Professor Ulli Schall

Background: Polygenic scores (PGSs), which assess the genetic risk of individuals for a disease, are calculated as a weighted count of risk alleles identified in genome-wide association studies. PGS methods differ in which DNA variants are included and the weights assigned to them; some require an independent tuning sample to help inform these choices. PGSs are evaluated in independent target cohorts with known disease status. Variability between target cohorts is observed in applications to real data sets, which could reflect a number of factors, e.g., phenotype definition or technical factors. Methods: The Psychiatric Genomics Consortium Working Groups for schizophrenia and major depressive disorder bring together many independently collected case-control cohorts. We used these resources (31,328 schizophrenia cases, 41,191 controls; 248,750 major depressive disorder cases, 563,184 controls) in repeated application of leave-one-cohort-out meta-analyses, each used to calculate and evaluate PGS in the left-out (target) cohort. Ten PGS methods (the baseline PC+T method and 9 methods that model genetic architecture more formally: SBLUP, LDpred2-Inf, LDpred-funct, LDpred2, Lassosum, PRS-CS, PRS-CS-auto, SBayesR, MegaPRS) were compared. Results: Compared with PC+T, the other 9 methods gave higher prediction statistics, MegaPRS, LDPred2, and SBayesR significantly so, explaining up to 9.2% variance in liability for schizophrenia across 30 target cohorts, an increase of 44%. For major depressive disorder across 26 target cohorts, these statistics were 3.5% and 59%, respectively. Conclusions: Although the methods that more formally model genetic architecture have similar performance, MegaPRS, LDpred2, and SBayesR rank highest in most comparisons and are recommended in applications to psychiatric disorders.

We performed a transcriptome-wide meta-analysis and gene co-expression network analysis to identify genes and gene networks dysregulated in the peripheral blood of bipolar disorder (BD) cases relative to unaffected comparison subjects, and determined the specificity of the transcriptomic signatures of BD and schizophrenia (SZ). Nineteen genes and 4 gene modules were significantly differentially expressed in BD cases. Thirteen gene modules were shown to be differentially expressed in a combined case-group of BD and SZ subjects called ¿major psychosis¿, including genes biologically linked to apoptosis, reactive oxygen, chromatin remodeling, and immune signaling. No modules were differentially expressed between BD and SZ cases. Machine-learning classifiers trained to separate diagnostic classes based solely on gene expression profiles could distinguish BD cases from unaffected comparison subjects with an area under the curve (AUC) of 0.724, as well as BD cases from SZ cases with AUC = 0.677 in withheld test samples. We introduced a novel and straightforward method called ¿polytranscript risk scoring¿ that could distinguish BD cases from unaffected subjects (AUC = 0.672) and SZ cases (AUC = 0.607) significantly better than expected by chance. Taken together, our results highlighted gene expression alterations common to BD and SZ that involve biological processes of inflammation, oxidative stress, apoptosis, and chromatin regulation, and highlight disorder-specific changes in gene expression that discriminate the major psychoses.

Objective: Schizophrenia has recently been associated with widespread white matter microstructural abnormalities, but the functional effects of these abnormalities remain unclear. Widespread heterogeneity of results from studies published to date preclude any definitive characterization of the relationship between white matter and cognitive performance in schizophrenia. Given the relevance of deficits in cognitive function to predicting social and functional outcomes in schizophrenia, the authors carried out a meta-analysis of available data through the ENIGMA Consortium, using a common analysis pipeline, to elucidate the relationship between white matter microstructure and a measure of general cognitive performance, IQ, in patients with schizophrenia and healthy participants. Methods: The meta-analysis included 760 patients with schizophrenia and 957 healthy participants from 11 participating ENIGMA Consortium sites. For each site, principal component analysis was used to calculate both a global fractional anisotropy component (gFA) and a fractional anisotropy component for six long association tracts (LA-gFA) previously associated with cognition. Results: Meta-analyses of regression results indicated that gFA accounted for a significant amount of variation in cognition in the full sample (effect size [Hedges¿ g]=0.27, CI=0.17¿0.36), with similar effects sizes observed for both the patient (effect size=0.20, CI=0.05¿0.35) and healthy participant groups (effect size=0.32, CI=0.18¿0.45). Comparable patterns of association were also observed between LA-gFA and cognition for the full sample (effect size=0.28, CI=0.18¿0.37), the patient group (effect size=0.23, CI=0.09¿0.38), and the healthy participant group (effect size=0.31, CI=0.18¿0.44). Conclusions: This study provides robust evidence that cognitive ability is associated with global structural connectivity, with higher fractional anisotropy associated with higher IQ. This association was independent of diagnosis; while schizophrenia patients tended to have lower fractional anisotropy and lower IQ than healthy participants, the comparable size of effect in each group suggested a more general, rather than disease-specific, pattern of association.

