Molecular mechanisms of abnormal dendritic spine plasticity in schizophrenia

描述(申请人提供)：多条证据支持精神分裂症中突触连接异常的关键作用，但其发病的分子机制尚不清楚。了解这些机制可能使我们能够确定治疗干预的新靶点，特别是在疾病过程的早期。该应用将重点放在树突棘作为大脑连接的细胞底物上，因为大多数兴奋性突触位于棘突上，而脊椎密度降低在精神分裂症中已被广泛报道。越来越多的证据表明，已知的精神分裂症易感基因调节脊柱，脊柱可塑性的调节与精神分裂症有关，有力地支持了脊柱可塑性背后的分子网络的扰动在精神分裂症的发病机制中的关键作用的模型。然而，这个网络中的基因改变是如何导致与精神分裂症相关的特定神经生物学表型的机制尚不清楚。最近的数据表明，罕见的变异(包括氨基酸突变)累积起来占精神分裂症“缺失遗传性”的很大一部分，并聚集在控制突触的基因网络中。由于很大一部分此类突变估计会损害蛋白质功能，因此许多突变预计会导致大脑回路改变。因此，我们认为，通过识别、测试关联和表征富含精神分裂症的罕见变异，我们将为疾病发病机制提供关键的新见解，因为这些突变提供了有关受影响的分子和细胞功能的详细知识。基于我们的初步数据，我们假设，控制树突棘可塑性的基因的罕见编码变异，在精神分裂症患者中积累丰富，破坏皮质连接，并影响携带者的神经形态和认知测量。使用一种结合了人类遗传学、细胞模型中的分子和电生理学研究、小鼠的功能验证以及患者的认知评估和结构脑成像的多学科翻译方法，我们将追求以下具体目标：1)评估在精神分裂症受试者中发现的脊柱可塑性基因突变对细胞的影响。2)研究脊髓可塑性基因突变对谷氨酸能突触传递的影响。3)研究脊柱可塑性基因突变对小鼠大脑皮质超微结构和功能连接的影响。4)探讨脊柱可塑性基因突变与患者表型指标的关系。 公共卫生相关性：使用多学科和集成的翻译方法，我们将测试这一假设，即控制大脑皮层树突棘可塑性的基因罕见的蛋白质编码突变发生在精神分裂症患者身上，扰乱额叶皮质微回路内的突触结构和功能，并影响携带者的特定神经形态测量和认知测量。产生的数据将为精神分裂症异常大脑连接的基础路径提供新的机械性见解，使我们能够确定治疗目标。

DESCRIPTION (provided by applicant): Multiple lines of evidence support a key role for abnormal synaptic connectivity in schizophrenia, but the molecular mechanisms underlying its pathogenesis are not known. Understanding these mechanisms may allow us to identify new targets for therapeutic intervention, especially early in the course of illness. The application wil focus on dendritic spines as cellular substrates of brain connectivity, because the majority of excitatory synapses are located on spines, and reduced spine density has been extensively documented in schizophrenia. Mounting evidence indicating that known schizophrenia susceptibility genes regulate spines and that regulators of spine plasticity are implicated in schizophrenia, strongly support the model that perturbations in the molecular network underlying spine plasticity are critically involved in the pathogenesis of schizophrenia. However, the mechanisms through which genetic alterations in this network underlie specific neurobiological phenotypes related to schizophrenia are not known. Recent data indicates that rare variants (including amino acid mutations) cumulatively account for a significant fraction of the "missing heritability" in schizophrenia, and cluster in gene networks that control synapses. Because a large fraction of such mutations are estimated to impair protein function, many are expected to cause brain circuit alterations. Thus, we propose that by identifying, testing for association, and characterizing rare variants enriched in schizophrenia, we will provide critical new insights into disease pathogenesis, because such mutations provide detailed knowledge about the affected molecular and cellular functions. Based on our preliminary data, we hypothesize that rare coding variants in genes that control dendritic spine plasticity, cumulativel enriched in subjects with schizophrenia, disrupt cortical connectivity and impact neuromorphological and cognitive measures in carriers. Using a multidisciplinary translational approach that combines human genetics, molecular and electrophysiological studies in cellular models, functional validation in mice, and cognitive assessment and structural brain imaging in patients, we will pursue these specific aims: 1) To assess the cellular impact of mutations in spine plasticity genes identified in schizophrenia subjects. 2) To determine the impact of mutations in spine plasticity genes on glutamatergic synaptic transmission. 3) To determine the impact of mutations in spine plasticity genes on cortical ultrastructure and functional connectivit in mice. 4) To assess the relationships between mutations in spine plasticity genes and phenotypic measures in patients. PUBLIC HEALTH RELEVANCE: Using a multidisciplinary and integrated translational approach we will test the hypothesis that rare protein coding mutations in genes that control dendritic spine plasticity in the cerebral cortex, which occur in subjects with schizophrenia, disrupt synapse structure and function within frontal cortical microcircuits, and affect specific neuromorphometric and cognitive measures in carriers. Data generated will provide new mechanistic insights into pathways that underlie abnormal brain connectivity in schizophrenia that will allow us to identify therapeutic targets.