Epigenetics or “beyond Genetics” Part II
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Keywords

genetics, epigenetics, gene expression, ridgeology

How to Cite

Epigenetics or “beyond Genetics” Part II. (2025). Academic Journal of Internal Affairs, 73(8), 1617-1635. https://doi.org/10.38146/bsz-ajia.2025.v73.i8.pp1617-1635

Abstract

Aim: The authors of the two-part study describe a recently emerging scientific field, epigenetics, based on published literature data, and in this second part, they present results achieved in the domain of forensic sciences – genetics and ridgeology.

Methodology: The study reviews and synthesizes the articles on the epigenetic basis of fingerprint development and DNA-based biological age estimation. It also describes research results on identical twins.

Findings: Surprisingly little is known about the factors that influence the pattern formed by the dermal ridges. Related individuals have more similar fingerprints than unrelated individuals, suggesting that the formation of dermal ridge system is genetically controlled and that the size, shape, and spacing of the ridges are also influenced by genetic factors. In the formation process, small random events influence the formation of individual minutiae, which are therefore epigenetic effects. All external and internal environmental factors can cause chemical modifications in our genes, turn them on or off over time. DNA methylation patterns can be used to determine biological age (epigenetic clock). Knowing how old someone is at the epigenetic level can not only provide insight into an individual's biological clock but can also provide important investigative data in law enforcement. Age estimation is a critical aspect of reconstructing a biological profile in forensic science. Epigenetic clocks, which analyze DNA sections that undergo hypermethylation or hypomethylation as individuals age, are the best predictive models of age.

Value: The study provides comprehensive findings of the molecular background of epigenetic inheritance through published literature studies on the development of dermal ridges and DNA age estimation and offers actionable suggestions for slowing down the epigenetic clock.

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References

Alberti, A., Traebert, J., Traebert, E., Nodari Junior, R. J., & Comim, C. M. (2021). Association between gestational period and obesity in children with the use of dermatoglyphic traits: A preliminary study. PLOS ONE, 16(9), e0257153. https://doi.org/10.1371/journal.pone.0257153

Aourangzaib, M., Chandra, M., Maham, R., Naz, A., Malathi, H., Qadeer, S., Mateen, R. M., & Parveen, R. (2024). Solving the twin paradox – Forensic strategies to identify the identical twins. Forensic Science International, 363, 112205. https://doi.org/10.1016/j.forsciint.2024.112205

Ashbaugh, D. R. (1999). Quantitative-qualitative friction ridge analysis. CRC Press.

Chaitanya, L., Breslin, K., Zuñiga, S., Wirken, L., Pośpiech, E., Kukla-Bartoszek, M., Sijen, T., Knijff, P., Liu, F., Branicki, W., Kayser, M., & Walsh, S. (2018). The HIrisPlex-S system for eye, hair and skin colour prediction from DNA: Introduction and forensic developmental validation. Forensic Science International: Genetics, 35, 123–135. https://doi.org/10.1016/j.fsigen.2018.04.004

Champod, C., Lennard, C. J., Margot, P., & Stoilovic, M. (2016). Fingerprints and other ridge skin impressions. CRC Press.

Dale, C. (2004). The practice of crime scene investigation. CRC Press.

Dias, H. C., Cunha, E., Real, F. C., & Manco, L. (2022). Challenges and (un)certainties for DNAm age estimation in future. Forensic Sciences, 2(3), 601–614. https://doi.org/10.3390/forensicsci2030044

Fiorito, G., McCrory, C., Robinson, O., Carmeli, C., Rosales, C. O., Zhang, Y., Colicino, E., Dugué, P. A., Artaud, F., McKay, G. J., Jeong, A., Mishra, P. P., Nøst, T. H., Krogh, V., Panico, S., Sacerdote, C., Tumino, R., Palli, D., Matullo, G., … Polidoro, S. (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.101900

Garzón-Alvarado, D. A., & Ramírez Martinez, A. M. (2011). A biochemical hypothesis on the formation of fingerprints using a Turing patterns approach. Theoretical Biology and Medical Modelling, 8, 24. https://doi.org/10.1186/1742-4682-8-24

Glover, J. D., Sudderick, Z. R., Shih, B. B., Batho-Samblas, C., Charlton, L., Krause, A. L., Anderson, C., Riddell, J., Balic, A., Li, J. X., Klika, V., Woolley, T. E., Gaffney, E. A., Corsinotti, A., Anderson, R. A., Johnston, L. J., Brown, S. J., Wang, S., Chen, Y. H., Crichton, M. L., & Headon, D. J. (2023). The developmental basis of fingerprint pattern formation and variation. Cell, 186(5), 940–956. https://doi.org/10.1016/j.cell.2023.01.015

