Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No. 2 Hospital, Ningbo 315000, China; Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo 315000, China.
Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo 315000, China.
Neuroscience. 2023 Nov 21;533:22-35. doi: 10.1016/j.neuroscience.2023.09.017. Epub 2023 Oct 6.
Hypertensive individuals are at a high risk of stroke, and thus, prevention of stroke in hypertensive patients is essential. Metabolomics and lipidomics can be used to identify diagnostic biomarkers and conduct early assessments of stroke risk in hypertensive populations. In this study, serum samples were collected from 30 hypertensive ischemic stroke (IS), 30 matched hypertensive and 30 matched healthy participants. Metabolomics and lipidomics analyses were conducted via liquid chromatography-tandem mass spectrometry, and the data were analyzed using multivariate and univariate statistical methods. A random forest algorithm and binary logistic regression were used to screen the biomarkers and establish diagnostic model. We detected 21 differential metabolites and 38 differential lipids between the hypertensive IS and healthy group. Moreover, we found 18 differential metabolites and 31 differential lipids between the hypertensive IS and hypertension group. In particular, the following seven metabolites or lipids distinguished the hypertensive IS from the healthy group: 4-hydroxyphenylpyruvic acid, cafestol, phosphatidylethanolamine (PE) (18:0p/18:2), PE (16:0e/20:4), (O-acyI)-1-hydroxy fatty acid (36:3), PE (16:0p/20:3) and PE (18:1p/18:2) (rep). The following seven biomarkers distinguished the hypertensive IS from the hypertension group: diglyceride (DG) (20:1/18:2), PE (18:0p/18:2), PE (16:0e/22:5), phosphatidylcholine (40:7), dimethylphosphatidylethanolamine (50:3), DG (18:1/18:2), and 4-hydroxyphenylpyruvic acid. The aforementioned panels had good diagnostic and predictive ability for hypertensive IS. Our study determines the metabolomic and lipidomic profiles of hypertensive IS patients and thereby identifies potential biomarkers of the presence of IS in hypertensive populations.
高血压个体中风风险较高，因此，预防高血压患者中风至关重要。代谢组学和脂质组学可用于识别诊断生物标志物，并对高血压人群的中风风险进行早期评估。在这项研究中，收集了 30 例高血压缺血性中风（IS）、30 例匹配的高血压和 30 例匹配的健康参与者的血清样本。通过液相色谱-串联质谱进行代谢组学和脂质组学分析，使用多变量和单变量统计方法对数据进行分析。使用随机森林算法和二项逻辑回归筛选生物标志物并建立诊断模型。我们在高血压 IS 与健康组之间检测到 21 个差异代谢物和 38 个差异脂质。此外，我们还在高血压 IS 与高血压组之间发现了 18 个差异代谢物和 31 个差异脂质。特别是，以下七种代谢物或脂质将高血压 IS 与健康组区分开来：4-羟基苯丙酮酸、咖啡醇、磷脂酰乙醇胺（PE）（18:0p/18:2）、PE（16:0e/20:4）、（O-酰基）-1-羟基脂肪酸（36:3）、PE（16:0p/20:3）和 PE（18:1p/18:2）（rep）。以下七种生物标志物将高血压 IS 与高血压组区分开来：二酰基甘油（DG）（20:1/18:2）、PE（18:0p/18:2）、PE（16:0e/22:5）、磷脂酰胆碱（40:7）、二甲基磷脂酰乙醇胺（50:3）、DG（18:1/18:2）和 4-羟基苯丙酮酸。上述面板对高血压 IS 具有良好的诊断和预测能力。我们的研究确定了高血压 IS 患者的代谢组学和脂质组学特征，并由此确定了高血压人群中 IS 存在的潜在生物标志物。
