2/3-Whole Genome Sequencing for Schizophrenia and Bipolar Disorder in the GPC

GPC 中精神分裂症和躁郁症的 2/3 全基因组测序

基本信息

批准号：
9306200
负责人：
Steven Andrew McCarroll
金额：
$ 327.95万
依托单位：
BROAD INSTITUTE, INC.
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-19 至 2019-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9306200
关键词：
African Architecture Bipolar Disorder Brain Diseases California Chronic Clinical Code Collaborations Communities Complex Computer Analysis Copy Number Polymorphism DNA Data Delusions Deposition Development Diagnosis Disease Dissection Elements Ensure Etiology European Family health status First Degree Relative Frequencies Functional disorder Future Genes Genetic Genetic study Genome Genomic DNA Genomics Genotype Goals Hallucinations Haplotypes Heritability High-Throughput DNA Sequencing Human Genetics Impaired cognition Individual Institutes Knowledge Latino Leadership Libraries Life Manic Mental Depression Mental disorders Meta-Analysis Methods Michigan Molecular Moods Nucleotides Participant Pathway interactions Persons Pharmacotherapy Phenotype Prevalence Prevention Prevention strategy Process Psychiatry Public Health Quality Control Research Research Personnel Resources Risk Schizophrenia Statistical Data Interpretation Testing Universities Untranslated RNA Validation Variant analytical tool base case control cohort data resource data sharing database of Genotypes and Phenotypes disorder risk ethnic diversity experience experimental study follow-up genetic resource genetic variant genome analysis genome annotation genome sequencing genome wide association study genome-wide human disease improved innovation insertion/deletion mutation insight lifetime risk new technology novel therapeutics phenotypic data public health relevance risk variant tool trait whole genome

项目摘要

DESCRIPTION (provided by applicant): The goal of this collaborative project among investigators led by Drs. Michael Boehnke at the University of Michigan, Steven McCarroll of Harvard University and the Broad Institute, and Carlos Pato at the University of Southern California, is to use high-throughput DNA sequencing to identify genes and pathways that contribute to the risk for schizophrenia and bipolar disorder, and to construct a data resource for future genetic studies of these and other psychiatric disorders. This proposal builds on active collaborations among our groups on these important disorders and more generally on our experience in building genome variation resources, such as the 1000 Genomes Project, that are used throughout human genetics. Our research team combines strengths in high-throughput genetics and genomics, development and application of innovative computational and statistical analyses that maximize the benefits of new technologies, and leadership of large scientific consortia. In four Specific Aims, we propose whole genome sequencing (at ~30x coverage) and statistical analysis of 10,000 well-phenotyped and re-contactable individuals from the Genomic Psychiatry Cohort (GPC), equally divided among schizophrenia cases, bipolar cases, and psychiatrically normal controls, and comprised of equal numbers of European-Ancestry (EA), African-Ancestry (AA), and Latino individuals. We will carry out association analysis comparing schizophrenia cases to controls, bipolar cases to controls, and the combined cases to controls in the resulting sequence data, and by collaboration and meta-analysis with other investigators with relevant sequence data that become available. We will also use these sequence data as part of a reference panel to impute into tens of thousands of other genomes in the broader Psychiatric GWAS Consortium (PGC) data to allow association analysis based on substantially larger numbers of individuals. Finally, we will share data and methods to support similar studies of other psychiatric phenotypes and more broadly across the scientific community. The successful completion of these aims will provide new insights into molecular etiology that could catalyze breakthroughs in the prevention, treatment, and diagnosis of schizophrenia and bipolar disorder.

描述（由应用程序提供）：由DRS领导的调查人员之间的合作项目的目标。密歇根大学，哈佛大学的史蒂文·麦卡罗尔（Steven McCarroll）和布罗德学院（Broad Institute）和南加州大学的卡洛斯·帕托（Carlos Pato）的迈克尔·博伊尼克（Michael Boehnke）将使用高通量DNA测序来识别有助于精神分裂症和双极疾病的风险，并构建数据资源的风险这些和其他精神疾病的未来遗传研究。这项建议是基于我们小组之间就这些重要疾病的积极合作而建立的，更广泛地基于我们在建立基因组变异资源（例如1000个基因组项目）方面的经验，这些资源均在整个人类遗传学中使用。我们的研究团队结合了高通量遗传学和基因组学，创新计算和统计分析的开发和应用，从而最大程度地提高了新技术的好处，以及大型科学宪法的领导才能。 In four Specific Aims, we propose whole genome sequencing (at ~30x coverage) and statistical analysis of 10,000 well-phenotyped and re-contactable individuals from the Genomic Psychiatry Cohort (GPC), equally divided among schizophrenia cases, bipolar cases, and psychiatrially normal controls, and comprised of equal numbers of European-Ancestry (EA), African-Ancestry (AA), and Latino个人。我们将进行协会分析，将精神分裂症病例与对照组，双极病例与对照组以及合并病例与所得序列数据中的对照组合，以及与其他研究人员的协作和荟萃分析相关的相关序列数据。我们还将使用这些序列数据作为参考面板的一部分，将更广泛的精神GWAS联盟（PGC）数据中的数以万计的其他基因组归因于数以万计的其他基因组，以允许基于大量数量的个体的关联分析。最后，我们将分享数据和方法，以支持对其他精神病表型的类似研究，并在整个科学界更广泛地研究。这些目标的成功完成将为分子病因提供新的见解，这可能会促进精神分裂症和双相情感障碍的预防，治疗和诊断方面的突破。