Psychiatric GWAS Consortium Research Articles

The non-ergodic nature of mental health and psychiatric disorders: implications for biomarker and diagnostic research.

The non-ergodic nature of mental health and psychiatric disorders: implications for biomarker and diagnostic research.

An atlas of genetic correlations between gestational age and common psychiatric disorders.

We aim to systematically explore the potential genetic correlations between five major psychiatric disorders and gestational ages. Genome-wide association study (GWAS) summary datasets of attention deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) in discovery were downloaded from the Psychiatric GWAS Consortium (PGC) website. Suggestive (Raw p < 0.05) genetic associations in the discovery phrase were further replicated in independent GWASs which downloaded from PGC, the FinnGen study or Integrative Psychiatric Research (iPSYCH) website. GWASs of gestational duration, preterm and post-term birth were derived from previous studies of infants from the Early Growth Genetics (EGG) Consortium, the iPSYCH study, and the Genomic and Proteomic Network for Preterm Birth Research (GPN). We calculated genetic correlations using linkage disequilibrium score (LDSC) regression. Mendelian randomization (MR) analyses were performed to investigate the causal effects. We identified four suggestive genetic correlations between psychiatric disorders and gestational age factors in discovery LDSC and two replicated in a confirmation LDSC: gestational duration and ADHD (rg =-0.1405, FDR p=0.0406), post-term birth and SCZ (rg =-0.2003, FDR p=0.0042). We also observed causal effect of post-term birth on SCZ by MR (PWeighted median =0.037, PInverse variance weighted =0.007). Our analysis suggested no significant evidence of horizontal pleiotropy and heterogeneity. This study showed the genetic correlation evidences between gestational age phenotypes and psychiatric disorders, providing novel clues for understanding the pathogenic factors of common psychiatric disorders. LAY SUMMARY: Whereas gestational age factors were reported to be associated with psychiatric disorders, the genetic relationship and causality remain to be revealed. The present study reported the first large-scale genetic correlations investigation of the associations between gestational age phenotypes and psychiatric disorders. Results indicate causal relationships between post-term birth and schizophrenia (SCZ), as well as suggestive genetic correlations between gestational duration and attention deficit/hyperactivity disorder (ADHD). This study provided novel clues for understanding the pathogenic factors of common psychiatric disorders.

Dissecting the association between psychiatric disorders and neurological proteins: a genetic correlation and two-sample bidirectional Mendelian randomization study.

The role of neurological proteins in the development of bipolar disorder (BD) and schizophrenia (SCZ) remains elusive now. The current study aims to explore the potential genetic correlations of plasma neurological proteins with BD and SCZ. By using the latest genome-wide association study (GWAS) summary data of BD and SCZ (including 41,917 BD cases, 11,260 SCZ cases, and 396,091 controls) derived from the Psychiatric GWAS Consortium website (PGC) and a recently released GWAS of neurological proteins (including 750 individuals), we performed a linkage disequilibrium score regression (LDSC) analysis to detect the potential genetic correlations between the two common psychiatric disorders and each of the 92 neurological proteins. Two-sample Mendelian randomisation (MR) analysis was then applied to assess the bidirectional causal relationship between the neurological proteins identified by LDSC, BD and SCZ. LDSC analysis identified one neurological protein, NEP, which shows suggestive genetic correlation signals for both BD (coefficient = -0.165, p value = 0.035) and SCZ (coefficient = -0.235, p value = 0.020). However, those association did not remain significant after strict Bonferroni correction. Two sample MR analysis found that there was an association between genetically predicted level of NEP protein, BD (odd ratio [OR] = 0.87, p value = 1.61 × 10-6) and SCZ (OR = 0.90, p value = 4.04 × 10-6). However, in the opposite direction, there is no genetically predicted association between BD, SCZ, and NEP protein level. This study provided novel clues for understanding the genetic effects of neurological proteins on BD and SCZ.

Potential causal effect of posttraumatic stress disorder on alcohol use disorder and alcohol consumption in individuals of European descent: A Mendelian Randomization Study.

