Recent genetic findings in schizophrenia and their therapeutic relevance

In Vitro and In Vivo Models for the Investigation of Potential Drugs Against Schizophrenia

Schizophrenia (SZ) is a complex psychiatric disorder characterized by positive, negative, and cognitive symptoms, and is not satisfactorily treated by current antipsychotics. Progress in understanding the basic pathomechanism of the disease has been hampered by the lack of appropriate models. In order to develop modern drugs against SZ, efficient methods to study them in in vitro and in vivo models of this disease are required. In this review a short presentation of current hypotheses and concepts of SZ is followed by a description of current progress in the field of SZ experimental models. A critical discussion of advantages and limitations of in vitro models and pharmacological, genetic, and neurodevelopmental in vivo models for positive, negative, and cognitive symptoms of the disease is provided. In particular, this review concerns the important issue of how cellular and animal systems can help to meet the challenges of modeling the disease, which fully manifests only in humans, as experimental studies of SZ in humans are limited. Next, it is emphasized that novel clinical candidates should be evaluated in animal models for treatment-resistant SZ. In conclusion, the plurality of available in vitro and in vivo models is a consequence of the complex nature of SZ, and there are extensive possibilities for their integration. Future development of more efficient antipsychotics reflecting the pleiotropy of symptoms in SZ requires the incorporation of various models into one uniting model of the multifactorial disorder and use of this model for the evaluation of new drugs.

Impaired Potentiation of Theta Oscillations During a Visual Cortical Plasticity Paradigm in Individuals With Schizophrenia

Long-term potentiation (LTP) is a form of experience-dependent synaptic plasticity mediated by glutamatergic transmission at N-methyl-D-aspartate receptors (NMDARs). Impaired neuroplasticity has been implicated in the pathophysiology of schizophrenia, possibly due to underlying NMDAR hypofunction. Analogous to the high frequency electrical stimulation used to induce LTP in vitro and in vivo in animal models, repeated high frequency presentation of a visual stimulus in humans in vivo has been shown to induce enduring LTP-like neuroplastic changes in electroencephalography (EEG)-based visual evoked potentials (VEPs) elicited by the stimulus. Using this LTP-like visual plasticity paradigm, we previously showed that visual high-frequency stimulation (VHFS) induced sustained changes in VEP amplitudes in healthy controls, but not in patients with schizophrenia. Here, we extend this prior work by re-analyzing the EEG data underlying the VEPs, focusing on neuroplastic changes in stimulus-evoked EEG oscillatory activity following VHFS. EEG data were recorded from 19 patients with schizophrenia and 21 healthy controls during the visual plasticity paradigm. Event-related EEG oscillations (total power, intertrial phase coherence; ITC) elicited by a standard black and white checkerboard stimulus (~0.83 Hz, several 2-min blocks) were assessed before and after exposure to VHFS with the same stimulus (~8.9 Hz, 2 min). A cluster-based permutation testing approach was applied to time-frequency data to examine LTP-like plasticity effects following VHFS. VHFS enhanced theta band total power and ITC in healthy controls but not in patients with schizophrenia. The magnitude and phase synchrony of theta oscillations in response to a visual stimulus were enhanced for at least 22 min following VHFS, a frequency domain manifestation of LTP-like visual cortical plasticity. These theta oscillation changes are deficient in patients with schizophrenia, consistent with hypothesized NMDA receptor dysfunction.

Human gene and disease associations for clinical-genomics and precision medicine research

We are entering the era of personalized medicine in which an individual's genetic makeup will eventually determine how a doctor can tailor his or her therapy. Therefore, it is becoming critical to understand the genetic basis of common diseases, for example, which genes predispose and rare genetic variants contribute to diseases, and so on. Our study focuses on helping researchers, medical practitioners, and pharmacists in having a broad view of genetic variants that may be implicated in the likelihood of developing certain diseases. Our focus here is to create a comprehensive database with mobile access to all available, authentic and actionable genes, SNPs, and classified diseases and drugs collected from different clinical and genomics databases worldwide, including Ensembl, GenCode, ClinVar, GeneCards, DISEASES, HGMD, OMIM, GTR, CNVD, Novoseek, Swiss-Prot, LncRNADisease, Orphanet, GWAS Catalog, SwissVar, COSMIC, WHO, and FDA. We present a new cutting-edge gene-SNP-disease-drug mobile database with a smart phone application, integrating information about classified diseases and related genes, germline and somatic mutations, and drugs. Its database includes over 59 000 protein-coding and noncoding genes; over 67 000 germline SNPs and over a million somatic mutations reported for over 19 000 protein-coding genes located in over 1000 regions, published with over 3000 articles in over 415 journals available at the PUBMED; over 80 000 ICDs; over 123 000 NDCs; and over 100 000 classified gene-SNP-disease associations. We present an application that can provide new insights into the information about genetic basis of human complex diseases and contribute to assimilating genomic with phenotypic data for the availability of gene-based designer drugs, precise targeting of molecular fingerprints for tumor, appropriate drug therapy, predicting individual susceptibility to disease, diagnosis, and treatment of rare illnesses are all a few of the many transformations expected in the decade to come.

Case Report of Childhood-Onset Psychosis in a Patient with a Known WNT10A Mutation

OBJECTIVE

To report on a patient with childhood-onset psychosis at age 12 with a known WNT10A mutation.

METHODS

Case report.

RESULTS

The patient is a 12-year-old male who presented with an acute onset of psychosis in the context of a known WNT10A mutation.

CONCLUSION

WNT genes have only been previously linked to schizophrenia on a theoretical basis. To our knowledge, this is the first case report of an association between a childhood-onset psychosis and a WNT10A mutation. We conclude that there is a possibility that WNT10A may be one of the many genes contributing to the development of childhood-onset schizophrenia.

The origin of NMDA receptor hypofunction in schizophrenia

N-methyl-d-aspartate (NMDA) receptor (NMDAR) hypofunction plays a key role in pathophysiology of schizophrenia. Since NMDAR hypofunction has also been reported in autism, Alzheimer's disease and cognitive dementia, it is crucial to identify the location, timing, and mechanism of NMDAR hypofunction for schizophrenia for better understanding of disease etiology and for novel therapeutic intervention. In this review, we first discuss the shared underlying mechanisms of NMDAR hypofunction in NMDAR antagonist models and the anti-NMDAR autoantibody model of schizophrenia and suggest that NMDAR hypofunction could occur in GABAergic neurons in both models. Preclinical models using transgenic mice have shown that NMDAR hypofunction in cortical GABAergic neurons, in particular parvalbumin-positive fast-spiking interneurons, in the early postnatal period confers schizophrenia-related phenotypes. Recent studies suggest that NMDAR hypofunction can also occur in PV-positive GABAergic neurons with alterations of NMDAR-associated proteins, such as neuregulin/ErbB4, α7nAChR, and serine racemase. Furthermore, several environmental factors, such as oxidative stress, kynurenic acid and hypoxia, may also potentially elicit NMDAR hypofunction in GABAergic neurons in early postnatal period. Altogether, the studies discussed here support a central role for GABAergic abnormalities in the context of NMDAR hypofunction. We conclude by suggesting potential therapeutic strategies to improve the function of fast-spiking neurons.

Targeted Treatment of Individuals With Psychosis Carrying a Copy Number Variant Containing a Genomic Triplication of the Glycine Decarboxylase Gene

BACKGROUND

The increased mutational burden for rare structural genomic variants in schizophrenia and other neurodevelopmental disorders has so far not yielded therapies targeting the biological effects of specific mutations. We identified two carriers (mother and son) of a triplication of the gene encoding glycine decarboxylase, GLDC, presumably resulting in reduced availability of the N-methyl-D-aspartate receptor coagonists glycine and D-serine and N-methyl-D-aspartate receptor hypofunction. Both carriers had a diagnosis of a psychotic disorder.

