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Background: Few studies have explored the association between DNA methylation and physical activity. The aim of this study was to evaluate the association of objectively measured hours of sedentary behavior (SB) and moderate physical activity (MPA) with DNA methylation. We further aimed to explore the association between SB or MPA related CpG sites and cardiometabolic traits, gene expression, and genetic variation., Results: For discovery, we performed cross sectional analyses in pregnant women from the Epigenetics in pregnancy (EPIPREG) sample with both DNA methylation (Illumina MethylationEPIC BeadChip) and objectively measured physical activity data (SenseWear™ Pro 3 armband) (European = 244, South Asian = 109). For EWAS of SB and MPA, two main models were designed: model (1) a linear mixed model adjusted for age, smoking, blood cell composition, including ancestry as random intercept, and model (2) which was additionally adjusted for the total number of steps per day. In model 1, we did not identify any CpG sites associated with neither SB nor MPA. In model 2, SB was positively associated (false discovery rate, FDR < 0.05) with two CpG sites within the VSX1 gene. Both CpG sites were positively associated with BMI and were associated with several genetic variants in cis. MPA was associated with 122 significant CpG sites at FDR < 0.05 (model 2). We further analyzed the ten most statistically significant MPA related CpG sites and found that they presented opposite associations with sedentary behavior and BMI. We were not able to replicate the SB and MPA-related CpG sites in the Avon Longitudinal Study of Parents and Children (ALSPAC). ALSPAC had available objectively measured physical activity data from Actigraph (without steps/day available) and leucocyte DNA methylation data collected during adolescence (n = 408, European)., Conclusion: This study suggests associations of objectively measured SB and MPA with maternal DNA methylation in peripheral blood leukocytes, that needs to be confirmed in larger samples of similar study design., Competing Interests: Declarations. Ethics approval and consent to participate: In STORK G, all participants consisted of adult women who provided their informed written consent, and we had ethical approval from the Norwegian Regional Committee for Medical Health Research Ethics South East (ref. no. 2015/1035). In ALSPAC, informed consent was obtained for all participants. For children up to age 16 this was provided by the main caregiver or legal guardian (mostly mothers), and after the age of 16, the consent was provided by the teenagers themselves. Ethics approval for the study was obtained from the ALSPAC Law and Ethics Committee and the local National Health Service Research Ethics Committee. The study was performed in line with the Declaration of Helsinki. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Background: Epigenetic clocks have been recognized for their precise prediction of chronological age, age-related diseases, and all-cause mortality. Existing epigenetic clocks are based on CpGs from the Illumina HumanMethylation450 BeadChip (450 K) which has now been replaced by the latest platform, Illumina MethylationEPIC BeadChip (EPIC). Thus, it remains unclear to what extent EPIC contributes to increased precision and accuracy in the prediction of chronological age., Results: We developed three blood-based epigenetic clocks for human adults using EPIC-based DNA methylation (DNAm) data from the Norwegian Mother, Father and Child Cohort Study (MoBa) and the Gene Expression Omnibus (GEO) public repository: 1) an Adult Blood-based EPIC Clock (ABEC) trained on DNAm data from MoBa (n = 1592, age-span: 19 to 59 years), 2) an extended ABEC (eABEC) trained on DNAm data from MoBa and GEO (n = 2227, age-span: 18 to 88 years), and 3) a common ABEC (cABEC) trained on the same training set as eABEC but restricted to CpGs common to 450 K and EPIC. Our clocks showed high precision (Pearson correlation between chronological and epigenetic age (r) > 0.94) in independent cohorts, including GSE111165 (n = 15), GSE115278 (n = 108), GSE132203 (n = 795), and the Epigenetics in Pregnancy (EPIPREG) study of the STORK Groruddalen Cohort (n = 470). This high precision is unlikely due to the use of EPIC, but rather due to the large sample size of the training set., Conclusions: Our ABECs predicted adults' chronological age precisely in independent cohorts. As EPIC is now the dominant platform for measuring DNAm, these clocks will be useful in further predictions of chronological age, age-related diseases, and mortality.