Objectives: Large-scale genetic analysis of common variation in schizophrenia has been a powerful approach to understanding this complex but highly heritable psychotic disorder. To further investigate loci, genes and pathways associated more specifically in the well-characterized Australian Schizophrenia Research Bank cohort, we applied genome-wide single-nucleotide polymorphism analysis in these three annotation categories. Methods: We performed a case¿control genome-wide association study in 429 schizophrenia samples and 255 controls. Post-genome-wide association study analyses were then integrated with genomic annotations to explore the enrichment of variation at the gene and pathway level. We also examine candidate single-nucleotide polymorphisms with potential function within expression quantitative trait loci and investigate overall enrichment of variation within tissue-specific functional regulatory domains of the genome. Results: The strongest finding (p = 2.01 × 10-6, odds ratio = 1.82, 95% confidence interval = [1.42, 2.33]) in genome-wide association study was with rs10252923 at 7q21.13, downstream of FZD1 (frizzled class receptor 1). While this did not stand alone after correction, the involvement of FZD1 was supported by gene-based analysis, which exceeded the threshold for genome-wide significance (p = 2.78 × 10-6). Conclusion: The identification of FZD1, as an independent association signal at the gene level, supports the hypothesis that the Wnt signalling pathway is altered in the pathogenesis of schizophrenia and may be an important target for therapeutic development.

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

Background: It has long been recognized that sustained or repeated child maltreatment has lasting psychological and emotional effects on the victims. This has helped to inform the criminal and civil justice systems how best to deal with perpetrators of abuse, as well social and health services when treating the victims. However, what is generally less well recognized is that physical and emotional abuse has a lasting and potentially non-reversible effect on brain function. Methods: We conducted a literature review on the forensic, mental, psychological, and pathophysiological impact of child maltreatment and discuss the implications of child maltreatment as a potential mitigating factor in criminal court in cases where victims of abuse become perpetrators themselves. Findings: Repeated exposure to traumatic experiences changes the responsiveness in the hypothalamus-pituitary-adrenal axis with lasting consequences in the developing brain for structures, such as the hippocampus and amygdala. These physiological changes are thought to cause a range of mental disorders, which are associated with poor affect regulation, anxiety, depression, and substance abuse. Conclusions: The importance of developing our understanding of the long-term effects of child abuse and neglect cannot be overestimated as the result of child maltreatment will perpetrate criminal acts since offenders have higher rates of mental illness than the general community.

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.

Schizophrenia is a debilitating psychiatric disorder with approximately 1% lifetime risk globally. Large-scale schizophrenia genetic studies have reported primarily on European ancestry samples, potentially missing important biological insights. Here, we report the largest study to date of East Asian participants (22,778 schizophrenia cases and 35,362 controls), identifying 21 genome-wide-significant associations in 19 genetic loci. Common genetic variants that confer risk for schizophrenia have highly similar effects between East Asian and European ancestries (genetic correlation = 0.98 ± 0.03), indicating that the genetic basis of schizophrenia and its biology are broadly shared across populations. A fixed-effect meta-analysis including individuals from East Asian and European ancestries identified 208 significant associations in 176 genetic loci (53 novel). Trans-ancestry fine-mapping reduced the sets of candidate causal variants in 44 loci. Polygenic risk scores had reduced performance when transferred across ancestries, highlighting the importance of including sufficient samples of major ancestral groups to ensure their generalizability across populations.

