Abstract
Background: The past decade has seen the development of epigenetic models of aging that accurately estimate chronological age and predict disease incidence and mortality. These estimates are modulated by lifestyle and environmental factors linked to carcinogenesis, but to date this has primarily been studied in blood. Methods: We examined epigenetic aging in normal colonic tissue (n = 96), adjacent mucosa (n = 245), and tumors (n = 208), using models trained on age (Horvath, Hannum, Zhang), mortality (PhenoAge, GrimAge), aging rate (DunedinPACE), cellular mitotic history (EpiTOC, epiTOC2, miAGe), and telomere length (DNAmTL). Results: The Horvath model was the most accurate estimator of chronological age in normal colonic mucosa, with high correlation (r > 0.70) between the Horvath, Hannum, Zhang, PhenoAge, and GrimAge models as well as between mitotic clocks (r > 0.94). All models showed similar performance in normal tissue and adjacent mucosa but substantially more variation in estimates in tumors. Statistically significant differences in age acceleration were present between normal and adjacent mucosa by 6 models (Hannum, Zhang, PhenoAge, EpiTOC, epiTOC2, and miAge), while tumors showed highly statistically significant differences by all models. Age acceleration differed by region of the colon, with varying patterns by model type. Physical activity (PhenoAge), smoking history (GrimAge), and alcohol consumption (Horvath, mitotic clocks) were associated with epigenetic aging in adjacent mucosa, while smoking history, smoking intensity, and alcohol consumption were associated with DNAmTL in tumors. Conclusions: Our study reveals an impact of tissue type, region, and lifestyle factors on epigenetic aging and highlights heterogeneity between models and the need for careful consideration within study design.
Funding Information
  • National Institutes of Health (U01 CA206110)
  • National Institutes of Health (R01 CA189184)
  • National Institutes of Health (R01 CA207371)
  • National Institutes of Health (R01 CA254108)
  • National Institutes of Health (CA272529)
  • National Institutes of Health (R01 AG083580)

This publication has 48 references indexed in Scilit: