Somatic Mosaicism in Neuropsychiatric Disorders

项目摘要 在美国，神经精神障碍是导致残疾的主要原因。这些障碍可能 对个人的不同维度有深刻的影响，如社会和情感。标准 诊断基于相对主观的标准，倾向于将疾病类别一分为二，即使在 每个人都有不同的演讲方式。这种不一致强调了需要进一步理解 潜在的病人生物学。在拟议的研究中，我将重点关注精神分裂症(SCZ)、双相情感障碍(BP)、 和ADHD，因为尽管他们有许多临床差异，但他们在很大程度上导致了 在美国，残疾人生活的年数加起来为4.38%。此外，SCZ还跻身于前十名 全球残疾原因。尽管这些疾病造成的巨大健康负担是已知的，但它们的生物学 其机制仍很不清楚。遗传学研究表明，这些基因有很强的遗传成分 疾病，包括遗传变异，以及罕见的从头开始突变。然而，它最近一直在 提出体细胞嵌合体可能是缺失风险的部分原因。体细胞突变已经表明 在几种神经发育障碍中发挥重要的致病作用，如癫痫局灶性皮质 发育不全，斯特奇-韦伯障碍。我们的实验室和其他实验室发现了马赛克单核苷酸变异 (SNV)以及拷贝数变异(CNV)到自闭症谱系障碍(ASD)。有很强的重叠性 ASD在多种神经精神障碍中的遗传结构已有报道。这一观察结果表明 体细胞突变是否有助于SCZ及其相关基因结构的问题 精神错乱。 有了这笔赠款，我建议系统地测试和表征躯体细胞的贡献 神经精神障碍的遗传结构突变，如SCZ、BP和ADHD。目标1 建议检验马赛克拷贝数变异(CNV)导致这些疾病的假设。这 将利用我们的合作者陆宝如教授最近开发的方法来完成。这就做 增强算法对不同阵列平台的健壮性，以利用大型病例控制SNP阵列 数据库。这种方法将允许系统地识别和量化镶嵌CNV 来自精神病学基因组联盟的SCZ、BP、ADHD的大型数据集。目标2建议测试 马赛克SNV与这些疾病有关的假说。这将通过开发 从大脑来源的RNA-SEQ数据中识别镶嵌SNV的方法，因为存在着成长中的大脑 用于神经精神疾病的衍生RNA-SEQ数据库，具有足够的覆盖率以识别躯体SNV 与整个外显子组和全基因组测序工作相比。有了这种新方法，就有可能 从现成的数据集系统地描述SCZ和BP之间的突变负担和模式 来自心理编码、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.