Introduction Electrocardiographic (ECG) markers of ventricular depolarisation and repolarisation are associated with an increased risk of arrhythmia and sudden cardiac death. Our prior work indicated lower serum calcium concentrations are associated with longer QT and JT intervals in the general population. Here, we investigate whether serum calcium is a causal risk factor for changes in ECG measures using Mendelian Randomisation (MR).
Methods We performed a new genome-wide association study (GWAS) for serum calcium in >300,000 European-ancestry participants from UK-Biobank. Independent lead variants were extracted to be used as instrumental variables (figure 1). Two-sample MR analyses were performed to approximate the causal effect of serum calcium on QT, JT and QRS intervals using an inverse-weighted method in 76,226 UK-Biobank participants with ECG data, not contributing to the serum calcium GWAS. A secondary analysis wase performed using lead variants from a calcium GWAS corrected for serum albumin. Sensitivity analyses were performed using contemporary methods to test for the presence of horizontal pleiotropy.
Results 205 independent lead calcium-associated variants were used as instrumental variables for Mendelian Randomisation. A decrease of 0.1 mmol/L genetically-determined serum calcium, was associated with longer QT (3.01ms (95% CI 2.03, 3.99)) and JT (2.89ms (1.91, 3.87)) intervals. A weak association was observed for QRS duration in secondary analyses only (0.39ms (0.08, 0.69)). Results were concordant in all sensitivity analyses.
Conclusion These analyses support a causal effect of serum calcium levels on ventricular repolarisation, in a middle-aged population of European-ancestry where serum calcium concentrations are likely stable and chronic. Modulation of calcium concentration may therefore directly influence cardiovascular disease risk. Further research into the effects of serum calcium concentration on arrhythmogenesis is warranted and calcium variants could be considered for inclusion in genetic risk score models for predictive testing.
Conflict of Interest None
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