GWAS of the RDoC Cognitive Systems Domain: Modeling the Latent Genetic Architecture of Working Memory

项目摘要/摘要 RDoC认知系统领域的GWAS：对工作记忆的潜在遗传结构进行建模 该应用程序是对NIMH PAR-17-158《探索NIMH研究领域的二次数据分析》的响应 Criteria RDoC(R03)。这项拟议的两年研究将使用现有的全基因组关联研究(GWAS)数据，这些数据来自 认知基因组学联合会(COGGENT)研究工作记忆的潜在分子遗传结构。 工作记忆是RDoC认知系统领域的核心结构，被定义为主动维护和灵活 以能力有限且不受干扰的形式更新目标/任务相关信息。有限的工作 记忆能力是许多神经精神障碍中普遍存在的认知障碍的一个基本方面。大部分 一般工作记忆容量差异背后的变异性可以追溯到遗传因素。 然而，我们的DNA究竟是如何塑造工作记忆系统的，还有待于建立。因此，我们的目标是 识别工作记忆背后的全基因组等位基因变异谱--从单个基因座到基因再到多基因 功能生物学途径的风险分数--被确定为与工作记忆有关的因果关系，而不仅仅是相关关系 性能。为了实现我们的研究目标，我们将实施一种新的多变量GWAS方法，基因组结构 方程建模(基因组扫描电子显微镜；格罗辛格等人)。Nat Hum Behav 2019)，以进行工作的公共因素GWA 记忆识别全基因组显著基因座对遗传衍生的一般潜在工作记忆因子的影响 (“Gwm”)。我们有关于24,000名有说服力的参与者的个人层面的GWAS数据，他们贡献了100,000 基于性能的工作记忆数据点来自客观的临床和实验室任务，例如数字广度、空间广度 字母数字排序和N-Back。然后，在全基因组范围内，我们将建立共享遗传结构的范围 工作记忆和相关的中枢神经系统表型之间的关系，并预计会出现广泛的一致性。在分子层面 水平，孟德尔随机化将决定工作之间显著多变的因果关系的方向 记忆和相关的中枢神经系统表型，如ADHD、自闭症和精神分裂症。最后，确定工作记忆的优先顺序 后续研究的基因座、功能图谱和注释工具将描述因果机制的生物学特征 与工作记忆有关。据我们所知，这将是世界上最全面和统计上最强大的 工作记忆。结果将公开和迅速地与研究界分享。通过破译原因 等位基因变异扰乱或保护工作记忆系统的途径，这反过来又可以扰乱或 支持工作记忆下神经系统的开发和功能，我们可以利用现有的RDoC 数据集增强了以分子遗传学为坚实基础的工作记忆的理论和神经生物学模型 用于后续的功能和机制研究。

Project Summary/Abstract GWAS of the RDoC Cognitive Systems Domain: Modeling the Latent Genetic Architecture of Working Memory This application is in response to NIMH PAR-17-158, “Secondary Data Analyses to Explore NIMH Research Domain Criteria RDoC (R03).” The proposed two-year study will use existing genome-wide association study (GWAS) data from the Cognitive Genomics Consortium (COGENT) to investigate the latent molecular genetic architecture of working memory. Working memory is a core Construct of the RDoC Cognitive Systems Domain, defined as the active maintenance and flexible updating of goal/task relevant information in a form that has limited capacity and resists interference. Limited working memory capacity is a fundamental aspect of the cognitive impairments prevalent in many neuropsychiatric disorders. Most of the variability underlying differences in general working memory capacity can be traced back to inherited genetic factors. However, exactly how our DNA shapes the working memory system has yet to be established. As such, our objective is to identify the spectrum of genome-wide allelic variation underlying working memory – from individual loci to genes to polygenic risk scores to functional biological pathways – determined to be causal, not merely correlational, in relation to working memory performance. To accomplish our goals for the study, we will implement a new multivariate GWAS method, genomic structural equation modeling (Genomic SEM; Grotzinger, et al. Nat Hum Behav 2019), to conduct a common factor GWAS of working memory to identify genome-wide significant loci with effects on a genetically-derived general latent working memory factor (“Gwm”). We have individual-level GWAS data on 24,000 participants in COGENT who have contributed 100,000 performance-based working memory datapoints from objective clinical and laboratory tasks such as digit span, spatial span, letter-number sequencing, and N-back. At genome-wide scale, we will then establish the range of shared genetic architecture between working memory and correlated CNS phenotypes, and expect widespread coheritability to emerge. At the molecular level, Mendelian randomization will determine the direction of causality underlying significant pleiotropy between working memory and correlated CNS phenotypes such as ADHD, autism, and schizophrenia. Finally, to prioritize working memory loci for follow-up studies, functional mapping and annotation tools will characterize the biology of causal mechanisms associated with working memory. To our knowledge, this will be the most comprehensive and statistically powerful GWAS of working memory. The results are to be openly and rapidly shared with the research community. By deciphering the causal pathways through which allelic variation either perturbs or protects the working memory system, which in turn can disrupt or support the development and function of neural systems underlying working memory, we can leverage this existing RDoC dataset to enhance theoretical and neurobiological models of working memory more solidly grounded in molecular genetics for follow-up functional and mechanistic studies.