Best biological age tests in 2026: Blood, epigenetic, and wearable options

A 45-year-old with a biological age of 52 has roughly the mortality risk of a 52-year-old — not a 45-year-old. That single finding, replicated across dozens of cohorts, is why biological age has quietly become the most discussed metric in longevity medicine. It predicts all-cause mortality, cardiovascular events, and cognitive decline better than the number on your driver’s license.

But the moment you try to actually buy a biological age test, the market turns into a maze. A $99 saliva kit promises an “epigenetic age.” A $400 blood panel computes PhenoAge. A $12-per-month app estimates your age from VO2 max and HRV. Three tests, same person, three different numbers — sometimes three different decades. Which one is worth your money?

This guide compares the three mainstream categories — blood-based clocks, epigenetic clocks, and wearable-derived scores — on cost, accuracy, repeatability, and actionability, so you can pick the test that fits your specific longevity goal in 2026.

If your decision is specifically between the first two categories, use the focused epigenetic clock vs blood biomarker age decision framework to match the method to your goal without turning the comparison into a product ranking.

What you’ll learn:

• The three categories of biological age tests and what each actually measures
• Head-to-head comparison on cost, turnaround, and repeatability
• How to choose the right test for your specific goal
• What to do with the result once you have it

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Quick answer

Short version: For a cheap, repeatable benchmark, a blood-based PhenoAge or KDM score (derived from a standard lab panel) is the best starting point — low cost, annual repeatability, directly modifiable. For a one-off deep dive into mortality risk, a second-generation epigenetic clock (GrimAge, DunedinPACE) is the gold standard but expensive and noisier than marketing suggests. For daily trend tracking, a wearable-derived score (VO2-max-based fitness age, HRV composites) is the cheapest but measures fitness age, not cellular age. Most people get the best value by combining an annual blood panel with continuous wearable signals, reserving epigenetic testing for occasional calibration.

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Why biological age testing matters

Chronological age is a calendar. Biological age is a prediction. In a landmark 2018 analysis, Levine and colleagues showed that each 5-year increase in PhenoAge above chronological age roughly doubles near-term mortality risk. Similar effect sizes have been replicated for epigenetic clocks like GrimAge and third-generation pace-of-aging measures such as DunedinPACE.

For anyone over 40, the practical implication is simple: two people with the same birthday can have biological ages separated by 15 to 20 years — and the faster ager is far more likely to develop cardiovascular disease, cancer, or dementia in the next decade. Testing converts that invisible gap into a number you can act on.

The deeper question — how is that number actually calculated under the hood — is covered in our primer on how biological age is calculated. Here we focus on comparing products.

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The three categories of biological age tests

Blood-based clocks: PhenoAge, KDM, Levine’s equation

Blood-based clocks compute biological age from 9 to 12 routine blood biomarkers — albumin, creatinine, glucose, hs-CRP, lymphocyte percentage, MCV, RDW, alkaline phosphatase, and WBC — plus chronological age. PhenoAge (Levine, 2018) and the Klemera-Doubal Method (KDM) are the two dominant algorithms. Both are open-source, peer-reviewed, and require no proprietary lab — any standard CBC plus metabolic panel contains the inputs.

• Typical cost: $0 to $80 if you already get annual bloodwork; $150–$300 for a dedicated longevity panel.
• Turnaround: 1–3 days.
• What it captures: systemic inflammation, kidney and liver function, metabolic health, immune status.
• Strengths: cheap, fast, directly actionable (every input is a treatable clinical marker), easy to repeat quarterly.
• Weaknesses: biomarkers fluctuate with acute illness, hydration, recent meals; a bad night’s sleep before the draw can swing the score.

For the full methodology breakdown, see our deep dive on PhenoAge and KDM blood-based biological age. If you already have conflicting outputs, the focused PhenoAge vs KDM calculator comparison explains why the same person can receive different ages. If you want to know which blood markers matter beyond PhenoAge itself, our optimal longevity blood panel guide covers the broader workup.

