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http://dx.doi.org/10.5483/BMBRep.2017.50.11.175

DNA methylation-based age prediction from various tissues and body fluids  

Jung, Sang-Eun (Department of Forensic Medicine, Yonsei University College of Medicine)
Shin, Kyoung-Jin (Department of Forensic Medicine, Yonsei University College of Medicine)
Lee, Hwan Young (Department of Forensic Medicine, Yonsei University College of Medicine)
Publication Information
BMB Reports / v.50, no.11, 2017 , pp. 546-553 More about this Journal
Abstract
Aging is a natural and gradual process in human life. It is influenced by heredity, environment, lifestyle, and disease. DNA methylation varies with age, and the ability to predict the age of donor using DNA from evidence materials at a crime scene is of considerable value in forensic investigations. Recently, many studies have reported age prediction models based on DNA methylation from various tissues and body fluids. Those models seem to be very promising because of their high prediction accuracies. In this review, the changes of age-associated DNA methylation and the age prediction models for various tissues and body fluids were examined, and then the applicability of the DNA methylation-based age prediction method to the forensic investigations was discussed. This will improve the understandings about DNA methylation markers and their potential to be used as biomarkers in the forensic field, as well as the clinical field.
Keywords
Age prediction; DNA methylation; Forensic genetics;
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1 Marioni RE, Shah S, McRae AF et al (2015) DNA methylation age of blood predicts all-cause mortality in later life. Genome Biol 16-25
2 Armstrong NJ, Mather KA, Thalamuthu A et al (2017) Aging, exceptional longevity and comparisons of the Hannum and Horvath epigenetic clocks. Epigenomics 9(5), 689-700   DOI
3 Kurdyukov S and Bullock M (2016) DNA methylation analysis: choosing the right method. Biology (Basel) 5, 3
4 Suchiman HE, Slieker RC, Kremer D, Slagboom PE, Heijmans BT and Tobi EW (2015) Design, measurement and processing of region-specific DNA methylation assays: the mass spectrometry-based method EpiTYPER. Front Genet 6, 287
5 Kaminsky Z and Petronis A (2009) Methylation SNaPshot: a method for the quantification of site-specific DNA methylation levels. Methods Mol Biol 507, 241-255
6 Masser DR, Stanford DR and Freeman WM (2015) Targeted DNA methylation analysis by next-generation sequencing. J Vis Exp 96, e52488
7 Giuliani C, Cilli E, Bacalini MG et al (2016) Inferring chronological age from DNA methylation patterns of human teeth. Am J Phys Anthropol 159, 585-595   DOI
8 Jung M and Pfeifer GP (2015) Aging and DNA methylation. BMC Biol 13, 7   DOI
9 Klass MR (1983) A method for the isolation of longevity mutants in the nematode Caenorhabditis elegans and initial results. Mech Ageing Dev 22, 279-286   DOI
10 Lopez-Otin C, Blasco MA, Partridge L, Serrano M and Kroemer G (2013) The hallmarks of aging. Cell 153, 1194-1217   DOI
11 Weinhold B (2006) Epigenetics: the science of change. Environ Health Perspect 114, A160-167   DOI
12 Holliday R and Pugh JE (1975) DNA modification mechanisms and gene activity during development. Science 187, 226-232   DOI
13 Jones PA (2012) Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat Rev Genet 13, 484-492   DOI
14 Berdishev MT, Korotaev GK, Boiarskikh GV and Vanyushin BF (1967) Nucleotide composition of DNA and RNA from somatic tissues of humpback salmon and its changes during spawning. Biokhimiia 38, 988-993
15 Pogribny IP, James SJ, Jernigan S and Pogribna M (2004) Genomic hypomethylation is specific for preneoplastic liver in folate/methyl deficient rats and does not occur in non-target tissues. Mutat Res 548, 53-59   DOI
16 Wilson VL, Smith RA, Ma S and Cutler RG (1987) Genomic 5-methyldeoxycytidine decreases with age. J Biol Chem 262, 9948-9951
17 Bird A (2002) DNA methylation patterns and epigenetic memory. Genes Dev 16, 6-21   DOI
18 Teschendorff AE, Marabita F, Lechner M et al (2013) A beta- mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data. Bioinformatics 29, 189-196   DOI
19 Koch C and Wagner W (2011) Epigenetic-aging-signature to determine age in different tissues. Aging 3, 1018-1027   DOI
20 Garagnani P, Bacalini MG, Pirazzini C et al (2012) Methylation of ELOVL2 gene as a new epigenetic marker of age. Aging Cell 11, 1132-1134   DOI
21 Zbiec-Piekarska R, Spolnicka M, Kupiec T 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   DOI
22 Zbiec-Piekarska R, Spolnicka M, Kupiec T et al (2015) Development of a forensically useful age prediction method based on DNA methylation analysis. Forensic Sci Int Genet 17, 173-179   DOI