Guardiola Ripoll, M., Sotero Moreno, A., Chaumette, B., Kebir, O., Hostalet, N., Almodóvar Payá, C., Moreira, M., Giralt López, M., Krebs, M. O., & Fatjó Vilas, M. (2024). Genetic and neurodevelopmental markers in schizophrenia spectrum disorders: Analysis of the combined role of the CNR1 gene and dermatoglyphics. Biomedicines, 12(10), 2270. https://doi.org/10.3390/biomedicines12102270

Hannum, G., Guinney, J., Zhao, L., Zhang, L., Hughes, G., Sadda, S., Klotzle, B., Bibikova, M., Fan, J. B., Gao, Y., Deconde, R., Chen, M., Rajapakse, I., Friend, S., Ideker, T., & Zhang, K. (2013). Genome wide methylation profiles reveal quantitative views of human aging rates. Molecular Cell, 49(2), 359–367. https://doi.org/10.1016/j.molcel.2012.10.016

Hawthorne, M. R. (2008). Fingerprint pattern types and associated terminology. In Fingerprints (pp. 27–54). CRC Press.

Hefetz, I., Pasternak, Z., Liptz, Y., & Bet Yosef, M. (2022). Preliminary investigation of the ability of fingerprint examiners in detection of sib sib relationships based upon finger and palm prints similarities. Forensic Science International, 337, 111381. https://doi.org/10.1016/j.forsciint.2022.111381

Ho, Y. Y. W., Evans, D. M., Montgomery, G. W., Henders, A. K., Kemp, J. P., Timpson, N. J., St Pourcain, B., Heath, A. C., Madden, P. A. F., Loesch, D. Z., McNevin, D., Daniel, R., Davey Smith, G., Martin, N. G., & Medland, S. E. (2016). Common genetic variants influence whorls in fingerprint patterns. Journal of Investigative Dermatology, 136(4), 859–862. https://doi.org/10.1016/j.jid.2015.10.062

Holt, S. B. (1968). The genetics of dermal ridges. Charles C Thomas.

Hong, S. R., Jung, S. E., Lee, E. H., Shin, K. J., Yang, W. I., & Lee, H. Y. (2017). DNA methylation based age prediction from saliva: High age predictability by combination of 7 CpG markers. Forensic Science International: Genetics, 29, 118–125. https://doi.org/10.1016/j.fsigen.2017.04.006

Horvath, S. (2013). DNA methylation age of human tissues and cell types. Genome Biology, 14(10), R115. https://doi.org/10.1186/gb-2013-14-10-r115

Horvath, S., & Raj, K. (2018). DNA methylation based biomarkers and the epigenetic clock theory of ageing. Nature Reviews Genetics, 19(6), 371–384. https://doi.org/10.1038/s41576-018-0004-3

Horvath, S., Zhang, Y., Langfelder, P., Kahn, R. S., Boks, M. P. M., van Eijk, K., van den Berg, L. H., & Ophoff, R. A. (2012). Aging effects on DNA methylation modules in human brain and blood tissue. Genome Biology, 13(10), R97. https://doi.org/10.1186/gb-2012-13-10-r97

Hwa, H. L., Lin, C. Y., Yu, Y. J., Linacre, A., & Lee, J. C. I. (2024). DNA identification of monozygotic twins. Forensic Science International: Genetics, 69, Article 102998. https://doi.org/10.1016/j.fsigen.2023.102998

Irmak, M. K. (2010). Multifunctional Merkel cells: Their roles in electromagnetic reception, finger print formation, Reiki, epigenetic inheritance and hair form. Medical Hypotheses, 75(2), 162–168. https://doi.org/10.1016/j.mehy.2010.02.011

Jin, X., Ren, Z., Zhang, H., Wang, Q., Liu, Y., Ji, J., & Huang, J. (2022). Systematic selection of age-associated mRNA markers and the development of predicted models for forensic age inference by three machine learning methods. Frontiers in Genetics, 13, Article 924408. https://doi.org/10.3389/fgene.2022.924408

Kattamreddy, A. R. (2023). Cracking the code: Can forensic genetics distinguish identical twins? A technical perspective. Sri Lanka Journal of Forensic Medicine, Science & Law, 14(2), 46–51. https://doi.org/10.4038/sljfmsl.v14i2.7938

