Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

  • A.O., L.Y., D. Cesarini, P.T., P.M.V., J.P.B., D.J.B. and A.I.Y. designed and oversaw the study. A.O. was the study’s lead analyst, responsible for GWAS, quality control, meta-analyses, analyzing the predictive power of the PGI for EA and cognition outcomes and creating the PGIs used in other analyses (except for the disease PGIs). M.B. and H.K. conducted the recoding of the educational attainment measure in the UKB. A.O. and J.P.B. performed the GWAS replication. J.P.B. calculated the winner’s-curse-adjusted effect sizes. L.Y. conducted the analysis of predicted and actual PGI accuracy in the African-genetic-ancestry sample in the UKB. H.J. ran the bioinformatics analysis, under J.J.L.’s guidance. A.O., N.W., L.Y. and J.P.B. conducted the dominance GWAS meta-analysis. A.O., J.S. and P.M.V. oversaw and ran the X chromosome meta-analysis. Y.W. analyzed the predictive power of the PGI for disease phenotypes. S.M.N., R.A., S.O. and A.I.Y. conducted the within-family analyses. H.J., D. Cesarini and A.I.Y. conducted the assortative mating analyses. Besides the contributions explicitly listed above, N.W., H.J., M.B., G.G. and T.G. assisted for several subsections. C.W. coordinated data organization, and J.J. organized the computing infrastructure. D. Conley, P.D.K., M.J., D.L. and M.N.M. provided important input and feedback on various aspects of the study design. All authors contributed to and critically reviewed the manuscript.


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