Age estimation based on different molecular clocks in several tissues and a multivariate approach: an explorative study.


Journal

International journal of legal medicine
ISSN: 1437-1596
Titre abrégé: Int J Legal Med
Pays: Germany
ID NLM: 9101456

Informations de publication

Date de publication:
Mar 2020
Historique:
received: 28 01 2019
accepted: 25 03 2019
pubmed: 13 4 2019
medline: 20 11 2020
entrez: 13 4 2019
Statut: ppublish

Résumé

Several molecular modifications accumulate in the human organism with increasing age. Some of these "molecular clocks" in DNA and in proteins open up promising approaches for the development of methods for forensic age estimation. A natural limitation of these methods arises from the fact that the chronological age is determined only indirectly by analyzing defined molecular changes that occur during aging. These changes are not linked exclusively to the expired life span but may be influenced significantly by intrinsic and extrinsic factors in the complex process of individual aging. We tested the hypothesis that a combined use of different molecular clocks in different tissues results in more precise age estimates because this approach addresses the complex aging processes in a more comprehensive way. Two molecular clocks (accumulation of D-aspartic acid (D-Asp), accumulation of pentosidine (PEN)) in two different tissues (annulus fibrosus of intervertebral discs and elastic cartilage of the epiglottis) were analyzed in 95 cases, and uni- and multivariate models for age estimation were generated. The more parameters were included in the models for age estimation, the smaller the mean absolute errors (MAE) became. While the MAEs were 7.5-11.0 years in univariate models, a multivariate model based on the two protein clocks in the two tissues resulted in a MAE of 4.0 years. These results support our hypothesis. The tested approach of a combined analysis of different molecular clocks analyzed in different tissues opens up new possibilities in postmortem age estimation. In a next step, we will add the epigenetic clock (DNA methylation) to our protein clocks (PEN, D-Asp) and expand our set of tissues.

Identifiants

pubmed: 30976985
doi: 10.1007/s00414-019-02054-9
pii: 10.1007/s00414-019-02054-9
doi:

Substances chimiques

D-Aspartic Acid 4SR0Q8YD1X
Collagen 9007-34-5
Arginine 94ZLA3W45F
pentosidine BJ4I2X2CQJ
Lysine K3Z4F929H6

