ArticleScientific reports2020
Improvements and inter-laboratory implementation and optimization of blood-based single-locus age prediction models using DNA methylation of the ELOVL2 promoter.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review.International journal of molecular sciences · 2023Pooled it
- Chronological age estimation from DNA methylation data in a Serbian population: a SNaPshot-based forensic model.International journal of legal medicine · 2026Article
- 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
- Longitudinal changes and variation in human DNA methylation analysed with the Illumina MethylationEPIC BeadChip assay and their implications on forensic age prediction.Scientific reports · 2023Article
- Prediction of chronological age and its applications in forensic casework: methods, current practices, and future perspectives.Forensic sciences research · 2023Review
- Article
- Article
- A cautionary note on altered pace of aging in the COVID-19 era.Forensic science international. Genetics · 2022Article
- A high-throughput real-time PCR tissue-of-origin test to distinguish blood from lymphoblastoid cell line DNA for (epi)genomic studies.Scientific reports · 2022Article
- Chronological Age Prediction: Developmental Evaluation of DNA Methylation-Based Machine Learning Models.Frontiers in bioengineering and biotechnology · 2021Article
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8 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Several blood-based age prediction models have been developed using less than a dozen to more than a hundred DNA methylation biomarkers. Only one model (Z-P1) based on pyrosequencing has been developed using DNA methylation of a single locus located in the ELOVL2 promoter, which is considered as one of the best age-prediction biomarker. Although multi-locus models generally present better performances compared to the single-locus model, they require more DNA and present more inter-laboratory variations impacting the predictions. Here we developed 17,018 single-locus age prediction models based on DNA methylation of the ELOVL2 promoter from pooled data of four different studies (training set of 1,028 individuals aged from 0 and 91 years) using six different statistical approaches and testing every combination of the 7 CpGs, aiming to improve the prediction performances and reduce the effects of inter-laboratory variations. Compared to Z-P1 model, three statistical models with the optimal combinations of CpGs presented improved performances (MAD of 4.41-4.77 in the testing set of 385 individuals) and no age-dependent bias. In an independent testing set of 100 individuals (19-65 years), we showed that the prediction accuracy could be further improved by using different CpG combinations and increasing the number of technical replicates (MAD of 4.17).
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