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1. Improved functional mapping of complex trait heritability with GSA-MiXeR implicates biologically specific gene sets.

Author

Frei O, Hindley G, Shadrin AA, van der Meer D, Akdeniz BC, Hagen E, Cheng W, O'Connell KS, Bahrami S, Parker N, Smeland OB, Holland D, de Leeuw C, Posthuma D, Andreassen OA, and Dale AM

Subjects
Humans, Multifactorial Inheritance genetics, Models, Genetic, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genetic Predisposition to Disease, Chromosome Mapping methods, Computer Simulation, Quantitative Trait, Heritable, Genome-Wide Association Study methods, Schizophrenia genetics, Linkage Disequilibrium
Abstract

While genome-wide association studies are increasingly successful in discovering genomic loci associated with complex human traits and disorders, the biological interpretation of these findings remains challenging. Here we developed the GSA-MiXeR analytical tool for gene set analysis (GSA), which fits a model for the heritability of individual genes, accounting for linkage disequilibrium across variants and allowing the quantification of partitioned heritability and fold enrichment for small gene sets. We validated the method using extensive simulations and sensitivity analyses. When applied to a diverse selection of complex traits and disorders, including schizophrenia, GSA-MiXeR prioritizes gene sets with greater biological specificity compared to standard GSA approaches, implicating voltage-gated calcium channel function and dopaminergic signaling for schizophrenia. Such biologically relevant gene sets, often with fewer than ten genes, are more likely to provide insights into the pathobiology of complex diseases and highlight potential drug targets., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Published
2024
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2. On the interpretation of transcriptome-wide association studies.

Author

de Leeuw C, Werme J, Savage JE, Peyrot WJ, and Posthuma D

Subjects
Chromosome Mapping, Computer Simulation, Data Analysis, Genome-Wide Association Study, Transcriptome genetics
Abstract

Transcriptome-wide association studies (TWAS) aim to detect relationships between gene expression and a phenotype, and are commonly used for secondary analysis of genome-wide association study (GWAS) results. Results from TWAS analyses are often interpreted as indicating a genetic relationship between gene expression and a phenotype, but this interpretation is not consistent with the null hypothesis that is evaluated in the traditional TWAS framework. In this study we provide a mathematical outline of this TWAS framework, and elucidate what interpretations are warranted given the null hypothesis it actually tests. We then use both simulations and real data analysis to assess the implications of misinterpreting TWAS results as indicative of a genetic relationship between gene expression and the phenotype. Our simulation results show considerably inflated type 1 error rates for TWAS when interpreted this way, with 41% of significant TWAS associations detected in the real data analysis found to have insufficient statistical evidence to infer such a relationship. This demonstrates that in current implementations, TWAS cannot reliably be used to investigate genetic relationships between gene expression and a phenotype, but that local genetic correlation analysis can serve as a potential alternative., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 de Leeuw et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Published
2023
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3. Sensitive period-regulating genetic pathways and exposure to adversity shape risk for depression.

Author

Zhu Y, Wang MJ, Crawford KM, Ramírez-Tapia JC, Lussier AA, Davis KA, de Leeuw C, Takesian AE, Hensch TK, Smoller JW, and Dunn EC

Subjects
Brain, Child, Preschool, Humans, Infant, Life Change Events, Risk Factors, Depression genetics, Genome-Wide Association Study
Abstract

Animal and human studies have documented the existence of developmental windows (or sensitive periods) when experience can have lasting effects on brain structure or function, behavior, and disease. Although sensitive periods for depression likely arise through a complex interplay of genes and experience, this possibility has not yet been explored in humans. We examined the effect of genetic pathways regulating sensitive periods, alone and in interaction with common childhood adversities, on depression risk. Guided by a translational approach, we: (1) performed association analyses of three gene sets (60 genes) shown in animal studies to regulate sensitive periods using summary data from a genome-wide association study of depression (n = 807,553); (2) evaluated the developmental expression patterns of these genes using data from BrainSpan (n = 31), a transcriptional atlas of postmortem brain samples; and (3) tested gene-by-development interplay (dGxE) by analyzing the combined effect of common variants in sensitive period genes and time-varying exposure to two types of childhood adversity within a population-based birth cohort (n = 6254). The gene set regulating sensitive period opening associated with increased depression risk. Notably, 6 of the 15 genes in this set showed developmentally regulated gene-level expression. We also identified a statistical interaction between caregiver physical or emotional abuse during ages 1-5 years and genetic risk for depression conferred by the opening genes. Genes involved in regulating sensitive periods are differentially expressed across the life course and may be implicated in depression vulnerability. Our findings about gene-by-development interplay motivate further research in large, more diverse samples to further unravel the complexity of depression etiology through a sensitive period lens., (© 2021. The Author(s), under exclusive licence to American College of Neuropsychopharmacology.)

