Schizophrenia has a lifetime risk of around 1%, and is associated with substantial morbidity and mortality as well as personal and societal costs^1,2,3. Although pharmacological treatments are available for schizophrenia, their efficacy is poor for many patients⁴. All available antipsychotic drugs are thought to exert their main therapeutic effects through blockade of the type 2 dopaminergic receptor^5,6 but, since the discovery of this mechanism over 60 years ago, no new antipsychotic drug of proven efficacy has been developed based on other target molecules. Therapeutic stasis is in large part a consequence of the fact that the pathophysiology of schizophrenia is unknown. Identifying the causes of schizophrenia is therefore a critical step towards improving treatments and outcomes for those with the disorder.

High heritability points to a major role for inherited genetic variants in the aetiology of schizophrenia^7,8. Although risk variants range in frequency from common to extremely rare⁹, estimates^10,11 suggest half to a third of the genetic risk of schizophrenia is indexed by common alleles genotyped by current genome-wide association study (GWAS) arrays. Thus, GWAS is potentially an important tool for understanding the biological underpinnings of schizophrenia.

To date, around 30 schizophrenia-associated loci^{10,11,12,13,14,15,16,17,18,19,20,21,22,23} have been identified through GWAS. Postulating that sample size is one of the most important limiting factors in applying GWAS to schizophrenia, we created the Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC). Our primary aim was to combine all available schizophrenia samples with published or unpublished GWAS genotypes into a single, systematic analysis²⁴. Here we report the results of that analysis, including at least 108 independent genomic loci that exceed genome-wide significance. Some of the findings support leading pathophysiological hypotheses of schizophrenia or targets of therapeutic relevance, but most of the findings provide new insights.

We obtained genome-wide genotype data from which we constructed 49 ancestry matched, non-overlapping case-control samples (46 of European and three of east Asian ancestry, 34,241 cases and 45,604 controls) and 3 family-based samples of European ancestry (1,235 parent affected-offspring trios) (Supplementary Table 1 andSupplementary Methods). These comprise the primary PGC GWAS data set. We processed the genotypes from all studies using unified quality control procedures followed by imputation of SNPs and insertion-deletions using the 1000 Genomes Project reference panel²⁵. In each sample, association testing was conducted using imputed marker dosages and principal components (PCs) to control for population stratification. The results were combined using an inverse-variance weighted fixed effects model²⁶. After quality control (imputation INFO score ≥ 0.6, MAF ≥ 0.01, and successfully imputed in ≥ 20 samples), we considered around 9.5 million variants. The results are summarized inFig. 1. To enable acquisition of large samples, some groups ascertained cases via clinician diagnosis rather than a research-based assessment and provided evidence of the validity of this approach (Supplementary Information)^11,13. Post hoc analyses revealed the pattern of effect sizes for associated loci was similar across different assessment methods and modes of ascertainment (Extended Data Fig. 1), supporting oura priori decision to include samples of this nature.

Manhattan plot of the discovery genome-wide association meta-analysis of 49 case control samples (34,241 cases and 45,604 controls) and 3 family based association studies (1,235 parent affected-offspring trios). Thex axis is chromosomal position and they axis is the significance (–log₁₀P; 2-tailed) of association derived by logistic regression. The red line shows the genome-wide significance level (5 × 10⁻⁸). SNPs in green are in linkage disequilibrium with the index SNPs (diamonds) which represent independent genome-wide significant associations.

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For the subset of linkage-disequilibrium-independent single nucleotide polymorphisms (SNPs) withP < 1 × 10⁻⁶ in the meta-analysis, we next obtained results from deCODE genetics (1,513 cases and 66,236 controls of European ancestry). We define linkage-disequilibrium-independent SNPs as those with low linkage disequilibrium (r² < 0.1) to a more significantly associated SNP within a 500-kb window. Given high linkage disequilibrium in the extended major histocompatibility complex (MHC) region spans∼8 Mb, we conservatively include only a single MHC SNP to represent this locus. The deCODE data were then combined with those from the primary GWAS to give a data set of 36,989 cases and 113,075 controls. In this final analysis, 128 linkage-disequilibrium-independent SNPs exceeded genome-wide significance (P ≤ 5 × 10⁻⁸) (Supplementary Table 2).

As in meta-analyses of other complex traits which identified large numbers of common risk variants^27,28, the test statistic distribution from our GWAS deviates from the null (Extended Data Fig. 2). This is consistent with the previously documented polygenic contribution to schizophrenia^10,11. The deviation in the test statistics from the null (λ_GC = 1.47, λ₁₀₀₀ = 1.01) is only slightly less than expected (λ_GC = 1.56) under a polygenic model given fully informative genotypes, the current sample size, and the lifetime risk and heritability of schizophrenia²⁹.

Additional lines of evidence allow us to conclude the deviation between the observed and null distributions in our primary GWAS indicates a true polygenic contribution to schizophrenia. First, applying a novel method³⁰ that uses linkage disequilibrium information to distinguish between the major potential sources of test statistic inflation, we found our results are consistent with polygenic architecture but not population stratification (Extended Data Fig. 3). Second, the schizophrenia-associated alleles at 78% of 234 linkage-disequilibrium-independent SNPs exceedingP < 1 × 10⁻⁶ in the case-control GWAS were again overrepresented in cases in the independent samples from deCODE. This degree of consistency between the case-control GWAS and the replication data is highly unlikely to occur by chance (P = 6 × 10⁻¹⁹). The tested alleles surpassed theP < 10⁻⁶ threshold in our GWAS before we added either the trios or deCODE data to the meta-analysis. This trend test is therefore independent of the primary case-control GWAS. Third, analysing the 1,235 parent-proband trios, we again found excess transmission of the schizophrenia-associated allele at 69% of the 263 linkage-disequilibrium-independent SNPs withP < 1 × 10⁻⁶ in the case-control GWAS. This is again unlikely to occur by chance (P = 1 × 10⁻⁹) and additionally excludes population stratification as fully explaining the associations reaching our threshold for seeking replication. Fourth, we used the trios trend data to estimate the expected proportion of true associations atP < 1 × 10⁻⁶ in the discovery GWAS, allowing for the fact that half of the index SNPs are expected to show the same allelic trend in the trios by chance, and that some true associations will show opposite trends given the limited number of trio samples (Supplementary Methods). Given the observed trend test results, around 67% (95% confidence interval: 64–73%) orn = 176 of the associations in the scan atP < 1 × 10⁻⁶ are expected to be true, and therefore the number of associations that will ultimately be validated from this set of SNPs will be considerably more than those that now meet genome-wide significance. Taken together, these analyses indicate that the observed deviation of test statistics from the null primarily represents polygenic association signal and the considerable excess of associations at the tail of extreme significance largely correspond to true associations.

