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）：情绪障碍对公共卫生造成了重大负担。据估计，主要的抑郁症和躁郁症抑郁症是残疾的第一和第六主要原因，占全球残疾年总年的近15％。因此，有很大的动力可以更好地理解这些疾病的病因，以便可以开发出更合理有效的治疗和/或预防疾病的策略。家庭，双胞胎和收养研究清楚地表明，遗传因素在病因中起重要作用。但是，由于病因的明显复杂性，识别相关易感基因的成功受到了限制。人类基因组项目和基因分型技术的最新进展使得以前所未有的方式询问引起变异的疾病的基因组。越来越多的研究利用这些进步来进行情绪障碍进行遗传研究。现在，挑战正在成为如何综合并理解这些努力所产生的大量数据的方法。为了帮助应对这一挑战，我们提出以下目的：1）进行并整合在同行评审文献中发表的情绪障碍遗传研究的系统荟萃分析；荟萃分析将涵盖来自三个不同类别的基因组实验的数据，包括a）序列变化的关联研究，b）拷贝数变化的关联研究，c）基因表达研究； 2）开发一种基于网络的生物信息学资源，我们称为“ metamoodics”，用于在显着基因组注释的背景下呈现荟萃分析的结果；和3）在“ Metamoodics”中开发一种计算工具，以从三类基因组实验中进行基因集的富集分析，以测试有关某些分子遗传学途径的假设，以便通过该工具实施该工具，以测试WNT信号途径是否与您的敏感性相关联，该工具是否已与BiPollials进行了研究。我们计划通过利用我们可以使用的智力和技术资源来有效地实现这些目标。我们是一支由精神科医生，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，一直在研究情绪障碍的遗传学二十年来一直处于最前沿。我们在这个项目上的目标是创建一个中心位置，科学界可以聚集在一起，以探索有关哪些基因可能有助于对情绪障碍的易感性的当前知识状态，从而有助于指导在最富有成果的方向上对基因组的未来研究。通过实现这一目标，我们将创建一个资源，应有助于加速遗传因素如何促进情绪障碍病因的发现的速度。 公共卫生相关性：情绪障碍对公共卫生造成了重大负担；因此，了解他们的原因很重要。该建议旨在通过对情绪障碍中的可用基因关联和表达研究进行系统评价，并开发基于Web的生物信息学资源，以在其他基因组信息的背景下整合结果，来推进对遗传原因的研究。 Web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信号通路）的病因贡献。