Li Chunxiao, Gao Wenjing, Gao Ying, Yu Canqing, Lv Jun, Lv Ruoran, Duan Jiali, Sun Ying, Guo Xianghui, Cao Weihua, Li Liming
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
Beijing Center for Disease Control and Prevention, Beijing 100013, China.
Aging (Albany NY). 2018 May 12;10(5):1015-1026. doi: 10.18632/aging.101445.
The DNA methylation age, a good reflection of human aging process, has been used to predict chronological age of adults and newborns. However, the prediction model for children and adolescents was absent. In this study, we aimed to generate a prediction model of chronological age for children and adolescents aged 6-17 years by using age-specific DNA methylation patterns from 180 Chinese twin individuals. We identified 6,350 age-related CpGs from the epigenome-wide association analysis (N=179). 116 known age-related sites in children were confirmed. 83 novel CpGs were selected as predictors from all age-related loci by elastic net regression and they could accurately predict the chronological age of the pediatric population, with a correlation of 0.99 and the error of 0.23 years in the training dataset (N=90). The predictive accuracy in the testing dataset (N=89) was high (correlation=0.93, error=0.62 years). Among the 83 predictors, 49 sites were novel probes not existing on the Illumina 450K BeadChip. The top two predictors of age were on the and genes, which are associated with diabetes and cancer, respectively. Our results suggest that the chronological age can be accurately predicted among children and adolescents aged 6-17 years by 83 newly identified CpG sites.
DNA甲基化年龄是人类衰老过程的良好反映，已被用于预测成年人和新生儿的实际年龄。然而，针对儿童和青少年的预测模型却并不存在。在本研究中，我们旨在通过使用180名中国双胞胎个体的年龄特异性DNA甲基化模式，生成一个针对6至17岁儿童和青少年实际年龄的预测模型。我们从全表观基因组关联分析（N = 179）中鉴定出6350个与年龄相关的CpG位点。确认了儿童中116个已知的与年龄相关的位点。通过弹性网络回归从所有与年龄相关的位点中选择了83个新的CpG位点作为预测因子，它们能够准确预测儿科人群的实际年龄，在训练数据集（N = 90）中的相关性为0.99，误差为0.23岁。测试数据集（N = 89）中的预测准确性很高（相关性 = 0.93，误差 = 0.62岁）。在这83个预测因子中，有49个位点是Illumina 450K BeadChip上不存在的新型探针。年龄的前两个预测因子分别位于与糖尿病和癌症相关的基因上。我们的结果表明，通过83个新鉴定的CpG位点可以准确预测6至17岁儿童和青少年的实际年龄。
