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Blood plasma contains protein patterns that change with age, and researchers have used them to estimate chronological age, aging in particular organs, or health-related outcomes. But these are different research models—not one agreed-upon “healthy-aging signature.” The findings do not establish that a consumer blood test can tell an individual how well they are aging or how long they will stay healthy.
What is a blood protein signature?
A protein signature is a pattern across multiple measured proteins, considered together in a statistical model or comparison. A single protein may provide information about a particular aspect of health; a multi-protein pattern can capture a broader set of changes. In aging research, the phrase can refer to models with quite different goals, such as estimating a person’s chronological age or comparing the apparent ages of different organs.
Those goals matter. A model that estimates age from proteins does not, by itself, show whether someone is aging healthily, predict their healthy lifespan, diagnose disease, or identify a treatment. A signature can be associated with an outcome without causing it.
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Several studies have identified age-related protein patterns, but their populations, measurements, and outcomes differ. Their figures describe separate studies, not one pooled result or a single standardized test.
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A lifespan pattern associated with chronological age
A 2020 NIH summary of a 2019 study reports that researchers measured nearly 3,000 plasma proteins in more than 4,000 volunteers ages 18 to 95. A subset of 373 proteins predicted chronological age within a few years in the analyzed men and women. The study also found that protein changes were not simply linear across age: broad shifts appeared around ages 34, 60, and 78.
This is evidence that a collection of plasma proteins can carry information about age in the study population. Estimating chronological age is not the same as measuring healthy aging or forecasting an individual’s future health.
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Estimates of aging across 11 organs
A 2023 Nature study used plasma proteins to estimate age-related patterns across 11 major organs. It included 5,676 adults across five cohorts and reported associations between some accelerated organ-aging patterns and disease outcomes. An organ-age estimate is a research measure, not a direct clinical reading of how an organ is functioning; the reported associations do not establish that an apparent age difference causes disease.
A score developed around healthspan
A 2025 University of Connecticut release via EurekAlert! describes a Healthspan Proteomic Score developed using age and 86 proteins, drawing on data from more than 53,000 UK Biobank participants. Its stated purpose is to predict healthspan and disease risk. That makes it different from a model whose target is chronological age, but it remains a research score; the release does not establish it as a validated consumer test or individual diagnosis.
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Candidate proteins at the intersection of age and disease burden
A 2026 Aging Cell study measured 5,416 plasma proteins in 124 participants. The researchers identified 311 proteins that differed in both age-group comparisons and disease-burden comparisons. The study describes these as candidate biomarkers of biological aging and says further work is required. Its small, single-site sample makes it exploratory, not a basis for broad individual predictions.
| Study | Participants and protein data | What it examined |
|---|---|---|
| 2019 study, summarized by NIH in 2020 | More than 4,000 volunteers ages 18–95; nearly 3,000 plasma proteins measured; 373 used in an age-prediction subset | Chronological age and age-related protein changes |
| 2023 Nature study | 5,676 adults across five cohorts; 11 major organs assessed | Organ-specific age estimates and associations with health and disease |
| 2025 Healthspan Proteomic Score release | More than 53,000 UK Biobank participants; age and 86 proteins in the score | Healthspan and disease-risk prediction |
| 2026 Aging Cell study | 124 participants; 5,416 plasma proteins measured; 311 proteins shared across age-group and disease-burden comparisons | Candidate biomarkers at the intersection of age and disease burden |
Why these findings do not yet make a personal healthy-aging test
A research result can be promising without being ready to guide an individual’s care. To judge whether a protein signature is useful outside its original study, researchers need to establish that it works in other populations and settings, and that using its result improves decisions or outcomes. The studies described here address different questions and use different cohorts and methods, so their numbers cannot be treated as interchangeable panels or scores.
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- Why do I need the EldonCard: Your blood type is inherited from your parents and determined by the presence or absence of certain antigens and antibodies. The EldonCard is made of a special type of plastic upon which dried antibody formulations are placed. The EldonCard is a reliable, durable, and a flexible point-of-care blood typing system.
- How EldonCard Works: The type of antigen you have tells us what your blood type is. While there are more than 20 blood-type systems, A, B, O and Rh (Rhesus) factor are by far the most important types. The blood is drawn by using a single-use safety lancet, which prevents accidental piercing by anyone picking up the lancet after it has been used.
- EldonCard Accuracy: The EldonCard is extremely accurate. It has been tested against the standard blood typing procedure using directly agglutinating antibodies. Tests have been performed at several laboratories in different countries and the results are in-line with laboratory-based tests.
- Where and Who can use it: EldonCard is used by hospitals, blood banks, blood centres, where it can be used for general blood typing and for bed side testing. Given the flexibility, durability and accuracy of the EldonCard, it can be used outside hospitals and clinic environments. Often it is used within practitioner clinics, humanitarian settings, remote locations, battlefields, classrooms, private homes, and in many emergency, situations calling for a speedy and reliable test.
- Prediction target: Chronological age, organ-specific age, healthspan, and disease burden are distinct outcomes. A model’s accuracy for one does not establish accuracy for another.
- Population: Results from a study cohort may not generalize to people with different health backgrounds or demographics. The 2026 study’s 124-person, single-site sample is especially limited for broad individual conclusions.
- Clinical utility: An association or prediction is not proof that measuring the signature helps prevent or treat disease. The NIH notes that more research is needed to determine whether these signatures can identify people at greater risk of age-related disease.
- Causation: A protein pattern associated with aging or disease does not show that changing that pattern will improve health or lifespan.
What can a reader conclude today?
Researchers have shown that plasma proteins change with age and that multi-protein patterns can contain information about age and health-related outcomes. The evidence supports continued study of these signatures, not a claim that there is one definitive blood marker of healthy aging.
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The cited work does not establish a validated consumer blood test for the signatures described. A result from an age-prediction model would not tell someone on its own whether they are aging well, and the organ-age, healthspan, and disease-burden approaches should not be interpreted as interchangeable measures. These findings are research associations and predictions, not individual diagnoses or proven treatment targets.
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