DOI: 10.6084/m9.figshare.26984118.v1
title: Generations of epigenetic clocks and their links to socioeconomic status in the Health and Retirement Study

description: <b>Aim:</b> This is a brief description of links between nine epigenetic clocks related to human aging and socioeconomic and behavioral characteristics as well as health outcomes. <b>Materials & methods:</b> We estimate frequently used and novel clocks from one data source, the Health and Retirement Study. <b>Results:</b> While all of these clocks are thought to reflect “aging,” they use different CpG sites and do not strongly relate to each other. First and fourth generation clocks are not as linked to socioeconomic status or health outcomes as second and third generation clocks. <b>Conclusion:</b> Epigenetic clocks reflect exciting new tools and their continued evolution is likely to improve our understanding of how exposures get under the skin to accelerate aging. Biological aging occurs much earlier than mortality and the onset of diseases associated with age that can be clinically diagnosed. In fact, changes in biology that accelerate aging can occur throughout life in response to adverse exposures, behaviors and experiences. One such change is methylation or the attachment of methyl groups to genetic markers to affect their activity. Epigenetic clocks are measures of the amount of methylation that is related to aging. They are called clocks because they are measured in years or ticks of time or in change in years relative to age. We show that not all epigenetic clocks are the same in how they relate to socioeconomic status and health behaviors as well as subsequent mortality and morbidity. There are now four generations of these clocks developed in a little more than 10 years. The second and third generation clocks are more closely associated with lifetime socioeconomic status, health behaviors and health outcomes probably because they have been developed by relating them to health indicators in contrast to epigenetic measures that were developed because of their relation to age. Incorporating epigenetic measures into population studies reflects the beginning of our ability to measure some aspects of aging long before old age; it also provides entry to monitoring, measuring and intervening on biological aging throughout life. First generation: Horvath and Hannum’s clocks trained on chronological age. Second generation: Levine’s PhenoAge and Lu & Horvath’s GrimAge and GrimAge2 trained on multiple biomarkers and smoking. Third generation: Belsky measures the pace of epigenetic aging rather than a static age in DunedinPACE. Fourth generation: Causal clocks use Mendelian randomization to select sites that are putatively causal in general aging, adaptation to aging and age-related damage. Second and third generation clocks correlate more strongly with education, income, race/ethnicity, mortality and multimorbidity. Lower socioeconomic status is linked to accelerated aging and higher mortality and morbidity. Lifestyle factors like smoking and obesity impact epigenetic aging. Clocks vary in their correlation with risk factors and health outcomes due to many factors including different CpG site inclusion, different populations used for training and different outcomes used for training.