Association between epigenetic age and type 2 diabetes mellitus or glycemic traits: A longitudinal twin study

ImportanceData on the capacity of more recently developed epigenetic age measures to predict a future onset of Metabolic Syndrome (MetS) are lacking.ObjectiveThe 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 ParticipantsMetS 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.ExposuresSix different epigenetic age measures including DunedinPACE assessed at baseline to predict MetS in the future.Main Outcomes and MeasuresDiagnosis of incident MetS on average 7.4 ±1.5 years after baseline.ResultsDunedinPACE 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 RelevanceSystematic 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.Key PointsQuestionAre epigenetic age measures able to predict the future onset of Metabolic Syndrome?FindingsThis longitudinal observational study revealed that individuals with a one-year faster pace of aging (DunedinPACE) had 2.3-fold increased odds for incident Metabolic Syndrome ∼7.5-years later.MeaningThe data reported here will potentially help to implement epigenetic measures in clinical risk assessment.

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Association between epigenetic age and type 2 diabetes mellitus or glycemic traits: A longitudinal twin study

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References 86 publications

Association between advanced fibrosis and epigenetic age acceleration among individuals with MASLD

Association between advanced fibrosis and epigenetic age acceleration among individuals with MASLD

DunedinPACE Predicts Incident Metabolic Syndrome: Cross-sectional and Longitudinal Data from the Berlin Aging Study II (BASE-II)

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