scholarly journals DNA Methylation and Immune Cell Markers Demonstrate Evidence of Accelerated Aging in Patients with Chronic HBV or HCV, with or without HIV Co-Infection

Author(s):  
Yevgeniy Gindin ◽  
Anuj Gaggar ◽  
Anna S Lok ◽  
Harry L A Janssen ◽  
Carlo Ferrari ◽  
...  

Abstract Background Several chronic diseases have been shown to accelerate biological aging. We investigated age acceleration and the association between peripheral blood DNAm and immune cell markers in patients chronically infected with the hepatitis B virus (HBV) or the hepatitis C virus (HCV) with and without human immunodeficiency virus (HIV) co-infection. Methods Age acceleration was measured as the difference between epigenetic age (Horvath clock) and chronological age. The immune marker model of age acceleration was developed using Elastic Net regression to select both the immune markers and their associated weights in the final linear model. Results Patients with chronic HBV (n=51) had a significantly higher median epigenetic age compared to chronological age (age accelerated) (p < 0.001). In patients with chronic HCV infection (n=63), age acceleration was associated with liver fibrosis as assessed by histology (p < 0.05), or presence of HIV co-infection (p < 0.05), but not HCV mono-infection. Age acceleration defined by immune markers was concordant with age acceleration by DNA methylation (correlation coefficient=0.59 in HBV; p=0.0025). One-year treatment of HBV patients with nucleoside therapy was associated with a modest reduction in age acceleration as measured using the immune marker model (-0.65 years, p=0.018). Conclusion Our findings suggest that patients with chronic viral hepatitis have accelerated epigenetic aging and that immune markers defines biological age and has the potential to assess the effects of therapeutic intervention on age acceleration.

2018 ◽  
Author(s):  
Riccardo E Marioni ◽  
Daniel W Belsky ◽  
Ian J Deary ◽  
Wolfgang Wagner

AbstractEvaluation of biological age, as opposed to chronological age, is of high relevance for interventions to increase healthy aging. Highly reproducible age-associated DNA methylation (DNAm) changes can be integrated into algorithms for epigenetic age predictions. These predictors have mostly been trained to correlate with chronological age, but they are also indicative for biological aging. For example accelerated epigenetic age of blood is associated with higher risk of all-cause mortality in later life. The perceived age of facial images (face-age) is also associated with all-cause mortality and other aging-associated traits. In this study, we therefore tested the hypothesis that an epigenetic predictor for biological age might be trained on face-age as surrogate for biological age, rather than on chronological age. Our data demonstrate that facial aging and DNAm changes in blood provide two independent measures for biological aging.


2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii74-ii74
Author(s):  
Annette Molinaro ◽  
John Wiencke ◽  
Gayathri Warrier ◽  
JiYoon Lee ◽  
Devin Koestler ◽  
...  

Abstract Lineage-specific DNA methylation marks differentiate leukocyte cell types while individual biological aging mechanisms impact other methylation alterations. Human glioma incidence and survival times have been shown to be associated with aberrant immune profiles and have a strong dependency on age. Here we developed a single epigenetic analysis framework to evaluate both immune cell fractions and epigenetic age in peripheral blood. We examined these measures in archived blood from 197 triple-negative glioma patients (TNG; IDH wildtype, 1p19q intact and TERT wildtype) and 312 frequency-matched controls from the SF Bay Area Adult Glioma Study (AGS). Significant differences were observed with TNG cases having lower CD4 and CD8 T cell, natural killer, and B cell fractions, and higher neutrophil fractions than controls. TNG cases were significantly older than controls in two of three epigenetic age estimates; however, there was no difference in epigenetic age acceleration once immune cell proportions were considered. For the TNG cases, we augmented results from several machine learning methods to delineate risk groups of TNG patients with significantly different overall survival. We compared survival models built by recursive partitioning, random forest, and elastic net methods. The final model was chosen by repeated bootstrap sampling via the Brier score loss function and validated in an independent set of 72 IDH-mutant only or TERT-mutant only glioma patients also from the AGS. The final model indicated important interactions between immune cell fractions (including CD4 and CD8 T cells and neutrophils) and treatment, age, and dexamethasone status when adjusted for the main effects of epigenetic age, glioblastoma status, and the neutrophil-to-lymphocyte ratio. The capacity of immunomethylomics to capture diverse, clinically relevant information and the simplicity of its implementation make this a powerful tool for personalized patient evaluation in the neuro-oncology clinic.