One of the most robust electrophysiological features of schizophrenia is reduced mismatch negativity, a component of the event related potential (ERP) induced by rare and unexpected stimuli in an otherwise regular pattern. Emerging evidence suggests that mismatch negativity (MMN) is not the only ERP index of deviance detection in the mammalian brain and that sensitivity to deviant sounds in a regular background can be observed at earlier latencies in both the human and rodent brain. Pharmacological studies in humans and rodents have previously found that MMN reductions similar to those seen in schizophrenia can be elicited by N-methyl-D-aspartate (NMDA) receptor antagonism, an observation in agreement with the hypothesised role of NMDA receptor hypofunction in schizophrenia pathogenesis. However, it is not known how NMDA receptor antagonism affects early deviance detection responses. Here, we show that NMDA antagonism impacts both early and late deviance detection responses. By recording EEG in awake, freely-moving rats in a drug-free condition and after varying doses of NMDA receptor antagonist MK-801, we found the hypothesised reduction of deviance detection for a late, negative potential (N55). However, the amplitude of an early component, P13, as well as deviance detection evident in the same component, were increased by NMDA receptor antagonism. These findings indicate that late deviance detection in rats is similar to human MMN, but the surprising effect of MK-801 in increasing ERP amplitudes as well as deviance detection at earlier latencies suggests that future studies in humans should examine ERPs over early latencies in schizophrenia and after NMDA antagonism.

Background: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group. Methods: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11¿78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10¿87 years; 53% male) assessed with standardized methods at 39 centers worldwide. Results: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset. Conclusions: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia.

Genetic correlation is a key population parameter that describes the shared genetic architecture of complex traits and diseases. It can be estimated by current state-of-art methods, i.e., linkage disequilibrium score regression (LDSC) and genomic restricted maximum likelihood (GREML). The massively reduced computing burden of LDSC compared to GREML makes it an attractive tool, although the accuracy (i.e., magnitude of standard errors) of LDSC estimates has not been thoroughly studied. In simulation, we show that the accuracy of GREML is generally higher than that of LDSC. When there is genetic heterogeneity between the actual sample and reference data from which LD scores are estimated, the accuracy of LDSC decreases further. In real data analyses estimating the genetic correlation between schizophrenia (SCZ) and body mass index, we show that GREML estimates based on ~150,000 individuals give a higher accuracy than LDSC estimates based on ~400,000 individuals (from combined meta-data). A GREML genomic partitioning analysis reveals that the genetic correlation between SCZ and height is significantly negative for regulatory regions, which whole genome or LDSC approach has less power to detect. We conclude that LDSC estimates should be carefully interpreted as there can be uncertainty about homogeneity among combined meta-datasets. We suggest that any interesting findings from massive LDSC analysis for a large number of complex traits should be followed up, where possible, with more detailed analyses with GREML methods, even if sample sizes are lesser.

Maternal exposure to infectious agents during gestation has been identified as a significant risk factor for schizophrenia. Using a mouse model, past work has demonstrated that the gestational timing of the immune-activating event can impact the behavioural phenotype and expression of dopaminergic and glutamatergic neurotransmission markers in the offspring. In order to determine the inter-species generality of this effect to rats, another commonly used model species, the current study investigated the impact of a viral mimetic Poly (I:C) at either an early (gestational day 10) or late (gestational day 19) time-point on schizophrenia-related behaviour and neurotransmitter receptor expression in rat offspring. Exposure to Poly (I:C) in late, but not early, gestation resulted in transient impairments in working memory. In addition, male rats exposed to maternal immune activation (MIA) in either early or late gestation exhibited sensorimotor gating deficits. Conversely, neither early nor late MIA exposure altered locomotor responses to MK-801 or amphetamine. In addition, increased dopamine 1 receptor mRNA levels were found in the nucleus accumbens of male rats exposed to early gestational MIA. The findings from this study diverge somewhat from previous findings in mice with MIA exposure, which were often found to exhibit a more comprehensive spectrum of schizophrenia-like phenotypes in both males and females, indicating potential differences in the neurodevelopmental vulnerability to MIA exposure in the rat with regards to schizophrenia related changes.

