Importance: Data on the capacity of more recently developed epigenetic age measures to predict a future onset of Metabolic Syndrome (MetS) are lacking. Objective: The aim of the study was a comparative analysis of different DNA methylation (DNAm)-based epigenetic clocks with regard to their ability to predict a future onset of MetS. In addition, cross-sectional relationships between epigenetic age measures, MetS and its components were investigated. Design, Setting and Participants: MetS was diagnosed in participants of the Berlin Aging Study II at baseline (n=1,671, mean age 68.8 +/-3.7 years, 51.6% women) and at follow-up (n=1,083; 7.4 +/-1.5 years later). DNAm age (DNAmA) and its deviation from chronological age, i.e., DNAmA acceleration (DNAmAA), were calculated for a total of five epigenetic clocks at baseline. In addition, DunedinPACE, a DNAm-based measure of the pace of aging, was calculated. The relationship of MetS with DNAmAA and DunedinPACE was investigated by fitting regression models. Furthermore, receiver operating characteristic statistics were calculated to investigate the capacity of DNAm clocks assessed at baseline to predict incident MetS at follow-up. Exposures: Six different epigenetic age measures including DunedinPACE assessed at baseline to predict MetS in the future. Main Outcomes and Measures: Diagnosis of incident MetS on average 7.4 +/-1.5 years after baseline. Results: DunedinPACE was associated with incident MetS at follow-up on average 7.4 years later (OR: 9.84, p=0.028). Interestingly, we observed no significant differences (p>0.05) in the area under the curve in predicting MetS between a model that only included clinical parameters and a model that only used GrimAge DNAmAA. Cross-sectional differences between participants with and without MetS remained statistically significant for DunedinPACE only after covariate adjustment (baseline: β=0.042, follow-up: β=0.031, p<0.0001 in both cases). Conclusions and Relevance: Systematic comparison of epigenetic clocks within a single dataset in relation to MetS and its diagnostic components showed strong and consistent associations with DunedinPACE, but not with other epigenetic clocks. Our results highlight the potential of using certain DNAm-based measures of biological ageing in predicting the onset of clinical outcomes, such as MetS.

The authors have declared no competing interest.

This work was supported by grants of the Deutsche Forschungsgemeinschaft (grant number 460683900 to ID and LB), the ERC (as part of the Lifebrain project to LB), and the Cure Alzheimer's Fund (as part of the CIRCUITS consortium to LB). This article uses data from the Berlin Aging Study II (BASE-II) and the GendAge study which were supported by the German Federal Ministry of Education and Research under grant numbers #01UW0808, #16SV5536K, #16SV5537, #16SV5538, #16SV5837, #01GL1716A and #01GL1716B. J.H. was supported by a grant from the EU Joint Programme - Neurodegenerative Disease Research (JPND2021-650-289, coordinator: C.M.L.). C.M. Lill was supported by the Heisenberg program of the DFG (DFG, LI 2654/4-1). We thank all probands of the BASE-II/GendAge study for their participation in this research.

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All participants gave written informed consent. The medical assessments at baseline and follow-up were conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Charité - Universitätsmedizin Berlin (approval numbers EA2/029/09 and EA2/144/16).

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The data presented in this study are available from the BASE-II office after filling in a data request form that undergoes review, please see https://www.base2.mpg.de/7549/data-documentation for details. We are not in a position to make data publicly available because these contain information that could compromise research participants privacy and consent.