Independently associated SNPs do not translate to well-bounded chromosomal regions. Nevertheless, it is useful to define physical boundaries for the SNP associations to identify candidate risk genes. We defined an associated locus as the physical region containing all SNPs correlated atr² > 0.6 with each of the 128 index SNPs. Associated loci within 250 kb of each other were merged. This resulted in 108 physically distinct associated loci, 83 of which have not been previously implicated in schizophrenia and therefore harbour potential new biological insights into disease aetiology (Supplementary Table 3; regional plots inSupplementary Fig. 1). The significant regions include all but 5 loci previously reported to be genome-wide significant in large samples (Supplementary Table 3).

Of the 108 loci, 75% include protein-coding genes (40%, a single gene) and a further 8% are within 20 kb of a gene (Supplementary Table 3). Notable associations relevant to major hypotheses of the aetiology and treatment of schizophrenia includeDRD2 (the target of all effective antipsychotic drugs) and many genes (for example,GRM3,GRIN2A,SRR,GRIA1) involved in glutamatergic neurotransmission and synaptic plasticity. In addition, associations atCACNA1C,CACNB2 andCACNA1I, which encode voltage-gated calcium channel subunits, extend previous findings implicating members of this family of proteins in schizophrenia and other psychiatric disorders^11,13,31,32. Genes encoding calcium channels, and proteins involved in glutamatergic neurotransmission and synaptic plasticity have been independently implicated in schizophrenia by studies of rare genetic variation^33,34,35, suggesting convergence at a broad functional level between studies of common and rare genetic variation. We highlight in theSupplementary Discussion genes of particular interest within associated loci with respect to current hypotheses of schizophrenia aetiology or treatment (although we do not imply that these genes are necessarily the causal elements).

For each of the schizophrenia-associated loci, we identified a credible causal set of SNPs (for definition, seeSupplementary Methods)³⁶. In only 10 instances (Supplementary Table 4) was the association signal credibly attributable to a known non-synonymous exonic polymorphism. The apparently limited role of protein-coding variants is consistent both with exome sequencing findings³³ and with the hypothesis that most associated variants detected by GWAS exert their effects through altering gene expression rather than protein structure^37,38 and with the observation that schizophrenia risk loci are enriched for expression quantitative trait loci (eQTL)³⁹.

To try to identify eQTLs that could explain associations with schizophrenia, we merged the credible causal set of SNPs defined above with eQTLs from a meta-analysis of human brain cortex eQTL studies (n = 550) and an eQTL study of peripheral venous blood (n = 3,754)⁴⁰ (Supplementary Methods). Multiple schizophrenia loci contained at least one eQTL for a gene within 1 Mb of the locus (Supplementary Table 4). However, in only 12 instances was the eQTL plausibly causal (two in brain, and nine in peripheral blood, one in both). This low proportion suggests that if most risk variants are regulatory, available eQTL catalogues do not yet provide power, cellular specificity, or developmental diversity to provide clear mechanistic hypotheses for follow-up experiments.

To further explore the regulatory nature of the schizophrenia associations, we mapped the credible sets (n = 108) of causal variants onto sequences with epigenetic markers characteristic of active enhancers in 56 different tissues and cell lines (Supplementary Methods). Schizophrenia associations were significantly enriched at enhancers active in brain (Fig. 2) but not in tissues unlikely to be relevant to schizophrenia (for example, bone, cartilage, kidney and fibroblasts). Brain tissues used to define enhancers consist of heterogeneous populations of cells. Seeking greater specificity, we contrasted genes enriched for expression in neurons and glia using mouse ribotagged lines⁴¹. Genes with strong expression in multiple cortical and striatal neuronal lineages were enriched for associations, providing support for an important neuronal pathology in schizophrenia (Extended Data Fig. 4) but this is not statistically more significant than, or exclusionary of, contributions from other lineages⁴².

Cell and tissue type specific enhancers were identified using ChIP-seq data sets (H3K27ac signal) from 56 cell line and tissue samples (y axis). We defined cell and tissue type enhancers as the top 10% of enhancers with the highest ratio of reads in that cell or tissue type divided by the total number of reads. Enrichment of credible causal associated SNPs from the schizophrenia GWAS was compared with frequency matched sets of 1000 Genomes SNPs (Supplementary Methods). Thex axis is the –log₁₀P for enrichment.P values are uncorrected for the number of tissues or cells tested. A –log₁₀P of roughly 3 can be considered significant after Bonferroni correction. Descriptions of cell and tissue types at the Roadmap Epigenome website (http://www.roadmapepigenomics.org).

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Schizophrenia associations were also strongly enriched at enhancers that are active in tissues with important immune functions, particularly B-lymphocyte lineages involved in acquired immunity (CD19 and CD20 lines,Fig. 2). These enrichments remain significant even after excluding the extended MHC region and regions containing brain enhancers (enrichmentP for CD20 < 10⁻⁶), demonstrating that this finding is not an artefact of correlation between enhancer elements in different tissues and not driven by the strong and diffuse association at the extended MHC. Epidemiological studies have long hinted at a role for immune dysregulation in schizophrenia, the present findings provide genetic support for this hypothesis⁴³.

To develop additional biological hypotheses beyond those that emerge from inspection of the individual loci, we further undertook a limited mining of the data through gene-set analysis. However, as there is no consensus methodology by which such analyses should be conducted, nor an established optimal significance threshold for including loci, we sought to be conservative, using only two of the many available approaches^44,45 and restricting analyses to genes within genome-wide significant loci. Neither approach identified gene-sets that were significantly enriched for associations after correction for the number of pathways tested (Supplementary Table 5) although nominally significantly enrichments were observed among several predefined candidate pathways (Extended Data Table 1). A fuller exploratory analysis of the data will be presented elsewhere.

CNVs associated with schizophrenia overlap with those associated with autism spectrum disorder (ASD) and intellectual disability⁹, as do genes with deleteriousde novo mutations³⁴. Here we find significant overlap between genes in the schizophrenia GWAS associated intervals and those withde novo non-synonymous mutations in schizophrenia (P = 0.0061) (Extended Data Table 2), suggesting that mechanistic studies of rare genetic variation in schizophrenia will be informative for schizophrenia more widely. We also find evidence for overlap between genes in schizophrenia GWAS regions and those withde novo non-synonymous mutations in intellectual disability (P = 0.00024) and ASD (P = 0.035), providing further support for the hypothesis that these disorders have partly overlapping pathophysiologies^9,34.

