Application of droplet digital PCR method for DNA methylation-based age prediction from saliva
- Authors
- Lee, Min Ho; Hwang, Jung Hee; Seong, Ki Min; Ahn, Jeong Jin; Kim, Seung Jun; Hwang, Seung Yong; Lim, Si-Keun
- Issue Date
- Feb-2022
- Publisher
- Elsevier BV
- Keywords
- Droplet Digital PCR; DNA methylation; Age prediction; Saliva; Forensic science
- Citation
- Legal Medicine, v.54, pp.1 - 6
- Indexed
- SCIE
SCOPUS
- Journal Title
- Legal Medicine
- Volume
- 54
- Start Page
- 1
- End Page
- 6
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/107999
- DOI
- 10.1016/j.legalmed.2021.101992
- ISSN
- 1344-6223
- Abstract
- The recent studies reported that DNA methylation markers show changes with age, and expected that the DNA methylation markers can be effectively used for estimation of age in forensic genetics. In this study, we applied droplet digital PCR (ddPCR) method to investigate the DNA methylation pattern in the CpG sites, and we constructed an age prediction model based on the ddPCR method. The ddPCR is capable of highly sensitive quantitation of nucleic acid and detection of sequence variations in gene by separating the sample into large number of partitions and clonally amplifying nucleic acids in each partition. We extracted DNA from saliva samples collected from several age groups. The DNA was bisulfite converted and subjected to ddPCR using specifically designed primers and probes. The methylation ratio of each sample was calculated and correlation between the methylation ratio and the chronological age was analyzed. In the results, methylated DNA ratio at the 4 CpG sites (cg14361627, cg14361627, cg08928145 and cg07547549) showed strong correlation with chronological age. Percent-methylation values at 4 CpG markers and chronological ages of the 76 individuals were analyzed by multiple regression analysis, and we constructed an age prediction model. We observed a strong correlation (Spearman's rho = 0.922) between predicted and chronological ages of 76 individuals with a MAD from chronological age of 3.3 years. Collectively, the result in this study showed the potential applicability of ddPCR to predict age from saliva.
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