Quantitative Genetic Analyisis of Brain Structural Phenotypes

描述（由申请人提供）：神经影像学和定量遗传学领域对探索神经精神疾病的潜在生物学有着巨大的希望。该职业发展奖项的长期目标是为候选人提供设计和实施大型项目所需的技能，这些项目使用神经成像表型和多变量方法来研究复杂神经行为特征的遗传结构。为此，利用复杂扩展谱系的深层遗传结构和先前获得的大脑核磁共振成像的大型数据集（n=357），我们建议；1)使用复杂的神经影像学分析工具收集区域和全局结构脑表型，并确定这些表型与从同一个体收集的一组认知表型之间的结构-功能相关性；2)我们将实施多元统计方法来生成“复合表型”，更有效地捕获相关结构表型集背后的共同遗传成分；3)我们将对最有希望的表型进行数量性状位点连锁分析，以确定基因组中导致表型变异的候选区域，然后使用关联分析将这些发现转化为神经精神样本。候选人的正式培训将在加州大学洛杉矶分校丰富的遗传和神经影像学资源中进行，包括七个教学课程，三个密集讲习班和定期的每周研讨会。

DESCRIPTION (provided by applicant): The fields of neuroimaging and quantitative genetics hold great promise for exploring the underlying biology of neuropsychiatric disorders. The long-term goal of this career development award is to provide the candidate with the skills necessary to design and implement large-scale projects using neuroimaging phenotypes and multivariate methods to investigate the genetic architecture of complex neurobehavioral traits. Towards this end, using the deep genetic structure of a complex extended pedigree and a large data set (n=357) of previously acquired brain MRIs, we propose to; 1) Use sophisticated neuroimaging analysis tools to collect regional and global structural brain phenotypes and identify structure-function correlations between these phenotypes and a set of cognitive phenotypes collected from the same individuals; 2) We will implement multivariate statistical methods to generate 'composite phenotypes' that more efficiently capture common genetic components underlying a correlated set of structural phenotypes; 3) We will perform quantitative trait locus linkage analysis to the most promising phenotypes to identify candidate regions in the genome that contribute to phenotypic variance, and then translate these findings to a neuropsychiatric sample using association analysis. The candidate's formal training will take place in the rich genetic and neuroimaging resources at UCLA and will include seven didactic courses, three intensive workshops and regular weekly seminars. PUBLIC HEALTH RELEVANCE: Psychiatric disorders have a devastating impact on individuals, families and society. Although there is strong evidence for a genetic basis of psychiatric disorders, identification of the specific genes underlying these disorders has proved very difficult. This project aims to use the advantages of a well-developed genetic model system to identify genes related to brain structure and behavior and then translate these results into a psychiatric population.