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Analysis of epigenetic aging in vivo and in vitro: Factors controlling the speed and direction.

Mieko MatsuyamaArne SøraasSarah YuKyuhyeon KimEvi X StavrouPaolo F CaimiDavid WaldMarcos deLimaJohn Arne DahlSteve HorvathShigemi Matsuyama
Published in: Experimental biology and medicine (Maywood, N.J.) (2020)
Aging is associated with DNA methylation (DNAm) changes. Recent advancement of the whole-genome DNAm analysis technology allowed scientists to develop DNAm-based age estimators. A majority of these estimators use DNAm data from a single tissue type such as blood. In 2013, a multi-tissue age estimator using DNAm pattern of 353 CpGs was developed by Steve Horvath. This estimator was named "epigenetic clock", and the improved version using DNAm pattern of 391 CpGs was developed in 2018. The estimated age by epigenetic clock is named DNAmAge. DNAmAge can be used as a biomarker of aging predicting the risk of age-associated diseases and mortality. Although the DNAm-based age estimators were developed, the mechanism of epigenetic aging is still enigmatic. The biological significance of epigenetic aging is not well understood, either. This minireview discusses the current understanding of the mechanism of epigenetic aging and the future direction of aging research.
Keyphrases
  • dna methylation
  • gene expression
  • nk cells
  • genome wide
  • type diabetes
  • machine learning
  • risk factors
  • artificial intelligence
  • data analysis