Young women with poor ovarian response exhibit epigenetic age acceleration based on evaluation of white blood cells using a DNA methylation-derived age prediction model

2020 ◽  
Vol 35 (11) ◽  
pp. 2579-2588 ◽  
Author(s):  
Brent M Hanson ◽  
Xin Tao ◽  
Yiping Zhan ◽  
Timothy G Jenkins ◽  
Scott J Morin ◽  
...  

Abstract STUDY QUESTION Is poor ovarian response associated with a change in predicted age based on a DNA methylation-derived age prediction model (the Horvath algorithm) in white blood cells (WBCs) or cumulus cells (CCs)? SUMMARY ANSWER In young women, poor ovarian response is associated with epigenetic age acceleration within WBC samples but is not associated with age-related changes in CC. WHAT IS KNOWN ALREADY The majority of human tissues follow predictable patterns of methylation which can be assessed throughout a person’s lifetime. DNA methylation patterns may serve as informative biomarkers of aging within various tissues. Horvath’s ‘epigenetic clock’, which is a DNA methylation-derived age prediction model, accurately predicts a subject’s true chronologic age when applied to WBC but not to CC. STUDY DESIGN, SIZE, DURATION A prospective cohort study was carried out involving 175 women undergoing ovarian stimulation between February 2017 and December 2018. Women were grouped according to a poor (≤5 oocytes retrieved) or good (>5 oocytes) response to ovarian stimulation. Those with polycystic ovary syndrome (PCOS) (n = 35) were placed in the good responder group. PARTICIPANTS/MATERIALS, SETTING, METHODS DNA methylation patterns from WBC and CC were assessed for infertile patients undergoing ovarian stimulation at a university-affiliated private practice. DNA was isolated from peripheral blood samples and CC. Bisulfite conversion was then performed and a DNA methylation array was utilized to measure DNA methylation levels throughout the genome. Likelihood ratio tests were utilized to assess the relationship between predicted age, chronologic age and ovarian response. MAIN RESULTS AND THE ROLE OF CHANCE The Horvath-predicted age for WBC samples was consistent with patients’ chronologic age. However, predicted age from analysis of CC was younger than chronologic age. In subgroup analysis of women less than 38 years of age, poor ovarian response was associated with an accelerated predicted age in WBC (P = 0.017). Poor ovarian response did not affect the Horvath-predicted age based on CC samples (P = 0.502). No alternative methylation-based calculation was identified to be predictive of age for CC. LIMITATIONS, REASONS FOR CAUTION To date, analyses of CC have failed to identify epigenetic changes that are predictive of the aging process within the ovary. Despite the poor predictive nature of both the Horvath model and the novel methylation-based age prediction model described here, it is possible that our efforts failed to identify appropriate sites which would result in a successful age-prediction model derived from the CC epigenome. Additionally, lower DNA input for CC samples compared to WBC samples was a methodological limitation. We acknowledge that a universally accepted definition of poor ovarian response is lacking. Furthermore, women with PCOS were included and therefore the group of good responders in the current study may not represent a population with entirely normal methylation profiles. WIDER IMPLICATIONS OF THE FINDINGS The process of ovarian and CC aging continues to be poorly understood. Women who demonstrate poor ovarian response to stimulation represent a common clinical challenge, so clarifying the exact biological changes that occur within the ovary over time is a worthwhile endeavor. The data from CC support a view that hormonally responsive tissues may possess distinct epigenetic aging patterns when compared with other tissue types. Future studies may be able to determine whether alternative DNA methylation sites can accurately predict chronologic age or ovarian response to stimulation from CC samples. Going forward, associations between epigenetic age acceleration and reproductive and general health consequences must also be clearly defined. STUDY FUNDING/COMPETING INTEREST(S) No external funding was obtained for the study and there are no conflicts of interest. TRIAL REGISTRATION NUMBER N/A.

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Günter Raddatz ◽  
Ryan J. Arsenault ◽  
Bridget Aylward ◽  
Rose Whelan ◽  
Florian Böhl ◽  
...  

