Wu Qiong, Zhang Hai, Dong Xin, Chen Xiao-Fei, Zhu Zhen-Yu, Hong Zhan-Ying, Chai Yi-Feng
School of Pharmacy, Second Military Medical University, Shanghai 200433, China.
J Pharm Anal. 2014 Dec;4(6):360-367. doi: 10.1016/j.jpha.2014.04.002. Epub 2014 May 10.
Hyperlipidemia is considered to be a high lipid level in blood, can induce metabolic disorders and dysfunctions of the body, and results in some severe complications. Therefore, hunting for some metabolite markers and clarifying the metabolic pathways in vivo will be an important strategy in the treatment and prevention of hyperlipidemia. In this study, a rat model of hyperlipidemia was constructed according to histopathological data and biochemical parameters, and the metabolites of serum and urine were analyzed by UPLC-Q-TOF/MS. Combining pattern recognition and statistical analysis, 19 candidate biomarkers were screened and identified. These changed metabolites indicated that during the development and progression of hyperlipidemia, energy metabolism, lipid metabolism, amino acid metabolism and nucleotide metabolism were mainly disturbed, which are reported to be closely related to diabetes, cardiovascular diseases, etc. This study demonstrated that a UPLC-Q-TOF/MS based metabolomic approach is useful to profile the alternation of endogenous metabolites of hyperlipidemia.
高脂血症被认为是血液中脂质水平过高,可诱发身体的代谢紊乱和功能障碍,并导致一些严重并发症。因此,寻找一些代谢物标志物并阐明体内代谢途径将是治疗和预防高脂血症的重要策略。在本研究中,根据组织病理学数据和生化参数构建了高脂血症大鼠模型,并通过超高效液相色谱-四极杆-飞行时间串联质谱(UPLC-Q-TOF/MS)分析血清和尿液中的代谢物。结合模式识别和统计分析,筛选并鉴定了19种候选生物标志物。这些变化的代谢物表明,在高脂血症的发生和发展过程中,能量代谢、脂质代谢、氨基酸代谢和核苷酸代谢受到主要干扰,据报道这些代谢与糖尿病、心血管疾病等密切相关。本研究表明,基于UPLC-Q-TOF/MS的代谢组学方法有助于描绘高脂血症内源性代谢物的变化情况。