色谱 ›› 2020, Vol. 38 ›› Issue (5): 587-594.DOI: 10.3724/SP.J.1123.2019.07030

• 研究论文 • 上一篇    下一篇

基于气相色谱-质谱联用技术的血清氨基酸代谢谱在尿石症中的应用

高瑶1,*(), 龚思思1, 张天闻2, 唐敏洁3, 张蓓英1, 陈敏1,*(), 欧启水3, 毛厚平3   

  1. 1 福建医科大学医学技术与工程学院, 福建 福州 350004
    2 福建省渔业资源监测中心, 福建 福州 350003
    3 福建医科大学附属第一医院, 福建 福州 350005
  • 收稿日期:2019-07-27 出版日期:2020-05-08 发布日期:2020-12-10
  • 通讯作者: 高瑶,陈敏
  • 作者简介:陈敏.Tel:059183569236, E-mail:cmjy503@163.com
    高瑶.Tel:059183569236, E-mail:yaogao@fjmu.edu.cn;
  • 基金资助:
    国家自然科学基金(21405017);福建省自然科学基金(2018J01676);福建省大学生创新创业训练计划(201610392079);福建医科大学医学技术与工程学院青-科研基金计划项目(2018xy001)

Application of serum amino acid profile in urolithiasis based on gas chromatography-mass spectrometry

GAO Yao1,*(), GONG Sisi1, ZHANG Tianwen2, TANG Minjie3, ZHANG Beiying1, CHEN Min1,*(), OU Qishui3, MAO Houping3   

  1. 1 School of Medical Technology and Engineering, Fujian Medical University, Fuzhou 350004, China
    2 Fujian Fishery Resources Monitoring Center, Fuzhou 350003, China
    3 the First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China
  • Received:2019-07-27 Online:2020-05-08 Published:2020-12-10
  • Contact: GAO Yao,CHEN Min
  • Supported by:
    National Natural Science Foundation of China(21405017);Fujian Natural Science Foundation(2018J01676);College Students’ Innovation and Entrepreneurship Training Program of Fujian Province(201610392079);Youth Scientific Research Fund Project of School of Medical Technology and Engi- neering of Fujian Medical University(2018xy001)

摘要:

建立了基于气相色谱-质谱联用技术(GC-MS)的血清氨基酸检测平台,研究病例组(n=80,年龄(46.82±13.39)岁)和对照组(n=37,年龄(43.46±12.79)岁)的血清氨基酸代谢谱差异,运用多元统计分析模型,结合两样本t检验、逻辑回归分析、受试者工作特征(ROC)曲线筛选与尿石症相关差异氨基酸。该方法中目标氨基酸的线性相关系数(R2)均大于0.9985,检出限(LOD)在0.1~4.0 μmol/L之间。研究结果显示,通过血清氨基酸代谢谱能够很好地区分病例组和对照组,根据变量重要性投影(VIP)>1和p < 0.05筛选出的5种差异氨基酸可作为尿石症的潜在生物标志物,其联合指标的诊断灵敏度达97.3%;其中,丝氨酸ROC曲线下面积(AUC)达0.819,具有较好的临床价值,有望辅助临床进行尿石症的早期筛查诊断。

关键词: 气相色谱-质谱, 氨基酸代谢谱, 潜在生物标志物, 尿石症

Abstract:

An overall workflow based on gas chromatography-mass spectrometry (GC-MS) was established for the analysis of the serum amino acid profile between urolithiasis patients (n=80, age (46.82±13.39) years) and healthy controls (n=37, age (43.46±12.79) years). The raw data from GC-MS analysis were processed by multivariate statistical methods to build the model. Following this, student's t-test and logistic regression were performed and receiver operator characteristic (ROC) curve was plotted to identify the potential biomarkers. Good linearities were observed for the target amino acids, with correlation coefficients (R2) greater than 0.9985. The limits of detection (LODs) were 0.1-4.0 μmol/L. The results indicated a significant discrimination between the urolithiasis and control groups. Five significantly differentially expressed amino acids (variable importance in projection (VIP)>1 and p < 0.05) were found to provide the scientific evidence for the early diagnosis of urolithiasis, while the sensitivity of the integrated five differential amino acids was up to 97.3%. In particular, the area under the curve (AUC) of serine reached 0.819, which suggested a great clinical screening value.

Key words: gas chromatography-mass spectrometry (GC-MS), amino acid profile, potential biomarkers, urolithiasis