METHODS

We carried out two double-blind, placebo-controlled clinical trials of N-methyl-D-aspartate receptor augmentation of psychotropic drug treatment in these two individuals. Glycine was used in the first clinical trial, and D-cycloserine was used in the second one.

RESULTS

Glycine or D-cycloserine augmentation of psychotropic drug treatment each improved psychotic and mood symptoms in placebo-controlled trials.

CONCLUSIONS

These results provide two independent proof-of-principle demonstrations of symptom relief by targeting a specific genotype and explicitly link an individual mutation to the pathophysiology of psychosis and treatment response.

Therapeutic potential and underlying mechanism of sarcosine (N-methylglycine) in N-methyl-D-aspartate (NMDA) receptor hypofunction models of schizophrenia

BACKGROUND

Compelling animal and clinical studies support the N-methyl-D-aspartate receptor (NMDAR) hypofunction hypothesis of schizophrenia and suggest promising pharmacological agents to ameliorate negative and cognitive symptoms of schizophrenia, including sarcosine, a glycine transporter-1 inhibitor.

AIMS AND METHODS

It is imperative to evaluate the therapeutic potential of sarcosine in animal models, which provide indispensable tools for testing drug effects in detail and elucidating the underlying mechanisms. In this study, a series of seven experiments was conducted to investigate the effect of sarcosine in ameliorating behavioral deficits and the underlying mechanism in pharmacological (i.e., MK-801-induced) and genetic (i.e., serine racemase-null mutant (SR^-/-) mice) NMDAR hypofunction models.

RESULTS

In Experiment 1, the acute administration of 500/1000 mg/kg sarcosine (i.p.) had no adverse effects on motor function and serum biochemical responses. In Experiments 2-4, sarcosine significantly alleviated MK-801-induced (0.2 mg/kg) brain abnormalities and behavioral deficits in MK-801-induced and SR^-/- mouse models. In Experiment 5, the injection of sarcosine enhanced CSF levels of glycine and serine in rat brain. In Experiments 6-7, we show for the first time that sarcosine facilitated NMDAR-mediated hippocampal field excitatory postsynaptic potentials and influenced the movement of surface NMDARs at extrasynaptic sites.

CONCLUSIONS

Sarcosine effectively regulated the surface trafficking of NMDARs, NMDAR-evoked electrophysiological activity, brain glycine levels and MK-801-induced abnormalities in the brain, which contributed to the amelioration of behavioral deficits in mouse models of NMDAR hypofunction.

Genotype Variations of rs13381800 in TCF4 Gene and rs17039988 in NRXN1 Gene among a Sample of Iranian Patients with Schizophrenia

Objective: Schizophrenia is a complicated mental disorder that affects about 1% of the world's population. It is a complex disease and is approximately 80% inherited. One of the candidate genes in schizophrenia is transcription factor 4 (TCF4), which is positioned on chromosome 18 and is a transcription factor that plays a role in the transcription of Neurexin 1(NRXN1) gene, which is one of the candidate genes for developing schizophrenia. This case-control study aimed to investigate the correlation of TCF4 rs13381800 and NRXN1 rs17039988 polymorphisms with the risk of schizophrenia in a sample of Iranian patients with schizophrenia. Method : A total of 200 individuals were included in this study: 100 patients with schizophrenia (65 males and 35 females), with the mean age of 40.80 ± 11.298 years, and 100 as a control group (63 males and 37 females), with the mean age 32.92 ± 7.391 years. Allele specific polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP) were done, respectively, for genotyping of rs13381800 (T/C) and rs17039988 (A/C) polymorphisms. Results: The results showed that the frequency of C / C genotype in rs13381800 in patients' group was 9%, while it was 13% in the control group. Also, the frequency of C / C genotype in rs17039988 was 9% in patients and 7% in control groups. Statistical analysis of polymorphisms showed no correlation between patients and controls in rs13381800 (OR = 1.51; CI = 95%; P = 0.366) and rs17039988 (OR = 0.76; CI = 95%; P = 0.602). Conclusion: No significant difference was found between rs13381800 and rs17039988 genotypes between patients and control groups in terms of gender, age and education in the patients group. Our study suggests that there was no correlation between desired polymorphisms with schizophrenia in the studied population.

Prenatal Maternal Stress and the Cascade of Risk to Schizophrenia Spectrum Disorders in Offspring

PURPOSE OF REVIEW

Disruptions in fetal development (via genetic and environmental pathways) have been consistently associated with risk for schizophrenia in a variety of studies. Although multiple obstetric complications (OCs) have been linked to schizophrenia, this review will discuss emerging evidence supporting the role of prenatal maternal stress (PNMS) in the etiology of schizophrenia spectrum disorders (SSD). In addition, findings linking PNMS to intermediate phenotypes of the disorder, such as OCs and premorbid cognitive, behavioral, and motor deficits, will be reviewed. Maternal immune and endocrine dysregulation will also be explored as potential mechanisms by which PNMS confers risk for SSD.

RECENT FINDINGS

PNMS has been linked to offspring SSD; however, findings are mixed due to inconsistent and retrospective assessments of PNMS and lack of specificity about SSD outcomes. PNMS is also associated with various intermediate phenotypes of SSD (e.g., prenatal infection/inflammation, decreased fetal growth, hypoxia-related OCs). Recent studies continue to elucidate the impact of PNMS while considering the moderating roles of fetal sex and stress timing, but it is still unclear which aspects of PNMS (e.g., type, timing) confer risk for SSD specifically. PNMS increases risk for SSD, but only in a small portion of fetuses exposed to PNMS. Fetal sex, genetics, and other environmental factors, as well as additional pre- and postnatal insults, likely contribute to the PNMS-SSD association. Longitudinal birth cohort studies are needed to prospectively illuminate the mechanisms that account for the variability in outcomes following PNMS.

Multi-scale analysis of schizophrenia risk genes, brain structure, and clinical symptoms reveals integrative clues for subtyping schizophrenia patients

Analysis linking directly genomics, neuroimaging phenotypes and clinical measurements is crucial for understanding psychiatric disorders, but remains rare. Here, we describe a multi-scale analysis using genome-wide SNPs, gene expression, grey matter volume (GMV), and the positive and negative syndrome scale scores (PANSS) to explore the etiology of schizophrenia. With 72 drug-naive schizophrenic first episode patients (FEPs) and 73 matched heathy controls, we identified 108 genes, from schizophrenia risk genes, that correlated significantly with GMV, which are highly co-expressed in the brain during development. Among these 108 candidates, 19 distinct genes were found associated with 16 brain regions referred to as hot clusters (HCs), primarily in the frontal cortex, sensory-motor regions and temporal and parietal regions. The patients were subtyped into three groups with distinguishable PANSS scores by the GMV of the identified HCs. Furthermore, we found that HCs with common GMV among patient groups are related to genes that mostly mapped to pathways relevant to neural signaling, which are associated with the risk for schizophrenia. Our results provide an integrated view of how genetic variants may affect brain structures that lead to distinct disease phenotypes. The method of multi-scale analysis that was described in this research, may help to advance the understanding of the etiology of schizophrenia.

Stem cell models of schizophrenia, what have we learned and what is the potential?

