Systemic Metabolic Changes of Traumatic Critically III Patients Revealed by an NMR-Based Metabonomic Approach
Systemic Metabolic Changes of Traumatic Critically III Patients Revealed by an NMR-Based Metabonomic Approach
复制标题
基于核磁共振的代谢组学方法揭示了创伤性危重患者的全身代谢变化。
DOI：
10.1021/pr900576y
复制
发表时间：
2009-12-01
影响因子：
4.4
通讯作者：
Lin, Donghai
中科院分区：
文献类型：
--
作者：
Mao, Hailei;Wang, Huimin;Lin, Donghai
重症患者从全身炎症反应综合征（SIRS）进展为多器官功能障碍综合征（MODS）占成人外科重症监护室死亡人数的75%以上。目前，没有实用的临床技术来预测SIRS或MODS的进展。在这份报告中，我们描述了一种基于NMR的代谢组学方法，以帮助检测这些条件的基础上异常代谢签名。我们应用模式识别方法分析SIRS和MODS患者血清的一维（1）H NMR谱。采用主成分分析（PCA）和偏最小二乘判别分析（PLS-DA）对52例危重患者和26例健康对照者进行了鉴别。在通过正交信号校正（OSC）进行降噪后，PLS-DA也能够清楚地区分SIRS和MODS患者。相应的系数表明，负责区分的光谱位于SIRS的δ 3.06 -3.86 NMR积分区域，主要由糖、氨基酸和谷氨酰胺信号组成，以及MODS血清样品的δ 1.18 -1.3和δ 4.02 -4.1积分区域，主要由脂肪酰基链和脂质甘油主链的各种质子信号组成，沿着肌酸酐和乳酸。我们的结果与临床观察一致，即糖和氨基酸水平的变化在危重病的早期过程（SIRS阶段）和脂肪代谢的显着紊乱和器官异常的发展成为特征的晚期阶段（MODS）。这些数据表明，可以开发基于核磁共振的代谢组学方法来诊断重症患者的疾病进展。
Progression of critically ill patients from Systemic Inflammatory Response Syndrome (SIRS) to Multiple Organ Dysfunction Syndrome (MODS) accounts for more than 75% of deaths in adult surgical intensive care units. Currently, there is no practical clinical technique to predict the progression of SIRS or MODS. In this report, we describe an NMR-based metabonomic method to aid detection of these conditions based on abnormal metabolic signatures. We applied pattern recognition methods to analyze one-dimensional (1)H NMR spectra of SIRS and MODS patient sera. By using Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA), we could distinguish critically ill patients (n = 52) from healthy controls (n = 26). After noise reduction by Orthogonal Signal Correction (OSC), PLS-DA was also able to clearly discriminate SIRS and MODS patients. The corresponding coefficients indicated that spectra responsible for the discrimination were located in delta3.06-3.86 NMR integral regions from SIRS, mainly composed of sugars, amino acids and glutamine signals, and delta1.18-1.3 and delta4.02-4.1 integral regions of MODS serum samples, principally consisted of various proton signals of fatty acyl chains and glycerol backbone of lipids, along with creatinine and lactate. Our results are consistent with the clinical observations that carbohydrate and amino acid levels changes in the early course of critical illness (SIRS stage) and significant disturbances in fat metabolism and development of organ abnormalities become the characteristics in the late stage (MODS). These data suggest that NMR-based metabonomic approach can be developed to diagnose the disease progress of critically ill patients.