要点风险分层通常无法预测肺栓塞(PE)的临床恶化。首次对风险分层的PE患者进行高通量代谢组学分析。循环代谢物的变化反映了PE中能量代谢受损。代谢物在PE的病理生理学和危险分层中起关键作用。
背景急性肺栓塞(PE)患者在临床表现和结果方面表现出广泛的差异。我们对区分低风险和高风险PE的病理生理机制的理解是有限的。因此,目前的风险分层工作往往无法预测临床恶化,也不足以指导治疗.目的提高我们对区分低风险PE和高风险PE的生理学认识。我们进行了首次高通量代谢组学分析(843种代谢物命名),在巢式病例对照研究中比较了不同风险层的PE患者.患者/方法我们招募了92例诊断为急性PE的患者,并在PE诊断24小时内收集血浆。我们使用线性回归和途径分析来确定与PE风险层相关的代谢物和途径。结果当我们比较46个低风险与46个中/高风险PE时,50种代谢物经多次测试校正后差异显著。这些代谢物富含以下途径:三羧酸(TCA)循环,脂肪酸代谢(酰基肉碱)和嘌呤代谢,含(次)黄嘌呤/肌苷。此外,能源,中/高危PE患者的核苷酸和氨基酸通路下调.当我们比较28个中危和18个高危PE患者时,41种代谢物在标称P值水平上有所不同。这些代谢物富含脂肪酸代谢(酰基胆碱),血红蛋白和卟啉代谢。结论我们的结果表明,高通量代谢组学可以提供对PE病理生理学的了解。具体来说,循环代谢物的变化反映了中/高危PE患者的能量代谢受损。这些发现证明了代谢物在PE病理生理学中的重要作用,并强调了代谢组学作为PE风险分层的潜在工具。
Essentials Risk-stratification often fails to predict clinical deterioration in pulmonary embolism (PE). First-ever high-throughput metabolomics analysis of risk-stratified PE patients. Changes in circulating metabolites reflect a compromised energy metabolism in PE. Metabolites play a key role in the pathophysiology and risk stratification of PE.
Background Patients with acute pulmonary embolism (PE) exhibit wide variation in clinical presentation and outcomes. Our understanding of the pathophysiologic mechanisms differentiating low-risk and high-risk PE is limited, so current risk-stratification efforts often fail to predict clinical deterioration and are insufficient to guide management. Objectives To improve our understanding of the physiology differentiating low-risk from high-risk PE, we conducted the first-ever high-throughput metabolomics analysis (843 named metabolites) comparing PE patients across risk strata within a nested
case-control study. Patients/methods We enrolled 92 patients diagnosed with acute PE and collected plasma within 24 h of PE diagnosis. We used linear regression and pathway analysis to identify metabolites and pathways associated with PE risk-strata. Results When we compared 46 low-risk with 46 intermediate/high-risk PEs, 50 metabolites were significantly different after multiple testing correction. These metabolites were enriched in the following pathways: tricarboxylic acid (TCA) cycle, fatty acid metabolism (acyl carnitine) and purine metabolism, (hypo)xanthine/
inosine containing. Additionally, energy, nucleotide and amino acid pathways were downregulated in intermediate/high-risk PE patients. When we compared 28 intermediate-risk with 18 high-risk PE patients, 41 metabolites differed at a nominal P-value level. These metabolites were enriched in fatty acid metabolism (acyl cholines), and hemoglobin and porphyrin metabolism. Conclusion Our results suggest that high-throughput metabolomics can provide insight into the pathophysiology of PE. Specifically, changes in circulating metabolites reflect compromised energy metabolism in intermediate/high-risk PE patients. These findings demonstrate the important role metabolites play in the pathophysiology of PE and highlight metabolomics as a potential tool for risk stratification of PE.