Posttraumatic stress disorder (PTSD) often co-occurs with alcohol consumption (AC) and alcohol use disorder (AUD). However, it is unknown whether the same etiologic influences that underlie PTSD co-occurring with AUD are those that underlie PTSD and AC individually. This study used large-scale genome-wide association study (GWAS) data to test whether PTSD and drinks per week [DPW]/AUD are causally related to one another, and, if so, whether PTSD precedes DPW/AUD and/or vice versa. We used Mendelian Randomization methods to analyze European ancestry GWAS summary statistics from the Psychiatric Genomics Consortium (PGC; PTSD), GWAS & Sequencing Consortium of Alcohol and Nicotine Use (GSCAN; DPW), and the Million Veteran Program (MVP; AUD). PTSD exerted a potentially causal effect on AUD (β=0.039, SE=0.014, p=0.005), but not on DPW (β=0.002, SE=0.003, p=0.414). Additionally, neither DPW (β=0.019, SE=0.041, p=0.637) nor AUD (β=8.87×10-4 , SE=0.001, p=0.441) exerted a causal effect on PTSD. These findings are consistent with the self-medication model, in which individuals misuse alcohol to cope with aversive trauma-related symptoms. These findings extend latent analysis and molecular findings of shared and correlated risk between PTSD and alcohol phenotypes. Given the health behaviors associated with these phenotypes, these findings are important in that they suggest groups to prioritize for prevention efforts. Further, they provide a rationale for future preclinical and clinical studies examining the biological mechanisms by which PTSD may impact AUD.

Polygenic risk scores differentiate schizophrenia patients with toxoplasma gondii compared to toxoplasma seronegative patients

Schizophrenia (SCZ) is an etiologically heterogeneous disease with genetic and environmental risk factors (e.g., Toxoplasma gondii infection) differing among affected individuals. Distinguishing such risk factors may point to differences in pathophysiological pathways and facilitate the discovery of individualized treatments. Toxoplasma gondii (TOXO) has been implicated in increasing the risk of schizophrenia. To determine whether TOXO-positive individuals with SCZ have a different polygenic risk burden than uninfected people, we applied the SCZ polygenic risk score (SCZ-PRS) derived from the Psychiatric GWAS Consortium separately to the TOXO-positive and TOXO-negative subjects with the diagnosis of SCZ as the outcome variable. The SCZ-PRS does not include variants in the major histocompatibility complex.Of 790 subjects assessed for TOXO, the 662 TOXO-negative subjects (50.8% with SCZ) reached a Bonferroni corrected significant association (p = 0.00017, R2 = 0.023). In contrast, the 128 TOXO-positive individuals (53.1% with SCZ) showed no significant association (p = 0.354) for SCZ-PRS and had a much lower R2 (R2 = 0.007). To account for Type-2 error in the TOXO-positive dataset, we performed a random sampling of the TOXO-negative subpopulation (n = 130, repeated 100 times) to simulate equivalent power between groups: the p-value was <0.05 for SCZ-PRS 55% of the time but was rarely (6% of the time) comparable to the high p-value of the seropositive group at p > 0.354.We found intriguing evidence that the SCZ-PRS predicts SCZ in TOXO-negative subjects, as expected, but not in the TOXO-positive individuals. This result highlights the importance of considering environmental risk factors to distinguish a subgroup with independent or different genetic components involved in the development of SCZ.

Identifying 5 Common Psychiatric Disorders Associated Chemicals Through Integrative Analysis of Genome-Wide Association Study and Chemical-Gene Interaction Datasets.

Psychiatric disorders are a group of complex psychological syndromes whose etiology remains unknown. Previous study suggested that various chemicals contributed to the development of psychiatric diseases through affecting gene expression. This study aims to systematically explore the potential relationships between 5 major psychiatric disorders and more than 11 000 chemicals. The genome-wide association studies (GWAS) datasets of attention deficiency/hyperactive disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depression disorder (MDD), and schizophrenia (SCZ) were driven from the Psychiatric GWAS Consortium and iPSYCH website. The chemicals related gene sets were obtained from the comparative toxicogenomics database (CTD). First, transcriptome-wide association studies (TWAS) were performed by FUSION to calculate the expression association testing statistics utilizing GWAS summary statistics of the 5 common psychiatric disorders. Chemical-related gene set enrichment analysis (GSEA) was then conducted to explore the relationships between chemicals and each of the psychiatric diseases. We observed several significant correlations between chemicals and each of the psychiatric disorders. We also detected common chemicals between every 4 of the 5 major psychiatric disorders, such as androgen antagonists for ADHD (P value = .0098), ASD (P value = .0330), BD (P value = .0238), and SCZ (P value = .0062), and imipramine for ADHD (P value = .0054), ASD (P value = .0386), MDD (P value = .0438), and SCZ (P value = .0008). Our study results provide new clues for revealing the roles of environmental chemicals in the development of psychiatric disorders.

