缺血性卒中的代谢组学应用研究及展望Application Research and Prospect of Metabolomics in Ischemic Stroke

代谢组学在缺血性卒中研究中具有重要应用价值，本文综述了代谢组学方法在揭示缺血性卒中的发病机制、预测发病风险、辅助临床诊断、优化治疗策略及评估预后等方面的应用进展。研究表明：代谢组学能够揭示缺血性卒中发生发展中的多种代谢异常，为发掘病理机制提供线索；通过识别代谢生物标志物，能有效预测发病风险并为早期诊断提供支持；结合人工智能方法可构建早期诊断模型，有助于区分卒中亚型，明确不同类型卒中的代谢差异，提高诊断准确性；通过监测卒中后治疗与功能恢复过程中的代谢物变化，可揭示新的潜在治疗靶点。展望未来，代谢组学有望为缺血性卒中的个性化干预和精准医疗提供科学依据。 Abstract: Metabolomics has important application value in the study of ischemic stroke. This article reviews the progress of metabolomics methods in revealing the pathogenesis of ischemic stroke, predicting disease risk, assisting clinical diagnosis, optimizing treatment strategies, and evaluating prognosis. Studies have shown that metabolomics can reveal various metabolic abnormalities in the occurrence and development of ischemic stroke, providing clues for exploring pathological mechanisms. Through identifying metabolic biomarkers, it can effectively predict disease risk and help with early diagnosis. When combined with artificial intelligence to build early diagnosis models, it helps to distinguish stroke subtypes, clarify metabolic differences between different types of stroke, and improve diagnostic accuracy. By monitoring changes in metabolites during post-stroke treatment and functional recovery, it reveals new potential therapeutic targets. In the future, metabolomics is anticipated to serve as a scientific basis for personalized intervention and precision medicine in ischemic stroke.