Top

Published in:

01-11-2021 | Epigenetics | Original Article

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

Authors: Yessenia Anaya, Patrick Yew, Katherine A. Roberts, W. Reef Hardy

Published in: International Journal of Legal Medicine | Issue 6/2021

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.

Available only for authorised users

Lee H, Jung S, Lee E, Yang W, Shin K (2016) DNA methylation profiling for a confirmatory test for blood, saliva, semen, vaginal fluid and menstrual blood. Forensic Sci Int Genet 24:75–82. https://doi.org/10.1016/j.fsigen.2016.06.007CrossRefPubMed

Vidaki A, Kayser M (2018) Recent progress, methods and perspectives in forensic epigenetics. Forensic Sci Int Genet 37:180–195. https://doi.org/10.1016/j.fsigen.2018.08.008CrossRefPubMed

Unnikrishnan A, Freeman WM, Jackson J, Wren JD, Porter H, Richardson A (2019) The role of DNA methylation in epigenetics of aging. Pharmacol Ther 195:172–185. https://doi.org/10.1016/j.pharmthera.2018.11.001CrossRefPubMed

Richardson B (2003) Impact of aging on DNA methylation. Ageing Res Rev 2(3):245–261. https://doi.org/10.1016/s1568-1637(03)00010-2CrossRefPubMed

Christensen BC, Houseman EA, Marsit CJ, Zheng S, Wrensch MR, Wiemels JL et al (2009) Aging and environmental exposures alter tissue-specific DNA methylation dependent upon CpG island context. PloS Genet 5(8):e1000602. https://doi.org/10.1371/journal.pgen.1000602CrossRefPubMedPubMedCentral

Koch CM, Wagner W (2011) Epigenetic-aging-signature to determine age in different tissues. Aging 23(10):1018–1027. https://doi.org/10.18632/aging.100395CrossRef

Garagnani P, Bacalini MG, Pirazzini C, Gori D, Giuliani C, Mari D et al (2012) Methylation of ELOVL2 gene as a new epigenetic marker of age. Aging Cell 11:1132–1134. https://doi.org/10.1111/acel.12005CrossRefPubMed

Hannum G, Guinney J, Zhao L, Zhang L, Hughes G, Sadda S et al (2013) Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol Cell 49:359–367. https://doi.org/10.1016/j.molcel.2012.10.016CrossRefPubMed

Weidner C, Lin Q, Koch C, Eisele L, Beier F, Ziegler P et al (2014) Aging of blood can be tracked by DNA methylation changes at just three CpG sites. Genome Biol 15(2):R24. https://doi.org/10.1186/gb-2014-15-2-r24CrossRefPubMedPubMedCentral

10.

Florath I, Butterbach K, Muller H, Bewerunge-Hudler M, Brenner H (2013) Cross-sectional and longitudinal changes in DNA methylation with age: an epigenome-wide analysis revealing over 60 novel age-associated CpG sites. Hum Mol Genet 23(5):1186–1201. https://doi.org/10.1093/hmg/ddt531CrossRefPubMedPubMedCentral

11.

Bocklandt S, Lin W, Sehl ME, Sánchez FJ, Sinsheimer JS, Horvath S et al (2011) Epigenetic predictor of age. PLoS One 6:e14821. https://doi.org/10.1371/journal.pone.0014821CrossRefPubMedPubMedCentral

12.

Eipel M, Mayer F, Arent T, Ferreira MR, Birkhofer C, Gerstenmaier U et al (2016) Epigenetic age predictions based on buccal swabs are more precise in combination with cell type-specific DNA methylation signatures. Aging 8:1034–1048. https://doi.org/10.18632/aging.100972CrossRefPubMedPubMedCentral

13.

Hong S, Jung S, Lee E, Shin K, Yang W, Lee H (2017) DNA methylation-based age prediction from saliva: high age predictability by a combination of 7 CpG markers. Forensic Sci Int Genet 29:118–125. https://doi.org/10.1016/j.fsigen.2017.04.006CrossRefPubMed

14.

Hernandez DG, Nalls MA, Gibbs JR, Arepalli S, van der Brug M, Chong S et al (2011) Distinct DNA methylation changes highly correlated with chronological age in the human brain. Hum Mol Genet 20(6):1164–1172. https://doi.org/10.1093/hmg/ddq561CrossRefPubMedPubMedCentral

15.