Published
2022
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4. A global overview of pleiotropy and genetic architecture in complex traits.

Author

Watanabe K, Stringer S, Frei O, Umićević Mirkov M, de Leeuw C, Polderman TJC, van der Sluis S, Andreassen OA, Neale BM, and Posthuma D

Subjects
Humans, Phenotype, Genetic Pleiotropy, Genetics, Population, Genome-Wide Association Study methods, Multifactorial Inheritance genetics, Polymorphism, Single Nucleotide, Quantitative Trait Loci
Abstract

After a decade of genome-wide association studies (GWASs), fundamental questions in human genetics, such as the extent of pleiotropy across the genome and variation in genetic architecture across traits, are still unanswered. The current availability of hundreds of GWASs provides a unique opportunity to address these questions. We systematically analyzed 4,155 publicly available GWASs. For a subset of well-powered GWASs on 558 traits, we provide an extensive overview of pleiotropy and genetic architecture. We show that trait-associated loci cover more than half of the genome, and 90% of these overlap with loci from multiple traits. We find that potential causal variants are enriched in coding and flanking regions, as well as in regulatory elements, and show variation in polygenicity and discoverability of traits. Our results provide insights into how genetic variation contributes to trait variation. All GWAS results can be queried and visualized at the GWAS ATLAS resource ( https://atlas.ctglab.nl ).

Published
2019
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5. Genome-wide association analysis identifies 13 new risk loci for schizophrenia.

Author

Ripke S, O'Dushlaine C, Chambert K, Moran JL, Kähler AK, Akterin S, Bergen SE, Collins AL, Crowley JJ, Fromer M, Kim Y, Lee SH, Magnusson PK, Sanchez N, Stahl EA, Williams S, Wray NR, Xia K, Bettella F, Borglum AD, Bulik-Sullivan BK, Cormican P, Craddock N, de Leeuw C, Durmishi N, Gill M, Golimbet V, Hamshere ML, Holmans P, Hougaard DM, Kendler KS, Lin K, Morris DW, Mors O, Mortensen PB, Neale BM, O'Neill FA, Owen MJ, Milovancevic MP, Posthuma D, Powell J, Richards AL, Riley BP, Ruderfer D, Rujescu D, Sigurdsson E, Silagadze T, Smit AB, Stefansson H, Steinberg S, Suvisaari J, Tosato S, Verhage M, Walters JT, Levinson DF, Gejman PV, Kendler KS, Laurent C, Mowry BJ, O'Donovan MC, Owen MJ, Pulver AE, Riley BP, Schwab SG, Wildenauer DB, Dudbridge F, Holmans P, Shi J, Albus M, Alexander M, Campion D, Cohen D, Dikeos D, Duan J, Eichhammer P, Godard S, Hansen M, Lerer FB, Liang KY, Maier W, Mallet J, Nertney DA, Nestadt G, Norton N, O'Neill FA, Papadimitriou GN, Ribble R, Sanders AR, Silverman JM, Walsh D, Williams NM, Wormley B, Arranz MJ, Bakker S, Bender S, Bramon E, Collier D, Crespo-Facorro B, Hall J, Iyegbe C, Jablensky A, Kahn RS, Kalaydjieva L, Lawrie S, Lewis CM, Lin K, Linszen DH, Mata I, McIntosh A, Murray RM, Ophoff RA, Powell J, Rujescu D, Van Os J, Walshe M, Weisbrod M, Wiersma D, Donnelly P, Barroso I, Blackwell JM, Bramon E, Brown MA, Casas JP, Corvin AP, Deloukas P, Duncanson A, Jankowski J, Markus HS, Mathew CG, Palmer CN, Plomin R, Rautanen A, Sawcer SJ, Trembath RC, Viswanathan AC, Wood NW, Spencer CC, Band G, Bellenguez C, Freeman C, Hellenthal G, Giannoulatou E, Pirinen M, Pearson RD, Strange A, Su Z, Vukcevic D, Donnelly P, Langford C, Hunt SE, Edkins S, Gwilliam R, Blackburn H, Bumpstead SJ, Dronov S, Gillman M, Gray E, Hammond N, Jayakumar A, McCann OT, Liddle J, Potter SC, Ravindrarajah R, Ricketts M, Tashakkori-Ghanbaria A, Waller MJ, Weston P, Widaa S, Whittaker P, Barroso I, Deloukas P, Mathew CG, Blackwell JM, Brown MA, Corvin AP, McCarthy MI, Spencer CC, Bramon E, Corvin AP, O'Donovan MC, Stefansson K, Scolnick E, Purcell S, McCarroll SA, Sklar P, Hultman CM, and Sullivan PF

