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Diastolic Age predicts MACE and discriminates LVDD in heart failure cohortsDoctors Can Now Measure Your Heart’s True Age With One Scan

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Key Takeaway
Note that Diastolic Age independently predicts MACE (HR 2.30) and discriminates LVDD (AUC 0.89) in this observational cohort.

Participants from the Project Baseline Health Study (median age 50 [36-64] years, 54% female) and external validation cohorts (WASE and Stanford Cardiovascular Aging) were included in this cohort study. The total sample size was 1,952 in the primary cohort, 1,708 in WASE, and 313 in the Stanford cohort. The exposure was Diastolic Age, derived from echocardiographic parameters weighted against the PREVENT-HF risk score, compared against chronological age, Levine epigenetic clock, Horvath epigenetic clock, and ASE-defined LV diastolic dysfunction.

Diastolic Age demonstrated strong correlation with chronological age (r=0.78) and robust correlations in external validation cohorts, with r=0.76 in WASE and r=0.82 in Stanford. The measure correlated with the Levine epigenetic clock (r=0.76) and the Horvath epigenetic clock (r=0.41). Regarding diastolic dysfunction, Diastolic Age achieved an AUC of 0.89 for discrimination, which was comparable to ASE-defined LVDD (C-index 0.83 vs. 0.82).

The study assessed associations with hypertension, diabetes, elevated C-reactive protein, and epigenetic clocks. Diastolic Age independently predicted MACE with a hazard ratio of 2.30 (95% CI 1.70-3.18). Safety data, including adverse events, serious adverse events, discontinuations, and tolerability, were not reported. No specific limitations were detailed in the provided data, and funding or conflicts were not reported.

Diastolic Age provides a continuous, echocardiography-derived measure of cardiac biological aging that complements categorical diastolic grading and epigenetic aging clocks, and independently predicts cardiovascular outcomes. Clinicians should interpret these results as observational associations rather than causal relationships, noting that adverse event profiles remain uncharacterized in this dataset.

This new research changes how we look at heart health. It focuses on the heart’s ability to relax and fill with blood. Problems here often happen before the heart muscle weakens.

Doctors call this phase diastolic function. It is the time when the heart rests and prepares for the next beat. When this slows down, the heart struggles to pump blood efficiently.

The surprising shift

For years, doctors used simple categories like normal or abnormal. This binary view missed subtle changes in aging hearts. But here’s the twist. Scientists found a way to measure aging as a continuous number.

Instead of just saying a heart is healthy, they can now say it is 55 years old. This allows for earlier detection of potential trouble. It turns a vague feeling into a specific number.

Think of your heart like a car engine. An odometer tracks miles, but wear and tear vary by driver. This new tool acts like a wear-and-tear gauge. It looks at how the heart moves during an ultrasound.

The team used a special formula to weigh different heart features. They compared these features against a known risk score for heart failure. This calibration creates a score that reflects biological wear.

What scientists didn’t expect

The team analyzed nearly 2,000 participants from a large health study. They used standard heart ultrasound images to build the score. Then they tracked health outcomes for over four years.

They also tested the tool in two other groups of patients. These external groups confirmed the results were consistent. The tool worked well across different populations and settings.

The results were clear. People with a higher Diastolic Age faced more heart risks. This held true even when comparing them to others of the same age. The measure predicted major heart events better than standard checks.

Those with accelerated heart aging were more likely to have high blood pressure or diabetes. The tool also matched up with DNA-based aging clocks. However, it captured unique heart-specific changes that DNA missed.

A closer look

This doesn’t mean this treatment is available yet. The study shows promise, but it is not a finished product. It is a research tool designed for scientists and specialists.

Experts say this adds a new layer to prevention. It helps separate people who look healthy from those at risk. It complements other aging clocks based on DNA.

This approach moves medicine from treating sickness to preventing it. It gives doctors a clearer picture of long-term risk. It helps them decide who needs more aggressive care.

You cannot order this test at home today. Regular heart ultrasounds are already common for some patients. If you have risk factors, ask your doctor about standard screening.

Lifestyle changes remain the best way to slow heart aging. Eating well and staying active helps the heart relax better. This tool simply helps track progress over time.

The limits

The study group was mostly middle-aged adults. We do not know if it works for children or the very old. More data is needed to confirm accuracy across all groups.

It also relies on high-quality ultrasound images. Poor image quality could lead to inaccurate scores. Standardizing this process is a key challenge for the future.

Researchers are now testing this in different populations. Approval from health agencies will take time and more proof. But the goal is clear. To catch heart trouble before it starts.

If approved, this could become a standard part of checkups. It would allow doctors to spot risks years in advance. That early warning could save many lives in the long run.

Study Details

Study typeCohort
Sample sizen = 1,708
EvidenceLevel 3
PublishedApr 2026
View Original Abstract ↓
Background: Among cardiac measures, diastolic parameters demonstrate the earliest and most consistent age-related changes. This can be leveraged to develop a continuous left ventricular (LV) Diastolic Age from routine echocardiographic parameters. Analogous to how epigenetic clocks weight molecular markers against mortality risk, we calibrated Diastolic Age by weighting echocardiographic features against the validated PREVENT-Heart Failure (HF) risk score. Methods: We analyzed 1,952 participants from the Project Baseline Health Study (median age 50 [36-64] years, 54% female). The measure was derived using partial least-squares regression anchored on PREVENT-HF and calibrated within a healthy reference subgroup. External validation was performed in the WASE (n=1,708) and Stanford Cardiovascular Aging (n=313) cohorts. Associations with ASE-defined LV diastolic dysfunction (LVDD), epigenetic clocks, and major adverse cardiovascular events (MACE) were examined. Results: Diastolic Age correlated strongly with chronological age (r=0.78) with robust external validation (WASE r=0.76; Stanford r=0.82; calibration slopes {approx}1.0). It increased progressively across grades of diastolic dysfunction and discriminated LVDD with an AUC of 0.89 (95% CI 0.87-0.92), and was independently associated with hypertension, diabetes, and elevated C-reactive protein. While correlated with the Levine (r=0.76) and Horvath (r=0.41) epigenetic clocks, residual analyses indicated that Diastolic Age captures a distinct cardiac-specific dimension of biological aging. Over median follow-up of 4.2 years, it independently predicted MACE (HR 2.30, 95% CI 1.70-3.18), with accelerated diastolic aging across all age groups among those with events. Discrimination was comparable to ASE-defined LVDD (C-index 0.83 vs. 0.82). Conclusion: Diastolic Age provides a continuous, echocardiography-derived measure of cardiac biological aging that complements categorical diastolic grading and epigenetic aging clocks, and independently predicts cardiovascular outcomes.
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