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Genome-wide association study identifies 74 loci associated with educational attainment
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A genome-wide association study in 293,723 individuals identifies 74 genetic variants associated with educational attainment, which, although only explaining a small proportion of the variation in educational attainment, highlights candidate genes and pathways for further study. The level of educational attainment as measured by years of schooling completed, while strongly influenced by social and environmental factors, has also been shown to have a smaller genetic contribution. Philipp Koellinger, Peter Visscher and colleagues from the Social Science Genetic Association Consortium (SSGAC) now report a genome-wide association study in 293,723 individuals identifying 74 genetic variants associated with level of educational attainment. Although the genetic associations explain only a small proportion of the variation in educational attainment, they highlight candidate genes and pathways for further study. Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals1. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.
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“Of the 162 SNPs, 158 pass quality-control filters in our updated meta-analysis.”
From Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals (2018) · cites this paper as Okbay et al. [10]
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“Okbay et al. investigated the genetic correlation of EduYears with 14 traits and found positive genetic correlations between EduYears and intracranial volume, bipolar disorder, schizophrenia, cognitive performance, and height and negative genetic correlations between EduYears and Alzheimer’s disease, neuroticism and body mass index in the EUR population9.”
From Shared genetic architectures of educational attainment in East Asian and European populations (2024) · cites this paper as [9]
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“At the standard false discovery rate (FDR) threshold of 5%, the bioinformatics tool DEPICT19 prioritizes 1,838 genes (Supplementary Table 7), a tenfold increase relative to the DEPICT results from an earlier GWAS of EduYears10.”
From Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals (2018) · cites this paper as [10]
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“In the subsample of our data (N = 726,808) that did not contribute to the earlier study’s analyses, the SNPs replicate at a rate that closely matches theoretical projections derived from our Bayesian framework (Supplementary Figure 3).”
From Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals (2018) · cites this paper as [10]
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“The largest (N = 293,723) GWAS of EA to date identified 74 approximately independent SNPs at genome-wide significance (hereafter, lead SNPs)”
From Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals (2018) · cites this paper as [10]
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“all major conclusions from the largest previous GWAS of EduYears10 continue to hold but are statistically stronger.”
From Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals (2018) · cites this paper as [10]
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“reported that a 10-million-SNP linear predictor (hereafter, polygenic score) had an out-of-sample predictive power of 3.2%10.”
From Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals (2018) · cites this paper as [10]
