A new biomarker derived from the Framingham Heart Study measures the speed of biological decline, offering a more sensitive endpoint for anti-aging clinical trials.
A rate-based biomarker from the Framingham Heart Study may become the new gold standard for testing anti-aging therapies.
The quest to measure biological aging has long been dominated by single-time-point “clocks” that calculate a person’s biological age as a static number. But a growing body of evidence suggests that the speed at which we age, not just the current state, may be far more informative for testing interventions that target the aging process itself. A new biomarker derived from the multi-decade Framingham Heart Study, called the Pace of Aging, is gaining attention as a rate-based measure that can detect the effects of calorie restriction and other geroprotective strategies in relatively short clinical trials.
Why measure the pace of aging?
Traditional biomarkers of aging, such as telomere length or DNA methylation patterns, provide a snapshot of molecular wear and tear at a single moment. They have been widely used in observational studies and commercial tests, but their responsiveness to interventions has been inconsistent. For clinical trials aimed at slowing aging, researchers need an endpoint that changes meaningfully over months or a few years, not decades. The Pace of Aging approach fills that gap by measuring how quickly physiological decline accumulates across multiple organ systems over time.
The concept was introduced by investigators working with the Framingham Heart Study, one of the longest-running epidemiological studies in medical history. Instead of relying on one biological sample, the Pace of Aging uses repeated clinical measurements collected over years to estimate the rate of deterioration in cardiovascular, metabolic, pulmonary, and renal function. The result is a dynamic metric that reflects the cumulative effects of genetics, environment, and lifestyle on the body’s systems.
The Framingham approach to measuring pace
To develop the Pace of Aging biomarker, researchers analyzed data from thousands of Framingham participants who underwent standardized clinical examinations at multiple time points. The measurements include blood pressure, body mass index, cholesterol levels, blood glucose, pulmonary function, and kidney function tests. By applying statistical models that combine these serial measurements, the team generated a single trajectory for each individual, representing how many years of physiological aging occur per chronological year.
A Pace of Aging score of 1 indicates that a person’s biology ages at the same pace as chronological time. A score above 1 means accelerated aging, while a score below 1 indicates slower aging. In a 2024 analysis of approximately 5,000 participants, researchers linked a one-year faster Pace of Aging to significantly higher risks of cardiovascular disease and death, even after adjusting for traditional risk factors. This association provides strong evidence that the pace measure captures meaningful biological information beyond any single biomarker.
Validation in the CALERIE trial
The most compelling demonstration of the Pace of Aging’s utility came from the CALERIE trial, a randomized controlled study funded by the National Institute on Aging. CALERIE tested the effects of a 12% reduction in caloric intake on healthy, non-obese adults over two years. Using blood biomarkers collected at baseline and at 12 months, researchers calculated changes in the Pace of Aging score. The results showed that caloric restriction slowed the pace of aging by 2–3% per year, a modest but statistically significant effect.
This finding is notable because it shows that a rate-based biomarker can detect changes after only one year of an intervention. In contrast, most single-time-point clocks require longer follow-up or larger sample sizes to reveal intervention effects. The CALERIE results also predicted reduced morbidity and mortality in external cohorts, suggesting that a 2–3% slowing of the pace is clinically meaningful. For the first time, a biomarker has demonstrated both sensitivity to an intervention and correspondence with hard outcomes like disease and death.
Rate versus state: a paradigm shift for clinical trials
For decades, drug developers seeking to test anti-aging therapies have faced a fundamental problem: aging itself is not a recognized indication, and clinical trials typically rely on disease-specific endpoints. The FDA and other regulators have shown willingness to consider biomarkers of aging as surrogate endpoints, but only if they are robust and reproducible. The Pace of Aging offers a way forward by turning aging into a measurable process rather than a distant outcome.
Because the pace metric integrates multiple organ systems, it is less likely to be swayed by acute stress or transient fluctuations that affect epigenetic clocks. DNA methylation clocks, for example, can respond to short-term inflammation or medication, making them noisy in trial settings. The Pace of Aging, by contrast, reflects a longer-term trajectory, which may make it more reliable for assessing interventions that aim to slow the underlying biology of aging.