White matter abnormalities associated with schizophrenia have been widely reported, although the consistency of findings across studies is moderate. In this study, neuroimaging was used to investigate white matter pathology and its impact on whole-brain white matter connectivity in one of the largest samples of patients with schizophrenia. Fractional anisotropy (FA) and mean diffusivity (MD) were compared between patients with schizophrenia or schizoaffective disorder (n = 326) and age-matched healthy controls (n = 197). Between-group differences in FA and MD were assessed using voxel-based analysis and permutation testing. Automated whole-brain white matter fiber tracking and the network-based statistic were used to characterize the impact of white matter pathology on the connectome and its rich club. Significant reductions in FA associated with schizophrenia were widespread, encompassing more than 40% (234ml) of cerebral white matter by volume and involving all cerebral lobes. Significant increases in MD were also widespread and distributed similarly. The corpus callosum, cingulum, and thalamic radiations exhibited the most extensive pathology according to effect size. More than 50% of cortico-cortical and cortico-subcortical white matter fiber bundles comprising the connectome were disrupted in schizophrenia. Connections between hub regions comprising the rich club were disproportionately affected. Pathology did not differ between patients with schizophrenia and schizoaffective disorder and was not mediated by medication. In conclusion, although connectivity between cerebral hubs is most extensively disturbed in schizophrenia, white matter pathology is widespread, affecting all cerebral lobes and the cerebellum, leading to disruptions in the majority of the brain's fiber bundles.

The application of microarray technology in schizophrenia research was heralded as paradigm-shifting, as it allowed for high-throughput assessment of cell and tissue function. This technology was widely adopted, initially in studies of postmortem brain tissue, and later in studies of peripheral blood. The collective body of schizophrenia microarray literature contains apparent inconsistencies between studies, with failures to replicate top hits, in part due to small sample sizes, cohort-specific effects, differences in array types, and other confounders. In an attempt to summarize existing studies of schizophrenia cases and non-related comparison subjects, we performed two mega-analyses of a combined set of microarray data from postmortem prefrontal cortices (n = 315) and from ex-vivo blood tissues (n = 578). We adjusted regression models per gene to remove non-significant covariates, providing best-estimates of transcripts dysregulated in schizophrenia. We also examined dysregulation of functionally related gene sets and gene co-expression modules, and assessed enrichment of cell types and genetic risk factors. The identities of the most significantly dysregulated genes were largely distinct for each tissue, but the findings indicated common emergent biological functions (e.g. immunity) and regulatory factors (e.g., predicted targets of transcription factors and miRNA species across tissues). Our network-based analyses converged upon similar patterns of heightened innate immune gene expression in both brain and blood in schizophrenia. We also constructed generalizable machine-learning classifiers using the blood-based microarray data. Our study provides an informative atlas for future pathophysiologic and biomarker studies of schizophrenia.

Background Intervention trials for young people at ultra high risk (UHR) for psychosis have shown cognitive behaviour therapy (CBT) to have promising effects on treating psychotic symptoms but have not focused on functional outcomes. We hypothesized that compared to an active control, CBT would: (i) reduce the likelihood of, and/or delay, transition to psychosis; (ii) reduce symptom severity while improving social functioning and quality of life, whether or not transition occurred. Method This was a single-blind randomised controlled trial for young people at UHR for psychosis comparing CBT to an active control condition, Non Directive Reflective Listening (NDRL), both in addition to standard care, with a 6 month treatment phase and 12 months of follow-up. Statistical analysis is based on intention-to-treat and used random effect models to estimate treatment effects common to all time-points. Results Fifty-seven young people (mean age = 16.5 years) were randomised to CBT (n = 30) or NDRL (n = 27). Rate of transition to psychosis was 5%; the 3 transitions occurred in the CBT condition (baseline, 2 months, 5 months respectively). The NDRL condition resulted in a significantly greater reduction in distress associated with psychotic symptoms compared to CBT (treatment effect = 36.71, standard error = 16.84, p = 0.029). There were no significant treatment effects on frequency and intensity of psychotic symptoms, global, social or role functioning. Conclusion Our sample was higher functioning, younger and experiencing lower levels of psychotic like experiences than other trials. The significantly better treatment effect of NDRL on distress associated with psychotic symptoms supports the recommendations for a stepped-care model of service delivery. This treatment approach would accommodate the younger UHR population and facilitate timely intervention. Trial registration: ANZCTR 12606000101583

Since its inception in the 1970s, the mismatch negativity (MMN) event-related potential has improved our understanding of pre-attentive detection of rule violations, which is a fundamental cognitive process considered by some a form of "primitive intelligence". The body of research to date ranges from animal studies (i.e. when investigating the neural mechanisms and pharmacological properties of MMN generation) to researching the psychophysiological nature of human consciousness. MMN therefore offers the possibility to detect abnormal functioning in the neural system involved in MMN generation, such as it occurs in some neurodevelopmental disorders or patients in vegetative state. While the clinical research data holds considerable promise for translation into clinical practice, standardization and normative data of an optimized (i.e. disorder-specific) MMN recording algorithm is needed in order for MMN to become a valuable clinical investigation tool.

