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Evaluation of different computational methods for DNA methylation-based biological age

Pietro Di Lena, Claudia Sala, Christine Nardini

Briefings in Bioinformatics · 2022 · ▲ 8 citations

Abstract

In recent years there has been a widespread interest in researching biomarkers of aging that could predict physiological vulnerability better than chronological age. Aging, in fact, is one of the most relevant risk factors for a wide range of maladies, and molecular surrogates of this phenotype could enable better patients stratification. Among the most promising of such biomarkers is DNA methylation-based biological age. Given the potential and variety of computational implementations (epigenetic clocks), we here present a systematic review of such clocks. Furthermore, we provide a large-scale performance comparison across different tissues and diseases in terms of age prediction accuracy and age acceleration, a measure of deviance from physiology. Our analysis offers both a state-of-the-art overview of the computational techniques developed so far and a heterogeneous picture of performances, which can be helpful in orienting future research.

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Provenance

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OpenAlex
DOI
10.1093/bib/bbac274
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2026-10-14 MST

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APA
Lena, P.D., Sala, C., &amp; Nardini, C. (2022). Evaluation of different computational methods for DNA methylation-based biological age. <em>Briefings in Bioinformatics</em>. https://doi.org/10.1093/bib/bbac274
Vancouver
Lena PD, Sala C, Nardini C. Evaluation of different computational methods for DNA methylation-based biological age. Briefings in Bioinformatics. 2022. doi:10.1093/bib/bbac274.
BibTeX
@unpublished{pietro2022Evalua, title = {Evaluation of different computational methods for DNA methylation-based biological age}, author = {Pietro Di Lena and Claudia Sala and Christine Nardini}, journal = {Briefings in Bioinformatics}, year = {2022}, doi = {10.1093/bib/bbac274}, }

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