Genome-Wide Association Study Reveals Greater Polygenic Loading for Schizophrenia in Cases With a Family History of Illness

Abstract

Genome-wide association studies (GWAS) of schizophrenia have yielded more than 100 common susceptibility variants, and strongly support a substantial polygenic contribution of a large number of small allelic effects. It has been hypothesized that familial schizophrenia is largely a consequence of inherited rather than environmental factors. We investigated the extent to which familiality of schizophrenia is associated with enrichment for common risk variants detectable in a large GWAS. We analyzed single nucleotide polymorphism (SNP) data for cases reporting a family history of psychotic illness (N = 978), cases reporting no such family history (N = 4,503), and unscreened controls (N = 8,285) from the Psychiatric Genomics Consortium (PGC1) study of schizophrenia. We used a multinomial logistic regression approach with model-fitting to detect allelic effects specific to either family history subgroup. We also considered a polygenic model, in which we tested whether family history positive subjects carried more schizophrenia risk alleles than family history negative subjects, on average. Several individual SNPs attained suggestive but not genome-wide significant association with either family history subgroup. Comparison of genome-wide polygenic risk scores based on GWAS summary statistics indicated a significant enrichment for SNP effects among family history positive compared to family history negative cases (Nagelkerke’s R² = 0.0021; P = 0.00331; P-value threshold <0.4). Estimates of variability in disease liability attributable to the aggregate effect of genome-wide SNPs were significantly greater for family history positive compared to family history negative cases (0.32 and 0.22, respectively; P = 0.031).We found suggestive evidence of allelic effects detectable in large GWAS of schizophrenia that might be specific to particular family history subgroups. However, consideration of a polygenic risk score indicated a significant enrichment among family history positive cases for common allelic effects. Familial illness might, therefore, represent a more heritable form of schizophrenia, as suggested by previous epidemiological studies.

INTRODUCTION

Schizophrenia is a common (~1%) and debilitating neuropsychiatric disorder, for which a family history of the condition is among the strongest known risk factors [Gottesman, 1991; Sullivan et al., 2003; Mortensen et al., 2010]. Familial clustering has long been recognized as being typical of schizophrenia, with the biological siblings and children of an affected person having a 10-fold greater risk of developing the illness compared to the general• population [Gottesman and Shields, 1982; Kendler and Diehl, 1993; Lichtenstein et al., 2006]. Studies of twins indicate that schizophrenia is highly heritable (~80%), and adoption studies reveal no such aggregation among the adoptive relatives of affected persons, suggesting that this familial clustering is due largely to genetic factors [Kety et al., 1971; Kety and Ingraham, 2000; Sullivan et al., 2003]. However, despite decades of family, twin, and adoption studies supporting a substantial aggregate genetic component for schizophrenia [Kety et al., 1971; Rosenthal et al., 1971; Gottesman and Shields, 1982; Gottesman, 1991; Kendler and Diehl, 1993; Kety and Ingraham, 2000; Sullivan et al., 2003; Lichtenstein et al., 2006; Mortensen et al., 2010], the mode of transmission is complex and there is no evidence of Mendelian inheritance in affected families nor of genes of large effect in the general population.

In recent years, genome-wide association studies (GWAS) of schizophrenia have yielded a burgeoning list of common (typically, minor allele frequency greater than 1%) susceptibility loci, providing strong support for a substantial polygenic contribution of a large number of small genetic effects, as well as copy number variants (CNVs) with larger effects [International Schizophrenia Consortium, 2008; Stefansson et al., 2008; Walsh et al., 2008]. A polygenic model, described first by R.A. Fisher [Fisher, 1918] and subsequently hypothesized to apply to schizophrenia [Gottesman and Shields, 1967], has been shown to better explain the molecular findings of schizophrenia than any other model, with an estimated third of the variability in disease liability attributable to common variants [International Schizophrenia Consortium, 2009; Cross-Disorder Group of the Psychiatric Genomics Consortium, Genetic Risk Outcome of Psychosis Consortium, 2013; Ripke et al., 2013]. Furthermore, assuming polygenic inheritance and modest family size, for a disease with the observed prevalence and estimated heritability of schizophrenia, more sporadic than familial cases are expected [Yang et al., 2010]. This might explain the somewhat surprising observation that the majority (~96%) of schizophrenia cases in the general population have no affected first-degree relatives [Kety et al., 1971; Kendler, 1987].

In the present study, we sought to determine whether allelic effects detectable in a large GWAS demonstrate greater specificity to schizophrenia cases with a family history of psychotic illness in the Psychiatric GWAS Consortium (PGC) study of schizophrenia [Schizophrenia Psychiatric Genome-Wide Association Study Consortium, 2011], and whether family history positive cases were enriched for common effects overall. We conducted GWAS using a single omnibus test of association among family history positive and negative cases and population controls, followed by model-specification in order to assess whether an observed association was best explained by case-control differences overall, or by one of these two family history subgroups. We also considered the effect of common variants in aggregate by two alternative but complementary methods: polygenic risk score profiling based on SNP results from a large GWAS, as well as the GCTA method, which estimates the fraction of variability in disease liability attributable to common SNPs genome-wide [Yang et al., 2011; Lee et al., 2011a]. We sought to assess whether estimates obtained by either method differed significantly between cases with differing family history status.

METHODS

Samples, Ascertainment, and Assessment

The subsamples included in this study comprise Stage 1 of the Psychiatric Genomics Consortium Schizophrenia study [Schizophrenia Psychiatric Genome-Wide Association Study Consortium, 2011]. Ascertainment, diagnostic assessment, genotyping, and genotype quality control have been previously described [Schizophrenia Psychiatric Genome-Wide Association Study Consortium, 2011]. Briefly, 17 samples from the United States, Europe, and Australia comprising 9,394 cases were genotyped using a number of common Affymetrix and Illumina SNP array platforms. Imputation was performed with CEU+TSI HapMap phase 3 data (UCSC hg18/NCBI 36), resulting in a total of 1,252,901 autosomal SNPs, for GWAS analysis.

In the current study, we focus on family history of psychotic illness among affected subjects as the phenotype of interest, deriving this information directly from available clinical interviews and/or checklists from the individual PGC sites. A positive family history was defined as having at least one first- or second-degree relative with a diagnosis of psychotic illness. The individual sites and respective sample sizes are presented in Table I. Family history was determined using a variety of instruments including the DIGS, FIGS, OPCRIT, SCAN, and SCID, which we have detailed in the Supplementary Information.

TABLE I.

Numbers of Cases With Given Family History Status and Controls by PGC1 Study Site

		Cases
Study site	Source	Positive	Negative	Controls
ISC-Aberdeen	OPCRIT	106	521	698
ISC-Bulgaria	SCAN	83	302	609
ISC-Dublin	OPCRIT	37	138	860
ISC-Edinburgh	SADS-L	152	83	284
ISC-London	OPCRIT	99	355	492
ISC-Portugal	DIGS	53	216	216
MGS	DIGS	512	1,889	2,473
SGENE-Bonn	OPCRIT	129	342	1,304
SGENE-Copenhagen	OPCRIT	17	64	457
SGENE-Munich	SCID	122	311	351
SGENE-TOP3	SCID	37	158	351
Zucker hillside	SCID	42	124	190
Total		978	4,503	8,285

Abbreviations for study cohorts are as follows: SGENE, Schizophrenia Genetics Consortium; ISC, International Schizophrenia Consortium; TOP3, Thematic Organized Psychoses Research 3; UCLA, University of California at Los Angeles; MGS, Molecular Genetics of Schizophrenia.

Controls were mostly unscreened; this was justified given the low prevalence of schizophrenia in the population, and given the relatively large number of available controls. As family history information was largely unavailable for controls, this was not considered in these analyses.

