Abstract

We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05–21.6; P=1 × 10−4) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P=8.4 × 10−7). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08–1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.

Introduction

Amyotrophic lateral sclerosis (ALS) is a late-onset neurodegenerative condition characterized by progressive loss of upper and lower motor neurons, leading to death from respiratory failure in 70% of patients within 3 years of symptom onset. Although ALS is often described as a primarily motor-system disease, extramotor involvement occurs in up to 50% of cases, with prominent executive and behavioural impairment, and behavioural variant frontotemporal dementia (FTD) in up to 14% of cases1. A neuropsychiatric prodrome has been described in some people with ALS–FTD, and higher rates of schizophrenia and suicide have been reported in first and second degree relatives of those with ALS, particularly in kindreds associated with the C9orf72 hexanucleotide repeat expansion2. These clinical and epidemiological observations suggest that ALS and schizophrenia may share heritability.

ALS and schizophrenia both have high heritability estimates (0.65 and 0.64, respectively)3,4; however the underlying genetic architectures of these heritable components appear to differ. Analysis of large genome-wide association study (GWAS) datasets has implicated over 100 independent risk loci for schizophrenia5 and estimated that a substantial proportion (23%) of the variance in underlying liability for schizophrenia is due to additive polygenic risk (many risk-increasing alleles of low individual effect combining to cause disease) conferred by common genetic variants6. This proportion, the single nucleotide polymorphism (SNP)-based heritability, is lower in ALS (8.2%), in which fewer than ten risk loci have been identified by GWAS7. Nevertheless, both diseases have polygenic components, but the extent to which they overlap has not been investigated.

Recently, methods to investigate overlap between polygenic traits using GWAS data have been developed8,9,10. These methods assess either pleiotropy (identical genetic variants influencing both traits) or genetic correlation (identical alleles influencing both traits). Genetic correlation is related to heritability; for both measures, binary traits such as ALS and schizophrenia are typically modelled as extremes of an underlying continuous scale of liability to develop the trait. If two binary traits are genetically correlated, their liabilities covary, and this covariance is determined by both traits having identical risk alleles at overlapping risk loci. Studies of pleiotropy and genetic correlation have provided insights into the overlapping genetics of numerous traits and disorders, although none to date has implicated shared polygenic risk between neurodegenerative and neuropsychiatric disease. Here, we apply several techniques to identify and dissect the polygenic overlap between ALS and schizophrenia. We provide evidence for genetic correlation between the two disorders which is unlikely to be driven by diagnostic misclassification and we demonstrate a lack of polygenic overlap between ALS and other neuropsychiatric and neurological conditions, which could be due to limited power given the smaller cohort sizes for these studies.

Results

Genetic correlation between ALS and schizophrenia

To investigate the polygenic overlap between ALS and schizophrenia, we used individual-level and summary data from GWAS for ALS7 (36,052 individuals) and schizophrenia5 (79,845 individuals). At least 5,582 control individuals were common to both datasets, but for some cohorts included in the schizophrenia dataset this could not be ascertained so this number is likely to be higher. For ALS, we used summary data from both mixed linear model association testing11 and meta-analysis of cohort-level logistic regression12. We first used linkage disequilibrium (LD) score regression with ALS and schizophrenia summary statistics; this technique models, for polygenic traits, a linear relationship between a SNP’s LD score (the amount of genetic variation that it captures) and its GWAS test statistic13. This distinguishes confounding from polygenicity in GWAS inflation and the regression coefficient can be used to estimate the SNP-based heritability (hS2) for single traits13. In the bivariate case, the regression coefficient estimates genetic covariance (ρg) for pairs of traits, from which genetic correlation (rg) is estimated8; these estimates are unaffected by sample overlap between traits. Using constrained intercept LD score regression with mixed linear model ALS summary statistics, we estimated the liability-scale SNP-based heritability of ALS to be 8.2% (95% confidence interval=7.2–9.1; mean χ2=1.13; all ranges reported below indicate 95% confidence intervals), replicating previous estimates based on alternative methods7. Estimates based on ALS meta-analysis summary statistics and free-intercept LD score regression with mixed linear model summary statistics were lower (Supplementary Table 1), resulting in higher genetic correlation estimates (Supplementary Table 2); for this reason, we conservatively use constrained intercept genetic correlation estimates for ALS mixed linear model summary statistics throughout the remainder of this paper. Heritability estimates for permuted ALS data were null (Supplementary Table 1).

LD score regression estimated the genetic correlation between ALS and schizophrenia to be 14.3% (7.05–21.6; P=1 × 10−4). Results were similar for a smaller schizophrenia cohort of European ancestry (21,856 individuals)14, indicating that the inclusion of individuals of Asian ancestry in the schizophrenia cohort did not bias this result (Supplementary Fig. 1). In addition to schizophrenia, we estimated genetic correlation with ALS using GWAS summary statistics for bipolar disorder15, major depressive disorder16, attention deficit-hyperactivity disorder17, autism spectrum disorder17, Alzheimer's disease (Supplementary Note 1)18, multiple sclerosis19 and adult height20, finding no significant genetic correlation between ALS and any secondary trait other than schizophrenia (Fig. 1; Supplementary Table 2).

Figure 1: Genetic correlation between ALS and eight secondary traits.
Figure 1

Error bars indicating 95% confidence intervals and P-values were calculated by the LD score regression software using a block jackknife procedure. Secondary traits are: AD, Alzheimer’s disease; ADHD, attention deficit-hyperactivity disorder; ASD, autism spectrum disorder; BPD, bipolar disorder; MDD, major depressive disorder; MS, multiple sclerosis; SCZ, schizophrenia.

Polygenic risk score analysis

We supported the positive genetic correlation between ALS and schizophrenia by analysis of polygenic risk for schizophrenia in the ALS cohort. Polygenic risk scores (PRS) are per-individual scores based on the sum of alleles associated with one phenotype, weighted by their effect size, measured in an independent target sample of the same or a different phenotype10. PRS calculated on schizophrenia GWAS summary statistics for twelve P-value thresholds (PT) explained up to 0.12% (PT=0.2, P=8.4 × 10−7) of the phenotypic variance in a subset of the individual-level ALS genotype data that had all individuals removed that were known or suspected to be present in the schizophrenia cohort (Fig. 2; Supplementary Table 5). ALS cases had on average higher PRS for schizophrenia compared to healthy controls and harbouring a high schizophrenia PRS for PT=0.2 significantly increased the odds of being an ALS patient in our cohort (Fig. 3; Supplementary Table 6). Permutation of case–control labels reduced the explained variance to values near zero (Supplementary Fig. 3).

Figure 2: Analysis of PRS for schizophrenia in a target sample of 10,032 ALS cases and 16,627 healthy controls.
Figure 2

P-value thresholds (PT) for schizophrenia SNPs are shown on the x axis, where the number of SNPs increases with a more lenient PT. Δ Explained variances (Nagelkerke R2, shown as a %) of a generalized linear model including schizophrenia-based PRS versus a baseline model without polygenic scores (blue bars) are shown for each PT. −Log10 P-values of Δ explained variance per PT (red dots) represent P-values from the binomial logistic regression of ALS phenotype on PRS, accounting for LD (Supplementary Table 4) and including sex and significant principal components as covariates (Supplementary Fig. 2). Values are provided in Supplementary Table 5.

Figure 3: Odds ratio for ALS by PRS deciles for schizophrenia.
Figure 3

The figure applies to schizophrenia P-value threshold (PT)=0.2. The PRS for this threshold were converted to ten deciles containing near identical numbers of individuals. Decile 1 contained the lowest scores and decile 10 contained the highest scores, where decile 1 was the reference and deciles 2–10 were dummy variables to contrast to decile 1 for OR calculation. The case:control ratio per decile is indicated with grey bars. Error bars indicate 95% confidence intervals. Significant differences from decile 1 were determined by logistic regression of ALS phenotype on PRS decile, including sex and principal components as covariates and are indicated by *P<0.05 or ***P<0.001.

Modelling misdiagnosis and comorbidity

Using BUHMBOX21, a tool that distinguishes true genetic relationships between diseases (pleiotropy) from spurious relationships resulting from heterogeneous mixing of disease cohorts, we determined that misdiagnosed cases in the schizophrenia cohort (for example, young-onset FTD–ALS) did not drive the genetic correlation estimate between ALS and schizophrenia (P=0.94). Assuming a true genetic correlation of 0%, we estimated the required rate of misdiagnosis of ALS as schizophrenia to be 4.86% (2.47–7.13) to obtain the genetic correlation estimate of 14.3% (7.05–21.6; Supplementary Table 7), which we consider to be too high to be likely. However, if ALS and schizophrenia are genetically correlated, more comorbidity would be expected than if the genetic correlation was 0%. Modelling our observed genetic correlation of 14.3% (7.05–21.6), we estimated the odds ratio for having above-threshold liability for ALS given above-threshold liability for schizophrenia to be 1.17 (1.08–1.26), and the same for schizophrenia given ALS (Supplementary Fig. 4). From a clinical perspective, to achieve 80% power to detect a significant (α=0.05) excess of schizophrenia in the ALS cohort as a result of this genetic correlation, the required population-based incident cohort size is 16,448 ALS patients (7,310–66,670).

