Integrating Genomic and Environmental Perspectives on Internalizing Disorders

整合基因组和环境视角来看待内在疾病

• 批准号: 8092195
• 负责人: Daniel E Adkins
• 金额: $ 10.89万
• 依托单位: VIRGINIA COMMONWEALTH UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-01 至 2016-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8092195
• 关键词: Address; Adolescent; Affect; Algorithms; American; Anxiety; Area; Attention; Behavioral; Bioinformatics; Biological; Biological Markers; Biometry; Candidate Disease Gene; Child Care; Collaborations; Communities; Consensus; Custom; Data; Data Analyses; Data Set; Development; Development Plans; Disease; Environment; Environmental Risk Factor; Etiology; Family Study; Funding; Generalized Anxiety Disorder; Genes; Genetic; Genetic Epistasis; Genetic Models; Genetic Polymorphism; Genetic Research; Genetic Risk; Genome; Genomics; Genotype; Goals; Health; Heritability; Heterogeneity; Housing; Investigation; Knowledge; Laboratories; Longitudinal Studies; Machine Learning; Major Depressive Disorder; Maps; Measurement; Measures; Medical; Medicine; Mental Depression; Mental disorders; Mentors; Meta-Analysis; Methods; Methylation; Minnesota; Mission; Modeling; Outcome; Pathway interactions; Phase; Phenotype; Play; Population Control; Predisposition; Preventive Intervention; Psychometrics; Psychopathology; Reading; Research; Research Ethics; Research Personnel; Research Training; Resources; Risk; Role; Sampling; Schizophrenia; Scoring Method; Screening procedure; Series; Side; Signal Transduction; Staging; Statistical Models; Stratification; Structure; Substance Use Disorder; Sum; Techniques; Testing; Time; Training; Twin Multiple Birth; Twin Studies; Universities; Variant; Virginia; base; burden of illness; career; career development; cluster computing; data integration; depressive symptoms; design; developmental genetics; follow-up; functional/structural genomics; gene environment interaction; genetic variant; genome wide association study; genome-wide; global health; improved; indexing; method development; multidisciplinary; next generation; novel; programs; skills; symposium; trait

While biometric genetic studies have long indicated substantial heritability for internalizing disorders, including major depressive and generalized anxiety disorders, progress in mapping this influence onto specific genetic variants has been slow. Expert consensus suggests that finding this ¿missing heritability¿ will require moving beyond the current ¿one SNP at a time¿ genomewide association study (GWAS) paradigm to develop interactive models jointly considering effects across structural and functional genomic units (e.g., genes and biological pathways), as well as modeling gene-environmental interaction (GxE) in the highly dimensional GWAS context. The overarching goal of this proposal is to provide the candidate the training and research opportunities necessary to advance such an interactive model of internalizing disorder etiology, thus supporting the candidate¿s long-term career goal of becoming an independent investigator in the area. General training goals include building proficiency in statistical genetics and bioinformatics, and strengthening knowledge of substantive issues in developmental psychopathology and psychometric statistical modeling/programming. The candidate proposes to acquire a number of specific skills, including data integration techniques for including prior information in GWAS, aggregation methods to capture the possible effects of many markers with very small effects (e.g., gene-based, pathway-based, and polygenic ¿risk profile¿ score analyses) and machine learning applications for investigating epistasis and nonlinear genomic effects. Proposed training in these areas consists of an interlocking program of coursework, intensive mentoring, summer programs, reading groups, seminar series and conferences, with special attention to training in research ethics. Direct mentoring is a key feature of this program, with access to leading experts in each of the proposed training areas (i.e., Drs. Edwin van den Oord and Patrick Sullivan ¿ statistical genetics and bioinformatics, Dr. E. Jane Costello ¿ developmental psychopathology, and Dr. Michael Neale ¿ statistical modeling and programming) representing a core strength of the proposed training plan. The candidate proposes to apply acquired skills in the research portion of the project by conducting a multistage GWAS to investigate genomic influence, both direct and in interaction with environmental risk factors, on developmental trajectories of internalizing disorders. Methodologically, this approach focuses on integrating longitudinal statistical models of phenotypic development and environmental risk with emerging genomic methods. This will be facilitated by bringing together an unprecedented combination of longitudinal GWAS datasets, including a meta-analysis of the four Duke/VCU samples of the Gene, Environment, and Development Initiative (GEDI) (N=3,623). This ¿discovery¿ phase meta-analysis will then be followed by replication in two large independent longitudinal samples¿the National Longitudinal Study of Adolescent Health (N=~12,000) and the Minnesota Twin and Family Study (N=3,762). The exceptional statistical power of this design will be further complimented in a final analytical stage, with next-generation sequencing follow-up using targeted capture methods to extract promising genes/regions and extreme-trait methods to maximize power by selecting subjects from the extremes of the phenotypic distributions. The institutional environment provided by the Virginia Commonwealth University Center for Biomarker Research and Personalized Medicine (CBRPM) represents another core asset to the candidate¿s career development. The CBRPM¿s mission is to develop and apply novel methods for the purpose of identifying and using biomarkers to improve disease understanding and medical treatment. The Center operates from a strong multidisciplinary perspective with primary applications involving psychiatric outcomes, developmental psychopathology, and substance use disorders. Currently funded research programs at the CBRPM include serving as the data analysis core of the Duke/VCU GEDI project, method development in the design and analysis of adaptive multistage GWAS, a replication study of findings from schizophrenia GWAS, and whole genome profiling to detect schizophrenia methylation markers. These projects offer an ideal context for executing the proposed training and research, as they provide an environment focused on GWAS and next-generation sequencing applications to psychiatric disorders¿central topics of the candidate¿s career development plan. The CBRPM also provides several unique physical resources supporting the current proposal, including a SOLiD 4 next-generation sequencer, which will allow follow-up sequencing to be done in-house, and a Center-dedicated computing cluster, facilitating the computationally intensive analyses proposed. In addition to physical resources, the CBRPM offers a challenging and collegial intellectual environment that promotes collaboration both within and outside of the Center. In sum, the CBRPM provides a stimulating and supportive institutional environment with the all of the statistical, computational and laboratory resources necessary to make this proposal a successful one.