Schizophrenia is a complex disorder with clinical manifestations in early adulthood. However, it may start with disruption of brain development caused by genetic or environmental factors, or both. Early deteriorating effects of genetic/environmental factors on neural development might be key to described disease causing mechanisms. Establishing cellular models with cells from affected individual using the induced pluripotent stem cells (iPSC) technology could be used to mimic early neurodevelopment alterations caused by risk genes or environmental stressors. Indeed, cellular models have allowed identification and further study of risk factors and the biological pathways in which they are involved. New advancements in differentiation methods such as defined and robust monolayer protocols and cerebral 3D organoids have made it possible to faithfully mimic neural development and neuronal functionality while CRISPR-editing tools assist to engineer isogenic cell lines to precisely explore genetic variation in polygenic diseases such as schizophrenia. Here we review the current field of iPSC models of schizophrenia and how risk factors can be modelled as well as discussing the common biological pathways involved.

The role of polygenic risk score gene-set analysis in the context of the omnigenic model of schizophrenia

A recent development in the genetic architecture of schizophrenia suggested that an omnigenic model may underlie the risk for this disorder. The aim of our study was to use polygenic profile scoring to quantitatively assess whether a number of experimentally derived sets would contribute to the disorder above and beyond the omnigenic effect. Using the PGC2 secondary analysis schizophrenia case-control cohort (N = 29,125 cases and 34,836 controls), a robust polygenic signal was observed from gene sets based on TCF4, FMR1, upregulation from MIR137 and downregulation from CHD8. Additional analyses revealed a constant floor effect in the amount of variance explained, consistent with the omnigenic model. Thus, we report that putative core gene sets showed a significant effect above and beyond the floor effect that might be linked with the underlying omnigenic background. In addition, we demonstrate a method to quantify the contribution of specific gene sets within the omnigenic context.

NMDAR Hypofunction Animal Models of Schizophrenia

The N-methyl-d-aspartate receptor (NMDAR) hypofunction hypothesis has been proposed to help understand the etiology and pathophysiology of schizophrenia. This hypothesis was based on early observations that NMDAR antagonists could induce a full range of symptoms of schizophrenia in normal human subjects. Accumulating evidence in humans and animal studies points to NMDAR hypofunctionality as a convergence point for various symptoms of schizophrenia. Here we review animal models of NMDAR hypofunction generated by pharmacological and genetic approaches, and how they relate to the pathophysiology of schizophrenia. In addition, we discuss the limitations of animal models of NMDAR hypofunction and their potential utility for therapeutic applications.

Schizophrenia TreAtment with electRic Transcranial Stimulation (STARTS): design, rationale and objectives of a randomized, double-blinded, sham-controlled trial

INTRODUCTION

Schizophrenia is a severe mental disorder. While some antipsychotic medications have demonstrated efficacy in treating positive symptoms, there is no widely recognized treatment for negative symptoms, which can cause significant distress and impairment for patients with schizophrenia. Here we describe the rationale and design of the STARTS study (Schizophrenia TreAtment with electRic Transcranial Stimulation), a clinical trial aimed to test the efficacy of a non-pharmacological treatment known as transcranial direct current stimulation (tDCS) for treating the negative symptoms of schizophrenia.

METHODS

The STARTS study is designed as a randomized, sham-controlled, double-blinded trial evaluating tDCS for the treatment of the negative symptoms of schizophrenia. One-hundred patients will be enrolled and submitted to 10 tDCS sessions over the left dorsolateral prefrontal cortex (anodal stimulation) and left temporoparietal junction (cathodal stimulation) over 5 consecutive days. Participants will be assessed using clinical and neuropsychological tests before and after the intervention. The primary outcome is change in the Positive and Negative Syndrome Scale (PANSS) negative subscale score over time and across groups. Biological markers, including blood neurotrophins and interleukins, genetic polymorphisms, and motor cortical excitability, will also be assessed.

RESULTS

The clinical results will provide insights about tDCS as a treatment for the negative symptoms of schizophrenia, and the biomarker investigation will contribute towards an improved understanding of the tDCS mechanisms of action.

CONCLUSION

Our results could introduce a novel therapeutic technique for the negative symptoms of schizophrenia. Clinical trial registration: ClinicalTrials.gov, NCT02535676 .

A Bayesian framework that integrates multi-omics data and gene networks predicts risk genes from schizophrenia GWAS data

Genome-wide association studies (GWAS) have identified >100 schizophrenia (SCZ)-associated loci, but using these findings to illuminate disease biology remains a challenge. Here, we present integrative RIsk Gene Selector (iRIGS), a Bayesian framework that integrates multi-omics data and gene networks to infer risk genes in GWAS loci. By applying iRIGS to SCZ GWAS data, we predicted a set of high-confidence risk genes (HRGs), most of which are not the nearest genes to the GWAS index variants. HRGs account for a significantly enriched heritability estimated by stratified LD-score regression. Moreover, HRGs are predominantly expressed in brain tissues, especially prenatally, and are enriched for targets of approved drugs, suggesting opportunities to reposition existing drugs for SCZ. Thus, iRIGS can leverage accumulating functional genomics and GWAS data to advance understanding of SCZ etiology and potential therapeutics.

Machine learning in schizophrenia genomics, a case-control study using 5,090 exomes

Our hypothesis is that machine learning (ML) analysis of whole exome sequencing (WES) data can be used to identify individuals at high risk for schizophrenia (SCZ). This study applies ML to WES data from 2,545 individuals with SCZ and 2,545 unaffected individuals, accessed via the database of genotypes and phenotypes (dbGaP). Single nucleotide variants and small insertions and deletions were annotated by ANNOVAR using the reference genome hg19/GRCh37. Rare (predicted functional) variants with a minor allele frequency ≤1% and genotype quality ≥90 including missense, frameshift, stop gain, stop loss, intronic, and exonic splicing variants were selected. A file containing all cases and controls, the names of genes with variants meeting our criteria, and the number of variants per gene for each individual, was used for ML analysis. The supervised machine-learning algorithm used the patterns of variants observed in the different genes to determine which subset of genes can best predict that an individual is affected. Seventy percent of the data was used to train the algorithm and the remaining 30% of data (n = 1,526) was used to evaluate its efficiency. The supervised ML algorithm, gradient boosted trees with regularization (eXtreme Gradient Boosting implementation) was the best performing algorithm yielding promising results (accuracy: 85.7%, specificity: 86.6%, sensitivity: 84.9%, area under the receiver-operator characteristic curve: 0.95). The top 50 features (genes) of the algorithm were analyzed using bioinformatics resources for new insights about the pathophysiology of SCZ. This manuscript presents a novel predictor which could potentially enable studies exploring disease-modifying intervention in the early stages of the disease.

Association of rs4680 COMT, rs6280 DRD3, and rs7322347 5HT2A With Clinical Features of Youth-Onset Schizophrenia

We investigated the associations of rs4680 COMT, rs6280 DRD3, and rs7322347 5HT2A with youth-onset schizophrenia in the Russian population in a case-control study, and the role of the genotype in the severity of clinical features. The association between rs7322347 and schizophrenia (p = 0.0001) is described for the first time. Furthermore, we found a link with rs6280 and rs4680 in females (p = 0.001 and p = 0.02 respectively) and with rs7322347 in males (p = 0.002). Clinical symptoms were assessed on three scales: the Clinician-Rated Dimensions of Psychosis Symptom Severity scale, Positive and Negative Syndrome Scale, and Frontal Assessment Battery. Gender differences in clinical features are of particular interest. In our study we found gender differences in the severity of clinical features-higher scores for delusions (Positive and Negative Syndrome Scale and Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition) in males and higher scores for depression, delusions, somatic concern, motor retardation, poor attention were found in females.

