Deep Sequencing in Schizophrenia

精神分裂症的深度测序

• 批准号: 8633781
• 负责人: Debby Wen Tsuang
• 金额: --
• 依托单位: VA PUGET SOUND HEALTHCARE SYSTEM
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8633781
• 关键词: Accounting; Adoption; Adult; Affect; Behavior; Bioinformatics; Biological; Cataloging; Catalogs; Cell model; Code; Complex; Computer Simulation; Copy Number Polymorphism; Data; Delusions; Development; Disease; Disease susceptibility; Emotions; Environment; Etiology; Exons; Experimental Models; Family; Functional disorder; Funding; Funding Mechanisms; Genes; Genetic; Genetic Predisposition to Disease; Genome; Genome Scan; Genotype; Hallucinations; Hereditary Disease; Human; Human Genome; Individual; Influentials; Inherited; Knowledge; Lead; Life; Mental disorders; Methods; Molecular; Molecular Genetics; Morbidity - disease rate; National Institute of Mental Health; Nucleotides; Open Reading Frames; Outcome; Pathogenesis; Pathway interactions; Penetrance; Phenotype; Predisposition; Prevention therapy; Research; Research Personnel; Sampling; Schizophrenia; Sequence Alignment; Speech; Staging; Susceptibility Gene; Symptoms; System; Technology; Twin Multiple Birth; Validation; Variant; Veterans; animal model development; base; computerized data processing; cooperative study; deep sequencing; design; disorder prevention; disorder risk; exome; exome sequencing; experience; follow-up; genetic association; genetic linkage; genetic linkage analysis; genetic pedigree; genetic variant; genome sequencing; genome wide association study; high risk; improved; interest; mortality; new therapeutic target; next generation sequencing; novel; novel strategies; prevent; programs; public health relevance; rare variant; research study; risk variant; symptom management; transmission process

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.

描述（由申请人提供）： 精神分裂症是一种终生疾病，其特征为幻觉、妄想、言语混乱、行为严重混乱和阴性症状。尽管家庭、双胞胎和收养研究一致证明了精神分裂症的遗传病因，但尚未确定致病基因。因此，我们必须进一步了解精神分裂症的潜在病因。精神分裂症遗传易感因素的鉴定代表了检测处于该疾病高风险的症状前个体、设计新的治疗靶点以降低相关发病率和死亡率并最终预防该疾病的关键一步。随着技术的新进步，出现了更强大的方法。其中一种新方法称为“下一代测序”，是一种可以检测基因组中所有基因序列变异的方法。尽管对人类基因组中存在的三十亿个核苷酸中的每一个进行测序是可能的，但对大量个体的基因组进行测序在经济上是不可行的，特别是因为全基因组测序需要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 (~5 Mb)，并且人们相信外显子组包含人类的大部分功能变异。这些最新进展为识别潜在的罕见遗传变异所必需的综合分析奠定了基础，特别是基于家庭的样本，这是本提案的重点。全外显子组和目标序列数据，包括与非编码区域相关的数据，现在提供了进行全面分析的机会，以识别基于家族的样本中的精神分裂症易感基因。我们假设家族中罕见遗传变异的识别和分析 精神分裂症的研究将有助于我们了解精神分裂症背后的生物学途径。具体来说，我们假设具有相对较高外显率的罕见变异将 在从退伍军人事务合作研究计划 #366 和国家心理健康研究所精神分裂症遗传倡议中选出的家族性精神分裂症谱系中具有重要意义。我们的跨学科研究小组预计，我们可以使用新颖的分析方法、下一代测序和公开的生物信息学信息来识别这些罕见的变异。尽管个别情况很少见，但这些外显率较高的精神分裂症形式将导致人们更好地了解精神分裂症的遗传和分子基础。了解这些风险基因将有助于在分子水平上探索精神分裂症的发病机制，并开发该疾病的动物和细胞模型。此类研究工作将极大地推进精神分裂症治疗方法的探索。