An atlas of genetic correlations between psychiatric disorders and human blood plasma proteome.

Psychiatric disorders are a group of complex psychological syndromes with high prevalence. Recent studies observed associations between altered plasma proteins and psychiatric disorders. This study aims to systematically explore the potential genetic relationships between five major psychiatric disorders and more than 3,000 plasma proteins. The genome-wide association study (GWAS) datasets of attention deficiency/hyperactive disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) were driven from the Psychiatric GWAS Consortium. The GWAS datasets of 3,283 human plasma proteins were derived from recently published study, including 3,301 study subjects. Linkage disequilibrium score (LDSC) regression analysis were conducted to evaluate the genetic correlations between psychiatric disorders and each of the 3,283 plasma proteins. LDSC observed several genetic correlations between plasma proteins and psychiatric disorders, such as ADHD and lysosomal Pro-X carboxypeptidase (p value=0.015), ASD and extracellular superoxide dismutase (Cu-Zn; p value=0.023), BD and alpha-N-acetylgalactosaminide alpha-2,6-sialyltransferase 6 (p value=0.007), MDD and trefoil factor 1 (p value=0.011), and SCZ and insulin-like growth factor-binding protein 6 (p value=0.011). Additionally, we detected four common plasma proteins showing correlation evidence with both BD and SCZ, such as tumor necrosis factor receptor superfamily member 1B (p value=0.012 for BD, p value=0.011 for SCZ). This study provided an atlas of genetic correlations between psychiatric disorders and plasma proteome, providing novel clues for pathogenetic and biomarkers, therapeutic studies of psychiatric disorders.

Rs1625579 polymorphism in the MIR137 gene is associated with the risk of schizophrenia: updated meta-analysis

The Schizophrenia Psychiatric GWAS Consortium (PGC) has identified the rs1625579 polymorphism in the MIR137 gene, which encodes miR-137, as the strongest new association with schizophrenia in the European population. However, whether the influence of rs1625579 on schizophrenia in the Asian population is consistent with these results remains unclear. A total of 21 studies (9878 schizophrenic patients and 9447 control subjects) that met the inclusion criteria were included in our meta-analysis. Pooled analysis, subgroup analysis, sensitivity analysis and publication bias were performed.The T allele, TT genotype and TT + GG genotype were associated with schizophrenia as risk factors. Subgroup analysis shows that no heterogeneity existed in the European and Asian populations. Our meta-analysis found that the Rs1625579 polymorphism in the MIR137 gene was associated with the risk of schizophrenia. The current findings provide a reference for case-control studies of schizophrenia in the future.

SU40 - DISTINCT GENETIC VULNERABILITIES-BY-STRESSFUL LIFE EVENTS INTERACTIONS PROPOSE ADDITIONAL RISK FOR DEPRESSIVE SYMPTOMS

