Decoding the Genetics of Sexual Dimorphism in Autism Spectrum Disorders

我们的长期目标是利用基因工具来提高对自闭症的理解、预防和治疗 谱系障碍（ASD）。这项建议的目的是利用有关两性异形的知识， 复杂的特征，以扩大我们对ASD的一个主要风险因素，男性的遗传基础的理解。的 目前的假设是，性别二型的遗传来源可以发生在三个层面：全基因组负担 或责任阈值，代表基因-性别相互作用的特定遗传位点，以及相关的途径或组， 反映环境性别贡献的位点。为了支持这一假设，以前的工作表明， 在确定疾病状态的病例中，甚至在对照组中， 基因座可以是性别特异性的，多态性对第二性征的贡献因性别而异 影响疾病风险。我们的初步数据还表明，不同的基因组之间的遗传结构不同。 多态性和罕见变异风险。为了了解性别异质性SNP的作用，我们将 扩展和完善它们的定义，建立它们的行动途径，并测试它们的性机制- 的特异性为了建立SNV性二态性的人群基线，我们将评估 全基因组突变负担和性别差异的特定位点，并将任何新知识应用于ASD 数据最后，我们将利用我们的知识，基因性别相互作用，以确定功能性非编码遗传 与疾病风险相关的变化。我们期望建立关于遗传学中性别差异的预期， 并展示其对理解疾病生物学的实用性。我们将获得对复杂事物的新颖见解 导致特发性ASD的遗传机制，对治疗的影响， 利用性别作为复杂遗传疾病的精确工具的可行方法。

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.