Diagnostic and Prognostic Biomarkers in Pneumonia

肺炎的诊断和预后生物标志物

基本信息

  • 批准号:
    7733590
  • 负责人:
  • 金额:
    $ 9.45万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
  • 资助国家:
    美国
  • 起止时间:
  • 项目状态:
    未结题

项目摘要

The objective of this study (04-CC-0119)is to analyze bronchoalveolar lavage and serum from patients with lung infiltrates in order to discover new biomarkers and protein expression patterns that are associated with specific types of pulmonary disease. Bronchoalveolar lavage is a standard method to obtain lower airway samples to evaluate pulmonary infiltrates in order to diagnose infection, malignancy or non-infectious inflammation. After collecting the lavage, the clinical microbiology laboratory concentrates the formed elements (i.e. pathogens and cells) for stains and culture and discards the bronchoalveolar lavage supernatant. The supernatant however is a rich source of proteins and other molecules. We hypothesize that bronchoalveolar lavage will be an important source of biomarkers that reflect host-pathogen interactions. The analysis of protein mass profiles and biomarker identification in bronchoalveolar lavage and serum may help develop new diagnostic methods and extend our understanding of mechanisms of lung inflammation due to infectious causes. The study population will include all patients undergoing bronchoscopy for clinical indications at the Clinical Center and affiliated study hospitals. This will facilitate the acquisition of BAL samples that reflect a spectrum of community-acquired and opportunistic pathogens associated with pulmonary disease. In addition analysis of a range of non-infectious pulmonary processes (e.g. acute lung injury, acute respiratory distress syndrome and engraftment syndrome) is important to develop measures of sensitivity and specificity. We currently use several different platforms for analysis of biologic specimens including BAL fluid or serum/plasma. The Ciphergen Protein Chip Arrays (Ciphergen Biosystems, Inc., Palo Alto, CA, USA) selectively fractionates samples based on binding affinity to specialized surfaced including hydrophobic, cation, anion and immobilized metal affinity capture. This technique of surface chemistry optimization is termed Surface Enhanced Laser Desorption-Ionization (SELDI) and when combined with mass spectrometry, termed SELDI-TOF. We will complement our SELDI protein expression profiles with two-dimensional gel electrophoresis and a higher resolution mass spectrometry system (Bruker Daltonics Ultraflex MS/MS).In addition we are using high intensity antibody based protein arrays to interrogate candidate biomarkers in blood and BAL. By developing a large database of BAL fluid linked to specific microbiologic diagnoses, we plan to define protein expression signature response profiles that distinguish specific etiologies of lung infection and inflammation. These signature profiles will be based on mass spectrometry, two-dimensional gel electrophoresis and suspension array technologies. Because of the variability associated with individual host responses to infection due to differences in host immunity, sampling time effects, and external factors such as antibiotic or anti-inflammatory therapies, a large database will be required. The profiles of culture-negative BAL fluid will be of similar interest to assist in defining non-infectious etiologies of lung inflammation. A secondary objective is to perform proteomic analysis on serum collected from patients at the time of bronchoscopy. The goal is to link serum proteomic profiles to BAL proteomic profiles to determine whether a less invasive technique can predict infiltrate etiology with comparable sensitivity and specificity to BAL profiles. To complement the patient studies we will investigate protein biomarkers in blood and lavage from animal models of pneumonia. We are currently studying a rabbit model of invasive pulmonary aspergillosis and a canine model of staphylococcal pneumonia. Exploring these model systems will facilitate our identification of candidate biomarkers across species. A total of 490 patients have been enrolled in this study to date. Approximately one half of the participants have a specific microbiologic diagnosis as a cause of their pulmonary infiltrates. The bronchoalveolar lavage and blood samples are currently being analyzed.
本研究(04-CC-0119)的目的是分析肺浸润患者的支气管肺泡灌洗液和血清,以发现与特定类型肺部疾病相关的新的生物标志物和蛋白质表达模式。支气管肺泡灌洗是获得下气道样本以评估肺部浸润以诊断感染、恶性或非感染性炎症的标准方法。临床微生物实验室收集灌洗液后,将形成的成分(即病原体和细胞)浓缩染色培养,丢弃支气管肺泡灌洗液上清。然而,上清是蛋白质和其他分子的丰富来源。我们假设支气管肺泡灌洗将是反映宿主-病原体相互作用的生物标志物的重要来源。分析支气管肺泡灌洗液和血清中的蛋白质质量谱和生物标志物鉴定可能有助于开发新的诊断方法,并扩展我们对感染性肺部炎症机制的理解。

项目成果

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ANTHONY F. SUFFREDINI其他文献

ANTHONY F. SUFFREDINI的其他文献

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{{ truncateString('ANTHONY F. SUFFREDINI', 18)}}的其他基金

Inflammatory Responses to Bronchial Endotoxin Instillation in Humans
人类支气管内毒素滴注的炎症反应
  • 批准号:
    6431779
  • 财政年份:
  • 资助金额:
    $ 9.45万
  • 项目类别:
Effects Of Inhaled Nitric Oxide On Pulmonary Inflammator
吸入一氧化氮对肺部炎症的影响
  • 批准号:
    6825004
  • 财政年份:
  • 资助金额:
    $ 9.45万
  • 项目类别:
Effects Of Inhaled Nitric Oxide On Pulmonary Inflammator
吸入一氧化氮对肺部炎症的影响
  • 批准号:
    6683784
  • 财政年份:
  • 资助金额:
    $ 9.45万
  • 项目类别:
Detection of Respiratory Viruses in Upper and Lower Respiratory Tract Specimens
上呼吸道和下呼吸道标本中呼吸道病毒的检测
  • 批准号:
    8565333
  • 财政年份:
  • 资助金额:
    $ 9.45万
  • 项目类别:
Effects of Inhaled Carbon Monoxide on Human Lung Inflammation
吸入一氧化碳对人体肺部炎症的影响
  • 批准号:
    8565323
  • 财政年份:
  • 资助金额:
    $ 9.45万
  • 项目类别:
Diagnostic and Prognostic Biomarkers in Pneumonia
肺炎的诊断和预后生物标志物
  • 批准号:
    7215800
  • 财政年份:
  • 资助金额:
    $ 9.45万
  • 项目类别:
Inflammatory Effects Of High Mobility Group Protein 1
高迁移率族蛋白 1 的炎症作用
  • 批准号:
    7331954
  • 财政年份:
  • 资助金额:
    $ 9.45万
  • 项目类别:
Diagnostic and Prognostic Biomarkers in Pneumonia
肺炎的诊断和预后生物标志物
  • 批准号:
    9154076
  • 财政年份:
  • 资助金额:
    $ 9.45万
  • 项目类别:
Diagnostic and Prognostic Biomarkers in Pneumonia
肺炎的诊断和预后生物标志物
  • 批准号:
    9352009
  • 财政年份:
  • 资助金额:
    $ 9.45万
  • 项目类别:
Effects of Glucocorticoids or Mineralocorticoids on Endothelial Function
糖皮质激素或盐皮质激素对内皮功能的影响
  • 批准号:
    7593150
  • 财政年份:
  • 资助金额:
    $ 9.45万
  • 项目类别:

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