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

721-733

Références

Ritz-Timme S, Cattaneo C, Collins MJ, Waite ER, Schütz HW, Kaatsch HJ, Borrman HI (2000) Age estimation: the state of the art in relation to the specific demands of forensic practise. Int J Legal Med 113(3):129–136
doi: 10.1007/s004140050283
Meissner C, Ritz-Timme S (2010) Molecular pathology and age estimation. Forensic Sci Int 203(1–3):34–43. https://doi.org/10.1016/j.forsciint.2010.07.010
doi: 10.1016/j.forsciint.2010.07.010 pubmed: 20702051 pmcid: 20702051
Ritz-Timme S, Collins MJ (2002) Racemization of aspartic acid in human proteins. Ageing Res Rev 1(1):43–59
doi: 10.1016/S0047-6374(01)00363-3
Zapico SC, Ubelaker DH (2013) Applications of physiological bases of ageing to forensic sciences. Estimation of age-at-death. Ageing Res Rev 12(2):605–617. https://doi.org/10.1016/j.arr.2013.02.002
doi: 10.1016/j.arr.2013.02.002
Ritz-Timme S (1999) Lebensaltersbestimmung aufgrund des Razemisierungsgrades von Asparaginsäure: Grundlagen, Methodik, Möglichkeiten, Grenzen, Anwendungsbereiche ; mit 6 Tabellen. Arbeitsmethoden der medizinischen und naturwissenschaftlichen Kriminalistik, Bd 23. Schmidt-Römhild, Lübeck
Freire-Aradas A, Phillips C, Lareu MV (2017) Forensic individual age estimation with DNA: from initial approaches to methylation tests. Forensic Sci Rev 29(2):121–144
pubmed: 28691915 pmcid: 28691915
Ritz-Timme S, Schneider PM, Mahlke NS, Koop BE, Eickhoff SB (2018) Altersschätzung auf Basis der DNA-Methylierung. Rechtsmedizin 28(3):202–207. https://doi.org/10.1007/s00194-018-0249-3
doi: 10.1007/s00194-018-0249-3
Lee HY, Lee SD, Shin K-J (2016) Forensic DNA methylation profiling from evidence material for investigative leads. BMB Rep 49(7):359–369
doi: 10.5483/BMBRep.2016.49.7.070
Goel N, Karir P, Garg VK (2017) Role of DNA methylation in human age prediction. Mech Ageing Dev 166:33–41. https://doi.org/10.1016/j.mad.2017.08.012
doi: 10.1016/j.mad.2017.08.012 pubmed: 28844970
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.2018.08.008
doi: 10.1016/j.fsigen.2018.08.008 pubmed: 30176440 pmcid: 30176440
Parson W (2018) Age estimation with DNA: from forensic DNA fingerprinting to forensic (epi)genomics: a mini-review. Gerontology 64(4):326–332. https://doi.org/10.1159/000486239
doi: 10.1159/000486239 pubmed: 29393215 pmcid: 29393215
Zapico SC (2017) Mechanisms linking aging, diseases and biological age estimation. 23-Epigenetics. CRC Press, Portland
doi: 10.1201/9781315371382
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-r115
doi: 10.1186/gb-2013-14-10-r115 pubmed: 24138928 pmcid: 4015143
Jung S-E, Shin K-J, Lee HY (2017) DNA methylation-based age prediction from various tissues and body fluids. BMB Rep 50(11):546–553
doi: 10.5483/BMBRep.2017.50.11.175
Jones MJ, Goodman SJ, Kobor MS (2015) DNA methylation and healthy human aging. Aging Cell 14(6):924–932. https://doi.org/10.1111/acel.12349
doi: 10.1111/acel.12349 pubmed: 25913071 pmcid: 25913071
Spólnicka M, Pośpiech E, Adamczyk JG, Freire-Aradas A, Pepłońska B, Zbieć-Piekarska R, Makowska Ż, Pięta A, Lareu MV, Phillips C, Płoski R, Żekanowski C, Branicki W (2018) Modified aging of elite athletes revealed by analysis of epigenetic age markers. Aging 10(2):241–252. https://doi.org/10.18632/aging.101385
doi: 10.18632/aging.101385 pubmed: 29466246 pmcid: 5842850