Genome-Wide Association and Model Selection

We adopted a procedure analogous to that described by Huang et al. [2010] and Lee et al.[2011b], in which an omnibus test of association at each SNP, genome-wide, is followed by a model-selection approach to identify the configuration of outcomes most likely to be associated with a given variant. This entailed conducting a 2-df multinomial logistic regression (using the nnet package in R) [Venables and Ripley, 2002; R Core Team, 2013] in which allele frequencies can vary across three groups (family history positive cases, family history negative cases, and controls), and obtaining an estimate of the significance of this model relative to a null model in which allele frequencies are identical between groups. Imputed allelic dosages were analyzed, and sex, significantly associated ancestry principal components (PCs) [Schizophrenia Psychiatric Genome-Wide Association Study Consortium, 2011], and a study-site indicator were included as covariates. For those SNPs attaining suggestive significance by the omnibus test (P < 5 × 10⁻⁵), we compared the following logistic models: specific to family history positive cases (family history positive cases ≠ [controls = family history negative cases]); specific to family history negative cases (family history negative cases ≠ [family history positive cases = controls]); and non-specific effect ([family history positive cases = family history negative cases] ≠ controls). We compared these sub-models on the basis of the Bayesian Information Criterion to determine the best-fitting model for the observed disease-SNP association. (i.e., family history positive, family history negative, or non-specific). This is reported alongside the omnibus P-value in the presented results in Table II.

TABLE II.

Novel SNPs Demonstrating Specificity to Particular Family History Subgroups

CHR	Mb	SNP (assoc allele)	Info	PPGC1	Freqcases		Freqcont	Pomnibus	Model	Nearest gene (kb)
					Positive	Negative
2	40.11	rs7568579 (A)	0.9956	0.036	0.075	0.103	0.11	5.53E-06	+	SLC8A1 (−81.33 kb)
17	10.22	rs3809738 (T)	0.7261	3.45E-04	0.868	0.841	0.854	7.51E-06	−	MYH13 (+0.324 kb) +
9	100.34	rs2779600 (A)	0.9197	2.42E-03	0.565	0.513	0.501	8.28E-06	+	GABBR2 (0)
7	11.6	rs2354954 (A)	0.6895	0.101	0.295	0.323	0.337	1.26E-05	+	THSD7A (0)
16	1.33	rs1132356 (A)	0.8486	0.187	0.132	0.099	0.104	1.30E-05	+	BAIAP3 (0)
9	133.34	rs12552460 (T)	0.9969	7.71E-05	0.851	0.872	0.849	1.70E-05	−	POMT1 (−29.86 kb)
6	150.94	rs9398022 (A)	0.8542	1.27E-03	0.609	0.571	0.559	1.90E-05	+	PLEKHG1 (−23.03 kb)
5	17.06	rs11959796 (A)	0.9155	0.033	0.136	0.161	0.14	2.13E-05	−	MYO10 (+70.02 kb)
11	121.55	rs17126243 (A)	0.9717	1.47E-04	0.058	0.051	0.064	2.54E-05	−	BLID (+62.75 kb)
3	27.57	rs12498098 (T)	0.9933	0.721	0.816	0.854	0.857	2.73E-05	+	SLC4A7 (+100.4 kb) +
12	58.05	rs2203391 (T)	0.981	0.002	0.775	0.802	0.815	2.80E-05	+	SLC16A7 (−314.6 kb)
14	99.69	rs35257667 (A)	0.7317	0.05	0.311	0.278	0.277	2.89E-05	+	DEGS2 (0)
9	89.17	rs1930057 (T)	0.9487	0.002	0.775	0.756	0.779	2.97E-05	−	DAPK1 (−132.9 kb)
19	44.54	rs1375910 (A)	0.7775	0.025	0.064	0.049	0.044	3.00E-05	+	SAMD4B (0)
6	71.8	rs2018220 (A)	0.9694	8.20E-04	0.379	0.4	0.376	3.11E-05	−	B3GAT2 (+78.74 kb) +
14	70.27	rs1476610 (T)	0.988	0.282	0.081	0.11	0.1	3.67E-05	−	MAP3K9 (0)
21	14.38	rs6516605 (C)	0.8042	0.007	0.653	0.614	0.604	3.80E-05	+	LIPI (−24.51 kb)
19	16.6	rs12461484 (C)	0.9134	0.007	0.46	0.424	0.416	3.83E-05	+	MED26 (+4.194 kb) +
5	63.41	rs7737133 (T)	0.7356	0.043	0.008	0.004	0.006	4.01E-05	−	RNF180 (−89.89 kb)
12	127.69	rs12099512 (T)	0.0145	0.801	0.995	0.995	0.995	4.14E-05	+	SLC15A4 (−148.9 kb)
2	96.56	rs11693625 (T)	0.7397	0.01	0.842	0.812	0.801	4.52E-05	+	ARID5A (−9.116 kb)
9	37.89	rs7030885 (A)	0.2433	0.579	0.995	0.998	0.998	4.69E-05	+	MCART1 (0)

For SNPs demonstrating specificity to family history positive or negative schizophrenia, CHR and Mb give its genomic coordinates (hg18); assoc allele represents the tested allele; INFO and P_PGC1 are the imputation information and P-value as reported in the original PGC GWAS; Freq_cases and Freq_cont give the frequency of the tested allele in family history case subgroups and controls;P_omnibus and Model give the significance by 2df omnibus test of “any association” and best-fitting model. For each SNP, the nearest gene within 1 Mb is shown; its position relative to a gene is given parenthetically (negative and positive kb values indicate up- and downstream positions).

Polygene Scores

To test whether family history subgroups differed in the extent of enrichment for common polygenic effects, scores for schizophrenia, bipolar disorder, and major depressive disorder risk were calculated as previously described, using results from the respective PGC primary GWAS of each disorder [Psychiatric GWAS Consortium Bipolar Disorder Working Group, 2011; Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium, 2013; Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014]. Briefly, schizophrenia risk scores were generated for each study site in the PGC2 study of schizophrenia [Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014], using every other study as the training set in an iterative, “leave-one-out” procedure. This approach resolved any issues related to significance testing of a score among subjects included in the training set, while offering improved power and less sample attrition compared to subdividing the full cohort into approximate halves. Scores were computed based on varying P-value thresholds signifying the proportion of SNPs with smaller P-values in the training set; P-value thresholds ranged between 0.0001 and 1.0. We matched these PGC2 polygenic scores to the PGC1 samples used in the present analysis. We assessed the significance of the family history subgroup difference by standard logistic regression, including 10 ancestry-based principal component scores, sex and a study-site indicator as covariates.

Estimation of the Variance Explained by All the SNPs

We use the methods presented in Lee et al. [2011a], which have been implemented in the freely available GCTA software [Yang et al., 2010]. As described elsewhere, only those SNPs that had minor allele frequency >0.01 and imputation R² > 0.6 in all contributing cohort sub-samples (imputation cohorts) were retained [Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013]. Subjects were excluded to ensure that for all pairs of individuals, the genome-wide measure of genetic similarity was less than 0.05 (approximately second-cousins). Assuming a disease prevalence (K) of 1% [Gottesman, 1991], we estimated the heritability based on all schizophrenia cases and controls, and for each family history subgroup separately. For the comparison of family history subgroups, we assessed the significance of an observed difference in SNP-h² by comparison of the likelihood ratio test statistics obtained for each.

RESULTS

Genome-Wide Association and Model-Fitting

In total, we tested 1.25 M SNPs for association with schizophrenia by a 2-df omnibus test of any association between controls (N = 8,285) and family history positive (N = 978) and negative cases (N = 4,503). Total numbers of cases and controls contributed by each study site are given in Table I. The genomic inflation factor (l) was estimated as 1.127; scaled to a sample size of 1,000 cases and 1,000 controls (λ1,000), this was estimated as 1.018. No single variant attained significance at established genome-wide criteria (P < 5 × 10⁻⁸).

