Integrative network-based analysis of multi-omics data to elucidate the molecular connection between asthma and COPD

项目摘要/摘要 越来越多的证据表明哮喘和慢性阻塞性肺疾病之间存在病因学联系 (COPD)轻至中度持续性哮喘患者易发生持续性气流阻塞， 他们患慢性阻塞性肺疾病的风险更高。此外，宫内烟雾引起的表观遗传调节(IUS) 胎儿肺发育期间的暴露可能在哮喘和COPD中发挥作用。这些数据和其他数据表明， 从出生前肺发育到儿童哮喘再到成年慢性阻塞性肺疾病的肺损伤的终生轨迹。 纵向和仔细的表型多组学数据提供了理解分子的机会 这种疾病轨迹的决定因素。系统和网络生物学方法有可能有效地 整合、分析和解释多组学数据。尤其是多层网络，提供了可行的第一步 在从基因组到蛋白质组的多个分子水平上联合模拟疾病扰动。在这 应用，我们将同时分析丰富的多组学数据(SNP基因分型、DNA甲基化、mRNA 和miRNA表达)作为长期存在的哮喘和COPD队列的一部分，使用多层网络收集 方法：研究方法。我们将首先将IUS暴露、哮喘和COPD多组学数据整合到网络中，并开发 他们的统计框架，以便利后续的生物信息学分析。然后我们将追踪发展情况 通过对胎肺和儿童哮喘多组学数据的综合时间分析，探讨哮喘的发病机制。最后， 我们将确定从早期哮喘到慢性阻塞性肺疾病表型转变的关键分子和途径 使用多层网络的成年。Halu博士在统计物理和复杂网络方面的培训已经准备好 他对他提出的研究很满意。然而，理解连接复杂肺的分子基础 通过多组学数据分析哮喘和慢性阻塞性肺病等疾病是一项艰巨的任务，需要 在特定领域进行进一步培训。Halu博士将利用哈佛医学院优秀的智力环境 学校(HMS)及其教学医院，并将通过 陈宁市网络医学与卫生管理科。通过正式的课程作业和研讨会，并在 在一个具有互补专业知识的指导和咨询团队中，Halu博士将全身心投入到培训中 专注于统计遗传学、表观遗传学和组学集成的计划，医学信息学中的大数据，以及 肺部疾病生物学与临床翻译。Halu博士还将参加与 他的导师和顾问委员会成员，这将使他能够分享他的进步。总之，哈鲁博士的 培训和研究计划将使他能够扩展他目前的技能集，包括解决 分析大型流行病学队列的复杂基因组和表观基因组数据的挑战，确定 哮喘和慢性阻塞性肺疾病的系统生物学中的悬而未决的问题，并最终为精确医学做出贡献 肺部疾病。

Project Summary/Abstract Growing evidence suggests an etiological link between asthma and chronic obstructive pulmonary disease (COPD) wherein mild-to-moderate persistent asthmatics are susceptible to persistent airflow obstruction, putting them at a higher risk for developing COPD. Furthermore, epigenetic modulation due to in utero smoke (IUS) exposure during fetal lung development may play a role in asthma and COPD. These and other data suggest a lifelong trajectory of lung impairment from prenatal lung development to childhood asthma to COPD in adulthood. Longitudinal and carefully phenotyped multi-omic data offer the opportunity to understand the molecular determinants of this disease trajectory. Systems and network biology methods hold the potential to effectively integrate, analyze and interpret multi-omics data. Multilayer networks, in particular, offer a feasible first step to model disease perturbations jointly across multiple molecular levels, from the genome to the proteome. In this application, we will simultaneously analyze the rich multi-omics data (SNP genotyping, DNA methylation, mRNA and miRNA expression) collected as part of long-standing asthma and COPD cohorts using multilayer network methods. We will first integrate IUS exposure, asthma and COPD multi-omics data into networks and develop their statistical framework to facilitate subsequent bioinformatics analyses. We will then track the developmental origins of asthma by the integrated temporal analysis of fetal lung and childhood asthma multi-omics data. Finally, we will identify key molecules and pathways of the phenotypic transition from asthma in early life to COPD in adulthood using multilayer networks. Dr. Halu’s training in statistical physics and complex networks has prepared him well for his proposed research. However, understanding the molecular basis connecting complex lung diseases such as asthma and COPD through the analysis of multi-omics data is a formidable task that will require further training in specific areas. Dr. Halu will leverage the excellent intellectual environment of Harvard Medical School (HMS) and its teaching hospitals, and will have access to extensive computational resources through the Channing Division of Network Medicine and HMS. Through formal coursework and workshops, and with the help of a mentoring and advisory team with complementary expertise, Dr. Halu will immerse himself in a training program focusing on statistical genetics, epigenetics, and omics integration, big data in medical informatics, and the biology of pulmonary diseases and clinical translation. Dr. Halu will also participate in regular meetings with his mentors and advisory board members, which will allow him to share his progress. Altogether, Dr. Halu’s training and research plan will enable him to expand his current skill set to include the ability to address the challenges of analyzing the complex genomic and epigenomic data of large epidemiological cohorts, identify open questions in the systems biology of asthma and COPD, and ultimately contribute to the precision medicine of lung disease.