Epigenetic Age Estimation from Blood

The generation, preprocessing, and normalization of the DNAm data were described in our previous paper (19 (link)). Briefly, genome-wide DNAm from blood samples was determined on Illumina EPIC BeadChip, and the data were preprocessed with R package minfi. Detection p values comparing the total signal for each probe to the background signal level were calculated to evaluate the quality of the samples (20 (link)). Further analysis excluded samples of poor quality (mean detection p > .01). The single-sample Noob normalization method was used to normalize the data (21 (link)). The epigenetic age estimates, including Horvath’s (6 (link)) and Hannum’s (22 (link)) DNAmAge, DNAm PhenoAge (7 (link)), and GrimAge (8 (link)), were produced using an online calculator with default settings (https://dnamage.genetics.ucla.edu/new). Epigenetic age acceleration, which describes the difference between the chronological age and the epigenetic age estimate, was calculated as the residual from a linear regression model of epigenetic age estimates of chronological age. DNA collection and the assessment of DNAm age acceleration were conducted only at baseline.