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The medical term for heart rate over 100 beats per minute is tachycardia. The small molecule ivabradine reduces heart rate via specific inhibition of the pacemaker current. It is also used to alleviate chest pain (angina pectoris) and as a component in the treatment of heart failure. The HCN4 gene encodes the Potassium/sodium hyperpolarization-activated cyclic nucleotide-gated channel 4, which is primarily expressed in the pacemaker region of the heart and thought to be responsible for the pacemaker signal. It is possible that natural variants of HCN4 could mimic the effect of ivabradine in different disease states.
Marie-Pierre Dubé of Université de Montréal, Canada, and colleagues, investigated naturally occurring variants of HCN4 in the UK Biobank as a genetic model of ivabradine therapy to predict the effects of the drug on heart failure, atrial fibrillation and coronary artery disease (CAD). The results were published in the journal PLoS One.
The “G” allele at the HCN4 locus rs8038766 was associated with a heart rate reduction of 0.57 beats per minute (bpm). This locus was strongly associated with atrial fibrillation, but not with stroke, in the UK Biobank. Studies with larger numbers of stroke patients have previously shown an association between rs8038766 and stroke. There was also an association with unstable angina, but not heart failure, although there was a positive trend. Other larger heart failure specific studies have shown a protective effect of rs8038766.
The effects of genetic variants of HCN4 were broadly consistent with the pharmacological effect of ivabradine. However, the primary aim of the study to examine the correlation between HCN4 variant phenotypes and the phenotypic effect of ivabradine was limited by the fact that the gene variations were established for the lifetime of the patient, whereas ivabradine treatment was not.
“In conclusion, genetic modelling of ivabradine recapitulates its benefits in heart failure, promotion of atrial fibrillation, and neutral effect on myocardial infarction. This study supports the use of methods that leverage naturally occurring genetic variants to predict diverging results on different clinical outcomes and support the design of randomized clinical trials, even in a situation where more complex disease risks are at play,” concluded the authors.
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