Epigenetic clocks: Horvath, Hannum, GrimAge, DunedinPACE

Epigenetic clocks read DNA methylation — chemical tags at specific CpG sites in your genome — from a blood or saliva sample. Different clocks answer different questions:

• Horvath (2013) and Hannum (2013) — first-generation clocks, trained to predict chronological age. Useful for research, limited for health prediction.

• PhenoAge (methylation version) and GrimAge (Lu, 2019) — second-generation, trained on mortality. GrimAge is the single strongest methylation predictor of time-to-death.

• DunedinPACE (Belsky, 2022) — third generation. Rather than returning an age, it returns a rate — how many biological years you age per chronological year (1.0 = normal, 1.2 = 20% faster).

• Typical cost: $230–$500 for consumer kits, $600+ for research-grade assays.

• Turnaround: 3–6 weeks.

• Strengths: deeper biology than blood markers, mortality prediction is gold standard, DunedinPACE captures current trajectory.

• Weaknesses: high cost, slow turnaround, test-retest noise often 2–3 years on the same sample split, limited direct actionability (you can’t “lower your CpG methylation” the way you can lower CRP).

For clock-by-clock detail, see our epigenetic clocks explainer and the dedicated guide on pace of aging measurement.

Wearable-derived scores: VO2 max fitness age, HRV composites

A third category has emerged from the wearable ecosystem: biological age estimated from sensor data. The oldest example is fitness age from the Norwegian University of Science and Technology (NTNU), which maps estimated VO2 max to an age curve. Newer composites add heart rate variability (HRV), resting heart rate, sleep efficiency, and daily activity to produce a “health age” or “body age.”

• Typical cost: $0 to $15/month if you already own an Apple Watch, Garmin, Oura, or Whoop.
• Turnaround: instant, updated daily.
• Strengths: free feedback loop, high frequency (you see the impact of sleep, training, illness within days), no blood draw.
• Weaknesses: measures physiological fitness, not cellular aging. A sedentary 50-year-old who starts running will see a fitness age drop of 5–10 years in months — but that does not mean their CpG methylation moved. Different brands use proprietary, non-peer-reviewed algorithms.

For a framework on integrating wearable and lab signals in one view, see our personal health dashboard guide.

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Head-to-head comparison

Category	Typical cost	Turnaround	Inputs	What it measures	Actionability	Repeatability	Best for
Blood-based (PhenoAge, KDM)	$0–$300	1–3 days	9–12 routine biomarkers	Systemic health, inflammation, metabolic function	High — every input is modifiable	Good (quarterly)	Tracking interventions, annual benchmarking
First-gen epigenetic (Horvath, Hannum)	$230–$400	3–6 weeks	DNA methylation at CpG sites	Chronological age proxy	Low	Moderate	Research, curiosity
Second-gen epigenetic (GrimAge, PhenoAge DNAm)	$300–$500	3–6 weeks	DNA methylation	Mortality risk	Moderate	Moderate (annual)	Long-horizon risk assessment
Third-gen epigenetic (DunedinPACE)	$300–$500	3–6 weeks	DNA methylation	Current pace of aging	Moderate	Moderate (annual)	Tracking whether you’re aging faster or slower now
Wearable-derived (fitness age, health age)	$0–$15/month	Instant	VO2 max, HRV, sleep, activity	Physiological fitness age	High (directly tied to training, sleep)	Excellent (daily)	Trend tracking, intervention feedback

One unit note for U.S. readers: typical blood biomarker reference ranges are reported in American units first (e.g., hs-CRP < 1.0 mg/dL, glucose 70–100 mg/dL ≈ 3.9–5.6 mmol/L), with metric equivalents used outside the U.S.

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Accuracy, repeatability, and limitations

Test-retest noise

The most important — and least marketed — property of any biological age test is test-retest reliability: if you split one sample in two and run it twice, how close are the answers? For first-generation epigenetic clocks, the intraclass correlation is often 0.7–0.9 on split samples, which translates to a standard error of 2–3 years. DunedinPACE, being a rate, is more stable but still shows meaningful noise. Blood-based PhenoAge has similar order-of-magnitude noise, with one caveat — the noise source is biological (daily biomarker fluctuation) rather than technical.

Practical implication: a 2-year change between two tests six months apart may be noise, not signal. Look for consistent direction over 2–3 repeat measurements before declaring an intervention worked.