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“we found a strong and highly significant correlation with major depression 21 ( 𝑟 𝐺 = 0.412, p = 1.40 x 10 -25 )”
From Identification of common genetic risk variants for autism spectrum disorder (2019) · cites this paper as [21]
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Sudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., Downey, P., Elliott, P., Green, J., Landray, M., et al. (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001779 · Cited by 12,728
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Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559
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The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science · doi:10.1126/science.1262110 · Cited by 5,062
Self-citationCommon polygenic variation contributes to risk of schizophrenia and bipolar disorder
The International Schizophrenia Consortium (2009) · Nature · doi:10.1038/nature08185 · Cited by 4,821
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Partitioning heritability by functional annotation using genome-wide association summary statistics
ReproGen Consortium, Finucane, H. K., Schizophrenia Working Group of the Psychiatric Genomics Consortium, The RACI Consortium, Bulik-Sullivan, B., Gusev, A., Trynka, G., Reshef, Y., Loh, P.-R., Anttila, V., et al. (2015) · Nature Genetics · doi:10.1038/ng.3404 · Cited by 2,604
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Rietveld, C. A., Medland, S. E., Derringer, J., Yang, J., Esko, T., Martin, N. W., Westra, H.-J., Shakhbazov, K., Abdellaoui, A., Agrawal, A., et al. (2013) · Science · doi:10.1126/science.1235488 · Cited by 827
Self-citationBiological interpretation of genome-wide association studies using predicted gene functions
Pers, T. H., Karjalainen, J. M., Chan, Y., Westra, H.-J., Wood, A. R., Yang, J., Lui, J. C., Vedantam, S., Gustafsson, S., Esko, T., et al. (2015) · Nature Communications · doi:10.1038/ncomms6890 · Cited by 787
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Yang, J., Weedon, M. N., Purcell, S., Lettre, G., Estrada, K., Willer, C. J., Smith, A. V., Ingelsson, E., O’Connell, J. R., Mangino, M., et al. (2011) · European Journal of Human Genetics · doi:10.1038/ejhg.2011.39 · Cited by 571
Self-citationVariation in the Heritability of Educational Attainment: An International Meta-Analysis
Branigan, A. R., McCallum, K. J., & Freese, J. (2013) · Social Forces · doi:10.1093/sf/sot076 · Cited by 360
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Huin, V., Buée, L., Behal, H., Labreuche, J., Sablonnière, B., & Dhaenens, C. (2017) · Scientific Reports · doi:10.1038/s41598-017-12955-7 · Cited by 43
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Walters, G. B., Gústafsson, Ó., Sveinbjörnsson, G., Eiriksdottir, V. K., Agustsdottir, A. B., Jónsdóttir, G. A., Steinberg, S., Gunnarsson, A. F., Magnusson, M. I., Unnsteinsdóttir, U., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05595-6 · Cited by 43
Building causal knowledge in behavior genetics
Madole, J. W., & Harden, K. P. (2022) · Behavioral and Brain Sciences · doi:10.1017/s0140525x22000681 · Cited by 43
Hill, W. D., Davies, G., Harris, S. E., Hagenaars, S. P., The neuroCHARGE Cognitive Working group, Davies, G., Deary, I. J., Debette, S., Verbaas, C. I., Bressler, J., et al. (2016) · Translational Psychiatry · doi:10.1038/tp.2016.246 · Cited by 43
Self-citationBretherick, A. D., Canela-Xandri, O., Joshi, P. K., Clark, D. W., Rawlik, K., Boutin, T. S., Zeng, Y., Amador, C., Navarro, P., Rudan, I., et al. (2020) · PLOS Genetics · doi:10.1371/journal.pgen.1008785 · Cited by 42
