Methylomic and metabolomic determinants of Lung Function in Asthmatics

项目总结/摘要 哮喘进展与生长减慢和肺功能（LF）下降增加有关， 被认为是基因和环境复杂相互作用的结果。虽然几个哮喘遗传风险位点 到目前为止，环境因素如何与这些位点相互作用的深入利用仍然存在 有限公司甲基化组和代谢组都受到环境和最近研究的严重影响 确认这两个人之间的联系将DNA甲基化与代谢组相结合可能是一种强大的 一种获得影响哮喘肺功能轨迹的特定途径的会聚证据的方法， 全基因组水平。虽然以前的研究已经调查了代谢组或甲基化组的作用， 关于肺功能，没有人同时研究两种“omes”的肺功能结局， 哮喘患者这一提议的中心假设是DNA甲基化（CpG位点）在DNA甲基化中起着关键作用。 在调节下游代谢物和代谢途径中的作用，其中一些可能是由 哮喘儿童肺功能的潜在遗传效应。我们要特别调查 来自Wnt、Hippo和鞘脂通路的多组学数据，已知通常影响哮喘肺功能 在我们的初步数据中。我们利用了遗传，甲基组学和代谢组学数据， 三个大型前瞻性儿童队列，包括两个来自精准医学的跨组学（TOPMed） 儿童哮喘管理计划（CAMP）和哮喘遗传流行病学研究 哥斯达黎加（GECRA）研究和一项独立队列研究：维生素D治疗哮喘缓解试验 （VDAART）.本研究旨在使用创新和最先进的方法整合多种组学： 数量性状基因座（QTL）定位，以确定基因组甲基化与LF的关联（目的1），QTL定位 和因果推理测试，以评估甲基化代谢组与LF（目标2）的关联，基于相关性 网络方法，以确定一组高度相关的组学驱动的生物标志物在失调的途径（目的3）。 Priyadarshini Kachroo博士，MS是一名生物信息学家，其长期职业目标是向 成为一名独立的数据科学家，拥有利用多组学方法治疗复杂疾病的专业知识 表型随着Kachroo博士完成这些目标，她的职业发展计划将支持她的培训目标： 1)加深对哮喘LF表型的临床理解; 2）扩展统计技能，包括因果关系 推理测试3）开发用于集成多组学数据集网络方法的技能集4）提高以下技能： 研究设计、指导和科学行为的道德以及研究交流。Kachroo医生的 强大的定量和方法论背景使她能够实现这些目标，完成 这一建议的目的，并准备她的独立研究生涯。一个多样化的世界的支持- 类辅导和咨询团队在网络医学的钱宁司在布里格姆和妇女的 医院和哈佛医学院补充了研究领域，并确保这一建议的成功。

PROJECT SUMMARY/ABSTRACT Asthma progression is associated with reduced growth and an increased decline in lung function (LF) that is thought to arise from a complex interplay of genes and environment. While several asthma genetic risk loci have been identified to-date, an in-depth utilization of how environmental factors interact with these loci remains limited. The methylome and the metabolome are both heavily influenced by the environment and recent studies confirm a link between both omes. Integrating DNA methylation with the metabolome could be a powerful approach to obtain converging evidence of specific pathways influencing asthmatic lung function trajectories at the genome-wide level. While previous studies have investigated the role of the metabolome or methylome with regard to lung function, none have investigated both “omes” simultaneously for lung function outcomes in asthmatics. The central hypothesis of this proposal is that DNA methylation (CpG sites) plays a critical role in modulating downstream metabolites and thus metabolic pathways, some of which may be driven by an underlying genetic effect on lung function in children with asthma. We want to specifically investigate multi-omic data from Wnt, Hippo and sphingolipid pathways, known to affect asthmatic lung function generally and in our preliminary data. We capitalize on the genetic, methylomic and metabolomic data generated from three large prospective childhood cohorts including two from the Trans-omics for Precision Medicine (TOPMed) consortium: Childhood Asthma Management Program (CAMP) and The Genetic Epidemiology of Asthma in Costa Rica (GECRA) study and an independent cohort: The Vitamin D Antenatal Asthma Reduction Trial (VDAART). This study seeks to integrate multiple omics using innovative and state-of-the-art methodologies: quantitative trait loci (QTL) mapping to identify genome-methylome associations with LF (Aim 1), QTL mapping and causal inference testing to evaluate methylome-metabolome associations with LF (Aim 2), correlation-based network methods to identify a highly correlated set of omic-driven biomarkers in dysregulated pathways (Aim 3). Priyadarshini Kachroo, PhD, MS is a bioinformatician whose long-term career goal is to transition towards becoming an independent data scientist with expertise in utilizing multi-omic approaches to complex disease phenotypes. As Dr. Kachroo completes these aims, her career development plan will support her training goals: 1) deepen clinical understanding of asthmatic LF phenotypes; 2) expand on the statistical skills including causal inference testing 3) develop skill-set of network methods for integrating multi-omic datasets 4) enhance skills in study-design, mentorship and the ethics of scientific conduct and communication of research. Dr. Kachroo’s strong quantitative and methodological background well position her to accomplish these goals, complete the aims of this proposal and prepare her for an independent research career. The support of a diverse and world- class mentoring and advisory team in the Channing Division of Network Medicine at Brigham and Women’s Hospital and Harvard Medical School complement the research areas and ensure success of this proposal.