ABSTRACT
Age estimation is crucial for reconstructing the biological profiles of deceased victims in the forensic field. DNA methylation, which varies in an age-dependent manner in specific genes, is a candidate biomarker for estimating chronological age. DNA methylation-based models for estimating age have been developed using various technologies such as pyrosequencing. We recently quantified the methylation levels of elongation of very long chain fatty acids protein 2 (ELOVL2) in teeth using real-time methylation-specific polymerase chain reaction (RT-MSP) to rapidly assess the methylation value of CpG sites within a CpG island. The methylation levels of ELOVL2 were moderately correlated with chronological age, suggesting the usefulness of RT-MSP for age estimation. In this study, we designed eight and five new primer sets for ELOVL2 and ectodysplasin A receptor-associated death domain (EDARADD), respectively, and selected the best primer set. The DNA methylation level was analyzed in 59 tooth samples using the selected primer set. The ELOVL2 methylation value was positively correlated with age (R2 = 0.50), whereas the EDARADD methylation value negatively correlated with age (R2 = 0.44). A multiple regression model combining ELOVL2 and EDARADD showed high accuracy [mean absolute error (MAE) = 6.69], which was verified using 40 test samples (MAE = 8.28). Additionally, the MAE of three age groups showed no significant difference. These results indicate that the multiple regression model based on the two genes is useful for accurate age estimation across the human lifespan.
