Integrative Dynamic Omics Profiling: A First Step Towards Personalized Medicine

描述(由申请人提供)：可用组学技术的快速进步有望极大地帮助个性化、精确化和预防性医学的发展和应用。特别是，通过全球监测分子成分的变化，如转录组分、蛋白质组和代谢组信息的变化，结合监测不同的生理状态，有望获得新的医学见解。这就需要开发新的方法和工具来处理多个基因组数据的分析和集成，以期实现医学上的适用性。这项为期4年的K99/R00计划的拟议研究将在迈克尔·斯奈德博士的实验室开始，他是一位著名的遗传学和多重基因组学专家，他将在整个K99年度担任乔治·米亚斯博士的导师。这项建议的首要内容是开发一个框架，以整合通过监测多个时间点的多个基因组信息而获得的动态数据。这种创新的方法包括开发统计工具来分析不同的组学技术，包括原始数据处理、合并个体基因组数据、将数据归类到医学相关类别，以及通过路径分析确定生物学意义。在K99期间，将解决从患者获取样本时固有的考虑因素，如数据抽样不均匀、缺乏重复数据和噪音。此外，多个组学成分之间的相互作用将通过表达的变化来推断，并将定义可以分析的时变网络，以详细解释生理状态之间的转换。为了发展计算方法，将进行高精度的实验，通过监测刺激的B细胞[K99期的淋巴母细胞和R00期的原代B细胞]在多个时间点上的基因、蛋白质和代谢物的表达，重点关注重要和复杂的核因子-kappaB(NF？B)信号通路。此外，将在R00期间向科学界传播开发的工具、算法和数据。K99/R00奖项的拟议学习活动将使Mias博士能够将他的研究方法调整为跨多个平台的组学集成，并为独立研究获得必要的实验背景。斯奈德博士实验室的独特性质将为米亚斯博士提供与处于遗传学组学研究前沿的实验专家密切互动和合作的机会。此外，米亚斯博士随时可以获得的大量实验室资源将极大地促进他的研究和学术努力。K99/R00奖项将使Mias博士能够顺利过渡到R00阶段的独立教员职位，并在自己的实验室成功领导新颖的研究。

DESCRIPTION (provided by applicant): The rapid advancement in available -omics technologies is expected to greatly aid the development and application of personalized, precise and preventive medicine. In particular, novel medical insights are expected through the integration of genomic information through the global monitoring of changes in molecular components, such as transcriptomic, proteomic and metabolomic information in conjunction with monitoring varying physiological states. This necessitates the development of new methodology and tools to handle the analysis and integration of multiple omic data with a view towards medical applicability. The proposed research of this 4-year K99/R00 proposal will begin at the laboratory of Dr. Michael Snyder, a renowned expert in genetics and multiple omics, who will act as the mentor for Dr. George Mias throughout the K99 year of the award. Foremost in this proposal is the development of a framework to integrate dynamic data obtained from monitoring multiple omic information over multiple time points. The innovative methodology involves the development of statistical tools to analyze different omics technologies, including raw data processing, combining the individual omic data, categorizing the data in medically relevant categories, and ascertaining biological significance through pathway analyses. Considerations such as uneven sampling of data, lack of replicates and noise, inherent in obtaining samples from patients will be addressed during the K99 period. Additionally, the interactions between multiple omics components will be inferred through changes in expression, and time-varying networks will be defined that can be analyzed for detail explanation of transitions between physiological states. In order to develop the computational methodology, highly precise experiments will be performed, by monitoring gene, protein and metabolite expression over multiple time points in stimulated B-cells [lymphoblasts in K99 period and primary B cells in R00 period], with focus on the important and complex Nuclear Factor kappa B (NF?B) signaling pathways. Furthermore, developed tools, algorithms and data will be disseminated to the scientific community in the R00 period. The proposed learning activities of the K99/R00 award will allow Dr. Mias to adapt his research approaches to omics integration across multiple platforms, and acquire the necessary experimental background for independent investigations. The unique nature of Dr. Snyder's lab will provide Dr. Mias the opportunity to closely interact and collaborate with experimental experts conducting research at the forefront of omics research in genetics. Moreover, the lab's extensive resources readily available to Dr. Mias will greatly facilitate his research and academic endeavors. The K99/R00 award will enable Dr. Mias to smoothly transition into an independent faculty position in the R00 phase and successfully lead novel investigations in his own laboratory.