Untangling Infection from Inflammation: Pneumonia

解开炎症引起的感染：肺炎

• 批准号: 7140301
• 负责人: J PERREN COBB
• 金额: $ 18.6万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-30 至 2009-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7140301
• 关键词: RNA; biomarker; blood proteins; clinical research; communicable disease diagnosis; diagnosis design /evaluation; gene expression; gene expression profiling; gram negative bacteria; human subject; immunogenetics; inflammation; leukocytes; medical complication; nosocomial infections; nucleic acid quantitation /detection; opportunistic infections; pathologic process; patient oriented research; pneumonia; protein quantitation /detection; proteomics; respirators; respiratory infections; septicemia

DESCRIPTION (provided by applicant): A recent consensus conference concluded that there are no diagnostic criteria specific for differentiating between systemic inflammation and sepsis, and that a lack of sepsis molecular markers underscores the challenge still present in diagnosing sepsis. In preliminary studies, we systematically tested the hypothesis that circulating leukocyte gene expression profiles and plasma proteomic profiles can be used to diagnose sepsis and model the response to systemic inflammation. Having proved our hypothesis in preclinical models, we are now ready to move to the bedside. One of the very few data-rich environments where infection can be predicted on a population basis is the intensive care unit (ICU), typically manifested as ventilator-associated pneumonia (VAP). We hypothesize that circulating leukocyte RNA and plasma protein profiles over time in patients can be used to model the host response to sepsis secondary to VAP, and that the application of this model to clinical decision making will significantly improve our diagnostic and prognostic capabilities. To test this hypothesis, we established the University-wide infrastructure necessary, involving faculty from the departments of Surgery, Anesthesiology, Medicine, Pediatrics, Genetics, Pathology and Immunology, Radiation Oncology, Biostatistics, Systems Engineering, Computer Science, and Mathematics. In Aim 1, we measure changes over time in the circulating leukocyte transcriptome and plasma proteome of patients at risk for VAP. In Aim 2, we model the host response to VAP using generic and organism-specific markers that differentiate between patients who respond or do not respond to therapy. The optimized sample collection protocols are in use. Serial blood samples are drawn over 21 days from intubated patients at risk for VAP. Pilot data from the first two patients are presented herein, describing the clinical trajectory of Gram-negative pneumonia. Funds from this award are necessary to generate the preliminary data for a larger study, to untangle the septic response from the systemic inflammatory response.

描述（由申请人提供）： 最近的一次共识会议得出的结论是，没有专门用于区分全身炎症和脓毒症的诊断标准，并且缺乏脓毒症分子标记物强调了诊断脓毒症仍然存在挑战。在初步研究中，我们系统地测试了循环白细胞基因表达谱和血浆蛋白质组谱可用于诊断脓毒症并模拟对全身炎症反应的假设。在临床前模型中证明了我们的假设后，我们现在准备转向临床。重症监护病房 (ICU) 是极少数数据丰富、可根据人群预测感染情况的环境之一，通常表现为呼吸机相关性肺炎 (VAP)。我们假设，随着时间的推移，患者的循环白细胞 RNA 和血浆蛋白谱可用于模拟宿主对 VAP 继发脓毒症的反应，并且将该模型应用于临床决策将显着提高我们的诊断和预后能力。为了检验这一假设，我们建立了全校范围内必要的基础设施，包括来自外科、麻醉学、医学、儿科、遗传学、病理学和免疫学、放射肿瘤学、生物统计学、系统工程、计算机科学和数学系的教员。在目标 1 中，我们测量了有 VAP 风险的患者循环白细胞转录组和血浆蛋白质组随时间的变化。在目标 2 中，我们使用通用标记和生物体特异性标记来模拟宿主对 VAP 的反应，这些标记区分对治疗有反应或没有反应的患者。优化的样品采集方案正在使用中。在 21 天内从有 VAP 风险的插管患者中抽取连续血样。本文介绍了前两名患者的试验数据，描述了革兰氏阴性肺炎的临床轨迹。该奖项的资金对于为更大规模的研究生成初步数据是必要的，以理清脓毒症反应与全身炎症反应的关系。

项目成果

Plasticity of the systemic inflammatory response to acute infection during critical illness: development of the riboleukogram.

危重疾病期间对急性感染的全身炎症反应的可塑性：核白细胞图的发展。

• 发表时间: 2008
• 影响因子: 3.7
• 作者: McDunn, Jonathan E;Husain, Kareem D;Polpitiya, Ashoka D;Burykin, Anton;Ruan, Jianhua;Li, Qing;Schierding, William;Lin, Nan;Dixon, David;Zhang, Weixiong;Coopersmith, Craig M;Dunne, W Michael;Colonna, Marco;Ghosh, Bijoy K;Cobb, J Perren
• 通讯作者: Cobb, J Perren