Abstract
With the increase of globalization and migration, the topic of age estimation has become more and more important in diverse fields of application, especially for age estimation in living individuals as well as for age estimation in the identification of unknown deceased and of unknown donors of a trace. Especially in the last decade, the traditional spectrum of morphological methods has been expanded to numerous new approaches based on the use of age-dependent molecular changes. Articles in this field have been and are being published in quick succession but not all approaches can (already) meet the demands of forensic practice. It may be a challenge for the forensic practitioner to keep track of suitable methods and to find the optimal method for a single case with its specific questions, conditions and requirements. This overview is intended to provide orientation on the question of which molecular approaches can already be used or will be applicable in the foreseeable future in different application fields. The focus is on the accumulation of D‑aspartic acid and pentosidine, DNA methylation and the use of the bomb pulse-derived carbon-14 (14C).
Zusammenfassung
Mit Zunahme von Globalisierung und Migration hat das Thema Lebensaltersschätzung in den forensischen Wissenschaften mehr und mehr an Bedeutung gewonnen (bei Lebenden als auch bei nicht identifizierten Leichen oder im Zuge der Identifizierung eines unbekannten Spurenverursachers). Das traditionelle Spektrum morphologischer Methoden wurde insbesondere im letzten Jahrzehnt um zahlreiche neue Ansätze erweitert, die auf der Nutzung altersabhängiger molekularer Veränderungen basieren. In rascher Folge wurden und werden Beiträge in diesem Feld publiziert – aber nicht alle Ansätze können die Anforderungen der forensischen Praxis (bereits) erfüllen. Für den forensischen Praktiker kann es zur Herausforderung werden, die Übersicht über geeignete Methoden zu behalten und die optimale Methode für den konkreten Einzelfall mit seinen spezifischen Fragestellungen, Bedingungen und Voraussetzungen zu finden. Diese Übersicht will Orientierung zu der Frage geben, welche molekularen Ansätze unter welcher Fragestellung bereits einsetzbar sind oder in absehbarer Zeit einsetzbar sein werden. Im Fokus stehen dabei die Akkumulation von D‑Asparaginsäure und Pentosidin, die DNA-Methylierung und die Nutzung des bei Atombombenversuchen freigesetzten Radiocarbons (14C).
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Molecular methods of age estimation and the demands of forensic practice
Migration in a globalized world has increased the need for accurate methods for age estimation in forensic practice during the last decades in diverse fields of application, especially for age estimation in living individuals as well as for age estimation in the identification of unknown deceased of unknown donors of traces. The need for suitable methods in different contexts has further stimulated research. Various morphological and molecular approaches have been proposed by many publications of different quality. Not infrequently it remains open which methods have already reached or will reach a level of development that will allow their use in practice. Today, it may be challenging for the forensic practitioner to keep track of suitable methods and to find the optimal method for a single case with its specific questions, conditions and requirements.
Already 20 years ago, a paper titled “Age estimation: the state of the art in relation to the specific demands of forensic practice” addressed this problem [1]. This paper has been highly cited since it has given orientation by 1) defining the specific demands that have to be fulfilled by methods for forensic age estimation and by 2) identifying the methods that could fulfil these demands.
In short, these defined criteria were [1]:
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A.
“The methods must be transparent and provable, the underlying data must have been presented to the scientific community, as a rule by publication in peer-reviewed journals …”
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B.
“Clear information concerning the accuracy of age estimation by the method should be available. Accuracy must have been tested by using valid statistical procedures and described in clearly defined terms …”
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C.
“The methods need to be accurate enough to fulfil the specific demands of the single case to solve the underlying questions …”
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D.
“In cases of age estimation in living individuals principles of medical ethics and legal regulations have to be considered ….”
