scholarly journals Exploring the Relationship of Relative Telomere Length and the Epigenetic Clock in the LipidCardio Cohort

2019 ◽  
Vol 20 (12) ◽  
pp. 3032 ◽  
Author(s):  
Verena L. Banszerus ◽  
Valentin M. Vetter ◽  
Bastian Salewsky ◽  
Maximilian König ◽  
Ilja Demuth
Keyword(s):  
Telomere Length ◽  
Penalized Regression ◽  
Biological Age ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Single Nucleotide ◽  
Epigenetic Age ◽  
High Prevalence ◽  
Relationship Of ◽  
The Relationship

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.

scholarly journals Epigenetic clock and DNA methylation studies of roe deer in the wild

2020 ◽  
Author(s):  
Jean-François Lemaître ◽  
Benjamin Rey ◽  
Jean-Michel Gaillard ◽  
Corinne Régis ◽  
Emmanuelle Gilot ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Evolutionary Biology ◽  
Roe Deer ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Aging Effects ◽  
Methylation Array ◽  
Biomarkers Of Aging ◽  
Epigenetic Age ◽  
The Relationship

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.

scholarly journals Exploring Epigenetic Age in Response to Intensive Relaxing Training: A Pilot Study to Slow Down Biological Age

2019 ◽  
Vol 16 (17) ◽  
pp. 3074 ◽  
Author(s):  
Pavanello ◽  
Campisi ◽  
Tona ◽  
Lin ◽  
Iliceto
Keyword(s):  
Myocardial Infarction ◽  
Age Estimation ◽  
Healthy Subjects ◽  
Molecular Mechanisms ◽  
Biological Age ◽  
Chronological Age ◽  
Biological Aging ◽  
Epigenetic Clock ◽  
Age Related ◽  
Epigenetic Age

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.

scholarly journals Dysfunctional epigenetic aging of the normal colon and colorectal cancer risk

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Ting Wang ◽  
Sean K. Maden ◽  
Georg E. Luebeck ◽  
Christopher I. Li ◽  
Polly A. Newcomb ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Risk Group ◽  
Risk Groups ◽  
Biological Age ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Normal Colon ◽  
Epigenetic Aging ◽  
Epigenetic Age ◽  
Epigenetic Age Acceleration

Abstract Background Chronological age is a prominent risk factor for many types of cancers including colorectal cancer (CRC). Yet, the risk of CRC varies substantially between individuals, even within the same age group, which may reflect heterogeneity in biological tissue aging between people. Epigenetic clocks based on DNA methylation are a useful measure of the biological aging process with the potential to serve as a biomarker of an individual’s susceptibility to age-related diseases such as CRC. Methods We conducted a genome-wide DNA methylation study on samples of normal colon mucosa (N = 334). Subjects were assigned to three cancer risk groups (low, medium, and high) based on their personal adenoma or cancer history. Using previously established epigenetic clocks (Hannum, Horvath, PhenoAge, and EpiTOC), we estimated the biological age of each sample and assessed for epigenetic age acceleration in the samples by regressing the estimated biological age on the individual’s chronological age. We compared the epigenetic age acceleration between different risk groups using a multivariate linear regression model with the adjustment for gender and cell-type fractions for each epigenetic clock. An epigenome-wide association study (EWAS) was performed to identify differential methylation changes associated with CRC risk. Results Each epigenetic clock was significantly correlated with the chronological age of the subjects, and the Horvath clock exhibited the strongest correlation in all risk groups (r > 0.8, p < 1 × 10−30). The PhenoAge clock (p = 0.0012) revealed epigenetic age deceleration in the high-risk group compared to the low-risk group. Conclusions Among the four DNA methylation-based measures of biological age, the Horvath clock is the most accurate for estimating the chronological age of individuals. Individuals with a high risk for CRC have epigenetic age deceleration in their normal colons measured by the PhenoAge clock, which may reflect a dysfunctional epigenetic aging process.

scholarly journals The Epigenetic Pacemaker is a more sensitive tool than penalized regression for identifying moderators of epigenetic aging

2021 ◽  
Author(s):  
Colin Farrell ◽  
Kalsuda Lapborisuth ◽  
Chanyue Hu ◽  
Kyle Pu ◽  
Sagi Snir ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Penalized Regression ◽  
Chronological Age ◽  
Data Set ◽  
Epigenetic State ◽  
Age Related ◽  
Epigenetic Aging ◽  
Epigenetic Age ◽  
The Impact ◽  
The Relationship

Epigenetic clocks, DNA methylation based chronological age prediction models, are commonly employed to study age related biology. The error between the predicted and observed age is often interpreted as a form of biological age acceleration and many studies have measured the impact of environmental and other factors on epigenetic age. Epigenetic clocks are fit using approaches that minimize the error between the predicted and observed chronological age and as a result they reduce the impact of factors that may moderate the relationship between actual and epigenetic age. Here we compare the standard methods used to construct epigenetic clocks to an evolutionary framework of epigenetic aging, the epigenetic pacemaker (EPM) that directly models DNA methylation as a function of a time dependent epigenetic state. We show that the EPM is more sensitive than epigenetic clocks for the detection of factors that moderate the relationship between actual age and epigenetic state (ie epigenetic age). Specifically, we show that the EPM is more sensitive at detecting sex and cell type effects in a large aggregate data set and in an example case study is more sensitive sensitive at detecting age related methylation changes associated with polybrominated biphenyl exposure. Thus we find that the pacemaker provides a more robust framework for the study of factors that impact epigenetic age acceleration than traditional clocks based on linear regression models.

