Facial Emotion Recognition in Psychosis and Associations With Polygenic Risk for Schizophrenia: Findings From the Multi-Center EU-GEI Case-Control Study.

BACKGROUND AND HYPOTHESIS: Facial Emotion Recognition is a key domain of social cognition associated with psychotic disorders as a candidate intermediate phenotype. In this study, we set out to investigate global and specific facial emotion recognition deficits in first-episode psychosis, and whether polygenic liability to psychotic disorders is associated with facial emotion recognition. STUDY DESIGN: 828 First Episode Psychosis (FEP) patients and 1308 population-based controls completed assessments of the Degraded Facial Affect Recognition Task (DFAR) and a subsample of 524 FEP and 899 controls provided blood or saliva samples from which we extracted DNA, performed genotyping and computed polygenic risk scores for schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MD). STUDY RESULTS: A worse ability to globally recognize facial emotion expressions was found in patients compared with controls [B= -1.5 (0.6), 95% CI -2.7 to -0.3], with evidence for stronger effects on negative emotions (fear [B = -3.3 (1.1), 95% CI -5.3 to -1.2] and anger [B = -2.3 (1.1), 95% CI -4.6 to -0.1]) than on happiness [B = 0.3 (0.7), 95% CI -1 to 1.7]. Pooling all participants, and controlling for confounds including case/control status, facial anger recognition was associated significantly with Schizophrenia Polygenic Risk Score (SZ PRS) [B = -3.5 (1.7), 95% CI -6.9 to -0.2]. CONCLUSIONS: Psychosis is associated with impaired recognition of fear and anger, and higher SZ PRS is associated with worse facial anger recognition. Our findings provide evidence that facial emotion recognition of anger might play a role as an intermediate phenotype for psychosis.

The continuity of effect of schizophrenia polygenic risk score and patterns of cannabis use on transdiagnostic symptom dimensions at first-episode psychosis: findings from the EU-GEI study.

Diagnostic categories do not completely reflect the heterogeneous expression of psychosis. Using data from the EU-GEI study, we evaluated the impact of schizophrenia polygenic risk score (SZ-PRS) and patterns of cannabis use on the transdiagnostic expression of psychosis. We analysed first-episode psychosis patients (FEP) and controls, generating transdiagnostic dimensions of psychotic symptoms and experiences using item response bi-factor modelling. Linear regression was used to test the associations between these dimensions and SZ-PRS, as well as the combined effect of SZ-PRS and cannabis use on the dimensions of positive psychotic symptoms and experiences. We found associations between SZ-PRS and (1) both negative (B = 0.18; 95%CI 0.03-0.33) and positive (B = 0.19; 95%CI 0.03-0.35) symptom dimensions in 617 FEP patients, regardless of their categorical diagnosis; and (2) all the psychotic experience dimensions in 979 controls. We did not observe associations between SZ-PRS and the general and affective dimensions in FEP. Daily and current cannabis use were associated with the positive dimensions in FEP (B = 0.31; 95%CI 0.11-0.52) and in controls (B = 0.26; 95%CI 0.06-0.46), over and above SZ-PRS. We provide evidence that genetic liability to schizophrenia and cannabis use map onto transdiagnostic symptom dimensions, supporting the validity and utility of the dimensional representation of psychosis. In our sample, genetic liability to schizophrenia correlated with more severe psychosis presentation, and cannabis use conferred risk to positive symptomatology beyond the genetic risk. Our findings support the hypothesis that psychotic experiences in the general population have similar genetic substrates as clinical disorders.

Rare Copy Number Variants Are Associated With Poorer Cognition in Schizophrenia.