Pre-analytical variance

How the sample is collected matters enormously for blood-based clocks:

• Fasting vs fed state swings glucose and triglycerides.
• Recent intense exercise inflates hs-CRP and WBC for 24–48 hours.
• Dehydration alters albumin and creatinine.
• Acute infection (even a mild cold) can add 3–5 “biological years” to PhenoAge for weeks.

Standardize: draw fasted, morning, no intense exercise for 48 hours, not during illness.

Interpretation caveats

• “Epigenetic age” is not one number. Ask which clock the lab uses — a Horvath-age of 40 and a GrimAge of 40 mean very different things.
• Wearable-derived “age” is fitness age, not cellular age. Do not conflate the two.
• Beware brand rankings. No peer-reviewed head-to-head has established a single “best” consumer kit. Claims that one brand is “the most accurate” usually rest on internal validation.

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When to choose which test

Different goals call for different categories:

• One-off benchmark (“how am I doing right now?”) → Start with a blood-based PhenoAge or KDM score from your next annual panel. Lowest cost, fastest turnaround, directly actionable.
• Tracking interventions (diet change, new supplement, exercise program) → Blood-based clocks quarterly, plus a wearable-derived fitness age for daily feedback. Reserve epigenetic tests for once-a-year calibration — they are too slow and expensive to iterate against.
• Pace-of-aging focus (“am I aging faster than I should be right now?”) → A single DunedinPACE assay is the most direct answer. Pair with a blood panel to understand why.
• Metabolic focus (insulin resistance, fatty liver, pre-diabetes) → Blood-based PhenoAge plus a fasting insulin and lipid workup. Epigenetic tests will move slowly in response to metabolic changes; blood markers respond in weeks.
• Pre-retirement baseline (age 55–65, planning the next 20 years) → One high-quality second-generation epigenetic test (GrimAge-class) as a once-in-a-decade mortality benchmark, plus annual blood-based PhenoAge for ongoing tracking.

If you want a gentler on-ramp before spending on any lab, our guide to at-home biological age self-tests walks through simple functional measures (grip strength, sit-and-rise, stair climb) that cost nothing and correlate meaningfully with lab-based scores.

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How to act on your results

A biological age number is only useful if it changes your behavior. Here is a realistic action stack, ordered by effect size per effort:

1. Fix the worst single biomarker first. If PhenoAge says your hs-CRP and fasting glucose are the outliers, target those before anything else. Inflammation and glycemia drive a disproportionate share of the score.
2. Lock in the non-negotiables. Seven hours of sleep, 150 minutes/week of moderate aerobic activity plus two resistance sessions, no tobacco, moderate alcohol. These alone move PhenoAge by 2–4 years in intervention studies.
3. Use wearable trends as your short-loop feedback. A rising resting heart rate or falling HRV over 4 weeks usually predicts a worsening blood panel 3–6 months later. Catch the drift early.
4. Retest on a realistic cadence. Blood-based PhenoAge: every 3–6 months. Epigenetic clocks: every 12–24 months. Wearable scores: daily trends, monthly summaries.
5. Do not chase the number in isolation. A biological age that drops 3 years while your lipid profile worsens is a warning sign, not a win. Read the inputs, not just the composite.

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How SuperAge combines blood markers and wearable signals

SuperAge is built around the insight that the two most actionable categories — blood-based clocks and wearable-derived signals — work best together. It computes biological age using the peer-reviewed PhenoAge and KDM methodologies from blood values you enter from any standard lab panel (no proprietary kit required), then reads HealthKit to continuously overlay your VO2 max, HRV, resting heart rate, and sleep metrics.

The practical result:

• Zero repeat lab costs. Re-enter values from your normal annual or biannual workup — no subscription to a specific testing brand.
• Daily context. Wearable signals update between lab draws, so you see whether a dropping HRV trend is warning you before your next blood panel.
• Trend, not point. The app plots biological age over time so you can see whether interventions are actually working — the single biggest weakness of one-shot tests.

SuperAge is available on the App Store.

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Frequently asked questions

Are at-home epigenetic tests accurate?

