Abstract
Epigenetic clocks are among the most promising biomarkers of aging. It is particularly important to establish biomarkers of brain aging to better understand neurodegenerative diseases. To advance application of epigenetic clocks—which were largely created with DNA methylation levels in blood samples—for use in brain, we need clearer evaluation of epigenetic clock behavior in brain, including direct comparisons of brain specimens with blood, a more accessible tissue for research. We leveraged data from the Religious Orders Study and Rush Memory and Aging Project to examine three established epigenetic clocks (Horvath, Hannum, PhenoAge clocks) and a newer clock, trained in cortical tissue. We calculated each clock in three different specimens: (1) antemortem CD4+ cells derived from blood (n = 41); (2) postmortem dorsolateral prefrontal cortex (DLPFC, n = 730); and (3) postmortem posterior cingulate cortex (PCC, n = 186), among older women and men, age 66–108 years at death. Across all clocks, epigenetic age calculated from blood and brain specimens was generally lower than chronologic age, although differences were smallest for the Cortical clock when calculated in the brain specimens. Nonetheless, we found that Pearson correlations of epigenetic to chronologic ages in brain specimens were generally reasonable for all clocks; correlations for the Horvath, Hannum, and PhenoAge clocks largely ranged from 0.5 to 0.7 (all p < 0.0001). The Cortical clock outperformed the other clocks, reaching a correlation of 0.83 in the DLFPC (p < 0.0001) for epigenetic vs. chronologic age. Nonetheless, epigenetic age was quite modestly correlated across blood and DLPFC in 41 participants with paired samples [Pearson r from 0.21 (p = 0.2) to 0.32 (p = 0.05)], indicating that broader research in neurodegeneration may benefit from clocks using CpG sites better conserved across blood and brain. Finally, in analyses stratified by sex, by pathologic diagnosis of Alzheimer disease, and by clinical diagnosis of Alzheimer dementia, correlations of epigenetic to chronologic age remained consistently high across all groups. Future research in brain aging will benefit from epigenetic clocks constructed in brain specimens, including exploration of any advantages of focusing on CpG sites conserved across brain and other tissue types.
Highlights
Chronologic age is the strongest risk factor for many chronic diseases; disease risk is heterogeneous within age groups, likely due, in part, to variation in “biologic age.” Substantial research has explored biomarkers of aging (Jylhava et al, 2017), which are critical tools for predicting disease risk, assessing mechanisms underlying aging processes, and developing interventions to delay aging-associated declines in health
In additional analyses to explore whether there may be better correlations when considering the extent of epigenetic age acceleration across specimens than the extent of epigenetic aging, we found that results were generally similar for clock age acceleration as for clock age
There were suggestions of somewhat higher correlations of epigenetic to chronologic age in men than in women, and somewhat lower correlations in those with pathologic AD than without pathologic AD; for example, the correlation of Cortical age to chronologic age in DLFPC was 0.78 among men and 0.69 among women, and was 0.78 in those without pathologic AD compared to 0.68 in those with pathologic AD. In this investigation of characteristics of epigenetic clocks across blood and brain specimens in older adults, we confirmed previous reports (Armstrong et al, 2017; El Khoury et al, 2019; Shireby et al, 2020), that epigenetic age was generally lower than chronologic age, across specimen types
Summary
Chronologic age is the strongest risk factor for many chronic diseases; disease risk is heterogeneous within age groups, likely due, in part, to variation in “biologic age.” Substantial research has explored biomarkers of aging (Jylhava et al, 2017), which are critical tools for predicting disease risk, assessing mechanisms underlying aging processes, and developing interventions to delay aging-associated declines in health. Substantial research has explored biomarkers of aging (Jylhava et al, 2017), which are critical tools for predicting disease risk, assessing mechanisms underlying aging processes, and developing interventions to delay aging-associated declines in health. Epigenetic modifications are a hallmark of aging, and epigenetic clocks are among the most promising biomarkers of aging to date (Jylhava et al, 2017). The majority of research establishing the relevance of epigenetic clocks has largely focused on their relations with overall longevity (Fransquet et al, 2019). Establishing effective biomarkers of brain aging is important for improving public health in the coming decades, and eventually reducing neurodegenerative diseases of aging
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