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<p>Epigenetic aging signatures provide insights into human aging, but traditional clocks rely on linear regression of DNA methylation levels, assuming linear trajectories. This study explores a non-parametric approach using 2D-kernel density estimation to determine epigenetic age. Our weighted model achieves similar predictive accuracy as conventional clocks and provides a variation score reflecting the inherent variability of age-related epigenetic changes within samples. This score is significantly increased in various diseases and associated with mortality risk in the Lothian Birth Cohort 1921. Thus, weighted 2D-kernel density estimation facilitates accurate epigenetic age predictions and offers an additional variable for biological age estimation.</p>

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Weighted 2D-kernel density estimations provide a new probabilistic measure for epigenetic age

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月22日

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  • Juan-Felipe Perez-Correa,
  • Thomas Stiehl,
  • Riccardo E. Marioni,
  • Janie Corley,
  • Simon R. Cox,
  • Ivan G. Costa,
  • Wolfgang Wagner

摘要

Epigenetic aging signatures provide insights into human aging, but traditional clocks rely on linear regression of DNA methylation levels, assuming linear trajectories. This study explores a non-parametric approach using 2D-kernel density estimation to determine epigenetic age. Our weighted model achieves similar predictive accuracy as conventional clocks and provides a variation score reflecting the inherent variability of age-related epigenetic changes within samples. This score is significantly increased in various diseases and associated with mortality risk in the Lothian Birth Cohort 1921. Thus, weighted 2D-kernel density estimation facilitates accurate epigenetic age predictions and offers an additional variable for biological age estimation.