The Integrative Genomics of Acute Asthma Control

描述（由申请人提供）：本提案的首要假设是哮喘控制的个体间差异是由环境、基因组和社会经济因素在离散的、无标度的分子网络中组织的复杂相互作用造成的。虽然患者严格遵守哮喘控制治疗和避免环境触发因素是预防哮喘加重的重要策略，但未能保持控制是最常见的与健康相关的导致失学和旷工的原因。因此，需要更好地了解导致哮喘控制不良的分子基础和环境因素的作用。利用哮喘生物库整合基因组探索（Asthma BRIDGE），我们将进行一系列系统级基因组分析，整合临床、环境和各种形式的“组学”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，从而损害哮喘控制。该提案包括三个具体目标，每个目标由三个研究阶段组成：(i)初始计算发现阶段，使用Asthma BRIDGE数据集定义特定的分子网络，随后是两个验证阶段- (ii)使用独立临床队列的计算验证阶段，以及（iii）实验阶段，验证从定义的分子网络中出现的关键分子边缘（基因-基因相互作用）。在Specific Aim 1中，我们将使用Asthma BRIDGE数据集来定义哮喘控制不良的相互作用子模块；调节哮喘控制模块的调节变异；并建立哮喘控制的预测模型。在具体目标2中，我们将研究暴露于空气污染和环境烟草烟雾对调节哮喘控制网络的影响，测试网络动力学中环境依赖性的变化。在Specific Aim 3中，我们将通过比较服用和未服用类固醇的受试者急性哮喘控制的网络拓扑结构，研究吸入皮质类固醇（ICS -最有效的哮喘控制药物）对哮喘控制子模块网络动力学的影响。为了我们的实验验证，我们将通过shRNA研究支气管上皮和Jurkat T细胞系来评估相关基因-基因相互作用。第二阶段研究结果的实验验证将

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.