Imaging and Molecular Phenotyping of Cystic Fibrosis Lung Disease

囊性纤维化肺病的影像学和分子表型

基本信息

批准号：
10548868
负责人：
ZACKARY I CLEVELAND
金额：
$ 78.35万
依托单位：
CINCINNATI CHILDRENS HOSP MED CTR
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-02-03 至 2026-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10548868
关键词：
Acceleration Adolescence Adult Affect Age Anti-Inflammatory Agents Asthma Biological Markers Blood Blood Proteins Blood specimen Bronchi Bronchiectasis Bronchoalveolar Lavage Bronchoalveolar Lavage Fluid Bronchoscopy Cessation of life Chronic Obstructive Pulmonary Disease Clinical Clinical Trials Coupled Cystic Fibrosis Cystic Fibrosis Transmembrane Conductance Regulator Data Data Analyses Demographic Factors Diagnosis Disease Disease Progression Early Diagnosis Functional disorder Future Genetic Diseases Goals Health Heterogeneity Image Impairment Individual Infection Inflammation Intervention Investigation Irrigation Knowledge Life Life Expectancy Liquid Chromatography Liquid substance Lung Lung Transplantation Lung diseases Magnetic Resonance Imaging Mass Spectrum Analysis Measures Methods Mission Modeling Molecular Molecular Profiling Monitor Mucous body substance Mutation Nature Outcome Outcome Measure Pathologic Pathology Pathway interactions Patients Plasma Proteomics Public Health Pulmonary Cystic Fibrosis Pulmonary Function Test/Forced Expiratory Volume 1 Pulmonary Pathology Radiation Reaction Regulator Genes Research Resolution Respiratory Failure Respiratory Tract Infections Scanning Sensitivity and Specificity Serum Severity of illness Specialized Center Specimen Spirometry Structural defect Technology Testing Time Translating Translations United States United States National Institutes of Health Visualization Work X-Ray Computed Tomography airway remodeling children with cystic fibrosis cohort cystic fibrosis patients early cystic fibrosis evidence base functional decline functional loss high risk image guided imaging modality improved individualized medicine innovation loss of function lung injury molecular phenotype novel novel therapeutics personalized approach predictive marker prevent prognostic tool prospective pulmonary function pulmonary function decline reconstruction risk prediction model specific biomarkers tandem mass spectrometry tool ventilation

项目摘要

Cystic fibrosis (CF) is among the most common fatal genetic diseases in the U.S. and involves progressive lung function loss and structural remodeling, leading to lung transplant or death. Though life expectancy in CF patients has increased due to improved treatments, pathological changes still occur within the first year of life. It has been difficult to detect these early changes, because conventional measures of lung function such as spirometry (e.g., forced expiratory volume in 1 second, FEV1) are lagging indicators and insensitive to early disease. In contrast, ultra-short echo-time (UTE) and hyperpolarized (HP) 129Xe MRI can detect pathology years before FEV1. Addi- tionally, proteomic biomarkers from high-precisions mass spectrometry (MS), when coupled with modeling based on Functional Data (FD) analysis, accurately forecast CF lung disease progression. However, these biomarkers have only been validated in patients with established disease. The long-term goal of this research is to validate proteomic markers that detect and predict lung function decline and structural remodeling in early lung disease. The objective of this application is to use state-of-the-art HP 129Xe and UTE MRI to validate proteomic markers in early CF. This will be accomplished using blood serum and clinically obtained bronchoalveolar lavage (BAL) fluid from CF patients with known lung pathology. Our central hypothesis is that image-guided proteomics can forecast pathophysiology before spirometric changes are observed. Our rationale is that, while 129Xe and UTE MRI are currently limited to specialized centers, MS proteomics can be performed on readily obtained clinical specimens, and translated with FD analysis into an easily disseminated tool to predict impending lung disease progression, and thus enable interventions before permanent lung damage occurs. Guided by combined MRI and proteomic data and the utility of FD analysis to predict lung function decline, our central hypothesis will be tested by completing the following Specific Aims: 1) Validate our predictive biomarkers in CF patients with normal spirometry but abnormal ventilation; 2) determine the sensitivity and specificity of systemic biomarkers in pre- dicting early structural re-modeling in CF lung disease; and 3) perform clinical bronchoscopy to identify molecular signatures of irreversible lung remodeling. We have developed the MRI sequences and reconstruction pipeline needed to complete the work. For Aims 1 & 2, we have used MRI and MS proteomics to identify key biomarkers to predict structural and functional abnormalities in CF. For Aim 3, we have used BAL proteomics to identify molecular changes at the pathway level in CF patients. The proposed research is innovative, because it will use cutting-edge imaging to validate molecular tools to assess early lung disease. These results will be significant, because they will produce an easily disseminated tool to predict permanent structural remodelling and irreversi- ble functional losses. This work will have an immediate positive impact by developing and translating non-inva- sive tests to identify CF patients at high risk of lung damage and intervene before irreversible changes occur. It will also provide a unique platform to assess pathological progression in a wide range of lung diseases.

