Identifying and quantifying genetic effects on neurodevelopmental trajectories in adolescents

项目摘要 青春期神经发育变化的分期和节律表现出明显的个体性 然而，这种受试者之间和受试者内部的差异在多大程度上可归因于遗传因素 未知。目前对大脑结构和功能的遗传基础的理解 神经成像数据是基于对(主要是横截面的)成人样本的分析。通过从一个 发育关键期，即青春期，我们将能够确定已识别的基因 成分是不随时间变化的特征或对时间敏感的发育结果。我们的长期目标是 确定危险行为和精神障碍的潜在易感性的因果机制 出现在青春期。为了实现这一目标，我们的目标是寻找与 用多模式神经成像数据测量发育变异。我们提出了三种方法来 对青少年大脑认知发育(ABCD)数据进行无偏基因分析 研究：1)提取大脑各区域的发育变化模式；2)确定相关的遗传基因 通过跨衍生的发育多模式成像的综合全基因组关联研究 表型；3)确定精神疾病的遗传风险与 神经发育轨迹。我们将使用一种新的方法组合来实现这些目标，方法来自 群体遗传学和神经科学，同时创新地定制分析策略以避免潜在的 由于混杂和关联而产生的偏见和虚假联想。这项拟议的研究具有重要意义 因为已识别的遗传机制将为治疗学和公共卫生提供潜在的基础 干预措施，注意对ABCD数据进行流行病学指导抽样的影响。通过共享 我们在这个研究计划中开发的工具和由此产生的基因仪器，将对该领域产生影响 立即，使研究人员能够使用ABCD数据更深入地研究神经发育过程 以及他们可以访问的其他累积数据集。

Project Summary The staging and pacing of neurodevelopmental change during adolescence exhibits observable individual differences, yet how much of this between- and within-subject variation is attributable to genetic factors is unknown. Current understanding of the genetic basis for brain structure and function measured by neuroimaging data is based on analyses of (mostly cross-sectional) adult samples. By obtaining results from a developmentally-critical period, i.e. adolescence, we will be able to determine whether the identified genetic components are time-invariant traits or time-sensitive developmental results. Our long-term goal is to determine the causal mechanisms underlying vulnerabilities to risky behavior and psychiatric disorders that emerge during adolescence. To achieve this goal, we aim to search for genetic factors associated with developmental variation measured by multi-modal neuroimaging data. We propose three approaches to perform unbiased genetic analyses of data from the Adolescent Brain Cognitive Development (ABCD) study: 1) Extract patterns of developmental changes across brain regions; 2) Identify associated genetic loci through integrated genome-wide association studies across derived developmental multi-modal imaging phenotypes; 3) Determine the relationship between genetic risk for psychiatric diseases and neurodevelopmental trajectories. We will pursue these aims utilizing a novel combination of methods from population genetics and neuroscience while innovatively tailoring the analytic strategies to avoid potential biases and spurious associations due to admixture and relatedness. The proposed research is significant because the identified genetic mechanisms will provide a potential basis for therapeutics and public health interventions, attending to the impact of the epidemiologically guided sampling of ABCD data. By sharing the tools we develop in this research program and the resulting genetic instruments, we will impact the field immediately, enabling researchers to more deeply investigate neurodevelopmental processes with ABCD data as well as with other accumulating datasets to which they have access.