Department of Neurology, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea.
Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea.
Transl Stroke Res. 2024 Apr;15(2):422-432. doi: 10.1007/s12975-023-01137-5. Epub 2023 Feb 11.
Ischemic stroke is a heterogeneous disease with various etiologies. The current subtyping process is complicated, time-consuming, and costly. Metabolite-based biomarkers have the potential to improve classification and deliver optimal treatments. We here aimed to identify novel, targeted metabolomics-based biomarkers to discriminate between large-artery atherosclerosis (LAA) and cardioembolic (CE) stroke.
We acquired serum samples and clinical data from a hospital-based acute stroke registry (ischemic stroke within 3 days from symptom onset). We included 346 participants (169 LAA, 147 CE, and 30 healthy older adults) and divided them into training and test sets. Targeted metabolomic analysis was performed using quantitative and quality-controlled liquid chromatography with tandem mass spectrometry. A multivariate regression model using metabolomic signatures was created that could independently distinguish between LAA and CE strokes.
The training set (n = 193) identified metabolomic signatures that were different in patients with LAA and CE strokes. Six metabolomic biomarkers, i.e., lysine, serine, threonine, kynurenine, putrescine, and lysophosphatidylcholine acyl C16:0, could discriminate between LAA and CE stroke after adjusting for sex, age, body mass index, stroke severity, and comorbidities. The enhanced diagnostic power of key metabolite combinations for discriminating between LAA and CE stroke was validated using the test set (n = 123).
We observed significant differences in metabolite profiles in LAA and CE strokes. Targeted metabolomics may provide enhanced diagnostic yield for stroke subtypes. The pathophysiological pathways of the identified metabolites should be explored in future studies.
缺血性脑卒中是一种病因多样的异质性疾病。目前的亚型分类过程复杂、耗时且昂贵。基于代谢物的生物标志物有可能改善分类并提供最佳治疗方法。我们旨在确定新的、基于靶向代谢组学的生物标志物,以区分大动脉粥样硬化(LAA)和心源性栓塞(CE)卒中。
我们从医院急性脑卒中登记处(症状发作后 3 天内的缺血性脑卒中)获得血清样本和临床数据。我们纳入了 346 名参与者(169 名 LAA,147 名 CE 和 30 名健康老年人),并将其分为训练集和测试集。使用定量和质量控制的液相色谱-串联质谱进行靶向代谢组学分析。使用代谢组学特征创建了一个多元回归模型,可以独立区分 LAA 和 CE 脑卒中。
训练集(n = 193)确定了 LAA 和 CE 脑卒中患者之间存在差异的代谢组学特征。在调整性别、年龄、体重指数、卒中严重程度和合并症后,6 种代谢生物标志物,即赖氨酸、丝氨酸、苏氨酸、犬尿氨酸、腐胺和溶血磷脂酰胆碱酰基 C16:0,可以区分 LAA 和 CE 卒中。使用测试集(n = 123)验证了关键代谢物组合区分 LAA 和 CE 卒中的增强诊断能力。
我们观察到 LAA 和 CE 卒中之间代谢谱存在显著差异。靶向代谢组学可能为脑卒中亚型提供增强的诊断效果。应在未来研究中探讨所鉴定代谢物的病理生理途径。