Self-citationLinking Brain Age Gap to Mental and Physical Health in the Berlin Aging Study II
Jawinski, P., Markett, S. A., Drewelies, J., Düzel, S., Demuth, I., Steinhagen‐Thiessen, E., Wagner, G. G., Gerstorf, D., Lindenberger, U., Gaser, C., et al. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.791222 · Cited by 43
Self-citationSchmitz, L., & Conley, D. (2017) · Economics of Education Review · doi:10.1016/j.econedurev.2017.10.001 · Cited by 42
Self-citationGenetic Risks for Chronic Conditions: Implications for Long-term Wellbeing
Wehby, G. L., Domingue, B. W., & Wolinsky, F. D. (2017) · The Journals of Gerontology Series A · doi:10.1093/gerona/glx154 · Cited by 42
Whitton, L., Apostolova, G., Rieder, D., Dechant, G., Rea, S., Donohoe, G. J., & Morris, D. W. (2018) · PLoS Genetics · doi:10.1371/journal.pgen.1007515 · Cited by 42
Yang, Q., Millard, L. A. C., & Smith, G. D. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyz250 · Cited by 42
Evaluating the informativeness of deep learning annotations for human complex diseases
Dey, K. K., van de Geijn, B., Kim, S. S., Hormozdiari, F., Kelley, D. R., & Price, A. L. (2020) · Nature Communications · doi:10.1038/s41467-020-18515-4 · Cited by 42
Jin, T., Rehani, P. R., Ying, M., Huang, J., Liu, S., Roussos, P., & Wang, D. (2021) · Genome Medicine · doi:10.1186/s13073-021-00908-9 · Cited by 42
Estimating Intergenerational and Assortative Processes in Extended Family Data
Collado, M. D., Ortuño-Ortín, I., & Stuhler, J. (2023) · The Review of Economic Studies · doi:10.1093/restud/rdac060 · Cited by 41
Cohort Profile: The Nijmegen Biomedical Study (NBS)
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Epigenetic aging and perceived psychological stress in old age
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Self-citationDavies, N. M., Dickson, M., Smith, G. D., Windmeijer, F., & van den Berg, G. J. (2023) · International Journal of Epidemiology · doi:10.1093/ije/dyad104 · Cited by 40
Yeung, S. L. A., Li, A. M., He, B., Kwok, K. O., & Schooling, C. M. (2022) · Addiction · doi:10.1111/add.15852 · Cited by 40
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Sias, R. W., Starks, L. T., & Turtle, H. J. (2020) · National Bureau of Economic Research · doi:10.3386/w27638 · Cited by 40
Hegvik, T., Waløen, K., Pandey, S. K., Faraone, S. V., Haavik, J., & Zayats, T. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0540-z · Cited by 39
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Wong, P. C. M., Kang, X., Wong, K. H. Y., So, H., Choy, K. W., & Geng, X. (2020) · Science Advances · doi:10.1126/sciadv.aba5090 · Cited by 39
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Metadata
- Authors
- Okbay, A., Beauchamp, J. P., Fontana, M. A., Lee, J. J., Pers, T. H., Rietveld, C. A., Turley, P., Chen, G.-B., Emilsson, V., Meddens, S. F. W., Oskarsson, S., Pickrell, J. K., Thom, K., Timshel, P., de Vlaming, R., Abdellaoui, A., Ahluwalia, T. S., Bacelis, J., Baumbach, C., Bjornsdottir, G., Brandsma, J. H., Pina Concas, M., Derringer, J., Furlotte, N. A., Galesloot, T. E., Girotto, G., Gupta, R., Hall, L. M., Harris, S. E., Hofer, E., Horikoshi, M., Huffman, J. E., Kaasik, K., Kalafati, I. P., Karlsson, R., Kong, A., Lahti, J., Lee, S. J. V. D., deLeeuw, C., Lind, P. A., Lindgren, K.-O., Liu, T., Mangino, M., Marten, J., Mihailov, E., Miller, M. B., van der Most, P. J., Oldmeadow, C., Payton, A., Pervjakova, N., Peyrot, W. J., Qian, Y., Raitakari, O., Rueedi, R., Salvi, E., Schmidt, B., Schraut, K. E., Shi, J., Smith, A. V., Poot, R. A., St Pourcain, B., Teumer, A., Thorleifsson, G., Verweij, N., Vuckovic, D., Wellmann, J., Westra, H.