Immune and metabolic correlates of Coccidioides disease spectrum and outcomes

球虫感染可导致多种类型的急性或慢性肺部疾病(谷热) 疾病的严重性。然而，球孢子菌病的严重程度和治疗失败的机制并不是 播散性或未解决感染的充分阐明和相关性尚未得到很好的确立。整体而言 项目3的目标是调查球虫感染和疾病的免疫和代谢相关性。 以确定疾病的发病机制。我们免疫反应的初步数据和 球孢子虫感染患者样本中的代谢组特征 关键的失调通路。我们假设球虫感染引起的代谢变化反映了 主要失调的宿主细胞通路可以预测疾病的严重程度和临床结果。我们建议 加强我们在球孢子菌病诊断和大型患者临床护理方面的集体优势 在加州大学戴维斯分校用球孢子虫感染来确定球孢子菌病的致病机制 研究一种可确定未来疾病进展过程的预后生物特征。这个项目 利用球孢子菌病患者临床样本收集和数据库的可用性， 现有中心的资源、免疫学和新陈代谢的技术和科学知识 分析，球孢子菌病的小鼠模型，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：确定该病的免疫和代谢相关因素 谱和感染结果，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新诊断的球虫患者将接受免疫和代谢变化评估 并将确定关键的失调细胞/代谢途径和疾病结局的相关因素。目标 2：确定免疫和代谢与治疗失败的相关性，并确定导致治疗失败的机制 这次治疗失败了。播散性球虫感染合并严重疾病与 发病率/死亡率。UC临床护理的播散性球虫患者的临床标本 戴维斯将参加这项前瞻性研究。目的3：探讨慢性阻塞性肺疾病的致病决定因素。 在体内促进免疫和代谢功能障碍和肺部病理的球虫类化合物。我们会 利用球孢子菌病小鼠模型研究小鼠肺病理、嗜酸性粒细胞增多症的发生 以及球孢子虫野生型和突变株的代谢失调，并绘制了致病决定因素图。 将通过临床(项目3)对体内对球虫类药物的宿主反应进行综合分析， 代谢(项目3)和转录(项目2)数据和球孢子虫突变株在体外和在 老鼠模型(核心3，项目1和2)总的来说，我们拟议的研究将(A)填补我们 了解致病决定因素和宿主因素对疾病谱的作用 (B)确定疾病结局的潜在相关因素和治疗目标。

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.