囊性纤维化 (CF) 是美国最常见的致命遗传性疾病之一，涉及进行性肺部疾病功能丧失和结构重塑，导致肺移植或死亡。尽管 CF 患者的预期寿命尽管由于治疗方法的改进而有所增加，但病理变化仍会在出生后的第一年内发生。它一直很难检测到这些早期变化，因为肺功能的常规测量如肺活量测定（例如， 1 秒用力呼气量 (FEV1) 是滞后指标，对早期疾病不敏感。相比之下，超短回波时间 (UTE) 和超极化 (HP) 129Xe MRI 可以在 FEV1 之前数年检测到病理。阿迪- 理论上，来自高精度质谱（MS）的蛋白质组生物标志物，与基于模型的模型相结合功能数据（FD）分析，准确预测 CF 肺部疾病进展。然而，这些生物标志物仅在已确诊疾病的患者中得到验证。这项研究的长期目标是验证检测和预测早期肺部疾病中肺功能下降和结构重塑的蛋白质组标记物。此应用的目的是使用最先进的 HP 129Xe 和 UTE MRI 来验证蛋白质组标记在早期的CF中。这将使用血清和临床获得的支气管肺泡灌洗液 (BAL) 来完成来自患有已知肺部病理的 CF 患者的液体。我们的中心假设是图像引导的蛋白质组学可以在观察肺活量变化之前预测病理生理学。我们的理由是，虽然 129Xe 和 UTE MRI 目前仅限于专业中心，MS 蛋白质组学可以在容易获得的临床上进行样本，并通过 FD 分析转化为一种易于传播的工具，以预测即将发生的肺部疾病进展，从而能够在发生永久性肺损伤之前进行干预。联合 MRI 引导和蛋白质组数据以及 FD 分析预测肺功能下降的效用，我们的中心假设是通过完成以下具体目标进行测试：1) 在患有正常的 CF 患者中验证我们的预测生物标志物肺活量测定但通气异常； 2) 确定预检测中全身生物标志物的敏感性和特异性决定 CF 肺病的早期结构重塑； 3) 进行临床支气管镜检查以识别分子不可逆肺重塑的特征。我们开发了 MRI 序列和重建流程完成工作所需的。对于目标 1 和 2，我们使用 MRI 和 MS 蛋白质组学来识别关键生物标志物预测 CF 的结构和功能异常。对于目标 3，我们使用 BAL 蛋白质组学来识别 CF 患者通路水平的分子变化。拟议的研究具有创新性，因为它将使用尖端成像来验证评估早期肺部疾病的分子工具。这些成果将具有重大意义，因为它们将产生一种易于传播的工具来预测永久性结构重塑和不可逆转 ble 功能损失。这项工作将通过开发和转化非侵入性技术产生直接的积极影响。进行大量测试以识别肺损伤高风险的 CF 患者，并在发生不可逆转的变化之前进行干预。它还将提供一个独特的平台来评估各种肺部疾病的病理进展。