AbstractThe domestic chicken (Gallus gallus domesticus) is the globally most important source of commercially produced meat. While genetic approaches have played an important role in the development of chicken stocks, little is known about chicken epigenetics. We have systematically analyzed the chicken DNA methylation machinery and DNA methylation landscape. While overall DNA methylation distribution was similar to mammals, sperm DNA appeared hypomethylated, which correlates with the absence of the DNMT3L cofactor in the chicken genome. Additional analysis revealed the presence of low-methylated regions, which are conserved gene regulatory elements that show tissue-specific methylation patterns. We also used whole-genome bisulfite sequencing to generate 56 single-base resolution methylomes from various tissues and developmental time points to establish an LMR-based DNA methylation clock for broiler chicken age prediction. This clock was used to demonstrate epigenetic age acceleration in animals with experimentally induced inflammation. Our study provides detailed insights into the chicken methylome and suggests a novel application of the DNA methylation clock as a marker for livestock health.


Biomedicines ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 13
Author(s):  
Raúl Pérez ◽  
Juan Fernandez-Morera ◽  
Judit Romano-Garcia ◽  
Edelmiro Menendez-Torre ◽  
Elias Delgado-Alvarez ◽  
...  

Type 1 diabetes (T1D) is an autoimmune disease that leads to insulin deficiency and hyperglycemia. Little is known about how this metabolic dysfunction, which substantially alters the internal environment, forces cells to adapt through epigenetic mechanisms. Consequently, the purpose of this work was to study what changes occur in the epigenome of T1D patients after the onset of disease and in the context of poor metabolic control. We performed a genome-wide analysis of DNA methylation patterns in blood samples from 18 T1D patients with varying levels of metabolic control. We identified T1D-associated DNA methylation differences on more than 100 genes when compared with healthy controls. Interestingly, only T1D patients displaying poor glycemic control showed epigenetic age acceleration compared to healthy controls. The epigenetic alterations identified in this work make a valuable contribution to improving our understanding of T1D and to ensuring the appropriate management of the disease in relation to maintaining healthy aging.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Tess D. Pottinger ◽  
Sadiya S. Khan ◽  
Yinan Zheng ◽  
Wei Zhang ◽  
Hilary A. Tindle ◽  
...  

Abstract Background Cardiovascular health (CVH) has been defined by the American Heart Association (AHA) as the presence of the “Life’s Simple 7” ideal lifestyle and clinical factors. CVH is known to predict longevity and freedom from cardiovascular disease, the leading cause of death for women in the United States. DNA methylation markers of aging have been aggregated into a composite epigenetic age score, which is associated with cardiovascular morbidity and mortality. However, it is unknown whether poor CVH is associated with acceleration of aging as measured by DNA methylation markers in epigenetic age. Methods and results We performed a cross-sectional analysis of racially/ethnically diverse post-menopausal women enrolled in the Women’s Health Initiative cohort recruited between 1993 and 1998. Epigenetic age acceleration (EAA) was calculated using DNA methylation data on a subset of participants and the published Horvath and Hannum methods for intrinsic and extrinsic EAA. CVH was calculated using the AHA measures of CVH contributing to a 7-point score. We examined the association between CVH score and EAA using linear regression modeling adjusting for self-reported race/ethnicity and education. Among the 2,170 participants analyzed, 50% were white and mean age was 64 (7 SD) years. Higher or more favorable CVH scores were associated with lower extrinsic EAA (~ 6 months younger age per 1 point higher CVH score, p < 0.0001), and lower intrinsic EAA (3 months younger age per 1 point higher CVH score, p < 0.028). Conclusions These cross-sectional observations suggest a possible mechanism by which ideal CVH is associated with greater longevity.


2021 ◽  
pp. 109980042098389
Author(s):  
Jongmin Park ◽  
Chang Won Won ◽  
Leorey N. Saligan ◽  
Youn-Jung Kim ◽  
Yoonju Kim ◽  
...  