Twenty years ago only one molecular method, namely age estimation based on the D‑aspartic acid content of dentine, could withstand the strict selection criteria cited above [1]. Since then, the scientific field of molecular approaches for age estimation has been rapidly expanding, not least because of the discovery of DNA methylation as a biomarker of aging and age. These molecular methods have been attracting much scientific attention since they can be superior to traditional morphological anthropological methods by promising much more accurate results at least in adult age. Moreover, as laboratory methods that quantify certain parameters, molecular methods mostly offer more convincing possibilities for standardization, validation and quality assurance than the traditional morphological methods, which is an important aspect with respect to the demands on modern forensic disciplines. Finally, some molecular methods (especially those based on DNA methylation) address more fields of application; they can be applied not only in the traditional field of age estimation for the identification of unknown deceased but also for the analysis of traces and noninvasive age estimation in living persons.
Although a lot of research will still be necessary for optimization and validation of many molecular methods, it is evident that they already play or will play an increasing role in different fields of application [2].
The aim of this paper is to give orientation regarding the current state of the art of molecular methods for age estimation with respect to the criteria cited above and to the different application fields in forensic practice. It is not intended to be an all-encompassing review but rather a practical guide for those colleagues who ask themselves which of the multitude of published molecular approaches for age estimation can already be used in casework or could be used in the near future.
Which molecular methods have a very high potential to fulfil the specific demands of forensic practice?
In the last decades diverse molecular approaches for age estimation have been proposed, e.g. the analysis of DNA methylation, posttranslational protein modifications, telomere length, mitochondrial DNA deletions and signal joint T‑cell receptor rearrangement excision circles (sjTRECS) [2,3,4,5,6]. Some of these parameters are so closely related with age that they have been referred to as “molecular clocks”.
So far, several approaches have not made it from basic science to practical use. For some methods, there are only initial experiences and still insufficient data, and they have not yet been properly validated. Other methods do not provide the accuracy of age estimates that is needed. It may be very difficult to get satisfying information about the accuracy that can be expected when a method is applied in the field. The accuracy is described very differently, e.g. by correlation coefficients (R), by standard errors of estimates (SEE), by prediction intervals (PI), by mean absolute deviations or by mean absolute errors (MAD, MAE). Therefore, it is difficult to compare the accuracy of different methods.
When reviewing papers proposing molecular methods for age estimation under consideration of the defined demands (A-D), there are essentially the following molecular approaches that have a very high potential to meet these demands or already fulfil them, and that are already applied or can be expected to be ready for use in the near future:
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The accumulation of D‑aspartic acid (D-Asp) with increasing age is the result of a spontaneous, non-enzymatic conversion of L‑asparagine and L‑aspartic acid residues into their D form [5, 7]. It has been described for long-lived proteins in numerous tissues [8,9,10,11,12]. This approach is already established in forensic practice, especially in the analysis of dentine (e.g. [13,14,15,16]).
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The age-dependent accumulation of pentosidine (Pen), an advanced glycation end product (AGE), is the result of complex non-enzymatic posttranslational protein modifications [17, 18]; Pen accumulates in long-lived proteins in diverse tissues, such as dentine, bone, intervertebral discs and epiglottis [19,20,21,22].
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DNA methylation (DNAm) at certain sites in the genome are closely related to a person’s age. A large number of age-dependent DNAm markers have already been identified in diverse tissues and body fluids, and various models for age estimation have been proposed (e.g. [23,24,25,26,27,28,29,30]).
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Age estimation based on bomb pulse derived carbon-14 (14C) dating is more a physicochemical than a molecular method in a narrower sense. Nonetheless, this very interesting approach addresses age-dependent changes on a molecular level and is therefore listed here. It uses the rise of 14C in the atmosphere due to the above-ground nuclear bomb tests between 1955 and 1963 and its exponential drop after the tests were stopped. The amount of incorporated 14C in human tissues enables the estimation of the time of birth (and therefore an indirect estimation of age) of individuals born after ca. 1950; very low errors have been reported especially for the analysis of enamel [2, 31,32,33,34].