Gao X, Zhang Y, Breitling LP, Brenner H (2016) Relationship of tobacco smoking and smoking-related DNA methylation with epigenetic age acceleration. Oncotarget 7(30):46878–46889. https://doi.org/10.18632/oncotarget.9795
doi: 10.18632/oncotarget.9795 pubmed: 27276709 pmcid: 5216910
Kandi V, Vadakedath S (2015) Effect of DNA methylation in various diseases and the probable protective role of nutrition: a mini-review. Cureus 7(8):e309. https://doi.org/10.7759/cureus.309
doi: 10.7759/cureus.309 pubmed: 26430583 pmcid: 4582005
Stephenson RC, Clarke S (1989) Succinimide formation from aspartyl and asparaginyl peptides as a model for the spontaneous degradation of proteins. J Biol Chem 264(11):6164–6170
pubmed: 2703484
Geiger T, Clarke S (1987) Deamidation, isomerization, and racemization at asparaginyl and aspartyl residues in peptides. Succinimide-linked reactions that contribute to protein degradation. J Biol Chem 262(2):785–794
pubmed: 3805008
Dobberstein RC, Tung S-M, Ritz-Timme S (2010) Aspartic acid racemisation in purified elastin from arteries as basis for age estimation. Int J Legal Med 124(4):269–275. https://doi.org/10.1007/s00414-009-0392-1
doi: 10.1007/s00414-009-0392-1 pubmed: 19924428
Klumb K, Matzenauer C, Reckert A, Lehmann K, Ritz-Timme S (2016) Age estimation based on aspartic acid racemization in human sclera. Int J Legal Med 130(1):207–211. https://doi.org/10.1007/s00414-015-1255-6
doi: 10.1007/s00414-015-1255-6 pubmed: 26303762
Matzenauer C, Reckert A, Ritz-Timme S (2014) Estimation of age at death based on aspartic acid racemization in elastic cartilage of the epiglottis. Int J Legal Med 128(6):995–1000. https://doi.org/10.1007/s00414-013-0940-6
doi: 10.1007/s00414-013-0940-6 pubmed: 24218015
Ohtani S, Yamamoto K (1991) Age estimation using the racemization of amino acid in human dentin. J Forensic Sci 36(3):792–800
doi: 10.1520/JFS13089J
Ritz S, Schütz HW, Schwarzer B (1990) The extent of aspartic acid racemization in dentin: a possible method for a more accurate determination of age at death? Zeitschrift fur Rechtsmedizin. J Legal Med 103(6):457–462
Ritz S, Schütz HW, Peper C (1993) Postmortem estimation of age at death based on aspartic acid racemization in dentin: its applicability for root dentin. Int J Legal Med 105(5):289–293
doi: 10.1007/BF01370387
Ohtani S, Yamamoto T (2010) Age estimation by amino acid racemization in human teeth. J Forensic Sci 55(6):1630–1633. https://doi.org/10.1111/j.1556-4029.2010.01472.x
doi: 10.1111/j.1556-4029.2010.01472.x pubmed: 20561145
Chen S, Lv Y, Wang D, Yu X (2016) Aspartic acid racemization in dentin of the third molar for age estimation of the Chaoshan population in South China. Forensic Sci Int 266:234–238. https://doi.org/10.1016/j.forsciint.2016.06.010
doi: 10.1016/j.forsciint.2016.06.010 pubmed: 27337639
Elfawal MA, Alqattan SI, Ghallab NA (2015) Racemization of aspartic acid in root dentin as a tool for age estimation in a Kuwaiti population. Med Sci Law 55(1):22–29. https://doi.org/10.1177/0025802414524383
doi: 10.1177/0025802414524383 pubmed: 24589728
Wochna K, Bonikowski R, Śmigielski J, Berent J (2018) Aspartic acid racemization of root dentin used for dental age estimation in a Polish population sample. Forensic Sci Med Pathol 14(3):285–294. https://doi.org/10.1007/s12024-018-9984-8
doi: 10.1007/s12024-018-9984-8 pubmed: 29721810 pmcid: 6096966