The early detection of young people at-risk of developing a severe mental illness like schizophrenia offers the opportunity of introducing treatment earlier than currently possible. There is some evidence that early intervention improves prognosis and functional outcome, or even prevents the full clinical manifestation of the condition in some individuals. A key prerequisite to facilitate early intervention would be a biomarker that can reliably predict a transition to schizophrenia. A smaller event-related mismatch negativity (MMN) potential has emerged as one of the most robust psychophysiological finding in schizophrenia akin of a biomarker of the condition. More recent research further demonstrates that MMN, but also P3a amplitudes, are already reduced in the prodromal phase of illness. Several lines of pre-clinical and clinical research support this notion and are reviewed in this article together with current obstacles, which are still limiting the translation of MMN as a biomarker into clinical practice.

Background: Social difficulties are often noted among people with intellectual disabilities. Children and adults with 22q.11.2 deletion syndrome (22q11DS) often have poorer social competence as well as poorer performance on measures of executive and social-cognitive skills compared with typically developing young people. However, the relationship between social functioning and more basic processes of social cognition and executive functioning are not well understood in 22q11DS. The present study examined the relationship between social-cognitive measures of emotion attribution and theory of mind with executive functioning and their contribution to social competence in 22q11DS. Method: The present cross-sectional study measured social cognition and executive performance of 24 adolescents with 22q11DS compared with 27 age-matched typically developing controls. Social cognition was tested using the emotion attribution task (EAT) and a picture sequencing task (PST), which tested mentalising (false-belief), sequencing, cause and effect, and inhibition. Executive functioning was assessed using computerised versions of the Tower of London task and working memory measures of spatial and non-spatial ability. Social competence was also assessed using the parent-reported Strengths and Difficulties Questionnaire. Results: Adolescents with 22q11DS showed impaired false-belief, emotion attribution and executive functioning compared with typically developing control participants. Poorer performance was reported on all story types in the PST, although, patterns of errors and response times across story types were similar in both groups. General sequencing ability was the strongest predictor of false-belief, and performance on the false-belief task predicted emotion attribution accuracy. Intellectual functioning, rather than theory of mind or executive functioning, predicted social competence in 22q11DS. Conclusions: Performance on social-cognitive tasks of theory of mind indicate evidence of a general underlying dysfunction in 22q11DS that includes executive ability to understand cause and effect, to logically reason about social scenarios and also to inhibit responses to salient, but misleading cues. However, general intellectual ability is closely related to actual social competence suggesting that a generalised intellectual deficit coupled with more specific executive impairments may best explain poor social cognition in 22q11DS.

This study investigated neurodevelopmental changes in sound processing by recording mismatch negativity (MMN) in response to various degrees of sound complexity in 18 mildly to moderately autistic versus 15 healthy boys aged between 6 and 15¿years. Autistic boys presented with lower IQ and poor performance on a range of executive and social function measures when compared to their healthy counterparts. We found that MMN in response to duration deviants was less lateralized in the clinical group whereas larger amplitudes correlated with advanced age, thus capturing neurodevelopmental changes. Larger MMN in response to speech-like sound deviants was associated with better verbal fluency and executive function performance, respectively, but did not reliably discriminate the two groups.