Subjects
Case-Control Studies, Female, Humans, Male, Polymorphism, Single Nucleotide, Sweden, Genetic Predisposition to Disease, Genome-Wide Association Study, Schizophrenia genetics
Abstract

Schizophrenia is an idiopathic mental disorder with a heritable component and a substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases and 6,243 controls) followed by meta-analysis with previous schizophrenia GWAS (8,832 cases and 12,067 controls) and finally by replication of SNPs in 168 genomic regions in independent samples (7,413 cases, 19,762 controls and 581 parent-offspring trios). We identified 22 loci associated at genome-wide significance; 13 of these are new, and 1 was previously implicated in bipolar disorder. Examination of candidate genes at these loci suggests the involvement of neuronal calcium signaling. We estimate that 8,300 independent, mostly common SNPs (95% credible interval of 6,300-10,200 SNPs) contribute to risk for schizophrenia and that these collectively account for at least 32% of the variance in liability. Common genetic variation has an important role in the etiology of schizophrenia, and larger studies will allow more detailed understanding of this disorder.

Published
2013
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6. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment.

Author

Rietveld CA, Medland SE, Derringer J, Yang J, Esko T, Martin NW, Westra HJ, Shakhbazov K, Abdellaoui A, Agrawal A, Albrecht E, Alizadeh BZ, Amin N, Barnard J, Baumeister SE, Benke KS, Bielak LF, Boatman JA, Boyle PA, Davies G, de Leeuw C, Eklund N, Evans DS, Ferhmann R, Fischer K, Gieger C, Gjessing HK, Hägg S, Harris JR, Hayward C, Holzapfel C, Ibrahim-Verbaas CA, Ingelsson E, Jacobsson B, Joshi PK, Jugessur A, Kaakinen M, Kanoni S, Karjalainen J, Kolcic I, Kristiansson K, Kutalik Z, Lahti J, Lee SH, Lin P, Lind PA, Liu Y, Lohman K, Loitfelder M, McMahon G, Vidal PM, Meirelles O, Milani L, Myhre R, Nuotio ML, Oldmeadow CJ, Petrovic KE, Peyrot WJ, Polasek O, Quaye L, Reinmaa E, Rice JP, Rizzi TS, Schmidt H, Schmidt R, Smith AV, Smith JA, Tanaka T, Terracciano A, van der Loos MJ, Vitart V, Völzke H, Wellmann J, Yu L, Zhao W, Allik J, Attia JR, Bandinelli S, Bastardot F, Beauchamp J, Bennett DA, Berger K, Bierut LJ, Boomsma DI, Bültmann U, Campbell H, Chabris CF, Cherkas L, Chung MK, Cucca F, de Andrade M, De Jager PL, De Neve JE, Deary IJ, Dedoussis GV, Deloukas P, Dimitriou M, Eiríksdóttir G, Elderson MF, Eriksson JG, Evans DM, Faul JD, Ferrucci L, Garcia ME, Grönberg H, Guðnason V, Hall P, Harris JM, Harris TB, Hastie ND, Heath AC, Hernandez DG, Hoffmann W, Hofman A, Holle R, Holliday EG, Hottenga JJ, Iacono WG, Illig T, Järvelin MR, Kähönen M, Kaprio J, Kirkpatrick RM, Kowgier M, Latvala A, Launer LJ, Lawlor DA, Lehtimäki T, Li J, Lichtenstein P, Lichtner P, Liewald DC, Madden PA, Magnusson PK, Mäkinen TE, Masala M, McGue M, Metspalu A, Mielck A, Miller MB, Montgomery GW, Mukherjee S, Nyholt DR, Oostra BA, Palmer LJ, Palotie A, Penninx BW, Perola M, Peyser PA, Preisig M, Räikkönen K, Raitakari OT, Realo A, Ring SM, Ripatti S, Rivadeneira F, Rudan I, Rustichini A, Salomaa V, Sarin AP, Schlessinger D, Scott RJ, Snieder H, St Pourcain B, Starr JM, Sul JH, Surakka I, Svento R, Teumer A, Tiemeier H, van Rooij FJ, Van Wagoner DR, Vartiainen E, Viikari J, Vollenweider P, Vonk JM, Waeber G, Weir DR, Wichmann HE, Widen E, Willemsen G, Wilson JF, Wright AF, Conley D, Davey-Smith G, Franke L, Groenen PJ, Hofman A, Johannesson M, Kardia SL, Krueger RF, Laibson D, Martin NG, Meyer MN, Posthuma D, Thurik AR, Timpson NJ, Uitterlinden AG, van Duijn CM, Visscher PM, Benjamin DJ, Cesarini D, and Koellinger PD

