EXposomic Profiling in Airway disease to uNravel Determinants of disease in Asthma (EXPAND-Asthma) Center

摘要 哮喘是一种异质性和高负担的疾病，集中在有色人种和 社会经济地位低。临床哮喘的异质性反映了分子、蛋白质和蛋白质之间复杂的相互作用 环境、社会因素共同影响疾病结果和治疗反应。社会-- 环境暴露，包括心理社会应激源和空气污染，历史上集中在 在边际化社区，他们造成了糟糕的哮喘结果。然而，这些机制 在这些与暴露相关的结果背后，人们对此知之甚少。迫切需要了解如何 哮喘分子异质性1)在边缘人群中活动；2)受流行的影响 社会环境因素。提出的多组学方法既系统地考虑了病理学，又考虑了 在疾病的主要部位，呼吸道，对于解开接触之间的复杂相互作用至关重要， 这些未得到充分研究的社区的机制和成果。该项目的目标是招收200名青年和 加利福尼亚州里士满的100名没有哮喘的年轻人，这是一个以拉丁裔为主的社区，社会环境 应激源负担和哮喘患病率均在25%以上。多组数据将来自血液和呼吸道 (鼻拭子和痰)在病情稳定一年以上时采集样本和呼吸道样本采集 在急性呼吸事件和康复期间。这些数据将与深入的表型和暴露相结合 测试三个具体目标的数据。第一个目标是研究高心理社会压力之间的关系。 以及哮喘和健康的多组学结果。一种假设驱动的方法将关注压力- 与哮喘相关的病理改变，包括全身和呼吸道免疫反应、应激 激素相关微生物群的变化，以及β-肾上腺素能和糖皮质激素的病理学。第二个目标是 检查室内和室外空气污染与哮喘和多种疾病结局之间的关系 健康。将利用室内和精细分辨率室外空气污染监测进行暴露评估，以 考虑污染物如何与免疫反应、呼吸道修复和跨多组层的细胞应激有关。 第三个目标将研究社会环境和微生物沉淀剂在哮喘加重中的作用。 敏感性和机制，利用基线和急性呼吸事件期间获得的样本。一个 自定义多组分析流水线，考虑微生物加重沉淀剂和环境 将使用曝光。我们的最终目标是了解潜在的社会环境机制 影响哮喘结果的暴露，为治疗和管理决策提供信息和影响 以地点为基础的缓解努力的目标。

ABSTRACT Asthma is a heterogeneous and highly burdensome disease that is concentrated in communities of color and of low socioeconomic status. Clinical asthma heterogeneity reflects complex interactions between molecular, environmental, and social factors that combine to influence disease outcomes and therapeutic response. Socio- environmental exposures, including psychosocial stressors and air pollution, are concentrated in historically marginalized communities where they contribute to poor asthma outcomes. However, the mechanisms underlying these exposure-related outcomes are poorly understood. There is a critical need to understand how asthma molecular heterogeneity 1) operates in marginalized populations; and, 2) is influenced by prevalent socio-environmental factors. The proposed multi-omics approach considering pathology both systemically and at the main site of disease, the airways, is crucial to unraveling the complex interactions between exposures, mechanisms, and outcomes in these understudied communities. This project aims to enroll 200 youth with and 100 youth without asthma in Richmond, CA, a predominantly Latine community with high socio-environmental stressor burden and asthma prevalence upwards of 25%. Multi-omic data will be derived from blood and airway (nasal swab and sputum) samples collected at disease stability over one year and airway samples collected during acute respiratory events and recovery. These data will be integrated with deep phenotyping and exposure data to test three specific aims. The first aim will examine the relationships between high psychosocial stress and multi-omic outcomes across asthma and health. A hypothesis driven approach will focus on stress- associated asthma-relevant pathologic alterations including systemic and airway immune responses, stress hormone associated microbiome shifts, and beta-adrenergic and glucocorticoid pathology. The second aim will examine the relationships between indoor and outdoor air pollution and multi-omic outcomes across asthma and health. Indoor and fine-resolution outdoor air pollution monitoring will be leveraged for exposure assessments to consider how pollutants relate to immune responses, airway repair, and cellular stress across multi-omic layers. The third aim will examine the role of socio-environmental and microbial precipitants in asthma exacerbation susceptibility and mechanisms, leveraging samples obtained at baseline and during acute respiratory events. A custom multi-omic analytical pipeline that considers microbial exacerbation precipitants along with environmental exposures will be used. Our ultimate goal is to understand the mechanisms underlying socio-environmental exposures that influence asthma outcomes to inform therapeutic and management decisions and influence targets for place-based mitigation efforts.