Towards understanding the schizophrenia code: an expanded convergent functional genomics approach

Precision medicine for psychotic disorders: objective assessment, risk prediction, and pharmacogenomics

Psychosis occurs inside the brain, but may have external manifestations (peripheral molecular biomarkers, behaviors) that can be objectively and quantitatively measured. Blood biomarkers that track core psychotic manifestations such as hallucinations and delusions could provide a window into the biology of psychosis, as well as help with diagnosis and treatment. We endeavored to identify objective blood gene expression biomarkers for hallucinations and delusions, using a stepwise discovery, prioritization, validation, and testing in independent cohorts design. We were successful in identifying biomarkers that were predictive of high hallucinations and of high delusions states, and of future psychiatric hospitalizations related to them, more so when personalized by gender and diagnosis. Top biomarkers for hallucinations that survived discovery, prioritization, validation and testing include PPP3CB, DLG1, ENPP2, ZEB2, and RTN4. Top biomarkers for delusions include AUTS2, MACROD2, NR4A2, PDE4D, PDP1, and RORA. The top biological pathways uncovered by our work are glutamatergic synapse for hallucinations, as well as Rap1 signaling for delusions. Some of the biomarkers are targets of existing drugs, of potential utility in pharmacogenomics approaches (matching patients to medications, monitoring response to treatment). The top biomarkers gene expression signatures through bioinformatic analyses suggested a prioritization of existing medications such as clozapine and risperidone, as well as of lithium, fluoxetine, valproate, and the nutraceuticals omega-3 fatty acids and magnesium. Finally, we provide an example of how a personalized laboratory report for doctors would look. Overall, our work provides advances for the improved diagnosis and treatment for schizophrenia and other psychotic disorders.

The Genomic Intersection of Oligodendrocyte Dynamics in Schizophrenia and Aging Unravels Novel Pathological Mechanisms and Therapeutic Potentials

Schizophrenia is a significant worldwide health concern, affecting over 20 million individuals and contributing to a potential reduction in life expectancy by up to 14.5 years. Despite its profound impact, the precise pathological mechanisms underlying schizophrenia continue to remain enigmatic, with previous research yielding diverse and occasionally conflicting findings. Nonetheless, one consistently observed phenomenon in brain imaging studies of schizophrenia patients is the disruption of white matter, the bundles of myelinated axons that provide connectivity and rapid signalling between brain regions. Myelin is produced by specialised glial cells known as oligodendrocytes, which have been shown to be disrupted in post-mortem analyses of schizophrenia patients. Oligodendrocytes are generated throughout life by a major population of oligodendrocyte progenitor cells (OPC), which are essential for white matter health and plasticity. Notably, a decline in a specific subpopulation of OPC has been identified as a principal factor in oligodendrocyte disruption and white matter loss in the aging brain, suggesting this may also be a factor in schizophrenia. In this review, we analysed genomic databases to pinpoint intersections between aging and schizophrenia and identify shared mechanisms of white matter disruption and cognitive dysfunction.

Temporal effects on death by suicide: empirical evidence and possible molecular correlates

Popular culture and medical lore have long postulated a connection between full moon and exacerbations of psychiatric disorders. We wanted to empirically analyze the hypothesis that suicides are increased during the period around full moons. We analyzed pre-COVID suicides from the Marion County Coroner's Office (n = 776), and show that deaths by suicide are significantly increased during the week of the full moon (p = 0.037), with older individuals (age ≥ 55) showing a stronger effect (p = 0.019). We also examined in our dataset which hour of the day (3-4 pm, p = 0.035), and which month of the year (September, p = 0.09) show the most deaths by suicide. We had blood samples on a subset of the subjects (n = 45), which enabled us to look at possible molecular mechanisms. We tested a list of top blood biomarkers for suicidality (n = 154) from previous studies of ours 7, to assess which of them are predictive. The biomarkers for suicidality that are predictive of death by suicide during full moon, peak hour of day, and peak month of year, respectively, compared to outside of those periods, appear to be enriched in circadian clock genes. For full moon it is AHCYL2, ACSM3, AK2, and RBM3. For peak hour it is GSK3B, AK2, and PRKCB. For peak month it is TBL1XR1 and PRKCI. Half of these genes are modulated in expression by lithium and by valproate in opposite direction to suicidality, and all of them are modulated by depression and alcohol in the same direction as suicidality. These data suggest that there are temporal effects on suicidality, possibly mediated by biological clocks, pointing to changes in ambient light (timing and intensity) as a therapeutically addressable target to decrease suicidality, that can be coupled with psychiatric pharmacological and addiction treatment preventive interventions.

