Ye Yonglong, Chen Yunxian, Wan Zhidong, Pan Huiying, Hou Zhijun, Liu Jun
Department of Laboratory Medicine, Dongguan Hospital of Guangzhou University of Chinese Medicine, Dongguan 523005, China.
Department of Cardiology, Yue Bei People's Hospital, Shantou University Medical College, Shaoguan 512000, China.
Clin Chim Acta. 2025 Sep 1;577:120434. doi: 10.1016/j.cca.2025.120434. Epub 2025 Jun 16.
Coronary Slow Flow (CSF) is a significant cardiovascular disorder characterized by high incidence rates and frequently associated with adverse clinical outcomes. Early diagnosis and effective monitoring are essential for enhancing patient prognosis. Consequently, this study seeks to explore the metabolic distinctions among patients with CSF, individuals with coronary artery disease (CAD), and those with normal coronary arteries (NCA) through metabolomic analysis, with the aim of identifying potential biomarkers that could offer novel insights into the early diagnosis and treatment of CSF. This study utilized ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) to analyze 1,430 lipid metabolites. Comparative metabolomic profiling among the CSF, NCA, and CAD groups revealed significant metabolic disparities, with 66 differentially expressed metabolites identified in CSF patients. Enrichment analysis indicated that these metabolites were predominantly involved in critical metabolic pathways, including thermogenesis, glycerophospholipid metabolism, glycerolipid metabolism, and fat digestion and absorption. Subsequent analyses employing least absolute shrinkage and selection operator (LASSO) regression and random forest algorithms identified four critical biomarkers: DG(O-19:0_16:0), MG(16:0), DG(16:0_18:0), and Carnitine C6-2OH. These biomarkers demonstrated robust efficacy in differentiating between patients with CSF and those with CAD, with area under the curve values of 0.809, 0.924, 0.859, and 0.929, respectively. Furthermore, patients with CSF undergoing enhanced external counterpulsation exhibited significant symptomatic improvement, which was accompanied by a marked reduction in the expression levels of these metabolites. In conclusion, this metabolomic investigation elucidates the metabolic profile of CSF and identifies four pivotal metabolic biomarkers with potential diagnostic and prognostic utility. These results not only introduce novel biomarkers for the early detection of CSF but also provide new insights for personalized treatment strategies and therapeutic monitoring.
冠状动脉慢血流（CSF）是一种重要的心血管疾病，其发病率高，且常与不良临床结局相关。早期诊断和有效监测对于改善患者预后至关重要。因此，本研究旨在通过代谢组学分析探索CSF患者、冠状动脉疾病（CAD）患者和冠状动脉正常（NCA）者之间的代谢差异，以识别可能为CSF的早期诊断和治疗提供新见解的潜在生物标志物。本研究利用超高效液相色谱-串联质谱（UPLC-MS/MS）分析了1430种脂质代谢物。CSF、NCA和CAD组之间的比较代谢组学分析揭示了显著的代谢差异，在CSF患者中鉴定出66种差异表达的代谢物。富集分析表明，这些代谢物主要参与关键代谢途径，包括产热、甘油磷脂代谢、甘油酯代谢以及脂肪消化和吸收。随后采用最小绝对收缩和选择算子（LASSO）回归和随机森林算法的分析确定了四种关键生物标志物：DG（O-19:0_16:0）、MG（16:0）、DG（16:0_18:0）和肉碱C6-2OH。这些生物标志物在区分CSF患者和CAD患者方面表现出强大的效能，曲线下面积值分别为0.809、0.924、0.859和0.929。此外，接受增强型体外反搏治疗的CSF患者症状明显改善，同时这些代谢物的表达水平显著降低。总之，这项代谢组学研究阐明了CSF的代谢特征，并鉴定出四种具有潜在诊断和预后价值的关键代谢生物标志物。这些结果不仅为CSF的早期检测引入了新的生物标志物，还为个性化治疗策略和治疗监测提供了新的见解。
