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.