Our long-term goal is to use genetic tools to improve understanding, prevention, and treatment of autism spectrum disorder (ASD). The objective of this proposal is to utilize knowledge about sexual dimorphism in complex traits to extend our understanding of the genetic basis of a major risk factor for ASD, male sex. The current hypothesis is that genetic sources of sexual dimorphism can occur at three levels: genomewide burden or liability threshold, specific genetic loci representing gene-sex interaction, and relevant pathways or sets of loci reflecting environmental sex contribution. In support of this hypothesis, previous work has shown that genomewide genetic burden can differ by sex in cases ascertained for disease status and even in controls, risk loci can be sex-specific, and polymorphisms differing in contribution to secondary sex characteristics by sex impact disease risk. Our preliminary data also shows that genetic architecture differs between common polymorphism and rare variant risk. In order to understand the action of sex-heterogeneous SNPs, we will expand and refine their definition, establish their pathways of action, and test their mechanism of sex- specificity. In order to establish a population baseline for sexual dimorphism of SNVs, we will assess both genome-wide mutational burden and specific loci for sex differences and apply any new knowledge to ASD data. Finally, we will utilize our knowledge about gene-sex interaction to identify functional noncoding genetic variation relevant for disease risk. We expect to establish expectations about sex differences in genetic architecture and show its utility to understanding disease biology. We will gain novel insight into complex genetic mechanisms contributing to idiopathic ASD with implications for treatment and pioneer a generally applicable approach for utilizing sex as a precision tool for complex genetic disease.

Many common, complex disorders dominating morbidity and mortality show sex differences in prevalence, course, or co-morbities, and the basis for these sexual dimorphisms are poorly understood. In order to take an individualized approach to health, we need to understand relevant biological subgroups, of which sex is simple to determine and demonstrated to have high impact, including for autism spectrum disorder (OR >4). This project will investigate sex differences at several levels of analysis and across different approaches, follow up our results in experimental models, and gain insight into the genetic models, mechanisms, and predictive power of genetic-sex interactions