ADHD biotypes using genetic and imaging approaches

描述（由申请人提供）：注意缺陷多动障碍（ADHD）是一种常见的疾病，通常导致不良后果。虽然现在已经知道基因在多动症中起作用，并且通过核磁共振观察到的大脑变化与多动症有关，但基因效应是如何在大脑中实现形成多动症的尚不清楚。这可能有不同的发生方式，即ADHD的异质性病因。这些病因包括遗传和环境影响的结合，但目前的建议侧重于遗传影响。然后，它试图确定在大脑和认知中得到验证的多动症的遗传生物型。本研究采用系统视角，它将结合(a)使用功能和结构MRI扫描对大脑连接进行系统分析，以及(b)基于生物学相关基因群的基因通路分析。在Aim 1中，现有的遗传数据库将使用贝叶斯方法进行扩展，基因通路将使用公开的全基因组数据集和与ADHD相关的信息学方法进行优先排序。将增加一个新的队列并进行基因分型，以大幅度降低成本达到必要的样本量。Omni 2.5芯片将用于分析常见snp和拷贝数变异，Omni Exome芯片将用于分析罕见变异。然后，与多动症相关的途径将在一个新的队列中被复制，创造一套权威的基因途径发现。使用一种称为模块化分析的分析形式，将从幸存的基因通路集、ADHD和对照组参与者的概况或生物型中创建。该方法来源于图论社团检测方法。在目标2中，这些生物型将通过神经认知测量以及功能和结构MRI连接分析进行验证。目标2的重点将是对ADHD已建立的神经关联的遗传影响，并了解这些与生物型的关系。因此，特定神经回路的连通性将被研究。在Aim 3中，重点转移到ADHD的新视角

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.