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A computational genomics approach to identify roles of rare genetic variants in psychiatric disorders and gene expression

一种计算基因组学方法，用于识别罕见遗传变异在精神疾病和基因表达中的作用

基本信息

批准号：
9975854
负责人：
Jae Hoon Sul
金额：
$ 20.48万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-01 至 2021-04-25
项目状态：
已结题

项目摘要

Project Summary This is a proposal for the K01 Mentored Career Development Award in Biomedical Big Data Science. The goal of this proposal is to obtain training in biomedical science with focus on psychiatric disorders, and perform research to discover rare genetic variants that influence human complex traits including two psychiatric disorders, bipolar disorder (BP) and schizophrenia (SCZ). Identifying those rare variants is critical for both biology and human health as it will elucidate the genetic basis of those disorders and facilitate development of treatment. Recently, as the cost of next-generation sequencing decreases at a rate faster than that described by Moore's law for computer chips, many genetic studies are utilizing whole-genome sequencing (WGS) to identify roles of rare variants in human complex traits. However, these studies have had limited success most likely due to the small sample size. In this proposal, I will analyze three WGS data sets that provide unique opportunities to find effect of rare variants. The first is WGS data of large pedigrees with BP in which rare variants may be enriched in a certain large family, increasing our chance to detect their effect. The second is expression quantitative trait loci data that contain WGS and RNA-Seq from Genotype-Tissue Expression (GTEx) initiative. GTEx collected gene expression from multiple human tissues, which would enable discovery of functional effects of rare variants on different tissues. The third is WGS data of 4,000 BP and SCZ case-control samples from two recently bottlenecked populations. Deleterious rare variants may have elevated allele frequency in these populations, which increases statistical power to detect their effect. To effectively analyze the three WGS data sets, I will develop a new statistical approach and also utilize methods that I already developed. These methods combine effects of multiple rare variants in a gene to increase statistical power. I will apply these methods to the three WGS data sets to identify rare variants that influence psychiatric disorders (BP and SCZ) and gene expression. Although I have considerable knowledge and expertise in computer science and statistics, I seek to obtain additional training in biomedical science, especially in psychiatric disorders and clinical research to better interpret results of the rare variant analyses and extract biologically meaningful information from results. I will participate in several courses and workshops offered at UCLA and other institutions to obtain this training. This training will enable me to design and lead genomic studies for psychiatric disorders and to develop a niche as a statistical geneticist. These immediate goals will be the basis for my long-term career goal, which is to enhance understanding of how genome sequences influence one's susceptibility to diseases and to develop personalized treatments. I will be mentored by Drs. Nelson Freimer, Jonathan Flint, and Giovanni Coppola who are experts in neuropsychiatric disorders and genomics. They will provide guidance on my education and research training throughout the award period.

项目摘要这是生物医学大数据科学K01导师职业发展奖的提案。的目标是这项建议是为了获得生物医学方面的培训，重点是精神障碍，并进行研究发现影响人类复杂特征的罕见基因变异，包括两种精神障碍，躁郁症精神障碍(BP)和精神分裂症(SCZ)。识别这些罕见的变异对生物学和人类都是至关重要的因为它将阐明这些疾病的遗传基础，并促进治疗的发展。最近，因为下一代测序的成本以比摩尔定律所描述的速度更快的速度下降随着计算机芯片的出现，许多遗传学研究正在利用全基因组测序(WGS)来确定REARE的作用人类复杂特征的变异。然而，这些研究的成果有限，很可能是因为规模较小。样本大小。在这个提案中，我将分析三个WGS数据集，它们提供了独特的机会来发现罕见的变种。第一个是具有BP的大型家系的WGS数据，在这些家系中，稀有变异可能在特定的大家庭，增加了我们发现其影响的机会。第二个是表达数量性状基因座数据含有WGS和来自基因组织表达(GTEx)倡议的RNA-Seq。GTEx收集的基因从多个人类组织中表达，这将使发现稀有变体对细胞的功能影响不同的组织。三是最近采集的4,000个BP和SCZ病例对照样本的WGS资料人口瓶颈。有害的稀有变异可能在这些人群中具有更高的等位基因频率，这增加了检测其影响的统计能力。为了有效地分析三个WGS数据集，我将开发一种新的统计方法，并利用我已经开发的方法。这些方法结合了基因中的多个稀有变异对提高统计能力的影响。我将把这些方法应用到这三个方面 WGS数据集，以识别影响精神障碍(BP和SCZ)和基因表达的罕见变异。虽然我在计算机科学和统计学方面有相当多的知识和专业知识，但我寻求获得生物医学方面的额外培训，特别是精神障碍和临床研究方面的培训，以更好地解释罕见变异分析的结果，并从结果中提取有生物学意义的信息。这就做参加加州大学洛杉矶分校和其他机构提供的几个课程和研讨会，以获得这种培训。这培训将使我能够设计和领导精神障碍的基因组研究，并开发作为统计遗传学家。这些眼前的目标将是我长期职业目标的基础，那就是增强了解基因组序列如何影响一个人对疾病的易感性并形成个性化治疗。我将得到纳尔逊·弗雷默博士、乔纳森·弗林特博士和乔瓦尼·科波拉博士的指导，他们是神经精神障碍和基因组学。他们将为我的教育和研究培训提供指导在整个颁奖期间。