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. 2022 Mar 31;54(4):437–449. doi: 10.1038/s41588-022-01016-z

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Extended Data Fig. 3 — We examined the out-of-sample replicability of the 1,504 lead SNPs identified at genome-wide significance in a version of our previously published GWAS meta-analysis of EduYears (EA3), with the UKB GWAS in that analysis replaced by a UKB GWAS that uses the new phenotype coding explained in Supplementary Note section 1.1. Prior to clumping, we dropped SNPs that had a sample size smaller than 80% of the maximum sample size in the updated EA3 data (N_{EA3,max =} 1,130,819), or that had a sample size in the new data smaller than 80% of the maximum sample size of the new data (N_new,max = 2,272,216). The x axis is the winner’s-curse-adjusted estimate of the SNP’s effect size in the updated EA3 study (calculated using shrinkage parameters estimated using summary statistics from EA3). The y axis is the SNP’s effect size estimated from the subsample of our data that did not contribute to the EA3 GWAS. All effect sizes are from a regression where the phenotype has been standardized to have unit variance. The reference allele is chosen to be the allele estimated to increase EA in EA3. The dashed line is the identity, and the solid line is the fitted regression line. P-values are based on two-sided Z-tests.