Horvath S, Zhang Y, Langfelder P, Kahn RS, Boks MP, van Eijk K et al (2012) Aging effects on DNA methylation modules in human brain and blood tissue. Genome Biol 13(10):R97. https://doi.org/10.1186/gb-2012-13-10-r97CrossRefPubMedPubMedCentral

16.

Day K, Waite LL, Thalacker-Mercer A, West A, Bamman MM, Brooks JD et al (2013) Differential DNA methylation with age displays both common and dynamic features across human tissues that are influenced by CpG landscape. Genome Biol 14:R102. https://doi.org/10.1186/gb-2013-14-9-r102CrossRefPubMedPubMedCentral

17.

Horvath S (2013) DNA methylation age of human tissues and cell types. Genome Biol 14(10):R115. https://doi.org/10.1186/gb-2013-14-10-r115CrossRefPubMedPubMedCentral

18.

Slieker R, Relton C, Gaunt SP, Heijmans B (2018) Age-related DNA methylation changes are tissue-specific with ELOVL2 promoter methylation as exception. Epigenetics Chromatin 11:25. https://doi.org/10.1186/s13072-018-0191-3CrossRefPubMedPubMedCentral

19.

Freire-Aradas A, Philips C, Lareu M (2017) Forensic individual age estimation with DNA: from initial approaches to methylation tests. Forensic Sci Rev 29(2):121–144PubMed

20.

Ronaghi M, Karamohamed S, Pettersson B, Uhlén M, Nyrén P (1996) Real-time DNA sequencing using detection of pyrophosphate release. Anal Biochem 242:84–89. https://doi.org/10.1006/abio.1996.0432CrossRefPubMed

21.

Colella S, Shen L, Baggerly KA, Issa PJJ, Krahe R (2003) Sensitive and quantitative universal Pyrosequencing^TM methylation analysis of CpG sites. Biotechniques 35(1):146–150. https://doi.org/10.2144/03351md01CrossRefPubMed

22.

Tost J, Gut IG (2007) DNA methylation analysis by pyrosequencing. Nat Protocols 2:2265–2275. https://doi.org/10.1038/nprot.2007.314CrossRefPubMed

23.

Delaney C, Garg SK, Yung R (2015) Analysis of DNA methylation by pyrosequencing. Methods Mol Biol 1343:249–264. https://doi.org/10.1007/978-1-4939-2963-4_19CrossRefPubMedPubMedCentral

24.

Zbieć-Piekarska R, Spólnicka M, Kupiec T, Parys-Proszek A, Makowska Ż, Pałeczka A et al (2015) Development of a forensically useful age prediction method based on DNA methylation analysis. Forensic Sci Int Genet 17:173–179. https://doi.org/10.1016/j.fsigen.2015.05.001CrossRefPubMed

25.

Cho S, Jung SE, Hong SR, Lee EH, Lee JH, Lee SD et al (2017) Independent validation of DNA-based approaches for age prediction in blood. Forensic Sci Int Genet 29:250–256. https://doi.org/10.1016/j.fsigen.2017.04.020CrossRefPubMed

26.

Bekaert B, Kamalandua A, Zapico SC, Van de Voorde W, Decorte R (2015) Improved age determination of blood and teeth samples using a selected set of DNA methylation markers. Epigenetics 10(10):922–930. https://doi.org/10.1080/15592294.2015.1080413CrossRefPubMedPubMedCentral

27.

Hamano Y, Manabe S, Morimoto C, Fujimoto S, Ozeki M, Tamaki K (2016) Forensic age prediction for dead or living samples by use of methylation-sensitive high resolution melting. Leg Med 21:5–10. https://doi.org/10.1016/j.legalmed.2016.05.001CrossRef

28.

Naue J, Hoefsloot H, Mook O, Rijlaarsdam-Hoekstra L, van der Zwalm M, Henneman P et al (2017) Chronological age prediction based on DNA methylation: massive parallel sequencing and random forest regression. Forensic Sci Int Genet 31:19–28. https://doi.org/10.1016/j.fsigen.2017.07.015CrossRefPubMed

29.

