This study is hypothesis based since it utilises prior information from GWA studies and can consequently be likened to candidate gene studies. Therefore statistical significance was considered at p<0.05 level for the SNP associations on adult height, PHV1 and PHV2 and the age-SNP interaction on PHV. Since we do not have similar prior information for the timing of height growth spurt, we only declare statistical significance at p<0.0011 level for ATO and age at PHV2. This level is based on Bonferroni correction considering 44 independent signals. Previous GWA studies found no evidence for sex-SNP interactions on adult height, although sex is an important determinant of growth and adult height [4]–[6]. We test sex-SNP interactions on each outcome but due to the absence of prior evidence for interactions use Bonferroni correction (p<0.0011 level) for assessing their statistical significance.
