Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

The association between lower educational attainment and depression owing to shared genetic effects? Results in ~25 000 subjects

Subjects

Abstract

An association between lower educational attainment (EA) and an increased risk for depression has been confirmed in various western countries. This study examines whether pleiotropic genetic effects contribute to this association. Therefore, data were analyzed from a total of 9662 major depressive disorder (MDD) cases and 14 949 controls (with no lifetime MDD diagnosis) from the Psychiatric Genomics Consortium with additional Dutch and Estonian data. The association of EA and MDD was assessed with logistic regression in 15 138 individuals indicating a significantly negative association in our sample with an odds ratio for MDD 0.78 (0.75–0.82) per standard deviation increase in EA. With data of 884 105 autosomal common single-nucleotide polymorphisms (SNPs), three methods were applied to test for pleiotropy between MDD and EA: (i) genetic profile risk scores (GPRS) derived from training data for EA (independent meta-analysis on ~120 000 subjects) and MDD (using a 10-fold leave-one-out procedure in the current sample), (ii) bivariate genomic-relationship-matrix restricted maximum likelihood (GREML) and (iii) SNP effect concordance analysis (SECA). With these methods, we found (i) that the EA-GPRS did not predict MDD status, and MDD-GPRS did not predict EA, (ii) a weak negative genetic correlation with bivariate GREML analyses, but this correlation was not consistently significant, (iii) no evidence for concordance of MDD and EA SNP effects with SECA analysis. To conclude, our study confirms an association of lower EA and MDD risk, but this association was not because of measurable pleiotropic genetic effects, which suggests that environmental factors could be involved, for example, socioeconomic status.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1

Similar content being viewed by others

References

  1. Lorant V, Deliège D, Eaton W, Robert A, Ansseau M . Socioeconomic inequalities in depression: a meta-analysis. Am J Epidemiol 2003; 157: 98–112.

    Article  CAS  PubMed  Google Scholar 

  2. Bromet E, Andrade LH, Hwang I, Sampson Na, Alonso J, de Girolamo G, et al. Cross-national epidemiology of DSM-IV major depressive episode. BMC Med 2011; 9: 90–106.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Andrade L, Caraveo-Anduaga JJ, Berglund P, Bijl RV, De Graaf R, Vollebergh W, et al. The epidemiology of major depressive episodes: results from the International Consortium of Psychiatric Epidemiology (ICPE) Surveys. Int J Methods Psychiatr Res 2003; 12: 3–21.

    Article  PubMed  Google Scholar 

  4. de Graaf R, ten Have M, van Gool C, van Dorsselaer S . Prevalence of mental disorders and trends from 1996 to 2009. Results from the Netherlands Mental Health Survey and Incidence Study-2. Soc Psychiatry Psychiatr Epidemiol 2012; 47: 203–213.

    Article  PubMed  Google Scholar 

  5. Mezuk B, Myers JM, Kendler KS . Integrating social science and behavioral genetics: testing the origin of socioeconomic disparities in depression using a genetically informed design. Am J Public Health 2013; 103: S145–S151.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Turner RJ, Lloyd DA . The stress process and the social distribution of depression. J Health Soc Behav 1999; 40: 374–404.

    Article  CAS  PubMed  Google Scholar 

  7. Rietveld CA, Medland SE, Derringer J, Yang J, Esko T, Martin NW, et al. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science 2013; 340: 1467–1471.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Dongen van J, Slagboom PE, Draisma HHM, Martin NG, Boomsma DI . The continuing value of twin studies in the omics era. Nat Rev Genet 2012; 13: 640–653.

    Article  Google Scholar 

  9. Demirkan A, BWJH Penninx, Hek K, Wray NR, Amin N, Aulchenko YS, et al. Genetic risk profiles for depression and anxiety in adult and elderly cohorts. Mol Psychiatry 2011; 16: 773–783.

    Article  CAS  PubMed  Google Scholar 

  10. Lubke GH, Hottenga JJ, Walters R, Laurin C, De Geus EJC, Willemsen G, et al. Estimating the Genetic variance of major depressive disorder due to all single nucleotide polymorphisms. Biol Psychiatry 2012; 72: 707–709.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. López-León S, Choy W, Aulchenko Y . Genetic factors influence the clustering of depression among individuals with lower socioeconomic status. PLoS One 2009; 4: 1–5.

