Exploring the role of genetic structural variation in neuropsychiatric diseases

项目摘要 神经精神疾病，如自闭症谱系障碍(ASD)、精神分裂症(SCZ)和躁郁症 精神障碍(BP)是美国成年人最常见的长期疾病之一。遗传学在以下方面发挥着重要作用 这些条件，以及影响至少50个碱基的结构变异(SVS)-染色体重排 基因组对--尤其是对这些疾病的遗传风险有贡献。然而，只有一小部分人 目前的研究已经解释了人类人群中存在的SVS。这个项目的目标是 更充分地探讨SVS在神经精神疾病中的作用。 这项工作利用了最近创建的两个关键数据源：1)人类结构的广泛目录 1000基因组计划、基因组聚合数据库和其他项目的变异以及2) 精神病学基因组学在大型神经精神病学病例对照研究中的基因分型数据收集 财团和其他财团。单倍型分期和归因的统计遗传学原理提供了 整合这两种资源的框架。我将开发基于阶段和基于归因的方法来 检测合子后马赛克拷贝数变异(CNV)和群体多态SVS用于基因分型 强度数据。通过在神经精神病学病例对照队列中应用这些方法，我将：(I)确定后- 合子嵌合体拷贝数变异(CNV)在ASD个体中的存在；(Ii)在ASD患者中识别多态SVS 患有ASD、SCZ和BP的个体；以及(Iii)确定增加风险的嵌合体CNV和多态SVS 治疗神经精神障碍。 成功地完成这些目标将使我们更全面地理解SVS在 神经精神疾病；事实上，我将在这个项目中调查的SVS解释了大部分基因 人类种群的多样性。此外，我将开发的计算工具将适用于 研究其他人类疾病。这些工具将向研究界公开提供。 确定SVS在神经精神病学和其他医学疾病中的作用将有助于我们的 了解这些疾病的遗传结构。从长远来看，这可能有助于发现风险 人口，有助于诊断，并最终帮助治疗。

Project Summary Neuropsychiatric conditions such as Autism Spectrum Disorder (ASD), schizophrenia (SCZ), and bipolar disorder (BP) are among the most common long-term diseases in US adults. Genetics play an important role in these conditions, and structural variants (SVs) – chromosomal rearrangements impacting at least 50 base pairs of the genome – contribute particularly to the genetic risk of these diseases. Yet only a small minority of SVs present in the human population has been accounted for in current studies. The goal of this project is to more fully explore the role of SVs in neuropsychiatric conditions. This work leverages the recent creation of two key data sources: 1) extensive catalogues of human structural variation by the 1000 Genomes Project, Genome Aggregation Database, and other projects and 2) the collection of genotyping data in large neuropsychiatric case-control studies by the Psychiatric Genomics Consortium among others. The statistical genetic principles of haplotype phasing and imputation provide the framework to integrate these two resources. I will develop phase-based and imputation-based methods to detect post-zygotic mosaic copy number variations (CNVs) and population polymorphic SVs in genotyping intensity data. By applying these methods in neuropsychiatric case-control cohorts, I will: (i) identify post- zygotic mosaic copy number variants (CNVs) in individuals with ASD; (ii) identify polymorphic SVs in individuals with ASD, SCZ, and BP; and (iii) determine mosaic CNVs and polymorphic SVs that increase risk for neuropsychiatric disorders. Successful completion of these aims will result in a more complete understanding of the role of SVs in neuropsychiatric conditions; indeed, the SVs I will investigate in this project account for much of the genetic diversity in the human population. Furthermore, the computational tools I will develop will be applicable to study other human diseases. These tools will be made publicly available to the research community. Characterizing the role of SVs in neuropsychiatric and other medical conditions will contribute to our understanding of the genetic architectures of these diseases. Long-term, this may help detect at-risk populations, contribute to diagnosis, and ultimately aid in treatment.