基于液相色谱-质谱技术的高尿酸血症血浆代谢组学研究

Liquid chromatography-mass spectrometry-based research on plasma metabonomics of patients with hyperuricemia

目的利用代谢组学技术研究高尿酸血症患者与健康人血浆的代谢差异情况,寻找差异代谢标志物,为探讨高尿酸血症病因及与其他代谢性疾病的关系提供参考。方法通过超高效液相色谱-四级杆-飞行时间质谱(UPLC-Q-TOF-MS)技术分析高尿酸血症患者(高尿酸血症组)和健康者(对照组)血浆代谢物图谱,采用MarkerLynx XS软件对原始数据进行校正和归一化处理,应用SIMCA-P+12.0.1软件对样品进行分组并采用正交信号校正和偏最小二乘法判别分析(OSC-PLS-DA)分析。分析结果以二维、三维得分图和载荷图的形式表示,根据OSC-PLS-DA模型的VIP值及显著性差异检验结果等筛选出差异性代谢物。结果高尿酸血症组与对照组分别呈现聚类分布,两组之间未见交叉与重叠,得到了明显区分。初步确认6种化合物(质荷比分别为282.279 2、496.340 0、280.263 2、79.020 3、256.263 2及284.294 5)为区分高尿酸血症与健康人的潜在的血浆差异性代谢标志物。结论建立了利用液相色谱-质谱技术进行高尿酸血症血浆代谢组学研究的方法,为高尿酸血症的发病机制、预测和防治研究奠定了基础。

Abstract：Objective To explore the differences in plasma metabolism between patients with hyperuricemia and healthy people using the technology of metabolomics,searching the metabolic markers,which will provide a reference for exploring the etiology of hyperuricemia and its relationship with other metabolic diseases. Methods The plasma metaholites patterns of patients with hyperuricemia （hyperuricemia group） and healthy people（control group） were analyzed by ultra-performance liquid chromatographyquatrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS）. MarkerLynx XS software was used to regulate and normalize the original data. Statistical software SIMCA-P＋12.0.1 was applied to group the sample and analyze the data using orthogonal signal correction partial least square discriminate analysis（OSC-PLS-DA）. Results of the analysis were expressed by the form of two-di mensional and three-dimensional scores plot and loading plot,respectively. The different metabolites were screened according to the VIP value of OSC-PLS-DA model and the results of significant differences test. Results The cluster distribution was displayed in both hyperuricemia group and control group, no cross and overlap was observed between the two groups, which means that these two groups were distinguished from each other clearly. Six compounds （mass to charge ratios were 282. 279 2,496. 340 0, 280. 263 2,79. 020 3,256. 263 2 and 284. 294 5,respectively） were initially identified as potential plasma metabolic markers to distinguish hyperuricemia from healthy people. Conclusion The method of hyperuricemia plasma metabolomies study has been con structed using the technology of liquid chromatography-mass spectrometry which lay the foundation for the research of hyperuricemia pathogenesis,prediction and prevention.