Correia Dias H, Cordeiro C, Corte Real F, Cunha E, Manco L (2019) Age estimation based on DNA methylation using blood samples from deceased individuals. J Forensic Sci 65(2):465–470. https://doi.org/10.1111/1556-4029.14185CrossRefPubMed

30.

Chan YH (2003) Biostatistics 104: correlational analysis. Singap Med J 44(12):614–619

31.

Zbieć-Piekarska R, Spólnicka M, Kupiec T, Makowska Ż, Spas A, Parys-Proszek A et al (2015) Examination of DNA methylation status of the ELOVL2 marker may be useful for human age prediction in forensic science. Forensic Sci Int Genet 14:161–167. https://doi.org/10.1016/j.fsigen.2014.10.002CrossRefPubMed

32.

Marioni RE, Shah S, McRae AF, Chen BH, Colicino E, Harris SE et al (2015) DNA methylation age of blood predicts all-cause mortality in later life. Genome Biol 16:25. https://doi.org/10.1186/s13059-015-0584-6CrossRefPubMedPubMedCentral

33.

Pavanello S, Campisi M, Tona F, Lin CD, Iliceto S (2019) Exploring epigenetic age in response to intensive relaxing training: a pilot study to slow down biological age. Int J Environ Res Public Health 16(17):3074. https://doi.org/10.3390/ijerph16173074CrossRefPubMedCentral

34.

Jovanovic T, Vance LA, Cross D, Knight AK, Kilaru V, Michopoulos V et al (2017) Exposure to violence accelerates epigenetic aging in children. Sci Rep 7(1):8962. https://doi.org/10.1038/s41598-017-09235-9CrossRefPubMedPubMedCentral

35.

Hughes A, Smart M, Gorrie-Stone T, Hannon E, Mill J, Bao Y et al (2018) Socioeconomic position and DNA methylation age acceleration across the life course. Am J Epidemiol 187:2346–2354. https://doi.org/10.1093/aje/kwy155CrossRefPubMedPubMedCentral

36.

Austin MK, Chen E, Ross KM, McEwen LM, Maclsaac JL, Kobor MS et al (2018) Early-life socioeconomic disadvantage, not current, predicts accelerated epigenetic aging of monocytes. Psychoneuroendocrinology 97:131–134. https://doi.org/10.1016/j.psyneuen.2018.07.007CrossRefPubMed

37.

Fiorito G, McCrory C, Robinson O, Carmeli C, Rosales CO, Zhang Y et al (2019) Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: a multi-cohort analysis. Aging 11(7):2045–2070. https://doi.org/10.18632/aging.101900CrossRefPubMedPubMedCentral

38.

McCartney DL, Stevenson AJ, Walker RM, Gibson J, Morris SW, Campbell A et al (2018) Investigating the relationship between DNA methylation age acceleration and risk factors for Alzheimer’s disease. Alzheimers Dement (Amst) 10:429–437. https://doi.org/10.1016/j.dadn.2018.05.006CrossRef

39.

Rosen AD, Robertson KD, Hlady RA, Muench C, Lee J, Philibert R et al (2018) DNA methylation age is accelerated in alcohol dependence. Transl Psychiatry 8(1):182. https://doi.org/10.1038/s41398-018-0233-4CrossRefPubMedPubMedCentral

40.

Lévesque KF, Casey M, Szyf E, Ismaylova V, Ly MP, Verner M et al (2014) Genome-wide DNA methylation variability in adolescent monozygotic twins followed since birth. Epigenetics 9(10):1410–1421. https://doi.org/10.4161/15592294.2014.970060CrossRefPubMedPubMedCentral

41.

Fleckhaus J, Freire-Aradas A, Rothschild M, Schneider P (2017) Impact of genetic ancestry on chronological age prediction using DNA methylation analysis. Forensic Sci Int Genet Suppl Ser 6:e399–e400CrossRef

42.

Tajuddin SM, Hernandez DG, Chen BH, Noren Hooten N, Mode NA, Nalls MA et al (2019) Novel age-associated DNA methylation changes and epigenetic age acceleration in middle-aged African Americans and whites. Clin Epigenetics 11(1):119. https://doi.org/10.1186/s13148-019-0722-1CrossRefPubMedPubMedCentral

43.