For variants demonstrating suggestive association by the omnibus test (P < 5 × 10⁻⁵), we performed model-fitting to determine whether the observed association was better explained by either of the family history subgroups or by case-control differences overall. Of 67 suggestively associated independent SNPs, 22 had already attained this level of significance in the primary PGC case-control analysis [Schizophrenia Psychiatric Genome-Wide Association Study Consortium, 2011]. For an additional 20 loci, our model-fitting procedure demonstrated non-specificity of the observed association to any particular family history subgroup, suggesting that a large fraction of these SNPs appear to be associated with both family history negative and positive forms of schizophrenia (Fig. 1). After excluding all SNPs within one megabase of a SNP attaining suggestive levels of significance in the primary case-control analysis [Schizophrenia Psychiatric Genome-Wide Association Study Consortium, 2011], 22 independent loci demonstrated specificity to a particular family history subgroup (Table II). We observe the strongest of these associations at SNPs on 2p22.1. These SNPs, for which family history positive was found to be the best-fitting model, fall upstream of SLC8A1, a sodium/chloride ion exchanger expressed ubiquitously across human tissues.

FIG. 1.

Manhattan plot of primary family history GWAS. Red and blue horizontal lines show thresholds for genome-wide (5 × 10⁻⁸) and suggestive (5 × 10⁻⁵) significance, respectively. Highlighted SNPs demonstrated specificity to a particular family history subgroup and were not within 1 Mb of any position attaining suggestive significance in the original schizophrenia analysis [Color figure can be seen in the online version of this article, available at http://wileyonlinelibrary.com/journal/ajmgb].

Polygenic Scoring Analyses

Following replicated evidence for a polygenic contribution to schizophrenia [International Schizophrenia Consortium, 2009; Schizophrenia Psychiatric Genome-Wide Association Study Consortium, 2011], we assessed whether weighted polygenic risk scores based on a training-set [Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014] of cases and controls could predict family history status in an independent target dataset, namely each constituent dataset included herein. Given the requirement that training and target datasets be independent, scores were generated via a “leave-one-out” procedure (see Methods section). Results for scores based on varying P-value thresholds are displayed in Figure 2. Overall, family history positive subjects demonstrated enrichment for common polygenic effects compared to subjects with no known family history of illness. We observed the most significant such enrichment for a score constructed of SNPs with P-values less than 0.4 in the PGC2 GWAS of schizophrenia (Nagelkerke’s R² = 0.0021; 1-sided P = 0.00331).

FIG. 2.

Predictive value of bipolar disorder, major depressive disorder, and schizophrenia polygene scores. Results based on varying SNP P-value inclusion thresholds are grouped by “training set.” Proportion of variance explained (Nagelkerke’s pseudo-R²) is shown on y-axis, and represents comparison of family history positive and negative cases. Displayed P-values correspond to the inclusion thresholds yielding the largest proportion of variance explained and are one-sided [Color figure can be seen in the online version of this article, available at http://wileyonlinelibrary.com/journal/ajmgb].

Similarly, family history positive cases were also enriched for polygene scores indexing risk of bipolar and major depressive disorders [Psychiatric GWAS Consortium Bipolar Disorder Working Group, 2011; Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium, 2013] (Fig. 2). For the bipolar disorder score, we observed the greatest predictive ability for a score constructed from SNPs with P-values less than 0.4 (Nagelkerke’s R² = 0.0014; 1-sided P = 0.0107). By comparison, enrichment of family history positive cases for major depressive disorder risk was more modest, with greatest predictive value at P-value inclusion threshold of 0.2 (Nagelkerke’s R² = 0.00079; 1-sided P = 0.0424).

Estimation of the Variance Explained by All SNPs

It has been shown previously that the polygenic model explains a substantial proportion of the heritability of schizophrenia [Lee et al., 2012; Cross-Disorder Group of the Psychiatric Genomics Consortium, Genetic Risk Outcome of Psychosis Consortium, 2013; Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013]. There is a tendency for polygenic scoring to underestimate the total variation in liability that is tagged by all SNPs because SNP effects are estimated with error [Wray et al., 2013]. We, therefore, sought to assess family history subgroup differences in the proportion of variability in liability explained by common SNPs using GCTA [Yang et al., 2011; Lee et al., 2011a]. Assuming a disease prevalence of 0.01 [Gottesman, 1991] and using a common set of control subjects, we obtained SNP heritability (SNP-h²) estimates for the family history positive and negative case subgroups separately, as well as for schizophrenia overall,combining the two subgroups (Fig. 3). For the combined family history positive and negative group (5,365 cases and 8,101 controls), we estimated the heritability to be 0.239 (95% CI:[0.213,0.264]; P = 2 × 10⁻⁸⁷); we obtained a slightly lower estimate of 0.220 (95% CI:[0.191,0.249]; P = 1.2 × 10⁻⁵⁸) for the family history negative subgroup (4,412 cases and 8,104 controls); and 0.306 (95% CI:[0.213,0.399]; P = 5 × 10⁻¹²) for the family history positive subgroup (960 cases and 8,128 controls). Comparison of likelihood ratio test-statistics for SNP-h² estimates for family history negative and positive subgroups yielded a nominally significant, one-sided P-value of 0.031.

FIG. 3.

Estimated heritability of schizophrenia for family history positive and negative cases. SNP-heritability (SNP-h²) estimates based on genome-wide SNPs based on family history positive, family history negative and all schizophrenia cases, assuming disease prevalence of 1%; error bars represent standard error (S.E.) of estimate. Displayed P-value is one-sided [Color figure can be seen in the online version of this article, available at http://wileyonlinelibrary.com/journal/ajmgb].

DISCUSSION

We have performed the first GWAS meta-analysis of schizophrenia aimed at identifying risk factors specific to familial versus non-familial illness. Although no novel genome-wide significant associations were detected, we did observe a small number of suggestively associated SNPs that demonstrated specificity to familial schizophrenia. We compared estimates of the aggregate contribution of common variants to disease liability in each family history subgroup by two alternative methods, demonstrating a modest but significant enrichment for common polygenic effects among familial schizophrenia cases.

In our primary analysis, we observed genome-wide significant associations in the vicinity of the major histocompatibility complex on chromosome 6p, albeit less significant than reported in the primary PGC1 study (Schizophrenia Psychiatric Genome-Wide Association Study Consortium) and demonstrating no specificity to either family history subgroup. Similarly, the majority of observed suggestive associations in other regions were also nonspecific, having yielded comparable levels of significance in the primary GWAS of schizophrenia. It follows that any inflation in the observed test-statistic distribution—indicating deviation from the null hypothesis of no association—is largely owing to the power of the PGC1 discovery sample to detect genome-wide significant associations. That SNPs demonstrating specificity to family history negative cases achieved at least nominal significance in the primary GWAS is also not surprising, as the majority of schizophrenia cases are “sporadic” and, therefore, likely representative of the full PGC schizophrenia sample.

We observed the strongest evidence of an association demonstrating specificity to family history positive cases at SNPs upstream of SLC8A1. Despite not yielding previous evidence of association with schizophrenia, SLC8A1 is potentially of interest given its role as a ubiquitous sodium/chloride ion exchanger. Complicating our interpretation of its putative etiological relevance are reported associations between variants in SLC8A1 and both childhood obesity [Comuzzie et al., 2012] and electrocardiographic QT interval [Kim et al., 2012]. However, pleiotropy has been observed in even established schizophrenia and bipolar susceptibility genes, such CACNA1C, which is associated with the Brugada and Timothy Syndromes, both of which cause cardiac arrhythmias (http://www.omim.org/entry/114205). Of potential interest are SNPs demonstrating association to a specific family history subgroup despite having failed to yield even nominally significant [P < 0.05] associations in the primary GWAS of schizophrenia (Schizophrenia Psychiatric Genome-Wide Association Study Consortium). This includes variants in brain-expressed genes BAIAP3 (16p13.3) and THSD7A (7p21.3) for the family history positive subgroup, and MAP3K9 (14q24.2) for the family history positive subgroup.