-J., Yang, J., Zhao, W., Zhu, Z., Alizadeh, B. Z., Amin, N., Bakshi, A., Baumeister, S. E., Biino, G., Bønnelykke, K., Boyle, P. A., Campbell, H., Cappuccio, F. P., Davies, G., De Neve, J.-E., Deloukas, P., Demuth, I., Ding, J., Eibich, P., Eisele, L., Eklund, N., Evans, D. M., Faul, J. D., Feitosa, M. F., Forstner, A. J., Gandin, I., Gunnarsson, B., Halldórsson, B. V., Harris, T. B., Heath, A. C., Hocking, L. J., Holliday, E. G., Homuth, G., Horan, M. A., Hottenga, J.-J., de Jager, P. L., Joshi, P. K., Jugessur, A., Kaakinen, M. A., Kähönen, M., Kanoni, S., Keltigangas-Järvinen, L., Kiemeney, L. A. L. M., Kolcic, I., Koskinen, S., Kraja, A. T., Kroh, M., Kutalik, Z., Latvala, A., Launer, L. J., Lebreton, M. P., Levinson, D. F., Lichtenstein, P., Lichtner, P., Liewald, D. C. M., Cohort Study, L., Loukola, A., Madden, P. A., Mägi, R., Mäki-Opas, T., Marioni, R. E., Marques-Vidal, P., Meddens, G. A., McMahon, G., Meisinger, C., Meitinger, T., Milaneschi, Y., Milani, L., Montgomery, G. W., Myhre, R., Nelson, C. P., Nyholt, D. R., Ollier, W. E. R., Palotie, A., Paternoster, L., Pedersen, N. L., Petrovic, K. E., Porteous, D. J., Räikkönen, K., Ring, S. M., Robino, A., Rostapshova, O., Rudan, I., Rustichini, A., Salomaa, V., Sanders, A. R., Sarin, A.-P., Schmidt, H., Scott, R. J., Smith, B. H., Smith, J. A., Staessen, J. A., Steinhagen-Thiessen, E., Strauch, K., Terracciano, A., Tobin, M. D., Ulivi, S., Vaccargiu, S., Quaye, L., van Rooij, F. J. A., Venturini, C., Vinkhuyzen, A. A. E., Völker, U., Völzke, H., Vonk, J. M., Vozzi, D., Waage, J., Ware, E. B., Willemsen, G., Attia, J. R., Bennett, D. A., Berger, K., Bertram, L., Bisgaard, H., Boomsma, D. I., Borecki, I. B., Bültmann, U., Chabris, C. F., Cucca, F., Cusi, D., Deary, I. J., Dedoussis, G. V., van Duijn, C. M., Eriksson, J. G., Franke, B., Franke, L., Gasparini, P., Gejman, P. V., Gieger, C., Grabe, H.-J., Gratten, J., Groenen, P. J. F., Gudnason, V., van der Harst, P., Hayward, C., Hinds, D. A., Hoffmann, W., Hyppönen, E., Iacono, W. G., Jacobsson, B., Järvelin, M.-R., Jöckel, K.-H., Kaprio, J., Kardia, S. L. R., Lehtimäki, T., Lehrer, S. F., Magnusson, P. K. E., Martin, N. G., McGue, M., Metspalu, A., Pendleton, N., Penninx, B. W. J. H., Perola, M., Pirastu, N., Pirastu, M., Polasek, O., Posthuma, D., Power, C., Province, M. A., Samani, N. J., Schlessinger, D., Schmidt, R., Sørensen, T. I. A., Spector, T. D., Stefansson, K., Thorsteinsdottir, U., Thurik, A. R., Timpson, N. J., Tiemeier, H., Tung, J. Y., Uitterlinden, A. G., Vitart, V., Vollenweider, P., Weir, D. R., Wilson, J. F., Wright, A. F., Conley, D. C., Krueger, R. F., Davey Smith, G., Hofman, A., Laibson, D. I., Medland, S. E., Meyer, M. N., Yang, J., Johannesson, M., Visscher, P. M., Esko, T., Koellinger, P. D., Cesarini, D., & Benjamin, D. J.
- Affiliations
- Erasmus MC (NL)
- Harvard University (US)
- University of Southern California (US)
- University of Minnesota (US)
- Statens Serum Institut (DK)
- The University of Queensland (AU)
- University of Iceland (IS)
- Vrije Universiteit Amsterdam (NL)
- Uppsala University (SE)
- New York Genome Center (US)
- New York University (US)
- Broad Institute (US)
- University of Copenhagen (DK)
- Helmholtz Munich (DE)
- University of Illinois Urbana-Champaign (US)
- 23andMe (United States) (US)
- Radboud University Medical Center (NL)
- University of Trieste (IT)
- University of Helsinki (FI)
- University of Leicester (GB)
- University of Edinburgh (GB)
- Medical University of Graz (AT)
- Centre for Human Genetics (GB)
- Institute of Genetics and Cancer (GB)