Pleiotropic risk loci

We leveraged the genetic correlation between ALS and schizophrenia to discover novel ALS-associated genomic loci by conditional false discovery rate (cFDR) analysis9,22 (Fig. 4; Supplementary Table 8). Five loci already known to be involved in ALS were identified (corresponding to MOBP, C9orf72, TBK1, SARM1 and UNC13A) along with five potential novel loci at cFDR<0.01 (CNTN6, TNIP1, PPP2R2D, NCKAP5L and ZNF295-AS1). No gene set was significantly enriched (after Bonferroni correction) in genome-wide cFDR values when analysed using MAGENTA.

Figure 4: Pleiotropy-informed ALS risk loci determined by analysis of cFDR in ALS GWAS P-values given schizophrenia GWAS P-values (cFDRALS|SCZ).
Figure 4

Each point denotes a SNP; its x axis position corresponds to its chromosomal location and its height indicates the extent of association with ALS by cFDR analysis. The solid line indicates the threshold cFDR=0.01. Any gene whose role in ALS is already established is in bold. A complete list of all loci at cFDR0.05 is provided in Supplementary Table 8.

Discussion

There is evolving clinical, epidemiological and biological evidence for an association between ALS and psychotic illness, particularly schizophrenia. Genetic evidence of overlap to date has been based primarily on individual genes showing Mendelian inheritance, in particular the C9orf72 hexanucleotide repeat expansion, which is associated with ALS and FTD, and with psychosis in relatives of ALS patients2. In this study, we have replicated SNP-based heritability estimates for ALS and schizophrenia using GWAS summary statistics, and have for the first time demonstrated significant overlap between the polygenic components of both diseases, estimating the genetic correlation to be 14.3%. We have carefully controlled for confounding bias, including population stratification and shared control samples, and have shown through analysis of polygenic risk scores that the overlapping polygenic risk applies to SNPs that are modestly associated with both diseases. Given that our genetic correlation estimate relates to the polygenic components of ALS (hS2=8.2%) and schizophrenia (hS2=23%) and these estimates do not represent all heritability for both diseases, the accuracy of using schizophrenia-based PRS to predict ALS status in any patient is expected to be low (Nagelkerke’s R2=0.12% for PT=0.2), although statistically significant (P=8.4 × 10−7). Nevertheless, the positive genetic correlation of 14.3% indicates that the direction of effect of risk-increasing and protective alleles is consistently aligned between ALS and schizophrenia, suggesting convergent biological mechanisms between the two diseases.

Although phenotypically heterogeneous, both ALS and schizophrenia are clinically recognizable as syndromes23,24. The common biological mechanisms underlying the association between the two conditions are not well understood, but are likely associated with disruption of cortical networks. Schizophrenia is a polygenic neurodevelopmental disorder characterized by a combination of positive symptoms (hallucinations and delusions), negative symptoms (diminished motivation, blunted affect, reduction in spontaneous speech and poor social functioning) and impairment over a broad range of cognitive abilities25. ALS is a late onset complex genetic disease characterized by a predominantly motor phenotype with recently recognized extra-motor features in 50% of patients, including cognitive impairment1. It has been suggested that the functional effects of risk genes in schizophrenia converge by modulating synaptic plasticity, and influencing the development and stabilization of cortical microcircuitry5. In this context, our identification of CNTN6 (contactin 6, also known as NB-3, a neural adhesion protein important in axon development)26 as a novel pleiotropy-informed ALS-associated locus supports neural network dysregulation as a potential convergent mechanism of disease in ALS and schizophrenia.

No significantly enriched biological pathway or ontological term was identified within genome-wide cFDR values using MAGENTA. Low inflation in ALS GWAS statistics, coupled with a rare variant genetic architecture7, render enrichment-based biological pathway analyses with current sample sizes challenging. Nevertheless, nine further loci were associated with ALS risk at cFDR <0.01. Of these, MOBP, C9orf72, TBK1, SARM1 and UNC13A have been described previously in ALS and were associated by cFDR analysis in this study owing to their strong association with ALS through GWAS7. The remaining four loci (TNIP1, PPP2R2D, NCKAP5L and ZNF295-AS1) are novel associations and may represent pleiotropic disease loci. TNIP1 encodes TNFAIP3 interacting protein 1 and is involved in autoimmunity and tissue homoeostasis27. The protein product of PPP2R2D is a regulatory subunit of protein phosphatase 2 and has a role in PI3K-Akt signalling and mitosis28. NCKAP5L is a homologue of NCKAP5, encoding NAP5, a proline-rich protein that has previously been implicated in schizophrenia, bipolar disorder and autism29,30. ZNF295-AS1 is a noncoding RNA31. Further investigation into the biological roles of these genes may yield novel insight into the pathophysiology of certain subtypes of ALS and schizophrenia, and as whole-genome and exome datasets become available in the future for appropriately large ALS case–control cohorts, testing for burden of rare genetic variation across these genes will be particularly instructive, especially given the role that rare variants appear to play in the pathophysiology of ALS7.

Our data suggest that other neuropsychiatric conditions (bipolar disorder, autism and major depression) do not share polygenic risk with ALS. This finding contrasts with our recent observations from family aggregation studies and may be unexpected given the extensive genetic correlation between neuropsychiatric conditions6. This could relate to statistical power conferred by secondary phenotype cohort sizes, and future studies with larger sample sizes will shed further light on the relationship between ALS and neuropsychiatric disease. It is also possible that the current study underestimates genetic correlations due to the substantial role that rare variants play in the genetic architecture of ALS7 and future fine-grained studies examining heritability and genetic correlation in low-minor allele frequency and low-LD regions may identify a broader relationship between ALS and neuropsychiatric diseases.

A potential criticism of this study is that the polygenic overlap between ALS and schizophrenia could be driven by misdiagnosis, particularly in cases of ALS–FTD, which can present in later life as a psychotic illness and could be misdiagnosed as schizophrenia. This is unlikely, as strict diagnostic criteria are required for inclusion of samples in the schizophrenia GWAS dataset5. Furthermore, since core schizophrenia symptoms are usually diagnosed during late adolescence, a misdiagnosis of FTD-onset ALS–FTD as schizophrenia is unlikely. In this study, we found no evidence for misdiagnosis of ALS as schizophrenia (BUHMBOX P=0.94) and we estimated that a misdiagnosis of 4.86% of ALS cases would be required to spuriously observe a genetic correlation of 14.3%, which is not likely to occur in clinical practice. We are therefore confident that this genetic correlation estimate reflects a genuine polygenic overlap between the two diseases and is not a feature of cohort ascertainment, but the possibility of some misdiagnosis in either cohort cannot be entirely excluded based on available data.

A positive genetic correlation between ALS and schizophrenia predicts an excess of patients presenting with both diseases. Most neurologists and psychiatrists, however, will not readily acknowledge that these conditions co-occur frequently. Our genetic correlation estimate confers an odds ratio of 1.17 (1.08–1.26) for harbouring above-threshold liability for ALS given schizophrenia (or vice versa) and a lifetime risk of 1:34,336 for both phenotypes together. Thus, a very large incident cohort of 16,448 ALS patients (7,310–66,670), with detailed phenotype information, would be required to have sufficient power to detect an excess of schizophrenia within an ALS cohort. Coupled with reduced life expectancy in patients with schizophrenia32, this may explain the relative dearth of epidemiological studies to date providing clinical evidence of excess comorbidity. Moreover, it has also been proposed that prolonged use of antipsychotic medication may protect against developing all of the clinical features of ALS33, which would reduce the rate of observed comorbidity. Considering our novel evidence for a genetic relationship between ALS and schizophrenia, this underscores the intriguing possibility that therapeutic strategies for each condition may be useful in the other, and our findings provide rationale to consider the biology of ALS and schizophrenia as related in future drug development studies. Indeed, the glutamate-modulating ALS therapy riluzole has shown efficacy as an adjunct to risperidone, an antipsychotic medication, in reducing the negative symptoms of schizophrenia34.

In conclusion, we have estimated the genetic correlation between ALS and schizophrenia to be 14.3% (7.05–21.6), providing molecular genetic support for our epidemiological observation of psychiatric endophenotypes within ALS kindreds. To our knowledge, this is the first study to show genetic correlation derived from polygenic overlap between neurodegenerative and neuropsychiatric phenotypes. The presence of both apparent monogenic C9orf72-driven overlap2 and polygenic overlap in the aetiology of ALS and schizophrenia suggests the presence of common biological processes, which may relate to disruption of cortical circuitry. As both ALS and schizophrenia are heterogeneous conditions, further genomic, biological and clinical studies are likely to yield novel insights into the pathological processes for both diseases and will provide clinical sub-stratification parameters that could drive novel drug development for both neurodegenerative and psychiatric conditions.

