Calculation of epigenetic age

The epigenetic ages of each sample were estimated using 4 popular epigenetic clocks, which were the Hannum clock, which relies on 71 CpGs identified in blood DNA samples [21]; the Horvath clock, which relies on 353 CpGs and is based on the analysis of DNA methylation from multiple tissue types [22]; the PhenoAge clock, which is based on 513 CpGs derived to measure phenotypic aging [23]; and the EpiTOC clock, which is derived from the analysis of 385 Polycomb group target promoter CpGs [24]. Note these epigenetic clocks were developed using data from the HM450 array. Although the EPIC array lacks some of the CpGs in the Hannum (6), Horvath (19), and EpiTOC (31) clocks due to the differences in the array design between the HM450 and EPIC arrays (Additional file 1: Figure S3), McEwen et al. have demonstrated that the missing clock CpGs on the EPIC array do not substantially affect the accuracy of the Hannum or Horvath age determination [39]. To verify this observation for all 4 clocks, we performed a sensitivity analysis on our HM450 data. We selected the common clock CpGs on both arrays to calculate the epigenetic ages for the HM450 samples and compared these results with their epigenetic ages derived from using all clock CpGs (see results in the “Discussion” section).

A linear regression model was used to describe the relationship between the epigenetic age and chronological age at the time of tissue collection. The deviation between epigenetic age and chronological age, also known as epigenetic age acceleration, was calculated for every sample based on the residuals of regressing the epigenetic ages on the chronological ages of all the samples, as described by McEwen et al. [39].