- Harokopio University of Athens (GR)
- Karolinska Institutet (SE)
- deCODE Genetics (Iceland) (IS)
- QIMR Berghofer Medical Research Institute (AU)
- Max Planck Institute for Human Development (DE)
- King's College London (GB)
- University of Tartu (EE)
- Hunter Medical Research Institute (AU)
- University of Manchester (GB)
- Finnish Institute for Health and Welfare (FI)
- GGZ inGeest (NL)
- National Institute on Aging (US)
- University of Turku (FI)
- SIB Swiss Institute of Bioinformatics (CH)
- University of Milan (IT)
- Institut für Medizinische Informatik, Biometrie und Epidemiologie (DE)
- National Cancer Institute (US)
- Universitätsmedizin Greifswald (DE)
- University Medical Center Groningen (NL)
- University of Münster (DE)
- Rush University Medical Center (US)
- University of Michigan (US)
- National Research Council (IT)
- University of Warwick (GB)
- Queen Mary University of London (GB)
- Charité – Universitätsmedizin Berlin (DE)
- German Institute for Economic Research (DE)
- Translational Research Institute (AU)
- Washington University in St. Louis (US)
- University of Bonn (DE)
- Reykjavík University (IS)
- National Institutes of Health (US)
- University of Aberdeen (GB)
- Norwegian Institute of Public Health (NO)
- Imperial College London (GB)
- Tampere University (FI)
- University of Amsterdam (NL)
- Stanford University (US)
- Centre Hospitalier Universitaire Vaudois (CH)
- Premiere (BW)
- University of Bristol (GB)
- Queensland University of Technology (AU)
- IRCCS Materno Infantile Burlo Garofolo (IT)
- Endeavor Health (US)
- University of Graz (AT)
- University of Dundee (GB)
- Maastricht University (NL)
- Florida State University (US)
- Institute of Genetic and Biomedical Research (IT)
- Social Impact (United States) (US)
- Institute for Integrative and Experimental Genomics (DE)
- Union College (US)
- Donders Centre for Neuroscience (NL)
- Erasmus University Rotterdam (NL)
- University of South Australia (AU)
- Oulu University Hospital (FI)
- Queen's University (CA)
- University College London (GB)
- Union Graduate College (US)
- Stockholm School of Economics (SE)
- Corresponding author
- Visscher, Peter M.
- Koellinger, Philipp D.
- Cesarini, David
- Benjamin, Daniel J.
- ORCID
- Okbay, Aysu
- Beauchamp, Jonathan P.
- Lee, James J.
- Pers, Tune H.
- Rietveld, Cornelius A.
- Turley, Patrick
- Chen, Guo-Bo
- Emilsson, Valur
- Meddens, S. Fleur W.
- Oskarsson, Sven
- Timshel, Pascal
- Abdellaoui, Abdel
- Ahluwalia, Tarunveer S.
- Baumbach, Clemens
- Derringer, Jaime
- Galesloot, Tessel E.
- Girotto, Giorgia
- Gupta, Richa
- Harris, Sarah E.
- Hofer, Edith
- Horikoshi, Momoko
- Huffman, Jennifer E.
- Kalafati, Ioanna P.
- Karlsson, Robert
- Kong, Augustine
- Lahti, Jari
- Lee, Sven J. van der
- Lind, Penelope A.
- Lindgren, Karl-Oskar
- Mangino, Massimo
- Marten, Jonathan
- Oldmeadow, Christopher
- Payton, Antony
- Peyrot, Wouter J.
- Raitakari, Olli
- Rueedi, Rico
- Salvi, Erika
- Schmidt, Börge
- Shi, Jianxin
- Smith, Albert V.
- Poot, Raymond A.
- Teumer, Alexander
- Verweij, Niek
- Vuckovic, Dragana
- Westra, Harm-Jan
- Zhu, Zhihong
- Alizadeh, Behrooz Z.
- Amin, Najaf
- Bakshi, Andrew
- Baumeister, Sebastian E.
- Biino, Ginevra
- Bønnelykke, Klaus
- Boyle, Patricia A.
- Cappuccio, Francesco P.
- Deloukas, Panos
- Demuth, Ilja
- Ding, Jun
- Eibich, Peter
- Evans, David M.
- Faul, Jessica D.
- Feitosa, Mary F.
- Forstner, Andreas J.
- Gandin, Ilaria
- Halldórsson, Bjarni V.
- Harris, Tamara B.
- Heath, Andrew C.
- Hocking, Lynne J.
- Homuth, Georg
- Hottenga, Jouke-Jan
- Joshi, Peter K.
- Jugessur, Astanand
- Kaakinen, Marika A.