    Article  Google Scholar 

  12. Boardman JD, Domingue BW, Daw J . What can genes tell us about the relationship between education and health? Soc Sci Med 2014; 127: 171–180.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Ripke S, Wray NR, Lewis CM, Hamilton SP, Weissman MM, Breen G, et al. A mega-analysis of genome-wide association studies for major depressive disorder. Mol Psychiatry 2013; 18: 497–511.

    Article  CAS  PubMed  Google Scholar 

  14. Rietschel M, Mattheisen M, Frank J, Treutlein J, Degenhardt F, Breuer R, et al. Genome-wide association-, replication-, and neuroimaging study implicates HOMER1 in the etiology of major depression. Biol Psychiatry 2010; 68: 578–585.

    Article  CAS  PubMed  Google Scholar 

  15. Sullivan PF, De Geus EJC, Willemsen G, James MR, Smit JH, Zandbelt T, et al. Genome-wide association for major depressive disorder: a possible role for the presynaptic protein piccolo. Mol Psychiatry 2009; 14: 359–375.

    Article  CAS  PubMed  Google Scholar 

  16. Shi J, Potash JB, Knowles JA, Weissman MM, Coryell W, Scheftner WA, et al. Genome-wide association study of recurrent early-onset major depressive disorder. Mol Psychiatry 2011; 16: 193–201.

    Article  CAS  PubMed  Google Scholar 

  17. Muglia P, Tozzi F, Galwey NW, Francks C, Upmanyu R, Kong XQ, et al. Genome-wide association study of recurrent major depressive disorder in two European case–control cohorts. Mol Psychiatry 2010; 15: 589–601.

    Article  CAS  PubMed  Google Scholar 

  18. Ising M, Lucae S, Binder EB, Bettecken T, Uhr M, Ripke S, et al. A genomewide association study points to multiple loci that predict antidepressant drug treatment outcome in depression. Arch Gen Psychiatry 2009; 66: 966–975.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Wray NR, Pergadia ML, Blackwood DHR, Penninx BWJH, Gordon SD, Nyholt DR, et al. Genome-wide association study of major depressive disorder: new results, meta-analysis, and lessons learned. Mol Psychiatry 2012; 17: 36–48.

    Article  CAS  PubMed  Google Scholar 

  20. Lewis CM, Ng MY, Butler AW, Cohen-Woods S, Uher R, Pirlo K, et al. Genome-wide association study of major recurrent depression in the U.K. population. Am J Psychiatry 2010; 167: 949–957.

    Article  PubMed  Google Scholar 

  21. Shyn SI, Shi J, Kraft JB, Potash JB, Knowles Ja, Weissman MM, et al. Novel loci for major depression identified by genome-wide association study of Sequenced Treatment Alternatives to Relieve Depression and meta-analysis of three studies. Mol Psychiatry 2011; 16: 202–215.

    Article  CAS  PubMed  Google Scholar 

  22. Penninx BWJH Beekman ATF, Smit JH, Zitman FG, Nolen WA, Spinhoven P, et al. The Netherlands Study of Depression and Anxiety (NESDA): rationale, objectives and methods. Int J Methods Psychiatr Res 2008; 17: 121–140.

    Article  Google Scholar 

  23. Boomsma DI, de Geus EJC, Vink JM, Stubbe JH, Distel Ma, Hottenga J-J, et al. Netherlands Twin Register: from twins to twin families. Twin Res Hum Genet 2006; 9: 849–857.

    PubMed  Google Scholar 

  24. Leitsalu L, Haller T, Esko T, Tammesoo M-L, Alavere H, Snieder H, et al. Cohort Profile: Estonian Biobank of the Estonian Genome Center, University of Tartu. Int J Epidemiol 2014 E-pub ahead of print: 1–11..

  25. Boomsma D, Beem A, van den Berg M, Dolan C, Koopmans J, Vink J, et al. Netherlands twin family study of anxious depression (NETSAD). Twin Res 2012; 3: 323–334.

    Article  Google Scholar 

  26. Altshuler DM, Gibbs RA, Peltonen L, Dermitzakis E, Schaffner SF, Yu F, et al. Integrating common and rare genetic variation in diverse human populations. Nature 2010; 467: 52–58.

    Article  CAS  PubMed  Google Scholar 

  27. Yang J, Lee SH, Goddard ME, Visscher PM . GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet 2011; 88: 76–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Purcell SM, Wray NR, Stone JL, Visscher PM, O’Donovan MC, Sullivan PF, et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 2009; 460: 748–752.