2020 ◽  
Author(s):  
Lacey W. Heinsberg ◽  
Mitali Ray ◽  
Yvette P. Conley ◽  
James M. Roberts ◽  
Arun Jeyabalan ◽  
...  

ABSTRACTBackgroundPreeclampsia is a leading cause of maternal and neonatal morbidity and mortality. Chronological age and race are associated with increased risk of preeclampsia; however, the pathophysiology of preeclampsia and how these risk factors impact its development, are not entirely understood. This gap precludes clinical interventions to prevent preeclampsia occurrence or to address stark racial disparities in maternal and neonatal outcomes. Of note, cellular aging rates can differ between individuals and chronological age is often a poor surrogate of biological age. DNA methylation age provides a marker of biological aging, and those with a DNA methylation age greater than their chronological age have ‘age acceleration’. Examining age acceleration in the context of preeclampsia status, and race, could strengthen our understanding of preeclampsia pathophysiology, inform future interventions to improve maternal/neonatal outcomes, and provide insight to racial disparities across pregnancy.ObjectivesThe purpose of this exploratory study was to examine associations between age acceleration, preeclampsia status, and race across pregnancy.Study designThis was a longitudinal, observational, case-control study of 56 pregnant individuals who developed preeclampsia (n=28) or were normotensive controls (n=28). Peripheral blood samples were collected at trimester-specific time points and genome-wide DNA methylation data were generated using the Infinium MethylationEPIC Beadchip. DNA methylation age was estimated using the Elastic Net ‘Improved Precision’ clock and age acceleration was computed as Δage, the difference between DNA methylation age and chronological age. DNA methylation age was compared with chronological age using scatterplots and Pearson correlations, while considering preeclampsia status and race. The relationships between preeclampsia status, race, and Δage were formally tested using multiple linear regression, while adjusting for pre-pregnancy body mass index, chronological age, and (chronological age)2. Regressions were performed both with and without consideration of cell-type heterogeneity.ResultsWe observed strong correlations between chronological age and DNA methylation age in all trimesters, ranging from R=0.91-0.95 in cases and R=0.86-0.90 in controls. We observed significantly stronger correlations between chronological age and DNA methylation age in White versus Black participants ranging from R=0.89-0.98 in White participants and R=0.77-0.83 in Black participants. We observed no association between Δage and preeclampsia status within trimesters. However, even while controlling for covariates, Δage was higher in trimester 1 in participants with higher pre-pregnancy BMI (β=0.12, 95% CI=0.02 to 0.22, p=0.02) and lower in Black participants relative to White participants in trimesters 2 (β=−2.68, 95% CI=−4.43 to −0.94, p=0.003) and 3 (β=−2.10, 95% CI=−4.03 to −0.17, p=0.03). When controlling for cell-type heterogeneity, the observations with BMI in trimester 1 and race in trimester 2 persisted.ConclusionsWe report no association between Δage and preeclampsia status, although there were associations with pre-pregnancy BMI and race. In particular, our findings in a small sample demonstrate the need for additional studies to not only investigate the complex pathophysiology of preeclampsia, but also the relationship between race and biological aging, which could provide further insight into racial disparities in pregnancy and birth. Future efforts to confirm these findings in larger samples, including exploration and applications of other epigenetic clocks, is needed.


2020 ◽  
Author(s):  
Jean-François Lemaître ◽  
Benjamin Rey ◽  
Jean-Michel Gaillard ◽  
Corinne Régis ◽  
Emmanuelle Gilot ◽  
...  