Background Stressful Life Events (SLEs) and genetic risk factors both contribute to the aetiology of Major Depressive Disorder (MDD). Although SLEs are considered to be an environmental factor, studies suggest that they may act in part through interaction with the known genetic risk factors in MDD or more unexpectedly, through interaction with novel genetic factors specific to SLEs. Polygenic Risk Scores (PRS) reflect an individual's genetic vulnerability to develop depression. Such vulnerability to MDD has been commonly based on main additive effects, although a genetic contribution has been suggested for SLEs on risk of MDD. We used PRS for MDD and for a novel stress-sensitivity trait, derived from a Genome-Wide Interaction Study (GWEIS), to test these hypotheses. Methods We performed a GWEIS in UK Biobank (N=23,092; UKB), modeling the interaction between SNP allele and MDD status on neuroticism score (EPQ-N). The effect size of the interaction term was used to create a measure of genetic MDD-dependent stress-sensitivity (SS). The genetic vulnerability-stress model was tested using PRS weighted by MDD using Psychiatric GWAS Consortium MDD summary statistics (MDD-PRS), or PRS weighted by MDD-dependent stress-sensitivity effect (SS-PRS) in GS:SFHS STRADL (Stratifying Depression and Resilience Longitudinally; N=4,919). GS:SFHS STRADL has data on symptoms of depression assessed by General Health Questionnaire (GHQ-28) and past 6 month SLEs using the List of Threatening Experiences (LTE-Q). Results MDD-PRS, SS-PRS and main effects of SLEs significantly predicted symptoms of depression (MDD-PRS: P=5.48×10-9; SS-PRS: P=2.63×10-4; SLEs: P=1.01×10–58, using best predictor at full cohort). The MDD-PRS-by-SLEs interaction significantly contributed to the risk of MDD at population level (p-threshold=0.01, β=0.028, SE=0.014, R2=0.077%, P=4.91×10-2), although this was stronger in females (p-threshold=1×10-5, β=0.044, SE=0.018, R2=0.19%, P=1.84×10-2) and not significant in males (p-threshold=0.1, β=0.04, SE=0.022, R2=0.16%, P=6.37×10-2). The SS-PRS-by-SLEs interaction significantly contributed to the risk of MDD in males (p-threshold=0.01, β=0.078, SE=0.022, R2=0.6%, P=3.38×10-4) but not in females (p-threshold=0.05, β=-0.027, SE=0.018, R2=0.075%, P=0.14) or in the full cohort (p-threshold=1×10-5, β=0.025, SE=0.014, R2=0.063%, P=7.75×10-2), This SS-PRS-by-SLEs interaction in males explained almost as much as the variance explained by the main MDD-PRS effect at their best predictor (p-threshold=0.102, β=0.081, SE=0.022, R2=0.66%, P=2.09×10-4). Discussion Significant genetic vulnerability-SLEs interactions predict and additional MDD risk for individuals with high predisposition and high number of reported SLEs. However, the results suggest distinct interactions between genetic vulnerabilities and SLEs on the aetiology of depression in males versus females, although replication on a larger sample would be required.

Genome-Wide Association Study Detected Novel Susceptibility Genes for Schizophrenia and Shared Trans-Populations/Diseases Genetic Effect.

Genome-wide association studies (GWASs) have identified >100 susceptibility loci for schizophrenia (SCZ) and demonstrated that SCZ is a polygenic disorder determined by numerous genetic variants but with small effect size. We conducted a GWAS in the Japanese (JPN) population (a) to detect novel SCZ-susceptibility genes and (b) to examine the shared genetic risk of SCZ across (East Asian [EAS] and European [EUR]) populations and/or that of trans-diseases (SCZ, bipolar disorder [BD], and major depressive disorder [MDD]) within EAS and between EAS and EUR (trans-diseases/populations). Among the discovery GWAS subjects (JPN-SCZ GWAS: 1940 SCZ cases and 7408 controls) and replication dataset (4071 SCZ cases and 54479 controls), both comprising JPN populations, 3 novel susceptibility loci for SCZ were identified: SPHKAP (Pbest = 4.1 × 10-10), SLC38A3 (Pbest = 5.7 × 10-10), and CABP1-ACADS (Pbest = 9.8 × 10-9). Subsequent meta-analysis between our samples and those of the Psychiatric GWAS Consortium (PGC; EUR samples) and another study detected 12 additional susceptibility loci. Polygenic risk score (PRS) prediction revealed a shared genetic risk of SCZ across populations (Pbest = 4.0 × 10-11) and between SCZ and BD in the JPN population (P ~ 10-40); however, a lower variance-explained was noted between JPN-SCZ GWAS and PGC-BD or MDD within/across populations. Genetic correlation analysis supported the PRS results; the genetic correlation between JPN-SCZ and PGC-SCZ was ρ = 0.58, whereas a similar/lower correlation was observed between the trans-diseases (JPN-SCZ vs JPN-BD/EAS-MDD, rg = 0.56/0.29) or trans-diseases/populations (JPN-SCZ vs PGC-BD/MDD, ρ = 0.38/0.12). In conclusion, (a) Fifteen novel loci are possible susceptibility genes for SCZ and (b) SCZ "risk" effect is shared with other psychiatric disorders even across populations.

