Back

Towards prospective in-silico trials in atrial fibrillation: the case of polypharmacological SK and K2P channel block

Dasi, A.; Berg, L. A.; Martinez-Navarro, H.; Bueno-Orovio, A.; Rodriguez, B.

2024-03-30 bioengineering
10.1101/2024.03.30.586087 bioRxiv
Show abstract

BackgroundVirtual evaluation of medical therapy through human-based modelling and simulation can accelerate and augment clinical investigations. Treatment of the most common cardiac arrhythmia, atrial fibrillation (AF), requires novel approaches. ObjectivesTo prospectively evaluate and mechanistically explain novel pharmacological therapies for atrial fibrillation through in-silico trials, considering single and combined SK and K2P channel block. MethodsA large cohort of 1000 virtual patients was developed for simulations of AF and pharmacological action. Extensive calibration and validation with experimental and clinical data support their credibility. ResultsSustained AF was observed in 654 (65%) virtual patients. In this cohort, cardioversion efficacy increased to 82% (534 of 654) through combined SK+K2P channel block, from 33% (213 of 654) and 43% (278 of 654) for single SK and K2P blocks, respectively. Drug-induced prolongation of tissue refractoriness, dependent on the virtual patients ionic current profile, explained cardioversion efficacy (atrial refractory period increase: 133.0{+/-}48.4 ms for combined vs. 45.2{+/-}43.0 and 71.0{+/-}55.3 for single SK and K2P block, respectively). Virtual patients cardioverted by SK channel block presented lower K2P densities, while lower SK densities favoured the success of K2P channel inhibition. Both ionic currents had a crucial role on atrial repolarization, and thus, a synergism resulted from the polypharmacological approach. All three strategies, including the multi-channel block, preserved atrial electrophysiological function (i.e., conduction velocity and calcium transient dynamics) and thus, its contractile properties (safety). ConclusionIn-silico trials identify key factors determining efficacy of single vs combined SK+K2P channel block as effective and safe strategies for AF management.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
BMC Cardiovascular Disorders
14 papers in training set
Top 0.1%
23.4%
2
Scientific Reports
3102 papers in training set
Top 7%
9.5%
3
Computers in Biology and Medicine
120 papers in training set
Top 0.1%
8.7%
4
PLOS ONE
4510 papers in training set
Top 24%
7.1%
5
Frontiers in Physiology
93 papers in training set
Top 0.5%
6.6%
50% of probability mass above
6
PLOS Computational Biology
1633 papers in training set
Top 6%
5.0%
7
Frontiers in Cardiovascular Medicine
49 papers in training set
Top 1%
2.2%
8
Heart Rhythm
22 papers in training set
Top 0.3%
2.2%
9
Computational and Structural Biotechnology Journal
216 papers in training set
Top 3%
2.0%
10
Philosophical Transactions of the Royal Society B
51 papers in training set
Top 3%
1.8%
11
International Journal for Numerical Methods in Biomedical Engineering
12 papers in training set
Top 0.1%
1.7%
12
Annals of Biomedical Engineering
34 papers in training set
Top 0.6%
1.7%
13
International Journal of Molecular Sciences
453 papers in training set
Top 8%
1.5%
14
Frontiers in Pharmacology
100 papers in training set
Top 3%
1.4%
15
Circulation
66 papers in training set
Top 2%
0.9%
16
Biomechanics and Modeling in Mechanobiology
25 papers in training set
Top 0.7%
0.9%
17
Ultrasound in Medicine & Biology
10 papers in training set
Top 0.4%
0.8%
18
Communications Biology
886 papers in training set
Top 20%
0.8%
19
European Heart Journal
16 papers in training set
Top 0.7%
0.8%
20
JACC: Clinical Electrophysiology
11 papers in training set
Top 0.3%
0.8%
21
Physiological Measurement
12 papers in training set
Top 0.4%
0.8%
22
American Journal of Physiology-Heart and Circulatory Physiology
32 papers in training set
Top 1%
0.8%
23
Journal of Neural Engineering
197 papers in training set
Top 2%
0.7%
24
iScience
1063 papers in training set
Top 32%
0.7%
25
Computer Methods and Programs in Biomedicine
27 papers in training set
Top 1%
0.7%
26
npj Digital Medicine
97 papers in training set
Top 4%
0.7%
27
PeerJ
261 papers in training set
Top 18%
0.5%
28
Nature Communications
4913 papers in training set
Top 67%
0.5%