Metamoodics: Meta-analyses and bioinformatics display of mood disorders genetics

Metamoodics：情绪障碍遗传学的荟萃分析和生物信息学展示

• 批准号: 7995268
• 负责人: Peter P. Zandi
• 金额: $ 32.47万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-12-01 至 2012-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7995268
• 关键词: Accounting; Adoption; Bioinformatics; Bipolar Depression; Bipolar Disorder; Communities; Complex; Computers; Copy Number Polymorphism; Data; Development; Disease; Epidemiologist; Etiology; Family; Floods; Gene Expression; Gene Expression Profile; Genes; Genetic; Genome; Genomics; Goals; Human Genome Project; Individual; Internet; Investigation; Knowledge; Location; Major Depressive Disorder; Meta-Analysis; Molecular; Molecular Genetics; Mood Disorders; Motivation; Online Systems; Pathogenesis; Pathway interactions; Peer Review; Play; Predisposition; Psychiatrist; Public Health; Publishing; Research; Research Personnel; Resources; Review Literature; Role; Scientist; Signal Pathway; Susceptibility Gene; Testing; Twin Multiple Birth; Variant; Work; computerized tools; computing resources; disability; effective therapy; experience; genome-wide; genotyping technology; high throughput technology; meetings; prevent; public health relevance; research study; success; systematic review; tool; virtual; years lived with disability

DESCRIPTION (provided by applicant): Mood disorders impose a significant burden on public health. It has been estimated that major depressive disorder and bipolar depression are the first and sixth leading causes of disability, accounting for nearly 15% of the total years lived with disability worldwide. Thus, there is considerable motivation to better understand the etiology of these disorders so that more rational and effective strategies for treating and/or preventing them may be developed. Family, twin and adoption studies clearly show that genetic factors play an important role in the etiology. However, because of the apparent complexity of the etiology, success in identifying the relevant susceptibility genes has been limited. Recent advances from the Human Genome Project and in genotyping technology have made it possible to interrogate the genome for disease causing variants in an unprecedented fashion. An increasing number of studies are taking advantage of these advances in order to carry out genetic studies in mood disorders. The challenge is now becoming how to synthesize and make sense of the flood of data that is being generated by these efforts. To help meet this challenge, we propose the following aims: 1) To carry out and integrate systematic meta-analyses of genetic studies of mood disorders that have been published in the peer review literature; the meta-analyses will encompass data from three different classes of genomic experiments including a) association studies of sequence variation, b) association studies of copy number variation, and c) gene expression studies; 2) To develop a web-based bioinformatics resource, that we refer to as "Metamoodics," for presenting the results of the meta-analyses in the context of salient genomic annotation; and 3) To develop a computational tool within "Metamoodics" for conducting gene set enrichment analyses of meta-analyzed data from the three classes of genomic experiments to test hypotheses about whether certain molecular genetics pathways are relevant to mood disorders, and to implement this tool to test whether the Wnt signaling pathway relates to susceptibility for bipolar disorder as has been suggested by prior work from our group. We plan to achieve these aims efficiently over a three year period by capitalizing on the intellectual and technical resources at our disposal. We are a multi-disciplinary team of psychiatrists, genetic epidemiologists, bioinformaticists and computer scientists that has been at the forefront of studying the genetics of mood disorders for over two decades. Our goal with this project is to create a central location where the scientific community can gather to explore the current state of knowledge about which genes may contribute to susceptibility to mood disorders in such a way that will help guide future research of the genome in the most fruitful directions. By achieving this goal, we will create a resource that should help to accelerate the pace of discovery for how genetic factors contribute to the etiology of mood disorders. PUBLIC HEALTH RELEVANCE: Mood disorders impose a significant burden on public health; therefore, it is important to understand their causes. This proposal seeks to advance research into the genetic causes by conducting systematic reviews of available gene association and expression studies in mood disorders and developing a web-based bioinformatics resource for integrating the results within the context of other genomic information. The web resource will provide a computational tool for analyzing the synthesized data to test the etiologic contribution of different molecular pathways, such as the Wnt signaling pathway.

描述（由申请人提供）：情绪障碍给公共健康带来重大负担。据估计，重度抑郁症和双相抑郁症是导致残疾的第一和第六大原因，占全球残疾总寿命的近15%。因此，有相当大的动机去更好地了解这些疾病的病因学，以便可以开发出更合理和有效的治疗和/或预防策略。家庭、双胞胎和收养研究清楚地表明，遗传因素在病因学中发挥着重要作用。然而，由于病因学的明显复杂性，鉴定相关易感基因的成功受到限制。人类基因组计划和基因分型技术的最新进展使得以前所未有的方式询问基因组中致病变异成为可能。越来越多的研究正在利用这些进展来开展情绪障碍的基因研究。现在的挑战是如何综合并理解这些努力产生的大量数据。为了帮助应对这一挑战，我们提出以下目标：1）对同行评审文献中发表的情绪障碍遗传研究进行系统荟萃分析并整合；荟萃分析将涵盖来自三类不同基因组实验的数据，包括a）序列变异的关联研究，b）拷贝数变异的关联研究，以及c）基因表达研究； 2）开发基于网络的生物信息学资源，我们称之为“Metamoodics”，用于在显着基因组注释的背景下呈现荟萃分析的结果； 3) 在“Metamoodics”中开发一个计算工具，用于对三类基因组实验的荟萃分析数据进行基因集富集分析，以测试某些分子遗传学途径是否与情绪障碍相关的假设，并实施该工具测试 Wnt 信号通路是否与双相情感障碍的易感性相关，正如我们小组之前的工作所表明的那样。我们计划利用我们掌握的智力和技术资源，在三年内有效地实现这些目标。我们是一个由精神病学家、遗传流行病学家、生物信息学家和计算机科学家组成的多学科团队，二十多年来一直处于情绪障碍遗传学研究的前沿。我们这个项目的目标是创建一个中心位置，科学界可以聚集在一起探索哪些基因可能导致情绪障碍易感性的当前知识状态，从而有助于指导未来基因组的研究。富有成果的方向。通过实现这一目标，我们将创建一个资源，有助于加快发现遗传因素如何影响情绪障碍病因的步伐。 公共卫生相关性：情绪障碍给公共卫生带来重大负担；因此，了解其原因非常重要。该提案旨在通过对情绪障碍中可用的基因关联和表达研究进行系统回顾，并开发基于网络的生物信息学资源，将结果整合到其他基因组信息的背景下，从而推进对遗传原因的研究。该网络资源将提供一个计算工具，用于分析合成数据，以测试不同分子途径（例如 Wnt 信号途径）的病因学贡献。