虽然生物统计遗传学研究长期以来表明内化障碍具有显着的遗传性，包括 重度抑郁症和广泛性焦虑症，将这种影响映射到特定遗传上的进展 变种进展缓慢。专家共识表明，找到这种“缺失的遗传性”需要移动 超越当前的“一次一个 SNP”全基因组关联研究 (GWAS) 范式 交互模型共同考虑跨结构和功能基因组单元（例如基因和功能）的影响 生物途径），以及在高维度中对基因与环境相互作用（GxE）进行建模 GWAS 背景。该提案的总体目标是为候选人提供培训和研究 推进这种内化疾病病因学的互动模型所必需的机会，从而支持 候选人的长期职业目标是成为该领域的独立调查员。一般培训 目标包括提高统计遗传学和生物信息学的熟练程度，并加强对 发展精神病理学和心理测量统计模型/编程的实质性问题。这 候选人建议获得一些特定技能，包括数据集成技术，包括 GWAS 中的先验信息，聚合方法可以捕获许多具有非常大的标记的可能影响 小影响（例如，基于基因、基于途径和多基因“风险概况”评分分析）和机器 用于研究上位性和非线性基因组效应的学习应用程序。建议进行这些方面的培训 领域由课程作业、强化指导、暑期项目、阅读等相互关联的项目组成 小组、研讨会系列和会议，特别注重研究伦理方面的培训。直接指导 是该计划的一个关键特点，可以接触到每个拟议培训领域的领先专家（即 Drs. Edwin van den Oord 和 Patrick Sullivan ¿ 统计遗传学和生物信息学，E. Jane Costello 博士 ¿ 发展精神病理学和 Michael Neale 博士（统计建模和编程）代表 拟议培训计划的核心优势。 候选人建议通过进行一项研究，将获得的技能应用于项目的研究部分 多阶段 GWAS 研究基因组影响，包括直接影响和与环境风险的相互作用 因素，影响内化障碍的发展轨迹。从方法论上来说，这种方法侧重于 将表型发育和环境风险的纵向统计模型与新兴的 基因组方法。这将通过前所未有的纵向组合来促进 GWAS 数据集，包括对基因、环境和 4 个 Duke/VCU 样本的荟萃分析 发展倡议 (GEDI) (N=3,623)。随后将进行“发现”阶段荟萃分析 两个大型独立纵向样本的复制——国家青少年纵向研究 健康 (N=~12,000) 和明尼苏达双胞胎和家庭研究 (N=3,762)。卓越的统计能力 该设计将在最终分析阶段得到进一步的称赞，并进行下一代测序后续工作 使用靶向捕获方法提取有希望的基因/区域和极端性状方法以最大化 通过从表型分布的极端中选择受试者来获得权力。 弗吉尼亚联邦大学生物标记中心提供的机构环境 研究和个性化医疗 (CBRPM) 是候选人职业生涯的另一项核心资产 发展。 CBRPM 的使命是开发和应用新方法，以识别和 使用生物标志物来改善疾病的理解和医疗。该中心的运作依靠强大的 多学科视角，主要应用涉及精神病学结果、发育 精神病理学和物质使用障碍。 CBRPM 目前资助的研究项目包括 作为Duke/VCU GEDI项目的数据分析核心，设计和方法开发 适应性多阶段 GWAS 分析、精神分裂症 GWAS 结果的重复研究以及整体 基因组分析以检测精神分裂症甲基化标记。这些项目提供了理想的环境 执行拟议的培训和研究，因为它们提供了专注于 GWAS 和下一代的环境 精神疾病的排序应用——候选人职业生涯的中心主题 发展计划。 CBRPM 还提供了多种独特的物理资源来支持当前的 提案，包括 SOLiD 4 下一代测序仪，这将允许后续测序在内部完成， 以及一个中心专用计算集群，促进所提出的计算密集型分析。 除了物质资源外，CBRPM 还提供具有挑战性和学院精神的环境， 促进中心内外的合作。总之，CBRPM 提供了一种刺激和 具有所有统计、计算和实验室资源的支持性制度环境 使这一提案获得成功所必需的。