基于UFLC-IT-TOF MS技术的乙型肝炎病毒慢性感染后肝病不同临床阶段的血清代谢组学研究

发布时间：2018-08-22 20:52

【摘要】：目的:利用超快速液相色谱-离子阱-飞行时间串联质谱分析(UFLC-IT-TOF MS)技术,建立了分析检测肝癌患者血清中广谱小分子代谢物的代谢组学新方法。并将该方法应用于测定乙肝病毒感染后肝病的不同阶段患者及健康志愿者血清中的代谢产物,分析其间的差异和变化,探讨其在机体内的代谢特征,为揭示其发病机制及辅助诊断提供可参考的代谢组学信息。方法:1利用UFLC-IT-TOF MS技术,建立检测小分子代谢产物新方法随机选取肝癌患者80例、健康者20例,留取晨起空腹外周静脉血3ml,置于标准一次性采血玻璃管中,离心后取血清1.5ml存放至EP管密封,置于-80℃冰箱中冷冻保存备用。根据标准物质的质谱相应值确定各物质检测的离子模式,配制内标溶液备用。比较不同的溶剂系统种类、与血清的体积比和预存温度,观察沉淀蛋白的效果;比较不同色谱-质谱条件下,有效信号、干扰噪音峰形及离子化效率,确定最佳方案,并通过在肝癌组混合血清样本中加入标准溶液,经多次平行测定验证方法良好。将上述80例肝癌患者和20例健康者的混合血清样本按该方法进行UFLC-IT-TOF MS检测。检测结果应用LCMS Solution(版本3.60)等软件对上述三维数据进行多维统计分析,以筛选出有统计学意义的变量。2具有潜在临床应用价值的代谢标志物分析随机选取处于肝病不同阶段的HBV感染患者197例,同期选择58例健康志愿者,入选受试者共255例。诊断标准,样本制备方法同上。应用上述方法,检测上述各组共255例血清单个样本,得到的数值应用IBM SPSS(版本24.0)软件进行分析。结果:1用于检测血清中小分子代谢产物的检测方法得到优化通过对比成分、比例不同的溶剂,比较提取离子流色谱图的峰强度、分离度和检测物质峰数,通过对比溶剂与血清不同体积比的柱压情况,结合环境保护的原则,通过对比不同预存温度下的提取效率,确定最佳的有机蛋白沉淀方案。通过评价不同流动相的获得信号、减少噪音、峰形的灵敏度和分离度继离子化效率,确定最佳流动相的体系、组成、流速和柱温。并利用标准溶液,平行在不同时间点、连续测定多个样本,计算RSD值,进行PCA分析,结果表明该方法精密度、稳定性、可靠性良好。2在肝癌患者与健康人混合血清中筛选出有价值的潜在标志物通过应用多变量统计分析方法,分析肝癌患者与对照组的代谢物指纹图谱,筛选出8种有临床价值的肝癌潜在标志代谢产物,确定为:甘氨胆酸、甘油磷酸酯、十四酰胺、乙酰苯丙氨酸、油酰胺、乙酰肉毒碱、溶血卵磷脂、甘氨鹅去氧胆酸。3应用上述方法检测HBV感染各组及健康对照组单个样本确定有临床价值的代谢标志物通过上述方法,测定上述255例受试者的单个血清样本中上述8种代谢产物的含量。发现其中4种物质含量极低,各个样本间差别较大,多数样本测定数值为0,无法进行统计学归纳。另外4种代谢产物:溶血卵磷脂、乙酰肉毒碱、油酰胺、甘氨胆酸,通过非参数检验,确定其在各组间的差别有统计学意义。对乙酰肉毒碱在肝硬化和肝癌患者中较为显著的变化,应用ROC曲线,计算AUC值,得到最佳界定点的灵敏的和特异性。结论:1通过优化对肝癌患者与健康组混合血清样本的预处理方式,建立了基于UFLC-IT-TOF MS技术的新方法,符合高通量的筛选代谢组学成分的研究方法要求,适合对待研究的生物样本进行大批量筛选代谢组学成分的研究。2溶血卵磷脂、乙酰肉毒碱、油酰胺有望成为肝癌的代谢标志物。其中,溶血卵磷脂在肝癌患者血液中的含量较其他各组明显降低,与另外2种代谢物相比较,AUC值最大,诊断效能好,为辅助临床诊断及开展科学研究提供可参考的代谢组学信息。
[Abstract]:OBJECTIVE:To establish a new method for the determination of broad-spectrum small molecule metabolites in serum of patients with hepatocellular carcinoma by ultra-fast liquid chromatography-ion trap-time-of-flight mass spectrometry(UFLC-IT-TOF MS). METHODS: 1 Using UFLC-IT-TOF MS, a new method was established to detect small molecule metabolites in 80 patients with hepatocellular carcinoma (HCC) and 20 healthy volunteers. Peripheral venous blood was stored in a standard disposable glass tube for 3 ml. After centrifugation, 1.5 ml of serum was taken and sealed in an EP tube. The plasma was frozen in a refrigerator at - 80 C for reserve. Ion patterns of each substance were determined according to the corresponding mass spectrometry values of the standard substances, and internal standard solutions were prepared. The effect of precipitated protein was observed at pre-storage temperature, and the best scheme was determined by comparing the effective signal, noise peak shape and ionization efficiency under different conditions of GC-MS. The method was verified by adding standard solution into mixed serum samples of hepatocellular carcinoma group, and was verified by many parallel tests. Serum samples were tested by UFLC-IT-TOF MS. The results were analyzed by LCMS Solution (Version 3.60) and other software to screen statistically significant variables. 