Understanding the genomic risk architecture of schizophrenia using gene expressio

Description (provided by applicant): This proposal represents a move from genomics to biology designed to identify the patterns of gene expression induced by disease-associated mutations and help frame our understanding and elucidate the structure of the still elusive genetic interactions underlying disease risk ("Schizophrenia interactome"). Recent studies have unequivocally demonstrated an important contribution of rare structural mutations to the genetic architecture of numerous psychiatric disorders, including schizophrenia. Determining how such mutations act in concert with modifiers to cause and influence the clinical phenotype is an important question that remains to be addressed. We contend that common genetic variation (including single nucleotide polymorphisms, SNPs) plays a key role in determining the penetrance or the expressivity of rare mutations. This hypothesis has not been directly tested and given the difficulties and uncertainties associated with testing common variation in patient populations it may be impossible to test it unequivocally using human genetic approaches. However, availability of animal models could offer important insights into how rare and common variation interact to affect key neurobiological processes and the gene expression networks underlying such processes. To accomplish this goal, we propose to utilize four "key" mouse lines generated in our lab: i. Two lines that faithfully model two rare mutations that unequivocally predispose to schizophrenia: a truncation of the DISC1 (short for Disrupted-In-Schizophrenia 1) gene and a microdeletion on chromosome 22q11.2;ii. Two lines that faithfully model two alleles of a common variant (BDNF Val66Met) associated with a number of psychiatric diseases and related traits, which undoubtedly modulates neurotrophic action in the developing brain. We propose to analyze the transcriptional profile in the hippocampus and prefrontal cortex across critical developmental periods to obtain an unbiased evaluation of the transcriptional programs affected by the combined effect of rare and common disease-associated variation, reflecting downstream effects of the mutation and/or adaptive/compensatory changes. Our work promises to advance our current genetic knowledge, identify novel disease-related genes or genetic pathways that could be tested in future human genetic studies of SCZ, as well as provide targets for novel pharmacotherapy approaches