Evidence map›Paper›PMID 33744870›Full record

ArticleAging2021

Male-specific age estimation based on Y-chromosomal DNA methylation.

Athina Vidaki, Diego Montiel González, Benjamin Planterose Jiménez, Manfred Kayser

Open access · greenAbstract read
In one paragraph

Article in Aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
2.4field-weighted citation impact, top 10% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 34 citations in OpenAlex.

  1. Pooled it
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  6. Molecular Age Estimation: Current Perspectives and Future Considerations.International journal of molecular sciences · 2026
    Review
  7. Age-Related Transcriptomic Changes in the Vermiform Appendix.International journal of molecular sciences · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Athina VidakiDepartment of Genetic Identification, Erasmus University Medical Center Rotterdam, Rotterdam 3000, CA, The Netherlands.
Diego Montiel GonzálezDepartment of Genetic Identification, Erasmus University Medical Center Rotterdam, Rotterdam 3000, CA, The Netherlands.
Benjamin Planterose JiménezDepartment of Genetic Identification, Erasmus University Medical Center Rotterdam, Rotterdam 3000, CA, The Netherlands.
Manfred KayserDepartment of Genetic Identification, Erasmus University Medical Center Rotterdam, Rotterdam 3000, CA, The Netherlands.
Erasmus MC · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although DNA methylation variation of autosomal CpGs provides robust age predictive biomarkers, no male-specific age predictor exists based on Y-CpGs yet. Since sex chromosomes play an important role in aging, a Y-chromosome-based age predictor would allow studying male-specific aging effects and would also be useful in forensics. Here, we used blood-based DNA methylation microarray data of 1,057 males from six cohorts aged 15-87 and identified 75 Y-CpGs with an interquartile range of ≥0.1. Of these, 22 and six were significantly hyper- and hypomethylated with age (p(cor)<0.05, Bonferroni), respectively. Amongst several machine learning algorithms, a model based on support vector machines with radial kernel performed best in male-specific age prediction. We achieved a mean absolute deviation (MAD) between true and predicted age of 7.54 years (cor=0.81, validation) when using all 75 Y-CpGs, and a MAD of 8.46 years (cor=0.73, validation) based on the most predictive 19 Y-CpGs. The accuracies of both age predictors did not worsen with increased age, in contrast to autosomal CpG-based age predictors that are known to predict age with reduced accuracy in the elderly. Overall, we introduce the first-of-its-kind male-specific epigenetic age predictor for future applications in aging research and forensics.

Indexed as

Chromosomes, Human, YDNA MethylationAdolescentAdultAgedAged, 80 and overAgingAlgorithmsCpG IslandsEpigenesis, GeneticHumansMachine LearningMaleMiddle AgedModels, GeneticSupport Vector MachineDNA methylationepigenetic age predictionepigeneticsmachine learningY-chromosome

Identifiers

PMID33744870
PMCPMC7993701
OpenAlexW3136988072

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.