In the present study, family history subgroups of schizophrenia were not distinguishable by individual genetic variants detectable in a large GWAS. We further asked whether these subgroups differed with respect to the total variability in liability attributable to common SNPs genome-wide. Using GCTA [Yang et al., 2011; Lee et al., 2011a], we obtained an estimate of SNP-heritability for family history positive cases that was slightly elevated relative to family history negative cases, an observation congruent with an underlying, continuous liability distribution. Comparison of schizophrenia polygene scores yielded additional support for this hypothesis, as family history positive cases were significantly enriched for common polygenic effects compared to family history negative cases. This supports a previous finding by our group demonstrating that the unaffected relatives of schizophrenia probands are similarly enriched for such effects [Bigdeli et al., 2013]. Taken together, these data might be construed as a positive—albeit somewhat preliminary—affirmation, using molecular genetic data, that familial schizophrenia is largely a consequence of inherited rather than environmental factors.

Polygenic scoring analyses also revealed enrichment of family history positive cases for common variants conferring risk of bipolar disorder and, to a lesser extent, major depressive disorder, although we note that these findings do not remain significant following correction for the number of scores examined. Nonetheless, the suggested pattern of enrichment is in keeping with several decades of findings from family studies demonstrating an elevated risk of psychotic and affective illness among the first-degree relatives of schizophrenia probands [Kendler and Gardner, 1997], as well as emergent molecular evidence supporting a shared genetic etiology for major psychiatric disorders [Cross-Disorder Group of the Psychiatric Genomics Consortium, Genetic Risk Outcome of Psychosis (GROUP) Consortium, 2013; Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013; Ruderfer et al., 2014].

The conclusion that cases with a positive family history of psychosis carry a greater signature of polygenic liability than those with no known family history has potentially important implications for genetic studies of schizophrenia. Large, population-based studies might also benefit from consideration of family history status. To date, the use of unscreened controls has typically been justified by the relatively low prevalence of schizophrenia among the general population, with the ability to include a larger number of controls expected to offset any attendant loss of statistical power. It is conceivable that the use of thoroughly screened controls could potentiate polygenic risk score profiling because of their likely lower polygenic risk, potentially improving individual risk prediction. However, this would entail ascertainment of an equivalent number of such screened controls, likely at greater expense. This could apply in screening for family history of mood disorders as well, if our finding of enrichment for polygenic risk of both bipolar disorder and major depressive disorder is confirmed.

The findings presented herein should be interpreted in light of several key limitations. First, as familial cases represent a minority of all schizophrenia cases, attaining the requisite sample sizes for an adequately powered GWAS is likely to remain a difficult task. This limited statistical power is reflected in the observation that neither the SNP-heritability nor polygenic enrichment findings survive an experiment-wide Bonferroni correction for multiple testing. However, this would be over-conservative given the nested nature of the multiple P-value thresholds in enrichment analysis as well as the non-independence of enrichment and GCTA analyses. Furthermore, there are several well-established limitations of family history based methods, discussed in detail by Kendler and coworkers [Kendler, 1987, 1988; Kendler et al., 1991; Roy et al., 1996]. Like age-at-onset, accounts of family history are typically retrospective. It has also been demonstrated that a respondent’s psychiatric diagnosis, as well as their relationship to the affected person (or proband) are relevant factors in the reporting of family history [Kendler et al., 1991; Roy et al., 1996]. It is important to note that, because we have defined family history based on first- and, if available, second-degree relatives, we cannot assume that family history negative cases are unequivocally “sporadic,” thus precluding the traditional comparison with “familial” schizophrenia. Finally, given limitations posed by the design of participating studies, we were unable to address the occurrence of schizophrenia spectrum disorders among probands’ relatives, and designations of “positive” family history were necessarily restricted to psychotic illness. The lower severity and diminished need for hospitalization in spectrum disorders would require them to be directly assessed in relatives, as they are unlikely to be reliably determined through case subjects’ reports. This of course could be prohibitively expensive in large case-control studies.

In summary, we have demonstrated, using molecular genetic data, that familial schizophrenia is largely a consequence of inherited rather than environmental factors.

