Metabolomic Prediction of Pneumonia Severity

肺炎严重程度的代谢组学预测

• 批准号: 10396094
• 负责人: Lilliam Ambroggio
• 金额: $ 19.44万
• 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 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10396094
• 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; pediatric sepsis; 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.

项目摘要 社区获得性肺炎（CAP）是世界上最流行的感染之一， 每年有180万名儿童接受医疗服务。经验证的工具可预测严重 目前尚不存在CAP患儿的临床结局。将生物标志物添加到临床 预测规则可以改善严重性预测，然而常规生物标志物（例如， 降钙素原）预测儿童严重程度的能力有限。我们建议鉴别新的 使用代谢组学的儿科CAP的生物标志物，小分子的研究。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（如感染）和环境之间复杂的生理相互作用。 单个样本中的宿主。核磁共振法测定尿样的初步数据 共振（NMR）光谱法，代谢组学的一个更具体的分析平台，表明 氨基酸、肉毒碱和胆汁酸分子是CAP严重程度的重要预测因子。作为 我们将进一步研究这些类别的代谢物和特定的 使用液相色谱质谱法测定血液样品中的脂质分子（即氧脂） （LC-MS），更灵敏的分析平台。尿液和血液样本的信息将 生成一套全面的预后代谢组学生物标志物，作为两者的优势 正在为这项提议利用分析平台。我们提出的目标方法， 除了使用两个单独的儿科CAP队列外， 代谢组学生物标志物预测规则，以预测儿童的严重程度， 急诊室与CAP