97 healthy volunteers and 255 healthy volunteers were selected at the same time. The diagnostic criteria and sample preparation methods were the same as above. Using the above methods, 255 serum samples from each group were detected. The values obtained were analyzed by IBM SPSS (version 24.0). Through comparing the components and the proportion of different solvents, the peak intensity, separation degree and the number of detection substances were compared. By comparing the column pressure of different volume ratio of solvent and serum, and combining with the principle of environmental protection, the best Precipitation Scheme of organic protein was determined by comparing the extraction efficiency under different storage temperature. The system, composition, flow rate and column temperature of the best mobile phase were determined by evaluating the signals obtained from different mobile phases, reducing noise, peak shape sensitivity and separation efficiency. Reliability is good. 2 Select valuable potential markers in the mixed serum of patients with liver cancer and healthy people. Analyse the metabolite fingerprint of patients with liver cancer and control group by using multivariate statistical analysis method. Screen out 8 potential metabolites of liver cancer markers with clinical value, which are: glycocholic acid, glycerophosphate, 14. Amide, acetylphenylalanine, oleamide, acetylcarnitine, lysophosphatidylcholine, glycine-geese deoxycholic acid. 3 The above methods were used to detect the metabolic markers of HBV infection in each group and in a single sample of healthy control group to determine the content of the above 8 metabolites in a single serum sample of the 255 subjects. The other four metabolites, hemolytic lecithin, acetylcarnitine, oleamide, glycocholic acid, were determined by non-parametric test, and the difference between the groups was statistically significant. Conclusion: 1. A new method based on UFLC-IT-TOF MS was established by optimizing the pretreatment method of mixed serum samples from patients with hepatocellular carcinoma and healthy subjects, which was in line with high throughput screening of metabolomic components. 2. Hemolytic lecithin, acetylcarnitine and oleamide are expected to be metabolic markers of hepatocellular carcinoma. Among them, the content of hemolytic lecithin in the blood of patients with hepatocellular carcinoma is significantly lower than that of the other two metabolites. It has the highest diagnostic value and good diagnostic efficacy, and can provide reference metabonomics information for clinical diagnosis and scientific research.
【学位授予单位】：河北医科大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R512.62

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