Age-related DNA methylation analysis for forensic age estimation using post-mortem blood samples from Japanese individuals.
DNA methylation
Forensic age estimation
Forensic epigenetics
Japanese individuals
Next-generation sequencing
Journal
Legal medicine (Tokyo, Japan)
ISSN: 1873-4162
Titre abrégé: Leg Med (Tokyo)
Pays: Ireland
ID NLM: 100889186
Informations de publication
Date de publication:
Nov 2021
Nov 2021
Historique:
received:
14
03
2021
revised:
28
05
2021
accepted:
31
05
2021
pubmed:
15
6
2021
medline:
26
11
2021
entrez:
14
6
2021
Statut:
ppublish
Résumé
As one of external visible characteristics (EVCs) in forensic phenotyping, age estimation is essential to providing additional information about a sample donor. With the development of epigenetics, age-related DNA methylation may be used as a reliable predictor of age estimation. With the aim of building a feasible age estimation model for Japanese individuals, 53 CpG sites distributed between 11 candidate genes were selected from previous studies. The DNA methylation level of each target CpG site was identified and measured on a massive parallel platform (synthesis by sequencing, Illumina, California, United States) from 60 forensic blood samples during the initial training phase. Multiple linear regression and quantile regression analyses were later performed to build linear and quantile age estimation models, respectively. Four CpG sites on four genes- ASPA, ELOVL2, ITGA2B, and PDE4C -, were found to be highly correlated with chronological age in DNA samples from Japanese individuals (|R| > 0.75). Subsequently, an independent validation dataset (n = 30) was used to verify and evaluate the performance of the two models. Comparison of mean absolute deviation (MAD) with other indicators showed that both models provide accurate age predictions (MAD: linear = 6.493 years; quantile = 6.243 years). The quantile model, however, can provide the changeable prediction intervals that grow wider with increasing age, and this tendency is consistent with the natural aging process in humans. Hence, the quantile model is recommended in this study.
Identifiants
pubmed: 34126371
pii: S1344-6223(21)00081-X
doi: 10.1016/j.legalmed.2021.101917
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
101917Informations de copyright
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