Literature DB >> 24727429

Isolation and identification of age-related DNA methylation markers for forensic age-prediction.

Shao Hua Yi1, Long Chang Xu1, Kun Mei1, Rong Zhi Yang1, Dai Xin Huang2.   

Abstract

Age-prediction is an important part of forensic science. There is no available method of individual age-prediction for general forensic biological samples at crime scenes. Accumulating evidence indicates that aging resembles a developmentally regulated process tightly controlled by specific age-associated methylation exists in human genome. This study isolated and identified eight gene fragments in which the degree of cytosine methylation is significantly correlated with age in blood of 40 donors. Furthermore, we validated two CpG sites of each gene fragment and replicated our results in a general population sample of 40 males and 25 females with a wide age-range (11-72 years). The methylation of these fragments is linear with age over a range of six decades (Fragment P1 (r=-0.64), P2 (r=-0.58), P3 (r=-0.79), R1 (r=0.82), R2 (r=0.63), R3 (r=0.59), R4 (r=0.63) and R5 (r=0.62)). Using average methylation of two CpG sites from each fragment, we built a regression model that explained 95% of the variance in age and is able to predict the age of an individual with great accuracy (R(2)=0.918). The predicted values are highly correlated with the observed age in the sample (r=0.91). This study implicates that DNA methylation will be an available biological marker of age-prediction. Furthermore, measurement of relevant sites in the genome could be a tool in routine forensic screening to predict age of biological samples.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Age; Correlation, Prediction; DNA methylation; Forensic marker

Mesh:

Year:  2014        PMID: 24727429     DOI: 10.1016/j.fsigen.2014.03.006

Source DB:  PubMed          Journal:  Forensic Sci Int Genet        ISSN: 1872-4973            Impact factor:   4.882


  13 in total

1.  Age-related DNA methylation changes for forensic age-prediction.

Authors:  Shao Hua Yi; Yun Shu Jia; Kun Mei; Rong Zhi Yang; Dai Xin Huang
Journal:  Int J Legal Med       Date:  2014-11-16       Impact factor: 2.686

Review 2.  DNA methylation-based variation between human populations.

Authors:  Farzeen Kader; Meenu Ghai
Journal:  Mol Genet Genomics       Date:  2016-11-04       Impact factor: 3.291

3.  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

4.  From stem cells to the law courts: DNA methylation, the forensic epigenome and the possibility of a biosocial archive.

Authors:  Caroline L Relton; Fernando Pires Hartwig; George Davey Smith
Journal:  Int J Epidemiol       Date:  2015-08       Impact factor: 7.196

5.  An epigenetic clock for gestational age at birth based on blood methylation data.

Authors:  Anna K Knight; Jeffrey M Craig; Christiane Theda; Marie Bækvad-Hansen; Jonas Bybjerg-Grauholm; Christine S Hansen; Mads V Hollegaard; David M Hougaard; Preben B Mortensen; Shantel M Weinsheimer; Thomas M Werge; Patricia A Brennan; Joseph F Cubells; D Jeffrey Newport; Zachary N Stowe; Jeanie L Y Cheong; Philippa Dalach; Lex W Doyle; Yuk J Loke; Andrea A Baccarelli; Allan C Just; Robert O Wright; Mara M Téllez-Rojo; Katherine Svensson; Letizia Trevisi; Elizabeth M Kennedy; Elisabeth B Binder; Stella Iurato; Darina Czamara; Katri Räikkönen; Jari M T Lahti; Anu-Katriina Pesonen; Eero Kajantie; Pia M Villa; Hannele Laivuori; Esa Hämäläinen; Hea Jin Park; Lynn B Bailey; Sasha E Parets; Varun Kilaru; Ramkumar Menon; Steve Horvath; Nicole R Bush; Kaja Z LeWinn; Frances A Tylavsky; Karen N Conneely; Alicia K Smith
Journal:  Genome Biol       Date:  2016-10-07       Impact factor: 13.583

6.  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

7.  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

8.  Quantitative comparison of DNA methylation assays for biomarker development and clinical applications.

Authors: 
Journal:  Nat Biotechnol       Date:  2016-06-27       Impact factor: 54.908

9.  Quantification of global mitochondrial DNA methylation levels and inverse correlation with age at two CpG sites.

Authors:  Shakhawan K Mawlood; Lynn Dennany; Nigel Watson; John Dempster; Benjamin S Pickard
Journal:  Aging (Albany NY)       Date:  2016-04       Impact factor: 5.682

10.  A novel strategy for forensic age prediction by DNA methylation and support vector regression model.

Authors:  Cheng Xu; Hongzhu Qu; Guangyu Wang; Bingbing Xie; Yi Shi; Yaran Yang; Zhao Zhao; Lan Hu; Xiangdong Fang; Jiangwei Yan; Lei Feng
Journal:  Sci Rep       Date:  2015-12-04       Impact factor: 4.379

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