Literature DB >> 33744870

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

Athina Vidaki1, Diego Montiel González1, Benjamin Planterose Jiménez1, Manfred Kayser1.   

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.

Entities:  

Keywords:  DNA methylation; Y-chromosome; epigenetic age prediction; epigenetics; machine learning

Mesh:

Year:  2021        PMID: 33744870      PMCID: PMC7993701          DOI: 10.18632/aging.202775

Source DB:  PubMed          Journal:  Aging (Albany NY)        ISSN: 1945-4589            Impact factor:   5.682


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