scholarly journals Deconvolution of the epigenetic age discloses distinct inter-personal variability in epigenetic aging patterns

2021 ◽  
Author(s):  
Tamar Shahal ◽  
Elad Segev ◽  
Thomas Konstantinovsky ◽  
Yonit Marcus ◽  
Gabi Shefer ◽  
...  

Epigenetic age not only correlates with chronological age but predicts morbidity and mortality. We assumed that deconvolution of epigenetic age to its individual components could shed light on the diversity of epigenetic, and by inference, biological aging. Using the Horvath original epigenetic clock, we identified several CpG sites linked to distinct genes that quantitatively explain much of the interpersonal variability in epigenetic aging, with secretagogin and malin showing the most dominant effects. The analysis shows that the same epigenetic age for any given chronological age can be accounted for by variable contributions of identifiable CpG sites; that old epigenetic relative to chronological age is mostly explained by the same CpG sites, mapped to genes showing the highest interindividual variability differences in healthy subjects but not in subjects with type 2 diabetes. This paves the way to form personalized aging cards indicating the sources of accelerated/decelerated epigenetic aging in each examinee, en route to targeting specific sites as indicators, and perhaps treatment targets of personal undesirable age drifting.

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.


Author(s):  
Jordan A. Anderson ◽  
Rachel A. Johnston ◽  
Amanda J. Lea ◽  
Fernando A. Campos ◽  
Tawni N. Voyles ◽  
...  

AbstractAging, for virtually all life, is inescapable. However, within populations, biological aging rates vary. Understanding sources of variation in this process is central to understanding the biodemography of natural populations. We constructed a DNA methylation-based age predictor for an intensively studied wild baboon population in Kenya. Consistent with findings in humans, the resulting “epigenetic clock” closely tracks chronological age, but individuals are predicted to be somewhat older or younger than their known ages. Surprisingly, these deviations are not explained by the strongest predictors of lifespan in this population, early adversity and social integration. Instead, they are best predicted by male dominance rank: high-ranking males are predicted to be older than their true ages, and epigenetic age tracks changes in rank over time. Our results argue that achieving high rank for male baboons—the best predictor of reproductive success—imposes costs consistent with a “live fast, die young” life history strategy.


2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Ting Wang ◽  
Sean K. Maden ◽  
Georg E. Luebeck ◽  
Christopher I. Li ◽  
Polly A. Newcomb ◽  
...  

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.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Föhr Tiina ◽  
Waller Katja ◽  
Viljanen Anne ◽  
Sanchez Riikka ◽  
Ollikainen Miina ◽  
...  

Abstract Background Epigenetic clocks are based on DNA methylation (DNAm). It has been suggested that these clocks are useable markers of biological aging and premature mortality. Because genetic factors explain variations in both epigenetic aging and mortality, this association could also be explained by shared genetic factors. We investigated the influence of genetic and lifestyle factors (smoking, alcohol consumption, physical activity, chronic diseases, body mass index) and education on the association of accelerated epigenetic aging with mortality using a longitudinal twin design. Utilizing a publicly available online tool, we calculated the epigenetic age using two epigenetic clocks, Horvath DNAmAge and DNAm GrimAge, in 413 Finnish twin sisters, aged 63–76 years, at the beginning of the 18-year mortality follow-up. Epigenetic age acceleration was calculated as the residuals from a linear regression model of epigenetic age estimated on chronological age (AAHorvath, AAGrimAge, respectively). Cox proportional hazard models were conducted for individuals and twin pairs. Results The results of the individual-based analyses showed an increased mortality hazard ratio (HR) of 1.31 (CI95: 1.13–1.53) per one standard deviation (SD) increase in AAGrimAge. The results indicated no significant associations of AAHorvath with mortality. Pairwise mortality analyses showed an HR of 1.50 (CI95: 1.02–2.20) per 1 SD increase in AAGrimAge. However, after adjusting for smoking, the HR attenuated substantially and was statistically non-significant (1.29; CI95: 0.84–1.99). Similarly, in multivariable adjusted models the HR (1.42–1.49) was non-significant. In AAHorvath, the non-significant HRs were lower among monozygotic pairs in comparison to dizygotic pairs, while in AAGrimAge there were no systematic differences by zygosity. Further, the pairwise analysis in quartiles showed that the increased within pair difference in AAGrimAge was associated with a higher all-cause mortality risk. Conclusions In conclusion, the findings suggest that DNAm GrimAge is a strong predictor of mortality independent of genetic influences. Smoking, which is known to alter DNAm levels and is built into the DNAm GrimAge algorithm, attenuated the association between epigenetic aging and mortality risk.


2021 ◽  
Author(s):  
Emily M Bertucci ◽  
Marilyn W Mason ◽  
Olin E Rhodes ◽  
Benjamin B Parrott

The rate at which individuals age underlies variation in life history and attendant health and disease trajectories. Age specific patterning of the DNA methylome (epigenetic aging) is strongly correlated with chronological age in humans and can be modeled to produce epigenetic age predictors. However, epigenetic age estimates vary among individuals of the same age, and this mismatch is correlated to the onset of age-related disease and all-cause mortality. Yet, the origins of epigenetic-to-chronological age discordance are not resolved. In an effort to develop a tractable model in which environmental drivers of epigenetic aging can be assessed, we investigate the relationship between aging and DNA methylation in a small teleost, medaka (Oryzias latipes). We find that age-associated DNA methylation patterning occurs broadly across the genome, with the majority of age-related changes occurring during early life. By modeling the stereotypical nature of age-associated DNA methylation dynamics, we built an epigenetic clock, which predicts chronological age with a mean error of 29.1 days (~4% of average lifespan). Characterization of clock loci suggests that aspects of epigenetic aging are functionally similar across vertebrates. To understand how environmental factors interact with epigenetic aging, we exposed medaka to four doses of ionizing radiation for seven weeks, hypothesizing that exposure to such an environmental stressor would accelerate epigenetic aging. While the epigenetic clock was not significantly affected, radiation exposure accelerated and decelerated patterns of normal epigenetic aging, with radiation-induced epigenetic alterations enriched at loci that become hypermethylated with age. Together, our findings advance ongoing research attempting to elucidate the functional role of DNA methylation in integrating environmental factors into the rate of biological aging.


eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Jordan A Anderson ◽  
Rachel A Johnston ◽  
Amanda J Lea ◽  
Fernando A Campos ◽  
Tawni N Voyles ◽  
...  

Aging, for virtually all life, is inescapable. However, within populations, biological aging rates vary. Understanding sources of variation in this process is central to understanding the biodemography of natural populations. We constructed a DNA methylation-based age predictor for an intensively studied wild baboon population in Kenya. Consistent with findings in humans, the resulting 'epigenetic clock' closely tracks chronological age, but individuals are predicted to be somewhat older or younger than their known ages. Surprisingly, these deviations are not explained by the strongest predictors of lifespan in this population, early adversity and social integration. Instead, they are best predicted by male dominance rank: high-ranking males are predicted to be older than their true ages, and epigenetic age tracks changes in rank over time. Our results argue that achieving high rank for male baboons—the best predictor of reproductive success—imposes costs consistent with a 'live fast, die young' life history strategy.


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.


2021 ◽  
Author(s):  
Xiaoyu Liang ◽  
Rajita Sinha ◽  
Amy C. Justice ◽  
Mardge H. Cohen ◽  
Bradley E. Aouizerat ◽  
...  

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.


2019 ◽  
Vol 20 (12) ◽  
pp. 3032 ◽  
Author(s):  
Verena L. Banszerus ◽  
Valentin M. Vetter ◽  
Bastian Salewsky ◽  
Maximilian König ◽  
Ilja Demuth

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.


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3194-3194 ◽  
Author(s):  
Anna Mies ◽  
Tanja Božić ◽  
Michael Kramer ◽  
Julia Franzen ◽  
Gerhard Ehninger ◽  
...  

Abstract Introduction: Myelodysplastic syndromes (MDS) are frequently associated with somatic mutations in epigenetic modifiers such as de novo methyltransferase 3A (DNMT3A). However, so far the significance of specific epigenetic modifications for disease stratification remains largely unknown. In this study, we investigated if epigenetic biomarkers, which were previously described to be relevant in acute myeloid leukemia (AML), are also of prognostic impact in MDS. Methods: Peripheral blood samples of MDS patients (n=126; f/m=59/67; median age 66; range 26-93) equally distributed across all risk groups based on the revised International Prognostic Scoring System (IPSS-R; very low/low=43; int=37; high/very high=43; n.a.=3) were analyzed at initial diagnosis. Genomic DNA was isolated, bisulfite converted, and DNA methylation (DNAm) level at selected genomic regions were determined by pyrosequencing as described before: (1) hypermethylation at a CpG site in complement component 1 subcomponent R (C1R), (2) an epigenetic age prediction with an Epigenetic-Aging-Signature based on three CpG sites located in the genes ITGA2B, ASPA and PDE4C, and (3) an epimutation in the DNMT3A locus, mimicking somatic mutations of this gene, were all reported to correlate with overall survival (OS) in AML patients. Results were subsequently compared to clinical parameters such as IPSS-R, leukemic progression, and OS. Results: A clear tendency for longer OS of MDS patients was observed if DNAm level at C1R was above median (22%; two-year survival 67% [95% CI 53-84%] in hypo- vs. 84% [95% CI 74-95%] in hypermethylated samples; P=0.071), which is in line with previous findings in AML samples. The predicted epigenetic age determined by the Epigenetic-Aging-Signature correlated moderately with the chronological age of the investigated MDS patients (R=0.42) and their OS (P=0.029). This effect was also seen in a multivariable analysis of this cohort including predicted and chronological age (P=0.040). Finally, we stratified MDS patients by the DNAm level of 10% in DNMT3A. Similar to AML, also MDS patients with higher methylation at the CpG site represented on a microarray (cg23009818) showed in tendency shorter OS (two-year survival 79% [95% CI 69-89%] in hypo- vs. 65% [95% CI 45-93%] in hypermethylated samples; P=0.110). In fact, this association was even more pronounced at a neighboring CpG site (two-year survival 83% [95% CI 74-92%] in hypo- vs. 49% [95% CI 29-84%] in hypermethylated samples; P=0.009; Figure A). Moreover, increased DNAm level at this neighboring CpG site in DNMT3A was indicative for progression into AML (after two years: 15% [95% CI 6-24%] in hypo- vs. 44% [95% CI 12-76%] in hypermethylated samples; P=0.011; Figure B). Of note, none of these markers correlated with IPSS-R categories indicating that they might provide independent prognostic parameters. Conclusion: The analyzed epigenetic biomarkers revealed prognostic relevance in MDS patients and we suggest considering them in future risk stratification models. Particularly the aberrant hypermethylation of DNMT3A, which may also result in alternative splicing of DNMT3A transcripts, was associated with accelerated leukemic progression and shorter OS. Figure Figure. Disclosures Božić: Cygenia GmbH: Consultancy. Wagner:Cygenia GmbH: Equity Ownership.


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