Methods

Study population and genetic data

For ALS, 7,740,343 SNPs genotyped in 12,577 ALS patients and 23,475 healthy controls of European ancestry organized in 27 platform- and country-defined strata were used7. The schizophrenia dataset comprised GWAS summary statistics for 9,444,230 SNPs originally genotyped in 34,241 patients and 45,604 controls of European and Asian ancestry5. For LD score regression, GWAS summary statistics were generated for the ALS cohort using mixed linear model association testing implemented in Genome-wide Complex Trait Analysis11 or logistic regression combined with cross-stratum meta-analysis using METAL12. To evaluate sample overlap for PRS and cFDR analyses, we also obtained individual-level genotype data for 27,647 schizophrenia cases and 33,675 controls from the schizophrenia GWAS (Psychiatric Genomics Consortium5 and dbGaP accession number phs000021.v3.p2). Using 88,971 LD-pruned (window size 200 SNPs; shift 20 SNPs; r2>0.25) SNPs in both datasets (INFO score>0.8; MAF>0.2), with SNPs in high-LD regions removed (Supplementary Table 4), samples were removed from the ALS dataset if they were duplicated or had a cryptically related counterpart (PLINK >0.1; 5,582 individuals) in the schizophrenia cohort and whole strata (representing Finnish and German samples; 3,811 individuals) were also removed if commonality with the schizophrenia cohort could not be ascertained (due to unavailability of individual-level genotype data in the schizophrenia cohort) and in which a sample overlap was suspected (Supplementary Table 3).

LD score regression

We calculated LD scores using LDSC v1.0.0 in 1 centiMorgan windows around 13,307,412 non-singleton variants genotyped in 379 European individuals (CEU, FIN, GBR, IBS and TSI populations) in the phase 1 integrated release of the 1,000 Genomes Project35. For regression weights13, we restricted LD score calculation to SNPs included in both the GWAS summary statistics and HapMap phase 3; for rg estimation in pairs of traits this was the intersection of SNPs for both traits and HapMap. Because population structure and confounding were highly controlled in the ALS summary statistics by the use of mixed linear model association tests, we constrained the LD score regression intercept to 1 for hS2 estimation in ALS, and we also estimated hS2 with a free intercept. For hS2 estimation in all other traits and for rg estimation the intercept was a free parameter. We also estimated rg using ALS meta-analysis results7 with free and constrained intercepts and with permuted data conserving population structure. Briefly, principal component analysis was carried out for each stratum using smartpca36 and the three-dimensional space defined by principal components 1–3 was equally subdivided into 1,000 cubes. Within each cube, case–control labels were randomly swapped and association statistics were re-calculated for the entire stratum using logistic regression. Study-level P-values were then calculated using inverse variance weighted fixed effect meta-analysis implemented in METAL7,12. hS2 was estimated for these meta-analysed permuted data using LD score regression (Supplementary Table 1).

Polygenic risk score analysis

We calculated PRS for 10,032 cases and 16,627 healthy controls in the ALS dataset (duplicate and suspected or confirmed related samples with the schizophrenia dataset removed), based on schizophrenia-associated alleles and effect sizes reported in the GWAS summary statistics for 6,843,674 SNPs included in both studies and in the phase 1 integrated release of the 1,000 Genomes Project35 (imputation INFO score <0.3; minor allele frequency <0.01; A/T and G/C SNPs removed). SNPs were clumped in two rounds (physical distance threshold of 250 kb and a LD threshold (R2) of>0.5 in the first round and a distance of 5,000 kb and LD threshold of >0.2 in the second round) using PLINK v1.90b3y, removing high-LD regions (Supplementary Table 4), resulting in a final set of 496,548 SNPs for PRS calculations. Odds ratios for autosomal SNPs reported in the schizophrenia summary statistics were log-converted to beta values and PRS were calculated using PLINK’s score function for twelve schizophrenia GWAS P-value thresholds (PT): 5 × 10−8, 5 × 10−7, 5 × 10−6, 5 × 10−5, 5 × 10−4, 5 × 10−3, 0.05, 0.1, 0.2, 0.3, 0.4 and 0.5. A total of 100 principal components (PCs) were generated for the ALS sample using GCTA version 1.24.4. Using R version 3.2.2, a generalized linear model was applied to model the phenotype of individuals in the ALS dataset. PCs that had a significant effect on the phenotype (P<0.0005, Bonferroni-corrected for 100 PCs) were selected (PCs 1, 4, 5, 7, 8, 10, 11, 12, 14, 36, 49).

To estimate explained variance of PRS on the phenotype, a baseline linear relationship including only sex and significant PCs as variables was modelled first:

where y is the phenotype in the ALS dataset, α is the intercept of the model with a slope β for each variable x.

Subsequently, a linear model including polygenic scores for each schizophrenia PT was calculated:

A Nagelkerke R2 value was obtained for every model and the baseline Nagelkerke R2 value was subtracted, resulting in a Δ explained variance that describes the contribution of schizophrenia-based PRS to the phenotype in the ALS dataset. PRS analysis was also performed in permuted case–control data (1,000 permutations, conserving case–control ratio) to assess whether the increased Δ explained variance was a true signal associated with phenotype. Δ explained variances and P-values were averaged across permutation analyses.

To ensure we did not over- or under-correct for population effects in our model, we tested the inclusion of up to a total of 30 PCs in the model, starting with the PC with the most significant effect on the ALS phenotype (Supplementary Fig. 2). Increasing the number of PCs initially had a large effect on the Δ explained variance, but this effect levelled out after 11 PCs. On the basis of this test we are confident that adding the 11 PCs that had a significant effect on the phenotype sufficiently accounted for possible confounding due to population differences.

For the schizophrenia PT for which we obtained the highest Δ explained variance (0.2), we subdivided observed schizophrenia-based PRS in the ALS cohort into deciles and calculated the odds ratio for being an ALS case in each decile compared to the first decile using a similar generalized linear model:

Odds ratios and 95% confidence intervals for ALS were derived by calculating the exponential function of the beta estimate of the model for each of the deciles 2–10.

Diagnostic misclassification

To distinguish the contribution of misdiagnosis from true genetic pleiotropy we used BUHMBOX21 with 417 independent ALS risk alleles in a sample of 27,647 schizophrenia patients for which individual-level genotype data were available. We also estimated the required misdiagnosis rate M of FTD–ALS as schizophrenia that would lead to the observed genetic correlation estimate as C/(C+1), where C=ρgNSCZ/NALS and NSCZ and NALS are the number of cases in the schizophrenia and ALS datasets, respectively37 (derived in Supplementary Methods 1).

Expected comorbidity

To investigate the expected comorbidity of ALS and schizophrenia given the observed genetic correlation, we modelled the distribution in liability for ALS and schizophrenia as a bivariate normal distribution with the liability-scale covariance determined by LD score regression (Supplementary Methods 2). Lifetime risks for ALS38 and schizophrenia25 of 1/400 and 1/100, respectively, were used to calculate liability thresholds above which individuals develop ALS or schizophrenia, or both. The expected proportions of individuals above these thresholds were used to calculate the odds ratio of developing ALS given schizophrenia, or vice versa (Supplementary Methods 2). The required population size to observe a significant excess of comorbidity was calculated using the binomial power equation.

Pleiotropy-informed risk loci for ALS

Using an adapted cFDR method9 that allows shared controls between cohorts22, we estimated per-SNP cFDR given LD score-corrected8 schizophrenia GWAS P-values for ALS mixed linear model summary statistics calculated in a dataset excluding Finnish and German cohorts (in which suspected control overlap could not be determined), but including all other overlapping samples (totalling 5,582). To correct for the relationship between LD and GWAS test statistics, schizophrenia summary statistics were residualized on LD score by subtracting the product of each SNP’s LD score and the univariate LD score regression coefficient for schizophrenia. cFDR values conditioned on these residualized schizophrenia GWAS P-values were calculated for mixed linear model association statistics calculated at 6,843,670 SNPs genotyped in 10,147 ALS cases and 22,094 controls. Pleiotropic genomic loci were considered statistically significant if cFDR<0.01 (following Andreassen et al.9) and were clumped with all neighbouring SNPs based on LD (r2>0.1) in the complete ALS dataset. Associated cFDR genomic regions were then mapped to the locations of known RefSeq transcripts in human genome build GRCh37. Genome-wide cFDR values were also tested for enrichment in 9,711 gene sets included in the MAGENTA software package (version 2.4, July 2011) and derived from databases such as Gene Ontology (GO, http://geneontology.org/), Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.kegg.jp/), Protein ANalysis THrough Evolutionary Relationships (PANTHER, http://www.pantherdb.org/) and INGENUITY (http://www.ingenuity.com/). SNPs were mapped to genes including 20 kb up- and downstream regions to include regulatory elements. The enrichment cutoff applied in our analysis was based on the 95th percentile of gene scores for all genes in the genome. The null distribution of gene scores for each gene set was based on 10,000 randomly sampled gene sets with equal size. MAGENTA uses a Mann–Whitney rank-sum test to assess gene-set enrichment39.

Data availability

All data used in this study are publically available and can be accessed via the studies cited in the text. Other data are available from the authors upon reasonable request.

Additional information

How to cite this article: McLaughlin, R. L. et al. Genetic correlation between amyotrophic lateral sclerosis and schizophrenia. Nat. Commun. 8, 14774 doi: 10.1038/ncomms14774 (2017).