All in all there have been many peer reviewed papers regarding these four approaches (demand A), but the question of the achievable accuracy (demand B) cannot be finally answered for all methods that have been proposed on their basis. Age estimation based on D‑Asp is the oldest of the four approaches; D‑Asp analysis in dentine has been evaluated over decades by many groups over the world (e.g. [10, 14,15,16, 35,36,37]). The approach seems to be robust against non-age-related factors, such as life style, diseases or biographic origin [38, 39]; however, data about D‑Asp in other tissues than dentine are still comparatively rare. In the case of Pen, there are still too few studies for a final evaluation; however, it seems to be very useful in combination with other approaches and in ancient cases [21, 40]. Also, for DNAm there are still open questions (e.g. regarding non-age-related factors that may influence DNAm [3, 41,42,43]) that have to be answered, before final statements about the accuracy of all derived methods can be made. Further research is also required with respect to the 14C approach; in particular, the future implication of the flattening of the bomb pulse curve due to the slow return to the pre-bomb pulse 14C levels on the errors in age estimation has to be clarified [34].
Nevertheless, it can safely be assumed that these four molecular approaches will sooner or later fulfil the demand B (clarity about the accuracy of age estimation). The question if the accuracy of a method is sufficient in a single case (demand C) depends on the application field and can be easily answered if there are clear data regarding the accuracy. Demand D (ethical issues of age estimation in living individuals) can be optimally addressed by DNAm, since epigenetic age estimation can be performed by analysis of buccal swabs or blood samples.
Which of these approaches (D-Asp, Pen, DNAm, 14C) are suitable or promising for which fields of application?
Table 1 gives an overview over eligible and promising molecular approaches for different fields of application (corpses or body parts in forensic cases, ancient skeletal remains, age estimation in living individuals, and estimation of the age of an unknown donor of a trace).
The compilation of literature in Table 1 does not claim to be complete but includes exemplary and current articles with relevant information regarding the approaches and their achievable accuracy. The statistical robustness of data regarding the accuracy varies widely; nevertheless, the extracted information listed in Table 1 allows at least a rough overview of the potential of the different approaches. Particular consideration was given to work recording correlation coefficients (R) above ca. 0.9 as well as SEEs, MAEs and MADs below ca. 5 years or 95% prediction intervals (PI) below ca. 10 years as an indication that the minimum required accuracy can be achieved to fulfil the demands of forensic casework [1, 44]. Due to complex aging processes with an accumulation of interfering confounding factors with age, the accuracy of nearly all models for age estimation becomes worse with increasing age.
The extent to which the methods can already be used in forensic practice depends on the level of development achieved by specialized laboratories. Therefore, in special cases it is always worth contacting a corresponding laboratory and discussing the question of whether a method should be applied under the special conditions of the single case.
From Table 1 it becomes very clear how inconsistently the information on accuracy is reported in the literature. In future, researchers should agree on procedures that allow a direct comparison between methods and clear statements about the accuracy in individual cases. This is not only important for research, but also for practical use in casework; those who have to work with the result of an age estimation must get a clear statement about the error in every individual case.
Final remarks
This paper aims to give some orientation regarding the state of the art in the field of molecular age estimation. In view of the extensive research activities in this field, this overview may no longer be up to date when it is published. Nevertheless, it seemed sensible to give such an overview, not least because some methods are already being used or will soon be implemented.
Another point that could be supported by this overview is the promotion of interdisciplinarity in the field of age estimation, in research and practice as well. Due to the different nature of the approaches and their different fields of application, very differently qualified scientists (such as morphologists and molecular geneticists) are involved in research regarding this topic. It has already been shown that multivariate approaches using several biological levels (morphology, proteins, DNAm) may produce better results than univariate approaches [21, 26, 45]. Important impulses can be expected by interdisciplinary approaches that require a look beyond the boundaries of the subdisciplines of (forensic) sciences.
This overview focuses only on molecular methods for age estimation and neglects morphological approaches, whose importance should by no means be negated. It will be exciting to see how the repertoire of methods will develop in the future and how it will be used as best as possible in practice.
