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

Area of Science:

• Biogerontology
• Epigenetics
• Computational Biology

Background:

• Aging is a major risk factor for diseases, necessitating better predictors of physiological vulnerability than chronological age.
• Molecular surrogates, particularly DNA methylation-based biological age, show potential for improved patient stratification.
• Numerous computational implementations, known as epigenetic clocks, exist for estimating biological age.

Purpose of the Study:

• To systematically review existing DNA methylation-based biological age clocks.
• To conduct a large-scale performance comparison of these clocks across diverse tissues and diseases.
• To provide an overview of computational techniques and their performance for future research guidance.

Main Methods:

• Systematic literature review of epigenetic clocks.
• Large-scale performance evaluation based on age prediction accuracy.
• Analysis of age acceleration as a measure of physiological deviance.

Main Results:

• A comprehensive overview of current computational techniques for epigenetic clocks.
• Heterogeneous performance observed across different tissues and disease contexts.
• Identification of variations in age prediction accuracy and age acceleration.

Conclusions:

• DNA methylation-based biological age clocks are valuable tools for aging research.
• Performance variability highlights the need for context-specific clock selection.
• This review aids in orienting future research towards more robust biomarkers of aging.