检验医学 ›› 2019, Vol. 34 ›› Issue (5): 383-389.DOI: 10.3969/j.issn.1673-8640.2019.05.001

• 临床应用研究·论著 •    下一篇

预测急性心肌梗死患者转归的血清代谢物谱研究

刘婕, 石欣荣, 周淑芬, 许宏敏, 张磊, 刘树业()   

  1. 天津市第三中心医院检验科,天津 300170
  • 收稿日期:2018-08-22 出版日期:2019-05-30 发布日期:2019-05-28
  • 作者简介:null

    作者简介:刘 婕,女,1988年生,硕士,技师,主要从事疾病的代谢组学研究。

Serum metabolins predicting acute myocardial infarction patients' outcome

LIU Jie, SHI Xinrong, ZHOU Shufen, XU Hongmin, ZHANG Lei, LIU Shuye()   

  1. Department of Clinical Laboratory,Tianjin Third Central Hospital,Tianjin 300170,China
  • Received:2018-08-22 Online:2019-05-30 Published:2019-05-28

摘要:

目的 采用液-质联用代谢组学研究平台寻找能在急性心肌梗死(AMI)患者入院时即预测患者转归的特异性代谢物。方法 运用超高效液相色谱串联质谱(UPLC-MS/MS)代谢组学研究平台分析48例心绞痛患者、24例AMI好转者、24例AMI死亡者及48名体检健康者(正常对照组)代谢物数据,对代谢轮廓数据的变异性进行分析,构建疾病区分模型。采用受试者工作特征(ROC)曲线评估特征代谢物的临床诊断效能。结果 成功构建了“正常对照组-心绞痛组-AMI好转组-AMI死亡组”的主成分分析(PCA)模型(R2X=40.2%,Q2=13.9%)及正交偏最小二乘判别分析(OPLS-DA)模型(R2X=79.0%,R2Y=83.2%,Q2=65.0%)。验证结果显示模型的预测准确度达100%。筛选并鉴定出10种可用于AMI预后判断的代谢物离子,其中4-羟基-6-二十二烷酮、N-乙酰-白三烯、溶血磷脂酰胆碱(LPC)[18:2(9Z,12Z)]、LPC(18: 0)、LPC(P-16:0)、LPC[P-18:1(9Z)]、LPC[20:1(11Z)]、LPC[20:2(11Z,14Z)]在AMI死亡患者的血清中水平较低,L-苏氨酸、3-甲基-2-丁烯-1-硫醇水平较高,与AMI好转患者比较差异均有统计学意义(P<0.05)。结论 采用代谢组学分析方法找到的特征代谢物具有很好的预测AMI患者预后的能力,可作为潜在的疾病转归标志物进一步研究。

关键词: 代谢组学, 心绞痛, 心肌梗死, 超高效液相色谱串联质谱

Abstract:

Objective To find serum metabolins predicting acute myocardial infarction (AMI)patients' outcome,using the metabolomics platform of ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS) when patients are admitted to hospital. Methods UPLC-MS/MS platform was used to analyze 48 healthy subjects(healthy control group),48 angina patients,24 AMI patients with improvement and 24 AMI dead patients. The disease distinguishing model was established. Receiver operating characteristic(ROC) curve was used to evaluate the clinical diagnostic performance of characteristic metabolins. Results A "Normal-Angina-AMI improved-AMI dead" of the principal component analysis(PCA)(R2X=40.2%, Q2=13.9%)and orthogonal partial least-square discrimination analysis (OPLS-DA) model (R2X=79.0%, R2Y=83.2%, Q2=65.0%) were established. Through verifying,the model prediction accuracy reached 100%. Totally,10 kinds of ions that can estimate the prognosis of AMI were screened and verified. 4-Hydroxy-6-docosanone,N-acetyl-leukotriene,lysophosphatldy choline(LPC)[18: 2(9Z,12Z)],LPC(18:0),LPC(P-16:0),LPC[P-18:1(9Z)],LPC[20:1(11Z)],LPC[20:2(11Z,14Z)] decreased,and L-threonine and 3-methyl-2-butene-1-thiol increased. There was statistical significance between AMI patients with improvement and AMI dead patients(P<0.05). Conclusions Specific metabolins can effectively predict the prognosis of patients with AMI. These ions may be potential prognosis biomarkers and have benefit in further clinical study.

Key words: Metabolomics, Angina, Myocardial infarction, Ultra-high performance liquid chromatography-tandem mass spectrometry

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