EQTLs Weighted Genetic Correlation Analysis Detected Brain Region Differences in Genetic Correlations for Complex Psychiatric Disorders.

Psychiatric disorders are usually caused by the dysfunction of various brain regions. Incorporating the genetic information of brain regions into correlation analysis can provide novel clues for pathogenetic and therapeutic studies of psychiatric disorders. The latest genome-wide association study (GWAS) summary data of schizophrenia (SCZ), bipolar disorder (BIP), autism spectrum disorder (AUT), major depression disorder (MDD), and attention-deficit/hyperactivity disorder (ADHD) were obtained from the Psychiatric GWAS Consortium (PGC). The expression quantitative trait loci (eQTLs) datasets of 10 brain regions were driven from the genotype-tissue expression (GTEx) database. The PGC GWAS summaries were first weighted by the GTEx eQTLs summaries for each brain region. Linkage disequilibrium score regression was applied to the weighted GWAS summary data to detect genetic correlation for each pair of 5 disorders. Without considering brain region difference, significant genetic correlations were observed for BIP vs SCZ (P = 1.68 × 10-63), MDD vs SCZ (P = 5.08 × 10-45), ADHD vs MDD (P = 1.93 × 10-44), BIP vs MDD (P = 6.39 × 10-9), AUT vs SCZ (P = .0002), and ADHD vs SCZ (P = .0002). Utilizing brain region related eQTLs weighted LD score regression, different strengths of genetic correlations were observed within various brain regions for BIP vs SCZ, MDD vs SCZ, ADHD vs MDD, and SCZ vs ADHD. For example, the most significant genetic correlations were observed at anterior cingulate cortex (P = 1.13 × 10-34) for BIP vs SCZ. This study provides new clues for elucidating the mechanism of genetic correlations among various psychiatric disorders.

A genome-wide association study identifies two novel susceptibility loci and trans population polygenicity associated with bipolar disorder

Genome-wide association studies (GWASs) have identified several susceptibility loci for bipolar disorder (BD) and shown that the genetic architecture of BD can be explained by polygenicity, with numerous variants contributing to BD. In the present GWAS (Phase I/II), which included 2964 BD and 61 887 control subjects from the Japanese population, we detected a novel susceptibility locus at 11q12.2 (rs28456, P=6.4 × 10−9), a region known to contain regulatory genes for plasma lipid levels (FADS1/2/3). A subsequent meta-analysis of Phase I/II and the Psychiatric GWAS Consortium for BD (PGC-BD) identified another novel BD gene, NFIX (Pbest=5.8 × 10−10), and supported three regions previously implicated in BD susceptibility: MAD1L1 (Pbest=1.9 × 10−9), TRANK1 (Pbest=2.1 × 10−9) and ODZ4 (Pbest=3.3 × 10−9). Polygenicity of BD within Japanese and trans-European-Japanese populations was assessed with risk profile score analysis. We detected higher scores in BD cases both within (Phase I/II) and across populations (Phase I/II and PGC-BD). These were defined by (1) Phase II as discovery and Phase I as target, or vice versa (for ‘within Japanese comparisons’, Pbest~10−29, R2~2%), and (2) European PGC-BD as discovery and Japanese BD (Phase I/II) as target (for ‘trans-European-Japanese comparison,’ Pbest~10−13, R2~0.27%). This ‘trans population’ effect was supported by estimation of the genetic correlation using the effect size based on each population (liability estimates~0.7). These results indicate that (1) two novel and three previously implicated loci are significantly associated with BD and that (2) BD ‘risk’ effect are shared between Japanese and European populations.