Previous studies have shown that risk profile scores (RPS) constructed from alleles showing modest association with schizophrenia in a discovery GWAS can predict case-control status in independent samples, albeit with low sensitivity and specificity^10,11,16. This finding was robustly confirmed in the present study. The estimate of NagelkerkeR² (a measure of variance in case-control status explained) depends on the specific target data set and threshold (P_T) for selecting risk alleles for RPS analysis (Extended Data Fig. 5 and6a). However, using the same target sample as earlier studies andP_T = 0.05,R² is now increased from 0.03 (ref.10) to 0.184 (Extended Data Fig. 5). Assuming a liability-threshold model, a lifetime risk of 1%, independent SNP effects, and adjusting for case-control ascertainment, RPS now explains about 7% of variation on the liability scale⁴⁶ to schizophrenia across the samples (Extended Data Fig. 6b), about half of which (3.4%) is explained by genome-wide significant loci.

We also evaluated the capacity of RPS to predict case-control status using a standard epidemiological approach to a continuous risk factor. We illustrate this in three samples, each with different ascertainment schemes (Fig. 3). The Danish sample is population-based (that is, inpatient and outpatient facilities), the Swedish sample is based on all cases hospitalized for schizophrenia in Sweden, and the Molecular Genetics of Schizophrenia (MGS) sample was ascertained specially for genetic studies from clinical sources in the US and Australia. We grouped individuals into RPS deciles and estimated the odds ratios for affected status for each decile with reference to the lowest risk decile. The odds ratios increased with greater number of schizophrenia risk alleles in each sample, maximizing for the tenth decile in all samples: Denmark 7.8 (95% confidence interval (CI): 4.4–13.9), Sweden 15.0 (95% CI: 12.1–18.7) and MGS 20.3 (95% CI: 14.7–28.2). Given the need for measures that index liability to schizophrenia^47,48, the ability to stratify individuals by RPS offers new opportunities for clinical and epidemiological research. Nevertheless, we stress that the sensitivity and specificity of RPS do not support its use as a predictive test. For example, in the Danish epidemiological sample, the area under the receiver operating curve is only 0.62 (Extended Data Fig. 6c,Supplementary Table 6).

Odds ratio for schizophrenia by risk score profile (RPS) decile in the Sweden (Sw1-6), Denmark (Aarhus), and Molecular Genetics of Schizophrenia studies (Supplementary Methods). Risk alleles and weights were derived from ‘leave one out’ analyses in which those samples were excluded from the GWAS meta-analysis (Supplementary Methods). The threshold for selecting risk alleles wasP_T < 0.05. The RPS were converted to deciles (1 = lowest, 10 = highest RPS), and nine dummy variables created to contrast deciles 2-10 to decile 1 as the reference. Odds ratios and 95% confidence intervals (bars) were estimated using logistic regression with PCs to control for population stratification.

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Finally, seeking evidence for non-additive effects on risk, we tested for statistical interaction between all pairs of 125 autosomal SNPs that reached genome-wide significance.P values for the interaction terms were distributed according to the null, and no interaction was significant after correction for multiple comparisons. Thus, we find no evidence for epistatic or non-additive effects between the significant loci (Extended Data Fig. 7). It is possible that such effects could be present between other loci, or occur in the form of higher-order interactions.

In the largest (to our knowledge) molecular genetic study of schizophrenia, or indeed of any neuropsychiatric disorder, ever conducted, we demonstrate the power of GWAS to identify large numbers of risk loci. We show that the use of alternative ascertainment and diagnostic schemes designed to rapidly increase sample size does not inevitably introduce a crippling degree of heterogeneity. That this is true for a phenotype like schizophrenia, in which there are no biomarkers or supportive diagnostic tests, provides grounds to be optimistic that this approach can be successfully applied to GWAS of other clinically defined disorders.

We further show that the associations are not randomly distributed across genes of all classes and function; rather they converge upon genes that are expressed in certain tissues and cellular types. The findings include molecules that are the current, or the most promising, targets for therapeutics, and point to systems that align with the predominant aetiological hypotheses of the disorder. This suggests that the many novel findings we report also provide an aetiologically relevant foundation for mechanistic and treatment development studies. We also find overlap between genes affected by rare variants in schizophrenia and those within GWAS loci, and broad convergence in the functions of some of the clusters of genes implicated by both sets of genetic variants, particularly genes related to abnormal glutamatergic synaptic and calcium channel function. How variation in these genes impact function to increase risk for schizophrenia cannot be answered by genetics, but the overlap strongly suggests that common and rare variant studies are complementary rather than antagonistic, and that mechanistic studies driven by rare genetic variation will be informative for schizophrenia.

Core funding for the Psychiatric Genomics Consortium is from the US National Institute of Mental Health (U01 MH094421). We thank T. Lehner (NIMH). The work of the contributing groups was supported by numerous grants from governmental and charitable bodies as well as philanthropic donation. Details are provided in theSupplementary Notes. Membership of the Wellcome Trust Case Control Consortium and of the Psychosis Endophenotype International Consortium are provided in theSupplementary Notes.

1. Wellcome Trust Case-Control Consortium and Thomas Werge: A list of authors and affiliations appear in the Supplementary Information.

2. Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland.

3. University College London, London WC1E 6BT, UK.

Authors and Affiliations

1. Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, 02114, Massachusetts, USA

   Stephan Ripke, Benjamin M. Neale, Kai-How Farh, Phil Lee, Brendan Bulik-Sullivan, Hailiang Huang, Menachem Fromer, Jacqueline I. Goldstein & Mark J. Daly

2. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, 02142, Massachusetts, USA

   Stephan Ripke, Benjamin M. Neale, Phil Lee, Brendan Bulik-Sullivan, Richard A. Belliveau Jr, Sarah E. Bergen, Elizabeth Bevilacqua, Kimberly D. Chambert, Menachem Fromer, Giulio Genovese, Colm O’Dushlaine, Edward M. Scolnick, Jordan W. Smoller, Steven A. McCarroll, Jennifer L. Moran, Aarno Palotie, Tracey L. Petryshen & Mark J. Daly

3. Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, 02142, Massachusetts, USA

   Benjamin M. Neale, Hailiang Huang, Tune H. Pers, Jacqueline I. Goldstein, Joel N. Hirschhorn, Alkes Price, Eli A. Stahl, Tõnu Esko & Mark J. Daly

4. Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, 02114, Massachusetts, USA