Lee, H. Y., Jung, S. E., Lee, E. H., Yang, W. I., & Shin, K. J. (2016). DNA methylation profiling for a confirmatory test for blood, saliva, semen, vaginal fluid and menstrual blood. Forensic Science International: Genetics, 24, 75–82. https://doi.org/10.1016/j.fsigen.2016.06.007

Li, J., Glover, J. D., Zhang, H., Peng, M., Tan, J., Mallick, C. B., Hou, D., Yang, Y., Wu, S., Liu, Y., Peng, Q., Zheng, S. C., Crosse, E. I., Medvinsky, A., Anderson, R. A., Brown, H., Yuan, Z., Zhou, S., Xu, Y., Kemp, J. P., … Wang, S. (2022). Limb development genes underlie variation in human fingerprint patterns. Cell, 185(1), 95–112.e18. https://doi.org/10.1016/j.cell.2021.12.008

López Otín, C., Blasco, M. A., Partridge, L., Serrano, M., & Kroemer, G. (2013). The hallmarks of aging. Cell, 153(6), 1194–1217. https://doi.org/10.1016/j.cell.2013.05.039

López Otín, C., Blasco, M. A., Partridge, L., Serrano, M., & Kroemer, G. (2023). Hallmarks of aging: An expanding universe. Cell, 186(2), 243–278. https://doi.org/10.1016/j.cell.2022.11.001

Lujan, S. A., Longley, M. J., Humble, M. H., Lavender, C. A., Burkholder, A., Blakely, E. L., Alston, C. L., Gorman, G. S., Turnbull, D. M., McFarland, R., Taylor, R. W., Kunkel, T. A., & Copeland, W. C. (2020). Ultrasensitive deletion detection links mitochondrial DNA replication, disease, and aging. Genome Biology, 21, 248. https://doi.org/10.1186/s13059-020-02138-5

Mittelbrunn, M., & Kroemer, G. (2021). Hallmarks of T cell aging. Nature Immunology, 22(6), 687–698. https://doi.org/10.1038/s41590-021-00927-z

Naue, J., Hoefsloot, H. C. J., Kloosterman, A. D., & Verschure, P. J. (2018a). Forensic DNA methylation profiling from minimal traces: How low can we go? Forensic Science International: Genetics, 33, 17–23. https://doi.org/10.1016/j.fsigen.2017.11.004

Naue, J., Sänger, T., Hoefsloot, H. C. J., Lutz Bonengel, S., Kloosterman, A. D., & Verschure, P. J. (2018b). Proof of concept study of age dependent DNA methylation markers across different tissues by massive parallel sequencing. Forensic Science International: Genetics, 36, 152–159. https://doi.org/10.1016/j.fsigen.2018.07.007

O’Brien, G., & Murphy, K. (2020). Fingerprint patterns through genetics. Journal of Emerging Investigators, 2, Article 20 012. https://doi.org/10.59720/20-012

Petronis, A. (2006). Epigenetics and twins: Three variations on the theme. Trends in Genetics, 22(7), 347–350. https://doi.org/10.1016/j.tig.2006.04.010

Schneider, P. M., Prainsack, B., & Kayser, M. (2019). The use of forensic DNA phenotyping in predicting appearance and biogeographic ancestry. Deutsches Ärzteblatt International, 116(51–52), 873–880. https://doi.org/10.3238/arztebl.2019.0873

Srihari, S. N., Srinivasan, H., & Fang, G. (2008). Discriminability of fingerprints of twins. Journal of Forensic Identification, 58(1), 109–127.

Sturm, Á., Sharma, H., Bodnár, F., Aslam, M., Kovács, T., Németh, Á., Hotzi, B., Billes, V., Sigmond, T., Tátrai, K., Egyed, B., Téglás Huszár, B., Schlosser, G., Charmpilas, N., Ploumi, C., Perczel, A., Tavernarakis, N., & Vellai, T. (2023). N6 Methyladenine progressively accumulates in mitochondrial DNA during aging. International Journal of Molecular Sciences, 24(19), 14858. https://doi.org/10.3390/ijms241914858

Vaiserman, A., & Krasnienkov, D. (2021). Telomere length as a marker of biological age: State of the art, open issues, and future perspectives. Frontiers in Genetics, 11, Article 630186. https://doi.org/10.3389/fgene.2020.630186

