ADHD biotypes using genetic and imaging approaches

描述(由申请人提供)：注意力缺陷多动障碍(ADHD)是一种常见的疾病，通常会导致不良的结果。虽然现在已经知道基因在ADHD中发挥了作用，而且MRI观察到的大脑变化与ADHD有关，但基因效应是如何在大脑中实施以塑造ADHD的尚不清楚。这很可能有不同的方式发生，也就是说，ADHD的不同病因。这些病因包括遗传和环境影响的组合，但目前的提议侧重于遗传影响。然后，它试图确定ADHD的遗传生物型，这些类型在大脑和认知中得到验证。这项研究采用了系统的观点，因为它将结合(A)使用功能和结构MRI扫描对大脑连通性的系统分析，以及(B)基于生物相关基因组的基因路径分析。在目标1中，现有的遗传数据库将用贝叶斯方法扩展，基因途径将通过信息学方法利用公共可获得的全基因组数据集进行优先排序，并与ADHD有关。将扩大一个新的队列，并对其进行基因分型，以实现必要的样本量，同时大幅降低成本。Omni 2.5芯片将用于检测常见的SNPs和拷贝数变异，Omni Exome芯片将用于检测罕见的变异。然后，与ADHD相关的通路将在新的队列中复制，创建一组权威的基因通路发现。从幸存的一组基因途径中，将使用一种称为模块化分析的分析形式来创建ADHD和对照组参与者的概况或生物型。该方法来源于图论的社区发现方法。在目标2中，这些生物类型将通过神经认知测量以及功能和结构磁共振连通性分析进行验证。目标2的重点将放在遗传对ADHD已确立的神经相关性的影响上，并了解这些与生物型的关系。因此，我们将研究特定神经回路中的连接性。在目标3中，焦点转移到ADHD的新视角 因为涉及到整个大脑组装水平的大脑组织或成熟的破坏。目标1中确定的路径分数将与特定的、定义明确的大脑效率和组织指标竞争，以解释来自功能和结构MRI数据的差异。生物类型也将在这些大脑组织指标上进行比较。CNV和QTL分析也将包括在AIM 3中，以获得关于大脑指标和基因途径的融合信息。最后，生物型核磁共振效应将通过合作安排在一个独立的、类似规模的队列中进行交叉验证测试。如果成功，该项目将在描述ADHD的遗传和神经变化之间的关系方面开辟新的天地，将使该领域超越ADHD的单一SNP基因分析，并将有助于为表征ADHD的生物学亚型提供一条新的道路。

DESCRIPTION (provided by applicant): Attention deficit hyperactivity disorder (ADHD) is a common disorder often leading to poor outcomes. Although it is now known that genes play a role in ADHD and that brain alterations, observed on MRI, are associated with ADHD, how genetic effects are implemented in the brain to shape ADHD is not known. It is likely that there are distinct ways this can happen, that is, heterogeneous etiology in ADHD. These etiologies include a combination of genetic and environmental influences, but the present proposal focuses on the genetic influences. It then attempts to identify genetic biotypes of ADHD that are validated in brain and cognition. This study adopts a systems perspective in that it will bring together (a) systemic analysis of brain connectivity using functional and structural MRI scanning, and (b) gene-pathway analyses based on biologically related gene groups. In Aim 1, existing genetic databases will be extended with Baysian methods, and gene pathways will be prioritized by informatics methods using publically available genome-wide datasets and related to ADHD. A new cohort will be augmented and genotyped, to achieve the necessary sample size at substantially reduced cost. The Omni 2.5 chip will be used to assay common SNPs and copy number variants, and the Omni Exome chip will be used to assay rare variants. Then, pathways associated with ADHD will be replicated in a new cohort, creating an authoritative set of gene-pathway findings. From the surviving set of gene pathways, profiles or biotypes of the ADHD and control participants will be created using a form of analysis called modularity analysis. This method comes from graph theory community detection methods. In Aim 2, these biotypes will be validated with neurocognitive measures, and with functional and structural MRI connectivity analyses. The focus in Aim 2 will be on the genetic influences on well-established neural correlates of ADHD and to understand these in relation to biotypes. Thus, connectivity in specific neural circuits will be studied. In Aim 3, the focus shifts to a newer perspective of ADHD as involving disruptions in brain organization or maturation at the level of whole brain assembly. The pathways scores identified in Aim 1 will compete to explain variation with specific, well defined metrics of brain efficiency and organization from functional and structural MRI data. Biotypes will also be compared on these brain-organization metrics. CNV and QTL analyses will be included in Aim 3 as well to gain converging information on brain metrics and gene pathways. Finally, biotype-MRI effects will be tested for cross-validation in an independent, similar-sized cohort through collaborative arrangements. If successful, the project will break new ground in describing the relation of genetic and neural alterations in ADHD, will move the field past single-SNP gene analyses in ADHD, and will help provide a way forward to characterize biological subtypes of the syndrome.