ADHD biotypes using genetic and imaging approaches

使用遗传和成像方法进行多动症生物型

• 批准号: 8706969
• 负责人: JOEL T NIGG
• 金额: $ 62.79万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8706969
• 关键词: Adopted; Amines; Anterior; Attention; Attention deficit hyperactivity disorder; Biological; Biological Assay; Brain; Build-it; Catecholamines; Child; Chromatin Modeling; Cognition; Cognitive; Communities; Copy Number Polymorphism; Corpus striatum structure; Data; Data Set; Detection; Development; Disease; Dopamine; Dorsal; Etiology; Functional disorder; Genes; Genetic; Genetic Databases; Genetic Epistasis; Genome; Genomics; Genotype; Glutamates; Graph; Heterogeneity; Image; Individual; Informatics; Length; MRI Scans; Magnetic Resonance Imaging; Measures; Metabolic Pathway; Methodology; Methods; Metric; Mono-S; Neurocognitive; Nucleus Accumbens; Outcome; Parietal; Participant; Pathway interactions; Patients; Pattern; Physiological; Play; Process; Quantitative Trait Loci; Role; Sample Size; Shapes; Specific qualifier value; Stream; Structure; Subgroup; Synaptic Transmission; Synaptic plasticity; Syndrome; System; Testing; Validation; Variant; axon growth; base; brain cell; brain volume; clinically relevant; cohort; cost; disorder control; disorder risk; exome; genome-wide; intercellular communication; mind control; neural circuit; neuroimaging; neuroregulation; novel; public health relevance; rare variant; relating to nervous system; segregation; theories; tool; transmission process; white matter

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.

描述（由申请人提供）：注意力缺陷多动障碍（ADHD）是一种常见疾病，通常会导致不良结果。尽管现在已知基因在 ADHD 中发挥作用，并且 MRI 观察到的大脑改变与 ADHD 相关，但遗传效应如何在大脑中影响 ADHD 的形成尚不清楚。这种情况的发生可能有多种不同的方式，即多动症的病因不同。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，它尝试识别在大脑和认知中得到验证的 ADHD 遗传生物型。这项研究采用系统视角，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) 基于生物学相关基因组的基因通路分析。在目标 1 中，现有的基因数据库将通过贝叶斯方法进行扩展，并且将使用公开的全基因组数据集和与 ADHD 相关的信息学方法对基因通路进行优先排序。新的队列将被扩充并进行基因分型，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的 SNP 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，从而创建一组权威的基因通路发现。将使用一种称为模块化分析的分析形式，从幸存的一组基因通路中创建 ADHD 和对照参与者的概况或生物型。该方法来源于图论社区检测方法。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 的重点是遗传对 ADHD 的既定神经相关因素的影响，并了解这些因素与生物型的关系。因此，将研究特定神经回路的连接性。在目标 3 中，焦点转向 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 中确定的路径分数将通过功能和结构 MRI 数据中的大脑效率和组织的具体、明确定义的指标来解释变异。生物型也将根据这些大脑组织指标进行比较。 CNV 和 QTL 分析也将包含在目标 3 中，以获得有关大脑指标和基因通路的聚合信息。最后，将通过合作安排在独立、相似规模的队列中测试生物型 MRI 效果，以进行交叉验证。如果成功，该项目将在描述 ADHD 遗传和神经改变的关系方面取得新的突破，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的生物亚型的方法。