Lifecourse CVD Risk and Midlife Cognitive Trajectories and Brain Aging: Implications for Alzheimer's and Dementia Prevention

摘要 血管健康已成为阿尔茨海默病及相关疾病最重要的决定因素之一 痴呆症。早期成人和中年心血管疾病 (CVD) 危险因素和亚临床疾病可能是 中年时期认知能力下降的重要驱动因素，这一时期很可能对影响晚年生活至关重要 痴呆症风险。然而，很少有研究调查成年早期 CVD 风险暴露，包括发病时间 暴露以及阈下水平是否影响以后的生活认知。为了实现这些目标，我们建议， 将认知测试添加到正在进行的多站点冠状动脉风险开发的第 35 年访视中 年轻人（CARDIA）研究。在基线时，CARDIA 招募了 5,115 名黑人和白人参与者（平均年龄 24) 已被仔细随访 30 年，并在第 25 和 30 年就诊时进行了认知测试。 认知 35 岁时的评估将使我们能够确定 10 年关键时刻的认知变化（平均年龄 50 至 60 岁） 认知能力下降开始出现分化并可能影响晚年痴呆风险的时间点。我们的具体目标 是： 1) 使用生命历程方法确定 10 年中年认知的独立关联 随 CVD 危险因素（包括体重）的时间、水平（阈下和阈值）和趋势而下降 指数、血压和空腹血糖，评估从早期成人到中年的 35 年； 2）确定 随着时间的推移，10 年中年认知能力下降与新的亚临床 CVD 标志物的关联，包括 颈动脉内膜厚度、冠状动脉钙化情况及心功能； 3）判断是否有CVD 危险因素和亚临床 CVD 标志物与中年大脑老化指数相关，由 机器学习神经成像模式分析在脑 MRI 和扩散张量成像数据中的应用 近 700 名中年 CARDIA 参与者获得的结果；探索性）评估 10- 中黑人/白人的差异 年认知能力下降，并确定这种差异在多大程度上可以用 CVD 风险负担来解释。 在强有力的初步数据的指导下，我们的主要假设是，CVD 危险因素很早就开始产生影响。 在生命的第三个十年，阈下水平（例如收缩压≥120毫米）很重要 为此的驱动程序。此外，我们假设亚临床 CVD 测量（尤其是心功能和 动脉粥样硬化）与中年认知能力大幅下降和大脑加速老化有关。没有其他 美国的一项研究对多种早期成人 CVD 危险因素拥有如此全面的数据， 影响认知老化。作为一个经验丰富的多学科团队，使用创新的统计方法 分析有关早期成人和中年 CVD 危险因素和亚临床疾病的基本独特的纵向数据， 我们有机会研究这些生命历程暴露与认知能力下降的关联 和中年的大脑健康。在生命历程的早期识别痴呆症危险因素可能会导致干预措施 有助于维持健康的大脑老化并预防痴呆症的发生。

ABSTRACT Vascular health has emerged as one of the most important determinants of Alzheimer's disease and related dementias. Early adult and midlife cardiovascular disease (CVD) risk factors and subclinical disease may be important drivers of cognitive decline in midlife, a period that most likely is critical for influencing later life dementia risk. Yet, few studies have investigated early adulthood CVD risk exposures, including timing of exposure and whether subthreshold levels impact later life cognition. To accomplish these goals, we propose, to add cognitive testing to the Year 35 visit of the ongoing multisite Coronary Artery Risk Development in Young Adults (CARDIA) study. At baseline, CARDIA enrolled 5,115 black and white participants (mean age 24) who have been carefully followed for 30 years and had cognitive testing at visit years 25 and 30. Cognitive evaluation at Year 35 will allow us to determine 10-year cognitive change (mean age 50 to 60) at a critical time point when cognitive decline starts to diverge and potentially impacts late-life dementia risk. Our specific aims are: 1) To determine, using a life-course approach, the independent associations of 10-year midlife cognitive decline with timing, level (both subthreshold and threshold) and trend in CVD risk factors including body mass index, blood pressure, and fasting glucose, assessed over 35 years from early adult to midlife; 2) To determine the association of 10-year midlife cognitive decline with novel subclinical CVD markers over time including carotid artery intima thickness, coronary artery calcification and cardiac function; 3) To determine whether CVD risk factors and subclinical CVD markers are associated with brain aging indices in midlife, derived by the application of machine-learning neuroimaging pattern analysis to brain MRI and diffusion tensor imaging data obtained on nearly 700 CARDIA participants at midlife; Exploratory) To assess black/white disparities in 10- year cognitive decline and determine the extent to which such disparities are explained by burden of CVD risk. Guided by strong preliminary data, our main hypothesis is that CVD risk factors begin to exert influence as early as the third decade of life and that subthreshold levels (eg systolic blood pressure ≥120 mm) are important drivers for this. In addition, we hypothesize that subclinical CVD measures (especially cardiac function and atherosclerosis) are associated with greater decline in midlife cognition and accelerated brain aging. No other study in the US has such comprehensive data on a wide array of early adult CVD risk factors that may influence cognitive aging. As an experienced multidisciplinary team using innovative statistical methods to analyze essentially unique longitudinal data on early adult and midlife CVD risk factors and subclinical disease, we have the opportunity to investigate the associations of these life-course exposures with cognitive decline and brain health in midlife. Identifying dementia risk factors early in the life-course may lead to interventions to help maintain healthy brain aging and prevent the onset of dementia.