scholarly journals DNA methylation age acceleration and risk factors for Alzheimer’s disease

2018 ◽  
Author(s):  
Daniel L McCartney ◽  
Anna J Stevenson ◽  
Rosie M Walker ◽  
Jude Gibson ◽  
Stewart W Morris ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Environmental Risk ◽  
Environmental Risk Factors ◽  
Biological Age ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
The Relationship

AbstractINTRODUCTIONThe ‘epigenetic clock’ is a DNA methylation-based estimate of biological age and is correlated with chronological age – the greatest risk factor for Alzheimer’s disease (AD). Genetic and environmental risk factors exist for AD, several of which are potentially modifiable. Here, we assess the relationship associations between the epigenetic clock and AD risk factors.METHODSLinear mixed modelling was used to assess the relationship between age acceleration (the residual of biological age regressed onto chronological age) and AD risk factors relating to cognitive reserve, lifestyle, disease, and genetics in the Generation Scotland study (n=5,100).RESULTSWe report significant associations between the epigenetic clock and BMI, total:HDL cholesterol ratios, socioeconomic status, and smoking behaviour (Bonferroni-adjusted P<0.05).DISCUSSIONAssociations are present between environmental risk factors for AD and age acceleration. Measures to modify such risk factors might improve the risk profile for AD and the rate of biological ageing. Future longitudinal analyses are therefore warranted.

scholarly journals IL-1R2 Polymorphisms and its Interaction Associates With Osteoporosis Susceptibility in Chinese Han Population

2020 ◽  
Author(s):  
Kai Rong ◽  
Zhiquan Liang ◽  
Wenyuan Xiang ◽  
Zhan Wang ◽  
Fengli Wen ◽  
...  
Keyword(s):  
Negative Regulator ◽  
Chinese Han Population ◽  
Nucleotide Polymorphisms ◽  
Chinese Han ◽  
Single Nucleotide ◽  
Han Population ◽  
Testing Accuracy ◽  
Relationship Of ◽  
The Relationship ◽  
Osteoporosis Risk

Abstract Background: IL-1R2, serves as a negative regulator of IL-1 signaling, is involved in the pathogenesis of osteoporosis. This study aimed to determine the correlation between IL-1R2 polymorphism and osteoporosis susceptibility among the Chinese Han population.Methods: We recruited 594 osteoporosis patients and 599 healthy controls. Six single nucleotide polymorphisms (SNPs) in IL-1R2 were selected for genotyping using Agena MassARRAY platform. Odds ratio (OR) and 95% confidence interval (CI) was calculated through logistic regression analysis with adjustment for age and sex. Linkage disequilibrium analysis was plotted by Haploview v4.2. Multifactor dimension reduction (MDR) was performed to estimate the SNP-SNP interaction of IL-1R2 variants.Results: Our result revealed that rs11674595 (OR = 1.86, p = 0.020), rs2072472 (OR = 1.26, p = 0.019) and rs4851527 (OR = 0.78, p = 0.007) were related to the risk of osteoporosis. Moreover, the contribution of IL-1R2 polymorphisms to osteoporosis risk presented age, sex and BMI difference. We found the relationship of Trs11674595Ars4851527 (OR = 0.80, p = 0.015), Crs11674595Grs4851527 (OR = 1.22, p = 0.043) and Ars3218977Grs2072472 (OR = 1.25, p = 0.022) haplotypes to osteoporosis occurrence, and a potential accumulated effect of IL-1R2 SNPs (testing accuracy = 0.5783 and CVC = 10/10) on osteoporosis susceptibility.Conclusion: IL-1R2 polymorphisms (rs11674595, rs4851527, rs2072472 and rs3218977) might contribute to osteoporosis risk among the Chinese Han population. Our finding may increase our understanding of the effects of IL-1R2 polymorphisms on the predisposition of osteoporosis.

scholarly journals Epigenetic clocks reveal a rejuvenation event during embryogenesis followed by aging

2021 ◽  
Author(s):  
Csaba Kerepesi ◽  
Bohan Zhang ◽  
Sang-Goo Lee ◽  
Alexandre Trapp ◽  
Vadim N. Gladyshev
Keyword(s):  
Pluripotent Stem Cells ◽  
Prenatal Development ◽  
Biological Age ◽  
Epigenetic Clock ◽  
Ground Zero ◽  
August Weismann ◽  
Age Related ◽  
Epigenetic Age ◽  
Human Prenatal Development ◽  
Changes Over Time