The effect of the DISC1 Ser704Cys polymorphism on striatal dopamine synthesis capacity: an [18F]-DOPA PET study

Whilst the role of the Disrupted-in-Schizophrenia 1 (DISC1) gene in the aetiology of major mental illnesses is debated, the characterization of its function lends it credibility as a candidate. A key aspect of this functional characterization is the determination of the role of common non-synonymous polymorphisms on normal variation within these functions. The common allele (A) of the DISC1 single-nucleotide polymorphism (SNP) rs821616 encodes a serine (ser) at the Ser704Cys polymorphism, and has been shown to increase the phosphorylation of extracellular signal-regulated protein Kinases 1 and 2 (ERK1/2) that stimulate the phosphorylation of tyrosine hydroxylase, the rate-limiting enzyme for dopamine biosynthesis. We therefore set out to test the hypothesis that human ser (A) homozygotes would show elevated dopamine synthesis capacity compared with cysteine (cys) homozygotes and heterozygotes (TT and AT) for rs821616. [18F]-DOPA positron emission tomography (PET) was used to index striatal dopamine synthesis capacity as the influx rate constant Kicer in healthy volunteers DISC1 rs821616 ser homozygotes (N = 46) and healthy volunteers DISC1 rs821616 cys homozygotes and heterozygotes (N = 56), matched for age, gender, ethnicity and using three scanners. We found DISC1 rs821616 ser homozygotes exhibited a significantly higher striatal Kicer compared with cys homozygotes and heterozygotes (P = 0.012) explaining 6.4% of the variance (partial η2 = 0.064). Our finding is consistent with its previous association with heightened activation of ERK1/2, which stimulates tyrosine hydroxylase activity for dopamine synthesis. This could be a potential mechanism mediating risk for psychosis, lending further credibility to the fact that DISC1 is of functional interest in the aetiology of major mental illness.

Associations between polygenic risk scores for four psychiatric illnesses and brain structure using multivariate pattern recognition

Psychiatric illnesses are complex and polygenic. They are associated with widespread alterations in the brain, which are partly influenced by genetic factors. There have been some attempts to relate polygenic risk scores (PRS) - a measure of the overall genetic risk an individual carries for a disorder - to brain structure using univariate methods. However, PRS are likely associated with distributed and covarying effects across the brain. We therefore used multivariate machine learning in this proof-of-principle study to investigate associations between brain structure and PRS for four psychiatric disorders; attention deficit-hyperactivity disorder (ADHD), autism, bipolar disorder and schizophrenia. The sample included 213 individuals comprising patients with depression (69), bipolar disorder (33), and healthy controls (111). The five psychiatric PRSs were calculated based on summary data from the Psychiatric Genomics Consortium. T1-weighted magnetic resonance images were obtained and voxel-based morphometry was implemented in SPM12. Multivariate relevance vector regression was implemented in the Pattern Recognition for Neuroimaging Toolbox (PRoNTo). Across the whole sample, a multivariate pattern of grey matter significantly predicted the PRS for autism (r = 0.20, pFDR = 0.03; MSE = 4.20 × 10-5, pFDR = 0.02). For the schizophrenia PRS, the MSE was significant (MSE = 1.30 × 10-5, pFDR = 0.02) although the correlation was not (r = 0.15, pFDR = 0.06). These results lend support to the hypothesis that polygenic liability for autism and schizophrenia is associated with widespread changes in grey matter concentrations. These associations were seen in individuals not affected by these disorders, indicating that this is not driven by the expression of the disease, but by the genetic risk captured by the PRSs.

DNA Methylation as a Biomarker of Treatment Response Variability in Serious Mental Illnesses: A Systematic Review Focused on Bipolar Disorder, Schizophrenia, and Major Depressive Disorder

So far, genetic studies of treatment response in schizophrenia, bipolar disorder, and major depression have returned results with limited clinical utility. A gene × environment interplay has been proposed as a factor influencing not only pathophysiology but also the treatment response. Therefore, epigenetics has emerged as a major field of research to study the treatment of these three disorders. Among the epigenetic marks that can modify gene expression, DNA methylation is the best studied. We performed a systematic search (PubMed) following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA guidelines for preclinical and clinical studies focused on genome-wide and gene-specific DNA methylation in the context of schizophrenia, bipolar disorders, and major depressive disorder. Out of the 112 studies initially identified, we selected 31 studies among them, with an emphasis on responses to the gold standard treatments in each disorder. Modulations of DNA methylation levels at specific CpG sites have been documented for all classes of treatments (antipsychotics, mood stabilizers, and antidepressants). The heterogeneity of the models and methodologies used complicate the interpretation of results. Although few studies in each disorder have assessed the potential of DNA methylation as biomarkers of treatment response, data support this hypothesis for antipsychotics, mood stabilizers and antidepressants.

Axon guidance pathway genes are associated with schizophrenia risk

In the present study, we analyzed schizophrenia (SCZ)-related genome-wide association studies (GWAS) to identify genes and pathways associated with SCZ. We identified 1,098 common genes (1,098/9,468) and 20 shared KEGG pathways (both P<0.01) by integrating candidate genes from the European and American SCZ-related GWAS. The pathways related to axon guidance, long term potentiation and arrhythmogenic right ventricular cardiomyopathy (ARVC) were highly significant (P<10^-3). Moreover, 15 axon guidance pathway-related genes were associated with SCZ. The association between axon guidance pathway genes and SCZ was validated by a two-stage case-control study on Shandong migrants in northeastern China. Moreover, individuals with the rs9944880 TT polymorphism in the deleted in colorectal cancer (DCC) gene were associated with SCZ. These findings indicate that the axon guidance pathway genes and the rs9944880 SNP in DCC gene are associated with SCZ pathogenesis.

Patient Similarity Networks for Precision Medicine

Clinical research and practice in the 21st century is poised to be transformed by analysis of computable electronic medical records and population-level genome-scale patient profiles. Genomic data capture genetic and environmental state, providing information on heterogeneity in disease and treatment outcome, but genomic-based clinical risk scores are limited. Achieving the goal of routine precision medicine that takes advantage of these rich genomics data will require computational methods that support heterogeneous data, have excellent predictive performance, and ideally, provide biologically interpretable results. Traditional machine-learning approaches excel at performance, but often have limited interpretability. Patient similarity networks are an emerging paradigm for precision medicine, in which patients are clustered or classified based on their similarities in various features, including genomic profiles. This strategy is analogous to standard medical diagnosis, has excellent performance, is interpretable, and can preserve patient privacy. We review new methods based on patient similarity networks, including Similarity Network Fusion for patient clustering and netDx for patient classification. While these methods are already useful, much work is required to improve their scalability for contemporary genetic cohorts, optimize parameters, and incorporate a wide range of genomics and clinical data. The coming 5 years will provide an opportunity to assess the utility of network-based algorithms for precision medicine.

Use of schizophrenia and bipolar disorder polygenic risk scores to identify psychotic disorders

BACKGROUND

There is increasing evidence for shared genetic susceptibility between schizophrenia and bipolar disorder. Although genetic variants only convey subtle increases in risk individually, their combination into a polygenic risk score constitutes a strong disease predictor.AimsTo investigate whether schizophrenia and bipolar disorder polygenic risk scores can distinguish people with broadly defined psychosis and their unaffected relatives from controls.

METHOD

Using the latest Psychiatric Genomics Consortium data, we calculated schizophrenia and bipolar disorder polygenic risk scores for 1168 people with psychosis, 552 unaffected relatives and 1472 controls.

RESULTS

Patients with broadly defined psychosis had dramatic increases in schizophrenia and bipolar polygenic risk scores, as did their relatives, albeit to a lesser degree. However, the accuracy of predictive models was modest.