An additional advantage is the ability to use the Pace of Aging in adaptive trial designs. Researchers can monitor changes in the pace score after a few months and decide whether to continue, discontinue, or modify the intervention. This approach could reduce the cost and duration of phase 2 trials for geroprotectors, which have historically been hampered by the need for large cohorts and long follow-up periods.
Challenges to implementation
Despite its promise, the Pace of Aging is not without limitations. The method requires repeated clinical measurements over time, which is more complex and expensive than a simple blood draw. In real-world settings, missing data and inconsistent measurement protocols can undermine the accuracy of the trajectory. Researchers have called for harmonizing real-world data and repeated samplings to improve the reliability of rate-based biological age measures across cohorts.
Another challenge is the need for standardized algorithms and reference populations. The Framingham-derived model was built on a primarily Caucasian cohort, and it is unclear how well it translates to other ethnic and socioeconomic groups. Open-access algorithms and cross-cohort validation are essential before the Pace of Aging can be widely adopted in clinical practice or regulatory evaluations.
Commercial hype and unproven claims
Industry interest in the Pace of Aging has spiked after the commercial launch of direct-to-consumer tests that claim to measure biological pace. These products often use a single blood sample or a handful of measurements, which is fundamentally incompatible with the longitudinal design required to estimate a rate. Experts have cautioned that such tests are not clinically validated and may mislead consumers who are seeking actionable insights about their health.
The gap between rigorous research and consumer access is not unique to the Pace of Aging. Similar issues have arisen with telomere length tests and epigenetic clocks, which were marketed to consumers long before they were clinically proven. The Pace of Aging is a valuable tool for research, but its translation to consumer products must be guided by evidence and regulatory oversight, not hype.
Toward harmonization and clinical use
Moving forward, the success of the Pace of Aging will depend on collaboration among research groups to share algorithms and data. Several international consortia are already working on harmonizing biological age measures, and the Pace of Aging could become a model for how to integrate longitudinal data from electronic health records, clinical trials, and wearable devices. If these efforts succeed, rate-based biomarkers could become standard endpoints in longevity medicine and drug development.
There is also potential for combining the Pace of Aging with molecular biomarkers such as methylomic or proteomic signatures. While the pace measure captures metabolic and organ function, molecular clocks provide insight into cellular machinery. A composite index that integrates both rate and state could offer a more holistic picture of aging, and might be even more predictive than either alone.
The next few years will be critical. As more clinical trials adopt the Pace of Aging as an exploratory endpoint, we will learn whether it truly delivers on its promise. The ultimate test will be whether a drug that slows the pace also reduces the incidence of age-related diseases and extends healthspan. If that evidence emerges, the pace of aging could become one of the most important biomarkers in preventive medicine.
Yet the idea that aging can be measured as a speed is not entirely new. In the 1990s, researchers proposed using longitudinal decline in physical and cognitive function to estimate “frailty” trajectories. These earlier concepts laid the groundwork for the Framingham score, but they were hindered by data scarcity and analytical limitations. The current interest in rate-based biomarkers reflects a broader shift in the aging field away from discrete biological age estimates and toward dynamic, process-oriented measures.
The direct-to-consumer longevity testing market has also seen a pattern of boom-and-bust cycles. Telomere testing gained popularity in the 2000s, only to be abandoned after replication studies failed to support its predictive power. DNA methylation clocks took its place in the 2010s, and are now widely used by startups and wellness clinics. The Pace of Aging is entering a crowded field, but its longitudinal design may offer a competitive edge if it can overcome the logistical hurdles that have limited previous rate-based approaches.
As with any new biomarker, the key will be rigorous validation. The history of aging biomarkers teaches us that no measure is perfect, and those that promise a simple answer to a complex question are often overhyped. The Pace of Aging is a welcome addition to the toolkit, but it should be seen as a complement to, not a replacement for, existing methods. By combining the best of longitudinal and molecular approaches, researchers may finally have the tools to test and deliver the first truly effective anti-aging therapies.