   Benjamin M. Neale, Phil Lee, Menachem Fromer, Jordan W. Smoller & Aarno Palotie

5. Department of Psychiatry, Neuropsychiatric Genetics Research Group, Trinity College Dublin, Dublin 8, Ireland.,

   Aiden Corvin, Paul Cormican, Gary Donohoe, Derek W. Morris & Michael Gill

6. MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff CF24 4HQ, UK.,

   James T. R. Walters, Peter A. Holmans, Noa Carrera, Nick Craddock, Valentina Escott-Price, Lyudmila Georgieva, Marian L. Hamshere, David Kavanagh, Sophie E. Legge, Andrew J. Pocklington, Alexander L. Richards, Douglas M. Ruderfer, Nigel M. Williams, George Kirov, Michael J. Owen & Michael C. O’Donovan

7. National Centre for Mental Health, Cardiff University, Cardiff CF24 4HQ, UK.,

   Peter A. Holmans, Nick Craddock, Michael J. Owen & Michael C. O’Donovan

8. Eli Lilly and Company Limited, Erl Wood Manor, Sunninghill Road, Windlesham, Surrey GU20 6PH, UK.,

   David A. Collier & Younes Mokrab

9. Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, London SE5 8AF, UK.,

   David A. Collier

10. Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, DK-2800, Denmark.,

    Tune H. Pers

11. Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Boston, 02115, Massachusetts, USA

    Tune H. Pers, Joel N. Hirschhorn & Tõnu Esko

12. Department of Clinical Neuroscience, Psychiatry Section, Karolinska Institutet, SE-17176 Stockholm, Sweden.,

    Ingrid Agartz, Erik Söderman & Erik G. Jönsson

13. Department of Psychiatry, Diakonhjemmet Hospital, 0319 Oslo, Norway.,

    Ingrid Agartz

14. NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, 0424 Oslo, Norway.,

    Ingrid Agartz, Srdjan Djurovic, Morten Mattingsdal, Ingrid Melle, Ole A. Andreassen & Erik G. Jönsson

15. Centre for Integrative Register-based Research, CIRRAU, Aarhus University, DK-8210 Aarhus, Denmark.,

    Esben Agerbo & Preben B. Mortensen

16. National Centre for Register-based Research, Aarhus University, DK-8210 Aarhus, Denmark.,

    Esben Agerbo & Preben B. Mortensen

17. The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark.,

    Esben Agerbo, Ditte Demontis, Thomas Hansen, Manuel Mattheisen, Ole Mors, Line Olsen, Henrik B. Rasmussen, Anders D. Børglum, Preben B. Mortensen & Thomas Werge

18. State Mental Hospital, 85540 Haar, Germany.,

    Margot Albus

19. Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, 94305, California, USA

    Madeline Alexander, Claudine Laurent & Douglas F. Levinson

20. Department of Psychiatry and Behavioral Sciences, Atlanta Veterans Affairs Medical Center, Atlanta, Georgia 30033, USA.,

    Farooq Amin

21. Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, 30322, Georgia, USA

    Farooq Amin

22. Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, 23298, Virginia, USA

    Silviu A. Bacanu, Tim B. Bigdeli, Bradley T. Webb & Brandon K. Wormley

23. Clinical Neuroscience, Max Planck Institute of Experimental Medicine, Göttingen 37075, Germany.,

    Martin Begemann, Christian Hammer, Sergi Papiol & Hannelore Ehrenreich

24. Department of Medical Genetics, University of Pécs, Pécs H-7624, Hungary.,

    Judit Bene & Bela Melegh

25. Szentagothai Research Center, University of Pécs, Pécs H-7624, Hungary.,

    Judit Bene & Bela Melegh

26. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm SE-17177, Sweden.,

    Sarah E. Bergen, Anna K. Kähler, Patrik K. E. Magnusson, Christina M. Hultman & Patrick F. Sullivan

27. Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, 52242, Iowa, USA

    Donald W. Black

28. Department of Psychiatry, University Medical Center Groningen, University of Groningen NL-9700 RB, The Netherlands

    Richard Bruggeman

29. School of Nursing, Louisiana State University Health Sciences Center, New Orleans, 70112, Louisiana, USA

    Nancy G. Buccola

30. Athinoula A. Martinos Center, Massachusetts General Hospital, Boston, 02129, Massachusetts, USA

    Randy L. Buckner & Joshua L. Roffman

31. Center for Brain Science, Harvard University, Cambridge, 02138, Massachusetts, USA

    Randy L. Buckner

32. Department of Psychiatry, Massachusetts General Hospital, Boston, 02114, Massachusetts, USA

    Randy L. Buckner & Joshua L. Roffman

33. Department of Psychiatry, University of California at San Francisco, San Francisco, 94143, California, USA

    William Byerley

34. Department of Psychiatry, University Medical Center Utrecht, Rudolf Magnus Institute of Neuroscience, 3584 Utrecht, The Netherlands.,

    Wiepke Cahn, René S. Kahn, Eric Strengman & Roel A. Ophoff

35. Department of Human Genetics, Icahn School of Medicine at Mount Sinai, New York, 10029, New York, USA

    Guiqing Cai & Joseph D. Buxbaum

36. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, 10029, New York, USA

    Guiqing Cai, Kenneth L. Davis, Elodie Drapeau, Joseph I. Friedman, Vahram Haroutunian, Elena Parkhomenko, Abraham Reichenberg, Jeremy M. Silverman & Joseph D. Buxbaum

37. Centre Hospitalier du Rouvray and INSERM U1079 Faculty of Medicine, 76301 Rouen, France.,

    Dominique Campion

38. Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, 90095, California, USA

    Rita M. Cantor & Roel A. Ophoff

39. Schizophrenia Research Institute, Sydney NSW 2010, Australia.,

    Vaughan J. Carr, Stanley V. Catts, Frans A. Henskens, Carmel M. Loughland, Patricia T. Michie, Christos Pantelis, Ulrich Schall, Rodney J. Scott & Assen V. Jablensky

40. School of Psychiatry, University of New South Wales, Sydney NSW 2031, Australia.,

    Vaughan J. Carr

41. Royal Brisbane and Women’s Hospital, University of Queensland, Brisbane, St Lucia QLD 4072, Australia.,

    Stanley V. Catts

42. Institute of Psychology, Chinese Academy of Science, Beijing, 100101, China

    Raymond C. K. Chan

43. Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China

    Ronald Y. L. Chen, Eric Y. H. Chen, Miaoxin Li, Hon-Cheong So, Emily H. M. Wong & Pak C. Sham

