Researchers are looking to aging clocks as a potential way to measure whether interventions designed to slow or reverse biological aging are actually working.

Scientists are increasingly using “aging clocks”, machine-learning tools that estimate a person’s biological age from measurable changes in the body, to investigate how quickly people are aging and whether that process can be altered.

Unlike chronological age, which simply counts the years since birth, biological age reflects changes that may be associated with the aging process. Aging clocks can be developed from many types of biological information, including genetic and epigenetic data, blood-test results, medical imaging and other health measurements.

In general, people whose estimated biological age is substantially higher than their chronological age tend to have a greater risk of age-related disease and mortality. This has made aging clocks an attractive research tool, but an important question remains: Can they reliably tell researchers whether a longevity treatment is actually slowing aging?

The promise and problem of aging clocks

A reliable aging clock could dramatically speed up longevity research. Instead of waiting years or decades to determine whether a treatment extends healthy lifespan, researchers could potentially use changes in a biological-age measurement as an early indication of whether an intervention is having an effect.

That could help scientists identify promising treatments sooner, improve existing therapies and direct resources toward the approaches most likely to benefit human health.

However, there is a major limitation.

Researchers still do not have a clear, direct map connecting the biological measurements used by aging clocks with the underlying mechanisms that drive aging. As a result, a clock that performs well in predicting age or health outcomes in a population may not necessarily respond accurately to a particular longevity intervention.

A treatment could, for example, change some of the biological signals used by a clock without actually slowing the fundamental processes of aging. Conversely, an intervention might improve important aspects of health without producing a large change in a particular aging clock.

This means researchers cannot simply assume that a change in an aging-clock score represents a corresponding change in biological aging.

Learning from existing clinical trials

To address this problem, researchers are compiling evidence from a growing number of animal studies and human clinical trials. By comparing how different aging clocks respond to different interventions, scientists hope to identify which measurements and approaches are most reliable.

A recent open-access analysis, titled “Responsiveness of epigenetic aging biomarkers to longevity interventions in humans,” contributes to this effort by examining available human clinical-trial data involving interventions that could potentially influence healthy aging and longevity.

The interventions studied so far are generally not dramatic rejuvenation therapies. Instead, they include approaches such as exercise, dietary interventions, including calorie restriction, metformin and therapeutic plasma exchange, among others.

Although these interventions may produce relatively modest effects on aging-related outcomes, their clinical-trial data provide an important testing ground for aging clocks.

A tool that could reshape longevity research

The long-term goal is to determine whether aging clocks can become dependable biomarkers for evaluating interventions aimed at extending healthy lifespan.

If researchers can establish that certain clocks consistently respond to effective interventions, and distinguish meaningful biological changes from superficial ones, they could become an important tool in the development of future longevity therapies.

For now, however, aging clocks should be viewed as promising research instruments rather than definitive measures of whether someone is biologically younger or whether a treatment has successfully slowed aging.

The growing collection of clinical-trial data may help researchers determine which clocks can ultimately be trusted, and bring the field closer to having a practical way to measure the effectiveness of interventions designed to improve human health in later life.