Full List of PGC Contributors

Stephan Ripke,^1,2 Benjamin M Neale,^1–4 Aiden Corvin,⁵ James TR Walters,⁶ Kai-How Farh,¹ Peter A Holmans,^6,7 Phil Lee,^1,2,4 Brendan Bulik-Sullivan,^1,2 David A Collier,^8,9 Hailiang Huang,^1,3 Tune H Pers,^3,10,11 Ingrid Agartz,^12–14 Esben Agerbo,^15–17 Margot Albus,¹⁸ Madeline Alexander,¹⁹ Farooq Amin,^20,21 Silviu A Bacanu,²² Martin Begemann,²³ Richard A Belliveau Jr,² Judit Bene,^24,25 Sarah E Bergen,^2,26 Elizabeth Bevilacqua,² Tim B Bigdeli,²² Donald W Black,²⁷ Richard Bruggeman,²⁸ Nancy G Buccola,²⁹ Randy L Buckner,^30–32 William Byerley,³³ Wiepke Cahn,³⁴ Guiqing Cai,^35,36 Dominique Campion,³⁷ Rita M Cantor,³⁸ Vaughan J Carr,^39,40 Noa Carrera,⁶ Stanley V Catts,^39,41 Kimberley D Chambert,² Raymond CK Chan,⁴² Ronald YL Chan,⁴³ Eric YH Chen,⁴⁴ Wei Cheng,⁴⁵ Eric FC Cheung,⁴⁶ Siow Ann Chong,⁴⁷ C Robert Cloninger,⁴⁸ David Cohen,⁴⁹ Nadine Cohen,⁵⁰ Paul Cormican,⁵ Nick Craddock,^6,7 James J Crowley,⁵¹ David Curtis,^52,53 Michael Davidson,⁵⁴ Kenneth L Davis,³⁶ Franziska Degenhardt,^55,56 Jurgen Del Favero,⁵⁷ Ditte Demontis,^17,58,59 Dimitris Dikeos,⁶⁰ Timothy Dinan,⁶¹ Srdjan Djurovic,^14,62 Gary Donohoe,^5,63 Elodie Drapeau,³⁶ Jubao Duan,^64,65 Frank Dudbridge,⁶⁶ Naser Durmishi,⁶⁷ Peter Eichhammer,⁶⁸ Johan Eriksson,^69–71 Valentina Escott-Price,⁶ Laurent Essioux,⁷² Ayman H Fanous,^73–76 Martilias S Farrell,⁵¹ Josef Frank,⁷⁷ Lude Franke,⁷⁸ Robert Freedman,⁷⁹ Nelson B Freimer,⁸⁰ Marion Friedl,⁸¹ Joseph I Friedman,³⁶ Menachem Fromer,^1,2,4,82 Giulio Genovese,² Lyudmila Georgieva,⁶ Ina Giegling,^81,83 Paola Giusti-Rodríguez,⁵¹ Stephanie Godard,⁸⁴ Jacqueline I Goldstein,^1,3 Vera Golimbet,⁸⁵ Srihari Gopal,⁸⁶ Jacob Gratten,⁸⁷ Lieuwe de Haan,⁸⁸ Christian Hammer,²³ Marian L Hamshere,⁶ Mark Hansen,⁸⁹ Thomas Hansen,^17,90 Vahram Haroutunian,^36,91,92 Annette M Hartmann,⁸¹ Frans A Henskens,^39,93,94 Stefan Herms,^55,56,95 Joel N Hirschhorn,^3,11,96 Per Hoffmann,^55,56,95 Andrea Hofman,^55,56 Mads V Hollegaard,⁹⁷ Masashi Ikeda,⁹⁸ Inge Joa,⁹⁹ Antonio Julià,¹⁰⁰ René S Kahn,¹⁰¹ Luba Kalaydjieva,^102,103 Sena Karachanak-Yankova,¹⁰⁴ Juha Karjalainen,⁷⁸ David Kavanagh,⁶ Matthew C Keller,¹⁰⁵ James L Kennedy,^106–108 Andrey Khrunin,¹⁰⁹ Yunjung Kim,⁵¹ Janis Klovins,¹¹⁰ James A Knowles,¹¹¹ Bettina Konte,⁸¹ Vaidutis Kucinskas,¹¹² Zita Ausrele Kucinskiene,¹¹² Hana Kuzelova-Ptackova,^113,114 Anna K Kähler,²⁶ Claudine Laurent,^19,115 Jimmy Lee,^47,116 S Hong Lee,⁸⁷ Sophie E Legge,⁶ Bernard Lerer,¹¹⁷ Miaoxin Li,¹¹⁸ Tao Li,¹¹⁹ Kung-Yee Liang,¹²⁰ Jeffrey Lieberman,¹²¹ Svetlana Limborska,¹⁰⁹ Carmel M Loughland,^39,122 Jan Lubinski,¹²³ Jouko Lönnqvist,¹²⁴ Milan Macek,^113,114 Patrik KE Magnusson,²⁶ Brion S Maher,¹²⁵ Wolfgang Maier,¹²⁶ Jacques Mallet,¹²⁷ Sara Marsal,¹⁰⁰ Manuel Mattheisen,^17,58,59,128 Morten Mattingsdal,^14,129 Robert W McCarley,^130,131 Colm McDonald,¹³² Andrew M McIntosh,^133,134 Sandra Meier,⁷⁷ Carin J Meijer,⁸⁸ Bela Melegh,^24,25 Ingrid Melle,^14,135 Raquelle I Mesholam-Gately,^130,136 Andres Metspalu,¹³⁷ Patricia T Michie,^39,138 Lili Milani,¹³⁷ Vihra Milanova,¹³⁹ Younes Mokrab,⁸ Derek W Morris,^5,63 Ole Mors,^17,58,140 Kieran C Murphy,¹⁴¹ Robin M Murray,¹⁴² Inez Myin-Germeys,¹⁴³ Bertram Müller-Myhsok,^144–146 Mari Nelis,¹³⁷ Igor Nenadic,¹⁴⁷ Deborah A Nertney,¹⁴⁸ Gerald Nestadt,¹⁴⁹ Kristin K Nicodemus,¹⁵⁰ Liene Nikitina-Zake,¹¹⁰ Laura Nisenbaum,¹⁵¹ Annelie Nordin,¹⁵² Eadbhard O’Callaghan,¹⁵³ Colm O’Dushlaine,² F Anthony O’Neill,¹⁵⁴ Sang-Yun Oh,¹⁵⁵ Ann Olincy,⁷⁹ Line Olsen,^17,90 Jim Van Os,^143,156 Christos Pantelis,^39,157 George N Papadimitriou,⁶⁰ Sergi Papiol,²³ Elena Parkhomenko,³⁶ Michele T Pato,¹¹¹ Tiina Paunio,^158,159 Milica Pejovic-Milovancevic,¹⁶⁰ Diana O Perkins,¹⁶¹ Olli Pietiläinen,^159,162 Jonathan Pimm,⁵³ Andrew J Pocklington,⁶ Danielle Posthuma,^163–165 John Powell,¹⁴² Alkes Price,¹⁶⁶ Ann E Pulver,¹⁴⁹ Shaun Purcell,⁸² Digby Quested,¹⁶⁷ Henrik B Rasmussen,^17,90 Abraham Reichenberg,³⁶ Mark A Reimers,¹⁶⁸ Alexander L Richards,^6,7 Joshua L Roffman,^30,32 Panos Roussos,^82,169 Douglas M Ruderfer,⁸² Veikko Salomaa,⁷¹ Alan R Sanders,^64,65 Ulrich Schall,^39,122 Christian R Schubert,¹⁷⁰ Thomas G Schulze,^77,171 Sibylle G Schwab,¹⁷² Edward M Scolnick,² Rodney J Scott,^39,173,174 Larry J Seidman,^130,136 Jianxin Shi,¹⁷⁵ Engilbert Sigurdsson,¹⁷⁶ Teimuraz Silagadze,¹⁷⁷ Jeremy M Silverman,^36,178 Kang Sim,⁴⁷ Petr Slominsky,¹⁰⁹ Jordan W Smoller,^2,4 Hon-Cheong So,⁴³ Chris C A Spencer,¹⁷⁹ Eli A Stahl,^3,82 Hreinn Stefansson,¹⁸⁰ Stacy Steinberg,¹⁸⁰ Elisabeth Stogmann,¹⁸¹ Richard E Straub,¹⁸² Eric Strengman,^183,184 Jana Strohmaier,⁷⁷ T Scott Stroup,¹²¹ Mythily Subramaniam,⁴⁷ Jaana Suvisaari,¹²⁴ Dragan M Svrakic,⁴⁸ Jin P Szatkiewicz,⁵¹ Erik Söderman,¹² Srinivas Thirumalai,¹⁸⁵ Draga Toncheva,¹⁰⁴ Sarah Tosato,¹⁸⁶ Juha Veijola,¹⁸⁷ Peter M Visscher,⁸⁷ John Waddington,¹⁸⁸ Dermot Walsh,¹⁸⁹ Dai Wang,⁸⁶ Qiang Wang,¹¹⁹ Bradley T Webb,²² Mark Weiser,⁵⁴ Durk Wiersma,¹⁹⁰ Dieter B Wildenauer,¹⁹¹ Nigel M Williams,¹⁹² Stephanie Williams,⁵¹ Stephanie H Witt,⁷⁷ Aaron R Wolen,¹⁶⁸ Emily HM Wong,⁴³ Brandon K Wormley,²² Hualin Simon Xi,¹⁹³ Clement C Zai,^106,107 Xuebin Zheng,¹⁹⁴ Fritz Zimprich,¹⁸¹ Naomi R Wray,⁸⁷ Kari Stefansson,¹⁸⁰ Wellcome Trust Case-Control Consortium 2,¹⁹⁵ Rolf Adolfsson,¹⁵² Ole A Andreassen,^14,135 Douglas HR Blackwood,¹³⁴ Elvira Bramon,¹⁹⁶ Joseph D Buxbaum,^35,36,91,197 Anders D Børglum,^17,58,59,140 Sven Cichon,^55,56,95,198 Ariel Darvasi,¹⁹⁹ Enrico Domenici,²⁰⁰ Hannelore Ehrenreich,²³ Tõnu Esko,^3,11,96,137 Pablo V Gejman,^64,65 Michael Gill,⁵ Hugh Gurling,⁵³ Christina M Hultman,²⁶ Nakao Iwata,⁹⁸ Assen V Jablensky,^39,201–203 Erik G Jönsson,¹² Kenneth S Kendler,²⁰⁴ George Kirov,⁶ Jo Knight,^106–108 Todd Lencz,^205–207 Douglas F Levinson,¹⁹ Qingqin S Li,⁸⁶ Jianjun Liu,^194,208 Anil K Malhotra,^205–207 Steven A McCarroll,^2,96 Andrew McQuillin,⁵³ Jennifer L Moran,² Preben B Mortensen,^15–17 Bryan J Mowry,^87,209 Markus M Nöthen,^55,56 Roel A Ophoff,^38,80,210 Michael J Owen,^6,7 Psychosis Endophenotypes International Consortium,²¹¹ Aarno Palotie,^4,162,212 Carlos N Pato,¹¹¹ Tracey L Petryshen,^130,212,213 Marcella Rietschel,⁷⁷ Brien P Riley,²⁰⁴ Dan Rujescu,^81,83 Pak C Sham,²¹⁴ Pamela Sklar,^82,91,169 David St Clair,²¹⁵ Daniel R Weinberger,^182,216 Jens R Wendland,¹⁷⁰ Thomas Werge,^17,90,217 Mark J Daly,¹ Patrick F Sullivan,^26,51,161 Michael C O’Donovan.^6,7

