Background: Patients with Type 2 diabetes mellitus (T2D) are at risk for micro- and macrovascular complications. Implementable risk scores are needed to improve targeted prevention for patients that are particularly susceptible to complications. The epigenetic clock estimates an individual's biological age using DNA methylation profiles.
Methods: In this study, we examined older adults of the Berlin Aging Study II that were reexamined on average 7.4 years after baseline assessment as part of the GendAge study. DNA methylation age (DNAmA) and its deviation from chronological age DNAmA acceleration (DNAmAA) were calculated with the 7-CpG clock (available at both timepoints, n = 1,071), Horvath's clock, Hannum's clock, PhenoAge and GrimAge (available at follow-up only, n = 1,067). T2D associated complications were assessed with the Diabetes Complications Severity Index (DCSI).
Results: We report on a statistically significant association between oral glucose tolerance test results and Hannum and PhenoAge DNAmAA. PhenoAge was also associated with fasting glucose. In contrast, we found no cross-sectional association after covariate adjustment between DNAmAA and a diagnosis of T2D. However, longitudinal analyses showed that every additional year of 7-CpG DNAmAA at baseline increased the odds for developing one or more additional complications or worsening of an already existing complication during the follow-up period by 11% in male participants with T2D. This association persisted after covariate adjustment (OR = 1.11, p = 0.045, n = 56).
Conclusion: Although our results remain to be independently validated, this study shows promising evidence of utility of the 7-CpG clock in identifying patients with diabetes who are at high risk for developing complications.
Deterioration of vision, kidney function and cardiovascular function are just a few examples of diabetes-related complications. However, not all patients develop these complications, and it is desirable to detect patients that have a high risk for the complications early. In this study, we examine markers, which are based on reversible modifications of the DNA, in the context of diabetes and its complications. We found that one of these biomarkers is able to predict the development of diabetes complications over a period of about seven years in our dataset. If these results can be confirmed in other studies, our findings might help physicians to identify patients with diabetes that have an increased risk for developing complications in the future.
© 2023. The Author(s).