AbstractDNA methylation-based biomarkers of aging (epigenetic clocks) promise to lead to new insights in the evolutionary biology of ageing. Relatively little is known about how the natural environment affects epigenetic aging effects in wild species. In this study, we took advantage of a unique long-term (>40 years) longitudinal monitoring of individual roe deer (Capreolus capreolus) living in two wild populations (Chizé and Trois Fontaines, France) facing different ecological contexts to investigate the relationship between chronological age and levels of DNA methylation (DNAm). We generated novel DNA methylation data from n=90 blood samples using a custom methylation array (HorvathMammalMethylChip40). We present three DNA methylation-based estimators of age (DNAm or epigenetic age), which were trained in males, females, and both sexes combined. We investigated how sex differences influenced the relationship between DNAm age and chronological age through the use of sex-specific epigenetic clocks. Our results highlight that both populations and sex influence the epigenetic age, with the bias toward a stronger male average age acceleration (i.e. differences between epigenetic age and chronological ages) particularly pronounced in the population facing harsh environmental conditions. Further, we identify the main sites of epigenetic alteration that have distinct aging patterns across the two sexes. These findings open the door to promising avenues of research at the crossroad of evolutionary biology and biogerontology.


Author(s):  
Pavanello ◽  
Campisi ◽  
Tona ◽  
Lin ◽  
Iliceto

DNA methylation (DNAm) is an emerging estimator of biological aging, i.e., the often-defined “epigenetic clock”, with a unique accuracy for chronological age estimation (DNAmAge). In this pilot longitudinal study, we examine the hypothesis that intensive relaxing training of 60 days in patients after myocardial infarction and in healthy subjects may influence leucocyte DNAmAge by turning back the epigenetic clock. Moreover, we compare DNAmAge with another mechanism of biological age, leucocyte telomere length (LTL) and telomerase. DNAmAge is reduced after training in healthy subjects (p = 0.053), but not in patients. LTL is preserved after intervention in healthy subjects, while it continues to decrease in patients (p = 0.051). The conventional negative correlation between LTL and chronological age becomes positive after training in both patients (p < 0.01) and healthy subjects (p < 0.05). In our subjects, DNAmAge is not associated with LTL. Our findings would suggest that intensive relaxing practices influence different aging molecular mechanisms, i.e., DNAmAge and LTL, with a rejuvenating effect. Our study reveals that DNAmAge may represent an accurate tool to measure the effectiveness of lifestyle-based interventions in the prevention of age-related diseases.


2020 ◽  
Vol 134 (6) ◽  
pp. 2215-2228
Author(s):  
Barbara Elisabeth Koop ◽  
Alexandra Reckert ◽  
Julia Becker ◽  
Yang Han ◽  
Wolfgang Wagner ◽  
...  

Abstract There is a growing perception that DNA methylation may be influenced by exogenous and endogenous parameters. Knowledge of these factors is of great relevance for the interpretation of DNA-methylation data for the estimation of chronological age in forensic casework. We performed a literature review to identify parameters, which might be of relevance for the prediction of chronological age based on DNA methylation. The quality of age predictions might particularly be influenced by lifetime adversities (chronic stress, trauma/post-traumatic stress disorder (PTSD), violence, low socioeconomic status/education), cancer, obesity and related diseases, infectious diseases (especially HIV and Cytomegalovirus (CMV) infections), sex, ethnicity and exposure to toxins (alcohol, smoking, air pollution, pesticides). Such factors may alter the DNA methylation pattern and may explain the partly high deviations between epigenetic age and chronological age in single cases (despite of low mean absolute deviations) that can also be observed with “epigenetic clocks” comprising a high number of CpG sites. So far, only few publications dealing with forensic age estimation address these confounding factors. Future research should focus on the identification of further relevant confounding factors and the development of models that are “robust” against the influence of such biological factors by systematic investigations under targeted inclusion of diverse and defined cohorts.


2021 ◽  
Vol 12 ◽  
Author(s):  
Chunhong Hong ◽  
Shaohua Yang ◽  
Qiaojin Wang ◽  
Shiqiang Zhang ◽  
Wenhui Wu ◽  
...  

