ArticleInternational journal of legal medicine2020
Inter-laboratory adaption of age estimation models by DNA methylation analysis-problems and solutions.
Article in International journal of legal medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 25 citations in OpenAlex.
- Advancing Forensic Human Chronological Age Estimation: Biochemical, Genetic, and Epigenetic Approaches from the Last 15 Years: A Systematic Review.International journal of molecular sciences · 2025Pooled it
- An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review.International journal of molecular sciences · 2023Pooled it
- The 12 o'clock assay: an optimized dodecaplex droplet digital PCR assay for robust DNA methylation quantification and epigenetic clock-based age-predictions.Clinical epigenetics · 2026Article
- A Ge.F.I. Collaborative Study: Evaluating Reproducibility and Accuracy of a DNA-Methylation-Based Age-Predictive Assay for Routine Implementation in Forensic Casework.Electrophoresis · 2025Article
- Getting the chronological age out of DNA: using insights of age-dependent DNA methylation for forensic DNA applications.Genes & genomics · 2023Review
- Prediction of chronological age and its applications in forensic casework: methods, current practices, and future perspectives.Forensic sciences research · 2023Review
- Altered DNA methylation at age-associated CpG sites in children with growth disorders: impact on age estimation?International journal of legal medicine · 2022Article
- Article
- Postmortem age estimation via DNA methylation analysis in buccal swabs from corpses in different stages of decomposition-a "proof of principle" study.International journal of legal medicine · 2021Article
- Improvements and inter-laboratory implementation and optimization of blood-based single-locus age prediction models using DNA methylation of the ELOVL2 promoter.Scientific reports · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, a lot of age prediction models based on different CpG motives in different cell types were published determining the biological age of a person by DNA methylation. For a general employment of this technique, maybe even as a routine method, the cross-laboratory application of such models has to be examined. Therefore, we tested two different published age prediction models for blood and mouth swab samples with regard to prediction accuracy (Bekaert et al Epigenetics 10:922-930, 2015a; Bekaert et al Forensic Sci Int Genet Suppl Ser 5:e144-e145, 2015b). Both models are based on CpG sites of four genes (ASPA, EDARADD, PDE4-C, and ELOVL2), but with a different combination of CpGs for the two tissue types. A mean absolute difference (MAD) between chronological and predicted age of 9.84 and 8.32 years for blood and buccal swab models could be demonstrated, respectively, which is significantly worse than the published data, probably due to higher DNA methylation variances in some CpGs. By retraining both prediction models, the prediction accuracy could be improved to a MAD of 5.55 and 4.65 years for the renewed blood and buccal swab model, respectively. This study demonstrates the usefulness of effective DNA standards to normalize DNA methylation data for better comparison of study results.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.