法医学杂志

法医学杂志 ›› 2020, Vol. 36 ›› Issue (4): 514-518，524.DOI: 10.12116/j.issn.1004-5619.2020.04.016

• 论著 • 上一篇    下一篇

基于microRNA表达量及判别分析的外周血与月经血鉴别

何红霞1，2， 季安全2， 韩娜3， 赵一霞2， 胡胜2， 孔庆兰4， 刘耀1，2， 孙启凡2   

  1. 1. 山西医科大学法医学院，山西 太原 030001； 2. 公安部物证鉴定中心 现场物证溯源技术国家工程实验室 法医遗传学公安部重点实验室，北京 100038； 3. 中国疾病预防控制中心传染病预防控制所 传染病预防控制国家重点实验室，北京 102206； 4. 枣庄学院数学与统计学院，山东 枣庄 277160
  • 发布日期:2020-08-25 出版日期:2020-08-28
  • 通讯作者: 刘耀，男，院士，研究员，主要从事法医毒物学研究；E-mail：liuyaol123@yahoo.cn 孙启凡，女，博士，副主任法医师，主要从事法医遗传学研究；E-mail：sunqifan@cifs.gov.cn
  • 作者简介:何红霞（1992—），女，硕士，主要从事法医学研究；E-mail：18606473949@163.com
  • 基金资助:
    国家重点研发计划资助项目（2017YFC0803503）；公安部物证鉴定中心基本科研业务费资助项目（2019JB010，2018JB036）

Identification of Peripheral Blood and Menstrual Blood Based on the Expression Level of MicroRNAs and Discriminant Analysis

HE Hong-xia1,2, JI An-quan2, HAN Na3, ZHAO Yi-xia2, HU Sheng2, KONG Qing-lan4, LIU Yao1,2, SUN Qi-fan2   

  1. 1. School of Forensic Medicine, Shanxi Medical University, Taiyuan 030001, China; 2. Key Laboratory of Forensic Genetics, Ministry of Public Security, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing 100038, China; 3. State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; 4. Faculty of Mathematics and Statistics, Zaozhuang University, Zaozhuang 277160, Shandong Province, China
  • Online:2020-08-25 Published:2020-08-28

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摘要： 目的 根据2种血液类体液（外周血和月经血）和3种非血液类体液（唾液、精液、阴道分泌液）中多种微RNA（microRNA，miRNA）差异表达的特征构建判别分析模型，形成外周血与月经血的鉴别方案。 方法 从文献中筛选出6种miRNA（miR-451a、miR-144-3p、miR-144-5p、miR-214-3p、miR-203-3p和miR-205-5p），收集5种法医学常见体液样本（外周血、月经血、唾液、精液和阴道分泌液），并将样本划分为训练集及测试集，采用SYBR Green荧光实时定量PCR技术检测，基于训练集的表达量数据构建判别分析模型，另外采用测试集的表达量数据检验该模型的准确度。 结果 成功构建了可同时区分血液与非血液类样本以及区分外周血与月经血样本的判别分析统计模型，模型的鉴别准确率达99%以上。 结论 本研究为外周血和月经血样本的法医学体液鉴别提供了科学准确的鉴别策略，有望在法医学实践中应用。

关键词: 法医遗传学；微RNAs；模型, 统计学；体液；月经血；外周血；鉴别

Abstract: Objective To construct a discriminant analysis model based on the differential expression of multiple microRNAs （miRNAs） in two kinds of blood samples （peripheral blood and menstrual blood） and three non-blood samples （saliva, semen and vaginal secretion）, to form an identification solution for peripheral blood and menstrual blood. Methods Six kinds of miRNA （miR-451a, miR-144-3p, miR-144-5p, miR-214-3p, miR-203-3p and miR-205-5p） were selected from literature, the samples of five kinds of body fluids commonly seen in forensic practice （peripheral blood, menstrual blood, saliva, semen, vaginal secretion） were collected, then the samples were divided into training set and testing set and detected by SYBR Green real-time qPCR. A discriminant analysis model was set up based on the expression data of training set and the expression data of testing set was used to examine the accuracy of the model. Results A discriminant analysis statistical model that could distinguish blood samples from non-blood samples and distinguish peripheral blood samples from menstrual blood samples at the same time was successfully constructed. The identification accuracy of the model was over 99%. Conclusion This study provides a scientific and accurate identification strategy for forensic fluid identification of peripheral blood and menstrual blood samples and could be used in forensic practice.

Key words: forensic genetics, microRNAs, models, statistical, body fluids, menstrual blood, peripheral blood, identification