    CAS  PubMed  Google Scholar 

  29. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007; 81: 559–575.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Lee SH, Goddard ME, Wray NR, Visscher PM . A better coefficient of determination for genetic profile analysis. Genet Epidemiol 2012; 36: 214–224.

    Article  PubMed  Google Scholar 

  31. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, et al. Common SNPs explain a large proportion of heritability for human height. Nat Genet 2010; 42: 565–569.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Lee SH, Yang J, Goddard ME, Visscher PM, Wray NR . Estimation of pleiotropy between complex diseases using single-nucleotide polymorphism-derived genomic relationships and restricted maximum likelihood. Bioinformatics 2012; 28: 2540–2542.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Lee SH, Wray NR, Goddard ME, Visscher PM . Estimating missing heritability for disease from genome-wide association studies. Am J Hum Genet 2011; 88: 294–305.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Nyholt DR . SECA: SNP effect concordance analysis using genome-wide association summary results. Bioinformatics 2014; 30: 2086–2088.

    Article  CAS  PubMed  Google Scholar 

  35. Dudbridge F . Power and predictive accuracy of polygenic risk scores. PLoS Genet 2013; 9: e1003348.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Pampel FC, Krueger PM, Denney JT . Socioeconomic disparities in health behaviors. Annu Rev Sociol 2010; 36: 349–370.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Cutler DM, Lleras-Muney A . Understanding differences in health behaviors by education. J Health Econ 2010; 29: 1–28.

    Article  PubMed  Google Scholar 

  38. Fletcher JM, Frisvold DE . Higher education and health investments: does more schooling affect preventive health care use? J Hum Cap 2009; 3: 144–176.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Johnston DW, Lordan G, Shields MA, Suziedelyte A . Education and health knowledge: evidence from UK compulsory schooling reform. Soc Sci Med 2015; 127: 92–100.

    Article  PubMed  Google Scholar 

  40. Lantz PM, House JS, Mero RP, Williams DR . Stress, life events, and socioeconomic disparities in health: results from the Americans’ Changing Lives Study. J Health Soc Behav 2005; 46: 274–288.

    Article  PubMed  Google Scholar 

  41. Lee SH, Ripke S, Neale BM, Faraone SV, Purcell SM, Perlis RH, et al. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat Genet 2013; 45: 984–994.

    Article  CAS  PubMed  Google Scholar 

  42. Cross-Disorder Group of the Psychiatric Genomics Consortium. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet 2013; 381: 1371–1379.

