Aging biomarkers

Aging biomarkers are measurable quantities intended to indicate how far or how fast a person is aging, independent of the calendar. The field wants them for a practical reason. Without one, a trial testing whether a drug slows aging must wait for participants to become ill or die, which takes decades and very large numbers of people; a validated biomarker would shorten that to a few years. None has been accepted for the purpose.

§Why the field needs one

The Geroscience hypothesis holds that slowing aging would delay many chronic diseases at once, and testing it requires an endpoint. Lifespan is unambiguous but unusable in humans. The incidence of a single disease brings back the disease-by-disease framing the hypothesis was built to escape. The TAME design adopts a compromise, a composite of several age-related diseases plus death, and it still needs thousands of participants followed over years.

A surrogate biomarker would change the economics. With a six-month readout, sponsors could run dose-ranging studies, compare candidate compounds and abandon failures early, as drug developers do in every field that has a surrogate. Its absence is a substantial part of the reason so few geroprotector candidates have entered serious human testing despite a large animal literature.

§What counts as a biomarker of aging

The criteria most often cited descend from work sponsored by the American Federation for Aging Research in the late 1980s and restated since.¹ A biomarker of aging should predict remaining lifespan or the onset of age-related dysfunction better than chronological age does. It should reflect an underlying process, ideally one of the Hallmarks of aging, rather than a specific disease. It should be measurable repeatedly without significant harm, and it should work in laboratory animals as well as in humans, so that it can be validated against lifespan in a species where lifespan is observable.

Modern framings split validation into three tiers. Analytical validity asks whether the measurement is reproducible across laboratories, platforms and repeat draws. Clinical validity asks whether it predicts outcomes in independent cohorts. Responsiveness asks whether the marker moves when an intervention is applied and, more demanding still, whether a change in the marker predicts a corresponding change in the outcome. Most candidates have some evidence for the first two tiers and almost none for the third.

§Candidate classes

Candidates are conventionally sorted by what they measure, a catalogue set out under Biological age. Sorting them instead by the validity tier at which each class is stuck is more useful, because the tier a class fails determines the experiment that would rescue it.

Molecular measures are cheap and hard to interpret. DNA methylation dominates, in the form of epigenetic clocks, with proteomic, metabolomic, glycomic and transcriptomic panels alongside. One blood draw yields tens of thousands of features, and a model can be fitted from them to almost any outcome. That flexibility is both the attraction and the difficulty. An index selected for prediction carries no evidence that moving it moves anything, and that evidence cannot come from the data the index was fitted on.

Cellular measures are the ones the field most wants and least has. Senescent-cell burden is the direct target of Senolytics, yet no accepted method exists for quantifying it in a living person, because there is no clean marker of Cellular senescence on which to build one. Assays therefore rely on surrogates for a surrogate. Clonal haematopoiesis, a readout of Stem cell exhaustion, is the exception: it is measurable by sequencing and predicts cardiovascular as well as blood outcomes, but it is confined to one tissue.

Immune and inflammatory measures track a real axis and move for the wrong reasons. Composite immune-aging scores, thymic output measures and circulating markers linked to Inflammaging all decline with age. They also shift within days after infection, injury or vaccination, which comes close to disqualifying them as a way to read a decades-long process from a single timepoint.

Functional measures are the only class with real responsiveness data. Gait speed, grip strength, chair-rise time and cardiorespiratory fitness predict mortality and disability well. They already serve as endpoints in frailty and sarcopenia trials, so their regulatory path is partly mapped. The awkwardness is commercial rather than scientific: these measures improve reliably with training, so a sponsor whose drug is judged on grip strength is competing against exercise.

§Coordination efforts

The Biomarkers of Aging Consortium, established in the early 2020s, brought together academic groups, companies and funders to standardise definitions, share data and set validation criteria. Its output includes a framework paper on what a biomarker would need before it could be used in longevity-intervention trials, followed by work on validation standards.² The consortium has contributed an agreed vocabulary and a shared benchmark, which the field previously lacked, more than any new measure.

Surrogates can mislead

Cardiology supplies the cautionary case. Antiarrhythmic drugs suppressed ventricular ectopic beats, a plausible surrogate for sudden cardiac death, and the Cardiac Arrhythmia Suppression Trial found that they increased mortality.³ A marker can be strongly associated with an outcome and still be the wrong thing to move.

§The regulatory bar

Regulators do not accept a surrogate because it correlates with outcomes. They require evidence that an intervention's effect on the surrogate accounts for its effect on the clinical outcome, a mediation claim that is much harder to establish. In the United States, formal qualification runs through a biomarker qualification programme, and no aging biomarker has been submitted successfully through it.

A second obstacle is categorical. The major regulators do not recognise aging as an indication, so even a perfect biomarker would measure progress against something a label cannot name. Proposals in the field are therefore usually framed around a specific age-related condition or around multimorbidity, and the ICD classification of aging-related decline has been argued over with unusual intensity for a coding question. A working group convened around Nir Barzilai's TAME trial published a shortlist of blood-based markers judged closest to usable in geroscience trials, chosen for availability and predictive validity rather than for mechanistic depth.⁴ The economic case for clearing this obstacle is set out under The longevity dividend.

§Validation problems

Validating a biomarker of aging against mortality is partly circular. Mortality is the outcome, and a marker that predicts it may be measuring current illness rather than aging. Telling the two apart requires long follow-up in healthy cohorts, which few datasets support.

Animal validation offers a partial way out. A marker that tracks lifespan across mouse strains and across interventions of known effect, including Caloric restriction and Rapamycin, has passed a test no human dataset can supply. Cross-species methylation clocks, which Horvath and collaborators extended across mammalian species, were built partly for this purpose. The translation gap remains, since a marker calibrated in mice may not carry the same meaning in a species that lives thirty times longer.

Reliability is the mundane problem that undermines many published intervention effects. Where a measure's test-retest variation is comparable to the effect being claimed, the claim cannot be evaluated. This has been documented for several widely used clocks and partly remedied by reconstructing them on principal components.⁵ The same difficulty afflicted leukocyte telomere length, the field's previous favourite marker, which proved too noisy at the individual level to be informative.

§Outlook

The field has two options. One is to keep improving molecular measures until one clears the mediation bar, which will require intervention trials large enough to show that the marker carries the treatment effect. The other is to set surrogates aside for now and measure function directly, the choice XPRIZE Healthspan made in defining its target as restored muscle, cognitive and immune performance. The second path is slower per trial but immune to the criticism that has attached to biological-age claims. The choice will help decide whether the first credible human geroprotector result comes from a biomarker readout or from a decade-long clinical endpoint.

§See also

• Biological age
• Epigenetic clocks
• Geroscience hypothesis
• Healthspan
• Hallmarks of aging
• XPRIZE Healthspan
• Compression of morbidity

§References