GWAS of Educational Attainment - Phase 3: Main results
Abstract
Genetic factors are estimated to account for at least 20% of the variation across individuals for educational attainment (Rietveld et al., 2013). The results of the latest GWAS for educational attainment identified 74... [ view full abstract ]
Genetic factors are estimated to account for at least 20% of the variation across individuals for educational attainment (Rietveld et al., 2013). The results of the latest GWAS for educational attainment identified 74 genome-wide significant loci for educational attainment (Okbay et al., 2016). Here, in one of the largest GWAS to date, we increase our sample to nearly 750,000 individuals, and we identify over 600 genome-wide significant loci associated with the number of years of schooling completed. Note that at the time of writing, we will likely have updated our meta-analysis to include over 1,000,000 individuals.
In this presentation, I will present the details of this new meta-analysis, including analyses on the X chromosome. I will also present details of our quality control procedures, a thorough investigation of population stratification biases in our results, and novel approaches to identifying variants associated with theoretically related phenotypes like late onset Alzheimer’s disease or cognitive function, using a new approach called Multi-Trait Analysis of GWAS (Turley et al., 2017). I will conclude by highlighting some basic findings from our polygenic prediction section and discussing the relevance of our findings for behavioral genetics and social sciences.
Authors
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Aysu Okbay
(Vrije Universiteit Amsterdam)
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Robbee Wedow
(University of Colorado Boulder)
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Edward Kong
(Harvard University, NBER)
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Patrick Turley
(Broad Institute of MIT and Harvard)
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James Lee
(University of Minnesota Twin Cities)
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Meghan Zacher
(Harvard University)
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Kevin Thom
(New York University)
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Anh Tuan Nguyen Viet
(University of Southern California)
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Omeed Maghzian
(Harvard University, NBER)
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Richard Karlsson Linnér
(Vrije Universiteit Amsterdam)
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Matthew Robinson
(The University of Queensland)
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Social Science Genetic Association Consortium
(NA)
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Peter Visscher
(The University of Queensland)
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Daniel Benjamin
(University of Southern California)
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David Cesarini
(New York University)
Topic Areas
Gene Finding Strategies , Statistical Methods , Developmental Disorders (e.g. ADHD) , Cognition: Education, Intelligence, Memory, Attention
Session
1C-OS » Educational Attainment (10:30 - Thursday, 29th June, Forum)