The Role of Executive Functions in Cognitive Aging and Risk for Mild Cognitive Impairment

项目摘要 改善阿尔茨海默病（AD）治疗的努力开始集中在早期识别上 因为诊断轻度认知障碍（MCI）阶段的个体可以改善患者的 并大大减少疾病的经济影响。中年的认知评估提供了 理想的早期预测器或筛选器，因为它们是低成本和非侵入性工具。虽然预测 MCI和AD的研究主要集中在情景记忆上，执行功能（EFs）是MCI和AD的重要功能之一。 重要性，因为他们控制和整合多个认知过程，因为他们的表现， 和相关的大脑区域是中年人最先衰退的区域之一。的确， 在MCI和AD中，EF的缺陷，但很少有研究纵向研究这些关联。我们提出 在MCI和AD的进展中，EF缺陷可以比记忆缺陷更早（或更早）出现。我们 将评估EF和记忆作为中年MCI的预测因子，并结合另一个有前途的早期MCI预测因子， 指标- AD多基因评分（目标1）。遗传风险评分在前瞻性研究中可能非常有用 因为基因分型程序也是非侵入性的，可以在生命中的任何时候进行。具体来说，我们将 检查认知测量是否在AD遗传风险高的个体中更强地预测MCI 成绩.我们还将研究其他早期生活因素（认知储备）如何阐明这种关联 EF、白色物质和中年AD遗传风险之间的关系（目的2）。 我们将检查越南时代双胞胎衰老研究的数据，该研究跟踪了大量男性双胞胎样本 在中年晚期的3个时间点（平均年龄56、62和67岁;每个波N约1200）。双胞胎完成 对所有波的EF进行广泛评估（包括多种反应抑制措施，任务集 移位、工作记忆和语言流畅性）以及其他认知能力的多项指标 （包括记忆力）、健康和心血管因素。早期成人一般认知能力（N=1552;我们的 认知储备代理）和基因分型（N=1162）可用于大多数个体。白色物质数据是 也适用于许多受试者（每个波的N约为350至400）。综合认知评估 VETSA允许在潜变量水平上检查EF和记忆，增加功率， 调查结果的普遍性。此外，样品的遗传信息性质（即，双胞胎和直接 基因分型），允许将EF和白色物质之间的关联分解为遗传和 环境的影响，并检查AD遗传风险评分在这些协会中的作用。 这个奖项将提供一个理想的机会，以促进我们对EF和认知变化的理解 在一个丰富的数据集中。由于所有研究都涉及对现有数据的二次分析， 将有足够的时间来实现这项建议的研究目标。这项工作也将导致发展 独立资助的项目（例如，R 01）旨在改善MCI和AD风险的早期识别。

PROJECT SUMMARY Efforts to improve treatment of Alzheimer’s disease (AD) are beginning to focus on early identification because diagnosing individuals in the mild cognitive impairment (MCI) stage could improve patient quality of life and substantially reduce the financial impact of the disease. Cognitive assessments in middle age provide ideal early predictors or screeners because they are low cost and non- invasive tools. Although predictive studies of MCI and AD generally focus on episodic memory, executive functions (EFs) are of substantial importance because they control and integrate multiple cognitive processes, and because their performance and associated brain regions are some of the first to decline in middle age. Indeed, there are prominent deficits in EFs in MCI and AD, but few studies have examined these associations longitudinally. We propose that EF deficits can appear as early (or earlier) than memory deficits in the progression to MCI and AD. We will evaluate EFs and memory as predictors of MCI in middle age in combination with another promising early indicator – AD polygenic scores (Aim 1). Genetic risk scores may become highly useful in prospective studies because genotyping procedures are also non-invasive and can be done anytime in life. Specifically, we will examine whether cognitive measures predict MCI more strongly in individuals with high AD genetic risk scores. We will also examine how other early life factors (cognitive reserve) elucidate the associations between EFs, white matter, and AD genetic risk in midlife (Aim 2). We will examine data from the Vietnam Era Twin Study of Aging, which follows a large sample of male twins across 3 time-points in late middle age (mean age 56, 62, and 67; N~1200 at each wave). Twins completed extensive assessment of EFs at all waves (including multiple measures of response inhibition, task-set shifting, working memory, and verbal fluency) as well as multiple measures of other cognitive abilities (including memory), health, and cardiovascular factors. Early adult general cognitive ability (N=1552; our proxy for cognitive reserve) and genotyping (N=1162) are available for most individuals. White matter data are also available for many subjects (N~ 350 to 400 at each wave). The comprehensive cognitive assessment in VETSA allows for the examination of EFs and memory at the level of latent variables, increasing power and generalizability of findings. Moreover, the genetically-informative nature of the sample (i.e., twins and direct genotyping), allows for the decomposition of associations between EFs and white matter into genetic and environmental influences, and examination of the role of AD genetic risk scores in these associations. This award will provide an ideal opportunity to advance our understanding of EFs and cognitive changes across middle age in a rich dataset. Because all research involves secondary analyses of existing data, there will be ample time to achieve the research aims of this proposal. This work will also lead to the development of independently funded projects (e.g., R01) aimed at improving early identification of MCI and AD risk.