    Article  PubMed Central  Google Scholar 

Download references

Acknowledgements

NRW and SHL supported by the Australian Research Council (FT0991360 and DE130100614) and the National Health and Medical Research Council (613608, 1011506 and 1047956). The PGC is supported by National Institute of Mental Health (NIMH) Grant U01 MH085520. Statistical analyses were carried out on the Genetic Cluster Computer (see Web Resources), which is financially supported by the Netherlands Scientific Organization. The Bonn/Mannheim (BoMa) GWAS was supported by the German Federal Ministry of Education and Research, within the context of the National Genome Research Network 2 (NGFN2), the National Genome Research Network plus (NGFNplus) and the Integrated Genome Research Network (IG) MooDS (Grant 01GS08144 to S Cichon and MMN, and Grant 01GS08147 to MR). The work at deCODE was funded by European Union Grants LSHM-CT-2006-037761 (Project SGENE), PIAP-GA-2008-218251 (Project PsychGene) and HEALTH-F2-2009-223423 (Project PsychCNVs). GenPod was funded by the Medical Research Council (UK) and supported by the Mental Health Research Network. Genotyping of the GenPod sample was funded by the Innovative Medicines Initiative Joint Undertaking under Grant Agreement number 115008 (NEWMEDS). The GenRED GWAS project was supported by NIMH R01 Grants MH061686 (to DFL), MH059542 (to WHC), MH075131 (to WBL), MH059552 (to JBP), MH059541 (to WAS) and MH060912 (to MMW). We acknowledge the contributions of Dr George S Zubenko and Dr Wendy N Zubenko, Department of Psychiatry, University of Pittsburgh School of Medicine, to the GenRED I project. The NIMH Cell Repository at Rutgers University and the NIMH Center for Collaborative Genetic Studies on Mental Disorders made essential contributions to this project. Genotyping was carried out by the Broad Institute Center for Genotyping and Analysis with support from Grant U54 RR020278 (which partially subsidized the genotyping of the GenRED cases). Collection and quality control analyses of the control data set were supported by grants from NIMH and the National Alliance for Research on Schizophrenia and Depression. We are grateful to Knowledge Networks (Menlo Park, CA, USA) for assistance in collecting the control data set. We express our profound appreciation to the families who participated in this project, and to the many clinicians who facilitated the referral of participants to the study. The Depression Genes and Networks ARRA grant was funded by RC2MH089916. Funding for the Harvard i2b2 sample was provided by a subcontract to RH Perlis and JW Smoller as part of the i2b2 Center (Informatics for Integrating Biology and the Bedside), an NIH-funded National Center for Biomedical Computing based at Partners HealthCare System (U54LM008748, PI: IS Kohane), and by an NIMH Grant (to RH Perlis; MH086026). Max Planck Institute of Psychiatry MARS study was supported by the BMBF Program Molecular Diagnostics: Validation of Biomarkers for Diagnosis and Outcome in Major Depression (01ES0811). Genotyping was supported by the Bavarian Ministry of Commerce, and the Federal Ministry of Education and Research (BMBF) in the framework of the National Genome Research Network (NGFN2 and NGFN-Plus, FKZ 01GS0481 and 01GS08145). The Netherlands Study of Depression and Anxiety (NESDA) and the Netherlands Twin Register (NTR) contributed to GAIN-MDD and to MDD2000. This study was funded by: the Netherlands Organization for Scientific Research (MagW/ZonMW Grants 904-61-090, 985-10-002, 904-61-193, 480-04-004, 400-05-717, 912-100-20; Spinozapremie 56-464-14192; Geestkracht program Grant 10-000-1002); the Center for Medical Systems Biology (NWO Genomics), Biobanking and Biomolecular Resources Research Infrastructure, VU University's Institutes for Health and Care Research and Neuroscience Campus Amsterdam, NBIC/BioAssist/RK (2008.024); the European Science Foundation (EU/QLRT-2001-01254); the European Community's Seventh Framework Program (FP7/2007-2013); ENGAGE (HEALTH-F4-2007-201413); and the European Science Council (ERC, 230374). Genotyping was funded, in part, by the Genetic Association Information Network (GAIN) of the Foundation for the US National Institutes of Health, and analysis was supported by grants from GAIN and the NIMH (MH081802). The PsyCoLaus study was supported by grants from the Swiss National Science Foundation (nos. 3200B0-105993, 3200B0-118′308, 33CSC0-122661) and from GlaxoSmithKline (Psychiatry Center of Excellence for Drug Discovery and Genetics Division, Drug Discovery—Verona, R&D). We express our gratitude to the Lausanne inhabitants who volunteered to participate in the PsyCoLaus study. We also thank V Mooser, G Weaber and P Vollenweider who initiated the CoLaus project. Funding for the QIMR samples was provided by the Australian National Health and Medical Research Council (241944, 339462, 389927, 389875, 389891, 389892, 389938, 442915, 442981, 496675, 496739, 552485, 552498, 613602, 613608, 613674, 619667), the Australian Research Council (FT0991360, FT0991022), the FP-5 GenomEUtwin Project (QLG2-CT- 2002-01254) and the US National Institutes of Health (AA07535, AA10248, AA13320, AA13321, AA13326, AA14041, MH66206, DA12854, DA019951), and the Center for Inherited Disease Research (Baltimore, MD, USA). We thank the twins and their families registered at the Australian Twin Registry for their participation in the many studies that have contributed to this research. RADIANT was funded by: a joint grant from the UK Medical Research Council and GlaxoSmithKline (G0701420); the National Institute for Health Research (NIHR) Specialist Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust and the Institute of Psychiatry, King's College London; and the UK Medical Research Council (G0000647). The GENDEP study was funded by a European Commission Framework 6 grant, EC Contract Ref.: LSHB-CT-2003-503428. SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (Grant nos. 01ZZ9603, 01ZZ0103 and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Genome-wide data have been supported by the Federal Ministry of Education and Research (Grant no. 03ZIK012) and a joint grant from Siemens Healthcare, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. The University of Greifswald is a member of the ‘Center of Knowledge Interchange’ program of the Siemens AG. SHIP-LEGEND is funded by the German Research Foundation (DFG: GR 1912/5-1). Genotyping of STAR*D was supported by an NIMH Grant to SP Hamilton (MH072802). STAR*D was funded by the National Institute of Mental Health (Contract No. N01MH90003) to the University of Texas Southwestern Medical Center at Dallas (AJ Rush, principal investigator). The TwinGene study was supported by the Swedish Ministry for Higher Education, the Swedish Research Council (M-2005-1112), GenomEUtwin (EU/QLRT-2001-01254; QLG2-CT-2002-01254), the Swedish Foundation for Strategic Research and the US National Institutes of Health (U01 DK066134). This study makes use of data generated by the Wellcome Trust Case–Control Consortium. A full list of the investigators who contributed to the generation of the data is available from http://www.wtccc.org.uk. Funding for the project was provided by the Wellcome Trust under awards 076113 and 085475. EGCUT received financing from FP7 Grant 313010 and from European Regional Development Fund, road map Grant No. 3.2.0304.11-0312 and grant 'Center of Excellence in Genomics' (EXCEGEN). EGCUT studies were covered also by targeted financing from Estonian Government (IUT24-6, IUT20-60) and CTG grant (SP1GVARENG) from Development Fund of the University of Tartu. We acknowledge EGCUT technical personnel, especially Mr V Soo and S Smit and Mari-Liis Tammesoo. EMB is supported by the National Health and Medical Research Early Career Fellowship Scheme.

