Genome-wide association study results for educational attainment aid in identifying genetic heterogeneity of schizophrenia

V. Bansal, M. Mitjans, C. A.P. Burik, R. K. Linnér, A. Okbay, C. A. Rietveld, M. Begemann, S. Bonn, S. Ripke, R. de Vlaming, M. G. Nivard, H. Ehrenreich, P. D. Koellinger*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


Higher educational attainment (EA) is negatively associated with schizophrenia (SZ). However, recent studies found a positive genetic correlation between EA and SZ. We investigate possible causes of this counterintuitive finding using genome-wide association study results for EA and SZ (N = 443,581) and a replication cohort (1169 controls; 1067 cases) with deeply phenotyped SZ patients. We find strong genetic dependence between EA and SZ that cannot be explained by chance, linkage disequilibrium, or assortative mating. Instead, several genes seem to have pleiotropic effects on EA and SZ, but without a clear pattern of sign concordance. Using EA as a proxy phenotype, we isolate FOXO6 and SLITRK1 as novel candidate genes for SZ. Our results reveal that current SZ diagnoses aggregate over at least two disease subtypes: one part resembles high intelligence and bipolar disorder (BIP), while the other part is a cognitive disorder that is independent of BIP.

Original languageEnglish
Article number3078
Pages (from-to)1-12
Number of pages12
JournalNature Communications
Issue number1
Publication statusPublished - 6 Aug 2018


This research was carried out under the auspices of the Social Science Genetic Association Consortium (SSGAC), including use of the UK Biobank Resource (application reference number 11425). We thank all research consortia that provide access to GWAS summary statistics in the public domain. Specifically, we acknowledge data access from the Psychiatric Genomics Consortium (PGC), the Genetic Investigation of ANthropometric Traits Consortium (GIANT), the International Inflammatory Bowel Disease Genetics Consortium (IIBDGC), the International Genomics of Alzheimer’s Project (IGAP), the CARDIoGRAMplusC4D Consortium, the Reproductive Genetics Consortium (ReproGen), the Tobacco and Genetics Consortium (TAG), the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC), the ENIGMA Consortium and the Childhood Intelligence Consortium (CHIC). We would like to thank the research participants and employees of 23andMe for making this work possible as well as Joyce Y. Tung, Nicholas A. Furlotte and David A. Hinds from the 23andMe research team. This study was supported by funding from an ERC Consolidator Grant (647648 EdGe, Philipp D. Koellinger), the Max Planck Society, the Max Planck Förderstiftung, the DFG (CNMPB), EXTRABRAIN EU-FP7, the Niedersachsen-Research Network on Neu-roinfectiology (N-RENNT) and EU-AIMS. Michel G. Nivard was supported by a Royal Netherlands Academy of Science Professor Award to Dorret I. Boomsma (PAH/6635). Additional acknowledgements are provided in the Supplementary Note 12.

FundersFunder number
Max Planck Förderstiftung
Royal Netherlands Academy of SciencePAH/6635
Horizon 2020 Framework Programme647648
European Research Council
Deutsche Forschungsgemeinschaft


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