GWAS was conducted using linear mixed models with random effects adjusting for relatedness within families using the R package GWAF (Chen and Yang, 2010). Sex, birth cohorts, array indicators, and the first four PCs were included as covariates. METAL (Willer et al., 2010) was used to perform meta-analysis with effect size of each variant weighted by the inverse of the estimated standard error from each subsample. Genomic control was applied to the results of each subsample as well as to the meta-analysis results. As SRE-T and SRE-5 were highly correlated (correlation coefficients were 0.75 and 0.78 in COGA-AA and COGA-EA, respectively), we used matSpD (Nyholt, 2004) to spectrally decompose the correlation matrix of SRE scores, resulting 1.44 effective test. Thus, the genomewide significance was set at p< 3.5 × 10-8. In regions of genomewide significance, conditional analyses were performed by including the most significant variant in the region as a covariate.
