- •The same amplicons from the same samples allow to reveal the differences dependent on the DNA methylation analysis methods.
- •There were high degrees of positive correlation between single-base extension and massively parallel sequencing results.
- •Despite high correlations between the two methods, detected DNA methylation status was not identical in most markers.
- •Rather than exploiting integrated models, applying method-specific models would achieve higher accuracy in age prediction.
Purchase one-time access:Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
One-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:Subscribe to Forensic Science International: Genetics
- Epigenetic predictor of age.PLoS One. 2011; 6e14821https://doi.org/10.1371/journal.pone.0014821
- DNA methylation age of human tissues and cell types.Genome Biol. 2013; 14: R115https://doi.org/10.1186/gb-2013-14-10-r115
- Genome-wide methylation profiles reveal quantitative views of human aging rates.Mol. Cell. 2013; 49: 359-367https://doi.org/10.1016/j.molcel.2012.10.016
- DNA methylation-based age prediction from various tissues and body fluids.BMB Rep. 2017; 50: 546-553https://doi.org/10.5483/BMBRep.2017.50.11.175
- Recent progress, methods and perspectives in forensic epigenetics.Forensic Sci. Int Genet. 2018; 37: 180-195https://doi.org/10.1016/j.fsigen.2018.08.008
- Development of a forensically useful age prediction method based on DNA methylation analysis.Forensic Sci. Int Genet. 2015; 17: 173-179https://doi.org/10.1016/j.fsigen.2015.05.001
- Development of the VISAGE enhanced tool and statistical models for epigenetic age estimation in blood, buccal cells and bones.Aging. 2021; 13: 6459-6484https://doi.org/10.18632/aging.202783
- Development and inter-laboratory validation of the VISAGE enhanced tool for age estimation from semen using quantitative DNA methylation analysis.Forensic Sci. Int.: Genet. 2022; 56102596https://doi.org/10.1016/j.fsigen.2021.102596
- der Deutschen Gesellschaft für, Forensische DNA-Methylierungsanalyse.Rechtsmedizin. 2021; 31: 202-216https://doi.org/10.1007/s00194-021-00493-6
- A collaborative exercise on DNA methylation-based age prediction and body fluid typing.Forensic Sci. Int.: Genet. 2022; 57https://doi.org/10.1016/j.fsigen.2021.102656
- Genetic analyzer-dependent DNA methylation detection and its application to existing age prediction models.ELECTROPHORESIS. 2021; 42: 1497-1506https://doi.org/10.1002/elps.202000312
- Platform-independent models for age prediction using DNA methylation data.Forensic Sci. Int Genet. 2019; 38: 39-47https://doi.org/10.1016/j.fsigen.2018.10.005
- A comparison of forensic age prediction models using data from four DNA methylation technologies.Front Genet. 2020; 11: 932https://doi.org/10.3389/fgene.2020.00932
- 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. 2019; 38: 1-8https://doi.org/10.1016/j.fsigen.2018.09.010
- Bisulfite-converted DNA quantity evaluation: a multiplex quantitative real-time PCR system for evaluation of bisulfite conversion.Front. Genet. 2021; 12: 173
- Independent validation of DNA-based approaches for age prediction in blood.Forensic Sci. Int Genet. 2017; 29: 250-256https://doi.org/10.1016/j.fsigen.2017.04.020
- BiSulfite bolt: a bisulfite sequencing analysis platform.Gigascience. 2021; 10: giab033https://doi.org/10.1093/gigascience/giab033
- A guideline of selecting and reporting intraclass correlation coefficients for reliability research.J. Chiropr. Med. 2016; 15: 155-163https://doi.org/10.1016/j.jcm.2016.02.012
H. Passing, W. Bablok, A. New Biometrical Procedure for Testing the Equality of Measurements from Two Different Analytical Methods. Application of linear regression procedures for method comparison studies in Clinical Chemistry, Part I, in, A New Biometrical Procedure for Testing the Equality of Measurements from Two Different Analytical Methods. Application of linear regression procedures for method comparison studies in Clinical Chemistry, Part I, Kooperation de Gruyter, 1983.
- Identification and evaluation of age-correlated DNA methylation markers for forensic use.Forensic Sci. Int Genet. 2016; 23: 64-70https://doi.org/10.1016/j.fsigen.2016.03.005
- Combining current knowledge on DNA methylation-based age estimation towards the development of a superior forensic DNA intelligence tool.Forensic Sci. Int Genet. 2022; 57102637https://doi.org/10.1016/j.fsigen.2021.102637
- DNA methylation age estimation in blood samples of living and deceased individuals using a multiplex SNaPshot assay.Forensic Sci. Int. 2020; 311110267https://doi.org/10.1016/j.forsciint.2020.110267
- Forensic DNA methylation profiling from minimal traces: How low can we go?.Forensic Sci. Int Genet. 2018; 33: 17-23https://doi.org/10.1016/j.fsigen.2017.11.004
- DNA methylation-based age prediction using massively parallel sequencing data and multiple machine learning models.Forensic Sci. Int.: Genet. 2018; 37: 215-226https://doi.org/10.1016/j.fsigen.2018.09.003
- DNA methylation-based forensic age prediction using artificial neural networks and next generation sequencing.Forensic Sci. Int Genet. 2017; 28: 225-236https://doi.org/10.1016/j.fsigen.2017.02.009
- Systematic feature selection improves accuracy of methylation-based forensic age estimation in Han Chinese males.Forensic Sci. Int Genet. 2018; 35: 38-45https://doi.org/10.1016/j.fsigen.2018.03.009
- DNA methylation-based age prediction from saliva: High age predictability by combination of 7 CpG markers.Forensic Sci. Int Genet. 2017; 29: 118-125https://doi.org/10.1016/j.fsigen.2017.04.006