ArticleClinical epigenetics2022
Epigenetic biomarkers of ageing are predictive of mortality risk in a longitudinal clinical cohort of individuals diagnosed with oropharyngeal cancer.
Article in Clinical epigenetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 24 citations in OpenAlex.
- Epigenetic age deceleration reflects exercise-induced cardiorespiratory fitness improvements.GeroScience · 2026Article
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- From the lab to lifestyle: epigenetic clocks in personalized aging and health.Biogerontology · 2026Review
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- Prognostic value of DNA methylation in head and neck cancer: a systematic review and meta-analysis.Translational cancer research · 2026Article
- Telomere Length, Epigenetic Age Acceleration, and Mortality Risk in US Adult Populations: An Additive Bayesian Network Analysis.Aging cell · 2025Article
- Article
- A Sex-Specific Minimal CpG-Based Model for Biological Aging UsingInternational journal of molecular sciences · 2025Article
- Housing insecurity pathways to physiological and epigenetic manifestations of health among aging adults: a conceptual model.Frontiers in public health · 2025Review
- The effect of phenotypic aging on the relationship between cancer history and mortality in US adults.Frontiers in aging · 2025Article
- Clinical promise and applications of epigenetic biomarkers.Clinical epigenetics · 2024Article
- The lipidomic correlates of epigenetic aging across the adult lifespan: A population-based study.Aging cell · 2023Article
- Metabolo-epigenetic interplay provides targeted nutritional interventions in chronic diseases and ageing.Frontiers in oncology · 2023Review
- Subjective Overview of Accelerated Aging in Schizophrenia.International journal of environmental research and public health · 2022Review
- Accelerated epigenetic aging in suicide attempters uninfluenced by high intent-to-die and choice of lethal methods.Translational psychiatry · 2022Article
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15 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundEpigenetic clocks are biomarkers of ageing derived from DNA methylation levels at a subset of CpG sites. The difference between age predicted by these clocks and chronological age, termed "epigenetic age acceleration", has been shown to predict age-related disease and mortality. We aimed to assess the prognostic value of epigenetic age acceleration and a DNA methylation-based mortality risk score with all-cause mortality in a prospective clinical cohort of individuals with head and neck cancer: Head and Neck 5000. We investigated two markers of intrinsic epigenetic age acceleration (IEAAHorvath and IEAAHannum), one marker of extrinsic epigenetic age acceleration (EEAA), one optimised to predict physiological dysregulation (AgeAccelPheno), one optimised to predict lifespan (AgeAccelGrim) and a DNA methylation-based predictor of mortality (ZhangScore). Cox regression models were first used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) for associations of epigenetic age acceleration with all-cause mortality in people with oropharyngeal cancer (n = 408; 105 deaths). The added prognostic value of epigenetic markers compared to a clinical model including age, sex, TNM stage and HPV status was then evaluated.
resultsIEAAHannum and AgeAccelGrim were associated with mortality risk after adjustment for clinical and lifestyle factors (HRs per standard deviation [SD] increase in age acceleration = 1.30 [95% CI 1.07, 1.57; p = 0.007] and 1.40 [95% CI 1.06, 1.83; p = 0.016], respectively). There was weak evidence that the addition of AgeAccelGrim to the clinical model improved 3-year mortality prediction (area under the receiver operating characteristic curve: 0.80 vs. 0.77; p value for difference = 0.069).
conclusionIn the setting of a large, clinical cohort of individuals with head and neck cancer, our study demonstrates the potential of epigenetic markers of ageing to enhance survival prediction in people with oropharyngeal cancer, beyond established prognostic factors. Our findings have potential uses in both clinical and non-clinical contexts: to aid treatment planning and improve patient stratification.
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