Converging evidence from epidemiological, clinical and neuropsychological research suggests a link between cannabis use and increased risk of psychosis. Long-term cannabis use has also been related to deficit-like "negative" symptoms and cognitive impairment that resemble some of the clinical and cognitive features of schizophrenia. The current functional brain imaging study investigated the impact of a history of heavy cannabis use on impaired executive function in first-episode schizophrenia patients. Whilst performing the Tower of London task in a magnetic resonance imaging scanner, event-related blood oxygenation level-dependent (BOLD) brain activation was compared between four age and gender-matched groups: 12 first-episode schizophrenia patients; 17 long-term cannabis users; seven cannabis using first-episode schizophrenia patients; and 17 healthy control subjects. BOLD activation was assessed as a function of increasing task difficulty within and between groups as well as the main effects of cannabis use and the diagnosis of schizophrenia. Cannabis users and non-drug using first-episode schizophrenia patients exhibited equivalently reduced dorsolateral prefrontal activation in response to task difficulty. A trend towards additional prefrontal and left superior parietal cortical activation deficits was observed in cannabis-using first-episode schizophrenia patients while a history of cannabis use accounted for increased activation in the visual cortex. Cannabis users and schizophrenia patients fail to adequately activate the dorsolateral prefrontal cortex, thus pointing to a common working memory impairment which is particularly evident in cannabis-using first-episode schizophrenia patients. A history of heavy cannabis use, on the other hand, accounted for increased primary visual processing, suggesting compensatory imagery processing of the task.

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.

The molecular mechanisms underlying schizophrenia remain largely unknown. Although schizophrenia is a mental disorder, there is increasing evidence to indicate that inflammatory processes driven by diverse environmental factors play a significant role in its development. With gene expression studies having been conducted across a variety of sample types, e.g., blood and postmortem brain, it is possible to investigate convergent signatures that may reveal interactions between the immune and nervous systems in schizophrenia pathophysiology. We conducted two meta-analyses of schizophrenia microarray gene expression data (N= 474) and non-psychiatric control (N= 485) data from postmortem brain and blood. Then, we assessed whether significantly dysregulated genes in schizophrenia could be shared between blood and brain. To validate our findings, we selected a top gene candidate and analyzed its expression by RT-qPCR in a cohort of schizophrenia subjects stabilized by atypical antipsychotic monotherapy (N= 29) and matched controls (N= 31). Meta-analyses highlighted inflammation as the major biological process associated with schizophrenia and that the chemokine receptor CX3CR1 was significantly down-regulated in schizophrenia. This differential expression was also confirmed in our validation cohort. Given both the recent data demonstrating selective CX3CR1 expression in subsets of neuroimmune cells, as well as behavioral and neuropathological observations of CX3CR1 deficiency in mouse models, our results of reduced CX3CR1 expression adds further support for a role played by monocyte/microglia in the neurodevelopment of schizophrenia.

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R2 increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

The neural response to occasional variations in acoustic stimuli in a regular sequence of sounds generates an N-methyl-D-aspartate receptor-modulated event-related potential in primates and rodents in the primary auditory cortex known as mismatch negativity (MMN). The current study investigated MMN in pigeons (Columba livia L) through intracranial recordings from Field L of the caudomedial nidopallium, the avian functional equivalent of the mammalian primary auditory cortex. Auditory evoked field potentials were recorded from awake birds using a low-frequency (800 Hz) and high-frequency (1400 Hz) deviant auditory oddball procedure with deviant-as-standard (flip-flop design) and multiple-standard control conditions. An MMN-like field potential was recorded and blocked with systemic 5 mg/kg ketamine administration. Our results are similar to human and rodent findings of an MMN-like event-related potential in birds suggestive of similar auditory sensory memory mechanisms in birds and mammals that are homologue from a common ancestor 300 million years ago or resulted from convergent evolution.

Mismatch negativity (MMN) is a scalp-recorded electrical potential that occurs in humans in response to an auditory stimulus that defies previously established patterns of regularity. MMN amplitude is reduced in people with schizophrenia. In this study, we aimed to develop a robust and replicable rat model of MMN, as a platform for a more thorough understanding of the neurobiology underlying MMN. One of the major concerns for animal models of MMN is whether the rodent brain is capable of producing a human-like MMN, which is not a consequence of neural adaptation to repetitive stimuli. We therefore tested several methods that have been used to control for adaptation and differential exogenous responses to stimuli within the oddball paradigm. Epidural electroencephalographic electrodes were surgically implanted over different cortical locations in adult rats. Encephalographic data were recorded using wireless telemetry while the freely-moving rats were presented with auditory oddball stimuli to assess mismatch responses. Three control sequences were utilized: the flip-flop control was used to control for differential responses to the physical characteristics of standards and deviants; the many standards control was used to control for differential adaptation, as was the cascade control. Both adaptation and adaptation-independent deviance detection were observed for high frequency (pitch), but not low frequency deviants. In addition, the many standards control method was found to be the optimal method for observing both adaptation effects and adaptation-independent mismatch responses in rats. Inconclusive results arose from the cascade control design as it is not yet clear whether rats can encode the complex pattern present in the control sequence. These data contribute to a growing body of evidence supporting the hypothesis that rat brain is indeed capable of exhibiting human-like MMN, and that the rat model is a viable platform for the further investigation of the MMN and its associated neurobiology.

Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia. © 2014 Macmillan Publishers Limited. All rights reserved.

Repetitive patterning facilitates inferences about likely properties of sound to follow. Mismatch negativity (MMN) occurs when sound fails to match an inference. Smaller MMN in schizophrenia indexes deficient gain control (difference in utilizing a limited dynamic range). Although it is clear that this group has a lower limit to MMN size, this study addressed whether smaller MMN indicates impaired perceptual inference. MMN was elicited to four deviants in two sequences: one in which occurrence was random and one in which it was paired. Despite smaller MMN, persons with schizophrenia are equally able to reduce MMN size evoked by a deviant when its occurrence is cued. Results also expose alterations in the evoked response to repeated sounds that appear to be exacerbations of age-related amplitude decline. Since these anomalies impact the computed MMN, they highlight the need to identify all contributions to limits in gain control in schizophrenia. © 2014 Society for Psychophysiological Research.

Transcranial direct current stimulation (tDCS) is a non-invasive intervention altering neural plasticity by modulating neuronal excitability of pre- and postsynaptic neuron populations, which has been shown to improve depression symptoms and cognition. We investigated the effects of a single session of 20 min of 2 mA left-prefrontal anodal versus sham stimulation on auditory event-related potentials (ERPs) in 11 male and 5 female healthy subjects (mean age of 28.6 [SD 6.2] years) by employing a randomized single-blind crossover design. Stimulation effects on cortical glutamate (Glu) and glutamine (Glx) levels were subsequently measured in 12 of the 16 healthy subjects in a 3 T proton magnetic resonance spectroscopy scan. tDCS was associated with a significant increase of N1 amplitudes while smaller P3b amplitudes correlated with higher cortical Glu and Glx levels in the stimulated brain area when performing an auditory go/no-go discrimination task. tDCS did not change mismatch negativity, nor task performance or cortical Glu/Glx levels which, together with N1 amplitudes, depended on stimulation order ("sham" versus "active"). Increased N1 amplitudes are consistent with higher levels of cortical excitability following prefrontal anodal tDCS. The failure to replicate Glu/Glx changes with tDCS may have been masked by between-session carry-over effects while ceiling effects may have masked tDCS effects on task performance. © 2014 Elsevier GmbH. All rights reserved.

Background: 22q11.2 deletion syndrome (22q11DS) is associated with a number of physical anomalies and neuropsychological deficits including impairments in executive and sensorimotor function. It is estimated that 25% of children with 22q11DS will develop schizophrenia and other psychotic disorders later in life. Evidence of genetic transmission of information processing deficits in schizophrenia suggests performance in 22q11DS individuals will enhance understanding of the neurobiological and genetic substrates associated with information processing. In this report, we examine information processing in 22q11DS using measures of startle eyeblink modification and antisaccade inhibition to explore similarities with schizophrenia and associations with neurocognitive performance. Methods: Startle modification (passive and active tasks; 120- and 480-ms pre-pulse intervals) and antisaccade inhibition were measured in 25 individuals with genetically confirmed 22q11DS and 30 healthy control subjects. Results: Individuals with 22q1 1DS exhibited increased antisaccade error as well as some evidence (trend-level effect) of impaired sensorimotor gating during the active condition, suggesting a dysfunction in controlled attentional processing, rather than a pre-attentive dysfunction using this paradigm. Conclusions: The findings from the present study show similarities with previous studies in clinical populations associated with 22q11DS such as schizophrenia that may indicate shared dysfunction of inhibition pathways in these groups.

