Modified aging of elite athletes revealed by analysis of epigenetic age markers.

Recent progress in epigenomics has led to the development of prediction systems that enable accurate age estimation from DNA methylation data. Our objective was to track responses to intense physical exercise of individual age-correlated DNA methylation markers and to infer their potential impact on the aging processes. The study showed accelerated DNA hypermethylation for two CpG sites in TRIM59 and KLF14. Both markers predicted the investigated elite athletes to be several years older than controls and this effect was more substantial in subjects involved in power sports. Accordingly, the complete 5-CpG model revealed age acceleration of elite athletes (P=1.503x10-7) and the result was more significant amongst power athletes (P=1.051x10-9). The modified methylation of TRIM59 and KLF14 in top athletes may be accounted for by the biological roles played by these genes. Their known anti-tumour and anti-inflammatory activities suggests that intense physical training has a complex influence on aging and potentially launches signalling networks that contribute to the observed lower risk of elite athletes to develop cardiovascular disease and cancer.

Erratum to: Donor age and C1orf132/MIR29B2C determine age-related methylation signature of blood after allogeneic hematopoietic stem cell transplantation.

[This corrects the article DOI: 10.1186/s13148-016-0257-7.].

Donor age and C1orf132/MIR29B2C determine age-related methylation signature of blood after allogeneic hematopoietic stem cell transplantation.

BACKGROUND: Our recent study demonstrated that DNA methylation status in a set of CpGs located in ELOVL2, C1orf132, TRIM59, KLF14, and FHL2 can accurately predict calendar age in blood. In the present work, we used these markers to evaluate the effect of allogeneic hematopoietic stem cell transplantation (HSCT) on the age-related methylation signature of human blood. METHODS: DNA methylation in 32 CpGs was investigated in 16 donor-recipient pairs using pyrosequencing. DNA was isolated from the whole blood collected from recipients 27-360 days (mean 126) after HSCT and from the donors shortly before the HSCT. RESULTS: It was found that in the recipients, the predicted age did not correlate with their calendar age but was correlated with the calendar age (r = 0.94, p = 4 × 10(-8)) and predicted age (r = 0.97, p = 5 × 10(-10)) of a respective donor. Despite this strong correlation, the predicted age of a recipient was consistently lower than the predicted age of a donor by 3.7 years (p = 7.8 × 10(-4)). This shift was caused by hypermethylation of the C1orf132 CpGs, for C1orf132 CpG_1. Intriguingly, the recipient-donor methylation difference correlated with calendar age of the donor (r = 0.76, p = 6 × 10(-4)). This finding could not trivially be explained by shifts of the major cellular factions of blood. CONCLUSIONS: We confirm the single previous report that after HSCT, the age of the donor is the major determinant of age-specific methylation signature in recipient's blood. A novel finding is the unique methylation dynamics of C1orf132 which encodes MIR29B2C implicated in the self-renewing of hematopoietic stem cells. This observation suggests that C1orf132 could influence graft function after HSCT.

Development of a forensically useful age prediction method based on DNA methylation analysis.

Forensic DNA phenotyping needs to be supplemented with age prediction to become a relevant source of information on human appearance. Recent progress in analysis of the human methylome has enabled selection of multiple candidate loci showing linear correlation with chronological age. Practical application in forensic science depends on successful validation of these potential age predictors. In this study, eight DNA methylation candidate loci were analysed using convenient and reliable pyrosequencing technology. A total number of 41 CpG sites was investigated in 420 samples collected from men and women aged from 2 to 75 years. The study confirmed correlation of all the investigated markers with human age. The five most significantly correlated CpG sites in ELOVL2 on 6p24.2, C1orf132 on 1q32.2, TRIM59 on 3q25.33, KLF14 on 7q32.3 and FHL2 on 2q12.2 were chosen to build a prediction model. This restriction allowed the technical analysis to be simplified without lowering the prediction accuracy significantly. Model parameters for a discovery set of 300 samples were R(2)=0.94 and the standard error of the estimate=4.5 years. An independent set of 120 samples was used to test the model performance. Mean absolute deviation for this testing set was 3.9 years. The number of correct predictions ±5 years achieved a very high level of 86.7% in the age category 2-19 and gradually decreased to 50% in the age category 60-75. The prediction model was deterministic for individuals belonging to these two extreme age categories. The developed method was implemented in a freely available online age prediction calculator.

Examination of DNA methylation status of the ELOVL2 marker may be useful for human age prediction in forensic science.

Age estimation in forensic investigations may complement the prediction of externally visible characteristics and the inference of biogeographical ancestry, thus allowing a better description of an unknown individual. Multiple CpG sites that show linear correlation between age and degree of DNA methylation have been identified in the human genome, providing a selection of candidates for age prediction. In this study, we optimized an assay based on bisulfite conversion and pyrosequencing of 7 CpG sites located in the ELOVL2 gene. Examination of 303 blood samples collected from individuals aged 2-75 years allowed selection of the most informative site, explaining 83% of variation in age. The final linear regression model included two CpG sites in ELOVL2 and enabled age prediction with R(2)=0.859, prediction error=6.85 and mean absolute deviation MAD=5.03. Examination of a testing set of 124 blood samples (MAD=5.75) showed that 68.5% of samples were correctly predicted, assuming that chronological and predicted ages matched ± 7 years. It was found that the ELOVL2 methylation status in bloodstains had not changed significantly after 4 weeks of storage in room temperature conditions. Analysis of 45 bloodstains deposited on tissue paper after 5, 10 and 15 years of storage in room conditions indicated that although a gradual decrease of positive PCR results was observed, the general age prediction success rate remained similar and equaled 60-78%. The obtained results show that the ELOVL2 locus provides a very good source of information about human chronological age based on analysis of blood, including bloodstains, and it may constitute a powerful and reliable predictor in future forensic age estimation models.