- Kähönen, Mika
- Kanoni, Stavroula
- Kiemeney, Lambertus A. L. M.
- Kroh, Martin
- Latvala, Antti
- Launer, Lenore J.
- Lebreton, Maël P.
- Levinson, Douglas F.
- Lichtenstein, Paul
- Lichtner, Peter
- Liewald, David C. M.
- Loukola, Anu
- Madden, Pamela A.
- Mägi, Reedik
- Mäki-Opas, Tomi
- Marioni, Riccardo E.
- Marques-Vidal, Pedro
- Meisinger, Christa
- Meitinger, Thomas
- Milani, Lili
- Montgomery, Grant W.
- Myhre, Ronny
- Nelson, Christopher P.
- Nyholt, Dale R.
- Ollier, William E. R.
- Palotie, Aarno
- Paternoster, Lavinia
- Pedersen, Nancy L.
- Räikkönen, Katri
- Ring, Susan M.
- Robino, Antonietta
- Rudan, Igor
- Rustichini, Aldo
- Salomaa, Veikko
- Sanders, Alan R.
- Sarin, Antti-Pekka
- Scott, Rodney J.
- Smith, Blair H.
- Smith, Jennifer A.
- Staessen, Jan A.
- Strauch, Konstantin
- Terracciano, Antonio
- Tobin, Martin D.
- Ulivi, Sheila
- Vaccargiu, Simona
- Venturini, Cristina
- Vinkhuyzen, Anna A. E.
- Völker, Uwe
- Vonk, Judith M.
- Vozzi, Diego
- Waage, Johannes
- Ware, Erin B.
- Willemsen, Gonneke
- Attia, John R.
- Bennett, David A.
- Bertram, Lars
- Bisgaard, Hans
- Boomsma, Dorret I.
- Borecki, Ingrid B.
- Bültmann, Ute
- Chabris, Christopher F.
- Cucca, Francesco
- Deary, Ian J.
- Dedoussis, George V.
- Eriksson, Johan G.
- Franke, Barbara
- Franke, Lude
- Gasparini, Paolo
- Gieger, Christian
- Gratten, Jacob
- Groenen, Patrick J. F.
- Gudnason, Vilmundur
- Hayward, Caroline
- Hinds, David A.
- Hyppönen, Elina
- Iacono, William G.
- Jacobsson, Bo
- Järvelin, Marjo-Riitta
- Kaprio, Jaakko
- Lehtimäki, Terho
- Magnusson, Patrik K. E.
- Martin, Nicholas G.
- McGue, Matt
- Metspalu, Andres
- Pendleton, Neil
- Penninx, Brenda W. J. H.
- Pirastu, Nicola
- Power, Christine
- Province, Michael A.
- Samani, Nilesh J.
- Schmidt, Reinhold
- Spector, Tim D.
- Timpson, Nicholas J.
- Tiemeier, Henning
- Uitterlinden, André G.
- Weir, David R.
- Wilson, James F.
- Conley, Dalton C.
- Krueger, Robert F.
- Laibson, David I.
- Medland, Sarah E.
- Yang, Jian
- Johannesson, Magnus
- Visscher, Peter M.
- Esko, Tõnu
- Koellinger, Philipp D.
- Cesarini, David
- Benjamin, Daniel J.
