Action potential durations and QT intervals

Here’s an interesting little result that is thanks to Kylie. She found it whilst doing the work for her paper on prediction of drug compound effects at the tissue scale using data on multiple ion channel block. But we didn’t manage to squeeze it into that paper, so thought I’d put it up here.

Lots of people have done simulations of drug effects on cardiac tissue cells, we wrote a review on this a couple of years ago.

All you need to know here is that the heart cells experience (and generate) a wave of electrical activity that causes them to contract and pump blood. The wave seen by any particular cell is called its action potential. Blocking certain ion channels can lead to the heart cells being electrically active (‘depolarized’) for a longer time than normal – giving a longer Action Potential Duration (APD); and blocking others can lead to cells being active for less time – having shorter APD. (Of course, you can get anything in between as blocking lots of channels at once could do either*).

Prolonging the APD is linked to prolongation of what’s called the QT interval on the electrocardiogram (ECG) – see Fig 1. When induced by taking pharmaceutical drugs, both effects are often due to a particular potassium current being blocked (the current is called IKr, it flows through an ion channel mostly made of proteins encoded by the hERG gene).

Figure 1: Relationship between ion current block, action potential duration, and QT interval. Top: IKr current, Middle: action potential (both simulated); Bottom: my artistic impression of the corresponding changes to the whole body ECG.

Figure 1: Relationship between ion current block, action potential duration, and QT interval. Top: IKr current, Middle: action potential (both simulated); Bottom: my artistic impression of the corresponding changes to the whole body ECG. This Figure is taken from my (open access) paper reviewing simulation for cardiac drug safety.

In Kylie’s paper, the idea of the study was to use ion channel screening data to predict changes to the QT interval that would be observed in experiments on rabbit heart tissue.

If you want to simulate ECG changes then you have a few options:

  • Simulate a single cell (0D) then just differentiate the action potential (you don’t see many people do this, but I can’t see why not as a first approximation).
  • Simulate a monodomain tissue and use a ‘pseudo-ECG’ calculation – details in this paper.
  • Simulate a bidomain tissue and compare extracellular potentials between locations directly (this is why you have a number of electrodes stuck on you for a real ECG).

Anyway, we did the middle one with a 1D ‘strand’ of tissue, to see if it would get closer to observed ECG changes in experiment than just looking at action potential duration changes (APD90). You can see the correlation between both approaches in Fig 2.

Simulated change in APD90 vs simulated change in QT interval

Figure 2: simulated change in APD90 vs simulated change in QT interval using the Shannon rabbit model. About 100 drugs are plotted here, for different concentrations (joined by black lines). The area around the origin contains most of the points.  The red line is 1:1 and the green line is the line of best fit with change in QT = 1.34 x change in APD90.

A change in APD90 is highly correlated with a change in QT in the simulations (as you’d probably expect). What we noticed, that I haven’t seen much comment on before, is that the relationship is not 1:1 (red line), instead it is steeper at about 1:1.34 (green line of best fit), so you get more change in QT in the simulation than you do in APD.

I’m not quite sure why we see this yet, whether different methods for measuring APD and QT would make much difference to this, or whether it is some effect of the boundaries in a tissue of finite length (obviously real tissues are finite so it might be a good boundary effect!). But if the relationship shown in Figure 2 holds more widely (for different models, in different tissues, for bidomain simulations etc.) it suggests a simple rescaling may allow more accurate QT predictions to be made from single cell APD predictions.

Why bother?

*Pharmaceutical drugs have a bit of a habit of blocking ion channels, sometimes that is how they work, but often it is an unintended side effect. For a lot of potential drugs block of cardiac ion channels is an issue. Both IKr block and QT prolongation are associated with a drug-induced increase in the risk of pro-arrhythmia: the heart going into an unusual rhythm which can be fatal. Obviously that’s an unacceptable side effect for something like a hay fever drug, and so pharmaceutical companies and regulators have to spend a lot of time and money checking this isn’t likely to happen, or weighing up the risk/benefit for e.g. a cancer treatment with a small risk of pro-arrhythmia.

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7 Responses to Action potential durations and QT intervals

  1. Zitoun says:

    I like your question about such small differences (linear and non linear…). May we see End of QT story?

  2. Hitesh says:

    Hi Gary, an interesting observation on the rabbit work you did. I wonder if it would be possible to look at this in experiments say compare monophasic action potential with QT from rabbit and guinea pig langendorf experiments? I was sent an interesting article from a collaborator where this group had looked at monophasic action potentials and ecg recordings for a number of drugs: Not looked at it in a great deal of detail but there is a nice table worth of data.

  3. Hitesh says:

    Hi Gary, so i had a little play with the data from that paper and indeed the ratio there was around 1:1.4. It is % change, just mean values and not a huge n (20) which is not great, would be great to get hold of the raw data so you could increase the n. Begs the question though, if the relationship holds for more data, if guinea pig computational models have a similar relationship to what you mention above. In fact is the gradient similar for all species? If not why not? Also if it is why would it be? Of course there are plenty of questions you could ask on this if more of this data was available.

    • Gary Mirams says:

      That’s really interesting, you would expect that some Langendorff optical mapping & ECG experiments would provide a host of data on this. We’ll have to investigate a bit more…

  4. MikeMo says:

    Hi Gary, I’m having trouble understanding your work. Could you explain what exactly is the difference between the APD and the QT interval? It would be much appreciated!


    • Gary Mirams says:

      Hi Mike,

      Both are measures of how long cardiac tissue is electrically active when a wave of excitation goes through it. The APD is a measurement of voltage across a single cell’s membrane – the middle graph of Figure 1. The QT interval is a measurement taken from the electric field outside the muscle (or on the surface of your body in a hospital) – looks a bit like the bottom graph in Figure 1. This post is about how changes in the APD correlate (in simulations) with changes in QT, but not at the 1:1 relationship one might expect.

      Hope that helps,


  5. MikeMo says:

    Thank you very much Gary! Keep up the great work.

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