BACKGROUND: Cognitive impairment in schizophrenia is a major contributor to poor outcomes, yet its causes are poorly understood. Some rare copy number variants (CNVs) are associated with schizophrenia risk and affect cognition in healthy populations, but their contribution to cognitive impairment in schizophrenia has not been investigated. We examined the effect of 12 schizophrenia CNVs on cognition in those with schizophrenia. METHODS: General cognitive ability was measured using the Measurement and Treatment Research to Improve Cognition in Schizophrenia composite z score in 875 patients with schizophrenia and in a replication sample of 519 patients with schizophrenia using Wechsler Adult Intelligence Scale Full Scale IQ. Using linear regression, we tested for association between cognition and schizophrenia CNV status, covarying for age and sex. In addition, we tested whether CNVs hitting genes in schizophrenia-enriched gene sets (loss-of-function intolerant and synaptic gene sets) were associated with cognitive impairment. RESULTS: A total of 23 schizophrenia CNV carriers were identified. Schizophrenia CNV carriers had lower general cognitive ability than nonschizophrenia CNV carriers in discovery (ß = -0.66, 95% confidence interval [CI] = -1.31 to -0.01) and replication samples (ß = -0.91, 95% CI = -1.71 to -0.11) and after meta-analysis (ß = -0.76, 95% CI = -1.26 to -0.25, p = .003). CNVs hitting loss-of-function intolerant genes were associated with lower cognition (ß = -0.15, 95% CI = -0.29 to -0.001, p = .048). CONCLUSIONS: In those with schizophrenia, cognitive ability in schizophrenia CNV carriers is 0.5-1.0 standard deviations below non-CNV carriers, which may have implications for clinical assessment and management. We also demonstrate that rare CNVs hitting genes intolerant to loss-of-function variation lead to more severe cognitive impairment, above and beyond the effect of known schizophrenia CNVs.

Jumping to conclusions, general intelligence, and psychosis liability: findings from the multi-centre EU-GEI case-control study.

BACKGROUND: The 'jumping to conclusions' (JTC) bias is associated with both psychosis and general cognition but their relationship is unclear. In this study, we set out to clarify the relationship between the JTC bias, IQ, psychosis and polygenic liability to schizophrenia and IQ. METHODS: A total of 817 first episode psychosis patients and 1294 population-based controls completed assessments of general intelligence (IQ), and JTC, and provided blood or saliva samples from which we extracted DNA and computed polygenic risk scores for IQ and schizophrenia. RESULTS: The estimated proportion of the total effect of case/control differences on JTC mediated by IQ was 79%. Schizophrenia polygenic risk score was non-significantly associated with a higher number of beads drawn (B = 0.47, 95% CI -0.21 to 1.16, p = 0.17); whereas IQ PRS (B = 0.51, 95% CI 0.25-0.76, p < 0.001) significantly predicted the number of beads drawn, and was thus associated with reduced JTC bias. The JTC was more strongly associated with the higher level of psychotic-like experiences (PLEs) in controls, including after controlling for IQ (B = -1.7, 95% CI -2.8 to -0.5, p = 0.006), but did not relate to delusions in patients. CONCLUSIONS: Our findings suggest that the JTC reasoning bias in psychosis might not be a specific cognitive deficit but rather a manifestation or consequence, of general cognitive impairment. Whereas, in the general population, the JTC bias is related to PLEs, independent of IQ. The work has the potential to inform interventions targeting cognitive biases in early psychosis.

Reinforcement learning as an intermediate phenotype in psychosis? Deficits sensitive to illness stage but not associated with polygenic risk of schizophrenia in the general population.

BACKGROUND: Schizophrenia is a complex disorder in which the causal relations between risk genes and observed clinical symptoms are not well understood and the explanatory gap is too wide to be clarified without considering an intermediary level. Thus, we aimed to test the hypothesis of a pathway from molecular polygenic influence to clinical presentation occurring via deficits in reinforcement learning. METHODS: We administered a reinforcement learning task (Go/NoGo) that measures reinforcement learning and the effect of Pavlovian bias on decision making. We modelled the behavioural data with a hierarchical Bayesian approach (hBayesDM) to decompose task performance into its underlying learning mechanisms. Study 1 included controls (n = 29, F|M = 0.81), At Risk Mental State for psychosis (ARMS, n = 23, F|M = 0.35) and FEP (First-episode psychosis, n = 26, F|M = 0.18). Study 2 included healthy adolescents (n = 735, F|M = 1.06), 390 of whom had their polygenic risk scores for schizophrenia (PRSs) calculated. RESULTS: Patients with FEP showed significant impairments in overriding Pavlovian conflict, a lower learning rate and a lower sensitivity to both reward and punishment. Less widespread deficits were observed in ARMS. PRSs did not significantly predict performance on the task in the general population, which only partially correlated with measures of psychopathology. CONCLUSIONS: Reinforcement learning deficits are observed in first episode psychosis and, to some extent, in those at clinical risk for psychosis, and were not predicted by molecular genetic risk for schizophrenia in healthy individuals. The study does not support the role of reinforcement learning as an intermediate phenotype in psychosis.

Population-based identity-by-descent mapping combined with exome sequencing to detect rare risk variants for schizophrenia.

