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Age estimated by changes to DNA can help predict health outcomes, mortality in older adults

Age estimated by changes to DNA can help predict health outcomes mortality 
in older adults
Measuring epigenetic age acceleration can help predict later-life health outcomes and death.

Estimates of biological age, as measured by epigenetic changes such as DNA methylation (DNAm), can aid prediction of age-related health outcomes, including multiple chronic diseases, impaired cognitive function, functional limitations, and mortality in older adults. However, other factors, such as demographics, socioeconomic status, mental health, and health behaviors, are comparable — and often more robust — predictors of late-life health outcomes. These are findings of an NIA-funded study published in Proceedings of the National Academy of Sciences.

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Previous research established that socioeconomic and behavioral factors are strong predictors of health outcomes in older adults. In this study, a research team led by University of Michigan scientists wanted to learn whether DNAm-based biomarkers of aging, known as epigenetic clocks, were also able to predict health outcomes and mortality. Additionally, the investigators sought to determine whether epigenetic clocks contribute more information to these predictions of health outcomes, above and beyond less expensive survey measures of social and behavioral factors and traditional biomarkers.

Biological age refers to the accumulating damage, physiological changes, and loss of function that occur in a person’s cells over time. One method scientists use to measure biological age examines the epigenome, which contains a record of changes to a cell’s DNA and DNA-associated proteins. Epigenetic clocks are tools used by researchers to quantify biological age using a set of biological markers. They are based on the concept that certain epigenetic modifications, such as DNAm patterns, change predictably over time in cells. Epigenetic age acceleration occurs when an estimate of a person’s DNAm-predicted biological age is higher than their chronological age.

For this current research, the scientific team analyzed data from more than 3,500 participants in the Health and Retirement Study, a long-term, nationally representative study of Americans age 51 and older. The scientists examined the association between epigenetic age acceleration and age-related health outcomes, including death, by using three types of epigenetic clocks: first generation (Horvath and Hannum), second generation (GrimAge and PhenoAge), and third generation (the DunedinPACE clock). They calculated the participants’ age acceleration and examined cross-sectional associations with cognitive dysfunction and functional limitations, and the ability of age acceleration measures to predict development of multiple chronic conditions after two years, and death after four years. The second and third generation clocks, which were designed to improve on earlier clocks, were capable of predicting functional limitations of daily living and impaired cognitive function.

The team also compared these measures to well-established social and behavioral predictors of health and mortality, such as health behavior, demographics, mental health, and socioeconomic status, and to other blood-based biomarkers. The newer epigenetic age acceleration measures were consistently associated with key aging health outcomes, though findings differed somewhat across clock type. Social and behavioral factors remained stronger predictors of aging-related outcomes than epigenetic age acceleration measures, with one notable exception: multimorbidity, or having multiple chronic diseases. When combined with other biomarkers, epigenetic age still predicted mortality and multimorbidity, but could not predict functional difficulties or cognitive dysfunction.

The study findings suggest that along with traditional social and behavioral predictors of health, epigenetic age measures are a valuable tool for aging research and predicting health outcomes later in life. Further research may examine whether age acceleration predictions differ within different population groups.

This research was supported by NIA grants R01AG068937, R01AG060110, R01AG071071, and U01AG009740.

Reference: Faul JD, et al. Epigenetic-based age acceleration in a representative sample of older Americans: Associations with aging-related morbidity and mortality. Proceedings of the National Academy of Sciences of the United States of America. 2023;120(23):e2215840120. doi: 10.1073/pnas.2215840120.

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