CONCLUSIONS

Although polygenic risk scores are not ready for clinical use, it is hoped that as they are refined they could help towards risk reduction advice and early interventions for psychosis.Declaration of interestR.M.M. has received honoraria for lectures from Janssen, Lundbeck, Lilly, Otsuka and Sunovian.

SULFATION PATHWAYS: The steroid sulfate axis and its relationship to maternal behaviour and mental health

Steroid hormones can exist in functionally dissociable sulfated and non-sulfated (free) forms and can exert profound effects on numerous aspects of mammalian physiology; the ratio of free-to-sulfated steroids is governed by the antagonistic actions of steroid sulfatase (STS) and sulfotransferase (SULT) enzymes. Here, I examine evidence from human and animal model studies, which suggests that STS and its major substrate (dehydroepiandrosterone sulfate, DHEAS) and product (DHEA) can influence brain function, behaviour and mental health, before summarising how the activity of this axis varies throughout mammalian pregnancy and the postpartum period. I then consider how the steroid sulfate axis might impact upon normal maternal behaviour and how its dysfunction might contribute towards risk of postpartum psychiatric illness. Understanding the biological substrates underlying normal and abnormal maternal behaviour will be important for maximising the wellbeing of new mothers and their offspring.

Hippocampal dysfunction in the pathophysiology of schizophrenia: a selective review and hypothesis for early detection and intervention

Scientists have long sought to characterize the pathophysiologic basis of schizophrenia and develop biomarkers that could identify the illness. Extensive postmortem and in vivo neuroimaging research has described the early involvement of the hippocampus in the pathophysiology of schizophrenia. In this context, we have developed a hypothesis that describes the evolution of schizophrenia-from the premorbid through the prodromal stages to syndromal psychosis-and posits dysregulation of glutamate neurotransmission beginning in the CA1 region of the hippocampus as inducing attenuated psychotic symptoms and initiating the transition to syndromal psychosis. As the illness progresses, this pathological process expands to other regions of the hippocampal circuit and projection fields in other anatomic areas including the frontal cortex, and induces an atrophic process in which hippocampal neuropil is reduced and interneurons are lost. This paper will describe the studies of our group and other investigators supporting this pathophysiological hypothesis, as well as its implications for early detection and therapeutic intervention.

De Novo Design, Synthesis, and Biological Evaluation of 3,4-Disubstituted Pyrrolidine Sulfonamides as Potent and Selective Glycine Transporter 1 Competitive Inhibitors

The development of glycine transporter 1 (GlyT1) inhibitors may offer putative treatments for schizophrenia and other disorders associated with hypofunction of the glutaminergic N-methyl-d-aspartate (NMDA) receptor. Herein, we describe the synthesis and biological evaluation of a series of 3,4-disubstituted pyrrolidine sulfonamides as competitive GlyT1 inhibitors that arose from de novo scaffold design. Relationship of chemical structure to drug-drug interaction (DDI) and bioactivation was mechanistically investigated. Murine studies were strategically incorporated into the screening funnel to provide early assessments of in vivo target occupancy (TO) by ex vivo binding studies. Advanced compounds derived from iterative structure-activity relationship (SAR) studies possessed high potency in ex vivo binding studies and good brain penetration, promising preliminary in vivo efficacy, acceptable preclinical pharmacokinetics, and manageable DDI and bioactivation liabilities.

Gabrb2-knockout mice displayed schizophrenia-like and comorbid phenotypes with interneuron-astrocyte-microglia dysregulation

Intronic polymorphisms of the GABA_A receptor β₂ subunit gene (GABRB2) under adaptive evolution were associated with schizophrenia and reduced expression, especially of the long isoform which differs in electrophysiological properties from the short isoform. The present study was directed to examining the gene dosage effects of Gabrb2 in knockout mice of both heterozygous (HT) and homozygous (KO) genotypes with respect to possible schizophrenia-like and comorbid phenotypes. The KO mice, and HT mice to a lesser extent, were found to display prepulse inhibition (PPI) deficit, locomotor hyperactivity, stereotypy, sociability impairments, spatial-working and spatial-reference memory deficits, reduced depression and anxiety, and accelerated pentylenetetrazol (PTZ)-induced seizure. In addition, the KO mice were highly susceptible to audiogenic epilepsy. Some of the behavioral phenotypes showed evidence of imprinting, gender effect and amelioration by the antipsychotic risperidone, and the audiogenic epilepsy was inhibited by the antiepileptic diazepam. GABAergic parvalbumin (PV)-positive interneuron dystrophy, astrocyte dystrophy, and extensive microglia activation were observed in the frontotemporal corticolimbic regions, and reduction of newborn neurons was observed in the hippocampus by immunohistochemical staining. The neuroinflammation indicated by microglial activation was accompanied by elevated brain levels of oxidative stress marker malondialdehyde (MDA) and the pro-inflammatory cytokines tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6). These extensive schizophrenia-like and comorbid phenotypes brought about by Gabrb2 knockout, in conjunction with our previous findings on GABRB2 association with schizophrenia, support a pivotal role of GABRB2 in schizophrenia etiology.

Genetic variability in scaffolding proteins and risk for schizophrenia and autism-spectrum disorders: a systematic review

Scaffolding proteins represent an evolutionary solution to controlling the specificity of information transfer in intracellular networks. They are highly concentrated in complexes located in specific subcellular locations. One of these complexes is the postsynaptic density of the excitatory synapses. There, scaffolding proteins regulate various processes related to synaptic plasticity, such as glutamate receptor trafficking and signalling, and dendritic structure and function. Most scaffolding proteins can be grouped into 4 main families: discs large (DLG), discs-large-associated protein (DLGAP), Shank and Homer. Owing to the importance of scaffolding proteins in postsynaptic density architecture, it is not surprising that variants in the genes that code for these proteins have been associated with neuropsychiatric diagnoses, including schizophrenia and autism-spectrum disorders. Such evidence, together with the clinical, neurobiological and genetic overlap described between schizophrenia and autism-spectrum disorders, suggest that alteration of scaffolding protein dynamics could be part of the pathophysiology of both. However, despite the potential importance of scaffolding proteins in these psychiatric conditions, no systematic review has integrated the genetic and molecular data from studies conducted in the last decade. This review has the following goals: to systematically analyze the literature in which common and/or rare genetic variants (single nucleotide polymorphisms, single nucleotide variants and copy number variants) in the scaffolding family genes are associated with the risk for either schizophrenia or autism-spectrum disorders; to explore the implications of the reported genetic variants for gene expression and/or protein function; and to discuss the relationship of these genetic variants to the shared genetic, clinical and cognitive traits of schizophrenia and autism-spectrum disorders.

Mini-review: Update on the genetics of schizophrenia

A number of important findings have recently emerged relevant to identifying genetic risk factors for schizophrenia. Findings using common variants point towards gene sets of interest and also demonstrate an overlap with other psychiatric and nonpsychiatric disorders. Imputation of variants of the gene for complement component 4 (C4) from GWAS data has shown that the predicted expression of the C4A product is associated with schizophrenia risk. Very rare variants disrupting SETD1A, RBM12 or NRXN1 have a large effect on risk. Other rare, damaging variants are enriched in genes that are loss of function intolerant and/or whose products localise to the synapse. These and particular copy number variants can result in increased risk of schizophrenia but also of other neurodevelopmental disorders. The findings for C4 and NRXN1 may be especially helpful for elucidating the biological mechanisms that can lead to disease.

