance to identify subjects with probable MCI and will follow them with annual assessments. We will relate a wealth of previously collected risk factors to the risk of incident AD and all-dementia, to AD endophenotypes, and to the risk of conversion from MCI to clinical AD. These risk factors include genetic (genome-wide, candidate gene and gene expression) and environmental (lifestyle, vascular, metabolic measures gathered repeatedly since midlife) data, circulating biomarker levels and baseline imaging data. To this array of putative risk markers we propose to add: (1) a key biomarker, circulating beta-amyloid (A240 and A242) levels; (2) a third round of quantitative brain MRI and NP testing to more precisely document change, and distinguish those with consistent signs of brain atrophy and cognitive decline at highest risk of transitioning to MCI and/or dementia; and, (3) detailed post-processing MR analyses of additional regions of interest from prior and newly acquired MRI images to enhance detection of subtle changes in brain morphology over time. The goal is to incorporate these new and existing data into a risk prediction score for AD and dementia and validate it in an independent epidemiological cohort. The aim of this risk profile is to identify persons at highest risk for developing AD, thus permitting targeted preventive and therapeutic interventions, including enrollment of susceptible subjects for clinical trials of promising therapies.