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Acknowledgements

We acknowledge helpful contributions from Mr Gert Jan van de Vendel in the design and execution of PRS analyses. This study received support from the ALS Association; Fondation Thierry Latran; the Motor Neurone Disease Association of England, Wales and Northern Ireland; Science Foundation Ireland; Health Research Board (Ireland), The Netherlands ALS Foundation (Project MinE, to J.H.V., L.H.v.d.B.), the Netherlands Organisation for Health Research and Development (Vici scheme, L.H.v.d.B.) and ZonMW under the frame of E-Rare-2, the ERA Net for Research on Rare Diseases (PYRAMID). Research leading to these results has received funding from the European Community’s Health Seventh Framework Programme (FP7/2007–2013). A.G. is supported by the Research Foundation KU Leuven (C24/16/045). A.A.-C. received salary support from the National Institute for Health Research (NIHR) Dementia Biomedical Research Unit and Biomedical Research Centre in Mental Health at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. Samples used in this research were in part obtained from the UK National DNA Bank for MND Research, funded by the MND Association and the Wellcome Trust. We acknowledge sample management undertaken by Biobanking Solutions funded by the Medical Research Council (MRC) at the Centre for Integrated Genomic Medical Research, University of Manchester. This is an EU Joint Programme-Neurodegenerative Disease Research (JPND) Project (STRENGTH, SOPHIA). In addition to those mentioned above, the project is supported through the following funding organizations under the aegis of JPND: UK, Economic and Social Research Council; Italy, Ministry of Health and Ministry of Education, University and Research; France, L’Agence nationale pour la recherche. The work leading up to this publication was funded by the European Community’s Health Seventh Framework Programme (FP7/2007–2013; Grant Agreement Number 2,59,867). We thank the International Genomics of Alzheimer's Project (IGAP) for providing summary results data for these analyses. The investigators within IGAP provided data but did not participate in analysis or writing of this report. IGAP was made possible by the generous participation of the control subjects, the patients, and their families. The i-Select chips was funded by the French National Foundation on Alzheimer's disease and related disorders. EADI was supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Université de Lille 2 and the Lille University Hospital. GERAD was supported by the MRC (Grant No. 5,03,480), Alzheimer’s Research UK (Grant No. 5,03,176), the Wellcome Trust (Grant No. 082604/2/07/Z) and German Federal Ministry of Education and Research: Competence Network Dementia Grant no. 01GI0102, 01GI0711, 01GI0420. CHARGE was partly supported by the NIH/NIA Grant R01 AG033193 and the NIA AG081220 and AGES contract N01-AG-12,100, the NHLBI Grant R01 HL105756, the Icelandic Heart Association, and the Erasmus Medical Center and Erasmus University. ADGC was supported by the NIH/NIA Grants: U01 AG032984, U24 AG021886, U01 AG016976, and the Alzheimer's Association Grant ADGC-10–196728. The Project MinE GWAS Consortium included contributions from the PARALS registry, SLALOM group, SLAP registry, FALS Sequencing Consortium, SLAGEN Consortium and NNIPPS Study Group; the Schizophrenia Working Group of the Psychiatric Genomics Consortium included contributions from the Psychosis Endophenotypes International Consortium and Wellcome Trust Case–control Consortium. Members of these eight consortia are listed in Supplementary Note 2.

Author information

Author notes

    • Russell L. McLaughlin
    •  & Dick Schijven

    These authors contributed equally to this work

    • Jurjen J. Luykx
    • , Orla Hardiman
    •  & Jan H. Veldink

    These authors jointly supervised this work

Affiliations

  1. Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin DO2 DK07, Republic of Ireland

    • Russell L. McLaughlin
    •  & Margaret O’Brien
  2. Smurfit Institute of Genetics, Trinity College Dublin, Dublin D02 DK07, Republic of Ireland

    • Russell L. McLaughlin
    • , Daniel G. Bradley
    •  & Orla Hardiman
  3. Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht 3584 CX, The Netherlands

    • Dick Schijven
    • , Wouter van Rheenen
    • , Kristel R. van Eijk
    • , Leonard H. van den Berg
    • , Jurjen J. Luykx
    • , Jan H. Veldink
    • , Annelot M. Dekker
    • , Frank P. Diekstra
    • , Rick A. A. van der Spek
    • , Perry T. C. van Doormaal
    •  & Michael A. van Es
  4. Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht 3584 CX, The Netherlands

    • Dick Schijven
    • , René S. Kahn
    • , Roel A. Ophoff
    • , Jurjen J. Luykx
    • , Sara L. Pulit
    •  & Wiepke Cahn
  5. Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California 90095, USA

    • Roel A. Ophoff
    • , Martina Wiedau-Pazos
    •  & Rita M. Cantor
  6. Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, California 90095, USA

    • Roel A. Ophoff
    • , Gerome Breen
    •  & Nelson B. Freimer
  7. Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND), KU Leuven—University of Leuven, Leuven B-3000, Belgium

    • An Goris
  8. Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, King’s College London, London WC2R 2LS, UK

    • Ammar Al-Chalabi
    • , Aleksey Shatunov
    • , William Sproviero
    • , Ashley R. Jones
    • , Isabella Fogh
    • , Kuang Lin
    • , Christopher E. Shaw
    • , Bradley N. Smith
    •  & John Powell
  9. Department of Psychiatry, Hospital Network Antwerp (ZNA) Stuivenberg and Sint Erasmus, Antwerp 2020, Belgium

    • Jurjen J. Luykx
  10. Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, New South Wales, Australia

    • Garth A. Nicholson
    • , Dominic B. Rowe
    • , Kelly Williams
    •  & Ian Blair
  11. Concord Hospital, ANZAC Research Institute, University of Sydney, Sydney, New South Wales, Australia

    • Garth A. Nicholson
  12. The Stacey MND Laboratory, Department of Pathology, The University of Sydney, Sydney, New South Wales, Australia

    • Roger Pamphlett
  13. Brain and Mind Research Institute, The University of, Sydney, New South Wales, Australia

    • Matthew C. Kiernan
  14. Transformational Bioinformatics, Commonwealth Scientific and Industrial Research Organisation, Sydney, New South Wales, Australia

    • Denis Bauer
    •  & Tim Kahlke
  15. Department of Neurology, Academic Medical Center, Amsterdam, The Netherlands

    • Filip Eftimov
    • , Anneke J. van der Kooi
    •  & Marianne de Visser
  16. Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milano, Italy

    • Isabella Fogh
    • , Nicola Ticozzi
    • , Cinzia Tiloca
    • , Antonia Ratti
    •  & Vincenzo Silani
  17. Department of Pathophysiology and Tranplantation, ‘Dino Ferrari’ Center, Università degli Studi di Milano, Milano, Italy

    • Nicola Ticozzi
    • , Antonia Ratti
    •  & Vincenzo Silani
  18. Institut du Cerveau et de la Moelle épinière, Inserm U1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMRS1127, Paris, France

    • Stéphanie Millecamps
  19. Ramsay Generale de Santé, Hopital Peupliers, Centre SLA Ile de France, Paris, France

    • François Salachas
    •  & Vincent Meininger
  20. Institute of Physiology and Institute of Molecular Medicine, University of Lisbon, Lisbon, Portugal

    • Mamede de Carvalho
    •  & Susana Pinto
  21. Department of Neurosciences, Hospital de Santa Maria-CHLN, Lisbon, Portugal

    • Mamede de Carvalho
    •  & Susana Pinto
  22. Department of Neurology, Hospital Carlos III, Madrid, Spain

    • Jesus S. Mora
  23. Neurology Department, Hospital de la Santa Creu i Sant Pau de Barcelona, Autonomous University of Barcelona, Barcelona, Spain

    • Ricardo Rojas-García
  24. Department Neurology and Emory ALS Center, Emory University School of Medicine, Atlanta, Georgia, USA

    • Meraida Polak
    •  & Jonathan Glass
  25. Euan MacDonald Centre for Motor Neurone Disease Research, Edinburgh, UK

    • Siddharthan Chandran
    • , Shuna Colville
    •  & Robert Swingler
  26. Centre for Neuroregeneration and Medical Research Council Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK

    • Siddharthan Chandran
  27. School of Clinical and Experimental Medicine, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK

    • Karen E. Morrison
  28. Queen Elizabeth Hospital, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK

    • Karen E. Morrison
  29. Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK

    • Pamela J. Shaw
  30. Department of Molecular Neuroscience, Institute of Neurology, University College London, UK

    • John Hardy
    •  & Alan Pittman
  31. Department of Clinical Neuroscience, Institute of Neurology, University College London, UK

    • Richard W. Orrell
    •  & Katie Sidle
  32. Reta Lila Weston Institute, Institute of Neurology, University College London, UK

    • Alan Pittman
  33. Department of Neurodegenerative Diseases, Institute of Neurology, University College London, UK

    • Pietro Fratta
  34. Centre for Neuroscience and Trauma, Blizard Institute, Queen Mary University of London, London, UK

    • Andrea Malaspina
  35. North-East London and Essex Regional Motor Neuron Disease Care Centre, London, UK

    • Andrea Malaspina
  36. Department of Neurology, Medical School Hannover, Hannover, Germany

    • Susanne Petri
  37. Department of Neurology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany

    • Susanna Abdulla
  38. Institute for Clinical Neurobiology, University of Würzburg, Würzburg, Germany

    • Carsten Drepper
    •  & Michael Sendtner
  39. Charité University Hospital, Humboldt-University, Berlin, Germany

    • Thomas Meyer
  40. Department of Neurology, University of California, San Francisco, California, USA

    • Catherine Lomen-Hoerth
  41. Center for Neurodegenerative Disease Research, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA

    • Vivianna M. Van Deerlin
    •  & John Q. Trojanowski
  42. Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Pennsylvania Philadelphia, USA

    • Lauren Elman
    •  & Leo McCluskey
  43. Neurodegeneration Research Laboratory, Bogazici University, Istanbul, Turkey

    • Nazli Basak
  44. Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany

    • Thomas Meitinger
    • , Peter Lichtner
    •  & Milena Blagojevic-Radivojkov
  45. INSERM U930, Université François Rabelais, Tours, France

    • Christian R. Andres
    • , Cindy Maurel
    •  & Patrick Vourc'h
  46. APHP, Département de Pharmacologie Clinique, Hôpital de la Pitié-Salpêtrière, UPMC Pharmacologie, Paris 6, Paris, France

    • Gilbert Bensimon
    • , Christine A. M. Payan
    •  & Peter M. Andersen
  47. Department of Neurology, Ulm University, Ulm, Germany

    • Bernhard Landwehrmeyer
    • , Albert C. Ludolph
    •  & Jochen H. Weishaupt
  48. INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, Paris, France

    • Alexis Brice
  49. Genethon, CNRS UMR 8587, Evry, France

    • Safa Saker-Delye
  50. Department of Medical Genetics, L'Institut du Cerveau et de la Moelle Épinière, Hoptial Salpêtrière, Paris

    • Alexandra Dürr
  51. Department of Neurogenetics, Institute of Neurology, University College London, London, UK

    • Nicholas Wood
  52. PopGen Biobank and Institute of Epidemiology, Christian Albrechts-University Kiel, Kiel, Germany

    • Lukas Tittmann
    •  & Wolfgang Lieb
  53. Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany

    • Andre Franke
  54. Central Institute of Mental Health; Medical Faculty Mannheim, Mannheim, Germany

    • Marcella Rietschel
  55. Institute of Human Genetics, University of Bonn, Bonn, Germany

    • Sven Cichon
    • , Markus M. Nöuthen
    • , Franziska Degenhardt
    • , Stefan Herms
    • , Per Hoffmann
    •  & Andrea Hofman
  56. Department of Genomics, Life and Brain Center, Bonn, Germany

    • Sven Cichon
    • , Markus M. Nöuthen
    • , Franziska Degenhardt
    • , Stefan Herms
    • , Per Hoffmann
    •  & Andrea Hofman
  57. University Hospital Basel, University of Basel, Basel, Switzerland

    • Sven Cichon
  58. Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland

    • Sven Cichon
    • , Stefan Herms
    •  & Per Hoffmann
  59. Institute of Neuroscience and Medicine INM-1, Research Center Juelich, Juelich, Germany

    • Sven Cichon
  60. Lille University, INSERM U744, Institut Pasteur de Lille, Lille, France

    • Philippe Amouyel
  61. Bordeaux University, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique & CIC-1401, CHU de Bordeaux, Pole de Sante Publique, Bordeaux, France

    • Christophe Tzourio
    •  & Jean- François Dartigues
  62. Department of Internal Medicine, Genetics Laboratory, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands

    • Andre G. Uitterlinden
    • , Fernando Rivadeneira
    •  & Karol Estrada
  63. Department of Epidemiology, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands

    • Andre G. Uitterlinden
    • , Fernando Rivadeneira
    •  & Albert Hofman
  64. MRC Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, London, UK

    • Charles Curtis
  65. Neuromuscular Diseases Unit/ALS Clinic, Kantonsspital St Gallen, 9007 St Gallen, Switzerland

    • Markus Weber
  66. Laboratory of Experimental Neurobiology, IRCCS 'C Mondino’ National Institute of Neurology Foundation, Pavia, Italy

    • Orietta Pansarasa
    •  & Cristina Cereda
  67. Neurologic Unit, IRCCS Foundation Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy

    • Roberto Del Bo
    •  & Giacomo P. Comi
  68. Department of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases, UPO, Università del Piemonte Orientale, Novara, Italy

    • Sandra D’Alfonso
  69. Department of Neurosciences, University of Padova, Padova, Italy

    • Cinzia Bertolin
    •  & Gianni Sorarù
  70. Department of Neurology, University of Eastern Piedmont, Novara, Italy

    • Letizia Mazzini
  71. Unit of Genetics of Neurodegenerative and Metabolic Diseases, Fondazione IRCCS Istituto Neurologico ‘Carlo Besta’, Milano, Italy

    • Viviana Pensato
    •  & Cinzia Gellera
  72. ‘Rita Levi Montalcini’ Department of Neuroscience, ALS Centre, University of Torino, Turin, Italy

    • Andrea Calvo
    • , Cristina Moglia
    • , Maura Brunetti
    • , Federico Casale
    •  & Adriano Chio
  73. Azienda Ospedaliera Città della Salute e della Scienza, Torino, Italy

    • Andrea Calvo
    • , Cristina Moglia
    • , Maura Brunetti
    •  & Adriano Chio
  74. Department of Clinical research in Neurology, University of Bari ‘AMoro’, at Pia Fondazione ‘CardG Panico’, Tricase, Italy

    • Simon Arcuti
    • , Rosa Capozzo
    • , Chiara Zecca
    •  & Rosanna Tortelli
  75. NEMO Clinical Center, Serena Onlus Foundation, Niguarda Ca' Granda Hostipal, Milan, Italy

    • Christian Lunetta
  76. Medical Genetics Unit, Department of Laboratory Medicine, Niguarda Ca' Granda Hospital, Milan, Italy

    • Silvana Penco
  77. Department of Neurology, Institute of Experimental Neurology (INSPE), Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy

    • Nilo Riva
  78. University Hospital ‘Spedali Civili’, Brescia, Italy

    • Alessandro Padovani
    •  & Massimiliano Filosto
  79. Department of Neurology, Brighton and Sussex Medical School Trafford Centre for Biomedical Research, University of Sussex, Falmer, East Sussex, UK

    • P Nigel Leigh
  80. Laboratory of Neurological Diseases, Department of Neuroscience, IRCCS Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy

    • Ettore Beghi
    •  & Elisabetta Pupillo
  81. Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari ‘Aldo Moro’, Bari, Italy

    • Giancarlo Logroscino
  82. Unit of Neurodegenerative Diseases, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro’, at Pia Fondazione Cardinale G Panico, Tricase, Lecce, Italy

    • Giancarlo Logroscino
  83. Department of Neurology, University Hospital Leuven, Leuven, Belgium

    • Wim Robberecht
    •  & Philip Van Damme
  84. KU Leuven-University of Leuven, Department of Neurosciences, VIB-Vesalius Research Center, Leuven, Belgium

    • Philip Van Damme
  85. Department of Neurology, University of Massachusetts Medical School, Worcester, Massachusetts, USA

    • Robert H. Brown
    •  & John E. Landers
  86. Department of Pharmacology and Clinical Neurosience, Umeå University, Umea, Sweden

    • Peter M. Andersen
  87. Centre SLA, CHRU de Tours, Tours, France

    • Philippe Corcia
  88. Federation des Centres SLA Tours and Limoges, LITORALS, Tours, France

    • Philippe Corcia
  89. Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands

    • R Jeroen Pasterkamp
  90. Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands

    • Cathryn M. Lewis
    • , Lude Franke
    •  & Juha Karjalainen
  91. Department of Medical and Molecular Genetics, King’s College London, London, UK

    • Cathryn M. Lewis
  92. IoPPN Genomics & Biomarker Core, Translational Genetics Group, MRC Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK

    • Gerome Breen
  93. NIHR Biomedical Research Centre for Mental Health, Maudsley Hospital and Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK

    • Gerome Breen
  94. Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, 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
  95. Stanley Center for Psychiatric Research, Broad Institute of MI.T. and Harvard, Cambridge, Massachusetts, USA

    • Stephan Ripke
    • , Benjamin M. Neale
    • , Phil Lee
    • , Brendan Bulik-Sullivan
    • , Richard A. Belliveau
    • , Sarah E. Bergen
    • , Elizabeth Bevilacqua
    • , Kimberley D. Chambert
    • , Menachem Fromer
    • , Giulio Genovese
    • , Colm O’Dushlaine
    • , Edward M. Scolnick
    • , Jordan W. Smoller
    • , Steven A. McCarroll
    •  & Jennifer L. Moran
  96. Medical and Population Genetics Program, Broad Institute of MI.T. and Harvard, Cambridge, Massachusetts, USA

    • Benjamin M. Neale
    • , Hailiang Huang
    • , Tune H. Pers
    • , Jacqueline I. Goldstein
    • , Joel N. Hirschhorn
    • , Eli A. Stahl
    •  & Tõnu Esko
  97. Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA

    • Benjamin M. Neale
    • , Phil Lee
    • , Menachem Fromer
    • , Jordan W. Smoller
    •  & Aarno Palotie
  98. Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College, Dublin, Ireland

