色氨酸代谢产物作为预测急性缺血性中风患者严重程度和预后的生物标志物。

Tryptophan metabolites as biomarkers to predict the severity and prognosis of acute ischemic stroke patients.

作者信息

Pan Chuzheng, Chen Feng, Yan Yan, Li Haiwen, Qiu Chengfeng

机构信息

Department of Neurology, The Hunan University of Medicine General Hospital, 144 Jinxi Road, Huaihua 418000, PR China.

Department of Clinical Pharmacy, The Hunan University of Medicine General Hospital, 144 Jinxi Road, Huaihua 418000, PR China.

出版信息

J Stroke Cerebrovasc Dis. 2025 Aug;34(8):108382. doi: 10.1016/j.jstrokecerebrovasdis.2025.108382. Epub 2025 Jun 17.

DOI:10.1016/j.jstrokecerebrovasdis.2025.108382

PMID:40553901

Abstract

OBJECTIVE

Ischemic stroke is among the leading causes of mortality and long-term disability worldwide. A growing body of evidence indicates alterations in metabolite levels and enzyme activities associated with the conversion of tryptophan (TRP) throughout the course of cerebral ischemia. In this study we aim to explore the potential relationship between TRP metabolism and clinical prognosis in acute ischemic stroke (AIS) patients of mainland China.

MATERIALS AND METHODS

Blood samples were obtained from a cohort of 304 patients diagnosed with AIS. The concentrations of ten TRP metabolites were quantified utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS). Stroke severity was evaluated upon admission using the National Institutes of Health Stroke Scale (NIHSS). A poor functional outcome was defined as a modified Rankin scale (mRS) > 3, whereas a good functional outcome was defined by mRS ≤ 3 at 3 months post-stroke. LASSO regression and random forest algorithms were then employed to identify key TRP metabolism parameters associated with prognosis.

RESULTS

Following the optimization of variable selection through Lasso regression, a prognostic risk model with 7-factors related to AIS was constructed, yielding an AUC of 0.917. Subsequently, a random forest analysis was conducted to establish an 11-factor prognostic risk model, which demonstrated an enhanced AUC of 1.000. Ultimately, three robust parameters related to TRP metabolism were identified. Multivariable logistic regression analysis, adjusted for covariates, revealed that TRP (odds ratio .[OR] = 0.46, 95 % confidence interval .[CI]: 0.26 - 0.76, p = 0.004), the kynurenine (KYN)/TRP ratio (OR = 2.06, 95 % CI: 1.23 - 3.60, p = 0.008), and the kynurenic acid (KYNA)/TRP ratio (OR = 2.15, 95 % CI: 1.23 - 4.12, p = 0.014) were independently associated with poor functional prognosis.

CONCLUSIONS

The results of this study indicate that TRP metabolism is associated with the severity and prognosis of AIS. The TRP, KYN/TRP ratio and KYNA/TRP ratio may serve as potential biomarkers for 3-month prognostic evaluation.

摘要

目的

缺血性中风是全球范围内导致死亡和长期残疾的主要原因之一。越来越多的证据表明，在脑缺血过程中，色氨酸（TRP）转化过程中代谢物水平和酶活性发生了改变。在本研究中，我们旨在探讨中国大陆急性缺血性中风（AIS）患者中TRP代谢与临床预后之间的潜在关系。

材料与方法

从304例诊断为AIS的患者队列中采集血样。使用液相色谱-串联质谱法（LC-MS/MS）对十种TRP代谢物的浓度进行定量。入院时使用美国国立卫生研究院卒中量表（NIHSS）评估中风严重程度。功能预后不良定义为改良Rankin量表（mRS）>3，而功能预后良好定义为中风后3个月时mRS≤3。然后采用LASSO回归和随机森林算法来识别与预后相关的关键TRP代谢参数。

结果

通过Lasso回归优化变量选择后，构建了一个与AIS相关的7因素预后风险模型，曲线下面积（AUC）为0.917。随后，进行随机森林分析以建立一个11因素预后风险模型，并显示AUC提高到1.000。最终，确定了三个与TRP代谢相关的可靠参数。经协变量调整的多变量逻辑回归分析显示，TRP（比值比[OR]=0.46，95%置信区间[CI]：0.26-0.76，p=0.004）、犬尿氨酸（KYN）/TRP比值（OR=2.06，95%CI：1.23-3.60，p=0.008）和犬尿酸（KYNA）/TRP比值（OR=2.15，95%CI：1.23-4.12，p=0.014）与功能预后不良独立相关。