44. State Key Laboratory for Brain and Cognitive Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China

    Eric Y. H. Chen, Miaoxin Li & Pak C. Sham

45. Department of Computer Science, University of North Carolina, Chapel Hill, 27514, North Carolina, USA

    Wei Cheng

46. Castle Peak Hospital, Hong Kong, China

    Eric F. C. Cheung

47. Institute of Mental Health, Singapore, 539747, Singapore

    Siow Ann Chong, Jimmy Lee Chee Keong, Kang Sim & Mythily Subramaniam

48. Department of Psychiatry, Washington University, St. Louis, 63110, Missouri, USA

    C. Robert Cloninger & Dragan M. Svrakic

49. Department of Child and Adolescent Psychiatry, Assistance Publique Hopitaux de Paris, Pierre and Marie Curie Faculty of Medicine and Institute for Intelligent Systems and Robotics, Paris 75013, France.,

    David Cohen

50. Blue Note Biosciences, Princeton, 08540, New Jersey, USA

    Nadine Cohen

51. Department of Genetics, University of North Carolina, Chapel Hill, 27599-7264, North Carolina, USA

    James J. Crowley, Martilias S. Farrell, Paola Giusti-Rodríguez, Yunjung Kim, Jin P. Szatkiewicz, Stephanie Williams & Patrick F. Sullivan

52. Department of Psychological Medicine, Queen Mary University of London, London E1 1BB, UK.,

    David Curtis

53. Division of Psychiatry, Molecular Psychiatry Laboratory, University College London, London WC1E 6JJ, UK.,

    David Curtis, Jonathan Pimm, Hugh Gurling & Andrew McQuillin

54. Sheba Medical Center, Tel Hashomer 52621, Israel.,

    Michael Davidson & Mark Weiser

55. Department of Genomics, Life and Brain Center, D-53127 Bonn, Germany.,

    Franziska Degenhardt, Stefan Herms, Per Hoffmann, Andrea Hofman, Sven Cichon & Markus M. Nöthen

56. Institute of Human Genetics, University of Bonn, D-53127 Bonn, Germany.,

    Franziska Degenhardt, Stefan Herms, Per Hoffmann, Andrea Hofman, Sven Cichon & Markus M. Nöthen

57. VIB Department of Molecular Genetics, Applied Molecular Genomics Unit, University of Antwerp, B-2610 Antwerp, Belgium.,

    Jurgen Del Favero

58. Centre for Integrative Sequencing, iSEQ, Aarhus University, DK-8000 Aarhus C, Denmark.,

    Ditte Demontis, Manuel Mattheisen, Ole Mors & Anders D. Børglum

59. Department of Biomedicine, Aarhus University, DK-8000 Aarhus C, Denmark.,

    Ditte Demontis, Manuel Mattheisen & Anders D. Børglum

60. First Department of Psychiatry, University of Athens Medical School, Athens 11528, Greece.,

    Dimitris Dikeos & George N. Papadimitriou

61. Department of Psychiatry, University College Cork, Co. Cork, Ireland.,

    Timothy Dinan

62. Department of Medical Genetics, Oslo University Hospital, 0424 Oslo, Norway.,

    Srdjan Djurovic

63. Cognitive Genetics and Therapy Group, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Co. Galway, Ireland.,

    Gary Donohoe & Derek W. Morris

64. Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, 60637, Illinois, USA

    Jubao Duan, Alan R. Sanders & Pablo V. Gejman

65. Department of Psychiatry and Behavioral Sciences, NorthShore University HealthSystem, Evanston, 60201, Illinois, USA

    Jubao Duan, Alan R. Sanders & Pablo V. Gejman

66. Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.,

    Frank Dudbridge

67. Department of Child and Adolescent Psychiatry, University Clinic of Psychiatry, Skopje 1000, Republic of Macedonia.,

    Naser Durmishi

68. Department of Psychiatry, University of Regensburg, 93053 Regensburg, Germany.,

    Peter Eichhammer

69. Department of General Practice, Helsinki University Central Hospital, University of Helsinki P.O. Box 20, Tukholmankatu 8 B, FI-00014, Helsinki, Finland,

    Johan Eriksson

70. Folkhälsan Research Center, Helsinki, Finland, Biomedicum Helsinki 1, Haartmaninkatu 8, FI-00290, Helsinki, Finland.,

    Johan Eriksson

71. National Institute for Health and Welfare, P.O. Box 30, FI-00271 Helsinki, Finland.,

    Johan Eriksson & Veikko Salomaa

72. Translational Technologies and Bioinformatics, Pharma Research and Early Development, F. Hoffman-La Roche, CH-4070 Basel, Switzerland.,

    Laurent Essioux

73. Department of Psychiatry, Georgetown University School of Medicine, 20057, Washington DC, USA

    Ayman H. Fanous

74. Department of Psychiatry, Keck School of Medicine of the University of Southern California, Los Angeles, California 90033, USA.,

    Ayman H. Fanous

75. Departmentof Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, 23298, Virginia, USA

    Ayman H. Fanous

76. Mental Health Service Line, Washington VA Medical Center, 20422, Washington DC, USA

    Ayman H. Fanous

77. Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, D-68159 Mannheim, Germany.,

    Josef Frank, Sandra Meier, Thomas G. Schulze, Jana Strohmaier, Stephanie H. Witt & Marcella Rietschel

78. Department of Genetics, University of Groningen, University Medical Centre Groningen, 9700 RB Groningen, The Netherlands.,

    Lude Franke & Juha Karjalainen

79. Department of Psychiatry, University of Colorado Denver, Aurora, 80045, Colorado, USA

    Robert Freedman & Ann Olincy

80. Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, 90095, California, USA

    Nelson B. Freimer & Roel A. Ophoff

81. Department of Psychiatry, University of Halle, 06112 Halle, Germany.,

    Marion Friedl, Ina Giegling, Annette M. Hartmann, Bettina Konte & Dan Rujescu

82. Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, 10029, New York, USA

    Menachem Fromer, Shaun M. Purcell, Panos Roussos, Douglas M. Ruderfer, Eli A. Stahl & Pamela Sklar

83. Department of Psychiatry, University of Munich, 80336, Munich, Germany.,

    Ina Giegling & Dan Rujescu

84. Departments of Psychiatry and Human and Molecular Genetics, INSERM, Institut de Myologie, Hôpital de la Pitiè-Salpêtrière, Paris 75013, France.,

