Deep Sequencing in Schizophrenia

描述（由申请人提供）： 精神分裂症是一种终身疾病，其特征是幻觉，妄想，无组织的言语，严重无组织的行为和阴性症状。虽然家庭、双胞胎和收养研究一致表明精神分裂症的遗传病因，但尚未确定致病基因。因此，至关重要的是，我们追求增加对精神分裂症的潜在病因的理解。精神分裂症的遗传易感因素的鉴定是检测症状前个体的关键一步，这些个体处于发展疾病的高风险中，设计新的治疗靶点以降低相关的发病率和死亡率，并最终预防该疾病。随着技术的新进步，出现了更强大的方法。其中一种新方法被称为“下一代测序”，它可以检测基因组中所有的遗传序列变异。尽管对人类基因组中存在的30亿个核苷酸中的每一个进行测序是可能的，但是对大量个体的基因组进行测序在经济上是不可行的，特别是因为用于全基因组测序的必要的计算和生物信息学数据处理方法仍在开发中。或者，人类外显子组包含基因组中的所有外显子或编码区（约5 Mb），并且据信外显子组包含人类中的许多功能变异。这些最新进展为识别潜在的罕见遗传变异所需的各种综合分析奠定了基础，特别是在基于家族的样本方面，这是本提案的重点。整个外显子组和靶序列数据，包括与非编码区相关的数据，现在提供了进行全面分析的机会，这些分析将在以家庭为基础的样本中识别精神分裂症易感基因。我们假设，鉴定和分析家庭中罕见的遗传变异， 将有助于我们理解精神分裂症背后的生物学途径。具体地说，我们假设具有相对高的突变率的罕见变异将 在选自退伍军人事务部合作研究计划#366和国家精神卫生研究所精神分裂症遗传倡议的家族性精神分裂症家系中是重要的。我们的跨学科研究小组预计，我们可以使用新的分析方法，下一代测序和公开的生物信息学信息来鉴定这些罕见的变异。虽然个别罕见，这些精神分裂症的高发病率形式将导致对精神分裂症的遗传和分子基础的更好理解。这些风险基因的知识将有助于探索精神分裂症的发病机制在分子水平和发展的动物和细胞模型的疾病。这种研究努力将大大推进精神分裂症治疗方法的研究。

DESCRIPTION (provided by applicant): Schizophrenia is a lifelong illness that is characterized by hallucinations, delusions, disorganized speech, grossly disorganized behavior, and negative symptoms. Although family, twin, and adoption studies have consistently demonstrated a genetic etiology for schizophrenia, no causative genes have yet been identified. Therefore, it is crucial that we pursue an increased understanding of the underlying etiology of schizophrenia. The identification of genetic susceptibility factors in schizophrenia represents a critical step toward detecting presymptomatic individuals who are at high risk for developing the disease, designing novel therapeutic targets to decrease associated morbidity and mortality, and ultimately, preventing the disorder. With new advances in technology, more powerful approaches have emerged. One of these new approaches, called "next-generation sequencing," is a method that can detect all of the genetic sequence variants in a genome. Although sequencing every one of the three billion nucleotides that is present in the human genome is possible, it is not financially feasible to sequence the genomes of a large number of individuals, particularly because the necessary computational and bioinformatics data processing methods for whole-genome sequencing are still under development. Alternatively, the human exome contains all of the exons or coding regions in a genome (~5 Mb), and it is believed that the exome harbors much of the functional variation in humans. These recent advances set the stage for the kinds of comprehensive analysis that are necessary to identify underlying rare genetic variants, particularly in regard to family-based samples, which are the focus of this proposal. Whole exome and targeted sequence data, including data related to noncoding regions, now provide the opportunity to perform comprehensive analyses that will identify schizophrenia susceptibility genes in family-based samples. We hypothesize that the identification and analysis of rare inherited variants in families with schizophrenia will contribute to our understanding of the biological pathways that underlie schizophrenia. Specifically, we hypothesize that rare variants with relatively high penetrance will be important in familial schizophrenia pedigrees selected from the Veterans Affairs Cooperative Study Program #366 and National Institute of Mental Health Genetic Initiative on Schizophrenia. Our interdisciplinary group of investigators anticipates that we can identify these rare variants using novel analytic approaches, next- generation sequencing, and publicly available bioinformatics information. Although individually rare, these higher-penetrance forms of schizophrenia will lead to an improved understanding of the genetic and molecular basis of schizophrenia. Knowledge of these risk genes will facilitate exploration of the pathogenesis of schizophrenia at a molecular level and the development of animal and cellular models for the disease. Such research endeavors will significantly advance the search for treatments for schizophrenia.