¹Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA. ²Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA. ³Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA. ⁴Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA. ⁵Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Ireland. ⁶MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK. ⁷National Centre for Mental Health, Cardiff University, Cardiff, Wales. ⁸Eli Lilly and Company Limited, Erl Wood Manor, Sunninghill Road, Windlesham, Surrey, UK. ⁹Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, London, UK. ¹⁰Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark. ¹¹Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Boston, MA, USA. ¹²Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden. ¹³Department of Psychiatry, Diakonhjemmet Hospital, Oslo, Norway. ¹⁴NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway. ¹⁵Centre for Integrative Register-based Research, CIRRAU, Aarhus University, Aarhus, Denmark. ¹⁶National Centre for Register-based Research, Aarhus University, Aarhus, Denmark. ¹⁷The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark. ¹⁸State Mental Hospital, Haar, Germany. ¹⁹Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA. ²⁰Department of Psychiatry and Behavioral Sciences, Atlanta Veterans Affairs Medical Center, Atlanta, GA, USA. ²¹Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA. ²²Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA. ²³Clinical Neuroscience, Max Planck Institute of Experimental Medicine, Göttingen, Germany. ²⁴Department of Medical Genetics, University of Pécs, Pécs, Hungary. ²⁵Szentagothai Research Center, University of Pécs, Pécs, Hungary. ²⁶Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. ²⁷Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA. ²⁸University Medical Center Groningen, Department of Psychiatry, University of Groningen, The Netherlands. ²⁹School of Nursing, Louisiana State University Health Sciences Center, New Orleans, LA, USA. ³⁰Athinoula A. Martinos Center, Massachusetts General Hospital, Boston, MA, USA. ³¹Center for Brain Science, Harvard University, Cambridge MA, USA. ³²Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA. ³³Department of Psychiatry, University of California at San Francisco, San Francisco, CA, USA. ³⁴University Medical Center Utrecht, Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, The Netherlands. ³⁵Department of Human Genetics, Icahn School of Medicine at Mount Sinai, New York, NY, USA. ³⁶Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA. ³⁷Centre Hospitalier du Rouvray and INSERM U1079 Faculty of Medicine, Rouen, France. ³⁸Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA. ³⁹Schizophrenia Research Institute, Sydney, Australia. ⁴⁰School of Psychiatry, University of New South Wales, Sydney, Australia. ⁴¹Royal Brisbane and Women’s Hospital, University of Queensland, Brisbane, Australia. ⁴²Institute of Psychology, Chinese Academy of Science, Beijing, PR China. ⁴³Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, PR China. ⁴⁴Department of Psychiatry and State Ket Laboratory for Brain and Cognitive Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, PR China. ⁴⁵Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA. ⁴⁶Castle Peak Hospital, Hong Kong SAR, PR China. ⁴⁷Institute of Mental Health, Singapore. ⁴⁸Department of Psychiatry, Washington University, St. Louis, MO, USA. ⁴⁹Department of Child and Adolescent Psychiatry, Pierre and Marie Curie Faculty of Medicine and Brain and Spinal Cord Institute (ICM), Paris, France. ⁵⁰Formerly of Neuroscience Therapeutic Area, Janssen Research and Development, LLC, Raritan, NJ, USA. ⁵¹Department of Genetics, University of North Carolina, Chapel Hill, NC, USA. ⁵²Department of Psychological Medicine, Queen Mary University of London, UK. ⁵³Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, UK. ⁵⁴Sheba Medical Center, Tel Hashomer, Israel. ⁵⁵Department of Genomics, Life and Brain Center, Bonn, Germany. ⁵⁶Institute of Human Genetics, University of Bonn, Bonn, Germany. ⁵⁷Applied Molecular Genomics Unit, VIB Department of Molecular Genetics, University of Antwerp, Antwerp, Belgium. ⁵⁸Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark. ⁵⁹Department of Biomedicine, Aarhus University, Aarhus, Denmark. ⁶⁰First Department of Psychiatry, University of Athens Medical School, Athens, Greece. ⁶¹Department of Psychiatry, University College Cork, Ireland. ⁶²Department of Medical Genetics, Oslo University Hospital, Oslo, Norway. ⁶³Cognitive Genetics and Therapy Group, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Ireland. ⁶⁴Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA. ⁶⁵Department of Psychiatry and Behavioral Sciences, NorthShore University HealthSystem, Evanston, IL, USA. ⁶⁶Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK. ⁶⁷Department of Child and Adolescent Psychiatry, University Clinic of Psychiatry, Skopje, Republic of Macedonia. ⁶⁸Department of Psychiatry, University of Regensburg, Regensburg, Germany. ⁶⁹Department of General Practice, Helsinki University Central Hospital, Helsinki, Finland. ⁷⁰Folkhälsan Research Center, Helsinki, Finland. ⁷¹National Institute for Health and Welfare, Helsinki, Finland. ⁷²Translational Technologies and Bioinformatics, Pharma Research and Early Development, F.Hoffman-La Roche, Basel, Switzerland. ⁷³Department of Psychiatry, Georgetown University School of Medicine, Washington DC, USA. ⁷⁴Department of Psychiatry, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA. ⁷⁵Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, VA, USA. ⁷⁶Mental Health Service Line, Washington VA Medical Center, Washington DC, USA. ⁷⁷Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany. ⁷⁸Department of Genetics, University of Groningen, University Medical Centre Groningen, The Netherlands. ⁷⁹Department of Psychiatry, University of Colorado Denver, Aurora, CO, USA. ⁸⁰Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA. ⁸¹Department of Psychiatry, University of Halle, Halle, Germany. ⁸²Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA. ⁸³Department of Psychiatry, University of Munich, Munich, Germany. ⁸⁴Departments of Psychiatry and Human and Molecular Genetics, INSERM, Institut de Myologie, Hôpital de la Pitiè-Salpêtrière, Paris, France. ⁸⁵Mental Health Research Centre, Russian Academy of Medical Sciences, Moscow, Russia. ⁸⁶Neuroscience Therapeutic Area, Janssen Research and Development, LLC, Raritan, NJ, USA. ⁸⁷Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia. ⁸⁸Academic Medical Centre University of Amsterdam, Department of Psychiatry, Amsterdam, The Netherlands. ⁸⁹Illumina, Inc., La Jolla, CA, USA. ⁹⁰Institute of Biological Psychiatry, MHC Sct. Hans, Mental Health Services Copenhagen, Denmark. ⁹¹Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. ⁹²JJ Peters VA Medical Center, Bronx, NY, USA. ⁹³Priority Research Centre for Health Behaviour, University of Newcastle, Newcastle, Australia. ⁹⁴School of Electrical Engineering and Computer Science, University of Newcastle, Newcastle, Australia. ⁹⁵Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland. ⁹⁶Department of Genetics, Harvard Medical School, Boston, MA, USA. ⁹⁷Section of Neonatal Screening and Hormones, Department of Clinical Biochemistry, Immunology and Genetics, Statens Serum Institut, Copenhagen, Denmark. ⁹⁸Department of Psychiatry, Fujita Health University School of Medicine, Toyoake, Aichi, Japan. ⁹⁹Regional Centre for Clinical Research in Psychosis, Department of Psychiatry, Stavanger University Hospital, Stavanger, Norway. ¹⁰⁰Rheumatology Research Group, Vall d’Hebron Research Institute, Barcelona, Spain. ¹⁰¹Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands. ¹⁰²Centre for Medical Research, The University of Western Australia, Perth, Western Australia, Australia. ¹⁰³Perkins Institute for Medical Research, The University of Western Australia, Perth, Western Australia, Australia. ¹⁰⁴Department of Medical Genetics, Medical University, Sofia, Bulgaria. ¹⁰⁵Department of Psychology, University of Colorado Boulder, Boulder, CO, USA. ¹⁰⁶Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada. ¹⁰⁷Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada. ¹⁰⁸Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada. ¹⁰⁹Institute of Molecular Genetics, Russian Academy of Sciences, Moscow, Russia. ¹¹⁰Latvian Biomedical Research and Study Centre, Riga, Latvia. ¹¹¹Department of Psychiatry and Zilkha Neurogenetics Institute, Keck