Pre- and Perinatal Risk Factors for Serious Mental Disorders: Ethical Considerations in Prevention and Prediction Efforts

Repeated findings have linked pre- and perinatal risk factors to a variety of mental disorders. Some studies have found large magnitudes of association, suggesting that fetal development represents an important period for understanding neurodevelopmental sequelae. Nevertheless, it remains unclear how best to translate the existing findings into early identification, prevention, and treatment strategies that would be useful for pregnant populations and/or for their offspring. This article will discuss key ethical considerations surrounding the incorporation of findings from studies of the associations between obstetric complications and risk for mental disorders into prevention and prediction efforts.

Associations between psychosis endophenotypes across brain functional, structural, and cognitive domains

BACKGROUND

A range of endophenotypes characterise psychosis, however there has been limited work understanding if and how they are inter-related.

METHODS

This multi-centre study includes 8754 participants: 2212 people with a psychotic disorder, 1487 unaffected relatives of probands, and 5055 healthy controls. We investigated cognition [digit span (N = 3127), block design (N = 5491), and the Rey Auditory Verbal Learning Test (N = 3543)], electrophysiology [P300 amplitude and latency (N = 1102)], and neuroanatomy [lateral ventricular volume (N = 1721)]. We used linear regression to assess the interrelationships between endophenotypes.

RESULTS

The P300 amplitude and latency were not associated (regression coef. -0.06, 95% CI -0.12 to 0.01, p = 0.060), and P300 amplitude was positively associated with block design (coef. 0.19, 95% CI 0.10-0.28, p 0.38). All the cognitive endophenotypes were associated with each other in the expected directions (all p < 0.001). Lastly, the relationships between pairs of endophenotypes were consistent in all three participant groups, differing for some of the cognitive pairings only in the strengths of the relationships.

CONCLUSIONS

The P300 amplitude and latency are independent endophenotypes; the former indexing spatial visualisation and working memory, and the latter is hypothesised to index basic processing speed. Individuals with psychotic illnesses, their unaffected relatives, and healthy controls all show similar patterns of associations between endophenotypes, endorsing the theory of a continuum of psychosis liability across the population.

Acquisition of nicotine self-administration in amphetamine and phencyclidine models of schizophrenia: A role for stress?

Nicotine use and dependence is very high in patients with schizophrenia. One possible reason is that altered dopamine or glutamate activity in schizophrenia enhances the reinforcing effectiveness of nicotine. We used animal models to test the hypothesis that a hyperdopaminergic state (induced by repeated intermittent injections of amphetamine) or altered glutamate function (subchronic injection of phencyclidine, PCP) facilitates spontaneous acquisition of nicotine self-administration in rats. In Experiment 1 animals in an amphetamine-induced sensitized state (AISS) did not differ from saline-injected controls in their acquisition and maintenance of nicotine self-administration. This effect was replicated in experiment 2, but it was also found that AISS rats and saline-injected controls showed higher rates of nicotine self-administration compared to uninjected controls. This difference was maintained across several fixed ratio and progressive ratio schedules of reinforcement. In Experiment 3 PCP treated rats and their saline-injected controls did not differ in nicotine self-administration. However, both groups showed consistently increased responding for nicotine on FR and PR schedules compared to an uninjected control group. Injection-stress appeared to influence the outcomes of these experiments in two ways. Firstly, injection stress potentially masked the impact of the AISS and PCP treatment on nicotine self-administration. Secondly, injection stress itself may have been sufficient to induce plastic changes in dopamine and glutamate systems, and these changes enhanced the acquisition and maintenance of nicotine self-administration. Further investigation is needed into the role of stress in the development of nicotine use and dependence, in the aetiology of schizophrenia and in their co-morbidity.

The interaction between cannabis use and the Val158Met polymorphism of the COMT gene in psychosis: A transdiagnostic meta - analysis

BACKGROUND

Neither environmental nor genetic factors are sufficient to predict the transdiagnostic expression of psychosis. Therefore, analysis of gene-environment interactions may be productive.

OBJECTIVE

A meta-analysis was performed using papers investigating the interaction between cannabis use and catechol-O-methyl transferase (COMT) polymorphism Val158Met (COMTVal158Met).

DATA SOURCES

PubMed, Embase, PsychInfo.

STUDY ELIGIBILITY CRITERIA

All observational studies assessing the interaction between COMTVal158Met and cannabis with any psychosis or psychotic symptoms measure as an outcome.

STUDY APPRAISAL AND SYNTHESIS METHODS

A meta-analysis was performed using the Meta-analysis of Observational Studies in Epidemiology guidelines and forest plots were generated. Thirteen articles met the selection criteria: 7 clinical studies using a case-only design, 3 clinical studies with a dichotomous outcome, and 3 studies analysing a continuous outcome of psychotic symptoms below the threshold of psychotic disorder. The three study types were analysed separately. Validity of the included studies was assessed using "A Cochrane Risk of Bias Assessment Tool: for Non-Randomized Studies of Interventions".

RESULTS

For case-only studies, a significant interaction was found between cannabis use and COMTVal158Met, with an OR of 1.45 (95% Confidence Interval = 1.05-2.00; Met/Met as the risk genotype). However, there was no evidence for interaction in either the studies including dichotomous outcomes (B = -0.51, 95% Confidence Interval -1.72, 0.70) or the studies including continuous outcomes (B = -0.04 95% Confidence Interval -0.16-0.08).

LIMITATION

A substantial part of the included studies used the case-only design, which has lower validity and tends to overestimate true effects.

CONCLUSION

The interaction term between cannabis use and COMTVal158Met was only statistically significant in the case-only studies, but not in studies using other clinical or non-clinical psychosis outcomes. Future additional high quality studies might change current perspectives, yet currently evidence for the interaction remains unconvincing.

Potential and Challenges for the Clinical Use of d-Serine As a Cognitive Enhancer

After 25 years of its discovery in the rat brain, d-serine is a recognized modulator of synaptic plasticity and cognitive processes through its actions on the NMDA-glutamate receptor. Importantly, cognitive impairment is a core feature of conditions, such as schizophrenia, Alzheimer's disease, depression, and aging, and is associated to disturbances in NMDA-glutamate receptors. The d-serine pathway has been associated with cognitive deficits and these conditions, and, for this reason, d-serine signaling is subject of intense research to probe its role in aiding diagnosis and therapy. Nevertheless, this has not resulted in new therapies being incorporated into clinical practice. Therefore, in this review we will address many questions that need to be solved by future studies, regarding d-serine pharmacokinetics, possible side effects, other strategies to modulate its levels, and combination with other therapies to increase its efficacy.

Integrating genome-wide association study and expression quantitative trait locus study identifies multiple genes and gene sets associated with schizophrenia

Schizophrenia is a serious mental disease with high heritability. To better understand the genetic basis of schizophrenia, we conducted a large scale integrative analysis of genome-wide association study (GWAS) and expression quantitative trait loci (eQTLs) data. GWAS summary data was derived from a published GWAS of schizophrenia, containing 9394 schizophrenia patients and 12,462 healthy controls. The eQTLs dataset was obtained from an eQTLs meta-analysis of 5311 subjects, containing 923,021 cis-eQTLs for 14,329 genes and 4732 trans-eQTLs for 2612 genes. Genome-wide single gene expression association analysis was conducted by SMR software. The SMR analysis results were further subjected to gene set enrichment analysis (GSEA) to identify schizophrenia associated gene sets. SMR detected 49 genes significantly associated with schizophrenia. The top five significant genes were CRELD2 (p value=1.65×10^-11), DIP2B (p value=3.94×10^-11), ZDHHC18 (p value=1.52×10^-10) and ZDHHC5 (p value=7.45×10^-10), C11ORF75 (p value=3.70×10^-9). GSEA identified 80 gene sets with p values <0.01. The top five significant gene sets were COWLING_MYCN_TARGETS (p value <0.001) and CHR16P11 (p value <0.001), ACTACCT_MIR196A_MIR196B (p value=0.002), CELLULAR_COMPONENT_DISASSEMBLY (p value=0.002) and GRAESSMANN_RESPONSE_TO_MC_AND_DOXORUBICIN_DN (p value=0.002). Our results provide useful information for revealing the genetic basis of schizophrenia.

