Epigenetic Clocks
The epigenetic clock exploits the reproducible relationship between DNAm at specific CpGs and age, to predict epigenetic age (EA). The difference between EA and CA highlights changes in cell or tissue function13. Positive EAA (EA > CA) in adults has been implicated in increased susceptibility to disease (e.g. Alzheimer’s disease, B cell lymphoma)15,18and increased mortality16,59. In children, positive EAA has been found in connection with maternal smoking60 and alcohol use61, as well as with diseases such as allergy and asthma19. There have also been exposures (e.g. exercise, consumption of fish and fruits and vegetables) associated with negative EAA62,63(epigenetic age < chronological age).
CpGs in most epigenetic clocks were selected using penalized linear regression methods13such as elastic net, which protect against overfitting in models containing many predictor variables64. However, these linear methods do not account for any non-additive interactions between CpG sites, and may not fully capture the complexity of DNAm in the aging process65. This limitation can be addressed by using non-linear methods in the development of the epigenetic clocks.