AUTHOR=Zhu Bowen , Li Dean , Han Guojing , Yao Xue , Gu Hongqin , Liu Tao , Liu Linghua , Dai Jie , Liu Isabella Zhaotong , Liang Yanlin , Zheng Jian , Sun Zheming , Lin He , Liu Nan , Yu Haidong , Shi Meifang , Shen Gaofang , Hu Zhaohui , Qu Lefeng 

TITLE=Multiplexing and massive parallel sequencing of targeted DNA methylation to predict chronological age

JOURNAL=Frontiers in Aging

VOLUME=Volume 6 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/aging/articles/10.3389/fragi.2025.1467639

DOI=10.3389/fragi.2025.1467639

ISSN=2673-6217

ABSTRACT=Estimation of chronological age is particularly informative in forensic contexts. Assessment of DNA methylation status allows for the prediction of age, though the accuracy may vary across models. In this study, we started with a carefully designed discovery cohort with more elderly subjects than other age categories, to diminish the effect of epigenetic drifting. We applied multiplexing and massive parallel sequencing of targeted DNA methylation, which let us to construct a model comprising 25 CpG sites with substantially improved accuracy (MAE = 2.279, R = 0.920). This model is further validated by an independent cohort (MAE = 2.204, 82.7% success (±5 years)). Remarkably, in a multi-center test using trace blood samples from forensic caseworks, the correct predictions (±5 years) are 91.7%. The nature of our analytical pipeline can easily be scaled up with low cost. Taken together, we propose a new age-prediction model featuring accuracy, sensitivity, high-throughput, and low cost. This model can be readily applied in both classic and newly emergent forensic contexts that require age estimation.