23 Cho S, Jung SE, Hong SR et al (2017) Independent validation of DNA-based approaches for age prediction in blood. Forensic Sci Int Genet 29, 250-256   DOI
24 Park JL, Kim JH, Seo E et al (2016) Identification and evaluation of age-correlated DNA methylation markers for forensic use. Forensic Sci Int Genet 23, 64-70   DOI
25 Freire-Aradas A, Phillips C, Mosquera-Miguel A et al (2016) Development of a methylation marker set for forensic age estimation using analysis of public methylation data and the Agena Bioscience EpiTYPER system. Forensic Sci Int Genet 24, 65-74   DOI
26 Vidaki A, Ballard D, Aliferi A, Miller TH, Barron LP and Syndercombe Court D (2017) DNA methylation-based forensic age prediction using artificial neural networks and next generation sequencing. Forensic Sci Int Genet 28, 225-236   DOI
27 Naue J, Hoefsloot HCJ, Mook ORF et al (2017) Chronological age prediction based on DNA methylation: massive parallel sequencing and random forest regression. Forensic Sci Int Genet 31, 19-28   DOI
28 Hong SR, Jung SE, Lee EH, Shin KJ, Yang WI and Lee HY (2017) DNA methylation-based age prediction from saliva: high age predictability by combination of 7 CpG markers. Forensic Sci Int Genet 29, 118-125   DOI
29 Eipel M, Mayer F, Arent T et al (2016) Epigenetic age predictions based on buccal swabs are more precise in combination with cell type-specific DNA methylation signatures. Aging (Albany NY) 8, 1034-1048
30 Lee HY, Jung SE, Oh YN, Choi A, Yang WI and Shin KJ (2015) Epigenetic age signatures in the forensically relevant body fluid of semen: a preliminary study. Forensic Sci Int Genet 19, 28-34   DOI
31 Jenkins TG, Aston KI, Pflueger C, Cairns BR and Carrell DT (2014) Age-associated sperm DNA methylation alterations: possible implications in offspring disease susceptibility. PLoS Genet 10, e1004458   DOI
32 Bekaert B, Kamalandua A, Zapico SC, Van de Voorde W and Decorte R (2015) Improved age determination of blood and teeth samples using a selected set of DNA methylation markers. Epigenetics 10, 922-930   DOI
33 Issa JP, Ottaviano YL, Celano P, Hamilton SR, Davidson NE and Baylin SB (1994) Methylation of the oestrogen receptor CpG island links ageing and neoplasia in human colon. Nat Genet 7, 536-540   DOI
34 Vire E, Brenner C, Deplus R et al (2006) The polycomb group protein EZH2 directly controls DNA methylation. Nature 439, 871-874   DOI
35 Vanyushin BF, Nemirovsky LE, Klimenko VV, Vasiliev VK and Belozersky AN (1973) The 5-methylcytosine in DNA of rats. Tissue and age specificity and the changes induced by hydrocortisone and other agents. Gerontologia 19, 138-152   DOI
36 Fuke C, Shimabukuro M, Petronis A et al (2004) Age related changes in 5-methylcytosine content in human peripheral leukocytes and placentas: an HPLC-based study. Ann Hum Genet 68, 196-204   DOI
37 Marino M, Masella R, Bulzomi P, Campesi I, Malorni W and Franconi F (2011) Nutrition and human health from a sex-gender perspective. Mol Aspects Med 32, 1-70   DOI
38 Wang Y, Zhang X, Zhang H et al (2012) Coiled-coil networking shapes cell molecular machinery. Mol Biol Cell 23, 3911-3922   DOI
39 Alisch RS, Barwick BG, Chopra P et al (2012) Ageassociated DNA methylation in pediatric populations. Genome Res 22, 623-632   DOI
40 Weidner CI, Lin Q, Koch CM et al (2014) Aging of blood can be tracked by DNA methylation changes at just three CpG sites. Genome Biol 15, R24   DOI
41 Zampieri M, Ciccarone F, Calabrese R, Franceschi C, Burkle A and Caiafa P (2015) Reconfiguration of DNA methylation in aging. Mech Ageing Dev 151, 60-70   DOI
42 Herskind AM, McGue M, Holm NV, Sorensen TI, Harvald B and Vaupel JW (1996) The heritability of human longevity: a population-based study of 2872 Danish twin pairs born 1870-1900. Hum Genet 97, 319-323   DOI
43 Hirner AV and Rettenmeier AW (2010) Methylated metal(loid) species in humans. Met Ions Life Sci 7, 465-521
44 Bocklandt S, Lin W, Sehl ME et al (2011) Epigenetic predictor of age. PLoS One 6, e14821   DOI
45 Numata S, Ye T, Hyde TM et al (2012) DNA methylation signatures in development and aging of the human prefrontal cortex. Am J Hum Genet 90, 260-272   DOI
46 Johansson A, Enroth S and Gyllensten U (2013) Continuous aging of the human DNA methylome throughout the human lifespan. PLoS One 8, e67378   DOI
47 Horvath S (2013) DNA methylation age of human tissues and cell types. Genome Biol 14, R115   DOI
48 Jones MJ, Goodman SJ and Kobor MS (2015) DNA methylation and healthy human aging. Aging Cell 14, 924-932   DOI
49 Fraga MF, Ballestar E, Paz MF et al (2005) Epigenetic differences arise during the lifetime of monozygotic twins. Proc Natl Acad Sci U S A 102, 10604-10609   DOI
50 Fraga MF and Esteller M (2007) Epigenetics and aging: the targets and the marks. Trends Genet 23, 413-418   DOI
51 Hannum G, Guinney J, Zhao L et al (2013) Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol Cell 49, 359-367   DOI