The Integrative Genomics of Acute Asthma Control

描述(由申请人提供)：该建议的总体假设是，哮喘控制的个体间差异是在离散的、无尺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的结果。虽然患者严格遵守哮喘控制治疗和避免环境触发是预防哮喘恶化的重要策略，但未能保持控制是最常见的与健康有关的失学和工作日原因。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。使用哮喘综合基因组探索生物信息库(哮喘桥)，我们将执行一系列系统级基因组分析，整合临床、环境和各种形式的“基因组”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，损害哮喘控制。这项建议包括三个具体目标，每个阶段包括三个研究阶段：(I)使用哮喘桥数据集定义特定分子网络的初始计算发现阶段，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)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)的实验阶段。在具体目标1中，我们将使用哮喘桥数据集来定义哮喘控制不良时干扰的相互作用组子模块；调节该哮喘控制模块的调节变量；并开发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哮喘控制网络调节的影响，测试网络动力学中环境相关的变化。在具体目标3中，我们将通过比较吸入皮质类固醇(ICS-最有效的哮喘控制药物)和未服用ICS的受试者之间急性哮喘控制的网络拓扑，来研究吸入皮质类固醇(ICS)对哮喘控制子模块网络动力学的影响。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细胞株来评估相关基因-基因的相互作用。对AIM 2发现的实验验证将 通过与香烟烟雾提取物(CSE)或臭氧共同处理细胞来实现。类似的研究将在地塞米松联合治疗的情况下进行，以验证AIM 2的发现。从这些研究的总体上，我们将获得对哮喘控制不良的病理生物学的新见解，并确定生物标记物开发和治疗靶点。

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.