Proj 4: Genetics (197-223)

项目 4：遗传学 (197-223)

• 批准号: 8078164
• 负责人: JOHN K. HEWITT
• 金额: $ 20.7万
• 依托单位: UNIVERSITY OF COLORADO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-02-03 至 2013-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8078164
• 关键词: Adult; Age; Attention; Behavioral; Brain; Clinical; Cognition; Cognitive; Complex; Computer Simulation; Data; Data Set; Dopamine; Equation; Etiology; Factor Analysis; Foundations; Future; Genes; Genetic; Genetic Polymorphism; Goals; Human; Individual; Individual Differences; Intelligence; Lead; Learning; Literature; Measures; Modeling; Molecular Genetics; Multivariate Analysis; Neurobiology; Performance; Population; Process; Production; Public Health; Regulation; Research; Research Personnel; Role; Sampling; Short-Term Memory; Sorting - Cell Movement; Source; Specific qualifier value; Structure; Study Subject; Testing; To specify; Translational Research; Twin Multiple Birth; Update; Wisconsin; cognitive function; dopamine system; executive function; frontal lobe; genetic analysis; indexing; mental set; neuropsychological; operation; psychologic; response; young adult

Molecular genetic studies of executive functions (EFs) examining the roles of dopamine-(DA) related genes have provided some support for the widely held view that DA modulates executive control. However, these studies have had little impact on current understanding of EFs, because they have usually only examined very few DA genes and have focused on gross executive control as measured by individual frontal-lobe tests, rather than separable, theoretically defined EFs identified in the cognitive literature. The goal of this project is to use molecular genetic analyses in concert with computational modeling to specify in more detail how the DA system regulates three correlated but separable EFs - inhibiting prepotent responses, updating working memory, and shifting mental sets. In doing so, it will begin to bridge current understanding of EFs across the psychological, computational, and neurobiological levels. The primary dataset will be existing EF data from 814 individual twins aged 17. Our multivariate analyses indicate that the three EF latent variables are highly heritable and reflect both common and unique genetic influences. This project will take the important next step of specifying how different DA-related genes influence the common and unique genetic variance in EFs. Specifically, we will (1) use computational models of EF tasks to both generate predictions and incorporate results for genetic analyses, with the goal of developing more detailed models of how the DA system dynamically regulates executive control; (2) examine the extent to which polymorphisms in a large set of DA-related genes contribute to variance in each EF, and whether the contributions differ for the three EFs; and (3) conduct parallel analyses on data from identical or comparable EF tasks collected as part of three ongoing studies of subjects selected for learning, conduct, and/or attention problems. Comparison of the results for the clinically extreme groups versus unselected samples will provide an additional source of information about how DA modulates EFs and serve as a foundation for future translational research in these and other clinical samples that are currently being collected by Center investigators and their collaborators. Hence, the results of the proposed study will contribute to a better understanding of how DA modulates different EFs in normal young adults, with broad implications for public health issues related to everyday cognitive functioning and EF deficits in both healthy and clinical populations.

执行功能 (EF) 的分子遗传学研究检查多巴胺 (DA) 相关基因的作用，为广泛持有的 DA 调节执行控制的观点提供了一些支持。然而，这些研究对目前对 EF 的理解影响不大，因为它们通常只检查很少的 DA 基因，并且重点关注通过个体额叶测试测量的总体执行控制，而不是在认知文学。该项目的目标是利用分子遗传学分析与计算模型相结合，更详细地说明 DA 系统如何调节三个相关但可分离的 EF：抑制优势反应、更新工作记忆和改变心理状态。在此过程中，它将开始在心理、计算和神经生物学层面上架起目前对 EF 的理解。主要数据集将是来自 814 名 17 岁双胞胎的现有 EF 数据。我们的多变量分析表明，三个 EF 潜在变量具有高度遗传性，反映了常见和独特的遗传影响。该项目将采取重要的下一步，具体说明不同的 DA 相关基因如何影响 EF 中常见和独特的遗传变异。具体来说，我们将（1）使用 EF 任务的计算模型来生成预测并整合遗传分析的结果，目标是开发关于 DA 系统如何动态调节执行控制的更详细的模型； (2) 检查大量 DA 相关基因的多态性对每个 EF 的方差的贡献程度，以及对三个 EF 的贡献是否不同； (3) 对来自相同或类似 EF 任务的数据进行并行分析，这些数据是三项正在进行的针对学习、行为和/或注意力问题的受试者研究的一部分而收集的。临床极端组与未选择样本的结果比较将提供有关 DA 如何调节 EF 的额外信息来源，并为这些样本和中心研究人员及其合作者目前正在收集的其他临床样本的未来转化研究奠定基础。 因此，拟议研究的结果将有助于更好地了解 DA 如何调节正常年轻人的不同 EF，对健康和临床人群中与日常认知功能和 EF 缺陷相关的公共卫生问题具有广泛的影响。