Novel Cellular Immune Profiles to Predict Lung Disease Outcomes

描述(申请人提供)：纤维性肺部疾病是越来越重要的肺部疾病，在普通人群中的发病率不断上升。我们的应用重点是闭塞性细支气管炎综合征(BOS)，这是一种人类肺移植后发生的纤维性疾病，是肺移植受者长期存活率较低的主要原因。令人信服的证据表明，BOS存在调节性T细胞(Tregs)、效应/记忆性T细胞和自身免疫V型胶原(Col-V)的免疫失调。Col-V通常隐藏在免疫系统之外，可能暴露在肺损伤或炎症的环境中，成为免疫系统的靶点。由于免疫失调和自身免疫在BOS发病机制中的重要性，需要检验的主要假设是Treg或T效应/记忆群体的变化和/或他们对Col-V的多功能细胞因子反应预测BOS的发生。我们将利用杜克大学大量的临床移植人群，预期获得的和之前储存的PB样本，以及经验丰富的多学科研究团队的专业知识。我们将通过互补的AIMS来验证这一假设，这些AIMS使用多色流式细胞术来测量外周血中的T亚群(AIM 1)及其Col-V抗原特异性反应(AIM 2)，并应用创新的统计学和生物信息学来确定BOS的精确细胞预测因子(AIM 3)。我们的生物信息学方法旨在使用多变量混合建模来识别新的候选免疫生物标记物，并使用定义识别预测细胞亚集所需的最小标记物组的区别性信息度量来促进应用于临床诊断。在CADET-2中，我们将使用这些方法来识别BOS的高危个体，并测试特定的临床干预措施，如加强免疫抑制，将延迟或防止BOS的发生。由于免疫失调似乎是许多慢性纤维化肺部疾病的中心主题，一个长期的发展目标是利用通过这些肺移植概念验证研究建立的临床、技术和生物信息学专业知识，将先进的免疫图谱带入肺部医学临床诊断的前沿。相关性(见说明书)：虽然肺移植使许多晚期肺部疾病患者受益，但肺移植后的长期结果受到称为闭塞性细支气管炎的进行性主干纤维化的限制。我们的研究将在血液中识别新的免疫生物标记物，可以识别这种疾病的高危患者，从而允许更早和更有效的干预措施，从而改善长期移植结果。

DESCRIPTION (provided by applicant): Fibrotic lung diseases are increasingly important lung conditions, with a rising incidence in the general population. Our application focuses on bronchiolitis obliterans syndrome (BOS), a fibrotic disease that occurs after human lung transplantation and is the primary reason for poor long-term survival among lung transplant recipients. Compelling evidence suggests that immune dysregulation involving regulatory T cells (Tregs), effector/memory T cells, and autoimmunity to type V collagen (Col-V) occurs in BOS. Normally hidden from the immune system, Col-V may be exposed in the setting of lung injury or inflammation and become an immune system target. Because ofthe importance of immune dysregulation and autoimmunity in the pathogenesis of BOS, the primary hypothesis to be tested is that alterations in Treg or T effector/memory populations and/or their polyfunctional cytokine response to Col-V predict the development of BOS. We will leverage the large clinical transplant population at Duke, prospectively obtained and previously banked PB samples, and the expertise of a highly experienced multi-disciplinary team of investigators. We will test this hypothesis through complementary aims that use polychromatic flow cytometry to measure T subsets in the peripheral blood (Aim 1) and their Col-V antigen specific responses (Aim 2) and apply innovative statistics and bioinformatics to identify precise cellular predictors of BOS (Aim 3). Our bioinformatics approach is designed to identify novel candidate immune biomarkers using multivariate mixture modeling and to facilitate application into clinical diagnostics using discriminative information measures that define the minimal group of markers necessary to identify predictive cellular subsets. In CADET-2, we will use these approaches to identify individual at high risk for BOS and test the idea that specific clinical interventions, such as intensification of immunosuppression, will delay or prevent its onset. As immune dysregulation appears a central theme across many chronic fibrotic lung diseases, a long-term development goal is to use the clinical, technical and bioinformatics expertise established through these proof-of-concept studies in lung transplant to bring advanced immune profiling to the forefront of clinical diagnostics in pulmonary medicine. RELEVANCE (See instructions): Although lung transplantation benefits many patients with advanced lung disease, long-term outcomes after lung transplantation are limited by progressive ainway fibrosis called bronchiolitis obliterans. Our research will identify novel immune biomarkers in the blood that can identify patients at high risk for this condition, thereby allowing for early and more effective interventions that will improve long-term transplant outcomes