Genome-wide association studies (GWASs) are highly effective at identifying common risk variants for schizophrenia. Rare risk variants are also important contributors to schizophrenia etiology but, with the exception of large copy number variants, are difficult to detect with GWAS. Exome and genome sequencing, which have accelerated the study of rare variants, are expensive so alternative methods are needed to aid detection of rare variants. Here we re-analyze an Irish schizophrenia GWAS dataset (n = 3,473) by performing identity-by-descent (IBD) mapping followed by exome sequencing of individuals identified as sharing risk haplotypes to search for rare risk variants in coding regions. We identified 45 rare haplotypes (>1 cM) that were significantly more common in cases than controls. By exome sequencing 105 haplotype carriers, we investigated these haplotypes for functional coding variants that could be tested for association in independent GWAS samples. We identified one rare missense variant in PCNT but did not find statistical support for an association with schizophrenia in a replication analysis. However, IBD mapping can prioritize both individual samples and genomic regions for follow-up analysis but genome rather than exome sequencing may be more effective at detecting risk variants on rare haplotypes.

Effects of MiR-137 genetic risk score on brain volume and cortical measures in patients with schizophrenia and controls.

Multiple genome-wide association studies of schizophrenia have implicated genetic variants within the gene encoding microRNA-137. As risk variants within or regulated by MIR137 have been implicated in memory performance, we investigated the additive effects of schizophrenia-associated risk variants in genes empirically regulated by MIR137 on brain regions associated with memory function. A polygenic risk score (PRS) was calculated (at a p = 0.05 threshold), using this empirically regulated MIR137 gene set, to investigate associations between this PRS and structural brain measures. These measures included total brain volume, cortical thickness, cortical surface area, and hippocampal volume, in a sample of 216 individuals consisting of healthy participants (n = 171) and patients with psychosis (n = 45). We did not observe a significant association between MIR137 PRS and these cortical thickness, surface area or hippocampal volume measures linked to memory function; a significant association between increasing PRS and decreasing total brain volume, independent of diagnosis status (R2 = 0.008, Beta = -0.09, p = 0.029), was observed. This did not survive correction for multiple testing. In conclusion, our study yielded only suggestive evidence that risk variants interacting with MIR137 impacts on cortical structure.

Cognitive Characterization of Schizophrenia Risk Variants Involved in Synaptic Transmission: Evidence of CACNA1C's Role in Working Memory.

With >100 common variants associated with schizophrenia risk, establishing their biological significance is a priority. We sought to establish cognitive effects of risk variants at loci implicated in synaptic transmission by (1) identifying GWAS schizophrenia variants whose associated gene function is related to synaptic transmission, and (2) testing for association between these and measures of neurocognitive function. We selected variants, reported in the largest GWAS to date, associated with genes involved in synaptic transmission. Associations between genotype and cognitive test score were analyzed in a discovery sample (988 Irish participants, including 798 with psychosis), and replication samples (528 UK patients with schizophrenia/schizoaffective disorder; 921 German participants including 362 patients with schizophrenia). Three loci showed significant associations with neuropsychological performance in the discovery samples. This included an association between the rs2007044 (risk allele G) within CACNA1C and poorer working memory performance (increased errors B (95% CI)=0.635-4.535, p=0.012), an effect driven mainly by the psychosis groups. In an fMRI analysis of working memory performance (n=84 healthy participants, a subset of the discovery sample), we further found evidence that the same CACNA1C allele was associated with decreased functional connectivity between the right dorsolateral prefrontal cortex and right superior occipital gyrus/cuneus and anterior cingulate cortex. In conclusion, these data provide evidence to suggest that the CACNA1C risk variant rs2007044 is associated with poorer memory function that may result from risk carriers' difficulty with top-down initiated responses caused by dysconnectivity between the right DLPFC and several cortical regions.

Cognitive analysis of schizophrenia risk genes that function as epigenetic regulators of gene expression.

