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

基于多组学数据的综合网络分析，阐明哮喘和慢性阻塞性肺病之间的分子联系

基本信息

批准号：
10219832
负责人：
Arda Halu
金额：
$ 18.9万
依托单位：
BRIGHAM AND WOMEN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-18 至 2025-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10219832
关键词：
Address Adult Advisory Committees Algorithms Area Asthma Award Big Data Bioinformatics Biological Biology Blood Blood specimen CD4 Positive T Lymphocytes Catalogs Childhood Childhood Asthma Chronic Obstructive Airway Disease Complex Computing Methodologies Confidence Intervals DNA Methylation Data Development Disease Disease Progression Disease model Educational workshop Environment Epidemiology Epigenetic Process Etiology Fetal Lung Gene Expression Genes Genetic Genetic Risk Genetic Transcription Genome Genomics Impairment Life Link Lung Lung diseases Mediating Mediator of activation protein Medical Informatics Medicine Mentors Messenger RNA Methodology Methods Methylation MicroRNAs Modeling Molecular Multiomic Data Network-based Pathway interactions Pattern Peripheral Blood Mononuclear Cell Phenotype Physics Play Population Proteome Public Health Research Role SNP genotyping Sampling Signal Transduction Site Smoke Standardization Structure of parenchyma of lung System Systems Biology Teaching Hospitals Testing Time Tissue Microarray Tissues Training Training Programs Transcription Process Whole Blood airway obstruction asthmatic base chronic airflow obstruction clinical translation cohort computing resources epigenetic regulation epigenomics fetal smoke exposure high risk human data improved in utero insight lung development medical schools meetings member precision medicine prenatal risk variant skills transcriptomics

项目摘要

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.

项目总结/文摘