3/5-Genetics of Transcriptional Endophenotypes for Schizophrenia

3/5-精神分裂症转录内表型的遗传学

• 批准号: 8657481
• 负责人: Ruben C. Gur
• 金额: $ 8万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-05-01 至 2015-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8657481
• 关键词: Affect; African American; Alabama; Biological Assay; Biological Process; Biology; Biomedical Research; California; Cell Line; Chromosome Mapping; DNA; DNA Methylation; Data; Data Collection; Data Set; Diagnosis; Diagnostic; Disease; Emotions; Etiology; Face; Family; Family Study; Family member; Freezing; Functional disorder; Gene Expression; Gene Expression Regulation; Genes; Genetic; Genetic Transcription; Genome Scan; Genomics; Genotype; Goals; Gur; Individual; Investigation; Joints; Measures; Memory; Methods; Molecular Genetics; National Institute of Mental Health; Neurocognition; Neurocognitive; Neurons; Parents; Pennsylvania; Phenotype; Prevention; Process; Psyche structure; Psychiatry; RNA; Research Institute; Research Personnel; Risk; Risk Factors; Role; Sampling; Schizophrenia; Signal Transduction; Site; Testing; Texas; Transcript; Universities; Variant; base; brain tissue; cognitive function; cost; database of Genotypes and Phenotypes; design; endophenotype; flexibility; genetic analysis; genetic pedigree; genome wide association study; genome-wide; innovation; interest; lymphoblastoid cell line; neurocognitive test; novel; proband; psychogenetics; repository; trait; transcriptomics

DESCRIPTION (provided by applicant): Schizophrenia is a common and debilitating condition with high personal costs to affected individuals and their families as well as high societal costs. Relatively little is known about the pathophysiology of schizophrenia. Although there is strong evidence for a genetic component to risk of schizophrenia, few specific genes involved in its etiology have been identified. In this set of coordinated R01s, we propose to take an alternative approach to localizing genes influencing risk of schizophrenia, combining established intermediate risk factors for schizophrenia with identification of novel transcriptional endophenotypes and combining standard GWAS gene localization approaches with innovative methods utilizing joint analysis of association and linkage and joint analysis of genomic and transcriptomic evidence. We will utilize existing samples and data from three ongoing studies: the Consortium on the Genetics of Schizophrenia (COGS); the Multiplex Multigenerational Investigation of Schizophrenia (MGI); and the Project among African Americans to Explore Risks for Schizophrenia (PAARTNERS). These three family studies were designed to investigate genetic influences on schizophrenia using neurocognitive phenotypes associated with schizophrenia risk. We hypothesize that alterations in gene regulation are responsible for some portion of the genetic liability to schizophrenia. Thus, we will use RNA expression levels both as potential endophenotypes for schizophrenia and as an alternative method of genome scanning. Identification of transcriptional correlates of schizophrenia will be facilitated by use of a novel Endophenotype Ranking Value (ERV) that combines the strength of the genetic signal on a potential endophenotype with the strength of its correlation with the disease of interest (i.e. schizophrenia) in a single measure. We will conduct a conventional genome-wide association study (GWAS) for schizophrenia, for newly identified transcriptional endophenotypes, and for classical neurocognitive risk factors. We will also take advantage of the large families in these samples to conduct joint linkage and association. Finally we will combine genomic and transcriptomic lines of evidence in a joint test to identify genes influencing schizophrenia and associated neurocognitive risk factors. All data generated in the course of the project will be shared through dbGaP and the NIMH Genetics Repository.

描述（由申请人提供）：精神分裂症是一种常见且令人衰弱的疾病，给受影响的个人及其家庭带来高昂的个人成本以及高昂的社会成本。人们对精神分裂症的病理生理学知之甚少。尽管有强有力的证据表明遗传因素与精神分裂症的风险有关，但很少有涉及其病因的特定基因已被确定。在这组协调的 R01 中，我们建议采取另一种方法来定位影响精神分裂症风险的基因，将已确定的精神分裂症中间风险因素与新转录内表型的识别相结合，并将标准 GWAS 基因定位方法与利用关联分析的创新方法相结合以及基因组和转录组证据的关联和联合分析。我们将利用来自三项正在进行的研究的现有样本和数据：精神分裂症遗传学联盟 (COGS)；精神分裂症多重多代调查（MGI）；以及非洲裔美国人探索精神分裂症风险项目（PAARTNERS）。这三项家庭研究旨在利用与精神分裂症风险相关的神经认知表型来研究遗传对精神分裂症的影响。我们假设基因调控的改变导致了精神分裂症的部分遗传倾向。因此，我们将使用 RNA 表达水平作为精神分裂症的潜在内表型和基因组扫描的替代方法。通过使用一种新的内表型排名值 (ERV)，将有助于鉴定精神分裂症的转录相关性，该排名值将潜在内表型上的遗传信号强度与其与感兴趣的疾病（即精神分裂症）的相关性强度结合在一个单一的数据中。措施。我们将对精神分裂症、新发现的转录内表型和经典神经认知危险因素进行传统的全基因组关联研究（GWAS）。我们还将利用这些样本中大家族的优势，进行联合联动和关联。最后，我们将在联合测试中结合基因组和转录组证据，以确定影响精神分裂症和相关神经认知风险因素的基因。项目过程中生成的所有数据将通过 dbGaP 和 NIMH 遗传学存储库共享。