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: 8435497
• 负责人: Daniel E Adkins
• 金额: $ 13.81万
• 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/8435497
• 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; 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; next generation sequencing; novel; programs; screening; 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.

虽然生物特征遗传学研究长期以来一直表明内化障碍具有很大的遗传性， 严重抑郁症和广泛性焦虑症，将这种影响映射到特定遗传因素的进展 变种是缓慢的。专家一致认为，要找到这种“缺失的遗传性”， 超越目前的一次一个SNP的全基因组关联研究（GWAS）范式， 共同考虑跨结构和功能基因组单元的效应的交互式模型（例如，基因和 生物学途径），以及在高度多维的基因-环境相互作用（GxE）建模 GWAS上下文。本提案的总体目标是为候选人提供培训和研究 机会，以推进这种互动模式的内在障碍病因，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， 发展心理病理学和心理测量统计建模/编程的实质性问题。的 候选人建议获得一些特定的技能，包括数据集成技术，包括 GWAS中的先验信息，聚集方法，以捕获许多标记物的可能影响， 较小的影响（例如，基于基因、基于途径和多基因风险特征评分分析）和机器 研究上位性和非线性基因组效应的学习应用。拟议的培训 包括课程作业、强化辅导、暑期课程、阅读、 研究伦理委员会的工作重点是研究伦理的培训，包括研究小组、系列研讨会和会议。直接指导 是该计划的一个关键特征，可以接触到每个拟议培训领域的领先专家（即，Drs. 埃德温货车登奥德和帕特里克沙利文统计遗传学和生物信息学，博士E。简·科斯特洛 发展精神病理学，和博士迈克尔尼尔<$统计建模和编程）代表 一个核心力量的拟议培训计划。 候选人建议通过开展一项研究，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，对发展轨迹的内化障碍。从方法论上讲，这种方法侧重于 整合表型发育和环境风险的纵向统计模型， 基因组方法。这将通过将前所未有的纵向 GWAS数据集，包括对基因、环境和环境的四个杜克/VCU样本的荟萃分析。 发展倡议（性别平等和发展倡议）（人数= 3 623）。在这一发现阶段的荟萃分析之后， 在两个大型独立纵向样本中进行重复研究-国家青少年纵向研究 健康（N=~ 12，000）和明尼苏达州双胞胎和家庭研究（N= 3，762）。统计学上的非凡力量 这种设计将在最后的分析阶段得到进一步的补充，并进行下一代测序 使用靶向捕获方法来提取有希望的基因/区域，并使用极端性状方法来最大化 从表型分布的极端中选择受试者。 弗吉尼亚联邦大学生物标志物中心提供的制度环境 研究和个性化医学（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的方法，以识别和 使用生物标记物来提高对疾病的认识和医疗水平。该中心从一个强大的 多学科观点，主要应用包括精神病学结局、发展 精神病理学和物质使用障碍CBRPM目前资助的研究项目包括 作为杜克/VCU GEDI项目的数据分析核心， 适应性多阶段GWAS的分析，精神分裂症GWAS结果的重复研究， 基因组分析检测精神分裂症甲基化标记。这些项目提供了一个理想的环境， 执行拟议的培训和研究，因为它们提供了一个专注于全球WAS和下一代的环境 精神疾病的测序应用是候选人职业生涯的中心话题 发展规划CBRPM还提供了几个独特的物理资源，支持当前的 建议，包括SOLiD 4下一代测序仪，这将允许后续测序在内部完成， 和一个中心专用的计算集群，便于进行拟议的计算密集型分析。 除了物理资源，CBRPM提供了一个具有挑战性的和合议的智力环境， 促进中心内外的合作。总之，CBRPM提供了一个刺激和 支持性的机构环境，包括所有的统计、计算和实验室资源 使这一提议获得成功。