Literature DB >> 34245337

DNA methylation of decedent blood samples to estimate the chronological age of human remains.

Yessenia Anaya1, Patrick Yew1, Katherine A Roberts2,3, W Reef Hardy4.   

Abstract

Chronological age estimation may offer valuable investigative leads in human identification cases. Bisulfite pyrosequencing analysis of single CpG sites on five genes (KLF14, ELOVL2, C1orf132, TRIM59, and FHL2) was performed on 264 postmortem blood samples from individuals aged 3 months to 93 years. The goals were to develop age prediction models based on the correlation between the methylation profile and chronological age and to assess the accuracy of the prediction. Linear regression between methylation levels and age at each CpG site revealed that the five markers show a statistically significant correlation with age. The methylation data from a training set of 160 postmortem blood samples were used to develop an age prediction model with a correlation coefficient of 0.65, explaining 73.1% of age variation, with a mean absolute deviation from the chronological age of 7.60 years. The accuracy of the model was evaluated with a test set of 72 samples producing a mean absolute deviation of 7.42 years. The training and test sets were also categorized by specific age groups to assess accuracy and deviation from chronological age. The data for both sets revealed a lower prediction potential as an individual increases in age, particularly for the age categories above 50 years.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Chronological age; Decedent blood samples; Epigenetics; Estimated age

Mesh:

Substances:

Year:  2021        PMID: 34245337     DOI: 10.1007/s00414-021-02650-8

Source DB:  PubMed          Journal:  Int J Legal Med        ISSN: 0937-9827            Impact factor:   2.686


  44 in total

Review 1.  Impact of aging on DNA methylation.

Authors:  Bruce Richardson
Journal:  Ageing Res Rev       Date:  2003-07       Impact factor: 10.895

2.  Cross-sectional and longitudinal changes in DNA methylation with age: an epigenome-wide analysis revealing over 60 novel age-associated CpG sites.

Authors:  Ines Florath; Katja Butterbach; Heiko Müller; Melanie Bewerunge-Hudler; Hermann Brenner
Journal:  Hum Mol Genet       Date:  2013-10-26       Impact factor: 6.150

3.  Methylation of ELOVL2 gene as a new epigenetic marker of age.

Authors:  Paolo Garagnani; Maria G Bacalini; Chiara Pirazzini; Davide Gori; Cristina Giuliani; Daniela Mari; Anna M Di Blasio; Davide Gentilini; Giovanni Vitale; Sebastiano Collino; Serge Rezzi; Gastone Castellani; Miriam Capri; Stefano Salvioli; Claudio Franceschi
Journal:  Aging Cell       Date:  2012-10-14       Impact factor: 9.304

4.  DNA methylation profiling for a confirmatory test for blood, saliva, semen, vaginal fluid and menstrual blood.

Authors:  Hwan Young Lee; Sang-Eun Jung; Eun Hee Lee; Woo Ick Yang; Kyoung-Jin Shin
Journal:  Forensic Sci Int Genet       Date:  2016-06-14       Impact factor: 4.882

Review 5.  Recent progress, methods and perspectives in forensic epigenetics.

Authors:  Athina Vidaki; Manfred Kayser
Journal:  Forensic Sci Int Genet       Date:  2018-08-17       Impact factor: 4.882

6.  Genome-wide methylation profiles reveal quantitative views of human aging rates.

Authors:  Gregory Hannum; Justin Guinney; Ling Zhao; Li Zhang; Guy Hughes; SriniVas Sadda; Brandy Klotzle; Marina Bibikova; Jian-Bing Fan; Yuan Gao; Rob Deconde; Menzies Chen; Indika Rajapakse; Stephen Friend; Trey Ideker; Kang Zhang
Journal:  Mol Cell       Date:  2012-11-21       Impact factor: 17.970

7.  Epigenetic predictor of age.

Authors:  Sven Bocklandt; Wen Lin; Mary E Sehl; Francisco J Sánchez; Janet S Sinsheimer; Steve Horvath; Eric Vilain
Journal:  PLoS One       Date:  2011-06-22       Impact factor: 3.240

Review 8.  The role of DNA methylation in epigenetics of aging.

Authors:  Archana Unnikrishnan; Willard M Freeman; Jordan Jackson; Jonathan D Wren; Hunter Porter; Arlan Richardson
Journal:  Pharmacol Ther       Date:  2018-11-09       Impact factor: 12.310

9.  Aging and environmental exposures alter tissue-specific DNA methylation dependent upon CpG island context.

Authors:  Brock C Christensen; E Andres Houseman; Carmen J Marsit; Shichun Zheng; Margaret R Wrensch; Joseph L Wiemels; Heather H Nelson; Margaret R Karagas; James F Padbury; Raphael Bueno; David J Sugarbaker; Ru-Fang Yeh; John K Wiencke; Karl T Kelsey
Journal:  PLoS Genet       Date:  2009-08-14       Impact factor: 5.917

10.  Aging of blood can be tracked by DNA methylation changes at just three CpG sites.

Authors:  Carola Ingrid Weidner; Qiong Lin; Carmen Maike Koch; Lewin Eisele; Fabian Beier; Patrick Ziegler; Dirk Olaf Bauerschlag; Karl-Heinz Jöckel; Raimund Erbel; Thomas Walter Mühleisen; Martin Zenke; Tim Henrik Brümmendorf; Wolfgang Wagner
Journal:  Genome Biol       Date:  2014-02-03       Impact factor: 13.583

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  1 in total

1.  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
  1 in total

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