Relationships between SATS z-scores and unweighted allele score within the ALSPAC study.

<p>All models include sex and age as covariables.</p

Overlay histograms showing z-scores for English and mathematics stratified by sex within the ALSPAC study.

<p>Boys’ results in grey; girls’ results in white. Girls exhibit an average 0.433 SD (95%CI 0.395, 0.470), p<10⁻¹⁰ advantage over boys in English, and attain more similar exam results in mathematics with boys exhibiting an average 0.042 SD (95%CI 0.004, 0.080), p = 0.0303 advantage over girls in mathematics.</p

Histogram of allele score, with linear relationships between SATS z-scores and the allele score superimposed.

<p>The unweighted allele score is created from three SNPs rs9320913, rs11584700 and rs4851266. Each unit increase in the allele score corresponds to an individual having an additional educational attainment increasing allele. The density for the allele score taking the value 6 is 0.0016, which is too small to be visible in this figure. The linear relationships with 95%CIs from our regressions of SATS z-scores on allele score are superimposed. The English regression is represented by a black line with grey 95%CI, and mathematics by a grey line with black 95%CI.</p

Theoretical predictions of power per causal SNP (upper panel) and out-of-sample <i>R</i>² of the PGS (lower panel), for a trait that across studies has SNP heritability (<i>x</i>-axis) and cross-study genetic correlation (<i>y</i>-axis).

<p>Factor levels: 50 studies, sample size 5,000 individuals per study, 100k independent SNPs, and heritability arising from a subset of 1k independent SNPs.</p

Theoretical predictions of power per causal SNP (upper panel) and out-of-sample <i>R</i>² of the PGS (lower panel), for a trait with GWAS results from the number of studies (<i>x</i>-axis) with cross-study genetic correlation (<i>y</i>-axis).

<p>Factor levels: total sample size 250,000 individuals, 100k independent SNPs, and arising from a subset of 1k independent SNPs.</p

Theoretical predictions of power per causal SNP, for total sample size (<i>x</i>-axis) and CGR between two sets of studies (<i>y</i>-axis).

<p>Factor levels: 2 sets of 50 studies, CGR equal to 1 within both sets, 100k independent SNPs, and arising from a subset of 1k independent SNPs.</p

Predicted and observed number of genome-wide-significant hits and PGS <i>R</i>², for large-scale GWAS efforts to date for height, BMI, <i>EduYears</i>, and self-rated health, assuming 250k effective SNPs (i.e., independent haplotype blocks) of which 20k trait-affecting, using averaged GREML estimates from Table 1 for setting SNP heritability and CGR.

<p>Notes on the sources for the large-scale GWAS efforts are listed in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006495#pgen.1006495.s009" target="_blank">S3 Table</a>.</p

Theoretical predictions of power per causal SNP (upper panel) and out-of-sample <i>R</i>² of the PGS (lower panel), for total sample size (<i>x</i>-axis) and cross-study genetic correlation (<i>y</i>-axis).

<p>Factor levels: 50 studies, 100k independent SNPs, and arising from a subset of 1k independent SNPs.</p

GREML estimates of SNP heritability and genetic correlation across studies and sexes.

<p>GREML estimates of SNP heritability and genetic correlation across studies and sexes.</p

Theoretical predictions of out-of-sample <i>R</i>² of the PGS, for the SNP heritability in the hold-out sample (<i>x</i>-axis) and the SNP heritability in the discovery samples (<i>y</i>-axis).

<p>Factor levels: 50 studies, sample size 5,000 individuals per study, cross-study genetic correlation 0.8, 100k independent SNPs, and heritability arising from a subset of 1k independent SNPs.</p