- Venue
- Nature
- Published
- 2016-05-11
- Volume
- 533
- Issue
- 7604
- Pages
- 539-542
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4883595
- OpenAlex
- W2346626662
- Cited by
- 1,297
- References
- 16
- Citations by year
- 2026: 44 · 2025: 81 · 2024: 88 · 2023: 110 · 2022: 119 · 2021: 130 · 2020: 190 · 2019: 170 · 2018: 176 · 2017: 140 · 2016: 48
- FWCI
- 143.64
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature (publishedVersion, other-oa)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, other-oa)
- Pure Amsterdam UMC (publishedVersion, other-oa)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, other-oa)
- VU Research Portal (publishedVersion)
- e-space (Manchester Metropolitan University) (acceptedVersion, other-oa)
- Warwick Research Archive Portal (University of Warwick) (acceptedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- UniSA Research Outputs Repository (University of South Australia) (acceptedVersion)
- Discovery Research Portal (University of Dundee) (acceptedVersion, other-oa)
- Leicester Research Archive (University of Leicester) (acceptedVersion, other-oa)
- Bristol Research (University of Bristol) (acceptedVersion, other-oa)
- SERVAL (Université de Lausanne) (acceptedVersion, other-oa)
- HAL (submittedVersion, other-oa)
- Max Planck Digital Library (submittedVersion, other-oa)
- IRIS (submittedVersion, other-oa)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
- Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
- ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/) (submittedVersion)
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- Lirias (submittedVersion)
- mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
- Site cant be reached (submittedVersion)
- PUB – Publications at Bielefeld University (Bielefeld University) (submittedVersion)
- Publikationen an der Universität Bielefeld (Universität Bielefeld) (submittedVersion)
- Research Explorer (The University of Manchester) (submittedVersion, other-oa)
- Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
- Queen Mary Research Online (Queen Mary University of London) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- Spiral (Imperial College London) (submittedVersion)
- OPUS (Augsburg University) (submittedVersion)
- NOVA (University of Newcastle Australia) (submittedVersion)
- STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- WOS
- ERIM Top-Core Articles
- Funders
- Brigham and Women's Hospital
- Massachusetts General Hospital
- Florida State University
- University of Minnesota
- Helsingin Yliopisto
- New York University Shanghai
- University of Dundee
- Queen Mary University of London
- NorthShore University HealthSystem
- QIMR Berghofer Medical Research Institute
- Broad Institute
- York University
- National Institute for Health and Care Research (NF-SI-0514-10027)
- University of Leicester
- Imperial College London
- University of Oxford
- University of Manchester
- University of Aberdeen
- Hunter Medical Research Institute
- Rijksuniversiteit Groningen
- University of South Australia
- Universiteit van Amsterdam
- Erasmus Universiteit Rotterdam
- Universiteit Maastricht
- Erasmus Medisch Centrum
- Queen's University
- Lundbeckfonden (R163-2013-16235, R190 2014-3904)
- King Abdulaziz University (21589)
- Universität zu Lübeck
- Vetenskapsrådet (421-2013-1061)
- Tampereen Yliopisto
- Consiglio Nazionale delle Ricerche
- Universitair Medisch Centrum Groningen
- Oulun Yliopisto
- Centre Hospitalier Universitaire Vaudois
- Rheinische Friedrich-Wilhelms-Universität Bonn
- Tays
- Terveyden ja hyvinvoinnin laitos
- Háskólinn í Reykjavík
- National Institutes of Health (AG042568)
- School of Medicine, New York University
- Stanley Center for Psychiatric Research, Broad Institute
- Medical Research Council (MR/N01104X/1, MR/J012165/1, MR/K026992/1)
- Biotechnology and Biological Sciences Research Council (BB/F022441/1)
- Economic and Social Research Council (ES/M010341/1)
- Helmholtz Zentrum München
- Netherlands Heart Institute
- School of Public Health, Imperial College London
- Amsterdam Brain and Cognition
- Biocenter, University of Oulu
- Diamantina Institute, University of Queensland
- Norwegian Institute of Public Health
- National Institute on Aging (R01AG017917, R01AG015819, P30AG010161, T32AG000186, AG005842, RF1AG015819, R01AG042568, P01AG005842, P30AG012810, U01AG009740)
- National Institute on Drug Abuse (R01DA036216, R37DA005147)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (P2CHD047879)
- Institute of Genetics
- H2020 European Research Council (647648)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- educational attainment, genetic variants, years of schooling, candidate genes, neural development, genetic architecture, cognitive characteristics, neuropsychiatric disorders
- MeSH terms
- Alzheimer Disease, Bipolar Disorder, Brain, Cognition, Educational Status, Fetus, Gene Expression Regulation, United Kingdom, Humans, Schizophrenia, Computational Biology, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Molecular Sequence Annotation, Gene-Environment Interaction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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