The Integrative Genomics of Acute Asthma Control

急性哮喘控制的综合基因组学

基本信息

批准号：
9301013
负责人：
ALBERT-LASZLO BARABASI
金额：
$ 83.07万
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：
2014
资助国家：
美国
起止时间：
2014-08-06 至 2020-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9301013
关键词：
Acute Adrenal Cortex Hormones Adult Affect Affinity Chromatography Air Pollution Asthma Behavior Biological Biometry Breathing Cell Line Cells Child Chronic Clinical Clinical Data Complex DNA Methylation Data Data Set Databases Dexamethasone Disease Environment Environmental Epidemiology Environmental Exposure Environmental Impact Environmental Risk Factor Environmental Tobacco Smoke Epigenetic Process Epithelial Exposure to Failure Gene Expression Gene Expression Profile Gene Targeting Genes Genetic Genetic Transcription Genetic study Genomics Glucocorticoids Health Hospitalization Human Impairment Individual Individual Differences Investigation Lead Lung diseases Maps Measures Medical Methods Modeling Molecular Molecular Biology Molecular Models Network-based Ozone Particulate Matter Pattern Pharmaceutical Preparations Phase Plasma Prevention strategy Process Research Research Personnel Resources Role Sampling Schools Science Series Socioeconomic Factors Spirometry Symptoms System T-Lymphocyte Testing Therapeutic Tobacco smoke Validation Variant Work asthma inhaler asthma prevention asthmatic asthmatic patient biobank biomarker development bronchial epithelium candidate marker cigarette smoking cohort compliance behavior cost data modeling drug candidate environmental tobacco smoke exposure gene interaction genetic epidemiology genome-wide genomic RNA immortalized cell insight knock-down molecular modeling network models non-compliance novel novel therapeutics phenotypic data predictive modeling prospective protein protein interaction public health relevance repository small hairpin RNA targeted biomarker therapeutic target

项目摘要

DESCRIPTION (provided by applicant): The over-arching hypothesis of this proposal is that inter-individual differences in asthma control result from the complex interplay of both environmental, genomic, and socioeconomic factors organized in discrete, scale-free molecular networks. Though strict patient compliance with asthma controller therapy and avoidance of environmental triggers are important strategies for the prevention of asthma exacerbation, failure to maintain control is the most common health-related cause of lost school and workdays. Therefore, better understanding of the molecular underpinnings and the role of environmental factors that lead to poor asthma control is needed. Using the Asthma BioRepository for Integrative Genomic Exploration (Asthma BRIDGE), we will perform a series of systems-level genomic analyses that integrate clinical, environmental and various forms of "omic" data (genetics, genomics, and epigenetics) to better understand how molecular processes interact with critical environmental factors to impair asthma control. This proposal consists three Specific Aims, each consisting of three investigational phases: (i) an initial computational discovery phase to define specific molecular networks using the Asthma BRIDGE datasets, followed by two validation phases - (ii) a computational validation phase using an independent clinical cohort, and (iii) an experimental phase to validate critical molecular edges (gene-gene interactions) that emerge from the defined molecular network. In Specific Aim 1, we will use the Asthma BRIDGE datasets to define interactome sub-module perturbed in poor asthma control; the regulatory variants that modulate this asthma-control module; and to develop a predictive model of asthma control. In Specific Aim 2, we will study the effects exposure to air pollution and environmental tobacco smoke on modulating the asthma control networks, testing for environment-dependent alterations in network dynamics. In Specific Aim 3, we will study the impact of inhaled corticosteroids (ICS - the most efficacious asthma-controller medication) on network dynamics of the asthma-control sub-module by comparing network topologies of acute asthma control between subjects taking ICS to those not on ICS. For our experimental validations, we will assess relevant gene-gene interactions by shRNA studies bronchial epithelial and Jurkat T- cell lines. Experimental validations of findings from Aim 2 will be performed by co-treating cells with either cigarette smoke extract (CSE) or ozone. Similar studies will be performed with co-treatment using dexamethasone to validate findings from Aim 2. From the totality of these studies, we will gain new insights into the pathobiology of poor asthma control, and define targets for biomarker development and therapeutic targeting.

描述（由申请人提供）：该提议的过度假设是，在离散的，无标度的分子网络中组织的环境，基因组和社会经济因素的复杂相互作用引起了哮喘控制的个体间差异。尽管严格的患者遵守哮喘控制器疗法和避免环境触发因素是预防哮喘加重的重要策略，但未能维持控制是失去学校和工作日的最常见的与健康相关的原因。因此，需要更好地了解分子基础和导致哮喘控制差的环境因素的作用。我们将使用哮喘生物措施进行综合基因组探索（哮喘桥），我们将进行一系列系统级别的基因组分析，以整合临床，环境和各种形式的“ OMIC”数据（遗传学，基因组学和表观遗传学），以更好地了解分子过程如何与关键环境因素相互作用以抑制ASTHMA的关键环境因素。 This proposal consists three Specific Aims, each consisting of three investigational phases: (i) an initial computational discovery phase to define specific molecular networks using the Asthma BRIDGE datasets, followed by two validation phases - (ii) a computational validation phase using an independent clinical cohort, and (iii) an experimental phase to validate critical molecular edges (gene-gene interactions) that emerge from the defined molecular network.在特定的目标1中，我们将使用哮喘桥数据集定义哮喘控制差的相互作用的子模块。调节此哮喘控制模块的调节变体；并开发哮喘控制的预测模型。在特定目标2中，我们将研究对空气污染和环境烟草烟雾调节哮喘控制网络的影响，并测试与环境依赖性网络动力学的变化。在特定的目标3中，我们将研究吸入的皮质类固醇（ICS，是最有效的哮喘控制药物）对哮喘控制亚模型网络动力学的影响，通过比较对受试者对IC的急性哮喘控制的网络拓扑的网络拓扑的影响，而不是对ICS进行ICS。对于我们的实验验证，我们将通过SHRNA研究支气管上皮和Jurkat T细胞系来评估相关的基因 - 基因相互作用。 AIM 2的发现的实验验证将通过与香烟烟雾提取物（CSE）或臭氧共同治疗细胞进行。将使用地塞米松进行类似的研究，以验证AIM 2的发现。从这些研究的整体中，我们将获得对贫困哮喘控制病理生物学的新见解，并定义了生物标志物发育和治疗靶标的靶标。