Abstract
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.
Highlights
The epigenetic landscape provides new perspectives for using as biomarkers with the development of experimental technologies mediated by high-throughput sequencing and omics data mining[10,11]
1,476 CpG sites were positively associated with age and 1,489 markers were negatively associated with age (Fig. 1a)
The results showed that using the same CpG sites as in multivariate linear regression analysis, the MADs were reduced to 4.1 years for multivariate nonlinear regression (Fig. 3b), 3.9 years for back propagation (BP) neural network (Fig. 3c), and 2 years for support vector recognition (SVR) (Fig. 3d), respectively
Summary
The epigenetic landscape provides new perspectives for using as biomarkers with the development of experimental technologies mediated by high-throughput sequencing and omics data mining[10,11] One of these epigenetic modifications, DNA methylation, has been shown to closely correlate with age, that is, the global level of methylated genomic DNA decreases as a person ages[12,13]. Based on comparative analyses integrating different loci and models, we established an age prediction strategy based on six CpG loci and SVR model with an average predictive accuracy at 4.7 years This strategy has a potential value in both forensic practice and other related studies for Chinese population, but for other populations as well
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