First-Generation Epigenetic Clocks
First generation clocks have been the most widely studied to date in the
studies of epigenetic aging. They are broadly generalizable to different
populations, and their accuracy can be easily assessed. Despite only
being trained on CA, the EAA calculated by these clocks has been
implicated in the incidence of many
diseases14. First
generation clocks can be further classified into single and multi-tissue
clocks. In this review, we will discuss in detail the first-generation
clocks that have broad utility (e.g. the Hannum
clock67, the Horvath
pan-tissue53 and Skin
& Blood clocks68, the
PedBE clock69). The
features of other clocks tailored to narrower use cases (e.g., those
aimed at studying specific tissues or primarily focusing on an age group
such as neonates), are summarized in Table 2 . The accuracy of
first-generation epigenetic clocks is assessed in relation to CA,
usually using Absolute Error (AE=|epigenetic-chronological
age|) or Pearson’s correlation coefficient (r ) between
EA and CA. The EA calculated by these clocks is correlated with CA but
the deviation between the two has been shown to be informative of
‘biological capacity’ (e.g. physical fragility, disease susceptibility)
in adults65.
First-generation clocks represent facets of both chronological and
biological aging; separating these components remains a major
challenge65.
Bocklandt et al developed the first epigenetic clock in 2011,
marking a milestone in the field. However, this clock was aimed
specifically at saliva samples and due to the tissue specificity of DNAm
has not been generalized to other sample types (Table
2) 57. Shortly
thereafter, the
Hannum67 clock – a
broadly used blood epigenetic clock – was published. Using Illumina
450K array data from 656 samples (482 training set and 174 testing set)
of whole blood (age range: 19-101years), the Hannum clock was developed
in stages67. In the
first step, ~70,000 age associated autosomal CpG sites
were identified. Then, elastic net regression with bootstrapping was
performed to build an epigenetic clock consisting of 71 CpGs, most of
which were located close to genes implicated in age-related
conditions67(Table 2 ). When applied to pediatric samples (CA
<18years) the Hannum clock demonstrated low
accuracy61, potentially
due to a lack of pediatric samples in the dataset used to develop this
clock61.