Literature DB >> 34806083

Epigenetic Forensics for Suspect Identification and Age Prediction.

Jonathan Foox1, Daniela Bezdan1, Priyanka Vijay2, Kylie Getz1, Kamolwat Ratanachai1, Justin W Davis3, Keith Booher4, Xiaojing Yang4, Cem Meydan1, Christopher E Mason1,5,6.   

Abstract

Background: Genetic testing at crime scenes is an instrumental molecular technique to identify or eliminate suspects, as well as to overturn wrongful convictions. Yet, genotyping alone cannot reveal the age of a sample, which could help advance the utility of crime scene samples for suspect identification. The distribution of cytosine methylation within a DNA sample can be leveraged to determine the epigenetic age of someone's blood. Methodology: We sought to demonstrate the ability of DNA methylation markers to accurately discern the age of blood spots from an actual crime scene, a "mock" crime scene, and also from a tube of blood stored in ethylenediaminetetraacetic acid for >20 years. This was achieved by quantifying methylation within known age-associated genetic loci across each DNA sample. We observed a strong linear coefficient (0.91) and high overall correlation (R 2 = 0.963) between the known age of a sample and the predicted age.
Conclusion: We show that novel methods for targeted methylation and low-input whole-genome bisulfite sequencing can enable a novel and improved forensic profile of a crime scene that discerns not only who was present at the crime, but also their age. Finally, we use this model to discern the age and provenance of a blood sample that was used in a criminal investigation. Copyright 2021, Mary Ann Liebert, Inc., publishers.

Entities:  

Keywords:  age prediction; bisulfite sequencing; blood; crime scene; epigenetics; low input sequencing

Year:  2021        PMID: 34806083      PMCID: PMC8596498          DOI: 10.1089/forensic.2021.0005

Source DB:  PubMed          Journal:  Forensic Genom        ISSN: 2690-8956


  13 in total

Review 1.  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

2.  Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications.

Authors:  Felix Krueger; Simon R Andrews
Journal:  Bioinformatics       Date:  2011-04-14       Impact factor: 6.937

3.  DNA methylation-based measures of biological age: meta-analysis predicting time to death.

Authors:  Brian H Chen; Riccardo E Marioni; Elena Colicino; Marjolein J Peters; Cavin K Ward-Caviness; Pei-Chien Tsai; Nicholas S Roetker; Allan C Just; Ellen W Demerath; Weihua Guan; Jan Bressler; Myriam Fornage; Stephanie Studenski; Amy R Vandiver; Ann Zenobia Moore; Toshiko Tanaka; Douglas P Kiel; Liming Liang; Pantel Vokonas; Joel Schwartz; Kathryn L Lunetta; Joanne M Murabito; Stefania Bandinelli; Dena G Hernandez; David Melzer; Michael Nalls; Luke C Pilling; Timothy R Price; Andrew B Singleton; Christian Gieger; Rolf Holle; Anja Kretschmer; Florian Kronenberg; Sonja Kunze; Jakob Linseisen; Christine Meisinger; Wolfgang Rathmann; Melanie Waldenberger; Peter M Visscher; Sonia Shah; Naomi R Wray; Allan F McRae; Oscar H Franco; Albert Hofman; André G Uitterlinden; Devin Absher; Themistocles Assimes; Morgan E Levine; Ake T Lu; Philip S Tsao; Lifang Hou; JoAnn E Manson; Cara L Carty; Andrea Z LaCroix; Alexander P Reiner; Tim D Spector; Andrew P Feinberg; Daniel Levy; Andrea Baccarelli; Joyce van Meurs; Jordana T Bell; Annette Peters; Ian J Deary; James S Pankow; Luigi Ferrucci; Steve Horvath
Journal:  Aging (Albany NY)       Date:  2016-09-28       Impact factor: 5.682

4.  Huntington's disease accelerates epigenetic aging of human brain and disrupts DNA methylation levels.

Authors:  Steve Horvath; Peter Langfelder; Seung Kwak; Jeff Aaronson; Jim Rosinski; Thomas F Vogt; Marika Eszes; Richard L M Faull; Maurice A Curtis; Henry J Waldvogel; Oi-Wa Choi; Spencer Tung; Harry V Vinters; Giovanni Coppola; X William Yang
Journal:  Aging (Albany NY)       Date:  2016-07       Impact factor: 5.682

5.  Distinct evolution and dynamics of epigenetic and genetic heterogeneity in acute myeloid leukemia.

Authors:  Sheng Li; Francine E Garrett-Bakelman; Stephen S Chung; Mathijs A Sanders; Todd Hricik; Franck Rapaport; Jay Patel; Richard Dillon; Priyanka Vijay; Anna L Brown; Alexander E Perl; Joy Cannon; Lars Bullinger; Selina Luger; Michael Becker; Ian D Lewis; Luen Bik To; Ruud Delwel; Bob Löwenberg; Hartmut Döhner; Konstanze Döhner; Monica L Guzman; Duane C Hassane; Gail J Roboz; David Grimwade; Peter J M Valk; Richard J D'Andrea; Martin Carroll; Christopher Y Park; Donna Neuberg; Ross Levine; Ari M Melnick; Christopher E Mason
Journal:  Nat Med       Date:  2016-06-20       Impact factor: 53.440

6.  Age-related DNA methylation changes are tissue-specific with ELOVL2 promoter methylation as exception.

Authors:  Roderick C Slieker; Caroline L Relton; Tom R Gaunt; P Eline Slagboom; Bastiaan T Heijmans
Journal:  Epigenetics Chromatin       Date:  2018-05-30       Impact factor: 4.954

Review 7.  DNA methylation: an epigenetic mark of cellular memory.

Authors:  Mirang Kim; Joseph Costello
Journal:  Exp Mol Med       Date:  2017-04-28       Impact factor: 8.718

8.  methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles.

Authors:  Altuna Akalin; Matthias Kormaksson; Sheng Li; Francine E Garrett-Bakelman; Maria E Figueroa; Ari Melnick; Christopher E Mason
Journal:  Genome Biol       Date:  2012-10-03       Impact factor: 13.583

9.  DNA methylation age of human tissues and cell types.

Authors:  Steve Horvath
Journal:  Genome Biol       Date:  2013       Impact factor: 13.583

Review 10.  DNA methylation and healthy human aging.

Authors:  Meaghan J Jones; Sarah J Goodman; Michael S Kobor
Journal:  Aging Cell       Date:  2015-04-25       Impact factor: 9.304

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