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253 results for “Epigenetic Aging”
Epigenetic aging of Māui and Hector's dolphins
<p>The age of an individual is an essential demographic parameter but is difficult to estimate without long-term monitoring or invasive sampling. Epigenetic approaches are increasingly used to age organisms, including non-model organisms such as cetaceans. Māui dolphins (<em>Cephalorhynchus hectori maui</em>) are a critically endangered subspecies endemic to Aotearoa New Zealand, and the age structure of this population is important for informing conservation. Here we present an epigenetic clock for aging Māui and Hector's dolphins (<em>C. h. hectori</em>) developed from methylation data using DNA from tooth aged individuals (<em>n </em>= 48). Based on this training dataset, the optimal model required only eight methylation sites, provided an age correlation of 0.95, and had a median absolute age error of 1.54 years. A leave-one-out cross-validation analysis with the same parameters resulted in an age correlation of 0.87 and median absolute age error of 2.09 years. To improve age estimate, we included previously published beluga whale (<em>Delphinapterus leucas</em>) data to develop a joint beluga/dolphin clock, resulting in a clock with comparable performance and improved estimation of older individuals. Application of the models to DNA from skin biopsy samples of living Māui dolphins revealed a shift in the median age of 8–9 years to a younger population aged 7–8 years 10 years later. These models could be applied to other dolphin species and demonstrate the ability to construct a clock even when the number of known age samples is limited, removing this impediment to estimating demographic parameters vital to the conservation of critically endangered species.</p>
A Data-Driven Epigenetic Characterization of Morning Fatigue Severity in Oncology Patients Receiving Chemotherapy: Associations with Epigenetic Age Acceleration, Blood Cell Types, and Expression-Associated Methylation
<p>This dataset contains supplementary materials including the eCpG mapping analysis results and annotation. The manuscript has been accepted for publication at Cancer Medicine. Please cite both the paper as well as the DOI of this dataset if you make use of the data.</p>
DNA methylation-based age prediction and sex-specific epigenetic aging in a lizard with female-biased longevity
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Epigenetic aging of Māui and Hector's dolphins
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Independent avian epigenetic clocks for aging and development
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Epigenetic aging signatures in mice livers are slowed by dwarfism, calorie restriction and rapamycin treatment
<p>Processed dataset and source data for iPython notebooks hosted by: https://doi.org/10.5281/zenodo.291961</p>
Epigenetic models developed for plains zebras predict age in domestic horses and endangered equids
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Data for: Epigenetic Age and Long-Term Cancer Risk Following a Stroke
<p><strong>Data for Manuscript: "Epigenetic Age and Long-Term Cancer Risk Following a Stroke"</strong></p> <p>In this study, we investigated whether stroke patients who later developed cancer exhibited an accelerated epigenetic age compared to those who did not. A total of 648 stroke patients were followed for 15 years, during which 83 individuals were diagnosed with cancer. Biological age (B-age) was estimated from DNA methylation data derived from whole blood samples collected within 24 hours of stroke onset. These samples were analyzed using the 450K or EPIC Illumina Beadchip arrays. We employed several epigenetic clocks to calculate B-age, including the Hannum, Horvath, PhenoAge, ZhangBLUP, ZhangEN, and the mitotic epiTOC clocks.</p> <p>After adjusting for multiple testing, competing risks, and key confounders, we found that patients who developed cancer were biologically older, as measured by the Hannum clock.</p> <p>This repository provides the associated phenotypic data, estimated white cell counts and B-age estimations, including both raw data and age acceleration values.</p>
Ketamine and Epigenetic Aging
ClinicalTrials.gov study NCT05294835. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Effects of Tildrakizumab on Epigenetic Age
ClinicalTrials.gov study NCT05110313. IPD Sharing: NO. Countries: 1. Publications: 19.
The Effects Of Therapeutic Plasma Exchange (TPE) On Age Related Biomarkers And Epigenetics
ClinicalTrials.gov study NCT06534450. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Epigenetics in the Aging Process
ClinicalTrials.gov study NCT00242255. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Safety and Effectivness of Quercetin & Dasatinib on Epigenetic Aging
ClinicalTrials.gov study NCT04946383. IPD Sharing: NO. Countries: 1. Publications: 3.
The Impact of a Polyphenol-Rich Supplement on Epigenetic and Cellular Markers of Immune Age
ClinicalTrials.gov study NCT05234203. IPD Sharing: UNDECIDED. Countries: 1. Publications: 15.
The Impact of a Fast Diet and Calorie Mimetic Supplements on Epigenetic Aging
ClinicalTrials.gov study NCT04962464. IPD Sharing: NO. Countries: 1. Publications: 3.
TirolGESUND: Baseline-controlled Comparison of the Effects of Fasting Dietary Intervention or Smoking Cessation Combined With Exercise in Healthy Female Tyrolean Volunteers Aged 30-60 on Epigenetic an
ClinicalTrials.gov study NCT05678426. IPD Sharing: YES. Countries: 1. Publications: 8.
Data from: Epigenetic estimation of age in humpback whales
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High social status males experience accelerated epigenetic aging in wild baboons
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Data from: Accelerated epigenetic age and cognitive decline among urban-dwelling adults
Objectives. Epigenetic modifications are closely linked with aging, but their relationship with cognition remains equivocal. Given known sex differences in epigenetic aging, we explored sex-specific associations of three DNA methylation-based (DNAm) measures of epigenetic age acceleration (EAA) with baseline and longitudinal change in cognitive performance among middle-aged urban adults. Methods. We used exploratory data from a sub-group of participants in the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study with complete DNA samples and whose baseline ages were >50.0y (2004-2009) to estimate three DNAm EAA measures: (A) universal epigenetic age acceleration (AgeAccel); (B) intrinsic epigenetic age acceleration (IEAA) ; and (C) extrinsic epigenetic age acceleration (EEAA). Cognitive performance was measured at baseline visit (2004-2009) and first follow-up (2009-2013) with 11 test scores covering global mental status and specific domains such as learning/memory, attention, visuo-spatial, psychomotor speed, language/verbal and executive function executive. A series of mixed-effects regression models were conducted adjusting for covariates and multiple testing (N=147-156, ~51% men, k=1.7-1.9 observations/participant, mean follow-up time~4.7y). Results. EEAA, a measure of both biological age and immunosenescence, was consistently associated with greater cognitive decline among men on tests of visual memory/visuo-constructive ability (Benton Visual Retention Test: γ11=0.0512±0.0176, p=0.004) and attention/processing speed (Trail making test, part A: γ11=0.219±0.080, p=0.007). AgeAccel and IEAA were not associated with cognitive change in this sample. Conclusions. EEAA capturing immune system cell aging was associated with faster decline among men in domains of attention and visual memory. Larger longitudinal studies are needed to replicate our findings.
Data from: Accelerated epigenetic age and cognitive decline among urban-dwelling adults
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OpenNeuro
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