References
Ritz-Timme S, Cattaneo C, Collins MJ et al (2000) Age estimation: the state of the art in relation to the specific demands of forensic practise. Int J Legal Med. https://doi.org/10.1007/s004140050283
Adserias-Garriga J, Thomas C, Ubelaker DH et al (2018) When forensic odontology met biochemistry: multidisciplinary approach in forensic human identification. Arch Oral Biol 87:7–14. https://doi.org/10.1016/j.archoralbio.2017.12.001
Maulani C, Auerkari EI (2020) Age estimation using DNA methylation technique in forensics: a systematic review. Egypt J Forensic Sci 10:81. https://doi.org/10.1186/s41935-020-00214-2
Parson W (2018) Age estimation with DNA: from forensic DNA fingerprinting to forensic (Epi)Genomics: a mini-review. Gerontology 64:326–332. https://doi.org/10.1159/000486239
Zapico SC (2017) Mechanisms linking aging, diseases and biological age estimation. CRC Press, Portland
Meissner C, Ritz-Timme S (2010) Molecular pathology and age estimation. Forensic Sci Int 203:34–43. https://doi.org/10.1016/j.forsciint.2010.07.010
Ritz-Timme S, Collins MJ (2002) Racemization of aspartic acid in human proteins. Ageing Res Rev 1:43–59. https://doi.org/10.1016/S0047-6374(01)00363-3
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 117:96–101. https://doi.org/10.1007/s00414-002-0355-2
Klumb K, Matzenauer C, Reckert A et al (2016) Age estimation based on aspartic acid racemization in human sclera. Int J Legal Med 130:207–211. https://doi.org/10.1007/s00414-015-1255-6
Ohtani S, Matsushima Y, Kobayashi Y et al (1998) Evaluation of aspartic acid racemization ratios in the human femur for age estimation. J Forensic Sci 43:949–953
Ohtani S, Yamamoto T, Abe I et al (2007) Age-dependent changes in the racemisation ratio of aspartic acid in human alveolar bone. Arch Oral Biol 52:233–236. https://doi.org/10.1016/j.archoralbio.2006.08.011
Pfeiffer H, Mörnstad H, Teivens A (1995) Estimation of chronologic age using the aspartic acid racemization method. I. On human rib cartilage. Int J Legal Med 108:19–23. https://doi.org/10.1007/BF01845611
Chen S, Lv Y, Wang D et al (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
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 55:22–29. https://doi.org/10.1177/0025802414524383
Rastogi M, Logani A, Shah N et al (2017) Age estimation of living Indian individuals based on aspartic acid racemization from tooth biopsy specimen. J Forensic Dent Sci 9:83–90. https://doi.org/10.4103/jfo.jfds_21_16
Wochna K, Bonikowski R, Śmigielski J et al (2018) Aspartic acid racemization of root dentin used for dental age estimation in a Polish population sample. Forensic Sci Med Pathol 14:285–294. https://doi.org/10.1007/s12024-018-9984-8
Chaudhuri J, Bains Y, Guha S et al (2018) The role of advanced glycation end products in aging and metabolic diseases: bridging association and causality. Cell Metab 28:337–352. https://doi.org/10.1016/j.cmet.2018.08.014
Soboleva A, Schmidt R, Vikhnina M et al (2017) Maillard proteomics: opening new pages. Int J Mol Sci. https://doi.org/10.3390/ijms18122677
Valenzuela A, Guerra-Hernández E, Rufián-Henares JÁ et al (2018) Differences in non-enzymatic glycation products in human dentine and clavicle: changes with aging. Int J Legal Med 132:1749–1758. https://doi.org/10.1007/s00414-018-1908-3
Greis F, Reckert A, Fischer K et al (2018) Analysis of advanced glycation end products (AGEs) in dentine: useful for age estimation? Int J Legal Med 132:799–805. https://doi.org/10.1007/s00414-017-1671-x