Subjects
Cognition, Endophenotypes, Female, Genetic Loci, Humans, Male, Multifactorial Inheritance, Educational Status, Genome-Wide Association Study, Polymorphism, Single Nucleotide
Abstract

A genome-wide association study (GWAS) of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination R(2) ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.

Published
2013
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7. The association between lower educational attainment and depression owing to shared genetic effects?: Results in ~25,000 subjects

Author

Patricia A. Peyser, Jessica D. Faul, Patrik K. E. Magnusson, Nicholas D. Hastie, Beate St Pourcain, Marcus Ising, Gérard Waeber, Behrooz Z. Alizadeh, Judith M. Vonk, Lawrence F. Bielak, Sang Hong Lee, Wouter J. Peyrot, Thomas Illig, M. M. Weissman, Nicholas J. Timpson, George Dedoussis, Nicholas G. Martin, Tomi E. Mäkinen, Jorma Viikari, Lili Milani, Harold Snieder, Laura J. Bierut, A. C. Heath, Reinhold E. Schmidt, Mariza de Andrade, Vilmundur Gudnason, K. Petrovic, Robert M. Kirkpatrick, Marcela González Gross, William G. Iacono, Michelle N. Meyer, Henry Völzke, Marisa Loitfelder, Maria Dimitriou, Lude Franke, Robert F. Krueger, E. J. C. G. van den Oord, Sven Cichon, Michael Conlon O'Donovan, Ian W. Craig, Shawn N. Murphy, Danielle Posthuma, Brenda W.J.H. Penninx, Aarno Palotie, Roy Thurik, Panos Deloukas, Matt McGue, M. Preisig, Patricia A. Boyle, Osorio Meirelles, Ben A. Oostra, Klaus Berger, G. M. Montgomery, Sharon L.R. Kardia, Peter K. Joshi, K. Stefansson, Paul Lichtenstein, Andrew Heath, Andrea Schulz, Dena G. Hernandez, Debbie A Lawlor, S. P. Hamilton, James B. Potash, Z. Kutalik, Elisabeth Widen, Emil L. Sigurdsson, Rudolf S N Fehrmann, Matthias Nauck, Mikael Landén, Kurt Lohman, S.D. Gordon, Lefkos T. Middleton, Caroline Hayward, Anjali K. Henders, Philipp Koellinger, Jeffrey A. Boatman, G van Grootheest, M. Daly, Jian Yang, Peter Vollenweider, Penelope A. Lind, Stacy Steinberg, Frank J. A. van Rooij, Florian Holsboer, Hkon K. Gjessing, Erkki Vartiainen, Magnus Johannesson, Jingmei Li, David Laibson, Henrik Grönberg, Tõnu Esko, Ivana Kolcic, Niina Eklund, Kelly S. Benke, Henning Tiemeier, Isaac S. Kohane, Nicolas W. Martin, Ronny Myhre, Frans G. Zitman, Arpana Agrawal, James F. Wilson, Michael R. Barnes, Lei Yu, Thorgeir E. Thorgeirsson, Franois Bastardot, Katri Räikkönen, William Lawson, Willem A. Nolen, M. Rietschel, René Breuer, Bertram Müller-Myhsok, James A. Knowles, Grant W. Montgomery, Eva Reinmaa, Rudolf Uher, Andreas Mielck, Luigi Ferrucci, S. E. Medland, Yuri Milaneschi, Philip L. De Jager, Manfred Uhr, A. E. Farmer, Cornelia M. van Duijn, Samuli Ripatti, Marja-Liisa Nuotio, Manuel Mattheisen, Sebastian E. Baumeister, David R. Van Wagoner, Martin Preisig, Fernando Rivadeneira, Peter Lichtner, Christopher Oldmeadow, Hreinn Stefansson, Ian B. Hickie, Darina Czamara, Elizabeth G. Holliday, Astanand Jugessur, Carla A. Ibrahim-Verbaas, Jaime Derringer, Vivian S. Gainer, P. Muglia, Daniel J. Benjamin, Patrick K.E. Magnusson, Patience J. Gallagher, Jennifer A. Smith, Lynn Cherkas, Pamela A. F. Madden, David A. Bennett, Zoltán Kutalik, George Davey-Smith, Gudny Eiriksdottir, Jens Treutlein, N. Craddock, Juliette Harris, Antti Latvala, Roy H. Perlis, Markus M. Noethen, Jan-Emmanuel De Neve, Stanley I. Shyn, J.H. Smit, Dalton Conley, Adriaan Hofman, Jari Lahti, Patrick J. F. Groenen, Jüri Allik, Albert V. Smith, Ozren Polasek, Susan M. Ring, Thomas Bettecken, Michele L. Pergadia, Patrick J. McGrath, Katherine