They are analytically accurate — the methylation chemistry is mature — but test-retest noise on consumer kits is typically 2–4 years. Treat a single result as a ballpark, not a precise reading. Look for consistent direction across 2–3 retests before drawing conclusions.

How often should you retest biological age?

Blood-based scores: every 3–6 months if you are actively changing something, otherwise annually. Epigenetic clocks: every 12–24 months — they move slowly and the per-test cost and noise do not justify more frequent testing. Wearable-derived scores: watch the trend daily, but evaluate monthly. For a full decision framework that matches retest cadence to your clock and goal, see our dedicated guide.

Is a blood test or an epigenetic test better?

Neither is universally better — they answer different questions. Blood tests measure current systemic physiology and are cheaper, faster, and directly modifiable. Epigenetic tests measure deeper cellular aging and predict mortality more robustly. A reasonable default for most people under 55 is annual blood-based PhenoAge plus an epigenetic test every few years for calibration.

Can wearable-derived biological age replace a lab test?

No. Wearable scores measure cardiovascular and sleep fitness — critically important, but a subset of what PhenoAge and GrimAge capture. A 55-year-old with elite VO2 max and a wearable “fitness age” of 35 can still have elevated hs-CRP, rising fasting glucose, and an accelerated PhenoAge. Use wearables for trend, labs for ground truth.

Does a lower biological age mean I’ll live longer?

It shifts the probability — it is not a guarantee. A PhenoAge 5 years below chronological age correlates with lower all-cause mortality in population studies, but individual outcomes depend on genetics, environment, and accidents. Treat the number as one input to a longevity strategy, not a destiny.

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Key takeaways

• Three categories dominate the market — blood-based clocks (PhenoAge, KDM), epigenetic clocks (Horvath, GrimAge, DunedinPACE), and wearable-derived fitness age. They measure different things.
• Blood-based is the best default. Cheap, fast, actionable, every input is a treatable marker. Ideal for repeat testing.
• Epigenetic tests are the mortality gold standard — but expensive, slow, and noisier than marketing claims. Reserve for annual or biennial calibration.
• Wearable scores measure fitness, not cellular age. Use them for short-loop feedback, not as a lab substitute.
• The most useful setup combines all three at different cadences — labs for ground truth, wearables for trend, epigenetic tests for occasional deep validation.

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Start your biological age journey today

If you already get annual bloodwork, you have everything you need to start. SuperAge turns a standard lab panel into a peer-reviewed PhenoAge/KDM score, layers in wearable context from HealthKit, and plots the trend so you can see whether what you’re doing is actually working.

Download SuperAge on the App Store and get your first biological age read today.

For a broader view of the longevity app landscape, see our comparison of Humanity alternatives.

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For a narrower decision guide, see Biological age confidence intervals: why one number is not enough.

References

1. Horvath, S. (2013). DNA methylation age of human tissues and cell types. Genome Biology, 14(10), R115. https://doi.org/10.1186/gb-2013-14-10-r115
2. Levine, M. E., Lu, A. T., Quach, A., et al. (2018). An epigenetic biomarker of aging for lifespan and healthspan. Aging, 10(4), 573–591. https://doi.org/10.18632/aging.101414
3. Lu, A. T., Quach, A., Wilson, J. G., et al. (2019). DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging, 11(2), 303–327. https://doi.org/10.18632/aging.101684
4. Belsky, D. W., Caspi, A., Corcoran, D. L., et al. (2022). DunedinPACE, a DNA methylation biomarker of the pace of aging. eLife, 11, e73420. https://doi.org/10.7554/eLife.73420
5. Klemera, P., & Doubal, S. (2006). A new approach to the concept and computation of biological age. Mechanisms of Ageing and Development, 127(3), 240–248. https://doi.org/10.1016/j.mad.2005.10.004
6. Hannum, G., Guinney, J., Zhao, L., et al. (2013). Genome-wide methylation profiles reveal quantitative views of human aging rates. Molecular Cell, 49(2), 359–367. https://doi.org/10.1016/j.molcel.2012.10.016

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Last updated: 2026-04-15. This article is regularly reviewed to ensure accuracy.