Author information

Authors and Affiliations

Authors

Consortia

Corresponding author

Correspondence to W J Peyrot.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Additional information

Members of Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium The following people are not listed as coauthors on this manuscript, but did contribute to the Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium,13 from which individual-level genotype and phenotype data was used. We are grateful for their contribution to the Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium. The views presented in the present paper may not reflect the opinions of the individuals listed below. We thank: CM Lewis, SP Hamilton, MM Weissman, G Breen, DH Blackwood, S Cichon, AC Heath, F Holsboer, PA Madden, P McGuffin, P Muglia, ML Pergadia, D Lin, B Müller-Myhsok, S Steinberg, HJ Grabe, P Lichtenstein, P Magnusson, RH Perlis, M Preisig, JW Smoller, K Stefansson, R Uher, Z Kutalik, KE Tansey, A Teumer, A Viktorin, MR Barnes, T Bettecken, EB Binder, R Breuer, VM Castro, SE Churchill, WH Coryell, N Craddock, IW Craig, D Czamara, F Degenhardt, AE Farmer, M Fava, J Frank, VS Gainer, PJ Gallagher, SD Gordon, S Goryachev, M Gross, M Guipponi, AK Henders, S Herms, IB Hickie, S Hoefels, W Hoogendijk, DV Iosifescu, M Ising, I Jones, L Jones, T Jung-Ying, JA Knowles, IS Kohane, MA Kohli, A Korszun, M Landen, WB Lawson, G Lewis, D Macintyre, W Maier, M Mattheisen, PJ McGrath, A McIntosh, A McLean, CM Middeldorp, L Middleton, GM Montgomery, SN Murphy, M Nauck, WA Nolen, DR Nyholt, M O'Donovan, H Oskarsson, N Pedersen, WA Scheftner, A Schulz, TG Schulze, SI Shyn, E Sigurdsson, SL Slager, JH Smit, H Stefansson, M Steffens, T Thorgeirsson, F Tozzi, J Treutlein, M Uhr, EJ van den Oord, G Van Grootheest, H Völzke, JB Weilburg, G Willemsen, FG Zitman, B Neale, M Daly and PF Sullivan.

