| 刘武纬,袁道祎,韩敏露,黄靓雯,谢 瑛.基于UPLC-MS技术筛选db/db小鼠血清和组织中的小分子2型糖尿病标志物[J].,2021,(15):2801-2807 |
| 基于UPLC-MS技术筛选db/db小鼠血清和组织中的小分子2型糖尿病标志物 |
| UPLC-MS Based Screening of Type 2 Diabetes Mellitus Micromolecule Markers in Serum and Tissues of db/db Mice |
| 投稿时间：2021-02-03 修订日期：2021-02-27 |
| DOI：10.13241/j.cnki.pmb.2021.15.001 |
| 中文关键词: 2型糖尿病 代谢组学 标志物 |
| 英文关键词: Type 2 diabetes mellitus Metabolomics Biomarker |
| 基金项目:国家重点研发计划项目(2017YFC1309701)；国家十三五新药创制重大专项(2018ZX09734005) |
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| 中文摘要: |
| 摘要 目的：2型糖尿病（Type 2 Diabetes Mellitus，T2DM）发病持续增长，并发症致死率高，疾病无法根治需长期用药维持，所以2型糖尿病的早期诊断和预防十分重要。故本研究探究2型糖尿病模型db/db小鼠不同疾病进程中血清和组织代谢谱的变化，筛选密切相关的小分子代谢产物，为2型糖尿病早诊和预防提供参考。方法：本研究利用超高效液相色谱联用四极杆时间飞行质谱（UPLC-QTOF/MS）技术，以8，12，16周龄三个不同阶段db/db小鼠及其对照的血清和组织为研究对象，进行非靶向代谢组学研究。利用MarkerView提取采集到的数据，通过SMICA-P软件进行主成分分析（PCA）和OPLS-DA建模分析，对数据进行降维处理，结合t检验筛选出特异性的差异代谢物，联合二元逻辑回归建立诊断模型。结果：随着病程发展，显示出更多代谢紊乱。二十碳五烯酸(Eicosapentaenoic acid，EPA)，酪氨酸(Tyrosine)和亮氨酸(Leucine)三个代谢物在T2DM模型db/db小鼠及其野生对照组血清和组织中具有显著性差异，差异倍数明显且与随疾病进程呈现正负相关性。经过二元逻辑回归建立联合诊断模型，三种代谢物组合的诊断模型为Logit[P=T2DM]=-6.052*[ EPA]+5.837*[ Tyrosine]+1.985*[ Leucine]-14.092。根据此模型建立受试者工作特征曲线(Receiver operating characteristic curve，ROC)，曲线下面积(Area under curve，AUC)为0.988，灵敏度和特异性均为98.1%。结论：EPA，Tyrosine和Leucine可被认为是最典型的T2DM标志物，值得进一步探讨，为2型糖尿病的发生风险和治疗提供参考。 |
| 英文摘要: |
| ABSTRACT Objective: The incidence of type 2 diabetes mellitus (T2DM) continues to increase and the mortality rate of its complications is high. The disease cannot be completely cured and needs to be controlled by medicines for a long time, so it is important to early diagnose and prevent. Therefore, this study explored the changes of serum and tissue metabolic profiles in different disease processes of db/db mice. Methods: Based on the Ultra-high performance liquid chromatography combined with quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS), non-targeted metabonomics was studied in serum and tissues of db/db mice and their controls at the age of 8, 12 and 16 weeks. The specific differential metabolites were screened by PCA, OPLS-DA and t-test, then the diagnosis model was established by binary logistic regression. Results: More metabolic disorders were shown with the development of the disease. The levels of eicosapentaenoic acid (EPA), tyrosine and leucine had significant differences in the serum and tissues of db/db mice and their controls, which were positively and negatively correlated with the progression of the disease. A joint diagnosis model based on the three metabolites for the detection of T2DM was established as follows: Logit [P=T2DM] =-6.052 * [EPA] + 5.837 * [Tyrosine] + 1.985 * [Leucine]-14.092. The Receiver operating characteristic curve (ROC) was constructed according to the diagnosis model. Outstanding diagnostic efficiency had been achieved with area under curve (AUC) of 0.988, sensitivity and specificity both of 98.1%. Conclusion: EPA, tyrosine and leucine can be regarded as the most typical T2DM markers. |
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