Integrative Dynamic Omics Profiling: A First Step Towards Personalized Medicine

综合动态组学分析：迈向个性化医疗的第一步

• 批准号: 8424610
• 负责人: George Ioannou Mias
• 金额: $ 9万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-03-15 至 2014-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8424610
• 关键词: Accounting; Address; Adopted; Algorithms; Award; B-Lymphocytes; Biological; Biological Models; Biological Process; Caring; Categories; Cell Line; Cells; Collection; Communities; Complex; Computing Methodologies; Data; Development; Diagnosis; Disease; Evolution; Excision; Faculty; Funding; Gene Proteins; Genetic; Genomics; Individual; Investigation; Laboratories; Lead; Learning; Measures; Medical; Medicine; Mentors; Metabolic Pathway; Methodology; Methods; Modeling; Molecular; Monitor; NF-kappa B; Nature; Noise; Onset of illness; Outcome; Pathway interactions; Patients; Phase; Physiological; Positioning Attribute; Precursor B-Lymphoblast; Preventive Medicine; Procedures; Process; Proteomics; Research; Resources; Sampling; Signal Pathway; Statistical Methods; System; Techniques; Technology; Testing; Time; Transcript; base; biological systems; career; computerized data processing; design; human disease; improved; innovation; insight; interest; lymphoblast; metabolomics; network models; new technology; novel; programs; protein metabolite; public health relevance; research study; response; tool; transcriptomics; treatment effect

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.

描述（由申请人提供）：可用组学技术的快速发展有望极大地促进个性化，精准和预防医学的发展和应用。特别是，通过对分子组分变化的全球监测，如转录组学、蛋白质组学和代谢组学信息与监测不同的生理状态相结合，整合基因组信息，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种组学数据的分析和整合，以期实现医疗适用性。这项为期4年的K99/R00计划的拟议研究将在Michael Snyder博士的实验室开始，Michael Snyder博士是遗传学和多组学领域的知名专家，他将在K99年期间担任George Mias博士的导师。在这个建议中，最重要的是开发一个框架来集成从多个时间点监测多个基因组信息获得的动态数据。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，结合个体组学数据，将数据分类为医学相关类别，以及通过途径分析确定生物学意义。在K99期间，将解决数据采样不均匀、缺少重复和噪声等从患者中获取样本所固有的问题。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，并将定义时变网络，可以分析生理状态之间转换的详细解释。为了开发计算方法，将进行高度精确的实验，通过监测受刺激B细胞（K99期淋巴细胞和R00期原代B细胞）在多个时间点上的基因、蛋白质和代谢物表达，重点关注重要而复杂的核因子κ B (NF？B)信号通路。此外，开发的工具、算法和数据将在00期间传播给科学界。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用于跨多个平台的组学整合，并获得独立研究所需的实验背景。Snyder博士实验室的独特性质将为Mias博士提供与实验专家密切互动和合作的机会，这些专家在遗传学组学研究的前沿进行研究。此外，实验室的广泛资源随时可供米亚斯博士使用，这将极大地促进他的研究和学术努力。K99/R00奖项将使Mias博士顺利过渡到R00阶段的独立教师职位，并成功地在他自己的实验室领导新的研究。