Dissecting Cis Regulation of Gene Expression in Schizophrenia

项目摘要 尽管精神分裂症的流行及其相当大的影响，但对其 病理生理学是最基本的。鉴于它对我们退伍军人福祉的深远影响，有一个紧迫的问题 需要发现新的分子靶点，以便更好地进行诊断测试、治疗和预防措施 是可以实现的。尽管已知某些遗传因素会增加患精神分裂症的风险，但研究表明 到目前为止，已经研究了它的遗传基础的人提供的见解有限。我们的建议旨在更好地 了解精神分裂症的遗传因素及其作用机制。 最近关于精神分裂症的大规模全基因组关联研究--即筛选 患者和对照组的全基因组--已经确定了数百个易感基因。然而，因为 大多数这些基因座位于非编码区--即不表达任何基因的区域 产物(即，信使核糖核酸转录本)--因果变异和它们通过增加 这种疾病的风险尚不清楚。而在过去，这些基因组区域被定性为“垃圾” 最近的发现提供了强有力的证据，表明它们在调节转录方面发挥着重要作用 以基因为模板合成信使核糖核酸转录本的过程。更确切地说，是具体的 蛋白质被称为转录因子，与这些“垃圾DNA”区域结合，促进或抑制转录。 调节区的可及性由组蛋白的多种生物修饰控制-- 包裹基因组DNA并使其在每个细胞内保持紧凑状态的蛋白质。生物化学 组蛋白的修饰提供了一种机制，它充当一个开关，“打开”或“关闭”结合 转录因子结合到调控元件，并随后控制转录因子的速率和数量 抄写。因为精神分裂症的大多数遗传风险变异位于“垃圾DNA”中，并且 因为大量的人类尸检研究描述了转录的异常 精神分裂症，在这项建议中，我们的目标是精确地绘制调控区域，以识别精神分裂症 风险这些区域内的遗传变异，并定义受影响的转录本。 我们对精神分裂症的研究很感兴趣；因此，分析需要在组织中进行 在这种情况下会出现异常情况。出于这个原因，我们将使用死后人脑样本 并将重点放在精神分裂症中持续表现出异常的两个大脑区域(优势 颞回和背外侧前额叶皮质)。因为脑组织含有不同类型的细胞， 因为影响调控区域的组蛋白修饰对于每种细胞类型都是特定的，所以我们将使用 先进的分子技术，使我们能够将神经元与大脑中的其他细胞分开。接下来，我们将 在神经细胞中进行基因组扫描，并确定在 调节转录，并将确定这些调节区是否存在于“开放”或“关闭”中 各州。此方法将生成可用于识别精神分裂症风险的注记地图 位于调控区域内的遗传变异，从而影响转录因子和 随后转录。将通过此方法检测到的特定记录将在 精神分裂症患者体外细胞培养模型及死后基因表达的研究。最后，通过使用 高级生物数学模型，我们将检查这些基因是否聚集在“基因”中 在精神分裂症患者中受到显著影响。如果他们这样做了，我们将获得重要的 针对特定的一组基因和特定的分子途径的知识。这将是非常 有望开发出比目前使用的药物更有效的药物治疗方法。

Project Summary Despite the prevalence of schizophrenia and its considerable impact, knowledge about its pathophysiology is rudimentary. Given its profound impact on the wellbeing of our Veterans, there is an urgent need to discover novel molecular targets, so that better diagnostic tests, treatments, and preventive measures can be attained. Although the risk of schizophrenia is known to be increased by certain genetic factors, studies that have examined its genetic basis have up-to-now provided only limited insight. Our proposal aims to better understand the genetic factors that carry risk for schizophrenia and the mechanisms through which they act. Recent large-scale genome-wide association studies in schizophrenia -- i.e., studies that screen the whole genome in patients vs. controls -- have identified hundreds of susceptibility loci. However, because the majority of these loci are located within non-coding regions -- i.e., regions that do not express any gene products (i.e., mRNA transcripts) -- the causal variants and the mechanism through which they increase the risk for the disease remains unclear. While in the past these genomic regions were characterized as "junk DNA," recent findings provide strong evidence that they play an important role in regulating transcription -- the process in which mRNA transcripts are synthesized using genes as templates. More precisely, specific proteins, named transcription factors, bind to these "junk DNA" regions and facilitate or inhibit transcription. The accessibility of the regulatory regions is controlled by multiple biological modifications of histones -- the proteins that wrap genomic DNA and keep it in a compacted state within each cell. The biochemical modifications of histones provide the mechanism that acts as a switch which "opens" or "closes" the binding of transcription factors to the regulatory elements, and subsequently controls the rate and quantity of transcription. Because the majority of genetic risk variants for schizophrenia are located in the "junk DNA," and because the abnormalities in transcription are described by numerous human postmortem studies in schizophrenia, in this proposal we aim to precisely map the regulatory regions, to identify the schizophrenia risk genetic variants that are localized within these regions, and to define the affected transcripts. We are interested in studying schizophrenia; therefore, the analysis needs to be performed in tissues that present abnormalities in this condition. For this reason, we will use postmortem human brain specimens and will focus on two brain regions that have consistently showed abnormalities in schizophrenia (superior temporal gyrus and dorsolateral prefrontal cortex). Because the brain tissue contains different cell types, and because the histone modifications that affect regulatory regions are specific for each cell type, we will use an advanced molecular technique that will allow us to separate neurons from other cells in the brain. Next, we will perform genome scans in neuronal cells and identify the genomic regions that have a significant role in regulating transcription, as well as will determine if these regulatory regions are present in "open" or "closed" states. This approach will generate an annotation map that can be used to identify the schizophrenia risk genetic variants that are located within the regulatory regions, thus affecting binding of transcription factors and subsequently transcription. Specific transcripts that will be detected by this approach will be further validated in in vitro cell culture models and gene expression human postmortem studies in schizophrenia. Finally, by using advanced biomathematical models, we will examine whether or not these genes cluster together in "gene networks", which are significantly affected in schizophrenia. If they do, we will have gained important knowledge of targeting a specific group of genes and specific molecular pathways. This would be very promising for the development of drug treatments which are more efficacious than those currently in use today.