Table S8.

Summary information on the polygenic scores of the different phenotypes

ScoreOptimal Gaussian mixture weight for LDpredLDpred window size (no. of SNPs)No. of SNPs usedAssumed GWAS sample sizeGWAS articleSource for GWAS summary statisticsR2, previously reportedIncremental R2 (SE), estimated in HRS
Score of BMI0.1170505,254232,186(19)*** (0.007)
Score of EA0.1180544,493386,098(20)SSGAC (Summary statistics from a meta-analysis excluding the HRS were used)0.0390.074*** (0.006)
Score of GLU0.031022,894120,000(21)
Score of HGT1170510,411243,630(22)*** (0.009)
Score of SCZ0.3180544,22575,000(23)
Score of TC0.3175530,01292,793(24)*** (0.004)
Score of AAM0.3170506,120120,000(25)
  • For every phenotype, the polygenic score was constructed using LDpred (33), using the individuals' genotyped SNPs that passed quality control filters and overlapped with the SNPs in the phenotype's summary statistics file. The optimal Gaussian mixture weights (the assumed fractions of causal markers) were selected to maximize each score's R2 with respect to the corresponding phenotype or to maximize the correlations between each score and known correlates of the corresponding phenotype. As recommended, LDpred windows approximately equal to the number of used SNPs divided by 3,000 were used. The assumed GWAS sample sizes are the assumed sample sizes for LDpred, based on mean sample sizes across the used SNPs (when SNP-level sample sizes are reported) or based on the reported GWAS sample sizes (slightly reduced to account for missing observations). The previously reported R2 and the incremental R2 estimated in the HRS are the numerical values of the results presented in Fig. 1 (with SEs instead of 95% CI). The incremental R2 estimated in the HRS for the score of EA is substantially higher than the previously reported R2 because the score I used in the HRS is based on summary statistics from a meta-analysis that includes one additional large cohort (the UK Biobank). (***P < 0.01.)