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 Epigenetic Age Acceleration Reflects Long-Term Cardiovascular Health

2021 ◽  
Author(s):  
Brian Joyce ◽  
Tao Gao ◽  
Yinan Zheng ◽  
Jiantao Ma ◽  
Shih-Jen Hwang ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Dna Methylation ◽  
Cardiovascular Health ◽  
Clinical Score ◽  
Chronological Age ◽  
Cvd Risk ◽  
Cross Sectional ◽  
Age Related ◽  
Epigenetic Aging ◽  
Epigenetic Age

Rationale: Epigenetic aging is a novel measure of biological age, reflecting exposures and disease risks independent of chronological age. It may serve as a useful biomarker of cardiovascular health (CVH) and/or cardiovascular disease (CVD) risk for early detection or prevention. Objective: To examine associations between GrimAge acceleration (GrimAA), a measure of epigenetic aging calculated from the residuals of GrimAge regressed on chronological age, and two repeated CVH measures: a full score for the AHA "Life's Simple 7" (diet, smoking, physical activity, BMI, blood pressure, total cholesterol, and glucose) and a clinical CVH score (BMI, blood pressure, cholesterol, and glucose). Methods and Results: We used Illumina array DNA methylation data from two prospective cohort studies: The Coronary Artery Risk Development in Young Adults (CARDIA) study and Framingham Heart Study (FHS), to calculate GrimAA and model associations with CVH. CARDIA randomly selected 1,118 participants for assays at Y15 (2000-2001; mean age 40) and/or Y20 (2005-2006); in FHS, 2,106 Offspring participants had DNA methylation measured at exam 8 (2005-2008; mean age 66). We examined multiple cross-sectional and longitudinal models of GrimAA and each CVH score measured at CARDIA Y0-Y20 and FHS exams 7-8. In CARDIA clinical CVH score from Y0-Y20 was associated with Y15 and Y20 GrimAA (β range -0.41 to -0.21 years per 1-point increase in CVH; p range <0.01 to 0.01), as was full score (β range -0.65 to -0.67 years; p<0.01 for all). These findings were validated in FHS (clinical score β range -0.51 to -0.54 years; full score β range -0.76 to -0.83 years; p<0.01 for all). Conclusions: Our data demonstrate that faster GrimAA is associated with the loss of CVH from young age. Epigenetic age may be a useful biomarker of CVD risk and provides biological insight into the role of epigenetic mechanisms linking age-related CVH loss and CVD.

scholarly journals The aging DNA methylome reveals environment-by-aging interactions in a model teleost

2021 ◽  
Author(s):  
Emily M Bertucci ◽  
Marilyn W Mason ◽  
Olin E Rhodes ◽  
Benjamin B Parrott
Keyword(s):  
Dna Methylation ◽  
Environmental Factors ◽  
Environmental Drivers ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Ongoing Research ◽  
Dna Methylome ◽  
Age Related ◽  
Epigenetic Aging ◽  
Epigenetic Age

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.

scholarly journals Epigenetic Age Acceleration and Hearing: Observations From the Baltimore Longitudinal Study of Aging

2021 ◽  
Vol 13 ◽  
Author(s):  
Pei-Lun Kuo ◽  
Ann Zenobia Moore ◽  
Frank R. Lin ◽  
Luigi Ferrucci
Keyword(s):  
Dna Methylation ◽  
Longitudinal Study ◽  
Smoking History ◽  
Future Research ◽  
Age Related ◽  
Epigenetic Age ◽  
Epigenetic Age Acceleration ◽  
Baltimore Longitudinal Study ◽  
Age Related Hearing Loss ◽  
The Relationship

Objectives: Age-related hearing loss (ARHL) is highly prevalent among older adults, but the potential mechanisms and predictive markers for ARHL are lacking. Epigenetic age acceleration has been shown to be predictive of many age-associated diseases and mortality. However, the association between epigenetic age acceleration and hearing remains unknown. Our study aims to investigate the relationship between epigenetic age acceleration and audiometric hearing in the Baltimore Longitudinal Study of Aging (BLSA).Methods: Participants with both DNA methylation and audiometric hearing measurements were included. The main independent variables are epigenetic age acceleration measures, including intrinsic epigenetic age acceleration—“IEAA,” Hannum age acceleration—“AgeAccelerationResidualHannum,” PhenoAge acceleration—“AgeAccelPheno,” GrimAge acceleration—“AgeAccelGrim,” and methylation-based pace of aging estimation—“DunedinPoAm.” The main dependent variable is speech-frequency pure tone average. Linear regression was used to assess the association between epigenetic age acceleration and hearing.Results: Among the 236 participants (52.5% female), after adjusting for age, sex, race, time difference between measurements, cardiovascular factors, and smoking history, the effect sizes were 0.11 995% CI: (–0.00, 0.23), p = 0.054] for Hannum’s clock, 0.08 [95% CI: (–0.03, 0.19), p = 0.143] for Horvath’s clock, 0.10 [95% CI: (–0.01, 0.21), p = 0.089] for PhenoAge, 0.20 [95% CI: (0.06, 0.33), p = 0.004] for GrimAge, and 0.21 [95% CI: (0.09, 0.33), p = 0.001] for DunedinPoAm.Discussion: The present study suggests that some epigenetic age acceleration measurements are associated with hearing. Future research is needed to study the potential subclinical cardiovascular causes of hearing and to investigate the longitudinal relationship between DNA methylation and hearing.

