Eight Weeks of Physical Training Decreases 2 Years of DNA Methylation Age of Sedentary Women

Purpose: The acceleration of epigenetic age is a predictor of mortality and contributes to the increase in chronic diseases. Adherence to a healthy lifestyle is a strategy to reduce epigenetic age. The present study aimed to determine whether eight weeks of combined (aerobic and strength) training (CT) can influence the epigenetic age of women between 50 and 70 years old and the differences in sites and methylated regions. Methods: Eighteen women (AAR_Low: lower age acceleration residual, n = 10; AAR_High: higher age acceleration residual, n = 8) participated in a combined exercise training program (60 minutes, 3× a week) for eight weeks. DNA was extracted from whole blood using the salting out technique. DNA methylation was performed using the array technique (Illumina's Infinium Methylation BeadChip 850k). We used the DNA Methylation Age Calculator platform to calculate the biological epigenetic age. Two-way ANOVA followed by FISHER LSD posthoc was Applied, adopting p < .05. Results: After eight weeks of CT, there were no changes to the epigenetic age acceleration for the AAR_Low group (PRE: -2.3 ± 3.2 to POST: -2.3 ± 3.6). However, the AAR_High group significantly decreased the age acceleration (PRE: 3.6 ± 2.6 to POST: 2.2 ± 2.7) (group effect, p = .01; time effect, p = .31; group vs. time effect, p = .005). Conclusion: CT for eight weeks benefits the epigenetic clock of women with the most accelerated age.

DNA methylation epi-signature and biological age in attention deficit hyperactivity disorder patients

OBJECTIVE

Attention Deficit/Hyperactivity Disorder (ADHD) is a common behavioral syndrome that begins in childhood and affects 3.4% of children worldwide. Due to its etiological complexity, there are no consistent biomarkers for ADHD, however the high heritability presented by the disorder indicates a genetic/epigenetic influence. The main epigenetic mechanism is DNA methylation, a process with an important role in gene expression and in many psychiatric disorders. Thus, our study sought to identify epi-signatures biomarkers in 29 children clinically diagnosed with ADHD.

METHODS

After DNA extraction and bisulfite conversion, we performed methylation array experiment for differential methylation, ontological and biological age analysis.

RESULTS

The biological response in ADHD patients was not sufficient to determine a conclusive epi-signature in our study. However, our results highlighted the interaction of energy metabolism and oxidative stress pathways in ADHD patients detected by differential methylation patterns. Furthermore, we were able to identify a marginal association between the DNAmAge and ADHD.

CONCLUSION

Our study present new methylation biomarkers findings associated with energy metabolism and oxidative stress pathways, in addition to DNAmAge in ADHD patients. However, we propose that further multiethnic studies, with larger cohorts and including maternal conditions, are necessary to demonstrate a definitive association between ADHD and these methylation biomarkers.

Distinguishable DNA methylation defines a cardiac-specific epigenetic clock

BACKGROUND

The present study investigates whether epigenetic differences emerge in the heart of patients undergoing cardiac surgery for an aortic valvular replacement (AVR) or coronary artery bypass graft (CABG). An algorithm is also established to determine how the pathophysiological condition might influence the human biological cardiac age.

RESULTS

Blood samples and cardiac auricles were collected from patients who underwent cardiac procedures: 94 AVR and 289 CABG. The CpGs from three independent blood-derived biological clocks were selected to design a new blood- and the first cardiac-specific clocks. Specifically, 31 CpGs from six age-related genes, ELOVL2, EDARADD, ITGA2B, ASPA, PDE4C, and FHL2, were used to construct the tissue-tailored clocks. The best-fitting variables were combined to define new cardiac- and blood-tailored clocks validated through neural network analysis and elastic regression. In addition, telomere length (TL) was measured by qPCR. These new methods revealed a similarity between chronological and biological age in the blood and heart; the average TL was significantly higher in the heart than in the blood. In addition, the cardiac clock discriminated well between AVR and CABG and was sensitive to cardiovascular risk factors such as obesity and smoking. Moreover, the cardiac-specific clock identified an AVR patient's subgroup whose accelerated bioage correlated with the altered ventricular parameters, including left ventricular diastolic and systolic volume.

CONCLUSION

This study reports on applying a method to evaluate the cardiac biological age revealing epigenetic features that separate subgroups of AVR and CABG.

The trajectory of the blood DNA methylome ageing rate is largely set before adulthood: evidence from two longitudinal studies

The epigenetic clock, defined as the DNA methylome age (DNAmAge), is a candidate biomarker of ageing. In this study, we aimed to characterize the behaviour of this marker during the human lifespan in more detail using two follow-up cohorts (the Young Finns study, calendar age i.e. cAge range at baseline 15-24 years, 25-year-follow-up, N = 183; The Vitality 90+ study, cAge range at baseline 19-90 years, 4-year-follow-up, N = 48). We also aimed to assess the relationship between DNAmAge estimate and the blood cell distributions, as both of these measures are known to change as a function of age. The subjects' DNAmAges were determined using Horvath's calculator of epigenetic cAge. The estimate of the DNA methylome age acceleration (Δ-cAge-DNAmAge) demonstrated remarkable stability in both cohorts: the individual rank orders of the DNAmAges remained largely unchanged during the follow-ups. The blood cell distributions also demonstrated significant intra-individual correlation between the baseline and follow-up time points. Interestingly, the immunosenescence-associated features (CD8+CD28- and CD4+CD28- cell proportions and the CD4/CD8 cell ratio) were tightly associated with the estimate of the DNA methylome age. In summary, our data demonstrate that the general level of Δ-cAge-DNAmAge is fixed before adulthood and appears to be quite stationary thereafter, even in the oldest-old ages. Moreover, the blood DNAmAge estimate seems to be tightly associated with ageing-associated shifts in blood cell composition, especially with those that are the hallmarks of immunosenescence. Overall, these observations contribute to the understanding of the longitudinal aspects of the DNAmAge estimate.