Becker J, Mahlke NS, Reckert A et al (2020) Age estimation based on different molecular clocks in several tissues and a multivariate approach: an explorative study. Int J Legal Med 134:721–733. https://doi.org/10.1007/s00414-019-02054-9
Arakawa S, Suzuki R, Kurosaka D et al (2020) Mass spectrometric quantitation of AGEs and enzymatic crosslinks in human cancellous bone. Sci Rep 10:18774. https://doi.org/10.1038/s41598-020-75923-8
Daunay A, Baudrin LG, Deleuze J‑F et al (2019) Evaluation of six blood-based age prediction models using DNA methylation analysis by pyrosequencing. Sci Rep 9:8862. https://doi.org/10.1038/s41598-019-45197-w
Fleckhaus J, Schneider PM (2020) Novel multiplex strategy for DNA methylation-based age prediction from small amounts of DNA via pyrosequencing. Forensic Sci Int Genet 44:102189. https://doi.org/10.1016/j.fsigen.2019.102189
Freire-Aradas A, Pośpiech E, Aliferi A et al (2020) A comparison of forensic age prediction models using data from four DNA methylation technologies. Front Genet 11:932. https://doi.org/10.3389/fgene.2020.00932
Naue J, Sänger T, Hoefsloot HCJ et al (2018) Proof of concept study of age-dependent DNA methylation markers across different tissues by massive parallel sequencing. Forensic Sci Int Genet 36:152–159. https://doi.org/10.1016/j.fsigen.2018.07.007
Xu Y, Li X, Yang Y et al (2019) Human age prediction based on DNA methylation of non-blood tissues. Comput Methods Programs Biomed 171:11–18. https://doi.org/10.1016/j.cmpb.2019.02.010
Correia Dias H, Corte-Real F, Cunha E et al (2020) DNA methylation age estimation from human bone and teeth. Aust J Forensic Sci 29:1–14. https://doi.org/10.1080/00450618.2020.1805011
Jung S‑E, Lim SM, Hong SR et al (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
Woźniak A, Heidegger A, Piniewska-Róg D et al (2021) Development of the VISAGE enhanced tool and statistical models for epigenetic age estimation in blood, buccal cells and bones. Aging (Albany NY). https://doi.org/10.18632/aging.202783
Alkass K, Buchholz BA, Druid H et al (2011) Analysis of 14C and 13C in teeth provides precise birth dating and clues to geographical origin. Forensic Sci Int 209:34–41. https://doi.org/10.1016/j.forsciint.2010.12.002
Alkass K, Saitoh H, Buchholz BA et al (2013) Analysis of radiocarbon, stable isotopes and DNA in teeth to facilitate identification of unknown decedents. PLoS ONE 8:e69597. https://doi.org/10.1371/journal.pone.0069597
Spalding KL, Buchholz BA, Bergman L‑E et al (2005) Forensics: age written in teeth by nuclear tests. Nature 437:333–334. https://doi.org/10.1038/437333a
Johnstone-Belford EC, Blau S (2020) A review of bomb pulse dating and its use in the investigation of unidentified human remains. J Forensic Sci 65:676–685. https://doi.org/10.1111/1556-4029.14227
Arany S, Ohtani S, Yoshioka N et al (2004) Age estimation from aspartic acid racemization of root dentin by internal standard method. Forensic Sci Int 141:127–130. https://doi.org/10.1016/j.forsciint.2004.01.017
Ritz S, Stock R, Schütz HW et al (1995) Age estimation in biopsy specimens of dentin. Int J Legal Med 108:135–139. https://doi.org/10.1007/BF01844824
Ritz-Timme S, Rochholz G, Schütz HW et al (2000) Quality assurance in age estimation based on aspartic acid racemisation. Int J Legal Med 114:83–86. https://doi.org/10.1007/s004140000159
Ritz S, Schtz H‑W, Schwarzer B (1990) The extent of aspartic acid racemization in dentin: a possible method for a more accurate determination of age at death? Z Rechtsmed. https://doi.org/10.1007/BF00204710
