摘要
本文验证前期已构建的基于DNA甲基化的9-CpG年龄推断模型并对其进行优化,进一步拓展年龄推断模型的应用范围。采集浙江汉族个体血液制备成血斑样本,男性100份,女性96份。男、女性样本年龄范围均为16-65岁,年龄均值分别为(41±13)岁、(38±13)岁,并按照年龄段各分为5组。磁珠法提取DNA后采用重亚硫酸盐转化,使用EpiTYPER技术平台检测模型中的9个CpG甲基化位点,最后按照多元回归推断公式计算年龄值。结果表明,所有样本的转化DNA平均回收率为42.92%±14.03%。男性样本的推断年龄与实际年龄的平均绝对偏差(MAD)为2.95岁,不同年龄组间的MAD值无明显差异,年龄高估与低估的样本数基本相等;女性样本的MAD为3.18岁,不同年龄组间的MAD差异显著。对女性样本调整回归模型后其年龄推断的MAD为2.65岁,不同年龄组间的MAD值较为均一。前期已构建的9-CpG年龄推断模型适用于浙江男性汉族个体的年龄推断,调整优化后的年龄推断模型对浙江女性汉族个体的预测更为精准,且上述两个预测模型均适用于现场血斑样本。
The DNA methylation-based 9-CpG age prediction model was to verify and optimize with purpose to further expand its application scope.From 100 male and 96 female individuals of Zhejiang Han-ethnic population,the blood samples were collected and left to separately dry on gauze.The male and female blood samples were divided into 5 groups according to their ages(ranging from 16—65 years old),having their DNA extracted with magnetic bead method and then converted through bisulfi te.EpiTYPER platform was adopted to detect the nine methylation sites available with the model.The predicted age value was calculated under the multiple regression inference formula.The average recovery of converted genome DNA was 42.92%±14.03%.For male samples,the mean absolute deviation(MAD)was about 2.95 years between the predicted age and the real,having no signifi cant difference in MAD values between the age-different groups but showing basically equal about the number of samples relating to age over-/under-estimation.For female samples,the MAD was 3.18 years,quite different between discrepant age groups and able to reduce to 2.65 years after the regression model was adjusted to result in relative similarity among different age groups.The DNA methylation-based 9-CpG age model established previously is suitable for prediction of Zhejiang Han-ethnic male individuals with detection of relevant bloodstains collected on the crime scene,and capable of being used for Zhejiang Han-ethnic female individuals with bloodstain as the samples after implementation of adjustment and optimization.
作者
高林林
王科文
李佑英
罗俊
徐红伟
周志全
王琴
丰蕾
GAO Linlin;WANG Kewen;LI Youying;LUO Jun;XU Hongwei;ZHOU Zhiquan;WANG Qin;FENG Lei(Institute of Criminal Science and Technology of Hangzhou Public Security Bureau,Hangzhou 310006,China;Institute of Forensic Science,Ministry of Public Security,Beijing 100038,China;Huashuo Center of Forensic Science,Hangzhou 310006,China;Jiande Public Security Bureau,Jiande 311600,Zhejiang,China)
出处
《刑事技术》
2022年第6期627-632,共6页
Forensic Science and Technology
基金
北京市现场物证检验工程技术研究中心开放课题(2019CSEEKFKT07)。