Immune and metabolic correlates of Coccidioides disease spectrum and outcomes

球孢子菌感染可导致急性或慢性肺部疾病（山谷热）， 疾病的严重程度。然而，球孢子菌病的严重性和治疗失败的机制并不清楚。 尚未完全阐明播散性或未解决感染的相关性。整体 项目3的目的是调查球孢子菌感染和疾病的免疫和代谢相关性 光谱和确定疾病发病机制。我们的免疫反应的初步数据， 来自感染球孢子菌的患者的样品中的代谢组学谱鉴定了 关键的失调途径。我们假设球孢子菌感染引起的代谢变化反映了 主要失调的宿主细胞途径可以预测疾病的严重程度和临床结果。我们提出 建立我们在球孢子菌病诊断和大型患者队列临床护理方面的集体优势 与球孢子菌感染，以确定球孢子菌病的致病机制， 研究一种可以识别疾病进展未来过程的预后生物标志。这个项目 利用来自球孢子菌病患者的临床样品收集和数据库的可用性， 现有中心的资源，免疫学和代谢的技术和科学知识 我们的研究团队拥有丰富的临床分析、球孢子菌病小鼠模型、强大的初步数据和多学科研究团队。 有三个具体目标。目的1：确定疾病的免疫和代谢相关性 并确定治疗靶向的途径。纵向样本来自 加州大学戴维斯分校的一名新诊断的球孢子菌病患者将接受免疫和代谢变化的评估 并将确定关键失调的细胞/代谢途径和疾病结果的相关性。目的 2：确定治疗失败的免疫和代谢相关性，并确定导致 治疗失败。播散性球孢子菌感染伴严重疾病与 发病率/死亡率。来自在UC接受临床治疗的播散性球孢子菌患者的临床样本 Davis将入组本前瞻性研究。目的3：研究大肠癌的致病因素， 球孢子菌在体内促进诱导免疫和代谢功能障碍以及肺病理学。我们将 利用球孢子菌病的小鼠模型来研究肺病理学的发展，嗜酸性粒细胞增多， 和代谢失调的球孢子菌属野生型和突变株和地图的致病决定因素。 将通过临床（项目3），对宿主体内对球孢子菌的反应进行综合分析， 代谢（项目3）和转录组学（项目2）数据，并在体外和 小鼠模型（核心3，项目1和2）总的来说，我们提出的研究将（a）填补我们的空白 了解致病决定因素和宿主因素在疾病谱中的作用 和（B）鉴定疾病结果和治疗靶点的潜在相关性。

Coccidioides infection leads to acute or chronic pulmonary disease (Valley Fever) with a wide spectrum of disease severity. However, the mechanisms of coccidioidomycosis severity and therapeutic failures are not fully elucidated and correlates of disseminated or unresolved infection are not well established. The overall objective of Project 3 is to investigate the immune and metabolic correlates of Coccidioides infection and disease spectrum and to identify mechanisms of disease pathogenesis. Our preliminary data of immune responses and metabolomic profiles in samples from patients infected with Coccidioides identified the metabolic signature of key dysregulated pathways. We hypothesize that Coccidioides infection-induced metabolic changes reflecting the major dysregulated host cellular pathways can predict disease severity and clinical outcomes. We propose to build on our collective strengths in coccidioidomycosis diagnostics and clinical care of large patient cohorts with Coccidioides infection at UC Davis to determine the pathogenic mechanisms of coccidioidomycosis and to investigate a prognostic biosignature that can identify the future course of disease progression. This project leverages the availability of clinical sample collection from patients with coccidioidomycosis and database, resources from the existing Centers, technical and scientific knowledge of immunological and metabolic analyses, mouse models of coccidioidomycosis, strong preliminary data and a multi-disciplinary research team. There are three specific aims. Aim 1: To determine immune and metabolic correlates of the disease spectrum and infection outcomes and identify pathways for therapeutic targeting. Longitudinal samples from newly diagnosed patients with Coccidioides at UC Davis will be evaluated for immune and metabolic changes and the key dysregulated cellular/metabolic pathways and correlates of disease outcomes will be identified. Aim 2: To identify immune and metabolic correlates of treatment failures and determine mechanisms contributing to this treatment failure. Disseminated Coccidioides infection with severe disease is associated with morbidity/mortality. Clinical samples from patients with disseminated Coccidioides receiving clinical care at UC Davis will be enrolled in this prospective study. Aim 3: To investigate the pathogenic determinants of Coccidioides that promote induction of immune and metabolic dysfunction and lung pathology in vivo. We will utilize the mouse model of coccidioidomycosis to investigate the development of lung pathology, eosinophilia and metabolic dysregulation by Coccidioides wild-type and mutant strains and map the pathogenic determinants. An integrated analysis will be performed of host responses to Coccidioides in vivo through clinical (Project 3), metabolic (Project 3) and transcriptomic (Project 2) data and to Coccidioides mutant strains in vitro and in the mouse model (Core 3, Projects 1 and 2) Collectively, our proposed studies will (a) fill the gaps in our understanding of the role of both pathogenic determinants and host factors contributing to the disease spectrum of Valley Fever and (b) identify potential correlates of disease outcomes and targets for therapy.