A Comparison of Biological Age Measurement Approaches

Researchers here assess the performance of a range of approaches to measuring biological age, including a number of epigenetic clocks based on DNA methylation changes characteristic of aging. The ideal measurement of biological age is one that is quick and cheap to undertake, and that accurately reflects the underlying burden of damage and consequence that drives aging. Such a measure could be used to determine the effectiveness of potential rejuvenation therapies far more rapidly than is presently possible, and would thus accelerate development efforts. Unfortunately none of the existing approaches are quite ready for this, as it is far from clear as to whether they do actually measure the full range of damage and consequence in aging. Their effectiveness will have to be proven in conjunction with the development of each new class of rejuvenation therapies, starting with senolytics.

Everyone ages, but how aging affects health varies from person to person. This means that how old someone seems or feels does not always match the number of years they have been alive; in other words, someone's "biological age" can often differ from their "chronological age". Scientists are now looking at the physiological changes related to aging to better predict who is at the greatest risk of age-related health problems. Several measurements of biological age have been put forward to capture information about various age-related changes. For example, some measurements look at changes to DNA molecules, while others measure signs of frailty, or deterioration in cognitive or physical abilities. However, to date, most studies into measures of biological age have looked at them individually and less is known about how these physiological changes interact, which is likely to be important.

In a new study, researchers have looked at data on nine different measures of biological age in a group of 845 Swedish adults, aged between 50 and 90, that was collected several times over a follow-up period of about 20 years. The dataset also gave details of the individuals' birth year, sex, height, weight, smoking status, and education. The year of death was also collected from national registers for all individual in the group who had since died. The nine measures were telomere length, four different epigenetic clocks, physiological age derived from a list of age-correlated biomarkers, chronological age, functional aging index, and frailty index. Researchers found that all nine biological age measures could be used to explain the risk of individuals in the group dying during the follow-up period. In other words, when comparing individuals with the same chronological age in the group under study, the person with a higher biological age measure was more likely to die earlier. The analysis also revealed that biological aging appears to accelerate as individuals approach 70 years old, and that there are noticeable differences in the aging process between men and women.

Lastly, when combining all nine biological age measures, some of them worked better than others. Measurements of methylation groups added to DNA (known as DNA methylation age) and frailty (the frailty index) led to improved predictions for an individual's risk of death. Ultimately, if future studies confirm these results for measures from single individuals, DNA methylation and the frailty index may be used to help identify people who may benefit the most from interventions to prevent age-related health conditions.

Link: https://doi.org/10.7554/eLife.51507

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