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.

Abstract 160: DNA-Methylation and Aging. Contribution of Biological Age to Recovery After Ischemic Stroke

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Jordi Jimenez-Conde ◽  
Carolina Soriano-Tarraga ◽  
Eva Giralt-Steinhauer ◽  
Marina Mola ◽  
Rosa Vivanco-Hidalgo ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Ischemic Stroke ◽  
Functional Status ◽  
Biological Age ◽  
Chronological Age ◽  
Bivariate Analysis ◽  
Stroke Severity ◽  
Age Related ◽  
Recovery Capacity ◽  
The Impact

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.

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 DNA methylation GrimAge and Incident Diabetes: The Coronary Artery Risk Development in Young Adults (CARDIA) Study

2021 ◽  
Author(s):  
Kyeezu Kim ◽  
Brian T. Joyce ◽  
Yinan Zheng ◽  
Pamela J. Schreiner ◽  
David R. Jacobs Jr. ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Young Adults ◽  
Coronary Artery ◽  
Normal Weight ◽  
Incident Diabetes ◽  
Chronological Age ◽  
Age Related ◽  
Epigenetic Age ◽  
One Year

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.

scholarly journals The combined effect of obesity and aging on human sperm DNA methylation signatures: inclusion of BMI in the paternal germ line age prediction model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Albert Salas-Huetos ◽  
Emma R. James ◽  
Dallin S. Broberg ◽  
Kenneth I. Aston ◽  
Douglas T. Carrell ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Germ Line ◽  
Age Groups ◽  
Human Sperm ◽  
Absolute Error ◽  
Epigenetic Aging ◽  
Epigenetic Age ◽  
Sperm Dna ◽  
Epigenetic Age Acceleration ◽  
The Impact

Abstract Male aging and obesity have both been shown to contribute to declines in fertility in men. Recent work in aging has shown consistent epigenetic changes to sperm as a man ages. In fact, our lab has built a tool that utilizes DNA methylation signatures from sperm to effectively predict an individual’s age. Herein, we performed this preliminary cohort study to determine if increased BMI accelerates the epigenetic aging in sperm. A total of 96 participants were divided into four age groups (22–24, 30, 40–41, and > 48 years of age) and additionally parsed into two BMI sub-categories (normal and high/obese). We found no statistically significant epigenetic age acceleration. However, it is important to note that within each age category, high BMI individuals were predicted to be older on average than their actual age (~ 1.4 years), which was not observed in the normal BMI group. To further investigate this, we re-trained a model using only the present data with and without BMI as a feature. We found a modest but non-significant improvement in prediction with BMI [r2 = 0.8814, mean absolute error (MAE) = 3.2913] compared to prediction without BMI (r2 = 0.8739, MAE = 3.3567). Future studies with higher numbers of age-matched individuals are needed to definitively understand the impact of BMI on epigenetic aging in sperm.

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 Epigenetic age-predictions in mice using pyrosequencing, droplet digital PCR or barcoded bisulfite amplicon sequencing

2020 ◽  
Author(s):  
Yang Han ◽  
Miloš Nikolić ◽  
Michael Gobs ◽  
Julia Franzen ◽  
Gerald de Haan ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Model Organism ◽  
Amplicon Sequencing ◽  
Digital Pcr ◽  
Droplet Digital Pcr ◽  
Biological Aging ◽  
Epigenetic Aging ◽  
Epigenetic Age ◽  
Trait Locus ◽  
The Impact

AbstractAge-associated DNA methylation reflects aspects of biological aging - therefore epigenetic clocks for mice can help to elucidate the impact of treatments or genetic background on the aging process in this model organism. Initially, age-predictors for mice were trained on genome-wide DNA methylation profiles, whereas we have recently described a targeted assay based on pyrosequencing of DNA methylation at only three CG dinucleotides (CpGs). Here, we have re-evaluated pyrosequencing approaches in comparison to droplet digital PCR (ddPCR) and barcoded bisulfite amplicon sequencing (BBA-seq). At individual CpGs the correlation of DNA methylation with chronological age was slightly higher for pyrosequencing and ddPCR as compared to BBA-seq. On the other hand, BBA-seq revealed that neighboring CpGs tend to be stochastically modified in murine age-associated regions. Furthermore, the binary sequel of methylated and non-methylated CpGs in individual reads can be used for single-read predictions, which may reflect heterogeneity in epigenetic aging. In comparison to C57BL/6 mice the epigenetic age-predictions using BBA-seq were also accelerated in the shorter-lived DBA/2 mice, and in C57BL/6 mice with a lifespan quantitative trait locus of DBA/2 mice. Taken together, we describe further optimized and alternative targeted methods to determine epigenetic clocks in mice.

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