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

项目总结/摘要。改善阿尔茨海默病（AD）治疗的努力正在开始 专注于早期识别，因为诊断处于轻度认知障碍（MCI）阶段的个体 可以改善患者的生活质量，并大大减少疾病的经济影响。认知 中年评估提供了理想的早期预测或筛选，因为它们成本低， 侵入性工具虽然MCI和AD的预测研究通常集中在情景记忆上，但执行记忆的预测研究仍然存在。 功能（EF）是非常重要的，因为它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时最先衰退的区域。 事实上，在MCI和AD中存在明显的EF缺陷，但很少有研究检查这些关联 纵向。我们认为，EF缺陷可以出现早（或更早）比记忆缺陷， 进展为MCI和AD。我们将评估EF和记忆作为中年MCI的预测因子， 与另一个有前途的早期指标- AD多基因评分（Aim 1）相结合。遗传风险评分可能 在前瞻性研究中变得非常有用，因为基因分型程序也是非侵入性的， 在生活中的任何时候。具体来说，我们将研究认知测量是否能更强地预测MCI， AD遗传风险评分高的个体。我们还将研究其他早期生活因素（认知） 保留）阐明了EF、白色物质和中年AD遗传风险之间的关联（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，任务集转移， 工作记忆和语言流畅性）以及其他认知能力（包括 记忆），健康和心血管因素。早期成人的一般认知能力（N=1552;我们的代理， 认知储备）和基因分型（N=1162）可用于大多数个体。白色物质数据也是 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。这项工作还将导致发展 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 / ABSTRACT. 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.