Is HRV genetic?

About half of the difference in HRV between people is inherited. In 772 twins and siblings wearing 24-hour monitors, genes explained 40 to 48% of the variation in RMSSD and 35 to 47% in the SDNN index. The genes found so far explain only a small part of that, and age, fitness and habits make up the rest. Comparing your number with a friend's says little; comparing it with your own last month says a lot.

On this page 5 sections

Key takeaways

  • In 772 twins and siblings, genetic factors explained 40 to 48% of 24-hour RMSSD and 35 to 47% of the SDNN index (the average SDNN of 5-minute segments) across the day.
  • A genome study of 53,174 people found eight gene regions linked to HRV; together they explain only 0.9 to 2.6% of the variation.
  • Age is the other big factor: median RMSSD roughly halves between the mid-twenties and the mid-sixties.
  • Genes set the range you start from; sleep, training, alcohol and illness move you within it.
  • That is why a low HRV compared with other people can be ordinary for you.

Partly, and by a large share. In a study of 772 twins and siblings who wore 24-hour heart monitors, genetic factors explained 40 to 48% of the variation in RMSSD RMSSD Root mean square of successive differences: an HRV metric built from how much each heartbeat interval differs from the next, in milliseconds. It mainly reflects vagal activity. More about RMSSD and 35 to 47% of the variation in the SDNN index SDNN index The mean of the SDNN of each 5-minute segment of a 24-hour recording, in milliseconds. It keeps the variability inside each segment and drops the slow drift between them. More about SDNN index . The rest comes from age, fitness, habits and chance, which is why your own trend tells you more than any comparison with other people.

What the twin study found

Kupper and colleagues (2004) recorded a 24-hour ECG ECG A recording of the heart's electrical activity, taken with electrodes on the skin. ECG-based RR intervals are the reference standard for measuring HRV. More about ECG in 772 healthy twins and their singleton siblings in the Netherlands and compared how similar identical twins were with how similar fraternal twins and siblings were. The more identical twins resemble each other beyond the others, the larger the genetic share. For the SDNN index, the average of the 5-minute SDNN SDNN The standard deviation of all NN intervals in a recording, in milliseconds. It measures overall variability, and its value depends strongly on how long the recording lasts. More about SDNN values across the recording, genes accounted for 35 to 47% of the variation depending on the time of day (morning, afternoon, evening and night); for RMSSD, 40 to 48%. The authors concluded that ambulatory HRV is highly heritable, enough to use in genetic studies of cardiovascular risk.

A share of 40 to 48% means that if you lined up a hundred people, roughly half of the spread in their RMSSD would trace to the genes they were born with, and half to everything else.

Which genes, and how much they explain

Finding the genes is harder than measuring their total share. Nolte and colleagues (2017) ran a genome-wide study of three HRV measures in up to 53,174 people of European ancestry and found 17 significant variants in eight regions of the genome, several in genes active in the sinoatrial node Sinus node The heart's natural pacemaker, a small patch of cells that starts every normal heartbeat. Left alone it fires about 100 times a minute; the vagus nerve holds it lower at rest. More about Sinus node , the heart’s pacemaker. Yet a score built from those variants explained only 0.9 to 2.6% of the variation in HRV. Most of the inherited share is spread across many small effects not yet pinned down, as it is for height and blood pressure. The study also found genetic overlap between HRV, heart rate and blood pressure.

The other half

The non-genetic half has one dominant piece: age. Voss and colleagues (2015), in 1,906 healthy adults measured with a 5-minute resting ECG, found a median RMSSD of 36 to 38 ms at 25 to 34 and 17 ms at 65 to 74. Fitness, sleep, alcohol, illness and stress move the number within the range your genes and age set; the what affects HRV guide ranks them.

How much do the measurable factors explain together? In 28,175 people who took a morning reading with a phone app, Altini and Plews (2021) found that age, sex, physical activity level and body mass index together accounted for about 15% of the differences in RMSSD between people. The remaining spread, they argue, is why a higher HRV is not a realistic goal for everyone, and why the number is more useful for tracking change within one person.

What this means for your number

When to talk to a doctor

HRV cannot tell you about inherited heart conditions. If heart disease, sudden death or fainting runs in your family, talk to a doctor about screening, whatever your HRV shows.

Common questions

If HRV is half genetic, can I change the other half?

Some of it. The non-genetic half includes age, which you cannot change, and training, sleep, alcohol and body weight, which you can. The training page and the question on fitness show what moves it and by how much.

Do my parents' heart problems mean my HRV will be low?

Not directly. The genome study found genetic overlap between HRV and heart rate and blood pressure, but HRV is a measure of nervous-system control, not a family diagnosis. Talk to a doctor about family history; a wearable cannot assess it.

Why do two fit people of the same age differ so much?

Because inherited differences in nervous-system control sit on top of fitness. In a study of 28,175 app users, age, sex, activity and body mass index together explained only 15% of the differences between people.

Sources

  1. Heritability of ambulatory heart rate variability Circulation, 2004
  2. Genetic loci associated with heart rate variability and their effects on cardiac disease risk Nature Communications, 2017
  3. Short-term heart rate variability—influence of gender and age in healthy subjects PLOS ONE, 2015
  4. What Is behind Changes in Resting Heart Rate and Heart Rate Variability? A Large-Scale Analysis of Longitudinal Measurements Acquired in Free-Living Sensors, 2021