E. Tansey, Stephan Ripke, Hogni Oskarsson, Peng Lin, Douglas F. Levinson, Matthijs J. H. M. van der Loos, Melissa E. Garcia, Jonathan P. Beauchamp, Rodney J. Scott, Zhihong Zhu, Michel Guipponi, Lyle J. Palmer, Alexander Teumer, William Coryell, Stefan Kloiber, Gonneke Willemsen, John Frank, Victor M. Castro, Andrew M. McIntosh, John M. Starr, Antonio Terracciano, Mika Kähönen, Marco Masala, Markus Perola, André G. Uitterlinden, Sutapa Mukherjee, Alexander Viktorin, Lenore J. Launer, Elisabeth B. Binder, William A. Scheftner, Christel M. Middeldorp, D. H. R. Blackwood, I. Jones, Thais S. Rizzi, A. Teumer, Cornelius A. Rietveld, Aldo Rustichini, Guy Lewis, Susan L. Slager, David M. Evans, Dorret I. Boomsma, Harry Campbell, Susanne Churchill, Johan G. Eriksson, Alan F. Wright, Dan V. Iosifescu, W. Maier, Francesco Cucca, Federica Tozzi, David R. Weir, Eva Albrecht, L. Milani, Jennifer R. Harris, Min A. Jhun, Marjo-Riitta Järvelin, Martin F. Elderson, Ute Bültmann, Olli T. Raitakari, Konstantin Shakhbazov, Krista Fischer, Thomas G. Schulze, T. Jung-Ying, P. Lichtenstein, Terho Lethimäki, Jeffrey B. Weilburg, Rolf Holle, Bo Jacobsson, Pedro Marques Vidal, Jordan W. Smoller, Stavroula Kanoni, Kati Kristiansson, Sergey Goryachev, Michael Steffens, Peter M. Visscher, Toshiko Tanaka, Donald J. MacIntyre, Witte J.G. Hoogendijk, David Schlessinger, Ian J. Deary, Harm-Jan Westra, Erik Ingelsson, E.J.C. de Geus, Franziska Degenhardt, Lydia Quaye, John Barnard, David C. Liewald, John P. Rice, Christopher F. Chabris, P. McGuffin, Tamara B. Harris, C. M. Lewis, Gail Davies, Enda M. Byrne, H.-Erich Wichmann, Sara Hägg, David Cesarini, Najaf Amin, Juha Karjalainen, Dale R. Nyholt, Christian Gieger, Per Hall, Ania Korszun, Neale Bm, Wei Zhao, Abdel Abdellaoui, Andres Metspalu, Christina Holzapfel, Jae Hoon Sul, Christiaan de Leeuw, Antti-Pekka Sarin, Ida Surakka, Veikko Salomaa, Mina K. Chung, N. L. Pedersen, Gerome Breen, P. A. F. Madden, Martin A. Kohli, J Kaprio, John Attia, Jing Shi, Gibran Hemani, Rauli Svento, Veronique Vitart, Susanne Lucae, L. A. Jones, Jouke-Jan Hottenga, Daniel S. Evans, Hans-Jörgen Grabe, Yongmei Liu, Danyu Lin, Albert Hofman, George McMahon, Naomi R. Wray, Stefan Herms, Stefania Bandinelli, W. Hoffmann, P.F. Sullivan, Susanne Hoefels, Michael B. Miller, Alan W. McLean, Igor Rudan, Jürgen Wellmann, Anu Realo, Maurizio Fava, Matthew Kowgier, Marika Kaakinen, Helena Schmidt, Faculteit Medische Wetenschappen/UMCG, Peyrot, WJ, Lee, SH, Milaneschi, Y, Abdellaoui, A, Penninx, BWJH, Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium, Social Science Genetic Association Consortium, Psychiatry, NCA - Neurobiology of mental health, EMGO - Mental health, Applied Economics, Biological Psychology, Complex Trait Genetics, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, EMGO+ - Mental Health, Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium (Corporate Collaborator), Social Science Genetic Association Consortium Corporate Collaborator, Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium Corporate