Exploring legal age estimation using DNA methylation

Minors (subjects under the legal age, established at this study at 18 years) benefit from a series of legal rights created to protect them and guarantee their welfare. However, throughout the world there are many minors who have no way to prove they are underaged, leading to a great interest in pred...

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Published in:Forensic science international : genetics 2025-01, Vol.74, p.103142, Article 103142
Main Authors: Boullón-Cassau, M., Ambroa-Conde, A., Casares de Cal, M.A., Gómez-Tato, A., Mosquera-Miguel, A., Ruiz-Ramírez, J., Cabrejas-Olalla, A., González-Bao, J., Casanova-Adán, L., de la Puente, M., Rodríguez, A., Phillips, C., Lareu, MV, Freire-Aradas, A.
Format: Article
Language:English
Subjects:
DNA methylation
Horvath’s skin & blood clock
Legal age
Quantile regression
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Summary:Minors (subjects under the legal age, established at this study at 18 years) benefit from a series of legal rights created to protect them and guarantee their welfare. However, throughout the world there are many minors who have no way to prove they are underaged, leading to a great interest in predicting legal age with the highest possible accuracy. Current methods, mainly involving X-ray analysis, are highly invasive, so new methods to predict legal age are being studied, such as DNA methylation. To further such studies, we created two age prediction models based on five epigenetic markers: cg21572722 (ELOVL2), cg02228185 (ASPA), cg06639320 (FHL2), cg19283806 (CCDC102B) and cg07082267 (no associated gene), that were analysed in blood samples to determine possible limitations regarding DNA methylation as an effective tool for legal age estimation. A wide age range prediction model was created using a broad set of samples (14–94 years) yielding a mean absolute error (MAE) of ±4.32 years. A second model, the constrained age prediction model, was created using a reduced range of samples (14–25 years) yielding an MAE of ±1.54 years. Both models, in addition to Horvath’s Skin & Blood epigenetic clock, were evaluated using a test set comprising 732 pairs of 18-year-old twins (N=426 monozygotic (MZ) and N=306 dizygotic (DZ) pairs), representing a relevant age of study. Through analysis of the two former age prediction models, we found that constraining the age of the samples forming the training set around the desired age of study significantly reduced the prediction error (from MAE: ±4.07 and ±4.27 years for MZ and DZ twins, respectively; to ±1.31 and ±1.3 years). However, despite low prediction errors, DNA methylation models are still prone to classify same-aged individuals in different categories (minors or adults), despite each sample belonging to the same twin pair. Additional evaluation of Horvath’s Skin & Blood model (391 CpGs) led to similar results in terms of age prediction errors than if using only five epigenetic markers (MAE: ±1.87 and ±1.99 years for MZ and DZ twins, respectively). •A blood wide age range prediction model was built using 5 CpGs obtaining MAE: ±4.07 and ±4.27 years for a test set of 18-year-old MZ and DZ twins, respectively.•A blood constrained age range prediction model was built using 5 CpGs obtaining MAE: ±1.31 and ±1.3 years for a test set of 18-year-old MZ and DZ twins, respectively.•The analysis of 391 CpGs in front of 5 epige
ISSN:1872-4973
1878-0326
1878-0326
DOI:10.1016/j.fsigen.2024.103142