Ritz-Timme S, Rochholz G, Stammert R et al (2002) Biochemische Altersschätzung Zur Frage genetischer und soziokultureller (ethnischer) Einflüsse auf die Razemisierung von Asparaginsäure in Dentin. Rechtsmedizin 12:203–206. https://doi.org/10.1007/s00194-002-0152-8
Mahlke NS, Renhart S, Talaa D et al (2021) Molecular clocks in ancient proteins: do they reflect the age at death even after millennia? Int J Legal Med. https://doi.org/10.1007/s00414-021-02522-1
Koop BE, Reckert A, Becker J et al (2020) Epigenetic clocks may come out of rhythm-implications for the estimation of chronological age in forensic casework. Int J Legal Med 134:2215–2228. https://doi.org/10.1007/s00414-020-02375-0
Declerck K, Vanden Berghe W (2018) Back to the future: epigenetic clock plasticity towards healthy aging. Mech Ageing Dev 174:18–29. https://doi.org/10.1016/j.mad.2018.01.002
Dhingra R, Nwanaji-Enwerem JC, Samet M et al (2018) DNA methylation age-environmental influences, health impacts, and its role in environmental epidemiology. Curr Environ Health Rep 5:317–327. https://doi.org/10.1007/s40572-018-0203-2
Rösing FW, Kvaal SI (1998) Dental age in adults — a review of estimation methods. In: Alt KW, Rösing FW, Teschler-Nicola M (eds) Dental anthropology: fundamentals, limits and prospects. Springer Vienna, Vienna, pp 443–468
Shi L, Jiang F, Ouyang F et al (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
Koop BE, Mayer F, Gündüz T et al (2021) Postmortem age estimation via DNA methylation analysis in buccal swabs from corpses in different stages of decomposition—a “proof of principle” study. Int J Legal Med 135:167–173. https://doi.org/10.1007/s00414-020-02360-7
Ritz-Timme S (1999) Lebensaltersbestimmung aufgrund des Razemisierungsgrades von Asparaginsäure: Grundlagen, Methodik, Möglichkeiten, Grenzen, Anwendungsbereiche ; mit 6 Tabellen. Arbeitsmethoden der medizinischen und naturwissenschaftlichen Kriminalistik vol 23. Schmidt-Römhild, Lübeck
Pilin A, Cabala R, Pudil F et al (2001) The use of the D‑, L‑ aspartic ratio in decalcified collagen from human dentin as an estimator of human age. J Forensic Sci 46:1228–1231
Siahaan T, Reckert A, Becker J et al (2021) Molecular and morphological findings in a sample of oral surgery patients: what can we learn for multivariate concepts for age estimation? J Forensic Sci. https://doi.org/10.1111/1556-4029.14704
Ohtani S, Yamamoto T (2010) Age estimation by amino acid racemization in human teeth. J Forensic Sci 55:1630–1633. https://doi.org/10.1111/j.1556-4029.2010.01472.x
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. https://doi.org/10.1002/ajpa.22921
Bekaert B, Kamalandua A, Zapico SC et al (2015) Improved age determination of blood and teeth samples using a selected set of DNA methylation markers. Epigenetics 10:922–930. https://doi.org/10.1080/15592294.2015.1080413
Márquez-Ruiz AB, González-Herrera L, Luna JD et al (2020) DNA methylation levels and telomere length in human teeth: usefulness for age estimation. Int J Legal Med. https://doi.org/10.1007/s00414-019-02242-7
Ritz S, Turzynski A, Schütz HW et al (1996) Identification of osteocalcin as a permanent aging constituent of the bone matrix: basis for an accurate age at death determination. Forensic Sci Int 77:13–26. https://doi.org/10.1016/0379-0738(95)01834-4
Ritz-Timme S, Laumeier I, Collins MJ (2003) Aspartic acid racemization: evidence for marked longevity of elastin in human skin. Br J Dermatol 149:951–959. https://doi.org/10.1111/j.1365-2133.2003.05618.x
