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目的:以基于核磁共振(NMR)的代谢组学方法对Wilson病大鼠模型及正常对照组大鼠血清进行研究,分析血清中小分子代谢物的变化,从小分子代谢物层面上探讨Wilson病的内在机制,以更加清楚的认识本病。方法:22只雄性Wistar大鼠,体重(180±20)g,随机被分为模型组(n=11)和健康对照组(n=11),采用铜负荷法制作Wilson病大鼠模型,以核磁共振(NMR)技术对大鼠血清进行检测。采用MestRe-C 2.3软件及自编软件对谱图进行手动调相、基线校正和谱峰对齐。对样品进行分段积分,将积分数据归一化后构成数据矩阵,并利用PCA方法对数据矩阵进行统计分析。结果:相对于正常对照组,模型组大鼠血清甜菜碱(betaine)、氧化三甲胺(TAMO)、低密度脂蛋白(LDL)、极低密度脂蛋白(VLDL)、葡萄糖(glucose)含量有显著降低,胆碱(choline)、胆碱磷酸(phosphorylcholine)的含量有所降低,乳酸(lactate)、谷氨酰胺(glutamine)、糖蛋白(glycoprotein)有显著升高,肌氨酸+肌氨酸酐(creatine+creatinine),精氨酸(arginine)有所升高。这些发生改变的代谢物可以作为WD的小分子代谢标志物,为进一步研究WD的内在代谢机制提供参考。
OBJECTIVE: To study the changes of small molecule metabolites in serum of Wilson’s disease rat model and normal control rats based on nuclear magnetic resonance (NMR) metabolomics, and to explore the inner part of Wilson’s disease from the perspective of small molecule metabolites Mechanism to more clearly understand the disease. Methods: Twenty-two male Wistar rats weighing 180 ± 20 g were randomly divided into model group (n = 11) and healthy control group (n = 11) Nuclear magnetic resonance (NMR) detection of rat serum. Using MestRe-C 2.3 software and self-compiled software manual phasing, baseline correction and spectral peak alignment. The samples were segmented and integrated, the integral data were normalized to form the data matrix, and the data matrix was analyzed by PCA method. Results: Compared with the normal control group, the levels of serum betaine, TAMO, LDL, VLDL and glucose in model group were significantly Decreased, choline, phosphorylcholine content decreased, lactate, glutamine, glycoprotein were significantly increased, sarcosine + creatinine ( creatine + creatinine), arginine (arginine) has increased. These altered metabolites can serve as small molecule metabolic markers of WD, providing a reference for further study of the intrinsic metabolic mechanism of WD.