Abstract P106: Epigenetic Age Acceleration and Postprandial Lipemia in the Genetics of Lipid Lowering Drugs and Diet Network Study

Circulation ◽  
2017 ◽  
Vol 135 (suppl_1) ◽  
Author(s):  
Marguerite R Irvin ◽  
Bertha Hidalgo ◽  
Degui Zhi ◽  
Stella Aslibekyan ◽  
Hemant K Tiwari ◽  
...  
Keyword(s):  
Dna Methylation ◽  
T Cell ◽  
Density Lipoprotein ◽  
Lipid Lowering ◽  
Chronological Age ◽  
Lipid Levels ◽  
Lipid Lowering Drugs ◽  
Epigenetic Aging ◽  
Epigenetic Age ◽  
Epigenetic Age Acceleration

Background: Calculated ‘epigenetic age,’ a novel biomarker based on DNA methylation levels of 353 CpGs, has been demonstrated to accurately predict chronological age across a broad spectrum of tissues and cell types. Recently epigenetic age acceleration or older epigenetic age in comparison to chronological age has been robustly associated with all-cause mortality independent of chronological age in multiple human cohorts. However, accelerated epigenetic aging has not been associated with lipids levels, including postprandial lipid levels which are linked to prothrombotic and proinflammatory processes that may precipitate aging. In the current study we aimed to evaluate the association between epigenetic age acceleration and lipid levels. Methods: We used the Horvath DNA methylation age calculator to estimate epigenetic age in 988 Caucasian participants from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) using Illumina Infinium HumanMethylation450 BeadChip array data derived from CD4+ T-cell DNA. GOLDN participants did not take lipid lowering drugs for at least four weeks prior to enrollment and underwent a standardized high fat meal challenge after fasting for at least 8 hours followed by timed blood draws at 3.5 and 6 hours following the meal. Epigenetic age acceleration was calculated as the residual from regressing methylation age on chronological age. We used linear mixed models to examine the association of age acceleration quartiles with fasting and postrandial (3.5 and 6 hour time points) low density lipoprotein (LDL), high density lipoprotein (HDL) and triglyceride (TG) levels after adjusting for age, study site, sex, fasting lipid level (if applicable), deconvolution estimated T-cell type percentages and a random effect of family relationship. Results: The correlation between calculated methylation age and chronological age was 0.91. The difference between methylation age and chronological age (methylation age - chronological age) was on average -5.8 (5.9), -0.5 (4.7), 2.9 (4.3), and 7.8 (5.0) years for the first through fourth quartiles of age acceleration, respectively. After adjustment for covariates neither fasting nor postprandial lipids were associated with age acceleration quartile. Conclusions: Evidence from the current study suggests lipid levels in the fasting and postprandial state are not related to accelerated epigenetic aging, however given the association between epigenetic age acceleration and mortality observed in previous studies the relationship of other metabolic parameters with age acceleration may be worthy of investigation.

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 Blood Lipid Levels in Patients with Osteopenia and Osteoporosis: A Systematic Review and Meta-Analysis

2020 ◽  
Author(s):  
Hang Zhao ◽  
An Song ◽  
Yong Li ◽  
Licui Qi ◽  
Chong Zheng ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Density Lipoprotein ◽  
Blood Lipid ◽  
Relevant Information ◽  
Lipid Lowering ◽  
Cochrane Library ◽  
Lipid Levels ◽  
Lipid Lowering Drugs ◽  
Blood Lipid Levels

Abstract Background: Considering the controversial relationship between blood lipid levels and osteopenia and osteoporosis (OP), we performed this meta-analysis.Methods: Using specific keywords and related words, we searched PubMed, Embase, and Cochrane Library databases. The Newcastle-Ottawa Scale form was used to evaluate the quality of the literature. According to the inclusion and exclusion criteria, we systematically screened the literature to extract relevant information and data. Revman 5.3 and Stata 13.0 software were used for statistical analysis. Results were expressed as the mean difference and 95% confidence interval. The heterogeneity test was conducted according to I2 and Q tests. Egger’s test was used to quantitatively evaluate publication bias.Results: This analysis involved 12 studies and included 12,395 subjects. The quality of the literature was acceptable. Among subjects who were not taking lipid-lowering drugs, total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C) in the osteopenia were not significantly increased/decreased. There were no significant differences in LDL-C in postmenopausal women in osteopenia. TG was unchanged in the OP group in subjects without taking lipid-lowering drugs. HDL-C was elevated in OP group but not in osteopenia group in all subjectsConclusions: HDL-C was elevated in patients with OP.

scholarly journals Epigenetic Age Acceleration of Stomach Adenocarcinoma Associated With Tumor Stemness Features, Immunoactivation, and Favorable Prognosis

2021 ◽  
Vol 12 ◽  
Author(s):  
Chunhong Hong ◽  
Shaohua Yang ◽  
Qiaojin Wang ◽  
Shiqiang Zhang ◽  
Wenhui Wu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Correlation Analysis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Chronological Age ◽  
Favorable Prognosis ◽  
Molecular Features ◽  
Epigenetic Age ◽  
Epigenetic Age Acceleration ◽  
Stomach Adenocarcinoma

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.

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 Determination of saliva epigenetic age in infancy, and its association with parental socio-economic characteristics and pregnancy outcomes

2020 ◽  
pp. 1-9
Author(s):  
Maja Popovic ◽  
Valentina Fiano ◽  
Elena Isaevska ◽  
Chiara Moccia ◽  
Morena Trevisan ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Linear Regression ◽  
Pregnancy Outcomes ◽  
Positive Association ◽  
Absolute Difference ◽  
Chronological Age ◽  
Linear Regression Models ◽  
Epigenetic Age ◽  
Epigenetic Age Acceleration ◽  
Dna Methylation Age

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.

