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Warning Text %XTableStyleMedium9PivotStyleMedium7`4}Table S1S pLocus CpG location in custom referenceInternal CpG nameStrand analysedCpG_IDInclusion in the modelsBlood Buccal cellsBonesZbie-Piekarska et al., 2015Wozniak&Heidegger et al., 2020Standardized Coefficient  tP-valueR2 MIR29B2CHGC3chr1:207823672+ YesC2chr1:207823675 cg10501210C1chr1:207823681EDARADD- cg09809672FHL2chr2:105399282 cg06639320chr2:105399288chr2:105399291C4chr2:105399297C5chr2:105399300C6chr2:105399310 cg22454769C7chr2:105399314 cg24079702C8chr2:105399316C9chr2: 105399323C10chr2: 105399327TRIM59chr3:160450172chr3:160450174chr3:160450179chr3:160450184chr3:160450189 cg07553761chr3:160450192chr3:160450199chr3:160450202ELOVL2 chr6:11044628 chr6:11044631 chr6:11044634 chr6:11044640 chr6:11044642 chr6:11044644 cg16867657 chr6:11044647 chr6:11044655 cg24724428 chr6:11044661 cg21572722KLF14chr7:130734355 cg14361627chr7:130734357chr7:130734372chr7:130734375ASPA chr17:3476273 cg02228185PDE4Cchr19:18233079chr19:18233082chr19:18233091 cg17861230chr19:18233105chr19:18233127chr19:18233131 cg01481989chr19:18233133ELOVL2*chr1:236394371chr1:236394383429*435*C9*C7*chr6:11044628*chr6:11044634*Yes*?GRCh38 Chr:position (reported according to the analysed strand)s*the results of univariate regression analysis applied for the power transformed DNA methylation data are presentedN/A References:s1. Hannum G, Guinney J, Zhao L, Zhang L, Hughes G, Sadda S, Klotzle B, Bibikova M, Fan JB, 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. Mol Cell. 2013 Jan 24;49(2):359-367. doi: 10.1016/j.molcel.2012.10.016. Epub 2012 Nov 21. PMID: 23177740; PMCID: PMC3780611.P2. Zbie-Piekarska R, Splnicka M, Kupiec T, Parys-Proszek A, Makowska {, PaBeczka A, Kucharczyk K, PBoski R, Branicki W. (2015). Development of a forensically useful age prediction method based on DNA methylation analysis. Forensic Sci Int Genet. 2015 Jul;17:173-179. doi: 10.1016/j.fsigen.2015.05.001. Epub 2015 May 5. PMID: 26026729.3. Cho, S., Jung, S. E., Hong, S. R., Lee, E. H., Lee, J. H., Lee, S. D., & Lee, H. Y. (2017). Independent validation of DNA-based approaches for age prediction in blood. Forensic Sci. Int. Genet., 29, 250 256.4. Thong Z., Chan X.L.S. ,Tan J.Y.Y., Loo E.S., Syn C.K.C., (2017).Evaluation of DNA methylation-based age prediction on blood, Forensic Sci. Int. Genet. Supplement Series, 6, e249 e251. https://doi.org/10.1016/j.fsigss.2017.09.0955. Daunay, A., Baudrin, L.G., Deleuze, JF. 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-w6. Fleckhaus, Jan & Schneider, Peter M.. (2019). Novel multiplex strategy for DNA methylation-based age prediction from small amounts of DNA via Pyrosequencing. Forensic Science International: Genetics. 44. 102189. 10.1016/j.fsigen.2019.102189. 7. Smeers, I., Decorte, R., Van de Voorde, W., and Bekaert, B. (2018). Evaluation of three statistical prediction models for forensic age prediction based on DNA methylation. Foren. Sci. Int. Genet. 