    • Aiden Corvin
    • , Paul Cormican
    • , Gary Donohoe
    • , Derek W. Morris
    •  & Michael Gill
  99. MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, 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
    • , George Kirov
    • , Michael J. Owen
    •  & Michael C. O’Donovan
  100. National Centre for Mental Health, Cardiff University, Cardiff, Wales

    • Peter A Holmans
    • , Nick Craddock
    • , Alexander L. Richards
    • , Michael J. Owen
    •  & Michael C. O’Donovan
  101. Eli Lilly and Company Limited, Erl Wood Manor, Sunninghill Road, Windlesham, Surrey, UK

    • David A. Collier
    •  & Younes Mokrab
  102. Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, London, UK

    • David A. Collier
  103. Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark

    • Tune H. Pers
  104. Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Boston, Massachusetts, USA

    • Tune H. Pers
    • , Joel N. Hirschhorn
    •  & Tõnu Esko
  105. Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden

    • Ingrid Agartz
    • , Erik Söderman
    •  & Erik G. Jönsson
  106. Department of Psychiatry, Diakonhjemmet Hospital, Oslo, Norway

    • Ingrid Agartz
  107. NORMENT, K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway

    • Ingrid Agartz
    • , Srdjan Djurovic
    • , Morten Mattingsdal
    • , Ingrid Melle
    •  & Ole A. Andreassen
  108. Centre for Integrative Register-based Research, CIRRAU, Aarhus University, Aarhus, Denmark

    • Esben Agerbo
    •  & Preben B. Mortensen
  109. National Centre for Register-based Research, Aarhus University, Aarhus, Denmark

    • Esben Agerbo
    •  & Preben B. Mortensen
  110. 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
  111. State Mental Hospital, Haar, Germany

    • Margot Albus
  112. Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, USA

    • Madeline Alexander
    • , Claudine Laurent
    •  & Douglas F. Levinson
  113. Department of Psychiatry and Behavioral Sciences, Atlanta Veterans Affairs Medical Center, Atlanta, Georgia, USA

    • Farooq Amin
  114. Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia, USA

    • Farooq Amin
  115. Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, USA

    • Silviu A. Bacanu
    • , Tim B. Bigdeli
    • , Bradley T. Webb
    •  & Brandon K. Wormley
  116. Clinical Neuroscience, Max Planck Institute of Experimental Medicine, Göttingen, Germany

    • Martin Begemann
    • , Christian Hammer
    • , Sergi Papiol
    •  & Hannelore Ehrenreich
  117. Department of Medical Genetics, University of Pécs, Pécs, Hungary

    • Judit Bene
    •  & Bela Melegh
  118. Szentagothai Research Center, University of Pécs, Pécs, Hungary

    • Judit Bene
    •  & Bela Melegh
  119. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

    • Sarah E. Bergen
    • , Anna K. Kähler
    • , Patrik K. E. Magnusson
    • , Christina M. Hultman
    •  & Patrick F. Sullivan
  120. Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA

    • Donald W. Black
  121. University Medical Center Groningen, Department of Psychiatry, University of Groningen, The Netherlands

    • Richard Bruggeman
  122. School of Nursing, Louisiana State University Health Sciences Center, New Orleans, Louisiana, USA

    • Nancy G. Buccola
  123. Athinoula A Martinos Center, Massachusetts General Hospital, Boston, Massachusetts, USA

    • Randy L. Buckner
    •  & Joshua L. Roffman
  124. Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA

    • Randy L. Buckner
  125. Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA

    • Randy L. Buckner
    •  & Joshua L. Roffman
  126. Department of Psychiatry, University of California at San Francisco, San Francisco, California, USA

    • William Byerley
  127. Department of Human Genetics, Icahn School of Medicine at Mount Sinai, New York, New York, USA

    • Guiqing Cai
    •  & Joseph D. Buxbaum
  128. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, 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
  129. Centre Hospitalier du Rouvray and INSER.M. U1079 Faculty of Medicine, Rouen, France

    • Dominique Campion
  130. Schizophrenia Research Institute, Sydney, 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
  131. School of Psychiatry, University of New South Wales, New South Wales, Sydney, Australia

    • Vaughan J. Carr
  132. Royal Brisbane and Women’s Hospital, University of Queensland, Queensland, Brisbane, Australia

    • Stanley V. Catts
  133. Institute of Psychology, Chinese Academy of Science, Beijing, China

    • Raymond C. K. Chan
  134. Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China

    • Ronald Y. L. Chan
    • , Eric Y. H. Chen
    • , Miaoxin Li
    • , Hon-Cheong So
    • , Emily H. M. Wong
    •  & Pak C. Sham
  135. State Ket Laboratory for Brain and Cognitive Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China

    • Eric Y. H. Chen
    •  & Pak C. Sham
  136. Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina, USA

    • Wei Cheng
  137. Castle Peak Hospital, Hong Kong, China

    • Eric F. C. Cheung
  138. Institute of Mental Health, Singapore, Singapore

    • Siow Ann Chong
    • , Jimmy Lee
    • , Kang Sim
    •  & Mythily Subramaniam
  139. Department of Psychiatry, Washington University, St Louis, Missouri, USA

    • C Robert Cloninger
    •  & Dragan M. Svrakic
  140. Department of Child and Adolescent Psychiatry, Pierre and Marie Curie Faculty of Medicine and Brain and Spinal Cord Institute (ICM), Paris, France

    • David Cohen
  141. Neuroscience Therapeutic Area, Janssen Research and Development, LLC, Raritan, New Jersey, USA

    • Nadine Cohen
    • , Srihari Gopal
    • , Dai Wang
    •  & Qingqin S. Li
  142. Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA

    • James J. Crowley
    • , Martilias S. Farrell
    • , Paola Giusti-Rodríguez
    • , Yunjung Kim
    • , Jin P. Szatkiewicz
    • , Stephanie Williams
    •  & Patrick F. Sullivan
  143. Department of Psychological Medicine, Queen Mary University of London, London, UK

    • David Curtis
  144. Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, UK

    • David Curtis
    • , Jonathan Pimm
    • , Hugh Gurling
    •  & Andrew McQuillin
  145. Sheba Medical Center, Tel Hashomer, Israel

    • Michael Davidson
    •  & Mark Weiser
  146. Applied Molecular Genomics Unit, VI.B. Department of Molecular Genetics, University of Antwerp, Antwerp, Belgium

    • Jurgen Del Favero
  147. Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark

    • Ditte Demontis
    • , Manuel Mattheisen
    • , Ole Mors
    •  & Anders D. Børglum
  148. Department of Biomedicine, Aarhus University, Aarhus, Denmark

    • Ditte Demontis
    • , Manuel Mattheisen
    •  & Anders D. Børglum
  149. First Department of Psychiatry, University of Athens Medical School, Athens, Greece

    • Dimitris Dikeos
    •  & George N. Papadimitriou
  150. Department of Psychiatry, University College Cork, Ireland

    • Timothy Dinan
  151. Department of Medical Genetics, Oslo University Hospital, Oslo, Norway

    • Srdjan Djurovic
  152. Cognitive Genetics and Therapy Group, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Ireland

    • Gary Donohoe
    •  & Derek W. Morris
  153. Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois, USA

    • Jubao Duan
    • , Alan R. Sanders
    •  & Pablo V. Gejman
  154. Department of Psychiatry and Behavioral Sciences, NorthShore University HealthSystem, Evanston, Illinois, USA

    • Jubao Duan
    • , Alan R. Sanders
    •  & Pablo V. Gejman
  155. Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, London, UK

    • Frank Dudbridge
  156. Department of Child and Adolescent Psychiatry, University Clinic of Psychiatry, Skopje, Republic of Macedonia

    • Naser Durmishi
  157. Department of Psychiatry, University of Regensburg, Regensburg, Germany

    • Peter Eichhammer
  158. Department of General Practice, Helsinki University Central Hospital, Helsinki, Finland

    • Johan Eriksson
  159. Folkhälsan Research Center, Helsinki, Finland

    • Johan Eriksson
  160. National Institute for Health and Welfare, Helsinki, Finland

    • Johan Eriksson
    •  & Veikko Salomaa
  161. Translational Technologies and Bioinformatics, Pharma Research and Early Development, F. Hoffman-La Roche, Basel, Switzerland

    • Laurent Essioux
  162. Department of Psychiatry, Georgetown University School of Medicine, Washington, District Of Columbia, USA

    • Ayman H. Fanous
  163. Department of Psychiatry, Keck School of Medicine of the University of Southern California, Los Angeles, California, USA

    • Ayman H. Fanous
  164. Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, Virginia, USA

    • Ayman H. Fanous
  165. Mental Health Service Line, Washington V.A. Medical Center, Washington, District Of Columbia, USA

    • Ayman H. Fanous
  166. Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany

    • Josef Frank
    • , Sandra Meier
    • , Thomas G. Schulze
    • , Jana Strohmaier
    •  & Stephanie H. Witt
  167. Department of Psychiatry, University of Colorado Denver, Aurora, Colorado, USA

    • Robert Freedman
    •  & Ann Olincy
  168. Department of Psychiatry, University of Halle, Halle, Germany