Cognitive impairment is one of the most significant factors determining the long-term rehabilitation prospects of schizophrenia patients. Cognitive training has been shown to be beneficial; however, effect sizes of cognitive remediation remain relatively low. Anodal transcranial direct current stimulation (tDCS) increases cortical excitability along with larger N1 auditory event-related potentials (ERPs), thus providing a non-invasive physiological mechanism that is potentially capable of facilitating cognitive training of schizophrenia patients. The current study investigated the effects of left-prefrontal anodal tDCS on auditory discrimination performance and N1, Mismatch Negativity (MMN), and P3b ERPs, which have been linked to cognitive and global function deficits in schizophrenia. We compared 20 min of 2 mA tDCS versus sham stimulation in 14 schizophrenia patients by employing a randomised crossover design. Patients performed equally well in a go/no-go auditory discrimination task when compared to healthy subjects but presented with significantly smaller N1, MMN and P3b amplitudes, which did not change with tDCS. Auditory discrimination performance and reaction times also remained unaffected by tDCS. Our findings suggest that a single application of tDCS has no acute effects on ERPs and associated auditory information processing in schizophrenia patients.

Objective The present study was undertaken to evaluate the effect of cognitive training in improving trained and untrained cognitive processes in schizophrenia. Methods A simple pre- and post experimental study with a three month follow-up was conducted to determine the efficacy of cognitive training in speed of processing and executive functions improving cognition in 22 schizophrenia patients. Results Significant improvement was found in those cognitive domains specifically targeted in the training protocol, but also to a limited extent on verbal memory and social cognition. There was also evidence of improvements in symptoms and social functioning. The training effects failed to transfer to community functioning skills however. Except for social cognition, these improvements were maintained at 3 month follow-up. Conclusion The study highlights the importance of understanding the mechanisms that contribute to the transfer of skills as well as the maintenance of cognitive changes in individuals with schizophrenia. © 2013 Elsevier Inc. All rights reserved.

Schizophrenia is an idiopathic mental disorder with a heritable component and a substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases and 6,243 controls) followed by meta-Analysis with previous schizophrenia GWAS (8,832 cases and 12,067 controls) and finally by replication of SNPs in 168 genomic regions in independent samples (7,413 cases, 19,762 controls and 581 parent-offspring trios). We identified 22 loci associated at genome-wide significance; 13 of these are new, and 1 was previously implicated in bipolar disorder. Examination of candidate genes at these loci suggests the involvement of neuronal calcium signaling. We estimate that 8,300 independent, mostly common SNPs (95% credible interval of 6,300-10,200 SNPs) contribute to risk for schizophrenia and that these collectively account for at least 32% of the variance in liability. Common genetic variation has an important role in the etiology of schizophrenia, and larger studies will allow more detailed understanding of this disorder. © 2013 Nature America, Inc. All rights reserved.

Background Schizophrenia is associated with lower pre-morbid intelligence (IQ) in addition to (pre-morbid) cognitive decline. Both schizophrenia and IQ are highly heritable traits. Therefore, we hypothesized that genetic variants associated with schizophrenia, including copy number variants (CNVs) and a polygenic schizophrenia (risk) score (PSS), may influence intelligence. Method IQ was estimated with the Wechsler Adult Intelligence Scale (WAIS). CNVs were determined from single nucleotide polymorphism (SNP) data using the QuantiSNP and PennCNV algorithms. For the PSS, odds ratios for genome-wide SNP data were calculated in a sample collected by the Psychiatric Genome-Wide Association Study (GWAS) Consortium (8690 schizophrenia patients and 11 831 controls). These were used to calculate individual PSSs in our independent sample of 350 schizophrenia patients and 322 healthy controls. Results Although significantly more genes were disrupted by deletions in schizophrenia patients compared to controls (p = 0.009), there was no effect of CNV measures on IQ. The PSS was associated with disease status (R 2 = 0.055, p = 2.1 × 10 -7) and with IQ in the entire sample (R 2 = 0.018, p = 0.0008) but the effect on IQ disappeared after correction for disease status. Conclusions Our data suggest that rare and common schizophrenia-associated variants do not explain the variation in IQ in healthy subjects or in schizophrenia patients. Thus, reductions in IQ in schizophrenia patients may be secondary to other processes related to schizophrenia risk. © Cambridge University Press 2013.