Gene discovery and polygenic prediction from a 1.1-million-person GWAS of educational attainment
By James J. Lee, Robbee Wedow, A. Okbay, E. Kong, Omeed Maghzian, Meghan Zacher, Tuan Anh Nguyen-Viet, Peter M. Bowers, J. Sidorenko, R. Karlsson Linnér and 312 more. 2018
2,165 citations recorded by the source corpus.
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. Gene discovery and polygenic predictions from a genome-wide association study of educational attainment in 1.1 million individuals.
Subfields: Genetics
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Citations in the corpus
- Brain age prediction using deep learning uncovers associated sequence variants (2019, background): “(3) rs2184968-C is located in an intron of CENPW , a gene that has previously been associated with traits, such as, height 48 , cognitive performance 49 , and male-pattern baldness 50 .”
- Education and Cognitive Functioning Across the Life Span (2020, neutral): “…studies of educational attainment indicated an average genetic correlation between different study cohorts of .723, well below the genetic correlation of 1.0 that would be expected if the genetic bases of educational attainment were entirely consistent across populations ( J. J. Lee et al., 2018).”
- Polygenic prediction of weight and obesity trajectories from birth to adulthood (2019, neutral): “This lower strength of association using fewer variants is consistent with earlier studies, where predictors of up to 97 variants had a relatively low correlation with measured BMI, ranging from 0.01 to 0.12 (Belsky et al., 2013; Hung et al., 2015; Li et al., 2010; Sandholt et al., 2010).”