Background: Abnormal DNA methylation (DNAm) age has been assumed to be an indicator for canceration and all-cause mortality. However, associations between DNAm age and molecular features of stomach adenocarcinoma (STAD), and its prognosis have not been systematically studied.Method: We calculated the DNAm age of 591 STAD samples and 115 normal stomach samples from The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) database using the Horvath’s clock model. Meanwhile, we utilized survival analysis to evaluate the prognostic value of DNAm age and epigenetic age acceleration shift. In addition, we performed weighted gene co-expression network analysis (WGCNA) to identify DNAm age-associated gene modules and pathways. Finally, the association between DNAm age and molecular features was performed by correlation analysis.Results: DNA methylation age was significantly correlated with chronological age in normal gastric tissues (r = 0.85, p &lt; 0.0001), but it was not associated with chronological age in STAD samples (r = 0.060, p = 0.2369). Compared with tumor adjacent normal tissue, the DNAm age of STAD tissues was significantly decreased. Meanwhile, chronological age in STAD samples was higher than its DNAm age. Both DNAm age and epigenetic acceleration shift were associated with the prognosis of STAD patients. By using correlation analysis, we also found that DNAm age was associated with immunoactivation and stemness in STAD samples.Conclusion: In summary, epigenetic age acceleration of STAD was associated with tumor stemness, immunoactivation, and favorable prognosis.


2021 ◽  
Author(s):  
Kyeezu Kim ◽  
Brian T. Joyce ◽  
Yinan Zheng ◽  
Pamela J. Schreiner ◽  
David R. Jacobs Jr. ◽  
...  

DNA methylation-based biological age (epigenetic age) has been suggested as a useful biomarker of age-related conditions including type 2 diabetes (T2D), and its newest iterations (GrimAge measurements) have shown early promise. In this study, we explored the association between epigenetic age and incident T2D, in the context of their relationships with obesity. <p>A total of 1,057 participants in the Coronary Artery Risk Development in Young Adults (CARDIA) study were included in the current analyses. We stratified the participants into three groups; normal weight, overweight, and obese. A one-year increase of GrimAge was associated with higher 10-year (Y15 to Y25) incidence of T2D (OR=1.06, 95% CI=1.01-1.11). GrimAge acceleration, which represents the deviation of GrimAge from chronological age, was derived from the residuals of a model of GrimAge and chronological age, and any GrimAge acceleration (Positive GrimAA; having GrimAge older than chronological age) was associated with significantly higher odds of 10-year incidence of T2D in obese participants (OR=2.57, 95% CI=1.61-4.11). Cumulative obesity was estimated by years since obesity onset, and GrimAge partially mediated the statistical association between cumulative obesity and incident diabetes or prediabetes (proportion mediated = 8.0%). </p> In conclusion, both <a>older and accelerated GrimAge were associated with higher risk of T2D, particularly among obese participants. GrimAge also statistically mediated the associations between cumulative obesity and T2D. </a>Our findings suggest that epigenetic age measurements with DNA methylation can potentially be utilized as a risk factor or biomarker associated with T2D development.


Author(s):  
Maja Popovic ◽  
Valentina Fiano ◽  
Elena Isaevska ◽  
Chiara Moccia ◽  
Morena Trevisan ◽  
...  

Abstract Epigenetic age acceleration (AA) has been associated with adverse environmental exposures and many chronic conditions. We estimated, in the NINFEA birth cohort, infant saliva epigenetic age, and investigated whether parental socio-economic position (SEP) and pregnancy outcomes are associated with infant epigenetic AA. A total of 139 saliva samples collected at on average 10.8 (range 7–17) months were used to estimate Horvath’s DNA methylation age. Epigenetic AA was defined as the residual from a linear regression of epigenetic age on chronological age. Linear regression models were used to test the associations of parental SEP and pregnancy outcomes with saliva epigenetic AA. A moderate positive association was found between DNA methylation age and chronological age, with the median absolute difference of 6.8 months (standard deviation [SD] 3.9). The evidence of the association between the indicators of low SEP and epigenetic AA was weak; infants born to unemployed mothers or with low education had on average 1 month higher epigenetic age than infants of mothers with high education and employment (coefficient 0.78 months, 95% confidence intervals [CIs]: −0.79 to 2.34 for low/medium education; 0.96, 95% CI: −1.81 to 3.73 for unemployment). There was no evidence for association of gestational age, birthweight or caesarean section with infant epigenetic AA. Using the Horvath’s method, DNA methylation age can be fairly accurately predicted from saliva samples already in the first months of life. This study did not reveal clear associations between either pregnancy outcomes or parental socio-economic characteristics and infant saliva epigenetic AA.


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