    Stephanie Godard

85. Mental Health Research Centre, Russian Academy of Medical Sciences, 115522 Moscow, Russia.,

    Vera Golimbet

86. Neuroscience Therapeutic Area, Janssen Research and Development, Raritan, 08869, New Jersey, USA

    Srihari Gopal, Dai Wang & Qingqin S. Li

87. Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, QLD 4072, Australia.,

    Jacob Gratten, S. Hong Lee, Naomi R. Wray, Peter M. Visscher & Bryan J. Mowry

88. Department of Psychiatry, Academic Medical Centre University of Amsterdam, 1105 AZ Amsterdam, The Netherlands.,

    Lieuwe de Haan & Carin J. Meijer

89. Illumina, La Jolla, California, California 92122, USA.,

    Mark Hansen

90. Institute of Biological Psychiatry, Mental Health Centre Sct. Hans, Mental Health Services Copenhagen, DK-4000, Denmark.,

    Thomas Hansen, Line Olsen, Henrik B. Rasmussen & Thomas Werge

91. Friedman Brain Institute, Icahn School ofMedicine at Mount Sinai, New York, 10029, New York, USA

    Vahram Haroutunian, Joseph D. Buxbaum & Pamela Sklar

92. J. J. Peters VA Medical Center, Bronx, New York, 10468, New York, USA

    Vahram Haroutunian

93. Priority Research Centre for Health Behaviour, University of Newcastle, Newcastle NSW 2308, Australia.,

    Frans A. Henskens

94. School of Electrical Engineering and Computer Science, University of Newcastle, Newcastle NSW 2308, Australia.,

    Frans A. Henskens

95. Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel CH-4058, Switzerland.,

    Stefan Herms, Per Hoffmann & Sven Cichon

96. Department of Genetics, Harvard Medical School, Boston, Massachusetts, Massachusetts 02115, USA.,

    Joel N. Hirschhorn, Tõnu Esko & Steven A. McCarroll

97. Department of Clinical Biochemistry, Section of Neonatal Screening and Hormones, Immunology and Genetics, Statens Serum Institut, Copenhagen DK-2300, Denmark.,

    Mads V. Hollegaard & David M. Hougaard

98. Department of Psychiatry, Fujita Health University School of Medicine, Toyoake, Aichi,470-1192, Japan.,

    Masashi Ikeda & Nakao Iwata

99. Department of Psychiatry, Regional Centre for Clinical Research in Psychosis, Stavanger University Hospital, 4011 Stavanger, Norway.,

    Inge Joa

100. Rheumatology Research Group, Vall d'Hebron Research Institute, Barcelona 08035, Spain.,

     Antonio Julià & Sara Marsal

101. Centre for Medical Research, The University of Western Australia, Perth WA6009, Australia.,

     Luba Kalaydjieva

102. The Perkins Institute for Medical Research, The University of Western Australia, Perth WA6009, Australia.,

     Luba Kalaydjieva & Assen V. Jablensky

103. Department of Medical Genetics, Medical University, Sofia 1431, Bulgaria.,

     Sena Karachanak-Yankova & Draga Toncheva

104. Department of Psychology, University of Colorado Boulder, Boulder, 80309, Colorado, USA

     Matthew C. Keller

105. Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario M5T 1R8, Canada.,

     James L. Kennedy, Clement C. Zai & Jo Knight

106. Department of Psychiatry, University of Toronto, Toronto, Ontario M5T 1R8, Canada.,

     James L. Kennedy, Clement C. Zai & Jo Knight

107. Institute of Medical Science, University of Toronto, Toronto, Ontario M5S 1A8, Canada.,

     James L. Kennedy & Jo Knight

108. Institute of Molecular Genetics, Russian Academy of Sciences, Moscow 123182, Russia.,

     Andrey Khrunin, Svetlana Limborska & Petr Slominsky

109. Latvian Biomedical Research and Study Centre, Riga, LV-1067, Latvia.,

     Janis Klovins & Liene Nikitina-Zake

110. Department of Psychiatry and Zilkha Neurogenetics Institute, Keck School of Medicine at University of Southern California, Los Angeles, 90089, California, USA

     James A. Knowles, Michele T. Pato & Carlos N. Pato

111. Faculty of Medicine, Vilnius University, LT-01513 Vilnius, Lithuania.,

     Vaidutis Kucinskas & Zita Ausrele Kucinskiene

112. Department of Biology and Medical Genetics, 2nd Faculty of Medicine and University Hospital Motol, 150 06 Prague, Czech Republic.,

     Hana Kuzelova-Ptackova & Milan Macek Jr

113. Department of Child and Adolescent Psychiatry, Pierre and Marie Curie Faculty of Medicine, Paris 75013, France.,

     Claudine Laurent

114. Duke-NUS Graduate Medical School, Singapore 169857.,

     Jimmy Lee Chee Keong

115. Department of Psychiatry, Hadassah-Hebrew University Medical Center, Jerusalem 91120, Israel.,

     Bernard Lerer

116. Centre for Genomic Sciences, The University of Hong Kong, Hong Kong, China

     Miaoxin Li & Pak C. Sham

117. Mental Health Centre and Psychiatric Laboratory, West China Hospital, Sichuan University, Chengdu, 610041 Sichuan, China.,

     Tao Li & Qiang Wang

118. Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, 21205, Maryland, USA

     Kung-Yee Liang

119. Department of Psychiatry, Columbia University, New York, 10032, New York, USA

     Jeffrey Lieberman & T. Scott Stroup

120. Priority Centre for Translational Neuroscience and Mental Health, University of Newcastle, Newcastle NSW 2300, Australia.,

     Carmel M. Loughland & Ulrich Schall

121. Department of Genetics and Pathology, International Hereditary Cancer Center, Pomeranian Medical University in Szczecin, 70-453 Szczecin, Poland.,

     Jan Lubinski

122. Department of Mental Health and Substance Abuse Services; National Institute for Health and Welfare, P.O. BOX 30, FI-00271 Helsinki, Finland.,

     Jouko Lönnqvist & Jaana Suvisaari

123. National Institute for Health and Welfare, P.O. BOX 30, FI-00271 Helsinki, Finland.,

     Jouko Lönnqvist & Jaana Suvisaari

124. Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, 21205, Maryland, USA

     Brion S. Maher

125. Department of Psychiatry, University of Bonn, D-53127 Bonn, Germany.,

     Wolfgang Maier

126. Centre National de la Recherche Scientifique, Laboratoire de Génétique Moléculaire de la Neurotransmission et des Processus Neurodégénératifs, Hôpital de la Pitié Salpêtrière, 75013 Paris, France.,

     Jacques Mallet

127. Department of Genomics Mathematics, University of Bonn, D-53127 Bonn, Germany.,

     Manuel Mattheisen

128. Research Unit, Sørlandet Hospital, 4604 Kristiansand, Norway.,

     Morten Mattingsdal

129. Department of Psychiatry, Harvard Medical School, Boston, 02115, Massachusetts, USA

     Robert W. McCarley, Raquelle I. Mesholam-Gately, Larry J. Seidman & Tracey L. Petryshen

