An Interdisciplinary program for systems genomics of complex behaviors

复杂行为系统基因组学跨学科项目

• 批准号: 7637545
• 负责人: Fernando Pardo-Manuel de Villena
• 金额: $ 298.6万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7637545
• 关键词: Address; Adverse reactions; Algorithms; Alleles; Antipsychotic Agents; Anxiety; Area; Autistic Disorder; Behavior; Behavioral; Biological; Biology; Biomedical Research; Breeding; Cessation of life; Chromosome Mapping; Clozapine; Collection; Commit; Communities; Complement; Complex; Computational Biology; Copy Number Polymorphism; Data; Data Collection; Data Set; Databases; Development; Discipline; Disease; Disease model; Dissection; Environment; Environmental Impact; Etiology; Funding; Future; Gene Expression Profile; Genes; Genetic; Genetic Models; Genetic Variation; Genome; Genomics; Genotype; Goals; Haloperidol; Head; Human; Human Genetics; Imagery; Institution; Intention; Joints; Knowledge; Laboratory Organism; Language; Length; Major Depressive Disorder; Mental disorders; Meta-Analysis; Minority; Minority Groups; Modeling; Molecular; Morbidity - disease rate; Motivation; Mouse Strains; Mus; National Human Genome Research Institute; National Institute of Mental Health; Parents; Pathway interactions; Performance; Pharmaceutical Preparations; Pharmacogenetics; Pharmacogenomics; Pharmacotherapy; Phenotype; Pilot Projects; Policies; Population; Preparation; Principal Investigator; Probability; Production; Psychiatry; Public Health; Randomized; Reaction; Recombinants; Recording of previous events; Regulation; Research; Research Personnel; Research Support; Resource Sharing; Resources; Risk; Sample Size; Schizophrenia; Science; Scientist; Social Behavior; Societies; Stress; System; Systems Biology; TNFRSF5 gene; Testing; Time; Training; Underrepresented Minority; United States National Institutes of Health; Variant; Work; X Inactivation; Yeasts; computer science; computerized data processing; cost; data management; data sharing; depression; design; environmental enrichment for laboratory animals; expectation; genetic resource; genome wide association study; genome-wide; high risk; imprint; innovation; knowledge base; mammalian genome; metabolomics; model development; molecular phenotype; mortality; mouse model; novel; panacea; phenome; predictive modeling; programs; public health relevance; sex; success; tool; trait; user-friendly

DESCRIPTION (provided by applicant): In this application, we propose a highly ambitious yet realistically attainable goal: to align existing expertise at UNC-CH into a center of excellence in order to develop as a resource and demonstrate the utility of the murine Collaborative Cross (CC) to delineate genetic and environmental determinants of complex phenotypes drawn from psychiatry, the most intractable set of problems in all of biomedicine. We propose a particularly challenging definition of success - we will identify high probability etiological models (which can be realistically complex) and then prove the predictive capacity of these models by generating novel strains of mice bred to be at either very low or very high risk of the phenotype. Once validated, these high confidence models can then be tested in subsequent human studies. The data collected at the UNC center would be a valuable resource to the wider scientific community and could be used to interrogate any number of biological problems. The development of sophisticated, user-interactive databases to access the large, complex datasets collected represents a key component of the project. Accomplishing this overarching goal requires an exceptional diversity of scientific expertise - psychiatry, human genetics, mouse phenotyping, mouse genetics, statistical genetics, computational biology, and systems biology. Experts in all of these disciplines were deeply involved in the preparation of this application and are committed to the projects described here. Moreover, successful integration of these diverse fields is non-trivial; however, we can document that all scientists on this application have a history of extensive interactions over the past five years, know now how to work together and have a working knowledge of their colleagues' expertise. UNC-Chapel Hill has a shown an intense commitment to promoting inter-disciplinary genomics research and is one of the most collegial biomedical research institutions in the US which provides a fertile backdrop for "Science 2.0" projects such as that proposed here. PUBLIC HEALTH RELEVANCE Psychiatric disorders are a paradox-the associated morbidity, mortality, and societal costs are enormous and yet, despite over a century of scientific study, there are few hard facts about the etiology of the core diseases. Although GWAS meta-analyses are in progress, early results suggest that strong and replicable findings are elusive. Our proposal provides an alternative model approach to complement the study of fundamental psychiatric phenotypes.

描述（由申请人提供）：在本申请中，我们提出了一个雄心勃勃但现实可实现的目标：将 UNC-CH 的现有专业知识整合为卓越中心，以开发为资源并展示小鼠协作交叉 (CC) 的效用，以描述精神病学复杂表型的遗传和环境决定因素，这是所有生物医学中最棘手的问题。 我们提出了一个特别具有挑战性的成功定义——我们将确定高概率的病因模型（实际上可能很复杂），然后通过培育出表型风险非常低或非常高的新小鼠品系来证明这些模型的预测能力。 一旦经过验证，这些高置信度模型就可以在后续的人体研究中进行测试。 北卡罗来纳大学中心收集的数据对于更广泛的科学界来说将是宝贵的资源，可用于研究许多生物问题。 开发复杂的用户交互式数据库来访问收集的大型复杂数据集是该项目的关键组成部分。 实现这一总体目标需要极其多样化的科学专业知识——精神病学、人类遗传学、小鼠表型、小鼠遗传学、统计遗传学、计算生物学和系统生物学。 所有这些学科的专家都深入参与了本申请的准备工作，并致力于此处描述的项目。 此外，这些不同领域的成功整合并非易事。然而，我们可以证明，该应用程序的所有科学家在过去五年中都有广泛的互动历史，现在知道如何一起工作，并了解同事的专业知识。 北卡罗来纳大学教堂山分校致力于促进跨学科基因组学研究，是美国最大学化的生物医学研究机构之一，为此处提出的“科学 2.0”项目提供了肥沃的背景。 公共卫生相关性精神疾病是一个悖论——相关的发病率、死亡率和社会成本是巨大的，然而，尽管经过一个多世纪的科学研究，关于核心疾病的病因学却几乎没有确凿的事实。 尽管 GWAS 荟萃分析正在进行中，但早期结果表明，强有力且可复制的研究结果难以实现。 我们的建议提供了一种替代模型方法来补充基本精神病表型的研究。