Deep Sequencing in Schizophrenia

精神分裂症的深度测序

• 批准号: 8812721
• 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/8812721
• 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; Genetic study; 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; identity by descent; 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; targeted sequencing; 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身疾病，其特征是幻觉，妄想，言语混乱，严重混乱的行为和负面症状。尽管家族，双胞胎和收养研究一直证明了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，我们对精神分裂症的潜在病因有了更多的了解。精神分裂症中遗传敏感性因素的鉴定是检测患有疾病高风险，设计新型治疗靶标以降低相关的发病率和死亡率的高风险的预症状的关键步骤，并最终阻止这种疾病。随着技术的新进步，出现了更强大的方法。这些新方法之一，称为“下一代测序”，是一种可以检测基因组中所有遗传序列变体的方法。尽管对人类基因组中存在的三十亿个核苷酸中的每一种都进行了测序，但对大量个体的基因组进行测序在经济上是不可行的，尤其是因为为全基因组测序的必要计算和生物信息学数据处理方法仍在开发中。或者，人类外显子体包含基因组中的所有外显子或编码区域（〜5 MB），并且认为外显子体具有人类的许多功能变化。这些最近的进步为识别潜在的稀有遗传变异所必需的综合分析奠定了基础，尤其是在基于家庭的样本方面，这是本提案的重点。现在，整个外显子组和有针对性的序列数据（包括与非编码区域有关的数据）现在提供了进行全面分析的机会，这些分析将识别基于家庭样本中的精神分裂症易感基因。我们假设对家庭中稀有遗传变体的识别和分析 精神分裂症将有助于我们对精神分裂症基础的生物学途径的理解。具体而言，我们假设具有相对较高渗透率的稀有变体将 在从退伍军人事务合作研究计划中选择的家族精神分裂症研究＃366和国家心理健康研究所关于精神分裂症的基因研究计划很重要。我们的研究人员跨学科小组预计，我们可以使用新颖的分析方法，下一代测序以及公开获得的生物信息学信息来识别这些罕见的变体。尽管单独罕见，但这些较高的精神分裂症形式将导致人们对精神分裂症的遗传和分子基础的理解。这些风险基因的知识将促进探索分子水平上精神分裂症的发病机理，以及该疾病动物和细胞模型的发展。此类研究的努力将大大提高人们寻找精神分裂症的治疗方法。