Van Baak, T. E., Coarfa, C., Dugué, P.-A., Fiorito, G., Laritsky, E., Baker, M. S., Kessler, N. J., Dong, J., Duryea, J. D., Silver, M. J., Saffari, A., Prentice, A. M., Moore, S. E., Ghantous, A., Routledge, M. N., Gong, Y. Y., Herceg, Z., Vineis, P., Severi, G., … Waterland, R. A. (2018). Epigenetic supersimilarity of monozygotic twin pairs. Genome Biology, 19(1), 2. https://doi.org/10.1186/s13059-017-1374-0

van Dongen, J., Gordon, S. D., McRae, A. F., Odintsova, V. V., Mbarek, H., Breeze, C. E., Sugden, K., Lundgren, S., Castillo Fernandez, J. E., Hannon, E., Moffitt, T. E., Hagenbeek, F. A., van Beijsterveldt, C. E. M., Hottenga, J. J., Tsai, P. C., Min, J. L., Hemani, G., Ehli, E. A., Paul, F., … Boomsma, D. I. (2021). Identical twins carry a persistent epigenetic signature of early genome programming. Nature Communications, 12(1), 5618. https://doi.org/10.1038/s41467-021-25583-7

Vidaki, A., & Kayser, M. (2017). From forensic epigenetics to forensic epigenomics: Broadening DNA investigative intelligence. Genome Biology, 18, Article 238. https://doi.org/10.1186/s13059-017-1373-1

Vidaki, A., Ballard, D., Aliferi, A., Miller, T. H., Barron, L. P., & Syndercombe Court, D. (2017a). DNA methylation-based forensic age prediction using artificial neural networks and next generation sequencing. Forensic Science International: Genetics, 28, 225–236. https://doi.org/10.1016/j.fsigen.2017.02.009

Vidaki, A., Díez López, C., Carnero Montoro, E., Ralf, A., Ward, K., Spector, T., Bell, J. T., & Kayser, M. (2017b). Epigenetic discrimination of identical twins from blood under the forensic scenario. Forensic Science International: Genetics, 31, 67–80. https://doi.org/10.1016/j.fsigen.2017.07.014

Vidaki, A., Giangasparo, F., & Syndercombe Court, D. (2016). Discovery of potential DNA methylation markers for forensic tissue identification using bisulphite pyrosequencing. Electrophoresis, 37(21), 2767–2779. https://doi.org/10.1002/elps.201600261

Vidaki, A., Kalamara, V., Carnero Montoro, E., Spector, T. D., Bell, J. T., & Kayser, M. (2018). Investigating the epigenetic discrimination of identical twins using buccal swabs, saliva, and cigarette butts in the forensic setting. Genes, 9(5), Article 252. https://doi.org/10.3390/genes9050252

Walsh, S., Pośpiech, E., & Branicki, W. (2016). Hot on the trail of genes that shape our fingerprints. Journal of Investigative Dermatology, 136(4), 740–742. https://doi.org/10.1016/j.jid.2015.12.044

Weidner, C. I., Lin, Q., Koch, C. M., Eisele, L., Beier, F., Ziegler, P., Bauerschlag, D. O., Jöckel, K. H., Erbel, R., Mühleisen, T. W., Zenke, M., Brümmendorf, T. H., & Wagner, W. (2014). Aging of blood can be tracked by DNA methylation changes at just three CpG sites. Genome Biology, 15(2), R24. https://doi.org/10.1186/gb-2014-15-2-r24

Xiang, Z., Yang, Y., Chang, C., & Lu, Q. (2017). The epigenetic mechanism for discordance of autoimmunity in monozygotic twins. Journal of Autoimmunity, 83, 43–50. https://doi.org/10.1016/j.jaut.2017.04.003

Yet, I., Tsai, P. C., Castillo Fernandez, J. E., Carnero Montoro, E., & Bell, J. T. (2016). Genetic and environmental impacts on DNA methylation levels in twins. Epigenomics, 8(1), 105–117. https://doi.org/10.2217/epi.15.90

Zapico, S. C., & Ubelaker, D. H. (2022). Application of aspartic acid racemization for age estimation in a Spanish sample. Biology (Basel), 11(6), Article 856. https://doi.org/10.3390/biology11060856

Zbiec Piekarska, R., Spólnicka, M., Kupiec, T., Parys Proszek, A., Makowska, Ż., Pałeczka, A., Kucharczyk, K., Płoski, R., & Branicki, W. (2015). Development of a forensically useful age prediction method based on DNA methylation analysis. Forensic Science International: Genetics, 17, 173–179. https://doi.org/10.1016/j.fsigen.2015.05.001

Zgutka, K., Tkacz, M., Tomasiak, P., & Tarnowski, M. (2023). A role for advanced glycation end products in molecular ageing. International Journal of Molecular Sciences, 24(12), Article 9881. https://doi.org/10.3390/ijms24129881

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