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Researchers here report on an assessment of epigenetic clocks (and PhenoAge). The study is one of a fair number of attempts to quantify just how effective these aging clocks are when it comes to predicting age-related disease and death. The interesting conclusion here is that epigenetic age acceleration, as determined using the present leading epigenetic clocks, isn’t yet a meaningful improvement over the established, traditional, very low-tech correlations with age-related disease and death, such as socioeconomic status. This suggests that we should expect some years of further evolution of aging clocks of various forms before they become truly useful. That evolution will certainly take place: clocks are not going away, are a popular area of research and development, and significant effort is being devoted to their improvement.
Biomarkers developed from DNA methylation (DNAm) data are of growing interest as predictors of health outcomes and mortality in older populations. However, it is unknown how epigenetic aging fits within the context of known socioeconomic and behavioral associations with aging-related health outcomes in a large, population-based, and diverse sample. This study uses data from 3,581 Health and Retirement Study (HRS) participants to examine the relationship between DNAm-based age acceleration measures in the prediction of cross-sectional and longitudinal health outcomes and mortality.
We examine whether recent improvements to these scores, using principal component (PC)-based measures designed to remove some of the technical noise and unreliability in measurement, improve the predictive capability of these measures. We also examine how well DNAm-based measures perform against well-known predictors of health outcomes such as demographics, socioeconomic status (SES), and health behaviors.
In our sample, age acceleration calculated using “second and third generation clocks,” PhenoAge, GrimAge, and DunedinPACE, is consistently a significant predictor of health outcomes including cross-sectional cognitive dysfunction, functional limitations and chronic conditions assessed 2 years after DNAm measurement, and 4-year mortality. PC-based epigenetic age acceleration measures do not significantly change the relationship of DNAm-based age acceleration measures to health outcomes or mortality compared to earlier versions of these measures. While the usefulness of DNAm-based age acceleration as a predictor of later life health outcomes is quite clear, other factors such as demographics, SES, mental health, and health behaviors remain equally, if not more robust, predictors of later life outcomes.
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