scholarly journals Association of Facial Aging with DNA Methylation and Epigenetic Age Predictions

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.

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 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.


2020 ◽  
Author(s):  
Julia Franzen ◽  
Selina Nüchtern ◽  
Vithurithra Tharmapalan ◽  
Margherita Vieri ◽  
Miloš Nikolić ◽  
...  

AbstractAge is a major risk factor for severe outcome of coronavirus disease 2019 (COVID-19), but it remains unclear if this is rather due to increased chronological age or biological age. During lifetime, specific DNA methylation changes are acquired in our genome that act as “epigenetic clocks” allowing to estimate donor age and to provide a surrogate marker for biological age. In this study, we followed the hypothesis that particularly patients with accelerated epigenetic age are affected by severe outcomes of COVID-19. Using four different age predictors, we did not observe accelerated age in global DNA methylation profiles of blood samples of nine COVID-19 patients. Alternatively, we used targeted bisulfite amplicon sequencing of three age-associated genomic regions to estimate donor-age of blood samples of 95 controls and seventeen COVID-19 patients. The predictions correlated well with chronological age, while COVID-19 patients even tended to be predicted younger than expected. Furthermore, lymphocytes in nineteen COVID-19 patients did not reveal significantly accelerated telomere attrition. Our results demonstrate that these biomarkers of biological age are therefore not suitable to predict a higher risk for severe COVID-19 infection in elderly patients.


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 &lt; 0.001). In patients with chronic HCV infection (n=63), age acceleration was associated with liver fibrosis as assessed by histology (p &lt; 0.05), or presence of HIV co-infection (p &lt; 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.


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.


2021 ◽  
Vol 7 ◽  
pp. 233372142110464
Author(s):  
Trevor Lohman ◽  
Gurinder Bains ◽  
Lee Berk ◽  
Everett Lohman

As healthspan and lifespan research breakthroughs have become more commonplace, the need for valid, practical markers of biological age is becoming increasingly paramount. The accessibility and affordability of biological age predictors that can reveal information about mortality and morbidity risk, as well as remaining years of life, has profound clinical and research implications. In this review, we examine 5 groups of aging biomarkers capable of providing accurate biological age estimations. The unique capabilities of these biomarkers have far reaching implications for the testing of both pharmaceutical and non-pharmaceutical interventions designed to slow or reverse biological aging. Additionally, the enhanced validity and availability of these tools may have increasingly relevant clinical value. The authors of this review explore those implications, with an emphasis on lifestyle modification research, and provide an overview of the current evidence regarding 5 biological age predictor categories: Telomere length, composite biomarkers, DNA methylation “epigenetic clocks,” transcriptional predictors of biological age, and functional age predictors.


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 ◽  
Vol 2 ◽  
Author(s):  
Rebecca L. McIntyre ◽  
Mizanur Rahman ◽  
Siva A. Vanapalli ◽  
Riekelt H. Houtkooper ◽  
Georges E. Janssens

Intervening in aging processes is hypothesized to extend healthy years of life and treat age-related disease, thereby providing great benefit to society. However, the ability to measure the biological aging process in individuals, which is necessary to test for efficacy of these interventions, remains largely inaccessible to the general public. Here we used NHANES physical activity accelerometer data from a wearable device and machine-learning algorithms to derive biological age predictions for individuals based on their movement patterns. We found that accelerated biological aging from our “MoveAge” predictor is associated with higher all-cause mortality. We further searched for nutritional or pharmacological compounds that associate with decelerated aging according to our model. A number of nutritional components peak in their association to decelerated aging later in life, including fiber, magnesium, and vitamin E. We additionally identified one FDA-approved drug associated with decelerated biological aging: the alpha-blocker doxazosin. We show that doxazosin extends healthspan and lifespan in C. elegans. Our work demonstrates how a biological aging score based on relative mobility can be accessible to the wider public and can potentially be used to identify and determine efficacy of geroprotective interventions.


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.


Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Jordi Jimenez-Conde ◽  
Carolina Soriano-Tarraga ◽  
Eva Giralt-Steinhauer ◽  
Marina Mola ◽  
Rosa Vivanco-Hidalgo ◽  
...  

Background: Stroke has a great impact in functional status of patients, although there are substantial interindividual differences in recovery capacity. Apart from stroke severity, age is considered an important predictor of outcome after stroke, but aging is not only due to chronological age. There are age-related DNA-methylation changes in multiple CpG sites across the genome that can be used to estimate the biological age (b-Age), and we seek to analyze the impact of this b-Age in recovery after an ischemic stroke. Methods: We include 600 individuals with acute ischemic stroke assessed in Hospital del Mar (Barcelona). Demographic and clinical data such as chronological age (c-Age), vascular risk factors, NIHSS at admission, recanalization treatment (rtPA or endovascular treatment), previous modified Rankin scale (p-mRS) and 3 months post stroke functional status (3-mRS) were registered. Biological age (b-Age) was estimated with Hannumm algorithm, based on DNA methylation in 71 CpGs. Results: The bivariate analyses for association with 3-mRS showed a significant results of NIHSS, c-Age, b-Age, p-mRS, and current smoking (all with p<0.001). Recanalization treatment showed no significant differences in bivariate analysis. In multivariate ordinal models, b-Age kept its significance (p=0.025) nullifying c-Age (p=0.84). Initial NIHSS, p-mRS and recanalization treatment kept also significant results (p<0.001). Conclusions: Biological Age, estimated by DNA methylation, is an independent predictor of stroke prognosis, irrespective to chronological age. "Healthy aging” affects the capacity of recovering after an ischemic stroke.


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