Mapping the Schizophrenia Genes by Neuroimaging: The Opportunities and the Challenges

Schizophrenia (SZ) is a heritable brain disease originating from a complex interaction of genetic and environmental factors. The genes underpinning the neurobiology of SZ are largely unknown but recent data suggest strong evidence for genetic variations, such as single nucleotide polymorphisms, making the brain vulnerable to the risk of SZ. Structural and functional brain mapping of these genetic variations are essential for the development of agents and tools for better diagnosis, treatment and prevention of SZ. Addressing this, neuroimaging methods in combination with genetic analysis have been increasingly used for almost 20 years. So-called imaging genetics, the opportunities of this approach along with its limitations for SZ research will be outlined in this invited paper. While the problems such as reproducibility, genetic effect size, specificity and sensitivity exist, opportunities such as multivariate analysis, development of multisite consortia for large-scale data collection, emergence of non-candidate gene (hypothesis-free) approach of neuroimaging genetics are likely to contribute to a rapid progress for gene discovery besides to gene validation studies that are related to SZ.

Imaging genetics of schizophrenia in the post-GWAS era

Imaging genetics is a research methodology studying the effect of genetic variation on brain structure, function, behavior, and risk for psychopathology. Since the early 2000s, imaging genetics has been increasingly used in the research of schizophrenia (SZ). SZ is a severe mental disorder with no precise knowledge of its underlying neurobiology, however, new genetic and neurobiological data generate a climate for new avenues. The accumulating data of genome wide association studies (GWAS) continuously decode SZ risk genes. Global neuroimaging consortia produce collections of brain phenotypes from tens of thousands of people. In this context, imaging genetics will be strategically important both for the validation and discovery of SZ related findings. Thus, the study of GWAS supported risk variants as candidate genes to validate by neuroimaging is one trend. The study of epigenetic differences in relation to variations of brain phenotypes and the study of large scale multivariate analysis of genome wide and brain wide associations are other trends. While these studies hold a big potential for understanding the neurobiology of SZ, the problem of reproducibility appears as a major challenge, which requires standardizations in study designs and compensations of methodological limitations such as sensitivity and specificity. On the other hand, advancements of neuroimaging, optical and electron microscopy along with the use of genetically encoded fluorescent probes and robust statistical approaches will not only catalyze integrative methodologies but also will help better design the imaging genetics studies. In this invited paper, I will discuss the current perspective of imaging genetics and emerging opportunities of SZ research.

Deconstructing Schizophrenia: Advances in Preclinical Models for Biomarker Identification

Schizophrenia is considered to develop as a consequence of genetic and environmental factors impacting on brain neural systems and circuits during vulnerable neurodevelopmental periods, thereby resulting in symptoms in early adulthood. Understanding of the impact of schizophrenia risk factors on brain biology and behaviour can help in identifying biologically relevant pathways that are attractive for informing clinical studies and biomarker development. In this chapter, we emphasize the importance of adopting a reciprocal forward and reverse translation approach that is iteratively updated when additional new information is gained, either preclinically or clinically, for offering the greatest opportunity for discovering panels of biomarkers for the diagnosis, prognosis and treatment of schizophrenia. Importantly, biomarkers for identifying those at risk may inform early intervention strategies prior to the development of schizophrenia.Given the emerging nature of this approach in the field, this review will highlight recent research of preclinical biomarkers in schizophrenia that show the most promise for informing clinical needs with an emphasis on relevant imaging, electrophysiological, cognitive behavioural and biochemical modalities. The implementation of this reciprocal translational approach is exemplified firstly by the production and characterization of preclinical models based on the glutamate hypofunction hypothesis, genetic and environmental risk factors for schizophrenia (reverse translation), and then the recent clinical recognition of the thalamic reticular thalamus (TRN) as an important locus of brain dysfunction in schizophrenia as informed by preclinical findings (forward translation).

The Emerging Neurobiology of Bipolar Disorder

Bipolar disorder (BD) is a leading cause of global disability. Its biological basis is unknown, and its treatment unsatisfactory. Here, we review two recent areas of progress. First, the discovery of risk genes and their implications, with a focus on voltage-gated calcium channels as part of the disease process and as a drug target. Second, facilitated by new technologies, it is increasingly apparent that the bipolar phenotype is more complex and nuanced than simply one of recurring manic and depressive episodes. One such feature is persistent mood instability, and efforts are underway to understand its mechanisms and its therapeutic potential. BD illustrates how psychiatry is being transformed by contemporary neuroscience, genomics, and digital approaches.

A polygenic risk score analysis of psychosis endophenotypes across brain functional, structural, and cognitive domains

This large multi-center study investigates the relationships between genetic risk for schizophrenia and bipolar disorder, and multi-modal endophenotypes for psychosis. The sample included 4,242 individuals; 1,087 patients with psychosis, 822 unaffected first-degree relatives of patients, and 2,333 controls. Endophenotypes included the P300 event-related potential (N = 515), lateral ventricular volume (N = 798), and the cognitive measures block design (N = 3,089), digit span (N = 1,437), and the Ray Auditory Verbal Learning Task (N = 2,406). Data were collected across 11 sites in Europe and Australia; all genotyping and genetic analyses were done at the same laboratory in the United Kingdom. We calculated polygenic risk scores for schizophrenia and bipolar disorder separately, and used linear regression to test whether polygenic scores influenced the endophenotypes. Results showed that higher polygenic scores for schizophrenia were associated with poorer performance on the block design task and explained 0.2% (p = 0.009) of the variance. Associations in the same direction were found for bipolar disorder scores, but this was not statistically significant at the 1% level (p = 0.02). The schizophrenia score explained 0.4% of variance in lateral ventricular volumes, the largest across all phenotypes examined, although this was not significant (p = 0.063). None of the remaining associations reached significance after correction for multiple testing (with alpha at 1%). These results indicate that common genetic variants associated with schizophrenia predict performance in spatial visualization, providing additional evidence that this measure is an endophenotype for the disorder with shared genetic risk variants. The use of endophenotypes such as this will help to characterize the effects of common genetic variation in psychosis.

Association between B vitamins and schizophrenia: A population-based case-control study

To explore the association between schizophrenia and six types of B vitamins, including choline, biotin, riboflavin, pyridoxamine, pyridoxine and nicotinamide, based on the hydrophilic interaction liquid chromatography column (HILIC) Liquid Chromatography-Mass Spectrometry (LC-MS) platform. We conducted the case-control study between November 2015 and September 2016 in Weifang, Shandong Province, China. Blood samples from 128 cases of schizophrenia and 101 controls were collected, and B vitamin were measured by LC-MS coupled with HILIC. The HILIC UPLC-MS based analysis of serum B vitamins levels from 128 cases (30 cases with first-episode, 98 cases with relapse) and 101 controls were performed. The results indicated that lower pyridoxine level and schizophrenia was related. (total cases versus controls: β= -0.215, 95% CI: -0.271, -0.125, p < 0.001; first-episode cases versus controls: β = -0.190, 95% CI: -0.277, -0.103, p < 0.001). Higher nicotinamide level was also associated with schizophrenia after adjusting confounders (β = 0.343, 95% CI: 0.022, 0.664, p = 0.036). Other four B vitamins, including biotin, riboflavin, pridoxamine and choline, were showed no statistically difference in cases versus controls, first episode cases versus relapse cases. Two types of B Vitamins, pyridoxine and nicotinamide, show significant association with the schizophrenia.