School of Medicine at University of Southern California, Los Angeles, CA, USA. ¹¹² Faculty of Medicine, Vilnius University, Vilnius, Lithuania. ¹¹³2nd Faculty of Medicine and University Hospital Motol, Prague, Czech Republic. ¹¹⁴Department of Biology and Medical Genetics, Charles University Prague, Prague, Czech Republic. ¹¹⁵Pierre and Marie Curie Faculty of Medicine, Paris, France. ¹¹⁶Duke-NUS Graduate Medical School, Singapore. ¹¹⁷Department of Psychiatry, Hadassah-Hebrew University Medical Center, Jerusalem, Israel. ¹¹⁸Centre for Genomic Sciences and Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, PR China. ¹¹⁹Mental Health Centre and Psychiatric Laboratory, West China Hospital, Sichuan University, Chendu, Sichuan, PR China. ¹²⁰Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA. ¹²¹Department of Psychiatry, Columbia University, New York, NY, USA. ¹²²Priority Centre for Translational Neuroscience and Mental Health, University of Newcastle, Newcastle, Australia. ¹²³Department of Genetics and Pathology, International Hereditary Cancer Center, Pomeranian Medical University in Szczecin, Szczecin, Poland. ¹²⁴ Department of Mental Health and Substance Abuse Services; National Institute for Health and Welfare, Helsinki, Finland. ¹²⁵Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA. ¹²⁶Department of Psychiatry, University of Bonn, Bonn, Germany. ¹²⁷Centre National de la Recherche Scientifique, Laboratoire de Génétique Moléculaire de la Neurotransmission et des Processus Neurodégénératifs, Hôpital de la Pitié Salpêtrière, Paris, France. ¹²⁸Department of Genomics Mathematics, University of Bonn, Bonn, Germany. ¹²⁹Research Unit, Sørlandet Hospital, Kristiansand, Norway. ¹³⁰Department of Psychiatry, Harvard Medical School, Boston, MA, USA. ¹³¹VA Boston Health Care System, Brockton, MA, USA. ¹³²Department of Psychiatry, National University of Ireland Galway, Ireland. ¹³³Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK. ¹³⁴Division of Psychiatry, University of Edinburgh, Edinburgh, UK. ¹³⁵Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. ¹³⁶Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA, USA. ¹³⁷Estonian Genome Center, University of Tartu, Tartu, Estonia. ¹³⁸School of Psychology, University of Newcastle, Newcastle, Australia. ¹³⁹First Psychiatric Clinic, Medical University, Sofia, Bulgaria. ¹⁴⁰Department P, Aarhus University Hospital, Risskov, Denmark. ¹⁴¹Department of Psychiatry, Royal College of Surgeons in Ireland, Ireland. ¹⁴² King’s College London, UK. ¹⁴³Maastricht University Medical Centre, South Limburg Mental Health Research and Teaching Network, EURON, Maastricht, The Netherlands. ¹⁴⁴Institute of Translational Medicine, University Liverpool, UK. ¹⁴⁵Max Planck Institute of Psychiatry, Munich, Germany. ¹⁴⁶Munich Cluster for Systems Neurology (SyNergy), Munich, Germany. ¹⁴⁷Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany. ¹⁴⁸Department of Psychiatry, Queensland Brain Institute and Queensland Centre for Mental Health Research, University of Queensland, Brisbane, Queensland, Australia. ¹⁴⁹Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. ¹⁵⁰Department of Psychiatry, Trinity College Dublin, Ireland. ¹⁵¹Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN, USA. ¹⁵²Department of Clinical Sciences, Psychiatry, Umeå University, Umeå, Sweden. ¹⁵³DETECT Early Intervention Service for Psychosis, Blackrock, Dublin, Ireland. ¹⁵⁴Centre for Public Health, Institute of Clinical Sciences, Queens University Belfast, Belfast, UK. ¹⁵⁵Lawrence Berkeley National Laboratory, University of California at Berkeley, Berkeley, CA, USA. ¹⁵⁶Institute of Psychiatry at King’s College London, London, UK. ¹⁵⁷Melbourne Neuropsychiatry Centre, University of Melbourne& Melbourne Health, Melbourne, Australia. ¹⁵⁸Department of Psychiatry, University of Helsinki, Finland. ¹⁵⁹Public Health Genomics Unit, National Institute for Health and Welfare, Helsinki, Finland. ¹⁶⁰Medical Faculty, University of Belgrade, Belgrade, Serbia. ¹⁶¹Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA. ¹⁶²Institute for Molecular Medicine Finland, FIMM, Helsinki, Finland. ¹⁶³Department of Child and Adolescent Psychiatry, Erasmus University Medical Centre, Rotterdam, The Netherlands. ¹⁶⁴Department of Complex Trait Genetics, Neuroscience Campus Amsterdam, VU University Medical Center Amsterdam, Amsterdam, The Netherlands. ¹⁶⁵Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University, Amsterdam, The Netherlands. ¹⁶⁶Department of Epidemiology, Harvard University, Boston, MA, USA. ¹⁶⁷Department of Psychiatry, University of Oxford, Oxford, UK. ¹⁶⁸Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA. ¹⁶⁹Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. ¹⁷⁰PharmaTherapeutics Clinical Research, Pfizer Worldwide Research and Development, Cambridge, MA, USA. ¹⁷¹Department of Psychiatry and Psychotherapy, University of Gottingen, Göttingen, Germany. ¹⁷²Psychiatry and Psychotherapy Clinic, University of Erlangen, Germany. ¹⁷³Hunter New England Health Service, Newcastle, Australia. ¹⁷⁴School of Biomedical Sciences, University of Newcastle, Newcastle, Australia. ¹⁷⁵Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA. ¹⁷⁶University of Iceland, Landspitali, National University Hospital, Reykjavik, Iceland. ¹⁷⁷Department of Psychiatry and Drug Addiction, Tbilisi State Medical University (TSMU), Tbilisi, Georgia. ¹⁷⁸Research and Development, Bronx Veterans Affairs Medical Center, New York, NY, USA. ¹⁷⁹Wellcome Trust Centre for Human Genetics, Oxford, UK. ¹⁸⁰deCODE Genetics, Reykjavik, Iceland. ¹⁸¹ Department of Clinical Neurology, Medical University of Vienna, Austria. ¹⁸²Lieber Institute for Brain Development, Baltimore, MD, USA. ¹⁸³Department of Medical Genetics, University Medical Centre, Utrecht, The Netherlands. ¹⁸⁴Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, The Netherlands. ¹⁸⁵Berkshire Healthcare NHS Foundation Trust, Bracknell, UK. ¹⁸⁶Section of Psychiatry, University of Verona, Verona, Italy. ¹⁸⁷Department of Psychiatry, University of Oulu, Finland. ¹⁸⁸Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin, Ireland. ¹⁸⁹Health Research Board, Dublin, Ireland. ¹⁹⁰Department of Psychiatry, University Medical Center Groningen, University of Groningen, The Netherlands. ¹⁹¹Department of Psychiatry and Clinical Neurosciences, School of Psychiatry and Clinical Neurosciences, Queen Elizabeth II Medical Centre, Perth, Western Australia, Australia. ¹⁹²Department of Psychological Medicine and Neurology, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, Wales, UK. ¹⁹³Computational Sciences CoE, Pfizer Worldwide Research and Development, Cambridge, MA, USA. ¹⁹⁴Human Genetics, Genome Institute of Singapore, A*STAR, Singapore. ¹⁹⁵WTCCC2. ¹⁹⁶University College London, UK. ¹⁹⁷Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA. ¹⁹⁸Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Juelich, Germany. ¹⁹⁹Department of Genetics, The Hebrew University of Jerusalem, Jerusalem, Israel. ²⁰⁰Neuroscience Discovery and Translational Area, Pharma Research and Early Development, F.Hoffman-La Roche, Basel, Switzerland. ²⁰¹School of Psychiatry and Clinical Neurosciences, The University of Western Australia, Perth, Australia. ²⁰²The Perkins Institute of Medical Research, Perth, Australia. ²⁰³UWA Centre for Clinical Research in Neuropsychiatry. ²⁰⁴Virginia Institute for Psychiatric and Behavioral Genetics, Departments of Psychiatry and Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA. ²⁰⁵The Feinstein Institute for Medical Research, Manhasset, NY, USA. ²⁰⁶The Hofstra NS-LIJ School of Medicine, Hempstead, NY, USA. ²⁰⁷ The Zucker Hillside Hospital, Glen Oaks, NY, USA. ²⁰⁸Saw Swee Hock School of Public Health, National University of Singapore, Singapore. ²⁰⁹Queensland Centre for Mental Health Research, University of Queensland, Brisbane, Queensland, Australia. ²¹⁰Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands. ²¹¹PEIC. ²¹²The Broad Institute of MIT and Harvard, Cambridge, MA, USA. ²¹³Center for Human Genetic Research and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA. ²¹⁴Centre for Genomic Sciences, State Ket Laboratory for Brain and Cognitive Sciences, and Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, PR China. ²¹⁵University of Aberdeen, Institute of Medical Sciences, Aberdeen, Scotland, UK. ²¹⁶Departments of Psychiatry, Neurology, Neuroscience and Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA. ²¹⁷Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.