Thurston RC, Carroll JE, Levine M, Chang Y, Crandall C, Manson JE et al (2020) Vasomotor symptoms and accelerated epigenetic aging in the Women’s Health Initiative (WHI). J Clin Endocrinol Metab 105(4):1221–1227. https://doi.org/10.1210/clinem/dgaa081CrossRefPubMedCentral

44.

Horvath S, Gurven M, Levine ME, Trumble BC, Kaplan H, Allayee H et al (2016) An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease. Genome Biol 17(1):171. https://doi.org/10.1186/s13059-016-1030-0CrossRefPubMedPubMedCentral

45.

Spolnicka M, Pospiech E, Peplonska B, Zbiec-Piekarska R, Makowska Z, Pieta A et al (2017) DNA methylation in ELOVL2 and C1orf132 correctly predicted chronological age of individuals from three disease groups. Int J Legal Med 132:1–11. https://doi.org/10.1007/s00414-017-1636-0CrossRefPubMedPubMedCentral

46.

Spolnicka M, Zbiec-Piekarska R, Karp M, Machnicki MM, Wlasiuk P, Makowska Z et al (2018) DNA methylation signature in blood does not predict calendar age in patients with chronic lymphocytic leukemia but may alert to the presence of disease. Forensic Sci Int Genet 34:e15–e17. https://doi.org/10.1016/j.fsigen.2018.02.004CrossRefPubMed

47.

Perna L, Zhang Y, Mons U, Holleczek B, Saum KU, Brenner H (2016) Epigenetic age acceleration predicts cancer, cardiovascular, and all-cause mortality in a German case cohort. Clin Epigenetics 8:64. https://doi.org/10.1186/s13148-016-0228-zCrossRefPubMedPubMedCentral

48.

Zheng Y, Joyce BT, Colicino E, Liu L, Zhang W, Dai Q et al (2016) Blood epigenetic age may predict cancer incidence and mortality. EBioMedicine 5:68–73. https://doi.org/10.1016/j.ebiom.2016.02.008CrossRefPubMedPubMedCentral

49.

Ambatipudi S, Horvath S, Perrier F, Cuenin C, Hernandez-Vargas H, Le Calvez-Kelm F et al (2017) DNA methylome analysis identifies accelerated epigenetic ageing associated with postmenopausal breast cancer susceptibility. Eur J Cancer 75:299–307. https://doi.org/10.1016/j.ejca.2017.01.014CrossRefPubMedPubMedCentral

50.

Levine ME, Hosgood HD, Chen B, Absher D, Assimes T, Horvath S (2015) DNA methylation age of blood predicts future onset of lung cancer in the women’s health initiative. Aging 7(9):690–700. https://doi.org/10.18632/aging.100809CrossRefPubMedPubMedCentral

51.

Durso DF, Bacalini MG, Sala C, Pirazzini C, Marasco E, Bonafé M et al (2017) Acceleration of leukocytes’ epigenetic age as an early tumor and sex-specific marker of breast and colorectal cancer. Oncotarget 8(14):23237–23245. https://doi.org/10.18632/oncotarget.15573CrossRefPubMedPubMedCentral

Title: DNA methylation of decedent blood samples to estimate the chronological age of human remains
Authors: Yessenia Anaya
Patrick Yew
Katherine A. Roberts
W. Reef Hardy
Publication date: 01-11-2021
Publisher: Springer Berlin Heidelberg
Keyword: Epigenetics
Published in: International Journal of Legal Medicine / Issue 6/2021
Print ISSN: 0937-9827
Electronic ISSN: 1437-1596
DOI: https://doi.org/10.1007/s00414-021-02650-8

Keynote webinar | Spotlight on medication adherence

Springer Medicine

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

Abstract

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Please log in to get access to this content

Other articles of this Issue 6/2021

Correction to: Sharp force trauma with two katana swords: identifying the murder weapon by comparing tool marks on the skull bone

An unusual suicide by self-waterboarding: forensic pathological issues

Fatal massive pulmonary thromboembolism and concomitant pulmonary trophoblastic embolism associated with exaggerated placental site reaction: a case study

Retraction Note: Exploring the ancestry differentiation and inference capacity of the 28-plex AISNPs

Age estimation based on computed tomography exploration: a combined method

Expanding the Swiss autosomal marker set to 32 STRs