Applications of CRISPR/Cas9 in the Mammalian Central Nervous System

Within the central nervous system, gene regulatory mechanisms are crucial regulators of cellular development and function, and dysregulation of these systems is commonly observed in major neuropsychiatric and neurological disorders. However, due to a lack of tools to specifically modulate the genome and epigenome in the central nervous system, many molecular and genetic mechanisms underlying cognitive function and behavior are still unknown. Although genome editing tools have been around for decades, the recent emergence of inexpensive, straightforward, and widely accessible CRISPR/Cas9 systems has led to a revolution in gene editing. The development of the catalytically dead Cas9 (dCas9) expanded this flexibility even further by acting as an anchoring system for fused effector proteins, structural scaffolds, and RNAs. Together, these advances have enabled robust, modular approaches for specific targeting and modification of the local chromatin environment at a single gene. This review highlights these advancements and how the combination of powerful modulatory tools paired with the versatility of CRISPR-Cas9-based systems offer great potential for understanding the underlying genetic and epigenetic contributions of neuronal function, behavior, and neurobiological diseases.

A group II metabotropic glutamate receptor 3 (mGlu3, GRM3) isoform implicated in schizophrenia interacts with canonical mGlu3 and reduces ligand binding

As well as being expressed as a full-length transcript, the group II metabotropic glutamate receptor 3 (GRM3, mGlu3) gene is expressed as an mRNA isoform which lacks exon 4 (GRM3Δ4) and which is predicted to encode a protein with a novel C terminus (called mGlu3Δ4). This variant may contribute to the mechanism by which GRM3 acts as a schizophrenia risk gene. However, little is known about the properties or function of mGlu3Δ4. Here, using transiently transfected HEK293T/17 cells, we confirm that GRM3Δ4 cDNA is translated, with mGlu3Δ4 existing as a homodimer as well as a monomer, and localizing primarily to cell membranes including the plasma membrane. Co-immunoprecipitation shows that mGlu3Δ4 interacts with canonical mGlu3. mGlu3Δ4 does not bind the mGlu2/3 antagonist [³H]LY341495, but the presence of mGlu3Δ4 reduces binding of [³H]LY341495 to mGlu3, paralleled by a decrease in the abundance of membrane-associated mGlu3. These experiments indicate that mGlu3Δ4 may negatively modulate mGlu3, and thereby impact on the roles of GRM3/mGlu3 in schizophrenia and as a therapeutic target.

Exome sequences of multiplex, multigenerational families reveal schizophrenia risk loci with potential implications for neurocognitive performance

Schizophrenia is a serious mental illness, involving disruptions in thought and behavior, with a worldwide prevalence of about one percent. Although highly heritable, much of the genetic liability of schizophrenia is yet to be explained. We searched for susceptibility loci in multiplex, multigenerational families affected by schizophrenia, targeting protein-altering variation with in silico predicted functional effects. Exome sequencing was performed on 136 samples from eight European-American families, including 23 individuals diagnosed with schizophrenia or schizoaffective disorder. In total, 11,878 non-synonymous variants from 6,396 genes were tested for their association with schizophrenia spectrum disorders. Pathway enrichment analyses were conducted on gene-based test results, protein-protein interaction (PPI) networks, and epistatic effects. Using a significance threshold of FDR < 0.1, association was detected for rs10941112 (p = 2.1 × 10-5 ; q-value = 0.073) in AMACR, a gene involved in fatty acid metabolism and previously implicated in schizophrenia, with significant cis effects on gene expression (p = 5.5 × 10-4 ), including brain tissue data from the Genotype-Tissue Expression project (minimum p = 6.0 × 10-5 ). A second SNP, rs10378 located in TMEM176A, also shows risk effects in the exome data (p = 2.8 × 10-5 ; q-value = 0.073). PPIs among our top gene-based association results (p < 0.05; n = 359 genes) reveal significant enrichment of genes involved in NCAM-mediated neurite outgrowth (p = 3.0 × 10-5 ), while exome-wide SNP-SNP interaction effects for rs10941112 and rs10378 indicate a potential role for kinase-mediated signaling involved in memory and learning. In conclusion, these association results implicate AMACR and TMEM176A in schizophrenia risk, whose effects may be modulated by genes involved in synaptic plasticity and neurocognitive performance.

Rare Genome-Wide Copy Number Variation and Expression of Schizophrenia in 22q11.2 Deletion Syndrome

OBJECTIVE

Chromosome 22q11.2 deletion syndrome (22q11.2DS) is associated with a more than 20-fold increased risk for developing schizophrenia. The aim of this study was to identify additional genetic factors (i.e., "second hits") that may contribute to schizophrenia expression.

METHOD

Through an international consortium, the authors obtained DNA samples from 329 psychiatrically phenotyped subjects with 22q11.2DS. Using a high-resolution microarray platform and established methods to assess copy number variation (CNV), the authors compared the genome-wide burden of rare autosomal CNV, outside of the 22q11.2 deletion region, between two groups: a schizophrenia group and those with no psychotic disorder at age ≥25 years. The authors assessed whether genes overlapped by rare CNVs were overrepresented in functional pathways relevant to schizophrenia.

RESULTS

Rare CNVs overlapping one or more protein-coding genes revealed significant between-group differences. For rare exonic duplications, six of 19 gene sets tested were enriched in the schizophrenia group; genes associated with abnormal nervous system phenotypes remained significant in a stepwise logistic regression model and showed significant interactions with 22q11.2 deletion region genes in a connectivity analysis. For rare exonic deletions, the schizophrenia group had, on average, more genes overlapped. The additional rare CNVs implicated known (e.g., GRM7, 15q13.3, 16p12.2) and novel schizophrenia risk genes and loci.

CONCLUSIONS

The results suggest that additional rare CNVs overlapping genes outside of the 22q11.2 deletion region contribute to schizophrenia risk in 22q11.2DS, supporting a multigenic hypothesis for schizophrenia. The findings have implications for understanding expression of psychotic illness and herald the importance of whole-genome sequencing to appreciate the overall genomic architecture of schizophrenia.

Associations between SNPs and immune-related circulating proteins in schizophrenia

Genome-wide association studies (GWAS) and proteomic studies have provided convincing evidence implicating alterations in immune/inflammatory processes in schizophrenia. However, despite the convergence of evidence, direct links between the genetic and proteomic findings are still lacking for schizophrenia. We investigated associations between single nucleotide polymorphisms (SNPs) from the custom-made PsychArray and the expression levels of 190 multiplex immunoassay profiled serum proteins in 149 schizophrenia patients and 198 matched controls. We identified associations between 81 SNPs and 29 proteins, primarily involved in immune/inflammation responses. Significant SNPxDiagnosis interactions were identified for eight serum proteins including Factor-VII[rs555212], Alpha-1-Antitrypsin[rs11846959], Interferon-Gamma Induced Protein 10[rs4256246] and von-Willebrand-Factor[rs12829220] in the control group; Chromogranin-A[rs9658644], Cystatin-C[rs2424577] and Vitamin K-Dependent Protein S[rs6123] in the schizophrenia group; Interleukin-6 receptor[rs7553796] in both the control and schizophrenia groups. These results suggested that the effect of these SNPs on expression of the respective proteins varies with diagnosis. The combination of patient-specific genetic information with blood biomarker data opens a novel approach to investigate disease mechanisms in schizophrenia and other psychiatric disorders. Our findings not only suggest that blood protein expression is influenced by polymorphisms in the corresponding gene, but also that the effect of certain SNPs on expression of proteins can vary with diagnosis.