Wellcome Trust Case-Control Consortium 2

Management Committee: Peter Donnelly,^179,218 Ines Barroso,²¹⁹ Jenefer M Blackwell,^220,221 Elvira Bramon,¹⁹⁶ Matthew A Brown,²²² Juan P Casas,^223,224 Aiden Corvin,⁵ Panos Deloukas,²¹⁹ Audrey Duncanson,²²⁵ Janusz Jankowski,²²⁶ Hugh S Markus,²²⁷ Christopher G Mathew,²²⁸ Colin N A Palmer,²²⁹ Robert Plomin,⁹ Anna Rautanen,¹⁷⁹ Stephen J Sawcer,²³⁰ Richard C Trembath,²²⁸ Ananth C Viswanathan,^231,232 Nicholas W Wood.²³³

Data and Analysis Group: Chris C A Spencer,¹⁷⁹ Gavin Band,¹⁷⁹ Céline Bellenguez,¹⁷⁹ Peter Donnelly,^179,218 Colin Freeman,¹⁷⁹ Eleni Giannoulatou,¹⁷⁹ Garrett Hellenthal,¹⁷⁹ Richard Pearson,¹⁷⁹ Matti Pirinen,¹⁷⁹ Amy Strange,¹⁷⁹ Zhan Su,¹⁷⁹ Damjan Vukcevic.¹⁷⁹

DNA, Genotyping, Data QC, and Informatics: Cordelia Langford,²¹⁹ Ines Barroso,²¹⁹ Hannah Blackburn,²¹⁹ Suzannah J Bumpstead,²¹⁹ Panos Deloukas,²¹⁹ Serge Dronov,²¹⁹ Sarah Edkins,²¹⁹ Matthew Gillman,²¹⁹ Emma Gray,²¹⁹ Rhian Gwilliam,²¹⁹ Naomi Hammond,²¹⁹ Sarah E Hunt,²¹⁹ Alagurevathi Jayakumar,²¹⁹ Jennifer Liddle,²¹⁹ Owen T McCann,²¹⁹ Simon C Potter,²¹⁹ Radhi Ravindrarajah,²¹⁹ Michelle Ricketts,²¹⁹ Avazeh Tashakkori-Ghanbaria,²¹⁹ Matthew Waller,²¹⁹ Paul Weston,²¹⁹ Pamela Whittaker,²¹⁹ Sara Widaa.²¹⁹

Publications Committee: Christopher G Mathew,²²⁸ Jenefer M Blackwell,^220,221 Matthew A Brown,²²² Aiden Corvin,⁵ Mark I McCarthy,²³⁴ Chris C A Spencer.¹⁷⁹

Psychosis Endophenotype International Consortium

Maria J Arranz,^156,235, ¹⁰¹ Stephan Bender,^236,237 Elvira Bramon,^156,238,239 David A Collier,^8,9 Benedicto Crespo-Facorro,^240,241 Jeremy Hall,¹³⁴ Conrad Iyegbe,¹⁵⁶ Assen V Jablensky,²⁴² René S Kahn,¹⁰¹ Luba Kalaydjieva,^102,243 Stephen Lawrie,¹³⁴ Cathryn M Lewis,¹⁵⁶ Kuang Lin,¹⁵⁶ Don H Linszen,²⁴⁴ Ignacio Mata,^240,241 Andrew M McIntosh,¹³⁴ Robin M Murray,¹⁴² Roel A Ophoff,⁸⁰ Jim Van Os,^143,156 John Powell,¹⁵⁶ Dan Rujescu,^81,83 Muriel Walshe,¹⁵⁶ Matthias Weisbrod,²³⁷ Durk Wiersma.¹⁹⁰

²¹⁸Department of Statistics, University of Oxford, Oxford, UK. ²¹⁹Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. ²²⁰Cambridge Institute for Medical Research, University of Cambridge School of Clinical Medicine, Cambridge, UK. ²²¹Telethon Institute for Child Health Research, Centre for Child Health Research, University of Western Australia, Subiaco, Western Australia, Australia. ²²²Diamantina Institute of Cancer, Immunology and Metabolic Medicine, Princess Alexandra Hospital, University of Queensland, Brisbane, Queensland, Australia. ²²³Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK. ²²⁴Department of Epidemiology and Public Health, University College London, London, UK. ²²⁵Molecular and Physiological Sciences, The Wellcome Trust, London, UK. ²²⁶Peninsula School of Medicine and Dentistry, Plymouth University, Plymouth, UK. ²²⁷Clinical Neurosciences, St George’s University of London, London, UK. ²²⁸Department of Medical and Molecular Genetics, School of Medicine, King’s College London, Guy’s Hospital, London, UK. ²²⁹Biomedical Research Centre, Ninewells Hospital and Medical School, Dundee, UK. ²³⁰Department of Clinical Neurosciences, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK. ²³¹Institute of Ophthalmology, University College London, London, UK. ²³²National Institute for Health Research, Biomedical Research Centre at Moorfields Eye Hospital, National Health Service Foundation Trust, London, UK. ²³³Department of Molecular Neuroscience, Institute of Neurology, London, UK. ²³⁴Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, Oxford, UK. ²³⁵Fundació de Docència i Recerca Mútua de Terrassa, Universitat de Barcelona, Spain. ²³⁶Child and Adolescent Psychiatry, University of Technology Dresden, Dresden, Germany. ²³⁷Section for Experimental Psychopathology, General Psychiatry, Heidelberg, Germany. ²³⁸Institute of Cognitive Neuroscience, University College London, London, UK. ²³⁹Mental Health Sciences Unit, University College London, London, UK. ²⁴⁰Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain. ²⁴¹University Hospital Marqués de Valdecilla, Instituto de Formación e Investigación Marqués de Valdecilla, University of Cantabria, Santander, Spain. ²⁴²Centre for Clinical Research in Neuropsychiatry, The University of Western Australia, Perth, Western Australia, Australia. ²⁴³Western Australian Institute for Medical Research, The University of Western Australia, Perth, Western Australia, Australia. ²⁴⁴Department of Psychiatry, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.