GWAS for height, BMI, vWF and QTi to date have identified individual genetic variants that cumulatively explain about 10%, 1.5%, 13% and 7% of phenotypic variation, respectively15–17,26. In contrast, we show that 45%, 17%, 25% and 21% of the variance is explained by common SNPs (Table 1). The difference between these two sets of figures is due to SNPs that are associated with the traits but do not reach genome wide significance. The proportion of variance explained by all the SNPs is less than the heritability because of incomplete LD between the causal polymorphisms and the SNPs. Therefore, experiments to find SNPs that pass the genome-wide significance threshold can focus on the proportion of variation that is tagged by common SNPs by increasing sample size, or focus on the proportion of variation that is not tagged, for example, by considering less common variants. The former approach has been successfully done by the GIANT consortium, which reported that 10% and 1.5% of variation for height and BMI, respectively, can be accounted for by common SNPs using sample sizes of more than