Treatment-Resistant Schizophrenia, Clozapine Resistance, Genetic Associations, and Implications for Precision Psychiatry: A Scoping Review

Treatment-resistant schizophrenia (TRS) is often associated with severe burden of disease, poor quality of life and functional impairment. Clozapine is the gold standard for the treatment of TRS, although it is also known to cause significant side effects in some patients. In view of the burgeoning interest in the role of genetic factors in precision psychiatry, we conducted a scoping review to narratively summarize the current genetic factors associated with TRS, clozapine resistance and side effects to clozapine treatment. We searched PubMed from inception to December 2022 and included 104 relevant studies in this review. Extant evidence comprised associations between TRS and clozapine resistance with genetic factors related to mainly dopaminergic and serotoninergic neurotransmitter systems, specifically, TRS and rs4680, rs4818 within COMT, and rs1799978 within DRD2; clozapine resistance and DRD3 polymorphisms, CYP1A2 polymorphisms; weight gain with LEP and SNAP-25 genes; and agranulocytosis risk with HLA-related polymorphisms. Future studies, including replication in larger multi-site samples, are still needed to elucidate putative risk genes and the interactions between different genes and their correlations with relevant clinical factors such as psychopathology, psychosocial functioning, cognition and progressive changes with treatment over time in TRS and clozapine resistance.

Joint Sparse Collaborative Regression on Imaging Genetics Study of Schizophrenia

The imaging genetics approach generates large amount of high dimensional and multi-modal data, providing complementary information for comprehensive study of Schizophrenia, a complex mental disease. However, at the same time, the variety of these data in structures, resolutions, and formats makes their integrative study a forbidding task. In this paper, we propose a novel model called Joint Sparse Collaborative Regression (JSCoReg), which can extract class-specific features from different health conditions/disease classes. We first evaluate the performance of feature selection in terms of Receiver operating characteristic curve and the area under the ROC curve in the simulation experiment. We demonstrate that the JSCoReg model can achieve higher accuracy compared with similar models including Joint Sparse Canonical Correlation Analysis and Sparse Collaborative Regression. We then applied the JSCoReg model to the analysis of schizophrenia dataset collected from the Mind Clinical Imaging Consortium. The JSCoReg enables us to better identify biomarkers associated with schizophrenia, which are verified to be both biologically and statistically significant.

Cannabidiol prevents disruptions in sensorimotor gating induced by psychotomimetic drugs that last for 24-h with probable involvement of epigenetic changes in the ventral striatum

Cannabidiol (CBD), a major non-psychotomimetic component of the Cannabis sativa plant, shows therapeutic potential in several psychiatric disorders, including schizophrenia. The molecular mechanisms underlying the antipsychotic-like effects of CBD are not fully understood. Schizophrenia and antipsychotic treatment can modulate DNA methylation in the blood and brain, resulting in altered expression of diverse genes associated with this complex disorder. However, to date, the possible involvement of DNA methylation in the antipsychotic-like effects of CBD has not been investigated. Therefore, this study aimed at evaluating in mice submitted to the prepulse inhibition (PPI) model: i) the effects of a single injection of CBD or clozapine followed by AMPH or MK-801 on PPI and global DNA methylation changes in the ventral striatum and prefrontal cortex (PFC); and ii). if the acute antipsychotic-like effects of CBD would last for 24-h. AMPH (5 mg/kg) and MK-801 (0.5 mg/kg) impaired PPI. CBD (30 and 60 mg/kg), similar to clozapine (5 mg/kg), attenuated AMPH- and MK801-induced PPI disruption. AMPH, but not MK-801, increased global DNA methylation in the ventral striatum, an effect prevented by CBD. CBD and clozapine increased, by themselves, DNA methylation in the prefrontal cortex. The acute effects of CBD (30 or 60 mg/kg) on the PPI impairment induced by AMPH or MK-801 was also detectable 24 h later. Altogether, the results show that CBD induces acute antipsychotic-like effects that last for 24-h. It also modulates DNA methylation in the ventral striatum, suggesting a new potential mechanism for its antipsychotic-like effects.