Ritz-Timme S, Rochholz G, Stammert R, Ritz H-J (2002) Biochemische Altersschätzung Zur Frage genetischer und soziokultureller (ethnischer) Einflüsse auf die Razemisierung von Asparaginsäure in Dentin. Rechtsmedizin 12(4):203–206. https://doi.org/10.1007/s00194-002-0152-8
doi: 10.1007/s00194-002-0152-8
Ulrich P, Cerami A (2001) Protein glycation, diabetes, and aging. Recent Prog Horm Res 56:1–21
doi: 10.1210/rp.56.1.1
Singh R, Barden A, Mori T, Beilin L (2001) Advanced glycation end-products: a review. Diabetologia 44(2):129–146. https://doi.org/10.1007/s001250051591
doi: 10.1007/s001250051591 pubmed: 11270668
Goldberg T, Cai W, Peppa M, Dardaine V, Baliga BS, Uribarri J, Vlassara H (2004) Advanced glycoxidation end products in commonly consumed foods. J Am Diet Assoc 104(8):1287–1291. https://doi.org/10.1016/j.jada.2004.05.214
doi: 10.1016/j.jada.2004.05.214 pubmed: 15281050
Nass N, Bartling B, Navarrete Santos A, Scheubel RJ, Börgermann J, Silber RE, Simm A (2007) Advanced glycation end products, diabetes and ageing. Z Gerontol Geriatr 40(5):349–356. https://doi.org/10.1007/s00391-007-0484-9
doi: 10.1007/s00391-007-0484-9 pubmed: 17943238
Greis F, Reckert A, Fischer K, Ritz-Timme S (2018) Analysis of advanced glycation end products (AGEs) in dentine: useful for age estimation? Int J Legal Med 132(3):799–805. https://doi.org/10.1007/s00414-017-1671-x
doi: 10.1007/s00414-017-1671-x pubmed: 28905104
Odetti P, Rossi S, Monacelli F, Poggi A, Cirnigliaro M, Federici M, Federici A (2005) Advanced glycation end products and bone loss during aging. Ann N Y Acad Sci 1043:710–717. https://doi.org/10.1196/annals.1333.082
doi: 10.1196/annals.1333.082 pubmed: 16037297
Pokharna HK, Phillips FM (1998) Collagen crosslinks in human lumbar intervertebral disc aging. Spine 23(15):1645–1648
doi: 10.1097/00007632-199808010-00005
Verzijl N, DeGroot J, Oldehinkel E, Bank RA, Thorpe SR, Baynes JW, Bayliss MT, Bijlsma JW, Lafeber FP, Tekoppele JM (2000) Age-related accumulation of Maillard reaction products in human articular cartilage collagen. Biochem J 350(Pt 2):381–387
doi: 10.1042/bj3500381
Ramalho JS, Marques C, Pereira PC, Mota MC (1996) Role of glycation in human lens protein structure change. Eur J Ophthalmol 6(2):155–161
doi: 10.1177/112067219600600211
Pillin A, Pudil F, Bencko V, Bezdícková D (2007) Contents of pentosidine in the tissue of the intervertebral disc as an indicator of the human age. Soud Lek 52(4):60–64
pubmed: 18189072
Dyer DG, Dunn JA, Thorpe SR, Bailie KE, Lyons TJ, McCance DR, Baynes JW (1993) Accumulation of Maillard reaction products in skin collagen in diabetes and aging. J Clin Invest 91(6):2463–2469. https://doi.org/10.1172/JCI116481
doi: 10.1172/JCI116481 pubmed: 8514858 pmcid: 443306
Valenzuela A, Guerra-Hernández E, Rufián-Henares JÁ, Márquez-Ruiz AB, Hougen HP, García-Villanova B (2018) Differences in non-enzymatic glycation products in human dentine and clavicle: changes with aging. Int J Legal Med 132(6):1749–1758. https://doi.org/10.1007/s00414-018-1908-3
doi: 10.1007/s00414-018-1908-3 pubmed: 30069788 pmcid: 30069788
Li H, Yu S-J (2018) Review of pentosidine and pyrraline in food and chemical models: formation, potential risks and determination. J Sci Food Agric 98(9):3225–3233. https://doi.org/10.1002/jsfa.8853
doi: 10.1002/jsfa.8853 pubmed: 29280151
Stitt AW, Jenkins AJ, Cooper ME (2002) Advanced glycation end products and diabetic complications. Expert Opin Investig Drugs 11(9):1205–1223. https://doi.org/10.1517/13543784.11.9.1205
