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.
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.