    • Marion Friedl
    • , Ina Giegling
    • , Annette M. Hartmann
    • , Bettina Konte
    •  & Dan Rujescu
  169. Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA

    • Menachem Fromer
    • , Shaun M. Purcell
    • , Panos Roussos
    • , Douglas M. Ruderfer
    • , Eli A. Stahl
    •  & Pamela Sklar
  170. Department of Psychiatry, University of Munich, Munich, Germany

    • Ina Giegling
    •  & Dan Rujescu
  171. Departments of Psychiatry and Human and Molecular Genetics, INSERM, Institut de Myologie, Hôpital de la Pitiè-Salpêtrière, Paris, France

    • Stephanie Godard
  172. Mental Health Research Centre, Russian Academy of Medical Sciences, Moscow, Russia

    • Vera Golimbet
  173. Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia

    • Jacob Gratten
    • , S Hong Lee
    • , Naomi R. Wray
    • , Peter M. Visscher
    •  & Bryan J. Mowry
  174. Academic Medical Centre University of Amsterdam, Department of Psychiatry, Amsterdam, The Netherlands

    • Lieuwe de Haan
    •  & Carin J. Meijer
  175. Illumina, Inc., La Jolla, California, USA

    • Mark Hansen
  176. Institute of Biological Psychiatry, MH.C. Sct Hans, Mental Health Services, Copenhagen, Denmark

    • Thomas Hansen
    • , Line Olsen
    • , Henrik B. Rasmussen
    •  & Thomas Werge
  177. Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA

    • Vahram Haroutunian
    • , Joseph D. Buxbaum
    •  & Pamela Sklar
  178. JJ Peters V.A. Medical Center, Bronx, New York, USA

    • Vahram Haroutunian
  179. Priority Research Centre for Health Behaviour, University of Newcastle, Newcastle, Australia

    • Frans A. Henskens
  180. School of Electrical Engineering and Computer Science, University of Newcastle, Newcastle, Australia

    • Frans A. Henskens
  181. Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA

    • Joel N. Hirschhorn
    • , Tõnu Esko
    •  & Steven A. McCarroll
  182. Section of Neonatal Screening and Hormones, Department of Clinical Biochemistry, Immunology and Genetics, Statens Serum Institut, Copenhagen, Denmark

    • Mads V. Hollegaard
    •  & David M. Hougaard
  183. Department of Psychiatry, Fujita Health University School of Medicine, Toyoake, Aichi, Japan

    • Masashi Ikeda
    •  & Nakao Iwata
  184. Regional Centre for Clinical Research in Psychosis, Department of Psychiatry, Stavanger University Hospital, Stavanger, Norway

    • Inge Joa
  185. Rheumatology Research Group, Vall d’Hebron Research Institute, Barcelona, Spain

    • Antonio Julià
    •  & Sara Marsal
  186. Centre for Medical Research, The University of Western Australia, Perth, Western Australia, Australia

    • Luba Kalaydjieva
  187. Perkins Institute for Medical Research, The University of Western Australia, Perth, Western Australia, Australia

    • Luba Kalaydjieva
  188. Department of Medical Genetics, Medical University, Sofia, Bulgaria

    • Sena Karachanak-Yankova
    •  & Draga Toncheva
  189. Department of Psychology, University of Colorado Boulder, Boulder, Colorado, USA

    • Matthew C. Keller
  190. Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada

    • James L. Kennedy
    • , Clement C. Zai
    •  & Jo Knight
  191. Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada

    • James L. Kennedy
    • , Clement C. Zai
    •  & Jo Knight
  192. Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada

    • James L. Kennedy
    •  & Jo Knight
  193. Institute of Molecular Genetics, Russian Academy of Sciences, Moscow, Russia

    • Andrey Khrunin
    • , Svetlana Limborska
    •  & Petr Slominsky
  194. Latvian Biomedical Research and Study Centre, Riga, Latvia

    • Janis Klovins
    •  & Liene Nikitina-Zake
  195. Department of Psychiatry and Zilkha Neurogenetics Institute, Keck School of Medicine at University of Southern California, Los Angeles, California, USA

    • James A. Knowles
    • , Michele T. Pato
    •  & Carlos N. Pato
  196. Faculty of Medicine, Vilnius University, Vilnius, Lithuania

    • Vaidutis Kucinskas
    •  & Zita Ausrele Kucinskiene
  197. Second Faculty of Medicine and University Hospital Motol, Prague, Czech Republic

    • Hana Kuzelova-Ptackova
    •  & Milan Macek
  198. Department of Biology and Medical Genetics, Charles University Prague, Prague, Czech Republic

    • Hana Kuzelova-Ptackova
    •  & Milan Macek
  199. Pierre and Marie Curie Faculty of Medicine, Paris, France

    • Claudine Laurent
  200. Duke-NUS Graduate Medical School, Singapore, Singapore

    • Jimmy Lee
  201. Department of Psychiatry, Hadassah-Hebrew University Medical Center, Jerusalem, Israel

    • Bernard Lerer
  202. Centre for Genomic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China

    • Miaoxin Li
    •  & Pak C. Sham
  203. Mental Health Centre and Psychiatric Laboratory, West China Hospital, Sichuan University, Chendu, Sichuan, China

    • Tao Li
    •  & Qiang Wang
  204. Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA

    • Kung-Yee Liang
  205. Department of Psychiatry, Columbia University, New York, New York, USA

    • Jeffrey Lieberman
    •  & T Scott Stroup
  206. Priority Centre for Translational Neuroscience and Mental Health, University of Newcastle, Newcastle, Australia

    • Carmel M. Loughland
    •  & Ulrich Schall
  207. Department of Genetics and Pathology, International Hereditary Cancer Center, Pomeranian Medical University in Szczecin, Szczecin, Poland

    • Jan Lubinski
  208. Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare, Helsinki, Finland

    • Jouko Lönnqvist
    •  & Jaana Suvisaari
  209. Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA

    • Brion S. Maher
  210. Department of Psychiatry, University of Bonn, Bonn, Germany

    • Wolfgang Maier
  211. Centre National de la Recherche Scientifique, Laboratoire de Génétique Moléculaire de la Neurotransmission et des Processus Neurodégénératifs, Hôpital de la Pitié Salpêtrière, Paris, France

    • Jacques Mallet
  212. Department of Genomics Mathematics, University of Bonn, Bonn, Germany

    • Manuel Mattheisen
  213. Research Unit, Sørlandet Hospital, Kristiansand, Norway

    • Morten Mattingsdal
  214. Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA

    • Robert W. McCarley
    • , Raquelle I. Mesholam-Gately
    • , Larry J. Seidman
    •  & Tracey L. Petryshen
  215. Virginia Boston Health Care System, Brockton, Massachusetts, USA

    • Robert W. McCarley
  216. Department of Psychiatry, National University of Ireland, Galway, Ireland

    • Colm McDonald
  217. Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK

    • Andrew M. McIntosh
  218. Division of Psychiatry, University of Edinburgh, Edinburgh, UK

    • Andrew M. McIntosh
    •  & Douglas H. R. Blackwood
  219. Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway

    • Ingrid Melle
    •  & Ole A. Andreassen
  220. Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA

    • Raquelle I. Mesholam-Gately
    •  & Larry J. Seidman
  221. Estonian Genome Center, University of Tartu, Tartu, Estonia

    • Andres Metspalu
    • , Lili Milani
    • , Mari Nelis
    •  & Tõnu Esko
  222. School of Psychology, University of Newcastle, Newcastle, Australia

    • Patricia T. Michie
  223. First Psychiatric Clinic, Medical University, Sofia, Bulgaria

    • Vihra Milanova
  224. Department P, Aarhus University Hospital, Risskov, Denmark

    • Ole Mors
    •  & Anders D. Børglum
  225. Department of Psychiatry, Royal College of Surgeons in Ireland, Ireland

    • Kieran C. Murphy
  226. King’s College London, London, UK

    • Robin M. Murray
  227. Maastricht University Medical Centre, South Limburg Mental Health Research and Teaching Network, EURON, Maastricht, The Netherlands

    • Inez Myin-Germeys
    •  & Jim Van Os
  228. Institute of Translational Medicine, University Liverpool, UK

    • Bertram Müller-Myhsok
  229. Max Planck Institute of Psychiatry, Munich, Germany

    • Bertram Müller-Myhsok
  230. Munich Cluster for Systems Neurology (SyNergy), Munich, Germany

    • Bertram Müller-Myhsok
  231. Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany

    • Igor Nenadic
  232. Department of Psychiatry, Queensland Brain Institute and Queensland Centre for Mental Health Research, University of Queensland, Brisbane, Queensland, Australia

    • Deborah A. Nertney
  233. Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA

    • Gerald Nestadt
    •  & Ann E. Pulver
  234. Department of Psychiatry, Trinity College Dublin, Dublin, Ireland

    • Kristin K. Nicodemus
  235. Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana, USA

    • Laura Nisenbaum
  236. Department of Clinical Sciences, Psychiatry, Umeå University, Umeå, Sweden

    • Annelie Nordin
    •  & Rolf Adolfsson
  237. DETECT Early Intervention Service for Psychosis, Blackrock, Dublin, Ireland