Background: Epigenetic age acceleration has been studied as a promising biomarker of age-related conditions, including cognitive aging. This pilot study aims to explore potential cognitive aging-related biomarkers by investigating the relationship of epigenetic age acceleration and cognitive function and by examining the epigenetic age acceleration differences between successful cognitive aging (SCA) and normal cognitive aging (NCA) among Korean community-dwelling older adults (CDOAs). Methods: We used data and blood samples of Korean CDOAs from the Korean Frailty and Aging Cohort Study. The participants were classified into two groups, SCA (above the 50th percentile in all domains of cognitive function) and NCA. The genome-wide DNA methylation profiling array using Illumina Infinium MethylationEPIC BeadChip was used to calculate the following: the DNA methylation age, universal epigenetic age acceleration, intrinsic epigenetic age acceleration (IEAA), and extrinsic epigenetic age acceleration (EEAA). We also used Pearson correlation analysis and independent t-tests to analyze the data. Results: Universal age acceleration correlated with the Frontal Assessment Battery test results ( r = −0.42, p = 0.025); the EEAA correlated with the Word List Recognition test results ( r = −0.41, p = 0.027). There was a significant difference between SCA and NCA groups in IEAA ( p = 0.041, Cohen’s d = 0.82) and EEAA ( p = 0.042, Cohen’s d = 0.78). Conclusions: Epigenetic age acceleration can be used as a biomarker for early detection of cognitive decline in Korean community-dwelling older adults. Large longitudinal studies are warranted.


2021 ◽  
Vol 13 ◽  
Author(s):  
Pei-Lun Kuo ◽  
Ann Zenobia Moore ◽  
Frank R. Lin ◽  
Luigi Ferrucci

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.


2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Jennifer A. Smith ◽  
Jeremy Raisky ◽  
Scott M. Ratliff ◽  
Jiaxuan Liu ◽  
Sharon L. R. Kardia ◽  
...  

Abstract Background Epigenetic age acceleration, a measure of biological aging based on DNA methylation, is associated with cardiovascular mortality. However, little is known about its relationship with hypertensive target organ damage to the heart, kidneys, brain, and peripheral arteries. Methods We investigated associations between intrinsic (IEAA) or extrinsic (EEAA) epigenetic age acceleration, blood pressure, and six types of organ damage in a primarily hypertensive cohort of 1390 African Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. DNA methylation from peripheral blood leukocytes was collected at baseline (1996–2000), and measures of target organ damage were assessed in a follow-up visit (2000–2004). Linear regression with generalized estimating equations was used to test for associations between epigenetic age acceleration and target organ damage, as well as effect modification of epigenetic age by blood pressure or sex. Sequential Oligogenic Linkage Analysis Routines (SOLAR) was used to test for evidence of shared genetic and/or environmental effects between epigenetic age acceleration and organ damage pairs that were significantly associated. Results After adjustment for sex, chronological age, and time between methylation and organ damage measures, higher IEAA was associated with higher urine albumin to creatinine ratio (UACR, p = 0.004), relative wall thickness (RWT, p = 0.022), and left ventricular mass index (LVMI, p = 0.007), and with lower ankle-brachial index (ABI, p = 0.014). EEAA was associated with higher LVMI (p = 0.005). Target organ damage associations for all but IEAA with LVMI remained significant after further adjustment for blood pressure and antihypertensive use (p < 0.05). Further adjustment for diabetes attenuated the IEAA associations with UACR and RWT, and adjustment for smoking attenuated the IEAA association with ABI. No effect modification by age or sex was observed. Conclusions Measures of epigenetic age acceleration may help to better characterize the functional mechanisms underlying organ damage from cellular aging and/or hypertension. These measures may act as subclinical biomarkers for damage to the kidney, heart, and peripheral vasculature; however more research is needed to determine whether these relationships remain independent of lifestyle factors and comorbidities.


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