Identification of SLC25A37 as a major depressive disorder risk gene

Major depressive disorder (MDD) is one of the most prevalent and disabling mental disorders, but the genetic etiology remains largely unknown. We performed a meta-analysis (14,543 MDD cases and 14,856 controls) through combining the GWAS data from the Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium and the CONVERGE consortium and identified seven SNPs (four of them located in the downstream of SCL25A37) that showed suggestive associations (P < 5.0 × 10−7) with MDD. Systematic integration (Sherlock integrative analysis) of brain eQTL and GWAS meta-analysis identified SCL25A37 as a novel MDD risk gene (P = 2.22 × 10−6). A cis SNP (rs6983724, ∼28 kb downstream of SCL25A37) showed significant association with SCL25A37 expression (P = 1.19 × 10−9) and suggestive association with MDD (P = 1.65 × 10−7). We validated the significant association between rs6983724 and SCL25A37 expression in independent expression datasets. Finally, we found that SCL25A37 is significantly down-regulated in hippocampus and blood of MDD patients (P = 3.49 × 10−3 and P = 2.66 × 10−13, respectively). Our findings implicate that the SCL25A37 is a MDD susceptibility gene whose expression may influence MDD risk. The consistent down-regulation of SCL25A37 in MDD patients in three independent samples suggest that SCL25A37 may be used as a potential biomarker for MDD diagnosis. Further functional characterization of SCL25A37 may provide a potential target for future therapeutics and diagnostics.

Polygenic risk score prediction of antipsychotic dosage in schizophrenia

ObjectiveGenetic variants have yet to be identified as reliable predictors of antipsychotic dosage. The purpose of this study is to quantify significant genetic risk variants prioritized from the Psychiatric GWAS Consortium (PGC2) study for schizophrenia as a polygenic score to test our hypothesis that it may represent symptom severity in patients and therefore predict antipsychotic dosage. MethodsAntipsychotic medication and dosage were collected in our sample of 83 patients with schizophrenia spectrum disorders of a homogeneous European background. Antipsychotic dosage was standardized according to the Product Monograph (PM%), chlorpromazine equivalents (CPZe), and Defined Daily Dose (DDD). We calculated polygenic risk scores (PRS) for the significant risk loci identified from the PGC2 GWAS to predict dosage using a linear regression model. ResultsIn our analysis, the PRS showed no significant association with PM%, CPZe, and DDD dosage. Considering symptom severity and overall functioning, our PRS was similarly not significantly associated with Global Assessment of Functioning (GAF) scores. DiscussionOur results do not provide evidence for a polygenic inheritance of schizophrenia that influences levels of antipsychotic dosage. To the best of our knowledge, this is one of the first studies of its kind to use the PRS from the PGC2 significant risk variants to predict a clinically relevant phenotype. The PRS offers a novel approach to analyzing the genetic liability for many clinically relevant phenotypes in schizophrenia.

Evidence for schizophrenia susceptibility alleles in the Indian population: An association of neurodevelopmental genes in case–control and familial samples

Schizophrenia is a severe psychiatric disorder with lifetime prevalence of ~1% worldwide. A genotyping study was conducted using a custom panel of Illumina 1536 SNPs in 840 schizophrenia cases and 876 controls (351 patients and 385 controls from North India; and 436 patients, 401 controls and 143 familial samples with 53 probands containing 37 complete and 16 incomplete trios from South India). Meta-analysis of this population of Indo-European and Dravidian ancestry identified three strongly associated variants with schizophrenia: STT3A (rs548181, p=1.47×10−5), NRG1 (rs17603876, p=8.66×10−5) and GRM7 (rs3864075, p=4.06×10−3). Finally, a meta-analysis was conducted comparing our data with data from the Schizophrenia Psychiatric Genome-Wide Association Study Consortium (PGC-SCZ) that supported rs548181 (p=1.39×10−7). In addition, combined analysis of sporadic case–control association and a transmission disequilibrium test in familial samples from South Indian population identified three associations: rs1062613 (p=3.12×10−3), a functional promoter variant of HTR3A; rs6710782 (p=3.50×10−3), an intronic variant of ERBB4; and rs891903 (p=1.05×10−2), an intronic variant of EBF1. The results support the risk variants observed in the earlier published work and suggest a potential role of neurodevelopmental genes in the schizophrenia pathogenesis.

