Identification of genetic determinants of the sexual dimorphism in CNS XXXX .

@entity1 @entity19 @entity16 @entity56 @entity792 @entity15
@entity15 ( @entity15 ) is a debilitating chronic @entity16 that affects approximately 2.3 million individuals worldwide, with higher prevalence in females, and a strong genetic component. While over 200 @entity15 susceptibility loci have been identified in GWAS, the underlying mechanisms whereby they contribute to disease susceptibility remains ill-defined. Forward genetics approaches using conventional laboratory @entity19 strains are useful in identifying and functionally dissecting genes controlling disease-relevant phenotypes, but are hindered by the limited genetic diversity represented in such strains. To address this, we have combined the powerful chromosome substitution (consomic) strain approach with the genetic diversity of a wild-derived inbred @entity19 . Using @entity56 ( @entity56 ), a @entity19 model of @entity15 , we evaluated genetic control of disease course among a panel of 26 consomic strains of @entity19 inheriting chromosomes from the wild-derived PWD strain on the C57BL/6J background, which models the genetic diversity seen in @entity1 populations. Nineteen linkages on 18 chromosomes were found to harbor loci controlling @entity56 . Of these 19 linkages, six were male-specific, four were female-specific, and nine were non-sex-specific, consistent with a differential genetic control of disease course between males and females. An @entity15 -GWAS candidate-driven bioinformatic analysis using orthologous genes linked to @entity56 course identified sex-specific and non-sex-specific gene networks underlying disease pathogenesis. An analysis of sex hormone regulation of genes within these networks identified several key molecules, prominently including the MAP kinase family, known hormone-dependent regulators of sex differences in @entity56 course. Importantly, our results provide the framework by which consomic @entity19 strains with overall genome-wide genetic diversity, approximating that seen in @entity1 , can be used as a rapid and powerful tool for modeling the genetic architecture of @entity15 . Moreover, our data represent the first step towards mechanistic dissection of genetic control of sexual dimorphism in CNS @entity792 .
