Somatic Mosaicism in Neuropsychiatric Disorders

项目摘要 在美国，神经精神疾病是残疾的主要原因。这些疾病可以 对个人的不同方面有深刻的影响，如社会和情感。标准 诊断的依据是相对主观的标准，这些标准往往会将疾病类别一分为二，即使在 每个人都有一系列的表现。这种不一致性强调了进一步了解 潜在的病人生物学在拟议的研究中，我将重点放在精神分裂症（SCZ），双相情感障碍（BP）， 和多动症，因为即使他们有许多临床差异，他们有助于很大一部分， 年生活在美国的残疾人，合计4.38%。此外，SCZ是前10名之一， 残疾的全球原因。尽管这些疾病的巨大健康负担是已知的，但它们的生物学特性 其机制仍然是未知的。遗传学研究表明，这些疾病有很强的遗传成分。 疾病，包括遗传变异，以及罕见的新生突变。然而，最近， 提出，体细胞镶嵌可能有助于部分失踪的风险。体细胞突变已经表明， 在几种神经发育障碍中起重要的致病作用， 发育不良，Sturge-Weber二氏病。我们的实验室和其他实验室已经发现镶嵌单核苷酸变异 在自闭症谱系障碍（ASD）中，SNV以及拷贝数变体（CNV）是一个重要的基因。在这一领域有很强的重叠， 已经报道了多种神经精神疾病中ASD的遗传结构。这一观察表明， 体细胞突变是否有助于SCZ的遗传结构和相关的问题 紊乱 有了这笔资金，我打算系统地测试和描述体细胞的贡献， 神经精神疾病如SCZ、BP和ADHD的遗传结构的突变。要求1 提出测试假设，镶嵌拷贝数变异（CNVs）有助于这些疾病。这 将利用我们的合作者宝如洛教授最近开发的方法来完成。我会 增强算法对不同阵列平台的鲁棒性，以利用大型病例对照SNP阵列 数据库。该方法将允许系统地鉴定和定量嵌合CNV的负荷 SCZ、BP、ADHD的大型数据集。目标2建议测试 假设镶嵌SNV有助于这些疾病。这将通过开发 从脑来源的RNA-seq数据中鉴定镶嵌SNV的方法，因为已经有越来越多的脑 用于神经精神疾病的衍生RNA-seq数据库，覆盖范围足以识别体细胞SNV 与全外显子组和全基因组测序工作相比。有了这种新方法， 从现成的数据集系统地表征SCZ和BP的突变负荷和模式 来自PsychEncode、CommonMind和BrainSpan。

Project Abstract In the United States, neuropsychiatric disorders are the leading cause of disability. These disorders can have deep consequences on different dimensions of the individual such as social and emotional. The standard of diagnosis is based on relatively subjective criteria that tends to dichotomize disease categories, even when individuals have a spectrum of presentations. This discordance emphasizes the need to further understand the underlying patient biology. In the proposed study, I will focus on Schizophrenia (SCZ), Bipolar disorder (BP), and ADHD, because even though they have many clinical differences they contribute to a great proportion of years lived with disability in the United states, with a combined 4.38%. In addition, SCZ is one of the top 10 global causes of disability. Even though the great health burden of these disorders is known, their biological mechanism remains greatly unknown. Genetic studies have implicated a strong genetic component for these disorders, including inherited variants, as well as rare de novo mutations. However, it has recently been proposed that somatic mosaicism might contribute partly to the missing risk. Somatic mutations have shown to play an important pathogenic role in several neurodevelopmental disorders such epileptic focal cortical dysplasia, Sturge-Weber disorder. Our lab and others have implicated mosaic single nucleotide variants (SNVs) as well as copy number variants (CNVs) to autism spectrum disorder (ASD). Strong overlap in the genetic architecture of ASD in multiple neuropsychiatric disorders has been reported. This observation poses the question of whether somatic mutations could contribute to the genetic architecture of SCZ and related disorders. With this grant, I propose to systematically test and characterize the contribution of somatic mutations to the genetic architecture of neuropsychiatric disorders such as SCZ, BP, and ADHD. Aim 1 proposes to test the hypothesis that mosaic copy number variants (CNVs) contribute to these disorders. This will be accomplished by leveraging a recently developed method by our collaborator Prof. Po Ru Loh. I will enhance the robustness of the algorithm to varying array platforms to exploit large case-control SNP array databases. This method will allow for the systematic identification and burden quantification of mosaic CNVs across large datasets of SCZ, BP, ADHD from the Psychiatric Genomic Consortium. Aim 2 proposes to test the hypothesis that mosaic SNVs contribute to these disorders. This will be accomplished by developing methodology to identify mosaic SNVs from brain derived RNA-seq data, since there have been growing brain derived RNA-seq databases for neuropsychiatric disorders with enough coverage to identify somatic SNVs compared to whole exome and whole genome sequencing efforts. With this novel method it will be possible to systematically characterize mutational burden and patterns across SCZ and BP from readily available datasets from PsychEncode, CommonMind, and BrainSpan.