Longitudinal Imaging Study of ADHD Brain Development

描述（由申请人提供）：ADHD是一个严重的长期后果的主要公共卫生问题。现有的治疗方法不能实现长期的改变，这增加了发现生物标志物、异质性的生物学基础和效应的发育特异性的紧迫性。拟议的项目将在纵向设计中测试ADHD大脑网络异常发育组织的集中理论。它还将寻求根据大脑网络识别ADHD的亚型。将使用两种最新一代的方法：扩散张量成像（DTI）和功能连接MRI（fcMRI）。这些方法的使用直接符合NIH人类连接体指南，因此数据集也将作为最终创建子连接体的资源。在数据因磨损和运动伪影而丢失之前，共入组490名7-10岁儿童。每年将分三次进行，产生基于年龄的加速纵向设计，年龄范围为7-12岁。70%的样本将有ADHD（所有亚型），30%将是典型的发展比较青年。强调以社区为基础的招募，以便获得一些治疗前的扫描。将跟踪临床变化、治疗使用和心理社会调节因素。选定的认知测量将用于交叉验证临床结果，并确定有关脑回路的机械假设是否在认知分析水平上成立。该项目的主要创新点是：（a）将ADHD作为一个动态实体而不是静态现象进行评估，（B）首次对ADHD的功能连接或DTI进行纵向研究，（c）将ADHD的功能和结构连接措施相结合，（d）引入图论的复杂应用，以确定基于大脑网络的ADHD生物亚型。其主要意义在于，它将使关于ADHD大脑网络的新发现能够在描述易感性的神经生物学标志物（无论症状变化如何都会持续存在的标志物）和疾病过程的标志物（对表型变化非常敏感或预测结果或治疗反应的标志物）方面取得重大进展。这些数据可以为新的评估模型、个性化治疗和治疗监测提供信息。如果该项目取得成功，它将代表着利用有关大脑发育的最新见解绘制ADHD机制的综合性范式模型的重要一步。 公共卫生相关性：ADHD是一种代价高昂的疾病。由于ADHD在不同病例和不同时间表现出的变异性，大脑成像的不一致结果阻碍了对病因的理解。目前的研究将确定ADHD中改变的特定大脑网络，并跟踪这些变化。这些结果旨在确定大脑中ADHD的明确标记，这些标记随着时间的推移而持续，并根据大脑网络参与来确定ADHD的亚型。

DESCRIPTION (provided by applicant): ADHD is a major public health problem with severe long term outcomes. Existing treatments do not achieve long term change, which has increased the urgency of discovering biomarkers, biological bases of heterogeneity, and developmental specificity of effects. The proposed project would test focused theories of aberrant developmental organization of brain networks in ADHD in a longitudinal design. It would also seek to identify subtypes of ADHD based on brain networks. Two latest-generation methods will be utilized: Diffusion tensor imaging (DTI) and functional connectivity MRI (fcMRI). Use of these methods is directly in line with the NIH Human Connectome guidelines, so the data set will also serve as a resource in the eventual creation of a child connectome. A total of 490 children age 7-10 would be enrolled prior to data loss to attrition and motion artifact. They will be followed annually in three waves, yielding an age based accelerated longitudinal design spanning ages 7-12 years. 70% of the sample will have ADHD (all subtypes) and 30% will be typically developing comparison youth. Community- based recruitment is emphasized so that some treatment naove scans will be obtained. Clinical change, treatment use, and psychosocial moderators will be tracked. Selected cognitive measures will be used to cross validate clinical findings and determine whether mechanistic suppositions about brain circuits hold at the cognitive level of analysis. The major innovations in this project are: (a) evaluates ADHD as a dynamic entity rather than a static phenomenon, (b) the first longitudinal study of functional connectivity or DTI in ADHD, (c) combines functional and structural connectivity measures in ADHD, (d) introduces sophisticated usage of graph theory in order to determine biological subtypes of ADHD based on brain networks. The major significance is that it will enable new discoveries about brain networks in ADHD that can enable significant advances in describing neurobiological markers of liability (those that persist regardless of symptom change) and markers of course of illness (those that are acutely sensitive to phenotypic change or predict outcome or treatment response). Those data can inform new models of assessment, individualized treatments, and treatment monitoring. If the project is successful it will represent an important step forward in mapping integrative, paradigmatic models of ADHD mechanism using the newest insights about brain development. PUBLIC HEALTH RELEVANCE: ADHD is a costly disorder. Understanding of causes has been hampered by inconsistent findings on brain imaging due to the variability that ADHD exhibits across cases and across time. The present study will identify specific brain networks that are altered in ADHD and track these changes over time. The results are intended to identify clear markers of ADHD in the brain that endure over time, as well as to identify subtypes of ADHD based on brain network involvement.