The power to detect individual SNPs as significantly associated with a trait such as height depends on the variance associated with the SNP. This, in turn, depends on the LD between the SNP and the causal variant, the effect of the causal variant and its frequency. Causal variants with small effects or rare alleles with large effects (including rare Mendelian variants) will explain little variance and so will tend not to be significant even if they are in high LD with an assayed SNP. However, the cumulative effect of these SNPs will be included as part of the 45% of phenotypic variance explained by the SNPs in our analysis. Despite the use of ~295K SNPs, many causal variants, especially if they have low MAF, will not be in perfect LD with the assayed SNPs. This reduces the power of a conventional GWAS to detect them and reduces the variance estimated for the SNPs collectively in our study. The results imply that most causal variants explain such a small proportion of the variance that many causal variants affecting height must exist.
