Hepatology Institute, Peking University People's Hospital, No. 11 Xizhimen South Street, Beijing 100044, PR China.
BMC Gastroenterol. 2009 Dec 30;9:99. doi: 10.1186/1471-230X-9-99.
It is frequently important to identify the prognosis of fulminant hepatic failure (FHF) patients as this will influence patient management and candidacy for liver transplantation. Therefore, a novel scoring system based on metabonomics combining with multivariate logistic regression was developed to predict the prognosis of FHF mouse model.
BALB/c mice were used to construct FHF model. Parts of plasma were collected at 4, 5, and 6-h time points after treatment, respectively, and detected using gas chromatography/time-of-flight mass spectrometry (GC/TOFMS). The acquired data were processed using partial least square discriminant analysis (PLS-DA). The metabolic markers identified were used to construct a scoring system by multivariate regression analysis.
28 mice of survival group and 28 of dead group were randomly selected and analyzed. PLS regression analysis showed that both the PLS models of 5 h and 6 h after d-galactosamine/lipopolysaccharide treatment demonstrated good performances. Loadings plot suggested that phosphate, beta-hydroxybutyrate (HB), urea, glucose and lactate concentrations in plasma had the highest weightings on the clustering differences at the three time points. By the multivariate logistic regression analysis, the death/survival index (DSI) was constructed based on relative concentrations of HB, urea and phosphate. It provided general accurate rate of prediction of 93.3% in the independent samples.
The novel scoring system based on metabonomics combining with multivariate logistic regression is accurate in predicting the prognosis of FHF mouse model and may be referred in clinical practice as a more useful prognostic tool with other available information.
识别暴发性肝衰竭（FHF）患者的预后非常重要，因为这将影响患者的管理和肝移植的资格。因此，开发了一种基于代谢组学结合多元逻辑回归的新型评分系统，以预测 FHF 小鼠模型的预后。
使用 BALB/c 小鼠构建 FHF 模型。分别在治疗后 4、5 和 6 小时采集部分血浆，并使用气相色谱/飞行时间质谱（GC/TOFMS）进行检测。使用偏最小二乘判别分析（PLS-DA）处理获得的数据。使用多元回归分析构建了一个评分系统，其中包括鉴定的代谢标志物。
随机选择并分析了 28 只存活组和 28 只死亡组的小鼠。PLS 回归分析表明，半乳糖胺/脂多糖处理后 5 小时和 6 小时的 PLS 模型均表现出良好的性能。载荷图表明，血浆中磷酸盐、β-羟丁酸（HB）、尿素、葡萄糖和乳酸浓度在三个时间点的聚类差异上具有最高的权重。通过多元逻辑回归分析，基于 HB、尿素和磷酸盐的相对浓度构建了死亡/存活指数（DSI）。它在独立样本中提供了 93.3%的总体准确预测率。
基于代谢组学结合多元逻辑回归的新型评分系统可准确预测 FHF 小鼠模型的预后，并且可能在临床实践中作为更有用的预后工具与其他可用信息一起使用。
