Sci Rep发表中国学者法医鉴定年龄推断新成果

　　

　年龄推断是法医学领域研究的重要课题之一，尤其是涉及青少年犯罪以及推断高度腐败甚至白骨化无名尸的年龄，可为尸源的查找提供侦查范围和线索。另外，根据现场遗留生物物证推断嫌疑人年龄在法医学实践中也具有重要的应用价值。传统的个体年龄的评估主要是依据骨骼、牙齿等组织以及组织中各类物质的物理和化学特性等随年龄增长的时序性变化，而当法医样本为组织残缺碎片、毛发、斑迹等时，这种方法往往受到限制无法实现或者误差较大。另外，端粒DNA长度、线粒体DNA氧化损伤程度等“分子标记”，也由于生物体生长发育的生理性变化及其影响因素极为复杂，同样存在技术局限和判定年龄跨度大等问题。近年来随着表观遗传学研究的发展，发现DNA甲基化与年龄之间存在关联性，从而为年龄评估带来新的希望。

　　近日，中国科学院北京基因组研究所基因组科学与信息重点实验室严江伟、方向东、章张研究组与公安部物证鉴定中心法医遗传学重点实验室合作建立了一种基于SVR模型和DNA甲基化的准确推断年龄的新方法，将由血液样本年龄预测的误差降低到4.7岁。此项研究以A novel strategy for forensic age prediction by DNA methylation and support vector regression model 为题于近期发表在Scientific Reports 杂志。

　　该研究首先通过甲基化芯片检测21-32岁女性双胞胎血样样本的全基因组DNA甲基化，筛选出与中国汉族女性个体年龄具有高度相关性的位点，并利用Sequenom MassARRAY技术在介于20-80岁之间的女性血样样本内对上述年龄相关位点验证，将进一步获得的6个与年龄高度相关的位点分别利用普通线性回归、多元非线性回归、神经网络和支持向量回归（SVR）四种方法进行年龄推断。经比较，SVR方法预测的年龄误差为2.8岁、交叉验证之后的年龄误差为4.7岁，优于其它三种方法。

　　该方法在进一步经法医学样本适用性、准确性、灵敏度、特异性等法庭科学有效性验证后，最终有望在法医学实践中实现推断生物样品来源者的年龄，从而为解决法医学这一难题提供新的有价值的途径。

　　该项研究获得了国家自然科学基金委、公安部、中国科学院青年促进会等项目资助。

SVR进行年龄推断

原文摘要：

A novel strategy for forensic age prediction by DNA methylation and support vector regression model
High deviations resulting from prediction model, gender and population difference have limited age estimation application of DNA methylation markers. Here we identified 2,957 novel age-associated DNA methylation sites (P < 0.01 and R2 > 0.5) in blood of eight pairs of Chinese Han female monozygotic twins. Among them, nine novel sites (false discovery rate < 0.01), along with three other reported sites, were further validated in 49 unrelated female volunteers with ages of 20–80 years by Sequenom Massarray. A total of 95 CpGs were covered in the PCR products and 11 of them were built the age prediction models. After comparing four different models including, multivariate linear regression, multivariate nonlinear regression, back propagation neural network and support vector regression, SVR was identified as the most robust model with the least mean absolute deviation from real chronological age (2.8 years) and an average accuracy of 4.7 years predicted by only six loci from the 11 loci, as well as an less cross-validated error compared with linear regression model. Our novel strategy provides an accurate measurement that is highly useful in estimating the individual age in forensic practice as well as in tracking the aging process in other related applications.