A novel strategy for forensic age prediction by DNA methylation and support vector regression model.
A novel strategy for forensic age prediction by DNA methylation and support vector regression model.
复制标题
一种通过 DNA 甲基化和支持向量回归模型进行法医年龄预测的新策略。
DOI：
10.1038/srep17788
复制
发表时间：
2015-12-04
影响因子：
4.6
通讯作者：
Feng L
中科院分区：
文献类型：
--
作者：
Xu C;Qu H;Wang G;Xie B;Shi Y;Yang Y;Zhao Z;Hu L;Fang X;Yan J;Feng L
预测模型、性别和人群差异导致的高偏差限制了DNA甲基化标记的年龄估计应用。我们< 0.01 and R2 >在8对中国汉族女性单卵双胞胎的血液中发现了2,957个新的与年龄相关的DNA甲基化位点（P 0.5）。其中，9个新位点（错误发现率< 0.01），沿着其他3个已报道的位点，通过Sequenom Massarray在49名年龄为20-80岁的无关女性志愿者中进一步验证。PCR产物共覆盖了95个CpG，其中11个构建了年龄预测模型。通过对多元线性回归、多元非线性回归、反向传播神经网络和支持向量回归等4种模型的比较，发现支持向量回归模型与真实的实际年龄的平均绝对偏差最小，是最稳健的模型（2.8年）和平均准确度为4.7年，仅用11个位点中的6个位点预测，与线性回归模型相比，交叉验证误差较小。我们的新策略提供了一种准确的测量方法，在法医实践中估计个体年龄以及在其他相关应用中跟踪衰老过程方面非常有用。
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.