doi: 10.1517/13543784.11.9.1205 pubmed: 12225243
Ritz S, Turzynski A, Schütz HW (1994) Estimation of age at death based on aspartic acid racemization in noncollagenous bone proteins. Forensic Sci Int 69(2):149–159
doi: 10.1016/0379-0738(94)90251-8
Ritz S, Turzynski A, Schütz HW, Hollmann A, Rochholz G (1996) Identification of osteocalcin as a permanent aging constituent of the bone matrix: basis for an accurate age at death determination. Forensic Sci Int 77(1–2):13–26
doi: 10.1016/0379-0738(95)01834-4
Ritz-Timme S, Laumeier I, Collins M (2003) Age estimation based on aspartic acid racemization in elastin from the yellow ligaments. Int J Legal Med 117(2):96–101. https://doi.org/10.1007/s00414-002-0355-2
doi: 10.1007/s00414-002-0355-2 pubmed: 12690506
Monum T, Jaikang C, Sinthubua A, Prasitwattanaseree S, Mahakkanukrauh P (2017) Age estimation using aspartic amino acid racemization from a femur. Aust J Forensic Sci 116:1–9. https://doi.org/10.1080/00450618.2017.1391330
doi: 10.1080/00450618.2017.1391330
Ohtani S, Matsushima Y, Kobayashi Y, Kishi K (1998) Evaluation of aspartic acid racemization ratios in the human femur for age estimation. J Forensic Sci 43(5):949–953
doi: 10.1520/JFS14339J
Ohtani S, Yamamoto T, Abe I, Kinoshita Y (2007) Age-dependent changes in the racemisation ratio of aspartic acid in human alveolar bone. Arch Oral Biol 52(3):233–236. https://doi.org/10.1016/j.archoralbio.2006.08.011
doi: 10.1016/j.archoralbio.2006.08.011 pubmed: 17097046
Tiplamaz S, Gören MZ, Yurtsever NT (2018) Estimation of chronological age from postmortem tissues based on amino acid racemization. J Forensic Sci 63(5):1533–1538. https://doi.org/10.1111/1556-4029.13737
doi: 10.1111/1556-4029.13737 pubmed: 29341137
Sivan SS, Tsitron E, Wachtel E, Roughley P, Sakkee N, van der Ham F, Degroot J, Maroudas A (2006) Age-related accumulation of pentosidine in aggrecan and collagen from normal and degenerate human intervertebral discs. Biochem J 399(1):29–35. https://doi.org/10.1042/BJ20060579
doi: 10.1042/BJ20060579 pubmed: 16787390 pmcid: 1570172
Schmidt MB, Mow VC, Chun LE, Eyre DR (1990) Effects of proteoglycan extraction on the tensile behavior of articular cartilage. J Orthop Res 8(3):353–363. https://doi.org/10.1002/jor.1100080307
doi: 10.1002/jor.1100080307 pubmed: 2324854
Heems D, Luck G, Fraudeau C, Vérette E (1998) Fully automated precolumn derivatization, on-line dialysis and high-performance liquid chromatographic analysis of amino acids in food, beverages and feedstuff. J Chromatogr A 798(1–2):9–17. https://doi.org/10.1016/S0021-9673(97)01007-8
doi: 10.1016/S0021-9673(97)01007-8
Kaufman DS, Manley WF (1998) A new procedure for determining dl amino acid ratios in fossils using reverse phase liquid chromatography. Quat Sci Rev 17(11):987–1000. https://doi.org/10.1016/S0277-3791(97)00086-3
doi: 10.1016/S0277-3791(97)00086-3
Rokach L (2010) Ensemble-based classifiers. Artif Intell Rev 33(1–2):1–39. https://doi.org/10.1007/s10462-009-9124-7
doi: 10.1007/s10462-009-9124-7
Rasmussen CE, Williams CKI (2006) Gaussian processes for machine learning. Adaptive computation and machine learning. MIT Press, Cambridge
Cho S, Jung S-E, Hong SR, Lee EH, Lee JH, Lee SD, Lee HY (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.2017.04.020
doi: 10.1016/j.fsigen.2017.04.020 pubmed: 28511095 pmcid: 28511095