34, 128 133. doi: 10.1016/j.fsigen.2018.02.008 8. Bekaert, B., Kamalandua, A., Zapico, S. C., 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/10.1080/15592294.2015.10804139. Freire-Aradas, A., Phillips, C., Mosquera-Miguel, A., Girn-Santamara, L., Gmez-Tato, A., Cal, M. C. de, lvarez-Dios, J., Ansede-Bermejo, J., Torres-Espaol, M., Schneider, P. M., Po[piech, E., Branicki, W., Carracedo, ., & Lareu, M. V. (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 74.10. Zubakov, D., Liu, F., Kokmeijer, I., Choi, Y., van Meurs, J. B. J., van IJcken, W. F. J., et al. (2016). Human age estimation from blood using mRNA, DNA methylation, DNA rearrangement, and telomere length. Foren. Sci. Int. Genet. 24, 33 43. doi: 10.1016/j.fsigen.2016.05.01411. Bocklandt, S., Lin, W., Sehl, M. E., Snchez, F. J., Sinsheimer, J. S., Horvath, S., & Vilain, E. (2011). Epigenetic predictor of age. PLoS One, 6.12. Pan C., Yi S., Xiao C., Huang Y., Chen X., Huang D. (2020). The evaluation of seven age-related CpGs for forensic purpose in blood from Chinese Han population, Forensic Sci. Int. Genet., 46, 102251. https://doi.org/10.1016/j.fsigen.2020.102251G13. Jung, S. E., Lim, S. M., Hong, S. R., Lee, E. H., Shin, K. J., & Lee, H. Y. (2019). DNA methylation of the ELOVL2, FHL2, KLF14, C1orf132/MIR29B2C, and TRIM59 genes for age prediction from blood, saliva, and buccal swab samples. Forensic Science International: Genetics, 38, 1 8. https://doi.org/10.1016/j.fsigen.2018.09.010`14. Zbie-Piekarska R, Splnicka M, Kupiec T, Makowska {, Spas A, Parys-Proszek A, Kucharczyk K, PBoski R, Branicki W (2015). Examination of DNA methylation status of the ELOVL2 marker may be useful for human age prediction in forensic science. Forensic Sci Int Genet. Jan;14:161-7. doi:< 10.1016/j.fsigen.2014.10.002. Epub 2014 Oct 14. PMID: 25450787.15. Park, J. L., Kim, J. H., Seo, E., Bae, D. H., Kim, S. Y., Lee, H. C., et al. (2016). Identification and evaluation of age-correlated DNA methylation markers for forensic use. Forens. Sci. Int. Genet. 23, 64 70. doi: 10.1016/j.fsigen.2016.03.00516. Slieker, R. C., Relton, C. L., Gaunt, T. R., Slagboom, P. E., & Heijmans, B. T. (2018). Age-related DNA methylation changes are tissue-specific with ELOVL2 promoter methylation as exception. Epigenetics Chromatin, 11, 25.X17. Weidner, C. I., Lin, Q., Koch, C. M., Eisele, L., Beier, F., Ziegler, P., Bauerschlag, D. O., Jckel, K. H., Erbel, R., Mhleisen, T. W., Zenke, M., Brmmendorf, 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-r24O18. Eipel, M., Mayer, F., Arent, T., Ferreira, M. R. P., Birkhofer, C., Gerstenmaier, U., Costa, I. G., Ritz-Timme, S., & Wagner, W. (2016). Epigenetic age predictions based on buccal swabs are more precise in combination with cell type-specific DNA methylation signatures. Aging, 8(5), 1034 1048. https://doi.org/10.18632/aging.10097219. Huang, J. Yan, J. Hou, X. Fu, L. Li, Y. Hou (2015). Developing a DNA methylation assay for human age prediction in blood and bloodstain, Forensic Sci. Int. Genet. 17 129 136. https://doi.org/10.1016/j.fsigen.2015.05.00720. Xu, C., Qu, H., Wang, G., Xie, B., Shi, Y., Yang, Y., et al. (2015). A novel strategy for forensic age prediction by DNA methylation and support vector regression model. Sci. Rep. 5:17788. [1,2,3,4,5] [1,2,3,4,5,6][5,7][5,8,9,10,11,12][1,2,3,4,5,9,12,13][3,8,10][8][1,3][1,2,3,4,5,8,10,14][1,2,3,4,5,8,14][1,2,3,4,5,14][1,2,3,4,5,14,15,16][1,2,3,4,5,9,10,14,15][1,2,3,4,5,12][1,2,3,4,5,13][5,8,9,11,12,17,18,19][5,6,9][5,6,8,9,11,17][5,6,8,9,17,18,20] [5,6,9,20][6,8,9,17,18,20][6,9,20] ReferencesSupplementary Table 1. 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