Members of Social Science Genetic Association Consortium The following people who are not listed as coauthors on this manuscript contributed to the original GWAS meta-analysis on educational attainment,7 on which the present paper is based. Data access has been granted under section 4 of the Data Sharing Agreement of the Social Science Genetic Association Consortium (SSGAC). The views presented in the present paper may not reflect the opinions of the individuals listed below. We are grateful to the authors of Rietveld et al.7 for providing the meta-analysis data. We thank: Arpana Agrawal, Eva Albrecht, Behrooz Z Alizadeh, Jüri Allik, Najaf Amin, John R Attia, Stefania Bandinelli, John Barnard, François Bastardot, Sebastian E Baumeister, Jonathan Beauchamp, Daniel J Benjamin, Kelly S Benke, David A Bennett, Klaus Berger, Lawrence F Bielak, Laura J Bierut, Jeffrey A Boatman, Patricia A Boyle, Ute Bültmann, Harry Campbell, David Cesarini, Christopher F Chabris, Lynn Cherkas, Mina K Chung, Dalton Conley, Francesco Cucca, George Davey-Smith, Gail Davies, Mariza de Andrade, Philip L. De Jager, Christiaan de Leeuw, Jan-Emmanuel De Neve, Ian J. Deary, George V Dedoussis, Panos Deloukas, Jaime Derringer, Maria Dimitriou, Gudny Eiriksdottir, Niina Eklund, Martin F Elderson, Johan G Eriksson, Daniel S Evans, David M Evans, Jessica D Faul, Rudolf Fehrmann, Luigi Ferrucci, Krista Fischer, Lude Franke, Melissa E Garcia, Christian Gieger, Håkon K Gjessing, Patrick JF Groenen, Henrik Grönberg, Vilmundur Gudnason, Sara Hägg, Per Hall, Jennifer R Harris, Juliette M Harris, Tamara B Harris, Nicholas D Hastie, Caroline Hayward, Andrew C Heath, Dena G Hernandez, Wolgang Hoffmann, Adriaan Hofman, Albert Hofman, Rolf Holle, Elizabeth G Holliday, Christina Holzapfel, William G Iacono, Carla A Ibrahim-Verbaas, Thomas Illig, Erik Ingelsson, Bo Jacobsson, Marjo-Riitta Järvelin, Min A Jhun, Magnus Johannesson, Peter K Joshi, Astanand Jugessur, Marika Kaakinen, Mika Kähönen, Stavroula Kanoni, Jaakkko Kaprio, Sharon LR Kardia, Juha Karjalainen, Robert M Kirkpatrick, Philipp D Koellinger, Ivana Kolcic, Matthew Kowgier, Kati Kristiansson, Robert F Krueger, Zóltan Kutalik, Jari Lahti, David Laibson, Antti Latvala, Lenore J Launer, Debbie A Lawlor, Terho Lethimäki, Jingmei Li, Paul Lichtenstein, Peter K Lichtner, David C Liewald, Peng Lin, Penelope A Lind, Yongmei Liu, Kurt Lohman, Marisa Loitfelder, Pamela A Madden, Patrick KE Magnusson, Tomi E Mäkinen, Pedro Marques Vidal, Nicolas W Martin, Marco Masala, Matt McGue, George McMahon, Osorio Meirelles, Michelle N Meyer, Andreas Mielck, Lili Milani, Michael B Miller, Grant W Montgomery, Sutapa Mukherjee, Ronny Myhre, Marja-Liisa Nuotio, Dale R Nyholt, Christopher J Oldmeadow, Ben A Oostra, Lyle J Palmer, Aarno Palotie, Markus Perola, Katja E Petrovic, Patricia A Peyser, Ozren Polašek, Danielle Posthuma, Martin Preisig, Lydia Quaye, Katri Räikkönen, Olli T Raitakari, Anu Realo, Eva Reinmaa, John P Rice, Susan M Ring, Samuli Ripatti, Fernando Rivadeneira, Thais S Rizzi, Igor Rudan, Aldo Rustichini, Veikko Salomaa, Antti-Pekka Sarin, David Schlessinger, Helena Schmidt, Reinhold Schmidt, Rodney J Scott, Konstantin Shakhbazov, Albert V Smith, Jennifer A Smith, Harold Snieder, Beate St Pourcain, John M Starr, Jae Hoon Sul, Ida Surakka, Rauli Svento, Toshiko Tanaka, Antonio Terracciano, Alexander Teumer, A Roy Thurik, Henning Tiemeier, Nicholas J Timpson, André G Uitterlinden, Matthijs JHM van der Loos, Cornelia M van Duijn, Frank JA van Rooij, David R Van Wagoner, Erkki Vartiainen, Jorma Viikari, Peter M Visscher, Veronique Vitart, Peter K Vollenweider, Henry Völzke, Judith M Vonk, Gérard Waeber, David R Weir, Jürgen Wellmann, Harm-Jan Westra, H-Erich Wichmann, Elisabeth Widen, James F Wilson, Alan F Wright, Jian Yang, Lei Yu, Wei Zhao.

Supplementary Information accompanies the paper on the Molecular Psychiatry website

Supplementary information

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Peyrot, W., Lee, S., Milaneschi, Y. et al. The association between lower educational attainment and depression owing to shared genetic effects? Results in ~25 000 subjects. Mol Psychiatry 20, 735–743 (2015). https://doi.org/10.1038/mp.2015.50

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/mp.2015.50

This article is cited by

Search

Quick links