Ritz S, Schütz HW (1993) Aspartic acid racemization in intervertebral discs as an aid to postmortem estimation of age at death. J Forensic Sci 38(3):633–640
doi: 10.1520/JFS13449J
Sell DR, Nagaraj RH, Grandhee SK, Odetti P, Lapolla A, Fogarty J, Monnier VM (1991) Pentosidine: a molecular marker for the cumulative damage to proteins in diabetes, aging, and uremia. Diabetes Metab Rev 7(4):239–251
doi: 10.1002/dmr.5610070404
Brownlee M (1995) Advanced protein glycosylation in diabetes and aging. Annu Rev Med 46:223–234. https://doi.org/10.1146/annurev.med.46.1.223
doi: 10.1146/annurev.med.46.1.223 pubmed: 7598459
Semba RD, Nicklett EJ, Ferrucci L (2010) Does accumulation of advanced glycation end products contribute to the aging phenotype? J Gerontol A Biol Sci Med Sci 65A(9):963–975. https://doi.org/10.1093/gerona/glq074
doi: 10.1093/gerona/glq074 pmcid: 2920582
Aliferi A, Ballard D, Gallidabino MD, Thurtle H, Barron L, Syndercombe Court D (2018) DNA methylation-based age prediction using massively parallel sequencing data and multiple machine learning models. Forensic Sci Int Genet 37:215–226. https://doi.org/10.1016/j.fsigen.2018.09.003
doi: 10.1016/j.fsigen.2018.09.003 pubmed: 30243148
Jung S-E, Lim SM, Hong SR, Lee EH, Shin K-J, Lee HY (2019) DNA methylation of the ELOVL2, FHL2, KLF14, C1orf132/MIR29B2C, and TRIM59 genes for age prediction from blood, saliva, and buccal swab samples. Forensic Sci Int Genet 38:1–8. https://doi.org/10.1016/j.fsigen.2018.09.010
doi: 10.1016/j.fsigen.2018.09.010 pubmed: 30300865
Naue J, Hoefsloot HCJ, Mook ORF, Rijlaarsdam-Hoekstra L, van der Zwalm MCH, Henneman P, Kloosterman AD, Verschure PJ (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.2017.07.015
doi: 10.1016/j.fsigen.2017.07.015 pubmed: 28841467
Rhein M, Hagemeier L, Klintschar M, Muschler M, Bleich S, Frieling H (2015) DNA methylation results depend on DNA integrity—role of post mortem interval. Front Genet 6. https://doi.org/10.3389/fgene.2015.00182
Jarmasz JS, Stirton H, Davie JR, Del Bigio MR (2019) DNA methylation and histone post-translational modification stability in post-mortem brain tissue. Clin Epigenetics 11(1):5. https://doi.org/10.1186/s13148-018-0596-7
doi: 10.1186/s13148-018-0596-7 pubmed: 30635019 pmcid: 6330433
Vidaki A, Ballard D, Aliferi A, Miller TH, Barron LP, 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. https://doi.org/10.1016/j.fsigen.2017.02.009
doi: 10.1016/j.fsigen.2017.02.009 pubmed: 28254385 pmcid: 5392537
Shi L, Jiang F, Ouyang F, Zhang J, Wang Z, Shen X (2018) DNA methylation markers in combination with skeletal and dental ages to improve age estimation in children. Forensic Sci Int Genet 33:1–9. https://doi.org/10.1016/j.fsigen.2017.11.005
doi: 10.1016/j.fsigen.2017.11.005

Auteurs

Julia Becker (J)

Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Dusseldorf, Germany.

Nina Sophia Mahlke (NS)

Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Dusseldorf, Germany. nina.mahlke@hhu.de.

A Reckert (A)

Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Dusseldorf, Germany.

S B Eickhoff (SB)

Institute for Systems Neuroscience, University Hospital Düsseldorf, 40225, Dusseldorf, Germany.
Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, 52428, Julich, Germany.

S Ritz-Timme (S)

Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Dusseldorf, Germany.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH