Evaluating the Impact of Physiological Variability in Genome-Wide Association Studies of Resting Heart Rate

Genome-wide association studies (GWAS) have discovered hundreds of genetic loci for resting heart rate (RHR). However, the impact of intra-individual variation in RHR on GWAS results is unclear. We evaluated this impact by analyzing two RHR recordings from N ~61,000 subjects from UK Biobank. In addition, we modelled variations in RHR as independent white zero-mean Gaussian noise with a standard deviation of 0.5x, 1x, and 2x the standard deviation of the difference between the original RHR values (4,8, and 16 bpm, respectively). The two original RHR recordings were highly correlated (ρ =0.77), but results from the genetic analyses were s lightly different: the number of genome-wide significant (p < 5x10
⁻⁸
) variants at the locus with the strongest reported association (MYH6): n=39 vs. n=34; the p-value of the corresponding lead-variant, 3.6x10
⁻²⁴
vs. 2.1x10
⁻¹⁹
; and the estimated heritability 20.0% vs. 16.7%. Simulated data showed an inverse relationship between RHR variation and genetic association strength and heritability. Results formally demonstrate the impact of intra-individual RHR variability on the discovery of genetic variants in single-measurement studies.