Literature DB >> 27497326

Forensic age prediction for dead or living samples by use of methylation-sensitive high resolution melting.

Yuya Hamano1, Sho Manabe2, Chie Morimoto2, Shuntaro Fujimoto2, Munetaka Ozeki2, Keiji Tamaki3.   

Abstract

Age prediction with epigenetic information is now edging closer to practical use in forensic community. Many age-related CpG (AR-CpG) sites have proven useful in predicting age in pyrosequencing or DNA chip analyses. In this study, a wide range methylation status in the ELOVL2 and FHL2 promoter regions were detected with methylation-sensitive high resolution melting (MS-HRM) in a labor-, time-, and cost-effective manner. Non-linear-distributions of methylation status and chronological age were newly fitted to the logistic curve. Notably, these distributions were revealed to be similar in 22 living blood samples and 52 dead blood samples. Therefore, the difference of methylation status between living and dead samples suggested to be ignorable by MS-HRM. Additionally, the information from ELOVL2 and FHL2 were integrated into a logistic curve fitting model to develop a final predictive model through the multivariate linear regression of logit-linked methylation rates and chronological age with adjusted R(2)=0.83. Mean absolute deviation (MAD) was 7.44 for 74 training set and 7.71 for 30 additional independent test set, indicating that the final predicting model is accurate. This suggests that our MS-HRM-based method has great potential in predicting actual forensic age.
Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Age prediction; DNA methylation; Forensic science; MS-HRM

Mesh:

Year:  2016        PMID: 27497326     DOI: 10.1016/j.legalmed.2016.05.001

Source DB:  PubMed          Journal:  Leg Med (Tokyo)        ISSN: 1344-6223            Impact factor:   1.376


  11 in total

1.  DNA methylation levels and telomere length in human teeth: usefulness for age estimation.

Authors:  Ana Belén Márquez-Ruiz; Lucas González-Herrera; Juan de Dios Luna; Aurora Valenzuela
Journal:  Int J Legal Med       Date:  2020-01-02       Impact factor: 2.686

2.  Predicting Chronological Age from DNA Methylation Data: A Machine Learning Approach for Small Datasets and Limited Predictors.

Authors:  Anastasia Aliferi; David Ballard
Journal:  Methods Mol Biol       Date:  2022

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

Authors:  Yuya Hamano; Sho Manabe; Chie Morimoto; Shuntaro Fujimoto; Keiji Tamaki
Journal:  Sci Rep       Date:  2017-09-05       Impact factor: 4.379

4.  From forensic epigenetics to forensic epigenomics: broadening DNA investigative intelligence.

Authors:  Athina Vidaki; Manfred Kayser
Journal:  Genome Biol       Date:  2017-12-21       Impact factor: 13.583

5.  DNA methylation-based forensic age prediction using artificial neural networks and next generation sequencing.

Authors:  Athina Vidaki; David Ballard; Anastasia Aliferi; Thomas H Miller; Leon P Barron; Denise Syndercombe Court
Journal:  Forensic Sci Int Genet       Date:  2017-02-28       Impact factor: 4.882

6.  Chronological Age Prediction: Developmental Evaluation of DNA Methylation-Based Machine Learning Models.

Authors:  Haoliang Fan; Qiqian Xie; Zheng Zhang; Junhao Wang; Xuncai Chen; Pingming Qiu
Journal:  Front Bioeng Biotechnol       Date:  2022-01-24

7.  Age estimation using methylation-sensitive high-resolution melting (MS-HRM) in both healthy felines and those with chronic kidney disease.

Authors:  Huiyuan Qi; Kodzue Kinoshita; Takashi Mori; Kaori Matsumoto; Yukiko Matsui; Miho Inoue-Murayama
Journal:  Sci Rep       Date:  2021-10-07       Impact factor: 4.379

Review 8.  How (Epi)Genetic Regulation of the LIM-Domain Protein FHL2 Impacts Multifactorial Disease.

Authors:  Jayron J Habibe; Maria P Clemente-Olivo; Carlie J de Vries
Journal:  Cells       Date:  2021-10-01       Impact factor: 6.600

Review 9.  The use of DNA methylation clock in aging research.

Authors:  Xi He; Jiaojiao Liu; Bo Liu; Jingshan Shi
Journal:  Exp Biol Med (Maywood)       Date:  2020-11-11

10.  A Blood-Bone-Tooth Model for Age Prediction in Forensic Contexts.

Authors:  Helena Correia Dias; Licínio Manco; Francisco Corte Real; Eugénia Cunha
Journal:  Biology (Basel)       Date:  2021-12-10
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