Collaborator, Lewis, C.M., Hamilton, S.P., Weissman, M.M., Breen, G., Blackwood, D.H., Cichon, S., Heath, A.C., Holsboer, F., Madden, P.A., McGuffin, P., Muglia, P., Pergadia, M.L., Lin, D., Müller-Myhsok, B., Steinberg, S., Grabe, H.J., Lichtenstein, P., Magnusson, P., Perlis, R.H., Preisig, M., Smoller, J.W., Stefansson, K., Uher, R., Kutalik, Z., Tansey, K.E., Teumer, A., Viktorin, A., Barnes, M.R., Bettecken, T., Binder, E.B., Breuer, R., Castro, V.M., Churchill, S.E., Coryell, W.H., Craddock, N., Craig, I.W., Czamara, D., Degenhardt, F., Farmer, A.E., Fava, M., Frank, J., Gainer, V.S., Gallagher, P.J., Gordon, S.D., Goryachev, S., Gross, M., Guipponi, M., Henders, A.K., Herms, S., Hickie, I.B., Hoefels, S., Hoogendijk, W., Iosifescu, D.V., Ising, M., Jones, I., Jones, L., Jung-Ying, T., Knowles, J.A., Kohane, I.S., Kohli, M.A., Korszun, A., Landen, M., Lawson, W.B., Lewis, G., Macintyre, D., Maier, W., Mattheisen, M., McGrath, P.J., McIntosh, A., McLean, A., Middeldorp, C.M., Middleton, L., Montgomery, G.M., Murphy, S.N., Nauck, M., Nolen, W.A., Nyholt, D.R., O'Donovan, M., Oskarsson, H., Pedersen, N., Scheftner, W.A., Schulz, A., Schulze, T.G., Shyn, S.I., Sigurdsson, E., Slager, S.L., Smit, J.H., Stefansson, H., Steffens, M., Thorgeirsson, T., Tozzi, F., Treutlein, J., Uhr, M., van den Oord, E.J., Van Grootheest, G., Völzke, H., Weilburg, J.B., Willemsen, G., Zitman, F.G., Neale, B., Daly, M., Sullivan, P.F., Agrawal, A., Albrecht, E., Alizadeh, B.Z., Allik, J., Amin, N., Attia, J.R., Bandinelli, S., Barnard, J., Bastardot, F., Baumeister, S.E., Beauchamp, J., Benjamin, D.J., Benke, K.S., Bennett, D.A., Berger, K., Bielak, L.F., Bierut, L.J., Boatman, J.A., Boyle, P.A., Bültmann, U., Campbell, H., Cesarini, D., Chabris, C.F., Cherkas, L., Chung, M.K., Conley, D., Cucca, F., Davey-Smith, G., Davies, G., de Andrade, M., De Jager, P.L., de Leeuw, C., De Neve, J.E., Deary, I.J., Dedoussis, G.V., Deloukas, P., Derringer, J., Dimitriou, M., Eiriksdottir, G., Eklund, N., Elderson, M.F., Eriksson, J.G., Evans, D.S., Evans, D.M., Faul, J.D., Fehrmann, R., Ferrucci, L., Fischer, K., Franke, L., Garcia, M.E., Gieger, C., Gjessing, H.K., Groenen, P.J., Grönberg, H., Gudnason, V., Hägg, S., Hall, P., Harris, J.R., Harris, J.M., Harris, T.B., Hastie, N.D., Hayward, C., Hernandez, D.G., Hoffmann, W., Hofman, A., Holle, R., Holliday, E.G., Holzapfel, C., Iacono, W.G., Ibrahim-Verbaas, C.A., Illig, T., Ingelsson, E., Jacobsson, B., Järvelin, M.R., Jhun, M.A., Johannesson, M., Joshi, P.K., Jugessur, A., Kaakinen, M., Kähönen, M., Kanoni, S., Kaprio, J., Kardia, S.L., Karjalainen, J., Kirkpatrick, R.M., Koellinger, P.D., Kolcic, I., Kowgier, M., Kristiansson, K., Krueger, R.F., Lahti, J., Laibson, D., Latvala, A., Launer, L.J., Lawlor, D.A., Lethimäki, T., Li, J., Lichtner, P.K., Liewald, D.C., Lin, P., Lind, P.A., Liu, Y., Lohman, K., Loitfelder, M., Magnusson, P.K., Mäkinen, T.E., Vidal, P.M., Martin, N.W., Masala, M., McGue, M., McMahon, G., Meirelles, O., Meyer, M.N., Mielck, A., Milani, L., Miller, M.B., Montgomery, G.W., Mukherjee, S., Myhre, R., Nuotio, M.L., Oldmeadow, C.J., Oostra, B.A., Palmer, L.J., Palotie, A., Perola, M., Petrovic, K.E., Peyser, P.A., Polašek, O., Posthuma, D., Quaye, L., Räikkönen, K., Raitakari, O.T., Realo, A., Reinmaa, E., Rice, J.P., Ring, S.M., Ripatti, S., Rivadeneira, F., Rizzi, T.S., Rudan, I., Rustichini, A., Salomaa, V., Sarin, A.P., Schlessinger, D., Schmidt, H., Schmidt, R., Scott, R.J., Shakhbazov, K., Smith, A.V., Smith, J.A., Snieder, H., Pourcain, B.S., Starr, J.M., Sul, J.H., Surakka, I., Svento, R., Tanaka, T., Terracciano, A., Thurik, A.R., Tiemeier, H., Timpson, N.J., Uitterlinden, A.G., van der Loos, M.J., van Duijn, C.M., van Rooij, F.J., Van Wagoner, D.R., Vartiainen, E., Viikari, J., Visscher, P.M., Vitart, V., Vollenweider, P.K., Vonk, J.M., Waeber, G., Weir, D.R., Wellmann, J., Westra, H.J., Wichmann, H.E., Widen, E., Wilson, J.F., Wright, A.F., Yang, J., Yu, L., and Zhao, W.