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 Effects of Smoking Cessation on Epigenetic Aging

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 673-673
Author(s):  
Brian Chen ◽  
Weiye Wang ◽  
Nichole Rigby ◽  
Randal Olson ◽  
Steve Sabes
Keyword(s):  
Dna Methylation ◽  
Experimental Studies ◽  
Biological Aging ◽  
Multiple Time ◽  
Epigenetic Aging ◽  
Epigenetic Age ◽  
Epigenetic Age Acceleration ◽  
Aging Rates ◽  
Multiple Time Points ◽  
Over Time

Abstract “Epigenetic clocks” have become widely used to assess individual rates of biological aging. However, experimental data are limited in humans to identify potential confounding factors that may influence one’s rate of epigenetic aging and multiple health outcomes. We examined multiple epigenetic aging measures among regular smokers who quit smoking for two weeks. DNA methylation markers were assessed in both whole blood and saliva at multiple time points using a customized DNA methylation microarray. Generally, no changes in epigenetic aging rates were detected in the two week observation period with the exception of pronounced decreases over time in rate of Hannum’s clock and Extrinsic Epigenetic Age Acceleration in blood DNA. In saliva DNA, decreases over time were detected in the rates of the GrimAge and DNAmPhenoAge clocks, but we saw an increase in the rate of the Skin and Blood Clock. Additional experimental studies of other common exposures may be useful to better characterize factors that may affect the observed “rate” of epigenetic aging.

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 A pilot prospective study of sleep patterns and DNA methylation-characterized epigenetic aging in young adults

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Mary A. Carskadon ◽  
Kenneth R. Chappell ◽  
David H. Barker ◽  
Anne C. Hart ◽  
Kayla Dwyer ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Sleep Duration ◽  
Sleep Time ◽  
Chronological Age ◽  
Age Difference ◽  
Regularity Index ◽  
Epigenetic Aging ◽  
Epigenetic Age ◽  
Sleep Log ◽  
Healthy Sample

Abstract Objective Molecular markers in DNA methylation at a subset of CpG sites are affected by the environment and contribute to biological (epigenetic) age. We hypothesized that shorter sleep duration and possibly irregular sleep would be associated with accelerated epigenetic aging. We examined epigenetic vs. chronological age in 12 young women selected as shorter or longer sleepers studied prospectively across the first 9 weeks of college using a daily online sleep log. Genomic DNA was isolated from two blood samples spanning the interval, and DNA methylation levels were determined and used to measure epigenetic age. Results Epigenetic vs. chronological age differences averaged 2.07 at Time 1 and 1.21 at Time 2. Sleep duration was computed as average daily total sleep time and sleep regularity was indexed using the Sleep Regularity Index. Participants with longer and more regular sleep showed reduced age difference: mean = − 2.48 [95% CI − 6.11; 1.15]; those with shorter and more irregular sleep showed an increased age difference: 3.03 [0.02; 6.03]; and those with either shorter or more irregular sleep averaged no significant change: − 0.49 [− 3.55; 2.56]. These pilot data suggest that short and irregular sleep, even in a young healthy sample, may be associated with accelerated epigenetic aging.

scholarly journals Associations Between Blood Pressure and Accelerated DNA Methylation Aging

2022 ◽  
Author(s):  
Lili Xiao ◽  
Gaohui Zan ◽  
Chaoqun Liu ◽  
Xia Xu ◽  
Longman Li ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Dna Methylation ◽  
Systolic Blood Pressure ◽  
Pulse Pressure ◽  
Chronological Age ◽  
Cross Sectional ◽  
High Systolic Blood Pressure ◽  
Aging Rate ◽  
Epigenetic Age ◽  
Epigenetic Age Acceleration

Background Individuals of the same chronological age may exhibit diverse susceptibilities to death. However, few studies have investigated the associations between blood pressure and the accelerated aging. Methods and Results A cross‐sectional study was conducted in 288 adults aged ≥50 years. We assessed the DNA methylation‐based measures of biological age using CpG sites on the Illumina HumanMethylationEPIC BeadChip. Epigenetic age acceleration metrics were derived by regressing residuals (ΔAge) and ratios (aging rate) of DNA methylation age on chronological age. Dose‐response relationships between blood pressure and epigenetic age acceleration were quantified using multiple linear regression and restricted cubic regression models. We found that each 10–mm Hg increase in systolic blood pressure was associated with 0.608 (95% CI, 0.231–0.984) years increase in ΔAge and 0.007 (95% CI, 0.002–0.012) increase in aging rate; meanwhile, for pulse pressure, the increase was 1.12 (95% CI, 0.625–1.61) years for ΔAge and 0.013 (95% CI, 0.007–0.020) for aging rate. Subgroup analysis showed that the significant associations of systolic blood pressure and pulse pressure with epigenetic age acceleration appeared to be limited to women, although interactions between blood pressure and sex were not significant ( P values for interaction >0.05). The combination of women and hypertension was associated with a much higher increase in ΔAge (β [95% CI], 4.05 [1.07–7.02]) and aging rate (β [95% CI], 0.047 [0.008–0.087]), compared with male participants without hypertension. Conclusions Our findings suggested that high systolic blood pressure and pulse pressure were associated with the epigenetic age acceleration, providing important clues for relationships between blood pressure and epigenetic aging.

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