法医学杂志

法医学杂志 ›› 2020, Vol. 36 ›› Issue (6): 741-748.DOI: 10.12116/j.issn.1004-5619.2020.06.001

• 论 著 •    下一篇

基于GC-MS代谢组学推断不同环境温度下窒息死大鼠的早期死亡时间

方世勇， 戴鑫华， 肖莉， 邹静， 杨林， 叶懿， 廖林川   

  1. 四川大学华西基础医学与法医学院，四川 成都 610041
  • 收稿日期:2020-03-29 发布日期:2020-12-25 出版日期:2020-12-28
  • 通讯作者: 廖林川，男，教授，博士研究生导师，主要从事药物分析和法医毒物分析研究；E-mail：linchuanliao@scu.edu.cn
  • 作者简介:方世勇（1994—），男，硕士研究生，主要从事法医毒物分析研究；E-mail：1020354399@qq.com
  • 基金资助:
    国家自然科学基金面上项目（81373239）；四川省科技厅重点研发项目（2019YFS0066）

Estimation of Early Postmortem Interval of Asphyxial Death Rats at Different Ambient Temperatures by GC-MS-Based Metabolomics

FANG Shi-yong, DAI Xin-hua, XIAO Li, ZOU Jing, YANG Lin, YE Yi, LIAO Lin-chuan   

  1. West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu 610041, China
  • Received:2020-03-29 Online:2020-12-25 Published:2020-12-28

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摘要： 目的 基于气相色谱-质谱（gas chromatography-mass spectrometry，GC-MS）代谢组学技术建立4种 环境温度下窒息死大鼠早期死亡时间推断的正交偏最小二乘（orthogonal partial least square，OPLS）模型， 用于推断不同温度条件下窒息死大鼠的早期死亡时间。 方法 将 96 只大鼠平均分为 4 个温度组（5 ℃、 15 ℃、25 ℃、35 ℃），每组再分为死后3 h、6 h、12 h、24 h，另取6只大鼠作为对照组。4个温度组于设定的时 间点、对照组于死后 0 h 取心血进行 GC-MS 代谢组学分析。通过 OPLS 分析，以变量投影重要性（variable importance in projection，VIP）>1及Kruskal-Wallis检验P<0.001筛选出各温度组大鼠心血中与死亡时间相 关的差异代谢物，利用差异代谢物分别建立不同温度组的OPLS回归模型，同时设置预测组考察模型的预 测能力。 结果 通过OPLS分析，分别从5 ℃、15 ℃、25 ℃、35 ℃组大鼠心血中筛选出18、15、24、30种差异代 谢物（包括有机酸、氨基酸、糖类、脂质等）。4个温度组模型的预测结果显示，5 ℃模型相对其他组预测偏差较 大，其余各温度组预测结果较为理想。 结论 不同环境温度下大鼠尸体心血中的代谢物变化有一定差异， 利用代谢组学技术推断死亡时间的研究中应当考察环境温度的影响，有望提高死亡时间推断的准确性。

关键词: 法医病理学；代谢组学；气相色谱-质谱法；模型, 统计学；环境温度；代谢物；死亡时间推断；大鼠

Abstract: Objective To establish the orthogonal partial least square （OPLS） model for the estimation of early postmortem interval （PMI） of asphyxial death rats in four ambient temperatures based on gas chromatography-mass spectrometry （GC-MS） metabolomics. Methods The 96 rats were divided into four temperature groups （5 ℃, 15 ℃, 25 ℃ and 35 ℃）. Each temperature group was further divided into 3 h, 6 h, 12 h and 24 h after death, and 6 other rats were taken as the control group. The cardiac blood was collected at the set time points for the four temperature groups and 0 h after death for the control group for the metabolomics analysis by GC-MS. By OPLS analysis, the variable importance in projection （VIP）>1 and the result of Kruskal-Wallis test P<0.001 were used to screen out the differential metabolite related to PMIs in the cardiac blood of rats of different temperature groups. Then OPLS regression models of different temperature groups were established with these metabolites. At the same time, a prediction group for investigating the prediction ability of these models was set up. Results Through the analysis of OPLS, 18, 15, 24 and 30 differential metabolites （including organic acids, amino acids, sugars and lipids） were screened out from the rats in groups of 5 ℃, 15 ℃, 25 ℃ and 35 ℃, respectively. The prediction results of the four temperature group models showed that the prediction deviation of 5 ℃ model was larger than that of other groups. The prediction results of other temperature groups were satisfactory. Conclusion There are some differences in the changes of metabolites in cardiac blood of rats at different ambient temperatures. The influence of ambient temperature should be investigated in the study of PMI estimation by metabolomics, which may improve the accuracy of PMI estimation.

Key words: forensic pathology, metabolomics, gas chromatography-mass spectrometry, models, statistical, ambient temperature, metabolite, estimation of postmortem interval, rats

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