The notion that germline cells do not age goes back to the 19th century ideas of August Weismann. However, being in a metabolically active state, they accumulate damage and other age-related changes over time, i.e., they age. For new life to begin in the same young state, they must be rejuvenated in the offspring. Here, we developed a new multi-tissue epigenetic clock and applied it, together with other aging clocks, to track changes in biological age during mouse and human prenatal development. This analysis revealed a significant decrease in biological age, i.e. rejuvenation, during early stages of embryogenesis, followed by an increase in later stages. We further found that pluripotent stem cells do not age even after extensive passaging and that the examined epigenetic age dynamics is conserved across species. Overall, this study uncovers a natural rejuvenation event during embryogenesis and suggests that the minimal biological age (the ground zero) marks the beginning of organismal aging.

scholarly journals A New Monocyte Epigenetic Clock Reveals Effects of Alcohol Consumption on Epigenetic Aging in Three Independent Cohorts

2021 ◽  
Author(s):  
Xiaoyu Liang ◽  
Rajita Sinha ◽  
Amy C. Justice ◽  
Mardge H. Cohen ◽  
Bradley E. Aouizerat ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Hiv Infection ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Biological Age ◽  
Biological Aging ◽  
Epigenetic Clock ◽  
Excessive Alcohol Consumption ◽  
Epigenetic Age ◽  
The Impact

AbstractBackgroundExcessive alcohol consumption increases the risk of aging-related comorbidities and mortality. Assessing the impact of alcohol consumption on biological age is important for clinical decision-making and prevention. Evidence shows that alcohol alters monocyte function, and age is associated with DNA methylome and transcriptomic changes among monocytes. However, no monocyte-based epigenetic clock is currently available. In this study, we developed a new monocyte-based DNA methylation clock (MonoDNAmAge) by using elastic net regularization. The MonoDNAmAge was validated by benchmarking using epigenetic age acceleration (EAA) in HIV infection. Using MonoDNAmAge clock as well as four established clocks (i.e., HorvathDNAmAge, HannumDNAmAge, PhenoDNAmAge, GrimDNAmAge), we then evaluated the effect of alcohol consumption on biological aging in three independent cohorts (N=2,242).ResultsMonoDNAmAge, comprised of 186 CpG sites, was highly correlated with chronological age (rtraining=0.96, p<2.20E-16; rtesting=0.86, p=1.55E-141). The MonoDNAmAge clock predicted an approximately 10-year age acceleration from HIV infection in two cohorts. Quadratic regression analysis showed a nonlinear relationship between MonoDNAmAge and alcohol consumption in the Yale Stress Center Community Study (YSCCS, pmodel=4.55E-08, px2 =7.80E-08) and in the Veteran Aging Cohort Study (VACS, pmodel=1.85E-02, px2 =3.46E-02). MonoDNAmAge and light alcohol consumption showed a negative linear relationship in the Women’s Interagency HIV Study (WIHS, β=-2.63, px=2.82E-06). Heavy consumption increased EAAMonoDNAmAge up to 1.60 years in the VACS while light consumption decreased EAAMonoDNAmAge to 2.66 years in the WIHS. These results were corroborated by the four established epigenetic clocks.ConclusionsWe observed a nonlinear effect of alcohol consumption on epigenetic age that is estimated by a novel monocyte-based “clock” in three distinct cohorts, highlighting the complex effects of alcohol consumption on biological age.

scholarly journals COMPARABILITY OF BIOLOGICAL AGING MEASURES IN THE NATIONAL HEALTH AND NUTRITION EXAMINATION STUDY, 1999-2002

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S479-S479
Author(s):  
Waylon J Hastings ◽  
Daniel Belsky ◽  
Idan Shalev
Keyword(s):  
Risk Factors ◽  
Telomere Length ◽  
Cellular Level ◽  
Biological Age ◽  
Effect Sizes ◽  
Chronological Age ◽  
Biological Aging ◽  
Patient Level ◽  
Age Related ◽  
Level Information

Abstract Biological processes of aging are thought to be modifiable causes of many chronic diseases. Measures of biological aging could provide sensitive endpoints for studies of risk factors hypothesized to shorten healthy lifespan and/or interventions that extend it. However, uncertainty remains about how to measure biological aging and if proposed measures assess the same thing. We tested four proposed measures of biological aging with available data from NHANES 1999-2002: Klemera-Doubal method (KDM) Biological Age, homeostatic dysregulation, Levine Method (LM) Biological Age, and leukocyte telomere length. All measures of biological aging were correlated with chronological age. KDM Biological Age, homeostatic dysregulation, and LM Biological Age were all significantly associated with each other, but were each not associated with telomere length. NHANES participants with older biological ages performed worse on tests of physical, cognitive, perceptual, and subjective functions known to decline with advancing chronological age and thought to mediate age-related disability. Further, NHANES participants with higher levels of exposure to life-course risk factors were measured as having older biological ages. In both sets of analyses, effect-sizes tended to be larger for KDM Biological Age, homeostatic dysregulation, and LM Biological Age as compared to telomere length. Composite measures combining cellular- and patient-level information tended to have the largest effect-sizes. The cellular-level aging biomarker telomere length may measure different aspects of the aging process relative to the patient-level physiological measures. Studies aiming to test if risk factors accelerate aging or if interventions may slow aging should not treat proposed measures of biological aging as interchangeable.

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