Identifying the Polygenic Basis of the Human Brain and Psychiatric Disorders

描述(申请人提供)：最近，我们基于双胞胎的磁共振成像(MRI)数据，使用模糊聚类制作了第一个人类皮质遗传图谱。这一发现不仅证实了人类大脑的表型是可遗传的特征，而且还展示了一种非常明确的区域特定遗传模式，在这种模式下，大脑皮质可以细分为各种多效性区域。在这个项目中，我们将进一步扩展这一方法，并将其应用于具有MRI和单核苷酸多态(SNP)数据的独特的大型内部样本，以生成基于SNP的图谱。我们将采用Visscher和他的同事开发的统计框架(Yang et al.2010年，Deary等人。2012)研究所有SNPs对表型变异的总体贡献。这种方法类似于双胞胎模型，它检查聚合的遗传对一个性状的影响，并捕获了比传统的全基因关联研究(GWAS)方法更大的遗传力部分。然而，双胞胎和Visscher方法都不能提供关于每个遗传分裂背后的特定遗传变异的信息。接下来，我们将使用新的统计方法获取遗传图谱，并找到与每个遗传部门相关的SNPs，以建立一个数据库工具，其中包含特定基因变异对大脑不同部分表型变异的贡献信息。最后，众所周知，精神和物质使用障碍对大脑和行为都有影响。我们将结合大脑的多基因基础知识，研究与疾病或症状发病有关的遗传变异和机制。该提案的具体目标是：目标1：根据核磁共振和SNP数据生成人类大脑皮层的遗传图谱。我们将采用一种新的方法来实现杨等人开发的方法，该方法具有估计所有SNPs的总遗传效应的能力，通过模糊聚类生成皮质表面积和厚度的遗传图谱。目的2：发现与皮质簇图和皮质下结构的个体遗传划分相关的SNPs。我们将把大脑皮质分成由基于双胞胎的遗传图谱定义的遗传大脑区域，并找到与每个大脑区域相关的SNP或基因。目的3：确定精神和物质使用障碍的遗传基础，重点是与神经系统相关的SNPs。与脑部表型相关的单核苷酸多态信息将进一步应用于提高我们在精神病患者中识别与疾病相关的单核苷酸多态的能力。 精神障碍(包括精神分裂症、双相和单相)和物质依赖(包括酒精和尼古丁依赖)。

DESCRIPTION (provided by applicant): Recently we have produced the first genetic atlas of the human cortex based on magnetic resonance imaging (MRI) data of twins using fuzzy clustering. This finding not only confirms that human brain phenotypes are heritable traits but also demonstrates a very clear region-specific genetic pattern in which the cortex can be subdivided into various pleiotropic regions. In this project, we will extend this approach further and apply it to a uniquely large in-house sample with both MRI and single nucleotide polymorphism (SNP) data, in order to generate SNP-based atlases. We will adopt a statistical framework developed by Visscher and colleagues (Yang et al. 2010, Deary et al. 2012) to examine the contribution of all SNPs to phenotypic variation in aggregate. This approach is analogous to twin modeling which examines aggregate genetic influences on a trait, and captures a much larger portion of heritability than the conventional gene-wide association study (GWAS) approach. However, neither the twin nor the Visscher methods is informative about specific genetic variants underlying each genetic division. Next, we will take the genetic maps and find SNPs associated with each genetic division using new statistical methods to establish a database tool that has information about contribution of specific genetic variants to phenotypic variation in different parts of the brain. Finally, it is well-recognized that psychiatric and substance use disorders affect both brain and behavior. We will study the genetic variants and mechanisms that are involved in disease or symptom pathogenesis with benefit from incorporating the knowledge of polygenic basis of the brain. The Specific Aims of the proposal are: Aim 1: Generate genetic atlases of the human cortex based on MRI and SNP data. We will take a novel approach of implementing a method developed by Yang et al, with its strength for estimating aggregate genetic effects of all SNPs, to generate genetic maps of cortical surface area and thickness by fuzzy clustering. Aim 2: Discover SNPs associated with individual genetic divisions of the cortical cluster maps and individual subcortical structures. We will parcel the cortex into genetic brain regions defined by the twin-based genetic atlases and find SNPs or genes associated with each brain region. Aim 3: Identify genetic basis of psychiatric and substance use disorders with a focus on SNPs associated with neural systems implicated in the disorders. The information regarding SNPs associated with brain phenotypes will be further applied to enhance our ability in identifying disease- related SNPs in individuals with psychiatric disorders (including schizophrenia, and bipolar and unipolar disorders) and substance dependence (including alcohol and nicotine dependence).