1/3-Schizophrenia Genetics and Brain Somatic Mosaicism

 描述(申请人提供)：精神分裂症(SCZD)是一种衰弱的、典型的不可治愈的神经精神疾病，影响1%的人类人口。疾病症状，包括幻觉、偏执和认知障碍，被认为是由于神经元连接和可塑性受损引起的，但这些缺陷的病因尚不清楚。多条证据表明，SCZD有很强的遗传成分。因此，识别与SCZD相关的基因变异可能为理解和治疗该病提供关键工具。事实上，最近的全基因组关联研究已经确定了与SCZD相关的&gt；100个基因座，但这些遗传变异只占疾病发病率的一小部分。这一不令人满意的结果的一个潜在解释是，SCZD风险等位基因不是通过胚系遗传的，而是通过受影响个体神经元内的体细胞突变而产生的。也许这是SCZD患者遗传的体细胞嵌合体倾向。现在很清楚的是，DNA序列的体细胞嵌合体比以前认为的要普遍得多(即，一个个体内的所有细胞并不包含相同的基因组)，而且这种现象在大脑中特别普遍。这些基因组差异可能导致了神经元功能的多样性。然而，产生或控制体细胞嵌合体的过程的失调可能会导致与疾病相关的基因组不稳定。因此，我们的假设是，神经元或其前体细胞中的体细胞嵌合体是SCZD发病的主要因素。目的1将使用单细胞基因组测序技术从SCZD患者或神经型对照患者中鉴定神经细胞和非神经细胞类型的体细胞拷贝数变异(CNV)。这些分析将集中在额叶皮质和海马体，这两个大脑区域与SCZD的发病机制有关。结果将确定躯体CNV是否在SCZD大脑中过度表达，以及SCZD风险等位基因是否不成比例地受到这些CNV的影响。目的2将表征这些相同细胞类型中的体细胞反转录转座子插入，询问与对照组相比，SCZD患者神经元中反转录转座子事件的频率或位置是否发生了变化。在AIMS 1和AIMS 2中，总共将分析8000个神经元，这将是迄今为止对神经元体细胞嵌合体最全面的分析。在AIM 3中，在SCZD患者中表现最多的基因组变异(在AIMS 1和2中确定)将被工程化为hESCs进行功能验证测试。研究表明，与对照组相比，来自SCZD患者的培养神经元的连接水平降低，突起不发达。类似的分析将使用来自工程hESCs的神经元的同基因和马赛克培养进行。这些研究的结果将确定SCZD神经元中体细胞嵌合体的水平、模式或类型是否发生变化，并有可能确定受这些变化影响最大的基因和基因网络。确定致病因素将提供新的治疗目标，并使我们更接近找到治疗这种毁灭性疾病的方法。

 DESCRIPTION (provided by applicant): Schizophrenia (SCZD) is a debilitating and typically incurable neuropsychiatric disease that affects 1% of the human population. Disease symptoms, which include hallucinations, paranoia, and impaired cognition, are thought to arise from impairments in neuronal connectivity and plasticity, but etiology of these defects remains unclear. Multiple lines of evidence suggest a strong genetic component to SCZD. Thus, identifying genetic variants associated with SCZD may provide critical tools for understanding and treating the disease. Indeed, recent genome wide association studies have identified >100 loci that are associated with SCZD, but these genetic variants account for only a small percentage of disease incidence. One potential explanation for this unsatisfying result is that SCZD risk alleles are not inherited through the germline, but instead arise through somatic mutations within neurons of affected individuals. Perhaps it is the propensity for somatic mosaicism that is inherited in patients with SCZD. It is now clear that somatic mosaicism of DNA sequence is much more common than previously thought (i.e., all cells within an individual do not contain the same genome), and that this phenomenon is particularly prevalent in the brain. These genomic differences may contribute to the diversity of neuronal function. However, dysregulation of processes that generate or control somatic mosaicism may lead to disease-related genomic instability. Our hypothesis, therefore, is that somatic mosaicism in neurons or their progenitors are a major contributor to SCZD pathogenesis. Aim 1 will use single-cell genomic sequencing techniques to identify somatic copy number variants (CNVs) in neuronal and non-neuronal cell types from patients with SCZD or neurotypic controls. These analyses will focus on the frontal cortex and hippocampus, two brain regions associated with SCZD pathogenesis. Results will determine whether somatic CNVs are overrepresented in SCZD brains, and whether SCZD risk alleles are disproportionately affected by these CNVs. Aim 2 will characterize somatic retrotransposon insertions within these same cell types, asking whether the frequency or location of retrotransposition events is altered in neurons from patients with SCZD compared with controls. A total of 8000 neurons will be analyzed in Aims 1 and 2, making this the most comprehensive analysis of neuronal somatic mosaicism to date. In Aim 3, genomic variants most overrepresented in patients with SCZD (identified in Aims 1 and 2) will be engineered into hESCs for functional validation tests. It has been shown that cultured neurons derived from patients with SCZD exhibit reduced levels of connectivity and have underdeveloped neurites compared with controls. Similar analyses will be performed using isogenic and mosaic cultures of neurons derived from engineered hESCs. Results from these studies will determine whether the level, pattern, or type of somatic mosaicism is altered in SCZD neurons, and potentially identify genes and gene networks most affected by these changes. Identifying causal disease factors will provide new therapeutic targets and move us closer to finding a cure for this devastating disease.