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: 8576864
• 负责人: JOEL T NIGG
• 金额: $ 70.47万
• 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/8576864
• 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; 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）：注意缺陷多动症（ADHD）是一种常见的疾病，通常导致结果不佳。尽管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，但在大脑中如何实现遗传效应以塑造ADHD。这种可能发生的方式可能有不同的方式，即ADHD中的异质性病因。这些病因包括遗传和环境影响的结合，但目前的提议着重于遗传影响。然后，它试图鉴定在大脑和认知中验证的ADHD的遗传生物型。这项研究采用了系统的观点，它将通过功能和结构MRI扫描将大脑连通性的系统分析汇总在一起，以及（b）基于基于生物学相关基因组的基因pathway分析。在AIM 1中，现有的遗传数据库将使用Baysian方法扩展，并且使用公共可用全基因组数据集的信息学方法将基因途径优先考虑，并且与ADHD相关。新的队列将被增强和基因分型，以实现必要的样本量，以大幅降低的成本。 Omni 2.5芯片将用于分析常见的SNP和拷贝数变体，并且Omni Exome芯片将用于测定稀有变体。然后，与ADHD相关的途径将在新的队列中复制，从而创建一组权威的基因 - 校园发现。从存活的基因途径集，将使用称为模块化分析的分析形式创建ADHD和对照参与者的曲线或生物型。该方法来自图理论社区检测方法。在AIM 2中，这些生物型将通过神经认知度量以及功能和结构MRI连接分析来验证。 AIM 2的重点将是对ADHD的神经相关性的遗传影响，并与生物型有关。因此，将研究特定神经回路中的连通性。在AIM 3中，重点转移到了多动症的新观点 作为在整个大脑组装水平上涉及大脑组织中的破坏或成熟。 AIM 1中确定的途径得分将竞争以通过功能和结构MRI数据的特定，定义明确的脑效率和组织的指标来解释变化。还将在这些大脑组织指标上比较生物型。 CNV和QTL分析还将包括在AIM 3中，以获取有关脑指标和基因途径的收敛信息。最后，将通过协作安排在独立的类似大小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中遗传和神经改变的关系方面打破新的基础，将使该领域超过ADHD中的单SNP基因分析，并将有助于为表征综合征的生物亚型提供前进的方向。