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，往往导致不良后果。虽然现在已经知道基因在ADHD中起作用，并且在MRI上观察到的大脑改变与ADHD有关，但遗传效应如何在大脑中实施以塑造ADHD尚不清楚。很可能有不同的方式可以发生，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，它试图识别在大脑和认知中验证的ADHD的遗传生物型。本研究采用了系统的观点，因为它将（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）基于生物相关基因组的基因通路分析。在目标1中，现有的遗传数据库将使用贝叶斯方法进行扩展，基因通路将通过信息学方法使用可获得的全基因组数据集进行优先排序，并与ADHD相关。将增加一个新的队列并进行基因分型，以大幅降低成本，达到必要的样本量。Omni 2.5芯片将用于检测常见SNP和拷贝数变异，Omni Exome芯片将用于检测罕见变异。然后，与ADHD相关的通路将在一个新的队列中复制，创建一组权威的基因通路发现。从幸存的基因通路组中，将使用一种称为模块性分析的分析形式来创建ADHD和对照参与者的概况或生物型。该方法来源于图论中的社区检测方法。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的重点将是遗传对ADHD的既定神经相关性的影响，并了解这些与生物型的关系。因此，将研究特定神经回路中的连通性。在目标3中，重点转移到ADHD的新视角 涉及大脑组织的破坏或整个大脑组装水平的成熟。目标1中确定的通路分数将通过功能和结构MRI数据中明确定义的大脑效率和组织的具体指标来解释变化。生物型也将在这些大脑组织指标上进行比较。CNV和QTL分析也将包括在目标3中，以获得关于大脑指标和基因通路的聚合信息。最后，将通过合作安排在一个独立的、类似规模的队列中测试生物型-MRI效应以进行交叉验证。如果成功，该项目将在描述ADHD的遗传和神经改变的关系方面开辟新天地，将使该领域超越ADHD的单SNP基因分析，并将有助于提供一种表征该综合征生物亚型的方法。

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.