Subjects
Netherlands Twin Register (NTR), Male, Genome-wide association study, Logistic regression, Cohort Studies, Odds Ratio, pleiotropic genetic effects, Netherlands, Psychiatry, education.field_of_study, Likelihood Functions, Single Nucleotide, Middle Aged, Psychiatry and Mental health, educational attainment, depression, Major depressive disorder, Educational Status, Regression Analysis, Female, Psychology, Adult, Estonia, medicine.medical_specialty, Biochemistry & Molecular Biology, Aged, Depressive Disorder, Major/epidemiology, Depressive Disorder, Major/genetics, Depressive Disorder, Major/psychology, Estonia/epidemiology, Gene-Environment Interaction, Genetic Association Studies, Genotype, Humans, Netherlands/epidemiology, Polymorphism, Single Nucleotide/genetics, Psychiatric Status Rating Scales, Concordance, Population, SNP, Single-nucleotide polymorphism, Genetic correlation, behavioral disciplines and activities, Polymorphism, Single Nucleotide, Article, Cellular and Molecular Neuroscience, mental disorders, medicine, Polymorphism, education, Molecular Biology, Depressive Disorder, Depressive Disorder, Major, major depressive disorder, ta1184, Neurosciences, Major, Odds ratio, medicine.disease, ta3124, Neurosciences & Neurology, polymorphisms, Demography
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 similar to 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. Refereed/Peer-reviewed

Published
2015
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