Genetic liability for schizophrenia predicts risk of immune disorders

BackgroundSchizophrenia patients and their parents have an increased risk of immune disorders compared to population controls and their parents. This may be explained by genetic overlap in the pathogenesis of both types of disorders. The purpose of this study was to investigate the genetic overlap between schizophrenia and three immune disorders and to compare with the overlap between schizophrenia and two disorders not primarily characterized by immune dysregulation: bipolar disorder and type 2 diabetes. MethodsWe performed a polygenic risk score analysis using results from the schizophrenia Psychiatric GWAS consortium (PGC) (8922 cases and 9528 controls) and five Wellcome Trust Case Control Consortium (WTCCC) case samples as target cases: bipolar disorder (n=1998), type 1 diabetes (n=2000), Crohn's diseases (n=2005), rheumatoid arthritis (n=1999), and type 2 diabetes (n=1999). The WTCCC British Birth Cohort and National Blood Service samples (n=3004) were used as target controls. Additionally, we tested whether schizophrenia polygenic risk scores significantly differed between patients with immune disorder, bipolar disorder, and type 2 diabetes respectively. ResultsPolygenic risk scores for schizophrenia significantly predicted disease status in all three immune disorder samples (Nagelkerke-R2 1.1%–1.3%; p<0.05). The polygenic risk of schizophrenia in patients with immune disorders was significantly lower than in patients with bipolar disorder (Nagelkerke-R2 6.0%; p<0.05), but higher than in type 2 diabetes patients (Nagelkerke-R2 0.5%; p<0.05). ConclusionsOur results suggest that genetic factors are shared between schizophrenia and immune disorders. This contributes to an accumulating body of evidence that immune processes may play a role in the etiology of schizophrenia.

Variability in working memory performance explained by epistasis vs polygenic scores in the ZNF804A pathway.

We investigated the variation in neuropsychological function explained by risk alleles at the psychosis susceptibility gene ZNF804A and its interacting partners using single nucleotide polymorphisms (SNPs), polygenic scores, and epistatic analyses. Of particular importance was the relative contribution of the polygenic score vs epistasis in variation explained. To (1) assess the association between SNPs in ZNF804A and the ZNF804A polygenic score with measures of cognition in cases with psychosis and (2) assess whether epistasis within the ZNF804A pathway could explain additional variation above and beyond that explained by the polygenic score. Patients with psychosis (n = 424) were assessed in areas of cognitive ability impaired in schizophrenia including IQ, memory, attention, and social cognition. We used the Psychiatric GWAS Consortium 1 schizophrenia genome-wide association study to calculate a polygenic score based on identified risk variants within this genetic pathway. Cognitive measures significantly associated with the polygenic score were tested for an epistatic component using a training set (n = 170), which was used to develop linear regression models containing the polygenic score and 2-SNP interactions. The best-fitting models were tested for replication in 2 independent test sets of cases: (1) 170 individuals with schizophrenia or schizoaffective disorder and (2) 84 patients with broad psychosis (including bipolar disorder, major depressive disorder, and other psychosis). Participants completed a neuropsychological assessment battery designed to target the cognitive deficits of schizophrenia including general cognitive function, episodic memory, working memory, attentional control, and social cognition. Higher polygenic scores were associated with poorer performance among patients on IQ, memory, and social cognition, explaining 1% to 3% of variation on these scores (range, P = .01 to .03). Using a narrow psychosis training set and independent test sets of narrow phenotype psychosis (schizophrenia and schizoaffective disorder), broad psychosis, and control participants (n = 89), the addition of 2 interaction terms containing 2 SNPs each increased the R2 for spatial working memory strategy in the independent psychosis test sets from 1.2% using the polygenic score only to 4.8% (P = .11 and .001, respectively) but did not explain additional variation in control participants. These data support a role for the ZNF804A pathway in IQ, memory, and social cognition in cases. Furthermore, we showed that epistasis increases the variation explained above the contribution of the polygenic score.

Replication and cross-phenotype study based upon schizophrenia GWASs data in the Japanese population: support for association of MHC region with psychosis.

Recent genome-wide association studies (GWASs) of schizophrenia (SCZ) identified several susceptibility genes and suggested shared genetic components between SCZ and bipolar disorder (BD). We conducted a genetic association study of single nucleotide polymorphisms (SNPs) selected according to previous SCZ GWAS targeting psychotic disorders (SCZ and BD) in the Japanese population. Fifty-one SNPs were analyzed in a two-stage design using first-set screening samples (all SNPs: 1,032 SCZ, 1,012 BD, and 993 controls) and second-set replication samples ("significant" SNPs in the first-set screening analysis: 1,808 SCZ, 821 BD, and 2,321 controls). We assessed allelic associations between the selected SNPs and the three phenotypes (SCZ, BD, and "psychosis" [SCZ + BD]). Nine SNPs revealed nominal association signals for all comparisons (P(uncorrected) < 0.05), of which two SNPs located in the major histocompatibility complex region (rs7759855 in zinc finger and SCAN domain containing 31 [ZSCAN31] and rs1736913 in HLA-F antisense RNA1 [HLA-F-AS1]) were further assessed in the second-set replication samples. The associations were confirmed for rs7759855 (P(corrected) = 0.026 for psychosis; P(corrected) = 0.032 for SCZ), although the direction of effect was opposite to that in the original GWAS of the Chinese population. Finally, a meta-analysis was conducted using our two samples and using our data and data from Psychiatric GWAS Consortium (PGC), which have shown the same direction of effect. SNP in ZSCAN31 (rs7759855) had the strongest association with the phenotypes (best P = 6.8 × 10(-5) for psychosis: present plus PGC results). These data support shared risk SNPs between SCZ and BD in the Japanese population and association between MHC and psychosis.

Genetic association analysis of 300 genes identifies a risk haplotype in SLC18A2 for post-traumatic stress disorder in two independent samples.

The genetic architecture of post-traumatic stress disorder (PTSD) remains poorly understood with the vast majority of genetic association studies reporting on single candidate genes. We conducted a large genetic study in trauma-exposed European-American women (N=2538; 845 PTSD cases, 1693 controls) by testing 3742 SNPs across more than 300 genes and conducting polygenic analyses using results from the Psychiatric Genome-Wide Association Studies Consortium (PGC). We tested the association between each SNP and two measures of PTSD, a severity score and diagnosis. We found a significant association between PTSD (diagnosis) and SNPs (top SNP: rs363276, odds ratio (OR)=1.4, p=2.1E-05) in SLC18A2 (vesicular monoamine transporter 2). A haplotype analysis of 9 SNPs in SLC18A2, including rs363276, identified a risk haplotype (CGGCGGAAG, p=0.0046), and the same risk haplotype was associated with PTSD in an independent cohort of trauma-exposed African-Americans (p=0.049; N=748, men and women). SLC18A2 is involved in transporting monoamines to synaptic vesicles and has been implicated in a number of neuropsychiatric disorders including major depression. Eight genes previously associated with PTSD had SNPs with nominally significant associations (p<0.05). The polygenic analyses suggested that there are SNPs in common between PTSD severity and bipolar disorder. Our data are consistent with a genetic architecture for PTSD that is highly polygenic, influenced by numerous SNPs with weak effects, and may overlap with mood disorders. Genome-wide studies with very large samples sizes are needed to detect these types of effects.

Polygenic determinants of white matter volume derived from GWAS lack reproducibility in a replicate sample.

A recent publication reported an exciting polygenic effect of schizophrenia (SCZ) risk variants, identified by a large genome-wide association study (GWAS), on total brain and white matter volumes in schizophrenic patients and, even more prominently, in healthy subjects. The aim of the present work was to replicate and then potentially extend these findings. According to the original publication, polygenic risk scores—using single nucleotide polymorphism (SNP) information of SCZ GWAS—(polygenic SCZ risk scores; PSS) were calculated in 122 healthy subjects, enrolled in a structural magnetic resonance imaging (MRI) study. These scores were computed based on P-values and odds ratios available through the Psychiatric GWAS Consortium. In addition, polygenic white matter scores (PWM) were calculated, using the respective SNP subset in the original publication. None of the polygenic scores, either PSS or PWM, were found to be associated with total brain, white matter or gray matter volume in our replicate sample. Minor differences between the original and the present study that might have contributed to lack of reproducibility (but unlikely explain it fully), are number of subjects, ethnicity, age distribution, array technology, SNP imputation quality and MRI scanner type. In contrast to the original publication, our results do not reveal the slightest signal of association of the described sets of GWAS-identified SCZ risk variants with brain volumes in adults. Caution is indicated in interpreting studies building on polygenic risk scores without replication sample.