Shapiro SD, Endicott SK, Province MA et al (1991) Marked longevity of human lung parenchymal elastic fibers deduced from prevalence of D‑aspartate and nuclear weapons-related radiocarbon. J Clin Invest 87:1828–1834. https://doi.org/10.1172/JCI115204
Dobberstein RC, Tung SM, Ritz-Timme S (2010) Aspartic acid racemisation in purified elastin from arteries as basis for age estimation. Int J Legal Med. https://doi.org/10.1007/s00414-009-0392-1
Verzijl N, DeGroot J, Thorpe SR et al (2000) Effect of collagen turnover on the accumulation of advanced glycation end products. J Biol Chem 275:39027–39031. https://doi.org/10.1074/jbc.M006700200
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 128:995–1000. https://doi.org/10.1007/s00414-013-0940-6
Pillin A, Pudil F, Bencko V et al (2007) Contents of pentosidine in the tissue of the intervertebral disc as an indicator of the human age. Soud Lek 52:60–64
Dias HC, Cordeiro C, Pereira J et al (2020) DNA methylation age estimation in blood samples of living and deceased individuals using a multiplex SNaPshot assay. Forensic Sci Int 311:110267. https://doi.org/10.1016/j.forsciint.2020.110267
Schmeling A, Grundmann C, Fuhrmann A et al (2008) Aktualisierte Empfehlungen der Arbeitsgemeinschaft für Forensische Altersdiagnostik für Altersschätzungen bei Lebenden im Strafverfahren. Rechtsmedizin 18:451–453. https://doi.org/10.1007/s00194-008-0571-2
Zbieć-Piekarska R, Spólnicka 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. https://doi.org/10.1016/j.fsigen.2015.05.001
Cho S, Jung S‑E, Hong SR 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.2017.04.020
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. https://doi.org/10.1016/j.fsigen.2017.07.015
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. https://doi.org/10.1186/gb-2014-15-2-r24
Montesanto A, D’Aquila P, Lagani V et al (2020) A new robust epigenetic model for forensic age prediction. J Forensic Sci 65:1424–1431. https://doi.org/10.1111/1556-4029.14460
Al-Ghanmy HSG, Al-Rashedi NAM, Ayied AY (2021) Age estimation by DNA methylation levels in Iraqi subjects. Gene Rep 23:101022. https://doi.org/10.1016/j.genrep.2021.101022
Aliferi A, Ballard D, Gallidabino MD et al (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
Thong Z, Chan XLS, Tan JYY et al (2017) Evaluation of DNA methylation-based age prediction on blood. Forensic Sci Int Genet Suppl Ser 6:e249–e251. https://doi.org/10.1016/j.fsigss.2017.09.095
Naue J, Hoefsloot HCJ, Kloosterman AD et al (2018) Forensic DNA methylation profiling from minimal traces: how low can we go? Forensic Sci Int Genet 33:17–23. https://doi.org/10.1016/j.fsigen.2017.11.004
Lee JW, Choung CM, Jung JY et al (2018) A validation study of DNA methylation-based age prediction using semen in forensic casework samples. Leg Med (Tokyo) 31:74–77. https://doi.org/10.1016/j.legalmed.2018.01.005
Hong SR, Jung S‑E, Lee EH et al (2017) DNA methylation-based age prediction from saliva: high age predictability by combination of 7 CpG markers. Forensic Sci Int Genet 29:118–125. https://doi.org/10.1016/j.fsigen.2017.04.006
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Böhme, P., Reckert, A., Becker, J. et al. Molecular methods for age estimation. Rechtsmedizin 31, 177–182 (2021). https://doi.org/10.1007/s00194-021-00490-9
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DOI: https://doi.org/10.1007/s00194-021-00490-9