Epigenetic mechanisms are an important heritable and dynamic means of regulating various genomic functions, including gene expression, to orchestrate brain development, adult neurogenesis, and synaptic plasticity. These processes when perturbed are thought to contribute to schizophrenia pathophysiology. A core feature of schizophrenia is cognitive dysfunction. For genetic disorders where cognitive impairment is more severe such as intellectual disability, there are a disproportionally high number of genes involved in the epigenetic regulation of gene transcription. Evidence now supports some shared genetic aetiology between schizophrenia and intellectual disability. GWAS have identified 108 chromosomal regions associated with schizophrenia risk that span 350 genes. This study identified genes mapping to those loci that have epigenetic functions, and tested the risk alleles defining those loci for association with cognitive deficits. We developed a list of 350 genes with epigenetic functions and cross-referenced this with the GWAS loci. This identified eight candidate genes: BCL11B, CHD7, EP300, EPC2, GATAD2A, KDM3B, RERE, SATB2. Using a dataset of Irish psychosis cases and controls (n = 1235), the schizophrenia risk SNPs at these loci were tested for effects on IQ, working memory, episodic memory, and attention. Strongest associations were for rs6984242 with both measures of IQ (P = 0.001) and episodic memory (P = 0.007). We link rs6984242 to CHD7 via a long range eQTL. These associations were not replicated in independent samples. Our study highlights that a number of genes mapping to risk loci for schizophrenia may function as epigenetic regulators of gene expression but further studies are required to establish a role for these genes in cognition. © 2016 Wiley Periodicals, Inc.

Expression profile and function of Wnt signaling mechanisms in malignant mesothelioma cells.

Malignant mesothelioma (MM) is an uncommon and particularly aggressive cancer associated with asbestos exposure, which currently presents an intractable clinical challenge. Wnt signaling has been reported to play a role in the neoplastic properties of mesothelioma cells but has not been investigated in detail in this cancer. We surveyed expression of Wnts, their receptors, and other key molecules in this pathway in well established in vitro mesothelioma models in comparison with primary mesothelial cultures. We also tested the biological response of MM cell lines to exogenous Wnt and secreted regulators, as well as targeting ß-catenin. We detected frequent expression of Wnt3 and Wnt5a, as well as Fzd 2, 4 and 6. The mRNA of Wnt4, Fzd3, sFRP4, APC and axin2 were downregulated in MM relative to mesothelial cells while LEF1 was overexpressed in MM. Functionally, we observed that Wnt3a stimulated MM proliferation while sFRP4 was inhibitory. Furthermore, directly targeting ß-catenin expression could sensitise MM cells to cytotoxic drugs. These results provide evidence for altered expression of a number of Wnt/Fzd signaling molecules in MM. Modulation of Wnt signaling in MM may prove a means of targeting proliferation and drug resistance in this cancer.

Analysis of neurogranin (NRGN) in schizophrenia.

A recent study reported a genome-wide significant association between schizophrenia and rs12807809-a SNP located approximately 3 kbp upstream of the neurogranin gene (NRGN). We sought to determine if (a) NRGN contains common exonic variants or variants affecting expression (eQTLs) that could account for the association with rs12807809 and (b) there exist rare non-synonymous highly penetrant variants that could potentially confer high risk of schizophrenia. We sequenced all four exons of NRGN in a screening set of 14 individuals but found no novel common polymorphisms. We additionally sequenced the coding exons in up to 1,113 individuals (699 cases) but this revealed only a singleton-coding variant in exon 2 (G246T leading to Gly-55 → Val amino acid change) in which prediction of function analysis suggested is likely to be benign. Finally, analysis of a brain expression dataset of at least 130 individuals did not identify any eQTLs that were correlated with associated SNP rs12807809 following correction for multiple testing.

Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease.

We sought to identify new susceptibility loci for Alzheimer's disease through a staged association study (GERAD+) and by testing suggestive loci reported by the Alzheimer's Disease Genetic Consortium (ADGC) in a companion paper. We undertook a combined analysis of four genome-wide association datasets (stage 1) and identified ten newly associated variants with P ≤ 1 × 10(-5). We tested these variants for association in an independent sample (stage 2). Three SNPs at two loci replicated and showed evidence for association in a further sample (stage 3). Meta-analyses of all data provided compelling evidence that ABCA7 (rs3764650, meta P = 4.5 × 10(-17); including ADGC data, meta P = 5.0 × 10(-21)) and the MS4A gene cluster (rs610932, meta P = 1.8 × 10(-14); including ADGC data, meta P = 1.2 × 10(-16)) are new Alzheimer's disease susceptibility loci. We also found independent evidence for association for three loci reported by the ADGC, which, when combined, showed genome-wide significance: CD2AP (GERAD+, P = 8.0 × 10(-4); including ADGC data, meta P = 8.6 × 10(-9)), CD33 (GERAD+, P = 2.2 × 10(-4); including ADGC data, meta P = 1.6 × 10(-9)) and EPHA1 (GERAD+, P = 3.4 × 10(-4); including ADGC data, meta P = 6.0 × 10(-10)).