There were several factors that limited our ability to detect novel associations at the GWAS level (at p< 1.0 × 10 −8) with ECG traits. Our study population compared to recently published GWAS for ECG traits is relatively small and underpowered. Specifically, we were underpowered (<80%) to detect effects that explain less than 10% of the trait variability at p<1.0 × 10 −8 even for common variants (MAF >0.05). Power also limited our ability to generalize European/Asian identified associations to African Americans. As previously mentioned power is directly correlated to allele frequencies. Most GWAS fixed-content products are biased to common variation and based on LD patterns of European populations (Spencer et al. 2009). Therefore, the SNPs previously identified may only be common in Europeans and may be rare in other populations such as African Americans, limiting our power to generalize these variants. It is important to note the power calculations we report in our generalization analysis were limited to the effect sizes detected in the original study. These effect sizes could be subject to the “winner’s curse” and may over
