DNA methylation age (DNAm age; ‘epigenetic clock’) has recently been described as highly correlated with chronological age. Several studies suggest that DNAm age reflects, at least in part, biological age. Here we adapted a recently published methylation-sensitive single nucleotide primer extension method (MS-SNuPE) for epigenetic age estimation and calculated the DNAm age based on only seven CpG sites in 1,895 DNA samples of the Berlin Aging Study II (BASE-II). In a second step we explored the relationship between this new potential measure of biological age with an established marker of biological age, relative leukocyte telomere length (rLTL), in the same cohort. Our results showed a positive and significant correlation between DNAm age estimation and chronological age (N=1,895, R_s²=0.47), which persisted after adjustment for covariates (sex, leukocyte distribution, alcohol and smoking). We found a significant but weak negative association between DNAm age acceleration and rLTL in linear regression analysis adjusted for age, sex, alcohol and smoking (β=-0.002, p=0.007). Therefore, DNAm age appears to be a promising biomarker in the analysis of phenotypes of aging, which are not (only) related to pathways associated with mitotic age as measured by rLTL.

DNA methylation age acceleration (DNAmAA, derived from an epigenetic clock) and relative leukocyte telomere length (rLTL) are widely accepted biomarkers of aging. Nevertheless, it is still unclear which aspects of aging they represent best. Here we evaluated longitudinal associations between baseline rLTL and DNAmAA (estimated with 7-CpG clock) and functional assessments covering different domains of aging. Additionally, we made use of cross-sectional data on these assessments and examined their association with DNAmAA estimated by 5 different DNAm age measures. Two-wave longitudinal data were available for 1 083 participants of the Berlin Aging Study II who were reexamined on average 7.4 years after baseline as part of the GendAge study. Functional outcomes were assessed with Fried’s frailty score, Tinetti mobility test, falls in the past 12 months (yes/no), finger-floor distance, Mini-Mental State Examination, Center for Epidemiologic Studies—Depression scale, activities of daily living, instrumented ADL, and mini nutritional assessment. Overall, we found no evidence for an association between the molecular biomarkers measured at baseline, rLTL, and DNAmAA (7-CpG clock), and functional assessments assessed at follow-up. Similarly, a cross-sectional analysis of follow-up data did also not show evidence for associations of the various DNAmAA measures (7-CpG clock, Horvath’s clock, Hannum’s clock PhenoAge, and GrimAge) with functional assessments. In conclusion, neither rLTL nor 7-CpG DNAmAA was able to predict impairment in the analyzed assessments over a ~7-year time course. Similarly, DNAmAA estimated from 5 epigenetic clocks was not a good cross-sectional marker of health deterioration either.

Telomere length has been accepted widely as a biomarker of aging. Recently, a novel candidate biomarker has been suggested to predict an individual’s chronological age with high accuracy: The epigenetic clock is based on the weighted DNA methylation (DNAm) fraction of a number of cytosine-phosphate-guanine sites (CpGs) selected by penalized regression analysis. Here, an established methylation-sensitive single nucleotide primer extension method was adapted, to estimate the epigenetic age of the 1005 participants of the LipidCardio Study, a patient cohort characterised by high prevalence of cardiovascular disease, based on a seven CpGs epigenetic clock. Furthermore, we measured relative leukocyte telomere length (rLTL) to assess the relationship between the established and the promising new measure of biological age. Both rLTL (0.79 ± 0.14) and DNAm age (69.67 ± 7.27 years) were available for 773 subjects (31.6% female; mean chronological age= 69.68 ± 11.01 years; mean DNAm age acceleration = −0.01 ± 7.83 years). While we detected a significant correlation between chronological age and DNAm age (n = 779, R = 0.69), we found neither evidence of an association between rLTL and the DNAm age (β = 3.00, p = 0.18) nor rLTL and the DNAm age acceleration (β = 2.76, p = 0.22) in the studied cohort, suggesting that DNAm age and rLTL measure different aspects of biological age.

Adverse effects of psychological stress on physical and mental health, especially in older age, are well documented. How perceived stress relates to the epigenetic clock measure, DNA methylation age acceleration (DNAmAA), is less well understood and existing studies reported inconsistent results. DNAmAA was estimated from five epigenetic clocks (7-CpG, Horvath’s, Hannum’s, PhenoAge and GrimAge DNAmAA). Cohen’s Perceived Stress Scale (PSS) was used as marker of psychological stress. We analyzed data from 1,100 Berlin Aging Study II (BASE-II) participants assessed as part of the GendAge study (mean age = 75.6 years, SD = 3.8 years, 52.1% women). In a first step, we replicated well-established associations of perceived stress with morbidity, frailty, and symptoms of depression in the BASE-II cohort studied here. In a second step, we did not find any statistically significant association of perceived stress with any of the five epigenetic clocks in multiple linear regression analyses that adjusted for covariates. Although the body of literature suggests an association between higher DNAmAA and stress or trauma during early childhood, the current study found no evidence for an association of perception of stress with DNAmAA in older people. We discuss possible reasons for the lack of associations and highlight directions for future research.

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.