130. VA Boston Health Care System, Brockton, 02301, Massachusetts, USA

     Robert W. McCarley

131. Department of Psychiatry, National University of Ireland Galway, Co. Galway, Ireland

     Colm McDonald

132. Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH16 4SB, UK.,

     Andrew M. McIntosh

133. Division of Psychiatry, University of Edinburgh, Edinburgh EH16 4SB, UK.,

     Andrew M. McIntosh & Douglas H. R. Blackwood

134. Division of Mental Health and Addiction, Oslo University Hospital, 0424 Oslo, Norway.,

     Ingrid Melle & Ole A. Andreassen

135. Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, 02114, Massachusetts, USA

     Raquelle I. Mesholam-Gately & Larry J. Seidman

136. Estonian Genome Center, University of Tartu, Tartu 50090, Estonia.,

     Andres Metspalu, Lili Milani, Mari Nelis & Tõnu Esko

137. School of Psychology, University of Newcastle, Newcastle NSW 2308, Australia.,

     Patricia T. Michie

138. First Psychiatric Clinic, Medical University, Sofia 1431, Bulgaria.,

     Vihra Milanova

139. Department P, Aarhus University Hospital, DK-8240 Risskov, Denmark.,

     Ole Mors & Anders D. Børglum

140. Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin 2, Ireland.,

     Kieran C. Murphy

141. King’s College London, London SE5 8AF, UK.,

     Robin M. Murray & John Powell

142. Maastricht University Medical Centre, South Limburg Mental Health Research and Teaching Network, EURON, 6229 HX Maastricht, The Netherlands.,

     Inez Myin-Germeys & Jim Van Os

143. Institute of Translational Medicine, University of Liverpool, Liverpool L69 3BX, UK.,

     Bertram Müller-Myhsok

144. Max Planck Institute of Psychiatry, 80336 Munich, Germany.,

     Bertram Müller-Myhsok

145. Munich Cluster for Systems Neurology (SyNergy), 80336 Munich, Germany.,

     Bertram Müller-Myhsok

146. Department of Psychiatry and Psychotherapy, Jena University Hospital, 07743 Jena, Germany.,

     Igor Nenadic

147. Department of Psychiatry, Queensland Brain Institute and Queensland Centre for Mental Health Research, University of Queensland, Brisbane, Queensland, St Lucia QLD 4072, Australia.,

     Deborah A. Nertney

148. Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, 21205, Maryland, USA

     Gerald Nestadt & Ann E. Pulver

149. Department of Psychiatry, Trinity College Dublin, Dublin 2, Ireland.,

     Kristin K. Nicodemus

150. Eli Lilly and Company,Lilly Corporate Center, Indianapolis, 46285, Indiana, USA

     Laura Nisenbaum

151. Department of Clinical Sciences, Psychiatry, Umeå University, SE-901 87 Umeå, Sweden.,

     Annelie Nordin & Rolf Adolfsson

152. DETECT Early Intervention Service for Psychosis, Blackrock, Co. Dublin, Ireland.,

     Eadbhard O’Callaghan

153. Centre for Public Health, Institute of Clinical Sciences, Queen’s University Belfast, Belfast BT12 6AB, UK.,

     F. Anthony O’Neill

154. Lawrence Berkeley National Laboratory, University of California at Berkeley, Berkeley, 94720, California, USA

     Sang-Yun Oh

155. Institute of Psychiatry, King’s College London, London SE5 8AF, UK.,

     Jim Van Os

156. Melbourne Neuropsychiatry Centre, University of Melbourne & Melbourne Health, Melbourne, Vic 3053, Australia.,

     Christos Pantelis

157. Department of Psychiatry, University of Helsinki, P.O. Box 590, FI-00029 HUS, Helsinki, Finland.,

     Tiina Paunio

158. Public Health Genomics Unit, National Institute for Health and Welfare, P.O. BOX 30, FI-00271 Helsinki, Finland,

     Tiina Paunio & Olli Pietiläinen

159. Medical Faculty, University of Belgrade, 11000 Belgrade, Serbia.,

     Milica Pejovic-Milovancevic

160. Department of Psychiatry, University of North Carolina, Chapel Hill, 27599-7160, North Carolina, USA

     Diana O. Perkins & Patrick F. Sullivan

161. Institute for Molecular Medicine Finland, FIMM, University of Helsinki, P.O. Box 20FI-00014, Helsinki, Finland,

     Olli Pietiläinen & Aarno Palotie

162. Department of Epidemiology, Harvard School of Public Health, Boston, 02115, Massachusetts, USA

     Alkes Price

163. Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK.,

     Digby Quested

164. Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, 23298, Virginia, USA

     Mark A. Reimers & Aaron R. Wolen

165. Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, 10029, New York, USA

     Panos Roussos & Pamela Sklar

166. PharmaTherapeutics Clinical Research, Pfizer Worldwide Research and Development, Cambridge, 02139, Massachusetts, USA

     Christian R. Schubert & Jens R. Wendland

167. Department of Psychiatry and Psychotherapy, University of Gottingen, 37073 Göttingen, Germany.,

     Thomas G. Schulze

168. Psychiatry and Psychotherapy Clinic, University of Erlangen, 91054 Erlangen, Germany.,

     Sibylle G. Schwab

169. Hunter New England Health Service, Newcastle NSW 2308, Australia.,

     Rodney J. Scott

170. School of Biomedical Sciences, University of Newcastle, Newcastle NSW 2308, Australia.,

     Rodney J. Scott

171. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, 20892, Maryland, USA

     Jianxin Shi

172. University of Iceland, Landspitali, National University Hospital, 101 Reykjavik, Iceland.,

     Engilbert Sigurdsson

173. Department of Psychiatry and Drug Addiction, Tbilisi State Medical University (TSMU), N33, 0177 Tbilisi, Georgia.,

     Teimuraz Silagadze

174. Research and Development, Bronx Veterans Affairs Medical Center, New York, 10468, New York, USA

     Jeremy M. Silverman

175. Wellcome Trust Centre for Human Genetics, Oxford OX3 7BN, UK.,

     ChrisC. A. Spencer

176. deCODE Genetics, 101 Reykjavik, Iceland.,

     Hreinn Stefansson, Stacy Steinberg & Kari Stefansson

177. Department of Clinical Neurology, Medical University of Vienna, 1090 Wien, Austria.,

     Elisabeth Stogmann & Fritz Zimprich

178. Lieber Institute for Brain Development, Baltimore, 21205, Maryland, USA

     Richard E. Straub & Daniel R. Weinberger

179. Department of Medical Genetics, University Medical Centre Utrecht, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands.,

