Gene discovery and polygenic prediction (from genome-wide association study; GWAS) of educational attainment

These GEITP pages have previously described innumerable genotype-phenotype association studies, which have become more powerful during the last decade due to whole-genome association studies (GWAS) often involving hundreds of thousands of individuals in the cohort –– and the larger numbers (in the experimental vs control groups) enables more single-nucleotide variants (SNVs) to reach statistical significance. Educational attainment (associated with I.Q. as well as confidence in achieving success) can be considered a quantitative trait (phenotype) because it is moderately heritable and an important parallel to many social, economic and health outcomes. Thus, measures of educational attainment are available in most medical datasets. Partly for this reason, educational attainment has become the focus of large-scale GWAS of this social-science phenotype and has continued to serve as a ‘model phenotype’ for behavioral traits (analogous to ‘height’ for medical traits).

Previously, the largest (N = 293,723) GWAS dataset of educational attainment had identified 74 presumably independent SNVs (having genome-wide significance of P < 5.0e–08) and reported that a 10-million-SNV linear predictor (polygenic score) had an out-of-sample predictive power of 3.2%. Authors [see attached current article] expanded the sample size (to N = 1,131,881) –– and identified 1,271 genetic loci. For a subsample (N = 694,894), authors also conducted GWAS of variants on the X chromosome, identifying ten genetic loci. The striking increase in sample size enabled the authors to conduct a number of additional informative analyses. These biological annotation analyses, which focus on results from the autosomal GWAS (i.e. chromosomes other than the X and Y chromosome), reinforced the main findings from earlier GWAS in smaller samples –– such as the role of many of the prioritized genes in brain development. However, the newly identified SNVs also led to several new findings (e.g. strongly implicating genes involved in almost all aspects of neuron-to-neuron communication). Authors found that a polygenic score derived from their results can explain ~11% of the variance in educational attainment. They also report additional GWAS of three phenotypes that are highly genetically correlated with educational attainment: cognitive (test) performance (N = 257,841), self-reported math ability (N = 564,698), and hardest math class completed (N = 430,445); in these three "trait categories" authors identified 225, 618 and 365 SNVs, respectively. When they jointly analyzed all four phenotypes using a recently developed method, authors found that the explanatory power of polygenic scores based on the resulting summary statistics –– increases to 12% for educational attainment, and to 7–10% for cognitive performance. Nature Genet Aug 2o18; 50: 1112–1121

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