Metabolomic Prediction of Pneumonia Severity

肺炎严重程度的代谢组学预测

• 批准号: 10216792
• 负责人: Lilliam Ambroggio
• 金额: $ 23.33万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-21 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10216792
• 关键词: Accident and Emergency department; Admission activity; Amino Acids; Bile Acids; Biological Assay; Biological Markers; Blood; Blood specimen; C-reactive protein; Caring; Carnitine; Cessation of life; Chest; Child; Childhood; Clinical; Clinical Data; Cohort Studies; Complex; Data; Development; Diagnosis; Diagnostic tests; Disease; Drainage procedure; Empyema; Environment; Etiology; Financial Hardship; Functional disorder; Guidelines; Health Care Visit; Heterogeneity; Histidine; Hospitalization; Hospitals; Immune response; Infection; Inflammation; Intervention; Lipids; Measures; Metabolic; Mitochondria; Modeling; Nuclear Magnetic Resonance; Ohio; Organ; Outcome; Pediatric Hospitals; Pediatric Intensive Care Units; Pediatric cohort; Performance; Physiological; Pneumonia; Prospective cohort study; Provider; Regulation; Research; Research Personnel; Sampling; Sepsis; Severities; Severity of illness; Specificity; Specimen; Spectrometry; Time; Urine; base; clinically relevant; cohort; community acquired pneumonia; cost; data repository; improved; indexing; liquid chromatography mass spectrometry; metabolomics; novel; novel marker; predictive marker; predictive modeling; predictive test; prevent; procalcitonin; prognostic; prospective; respiratory; risk stratification; small molecule; tool; urinary

PROJECT SUMMARY Community-acquired pneumonia (CAP) is one of the most prevalent infections in children resulting in 1.8 million healthcare visits annually. Validated tools to predict severe clinical outcomes in children with CAP do not exist. The addition of biomarkers to clinical prediction rules may improve severity prediction, however conventional biomarkers (e.g. procalcitonin) have limited ability to predict severity in children. We propose identifying novel biomarkers for pediatric CAP using metabolomics, the study of small molecules. We hypothesize that metabolites may be better predictors of illness severity as they directly represent the complex physiological interaction between the environment (e.g. infection) and the host in a single sample. Preliminary data of urine samples assayed by Nuclear Magnetic Resonance (NMR) spectrometry, a more specific analytical platform for metabolomics, suggests amino acids, carnitine and bile acid molecules are important predictors of CAP severity. As a complimentary approach we will further investigate these classes of metabolites and specific lipid molecules (i.e. oxylipins) in blood samples using liquid chromatography mass spectrometry (LC-MS), a more sensitive analytical platform. Information from urine and blood specimens will generate a comprehensive set of prognostic metabolomic biomarkers as the strengths of both analytical platforms are being leveraged for this proposal. The targeted approach we propose in addition to the use of two separate pediatric CAP cohorts, will result in a clinical and metabolomic biomarker prediction rule to predict severity in children presenting to the emergency department with CAP.

项目总结 社区获得性肺炎(CAP)是中国最常见的传染病之一。 儿童每年的医疗就诊次数达到180万人次。经过验证的预测严重程度的工具 CAP儿童的临床结果并不存在。生物标志物在临床中的应用 预测规则可以改善严重性预测，然而，传统的生物标志物(例如， 降钙素原)对儿童病情的预测能力有限。我们建议辨别小说 利用代谢组学、小分子研究儿科CAP的生物标志物。我们 假设代谢物可能是疾病严重程度的更好预测因子，因为它们直接 代表环境(例如感染)与环境之间复杂的生理作用 寄主在单个样本中。核磁法测定尿样的初步数据 代谢组学的一种更具体的分析平台--核磁共振光谱分析表明 氨基酸、肉碱和胆汁酸分子是预测CAP严重程度的重要指标。作为一名 我们将进一步研究这些类别的代谢物和特定的 液质联用法测定血液样本中的脂类分子(即氧合脂) (LC-MS)，一个更灵敏的分析平台。从尿液和血液样本中获得的信息将 生成一套全面的预后代谢生物标志物，作为两者的优势 分析平台正被用于这项提议。我们在中提出的有针对性的方法 除了使用两个单独的儿科CAP队列外，还将导致临床和 代谢生物标记物预测儿童病情严重程度的预测规则 急诊科有CAP。