Abstract
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 PRKCB and REG4 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.
Highlights
Epigenetics refers to the molecular mechanisms regulating gene expression without changing the DNA sequence [1]
6,350 sites of them (0.78%) were significantly related with chronological age in the epigenome-wide association study (EWAS) (FDR < 0.05, Figure 1) and they were selected for the subsequent prediction modeling. 116 out of the 6,350 CpG sites were confirmed given the public accessible dataset "GSE27097"
It can be downloaded from the PubMed, which have focused on the age-related DNA methylation sites by Illumina 27K Beadchip among children aged 3 to 17 years old
Summary
Epigenetics refers to the molecular mechanisms regulating gene expression without changing the DNA sequence [1]. The mostly studied epigenetic marker is DNA methylation, the presence of methyl groups at CpG dinucleotides [2]. Previous evidence suggested that global levels of DNA methylation increased over the first few years of life [3] and decreased in late adulthood [4, 5], suggesting that epigenetic modifications might play a vital role in the human’s aging process [6, 7]. A growing body of evidence confirmed the presence of age-related epigenome-wide DNA methylation patterns [8, 9]. It has been shown that the methylation levels at specific age-related CpG sites represent stable and reproducible biomarkers of age. The age prediction model using a group of age-specific CpG sites has been widely used in adults and newborns for age prediction [14, 17]. The age prediction model for children and adolescents using DNA methylation biomarkers was scarce [9]
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