    • Eadbhard O’Callaghan
  238. Centre for Public Health, Institute of Clinical Sciences, Queens University Belfast, Belfast, UK

    • F Anthony O’Neill
  239. Lawrence Berkeley National Laboratory, University of California at Berkeley, Berkeley, California, USA

    • Sang-Yun Oh
  240. Institute of Psychiatry at King’s College London, London, UK

    • Jim Van Os
  241. Melbourne Neuropsychiatry Centre, University of Melbourne & Melbourne Health, Melbourne, Australia

    • Christos Pantelis
  242. Department of Psychiatry, University of Helsinki, Finland

    • Tiina Paunio
  243. Public Health Genomics Unit, National Institute for Health and Welfare, Helsinki, Helsinki, Finland

    • Tiina Paunio
    •  & Olli Pietiläinen
  244. Medical Faculty, University of Belgrade, Belgrade, Serbia

    • Milica Pejovic-Milovancevic
  245. Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina, USA

    • Diana O. Perkins
    •  & Patrick F. Sullivan
  246. Institute for Molecular Medicine Finland, FIMM, Helsinki, Finland

    • Olli Pietiläinen
    •  & Aarno Palotie
  247. Department of Epidemiology, Harvard University, Boston, Massachusetts, USA

    • Alkes Price
  248. Department of Psychiatry, University of Oxford, Oxford, UK

    • Digby Quested
  249. Vir ginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA

    • Mark A. Reimers
    •  & Aaron R. Wolen
  250. Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA

    • Panos Roussos
    •  & Pamela Sklar
  251. PharmaTherapeutics Clinical Research, Pfizer Worldwide Research and Development, Cambridge, Massachusetts, USA

    • Christian R. Schubert
    •  & Jens R. Wendland
  252. Department of Psychiatry and Psychotherapy, University of Gottingen, Göttingen, Germany

    • Thomas G. Schulze
  253. Psychiatry and Psychotherapy Clinic, University of Erlangen, Erlangen, Germany

    • Sibylle G. Schwab
  254. Hunter New England Health Service, Newcastle, Australia

    • Rodney J. Scott
  255. School of Biomedical Sciences, University of Newcastle, Newcastle, Australia

    • Rodney J. Scott
  256. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA

    • Jianxin Shi
  257. University of Iceland, Landspitali, National University Hospital, Reykjavik, Iceland

    • Engilbert Sigurdsson
  258. Department of Psychiatry and Drug Addiction, Tbilisi State Medical University (TSMU), Tbilisi, Georgia

    • Teimuraz Silagadze
  259. Research and Development, Bronx Veterans Affairs Medical Center, New York, New York, USA

    • Jeremy M. Silverman
  260. Wellcome Trust Centre for Human Genetics, Oxford, UK

    • Chris C. A. Spencer
  261. deCODE Genetics, Reykjavik, Iceland

    • Hreinn Stefansson
    • , Stacy Steinberg
    •  & Kari Stefansson
  262. Department of Clinical Neurology, Medical University of Vienna, Vienna, Austria

    • Elisabeth Stogmann
    •  & Fritz Zimprich
  263. Lieber Institute for Brain Development, Baltimore, Maryland, USA

    • Richard E. Straub
    •  & Daniel R. Weinberger
  264. Department of Medical Genetics, University Medical Centre, Utrecht, The Netherlands

    • Eric Strengman
  265. Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, Utrecht, The Netherlands

    • Eric Strengman
  266. Berkshire Healthcare NH.S. Foundation Trust, Bracknell, UK

    • Srinivas Thirumalai
  267. Section of Psychiatry, University of Verona, Verona, Italy

    • Sarah Tosato
  268. Department of Psychiatry, University of Oulu, Oulu, Finland

    • Juha Veijola
  269. University Hospital of Oulu, Oulu, Finland

    • Juha Veijola
  270. Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin, Ireland

    • John Waddington
  271. Health Research Board, Dublin, Ireland

    • Dermot Walsh
  272. Department of Psychiatry and Clinical Neurosciences, School of Psychiatry and Clinical Neurosciences, Queen Elizabeth I.I. Medical Centre, Perth, Western Australia, Australia

    • Dieter B. Wildenauer
  273. Department of Psychological Medicine and Neurology, MR.C. Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, Wales, UK

    • Nigel M. Williams
  274. Computational Sciences CoE, Pfizer Worldwide Research and Development, Cambridge, Massachusetts, USA

    • Hualin Simon Xi
  275. Human Genetics, Genome Institute of Singapore, Singapore, Singapore

    • Xuebin Zheng
    •  & Jianjun Liu
  276. University College London, London, UK

    • Elvira Bramon
  277. Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA

    • Joseph D. Buxbaum
  278. Department of Genetics, The Hebrew University of Jerusalem, Jerusalem, Israel

    • Ariel Darvasi
  279. Neuroscience Discovery and Translational Area, Pharma Research and Early Development, F. Hoffman-La Roche, Basel, Switzerland

    • Enrico Domenici
  280. School of Psychiatry and Clinical Neurosciences, The University of Western Australia, Perth, Australia

    • Assen V. Jablensky
  281. The Perkins Institute of Medical Research, Perth, Australia

    • Assen V. Jablensky
  282. UWA Centre for Clinical Research in Neuropsychiatry

    • Assen V. Jablensky
  283. Virginia Institute for Psychiatric and Behavioral Genetics, Departments of Psychiatry and Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia, USA

    • Kenneth S. Kendler
    •  & Brien P. Riley
  284. The Feinstein Institute for Medical Research, Manhasset, New York, USA

    • Todd Lencz
    •  & Anil K. Malhotra
  285. The Hofstra NS-LIJ School of Medicine, Hempstead, New York, USA

    • Todd Lencz
    •  & Anil K. Malhotra
  286. The Zucker Hillside Hospital, Glen Oaks, New York, USA

    • Todd Lencz
    •  & Anil K. Malhotra
  287. Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore

    • Jianjun Liu
  288. Queensland Centre for Mental Health Research, University of Queensland, Brisbane, Queensland, Australia

    • Bryan J. Mowry
  289. The Broad Institute of MI.T. and Harvard, Cambridge, Massachusetts, USA

    • Aarno Palotie
    •  & Tracey L. Petryshen
  290. Center for Human Genetic Research and Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA

    • Tracey L. Petryshen
  291. Department of Child and Adolescent Psychiatry, Erasmus University Medical Centre, Rotterdam, The Netherlands

    • Danielle Posthuma
  292. Department of Complex Trait Genetics, Neuroscience Campus Amsterdam, V.U. University Medical Center Amsterdam, Amsterdam, The Netherlands

    • Danielle Posthuma
  293. Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University, Amsterdam, The Netherlands

    • Danielle Posthuma
  294. University of Aberdeen, Institute of Medical Sciences, Aberdeen, Scotland, UK

    • David St Clair
  295. Departments of Psychiatry, Neurology, Neuroscience and Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA

    • Daniel R. Weinberger
  296. Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark

    • Thomas Werge

Consortia

  1. Project MinE GWAS Consortium

  2. Schizophrenia Working Group of the Psychiatric Genomics Consortium

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Contributions

O.H., J.H.V. and A.A.-C. conceived the study. R.L.McL., D.S., W.v.R., K.R.v.E., M.O’B., D.G.B., A.A.-C., L.H.v.d.B., J.J.L., O.H. and J.H.V. contributed to study design. R.L.McL., D.S. and W.v.R. conducted the analyses. R.L.McL., D.S., O.H., J.J.L. and J.H.V. drafted the manuscript. R.S.K., R.A.O. and A.G. provided data and critical revision of the manuscript. The Project MinE GWAS Consortium and Schizophrenia Working Group of the Psychiatric Genomics Consortium provided data. R.L.Mc.L. and D.S. contributed equally. J.J.L., O.H. and J.H.V. jointly directed the work.

Competing interests

O.H. has received speaking honoraria from Novartis, Biogen Idec, Sanofi Aventis and Merck-Serono. She has been a member of advisory panels for Biogen Idec, Allergen, Ono Pharmaceuticals, Novartis, Cytokinetics and Sanofi Aventis. She serves as Editor-in-Chief of Amyotrophic Lateral Sclerosis and Frontotemporal Dementia. L.H.v.d.B. serves on scientific advisory boards for Prinses Beatrix Spierfonds, Thierry Latran Foundation, Baxalta, Cytokinetics and Biogen, serves on the Editorial Board of the Journal of Neurology, Neurosurgery, and Psychiatry, Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, and Journal of Neuromuscular Diseases. A.A.C. has served on advisory panels for Biogen Idec, Cytokinetics, GSK, OrionPharma and Mitsubishi-Tanabe, serves on the Editorial Boards of Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration and F1000, and receives royalties for The Brain: A Beginner’s Guide, OneWorld Publications, and Genetics of Complex Human Diseases, Cold Spring Harbor Laboratory Press. The remaining authors declare no competing financial interests.

Corresponding author

Correspondence to Russell L. McLaughlin.

Supplementary information

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    Supplementary Information

    Supplementary Figures, Supplementary Tables, Supplementary Notes, Supplementary Methods, and Supplementary References

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