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Forensic age prediction for saliva samples using methylation-sensitive high resolution melting: exploratory application for cigarette butts

There is high demand for forensic age prediction in actual crime investigations. In this study, a novel age prediction model for saliva samples using methylation-sensitive high resolution melting (MS-HRM) was developed. The methylation profiles of ELOVL2 and EDARADD showed high correlations with age...

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Autores principales: Hamano, Yuya, Manabe, Sho, Morimoto, Chie, Fujimoto, Shuntaro, Tamaki, Keiji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5585169/
https://www.ncbi.nlm.nih.gov/pubmed/28874809
http://dx.doi.org/10.1038/s41598-017-10752-w
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author Hamano, Yuya
Manabe, Sho
Morimoto, Chie
Fujimoto, Shuntaro
Tamaki, Keiji
author_facet Hamano, Yuya
Manabe, Sho
Morimoto, Chie
Fujimoto, Shuntaro
Tamaki, Keiji
author_sort Hamano, Yuya
collection PubMed
description There is high demand for forensic age prediction in actual crime investigations. In this study, a novel age prediction model for saliva samples using methylation-sensitive high resolution melting (MS-HRM) was developed. The methylation profiles of ELOVL2 and EDARADD showed high correlations with age and were used to predict age with support vector regression. ELOVL2 was first reported as an age predictive marker for saliva samples. The prediction model showed high accuracy with a mean absolute deviation (MAD) from chronological age of 5.96 years among 197 training samples. The model was further validated with an additional 50 test samples (MAD = 6.25). In addition, the age prediction model was applied to saliva extracted from seven cigarette butts, as in an actual crime scene. The MAD (7.65 years) for these samples was slightly higher than that of intact saliva samples. A smoking habit or the ingredients of cigarettes themselves did not significantly affect the prediction model and could be ignored. MS-HRM provides a quick (2 hours) and cost-effective (95% decreased compared to that of DNA chips) method of analysis. Thus, this study may provide a novel strategy for predicting the age of a person of interest in actual crime scene investigations.
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spelling pubmed-55851692017-09-06 Forensic age prediction for saliva samples using methylation-sensitive high resolution melting: exploratory application for cigarette butts Hamano, Yuya Manabe, Sho Morimoto, Chie Fujimoto, Shuntaro Tamaki, Keiji Sci Rep Article There is high demand for forensic age prediction in actual crime investigations. In this study, a novel age prediction model for saliva samples using methylation-sensitive high resolution melting (MS-HRM) was developed. The methylation profiles of ELOVL2 and EDARADD showed high correlations with age and were used to predict age with support vector regression. ELOVL2 was first reported as an age predictive marker for saliva samples. The prediction model showed high accuracy with a mean absolute deviation (MAD) from chronological age of 5.96 years among 197 training samples. The model was further validated with an additional 50 test samples (MAD = 6.25). In addition, the age prediction model was applied to saliva extracted from seven cigarette butts, as in an actual crime scene. The MAD (7.65 years) for these samples was slightly higher than that of intact saliva samples. A smoking habit or the ingredients of cigarettes themselves did not significantly affect the prediction model and could be ignored. MS-HRM provides a quick (2 hours) and cost-effective (95% decreased compared to that of DNA chips) method of analysis. Thus, this study may provide a novel strategy for predicting the age of a person of interest in actual crime scene investigations. Nature Publishing Group UK 2017-09-05 /pmc/articles/PMC5585169/ /pubmed/28874809 http://dx.doi.org/10.1038/s41598-017-10752-w Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Hamano, Yuya
Manabe, Sho
Morimoto, Chie
Fujimoto, Shuntaro
Tamaki, Keiji
Forensic age prediction for saliva samples using methylation-sensitive high resolution melting: exploratory application for cigarette butts
title Forensic age prediction for saliva samples using methylation-sensitive high resolution melting: exploratory application for cigarette butts
title_full Forensic age prediction for saliva samples using methylation-sensitive high resolution melting: exploratory application for cigarette butts
title_fullStr Forensic age prediction for saliva samples using methylation-sensitive high resolution melting: exploratory application for cigarette butts
title_full_unstemmed Forensic age prediction for saliva samples using methylation-sensitive high resolution melting: exploratory application for cigarette butts
title_short Forensic age prediction for saliva samples using methylation-sensitive high resolution melting: exploratory application for cigarette butts
title_sort forensic age prediction for saliva samples using methylation-sensitive high resolution melting: exploratory application for cigarette butts
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5585169/
https://www.ncbi.nlm.nih.gov/pubmed/28874809
http://dx.doi.org/10.1038/s41598-017-10752-w
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