Integrating Genomic and Environmental Perspectives on Internalizing Disorders

虽然生物测定遗传学研究长期以来一直表明内在性障碍的遗传性很大，包括 严重的抑郁和广泛性焦虑症，将这种影响映射到特定基因的进展 变种的速度一直很慢。专家们一致认为，要找到这种缺失的遗传性，将需要 超越目前的一次一个SNP的全基因组关联研究(GWAS)范式 联合考虑跨结构和功能基因组单元(例如，基因和 生物途径)，以及在高维空间中模拟基因-环境相互作用(GxE Gwas的背景下。该提案的首要目标是为应聘者提供培训和研究 推进这种内化障碍病因学的互动模式所需的机会，从而支持 候选人S的长期职业目标是成为该地区的一名独立调查员。一般训练 目标包括培养对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学统计建模/方案编制方面的实质性问题。这个 候选人建议掌握一些具体技能，包括数据集成技术，包括 GWAS中的先验信息，聚集方法来捕捉许多标记可能产生的影响 小影响(例如，基于基因的、基于途径的和多基因的风险概况评分分析)和机器 研究上位性和非线性基因组效应的学习应用。建议在这些方面进行培训 区域包括课程作业、强化辅导、暑期计划、阅读 小组、系列研讨会和会议，特别注重研究伦理方面的培训。直接辅导 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顶尖专家(即博士。 统计遗传学和生物信息学博士E.Jane Costello 发展精神病理学和迈克尔·尼尔博士(统计学建模和编程)代表 拟议培训计划的核心力量。 应聘者建议在项目的研究部分应用所获得的技能，方法是进行 多阶段GWAS调查基因组影响，包括直接影响和与环境风险的相互作用 影响内化性疾病发展轨迹的因素。从方法论上讲，这种方法侧重于 将表型发展和环境风险的纵向统计模型与新兴市场相结合 基因组学方法。这将通过将史无前例的纵向 Gwas数据集，包括对基因、环境和基因的四个Duke/VCU样本的荟萃分析 发展倡议(GEDI)(N=3,623)。这一发现阶段的荟萃分析之后将 两个大的独立纵向样本复制--全国青少年纵向研究 健康(N=~12,000)和明尼苏达州双胞胎和家庭研究(N=3,762)。具有非凡的统计能力 这一设计将在最后的分析阶段得到进一步的赞扬，并将进行下一代测序 使用有针对性的捕获方法来提取有前景的基因/区域，并使用极端性状方法来最大化 通过从表型分布的极端中选择受试者的力量。 弗吉尼亚联邦大学生物标记中心提供的制度环境 研究和个性化医学是候选人S职业生涯的另一项核心资产 发展。CBRPM？S的使命是开发和应用新的方法，以识别和 利用生物标志物提高对疾病的认识和医疗水平。该中心从一个强大的 多学科视角与主要应用，涉及精神病学结果，发展 精神病理学和药物使用障碍。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，设计中的方法开发和 对精神分裂症的多阶段适应性研究的分析--对精神分裂症的研究结果的重复研究 检测精神分裂症甲基化标志物的基因组图谱。这些项目为以下项目提供了理想的环境 执行拟议的培训和研究，因为它们提供了一个专注于全球气候变化和下一代的环境 测序在精神障碍中的应用--S候选人职业生涯的中心话题 发展规划。CBRPM还提供了几种独特的物理资源，支持当前的 提议，包括一台坚固的4代下一代测序仪，这将允许在内部进行后续测序， 和一个中心专用的计算集群，为拟议的计算密集型分析提供便利。 除了物质资源，CBRPM还提供了一个具有挑战性和合作者的知识环境， 促进中心内外的协作。总而言之，CBRPM提供了一个刺激和 支持性的体制环境，拥有所有统计、计算和实验室资源 这是使这项提议成功所必需的。

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.