Researchers here report that more recently developed second generation epigenetic clocks do in fact demonstrate correlations between accelerated epigenetic age and risk of Alzheimer’s disease. Clocks are developed from databases of the status of DNA methylation sites on the genome in people of various ages. Some of these sites tend to become more or less methylated with advancing age, allowing machine learning approaches to derive algorithms that match a pattern of methylation to a chronological age. An accelerated epigenetic age implies that an individual’s epigenetics look more like those of someone with an older chronological age. The implication is that such an individual suffers a greater burden of age-related damage and dysfunction, and will thus have a higher risk of disease and mortality going forward.
Transgenic mouse models of Alzheimer’s disease (AD) demonstrate unique epigenetic alterations associated with AD pathology and studies of human brain tissue show marked DNA methylation differences in AD when compared to normal aging brain. By contrast, data from clinical studies has been mixed. For example, a recent systematic review largely using cross-sectional studies found no strong evidence that epigenetic age estimates were associated with risk for dementia or mild cognitive impairment (MCI), while other smaller studies have suggested a limited though promising relationship with risk for AD or related disease biomarkers.
There are multiple possible explanations for these surprisingly discrepant findings as insights from mouse models and postmortem human tissue are translated into clinical settings, and, taken together, these findings suggest the need for additional studies using more sensitive longitudinal and biomarker data paired with well-established and validated epigenetic clocks. Therefore, we investigated the relationship between two well-validated second-generation epigenetic clocks, DNAmPhenoAge and DNAmGrimAge, and risk for MCI or AD using longitudinal analyses and multimodal neuroimaging. Specifically, we analyzed the rate of progression from cognitively normal (CN) aging to either MCI or AD, cortical thinning and white matter hyperintensities (WMH) on magnetic resonance imaging (MRI), and longitudinal cognitive changes.
Using survival analyses, we found that DNAmPhenoAge and DNAmGrimAge predicted progression from cognitively normal aging to mild cognitive impairment or AD and worse longitudinal cognitive outcomes. Epigenetic age was also strongly associated with cortical thinning in AD-relevant regions and white matter disease burden. Thus, in contrast to earlier work suggesting limited applicability of blood-based epigenetic clocks in AD, our novel analytic framework suggests that second-generation epigenetic clocks have broad utility and may represent promising predictors of AD risk and pathophysiology.