     Eric Strengman

180. Berkshire Healthcare NHS Foundation Trust, Bracknell RG12 1BQ, UK.,

     Srinivas Thirumalai

181. Section of Psychiatry, University of Verona, 37134 Verona, Italy.,

     Sarah Tosato

182. Department of Psychiatry, University of Oulu, P.O. Box 5000, 90014, Finland.,

     Juha Veijola

183. University Hospital of Oulu, P.O. Box 20, 90029 OYS, Finland.,

     Juha Veijola

184. Health Research Board, Dublin 2, Ireland.,

     Dermot Walsh

185. School of Psychiatry and Clinical Neurosciences, The University of Western Australia, Perth WA6009, Australia.,

     Dieter B. Wildenauer & Assen V. Jablensky

186. Computational Sciences CoE, Pfizer Worldwide Research and Development, Cambridge, 02139, Massachusetts, USA

     Hualin Simon Xi

187. Human Genetics, Genome Institute of Singapore, A*STAR, Singapore 138672.,

     Jianjun Liu

188. Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, 10029, New York, USA

     Joseph D. Buxbaum

189. Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, 52428 Juelich, Germany.,

     Sven Cichon

190. Department of Genetics, The Hebrew University of Jerusalem, 91905 Jerusalem, Israel.,

     Ariel Darvasi

191. Neuroscience Discovery and Translational Area, Pharma Research and Early Development, F. Hoffman-La Roche, CH-4070 Basel, Switzerland.,

     Enrico Domenici

192. Centre for Clinical Research in Neuropsychiatry, School of Psychiatry and Clinical Neurosciences, The University of Western Australia, Medical Research Foundation Building, Perth WA6000, Australia.,

     Assen V. Jablensky

193. Departments of Psychiatry and Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, 23298, Virginia, USA

     Kenneth S. Kendler & Brien P. Riley

194. The Feinstein Institute for Medical Research, Manhasset, 11030, New York, USA

     Todd Lencz & Anil K. Malhotra

195. The Hofstra NS-LIJ School of Medicine, Hempstead, 11549, New York, USA

     Todd Lencz & Anil K. Malhotra

196. The Zucker Hillside Hospital, Glen Oaks, 11004, New York, USA

     Todd Lencz & Anil K. Malhotra

197. Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117597, Singapore.,

     Jianjun Liu

198. Queensland Centre for Mental Health Research, University of Queensland, Brisbane 4076, Queensland, Australia.,

     Bryan J. Mowry

199. Center for Human Genetic Research and Department of Psychiatry, Massachusetts General Hospital, Boston, 02114, Massachusetts, USA

     Tracey L. Petryshen

200. Department of Child and Adolescent Psychiatry, Erasmus University Medical Centre, Rotterdam 3000, The Netherlands.,

     Danielle Posthuma

201. Department of Complex Trait Genetics, Neuroscience Campus Amsterdam, VU University Medical Center Amsterdam, Amsterdam 1081, The Netherlands.,

     Danielle Posthuma

202. Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University, Amsterdam 1081, The Netherlands.,

     Danielle Posthuma

203. University of Aberdeen, Institute of Medical Sciences, Aberdeen AB25 2ZD, UK.,

     David St Clair

204. Departments of Psychiatry, Neurology, Neuroscience and Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, 21205, Maryland, USA

     Daniel R. Weinberger

205. Department of Clinical Medicine, University of Copenhagen, Copenhagen 2200, Denmark.,

     Thomas Werge

Consortia

Contributions

The individual studies or consortia contributing to the GWAS meta-analysis were led by R.A., O.A.A., D.H.R.B., A.D.B., E. Bramon, J.D.B., A.C., D.A.C., S.C., A.D., E. Domenici, H.E., T.E., P.V.G., M.G., H.G., C.M.H., N.I., A.V.J., E.G.J., K.S.K., G.K., J. Knight, T. Lencz, D.F.L., Q.S.L., J. Liu, A.K.M., S.A.M., A. McQuillin, J.L.M., P.B.M., B.J.M., M.M.N., M.C.O’D., R.A.O., M.J.O., A. Palotie, C.N.P., T.L.P., M.R., B.P.R., D.R., P.C.S, P. Sklar. D.St.C., P.F.S., D.R.W., J.R.W., J.T.R.W. and T.W. Together with the core statistical analysis group led by M.J.D. comprising S.R., B.M.N. and P.A.H., this group comprised the management group led by M.C.O’D. who were responsible for the management of the study and the overall content of the manuscript. Additional analyses and interpretations were contributed by E.A., B.B.-S., D.K., K.-H.F., M. Fromer, H.H., P.L., P.B.M., S.M.P., T.H.P., N.R.W. and P.M.V. The phenotype supervisory group comprised A.C., A.H.F., P.V.G., K.K.K. and B.J.M. D.A.C. led the candidate selected genes subgroup comprised of M.J.D., E. Dominici, J.A.K., A.M.H., M.C.O’D, B.P.R., D.R., E.M.S. and P. Sklar. Replication results were provided by S.S., H.S. and K.S. The remaining authors contributed to the recruitment, genotyping, or data processing for the contributing components of the meta-analysis. A.C., M.J.D., B.M.N., S.R., P.F.S. and M.C.O’D. took responsibility for the primary drafting of the manuscript which was shaped by the management group. All other authors saw, had the opportunity to comment on, and approved the final draft.

Corresponding author

Correspondence toMichael C. O’Donovan.

Competing interests

CFI statement–Several of the authors are employees of the following pharmaceutical companies; Pfizer (C.R.S., J.R.W., H.S.X.), F.Hoffman-La Roche (E.D., L.E.), Eli Lilly (D.A.C., Y.M., L.N.) and Janssen (S.G., D.W., Q.S.L.; also N.C. an ex-employee). Others are employees of deCODE genetics (S.S, H.S., K.S.). None of these companies influenced the design of the study, the interpretation of the data, or the amount of data reported, or financially profit by publication of the results which are pre-competitive. The other authors declare no competing interests.

Results can be downloaded from the Psychiatric Genomics Consortium website (http://pgc.unc.edu) and visualized using Ricopili (http://www.broadinstitute.org/mpg/ricopili). Genotype data for the samples where the ethics permit deposition are available upon application from the NIMH Genetics Repository (https://www.nimhgenetics.org).

A list of authors and affiliations appear in theSupplementary Information.

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