The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Development of a forensically useful age prediction method based on DNA methylation analysis
Open accessAbstract
Forensic DNA phenotyping needs to be supplemented with age prediction to become a relevant source of information on human appearance. Recent progress in analysis of the human methylome has enabled selection of multiple candidate loci showing linear correlation with chronological age. Practical application in forensic science depends on successful validation of these potential age predictors. In this study, eight DNA methylation candidate loci were analysed using convenient and reliable pyrosequencing technology. A total number of 41 CpG sites was investigated in 420 samples collected from men and women aged from 2 to 75 years. The study confirmed correlation of all the investigated markers with human age. The five most significantly correlated CpG sites in ELOVL2 on 6p24.2, C1orf132 on 1q32.2, TRIM59 on 3q25.33, KLF14 on 7q32.3 and FHL2 on 2q12.2 were chosen to build a prediction model. This restriction allowed the technical analysis to be simplified without lowering the prediction accuracy significantly. Model parameters for a discovery set of 300 samples were R(2)=0.94 and the standard error of the estimate=4.5 years. An independent set of 120 samples was used to test the model performance. Mean absolute deviation for this testing set was 3.9 years. The number of correct predictions ±5 years achieved a very high level of 86.7% in the age category 2-19 and gradually decreased to 50% in the age category 60-75. The prediction model was deterministic for individuals belonging to these two extreme age categories. The developed method was implemented in a freely available online age prediction calculator.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
DNA methylation age of human tissues and cell types
Horvath, S. (2013) · Genome Biology · doi:10.1186/gb-2013-14-10-r115 · Cited by 7,075
Genome-wide methylation profiles reveal quantitative views of human aging rates
Hannum, G., Guinney, J., Zhao, L., Zhang, L., Hughes, G., Sadda, S., Klotzle, B., Bibikova, M., Fan, J.-B., Gao, Y., et al. (2013) · Molecular Cell · doi:10.1016/j.molcel.2012.10.016 · Cited by 4,270
The Electronic Medical Records and Genomics (eMERGE) Consortium, Wood, A. R., The MIGen Consortium, The PAGE Consortium, Study, T. L. C., Esko, T., Yang, J., Vedantam, S., Pers, T. H., Gustafsson, S., et al. (2014) · Nature Genetics · doi:10.1038/ng.3097 · Cited by 1,853
DNA methylation age of blood predicts all-cause mortality in later life
Marioni, R. E., Shah, S., McRae, A. F., Chen, B. H., Colicino, E., Harris, S. E., Gibson, J., Henders, A. K., Redmond, P., Cox, S. R., et al. (2015) · Genome Biology · doi:10.1186/s13059-015-0584-6 · Cited by 1,261
TRIM family proteins and their emerging roles in innate immunity
Ozato, K., Shin, D.-M., Chang, T.-H., & Morse, H. C. (2008) · Nature Reviews Immunology · doi:10.1038/nri2413 · Cited by 1,120
Bocklandt, S., Lin, W., Sehl, M. E., Sánchez, F. J., Sinsheimer, J. S., Horvath, S., & Vilain, E. (2011) · PLoS ONE · doi:10.1371/journal.pone.0014821 · Cited by 1,012
Aging of blood can be tracked by DNA methylation changes at just three CpG sites
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., et al. (2014) · Genome Biology · doi:10.1186/gb-2014-15-2-r24 · Cited by 837
Sullivan, K. M., Mannucci, A., Kimpton, C. P., & Gill, P. (1993) · PubMed · Cited by 534
Methylation of ELOVL 2 gene as a new epigenetic marker of age
Garagnani, P., Bacalini, M. G., Pirazzini, C., Gori, D., Giuliani, C., Mari, D., Di Blasio, A. M., Gentilini, D., Vitale, G., Collino, S., et al. (2012) · Aging Cell · doi:10.1111/acel.12005 · Cited by 473
Continuous Aging of the Human DNA Methylome Throughout the Human Lifespan
Johansson, Å., Enroth, S., & Gyllensten, U. (2013) · PLoS ONE · doi:10.1371/journal.pone.0067378 · Cited by 380
Cited by
DNA methylation-based biomarkers and the epigenetic clock theory of ageing
Horvath, S., & Raj, K. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0004-3 · Cited by 3,095
Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging
McCartney, D. L., Min, J. L., Richmond, R. C., Lu, A. T., Sobczyk, M. K., Davies, G., Broer, L., Guo, X., Jeong, A., Jung, J., et al. (2021) · Genome Biology · doi:10.1186/s13059-021-02398-9 · Cited by 292
Bekaert, B., Kamalandua, A., Zapico, S. C., Van de Voorde, W., & Decorte, R. (2015) · Epigenetics · doi:10.1080/15592294.2015.1080413 · Cited by 276
Jung, S.-E., Lim, S. M., Hong, S. R., Lee, E. H., Shin, K.-J., & Lee, H. Y. (2019) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2018.09.010 · Cited by 202
Spólnicka, M., Pośpiech, E., Pepłońska, B., Zbieć-Piekarska, R., Makowska, Ż., Pięta, A., Karłowska-Pik, J., Ziemkiewicz, B., Wężyk, M., Gasperowicz, P., et al. (2018) · International Journal of Legal Medicine · doi:10.1007/s00414-017-1636-0 · Cited by 105
Self-citation
Metadata
- Authors
- Zbieć-Piekarska, R., Spólnicka, M., Kupiec, T., Parys-Proszek, A., Makowska, Ż., Pałeczka, A., Kucharczyk, K., Płoski, R., & Branicki, W.
- Venue
- Forensic Science International: Genetics
- Publisher
- Elsevier BV
- Published
- 2015-07
- Volume
- 17
- Pages
- 173-179
- ISSN
- 1872-4973 (ISSN-L)
- OpenAlex
- W1639076783
- Cited by
- 354
- References
- 29
- FWCI
- 12.75
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Development of a forensically useful age prediction method based on DNA methylation analysis. https://app.cochat.ai/papers/10.1016/j.fsigen.2015.05.001
- The paper
- Zbieć-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. https://doi.org/10.1016/j.fsigen.2015.05.001
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
