Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

Abstract

Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.

Fig. 1.. Manhattan Plot for GWAS of EduYears (N = 1,131,881).

P values and the mean χ² shown in figure are based on inflation-adjusted test statistics. The x-axis is chromosomal position, and the y-axis is the significance on a −log₁₀ scale. The dashed line marks the threshold for genome-wide significance (P = 5×10⁻⁸).

Fig 2.. Sign Concordance in Within-Family Association Analyses.

The set of LD-pruned SNPs is limited to SNPs with (a) P < 5×10⁻³, (b) P < 5×10⁻⁵, or (c) P < 5×10⁻⁸. Each panel compares the observed sign concordance between within-family and GWAS estimates to the distributions expected (i) by chance alone (pink); (ii) according to a Bayesian framework that adjusts the GWAS estimates for bias due to winner’s curse (green); and (iii) according to the same framework with an additional adjustment for bias due to assortative mating (blue). These results are based on a GWAS sample size of 1,070,751 individuals and a within-family sample of 22,135 sibling pairs (44,270 individuals).

Fig. 3.. Tissue-specific expression of genes in DEPICT-defined loci.

(a) We took microarray measurements from the Gene Expression Omnibus and determined whether the genes overlapping EduYears-associated loci (as defined by DEPICT) are significantly overexpressed (relative to genes in random sets of loci) in each of 180 tissues/cell types. These types are grouped in the figure by Medical Subject Headings (MeSH) first-level term. The y-axis is the one-sided P value from DEPICT on a –log₁₀ scale. The 28 dark bars correspond to tissues/cell types in which the genes are significantly overexpressed (FDR < 0.01), including all 22 classified as part of the central nervous system (see Supplementary Table 6 for identifiers of all tissues/cell types). (b) Whereas genes prioritized by DEPICT in a previous analysis based on a smaller sample tend to be more strongly expressed in the brain prenatally (red curve), the 1,703 newly prioritized genes show a flat trajectory of expression across development (blue curve). Both groups of DEPICT-prioritized genes show elevated levels of expression relative to protein-coding genes that are not prioritized (gray curve). Analyses were based on RNA-seq data from the BrainSpan Developmental Transcriptome. These results are based on the full GWAS sample of 1,131,881 individuals. Error bars represents 95% confidence intervals.

Fig. 4.. Prediction Accuracy.

(a) Mean prevalence of college completion by EduYears PGS quintile. Error bars show the 95% confidence interval for the mean. (b) Incremental R² of the EduYears PGS compared to that of other variables. (c) Incremental R² of the PGS for EduYears and Cognitive Performance constructed from the respective GWAS or MTAG summary statistics. Error bars for the R² values show bootstrapped 95% confidence intervals with 1000 iterations each. Sample sizes are N = 4,775 for Add Health and N = 8,609 for HRS.