The VETSA Longitudinal MRI Twin Study of Aging (VETSA MRI 4)

项目总结/摘要 阿尔茨海默病（AD）是昂贵且负担沉重的。随着美国人口老龄化，AD对公共卫生的影响 一个继续增长NIH和阿尔茨海默氏症协会的共识声明表明， 疾病进展的各个阶段，如轻度认知障碍（MCI），从中年开始， 减缓痴呆症发作据估计，及早识别有风险的个人也会节省大量资金。 尽管AD脑病理学进展缓慢，但对其从中晚期到晚期的时间进程知之甚少。 尤其是神经影像学指标。越南时代老龄化双胞胎研究（VETSA）的重点是 在受试者50多岁时开始早期识别MCI/AD和AD相关脑变化的风险。 拟议的VETSA MRI波4项目，平均年龄为74岁（67-78岁），发生在一个时间增加， MCI/AD事件。结合我们的纵向数据，可以提高确定 神经影像学相关性、轨迹及其预测因素。持续的数据收集将使我们能够检查 从发病前到发病后的过渡期，并扩大从中年开始的预测， 个人数量。该项目与资助的一般VETSA 4赠款（AG 050595）相关联， 每例受试者10-12小时的认知、健康/医学、心理社会和生物标志物数据。此外，我们还可以 阐明遗传和环境对这些过程的影响，通过结合双胞胎和全基因组 基因分型/多基因评分数据。我们还利用早期（20岁）的认知数据，这是一个独特的功能， 使我们能够区分认知衰退和长期差异。我们要求资金支付MRI 采集、处理和分析（n=500），利用一般VETSA 4中相关的正在进行的工作 格兰特.目的是：1）开发，验证和表征MCI/AD风险的新的早期脑指标。我们将 开发和验证一种新的基于扩散MRI的AD大脑签名，并表明这种大脑签名 只有50多岁的成年人改善了对MCI进展的预测。我们还假设正直 蓝斑--tau蛋白沉积的最早大脑部位--将是另一个早期、敏感的风险指标。 2)检查脑血管危险因素及其与认知和AD生物标志物的关系。 脑血管疾病（CVD）是伴随AD的最常见病理，可能导致 疾病进展或成为大脑和认知能力下降的独立来源。我们特别关注CVD 白色物质高信号和动脉自旋标记（ASL）灌注的标志物。3)量化幅度 从中年到老年早期的神经退化及其潜在的遗传和环境影响。 我们将研究遗传对大脑宏观和微观结构测量纵向变化的影响。我们 方法包括确定风险因素在整个生命周期中的中介/调节效应， 我们的双胞胎和全基因组基因型数据。该项目将涵盖约18年， 了解MCI/AD风险的早期识别，可能对公共卫生产生深远影响。

PROJECT SUMMARY/ABSTRACT Alzheimer’s disease (AD) is costly and burdensome. As the US population ages, AD’s public health impact continues to grow. NIH and Alzheimer’s Association consensus statements indicate that understanding early phases of disease progression—such as mild cognitive impairment (MCI)—beginning in middle age is key to slowing dementia onset. Identifying at-risk individuals early is also estimated to result in massive savings. Despite the protracted progression of AD brain pathology, little is known about its temporal course from middle to older age, particularly for neuroimaging indices. The Vietnam Era Twin Study of Aging (VETSA) focuses on early identification of risk for MCI/AD and AD-related brain changes beginning when subjects were in their 50s. The proposed VETSA MRI wave 4 project, with a mean age of 74 (67-78), occurs during a time of increased incident MCI/AD. That, in combination with our longitudinal data, allows for improved ability to determine neuroimaging correlates, trajectories, and their predictors. Continued data collection will allow us to examine the transition period from pre- to post-disease onset and expand on prediction from midlife for an increasing number of individuals. This project is linked to the funded general VETSA 4 grant (AG050595) which collects 10-12 hours per subject of cognitive, health/medical, psychosocial and biomarker data. In addition, we can elucidate genetic and environmental influences on these processes via combined twin and genome-wide genotyping/polygenic score data. We also capitalize on early (age 20) cognitive data, a unique feature enabling us to differentiate cognitive decline from longstanding differences. We request funds to cover MRI acquisition, processing, and analysis (n=500), leveraging associated ongoing work in the general VETSA 4 grant. Aims are: 1) Develop, validate, and characterize novel early brain indicators of risk for MCI/AD. We will develop and validate a novel AD brain signature based on diffusion MRI and show that this brain signature of adults who are only in their 50s improves prediction of progression to MCI. We also hypothesize that integrity of the locus coeruleus—the earliest brain site of tau deposition—will be another early, sensitive risk indicator. 2) Examine cerebrovascular risk factors and their relationship with cognition and AD biomarkers. Cerebrovascular disease (CVD) is the most common pathology concomitant with AD and may contribute to disease progression or be an independent source of brain and cognitive decline. We particularly focus on CVD markers of white matter hyperintensities and arterial spin labeling (ASL) perfusion. 3) Quantify the magnitude of neurodegeneration from midlife to early old age and its underlying genetic and environmental influences. We will examine genetic influences on longitudinal change in macro- and micro-structural brain measures. Our approach includes identifying mediating/moderating effects of risk factors across the lifespan and leveraging our twin and genome-wide genotype data. Covering ~18 years, this project will be a resource for advancing knowledge about early identification of risk for MCI/AD, with potential for a profound public health impact.