Botello-Marabotto Marina, Plana Emma, Martínez-Bisbal M Carmen, Medina Pilar, Bernardos Andrea, Martínez-Máñez Ramón, Miralles Manuel
Unidad Mixta de Investigación en Nanomedicina y Sensores, Instituto de Investigación Sanitaria La Fe (IISLAFE), Universitat Politècnica de València, Valencia, Spain; Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València - Universitat de València, Valencia, Spain; CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Spain.
Grupo Acreditado de Hemostasia, Trombosis, Arteriosclerosis y Biología Vascular, Instituto de Investigación Sanitaria La Fe (IISLAFE), Valencia, Spain; Servicio de Angiología y Cirugía Vascular, Hospital Universitario y Politécnico La Fe, Valencia, Spain.
Talanta. 2025 Mar 1;284:127211. doi: 10.1016/j.talanta.2024.127211. Epub 2024 Nov 12.
Carotid artery stenosis is mainly produced due to the progressive accumulation of atherosclerotic plaque in the vascular wall. The atherosclerotic plaque is characterized by the accumulation of lipids, low density proteins, expression of chemokines and adhesion molecules, and migration of monocytes and lymphocytes into the plaque. Its rupture can produce stroke, but embolic propensity depends principally on the composition and vulnerability of plaque rather than the severity of stenosis. It is important, then, to ascertain which patients with carotid artery stenosis have a greater risk of developing neurological symptomatology. Here, we present a metabolomic study by using nuclear magnetic resonance (NMR) spectroscopy in atheroma plaque and serum samples from patients with recently symptomatic and asymptomatic carotid stenosis to search for metabolites that could be used as biomarkers associated with plaque vulnerability and subsequent risk of rupture. Thirty-eight atheromatous plaque samples (24 asymptomatic patients and 14 symptomatic) and 70 serum samples (43 asymptomatic and 27 symptomatic) were studied by NMR spectroscopy. The data were analysed using multivariate statistics (PLS-DA) to determine a model to discriminate between symptomatic and asymptomatic samples (atheroma plaques and sera). The calculated PLS-DA models showed a 100 % sensitivity and a 96.6 % specificity for the cross validation to discriminate between symptomatic and asymptomatic plaques, and 88.37 % sensitivity and 77.78 % specificity when serum samples were analysed. According to the results of our multivariate and univariate analysis, the most discriminative metabolites for plaque vulnerability were threonine in serum samples, and glutamate in plaque samples. Also, an analysis of the main metabolic pathways involved in plaque vulnerability revealed that d-glutamine and d-glutamate metabolism, and phenylalanine, tyrosine, and tryptophan biosynthesis were the most affected pathways in plaque and serum, respectively.
颈动脉狭窄主要是由于血管壁上动脉粥样硬化斑块的逐渐积累所致。动脉粥样硬化斑块的特征是脂质、低密度蛋白的积累，趋化因子和黏附分子的表达，以及单核细胞和淋巴细胞向斑块内迁移。其破裂可导致中风，但栓塞倾向主要取决于斑块的成分和易损性，而非狭窄的严重程度。因此，确定哪些颈动脉狭窄患者发生神经症状的风险更高很重要。在此，我们进行了一项代谢组学研究，利用核磁共振（NMR）光谱对近期有症状和无症状颈动脉狭窄患者的动脉粥样硬化斑块和血清样本进行分析，以寻找可作为与斑块易损性及随后破裂风险相关生物标志物的代谢物。通过NMR光谱对38个动脉粥样硬化斑块样本（24例无症状患者和14例有症状患者）和70个血清样本（43例无症状患者和27例有症状患者）进行了研究。使用多变量统计（PLS-DA）对数据进行分析，以确定区分有症状和无症状样本（动脉粥样硬化斑块和血清）的模型。计算得到的PLS-DA模型在交叉验证中区分有症状和无症状斑块时灵敏度为100%，特异性为96.6%，分析血清样本时灵敏度为88.37%，特异性为77.78%。根据我们多变量和单变量分析的结果，血清样本中对斑块易损性最具鉴别力的代谢物是苏氨酸，斑块样本中是谷氨酸。此外，对斑块易损性所涉及的主要代谢途径的分析表明，d-谷氨酰胺和d-谷氨酸代谢以及苯丙氨酸、酪氨酸和色氨酸生物合成分别是斑块和血清中受影响最大的途径。
