This study investigates the epigenetic predictors of age by analyzing DNA methylation patterns in saliva samples from 34 male identical twin pairs aged 21 to 55 years. The researchers identified 88 CpG sites near 80 genes that are significantly correlated with age. These sites were validated in additional samples of unrelated males and females, and the methylation levels of three genes (EDARADD, TOM1L1, and NPTX2) were found to be linearly correlated with age over a five-decade range. A regression model using methylation data from these three genes explained 73% of the variance in age and predicted individual ages with an average accuracy of 5.2 years. This model could have applications in forensic science and medical screening to estimate age and predict age-related diseases based on epigenetic biomarkers.This study investigates the epigenetic predictors of age by analyzing DNA methylation patterns in saliva samples from 34 male identical twin pairs aged 21 to 55 years. The researchers identified 88 CpG sites near 80 genes that are significantly correlated with age. These sites were validated in additional samples of unrelated males and females, and the methylation levels of three genes (EDARADD, TOM1L1, and NPTX2) were found to be linearly correlated with age over a five-decade range. A regression model using methylation data from these three genes explained 73% of the variance in age and predicted individual ages with an average accuracy of 5.2 years. This model could have applications in forensic science and medical screening to estimate age and predict age-related diseases based on epigenetic biomarkers.