DNA methylation meta-analysis reveals cellular alterations in psychosis and markers of treatment-resistant schizophrenia

We performed a systematic analysis of blood DNA methylation profiles from 4483 participants from seven independent cohorts identifying differentially methylated positions (DMPs) associated with psychosis, schizophrenia, and treatment-resistant schizophrenia. Psychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNA methylation data, with the largest differences seen in treatment-resistant schizophrenia patients. We implemented a stringent pipeline to meta-analyze epigenome-wide association study (EWAS) results across datasets, identifying 95 DMPs associated with psychosis and 1048 DMPs associated with schizophrenia, with evidence of colocalization to regions nominated by genetic association studies of disease. Many schizophrenia-associated DNA methylation differences were only present in patients with treatment-resistant schizophrenia, potentially reflecting exposure to the atypical antipsychotic clozapine. Our results highlight how DNA methylation data can be leveraged to identify physiological (e.g., differential cell counts) and environmental (e.g., smoking) factors associated with psychosis and molecular biomarkers of treatment-resistant schizophrenia.

Increased RNA editing in maternal immune activation model of neurodevelopmental disease

The etiology of major neurodevelopmental disorders such as schizophrenia and autism is unclear, with evidence supporting a combination of genetic factors and environmental insults, including viral infection during pregnancy. Here we utilized a mouse model of maternal immune activation (MIA) with the viral mimic PolyI:C infection during early gestation. We investigated the transcriptional changes in the brains of mouse fetuses following MIA during the prenatal period, and evaluated the behavioral and biochemical changes in the adult brain. The results reveal an increase in RNA editing levels and dysregulation in brain development-related gene pathways in the fetal brains of MIA mice. These MIA-induced brain editing changes are not observed in adulthood, although MIA-induced behavioral deficits are observed. Taken together, our findings suggest that MIA induces transient dysregulation of RNA editing at a critical time in brain development.

Convergent Functional Genomics approach to prioritize molecular targets of risk in early life stress-related psychiatric disorders

There is an overwhelming evidence proving that mental disorders are not the product of a single risk factor - i.e. genetic variants or environmental factors, including exposure to maternal perinatal mental health problems or childhood adverse events - rather the product of a trajectory of cumulative and multifactorial insults occurring during development, such as exposures during the foetal life to adverse mental condition in the mother, or exposures to adverse traumatic events during childhood or adolescence. In this review, we aim to highlight the potential utility of a Convergent Functional Genomics (CFG) approach to clarify the complex brain-relevant molecular mechanisms and alterations induced by early life stress (ELS). We describe different studies based on CFG in psychiatry and neuroscience, and we show how this 'hypothesis-free' tool can prioritize a stringent number of genes modulated by ELS, that can be tested as potential candidates for Gene x Environment (GxE) interaction studies. We discuss the results obtained by using a CFG approach identifying FoxO1 as a gene where genetic variability can mediate the effect of an adverse environment on the development of depression. Moreover, we also demonstrate that FoxO1 has a functional relevance in stress-induced reduction of neurogenesis, and can be a potential target for the prevention or treatment of stress-related psychiatric disorders. Overall, we suggest that CFG approach could include trans-species and tissues data integration and we also propose the application of CFG to examine in depth and to prioritize top candidate genes that are affected by ELS across lifespan and generations.

Integrative In Silico Analysis of Genome-Wide DNA Methylation Profiles in Schizophrenia

Schizophrenia (SZ) is a complex and severe psychiatric disorder, which has a global lifetime prevalence of 0.4% and a heritability of around 0.81. A number of epigenome-wide association studies (EWAS) have been carried out for SZ, with discordant results. The main aim of this study was to carry out an integrative in silico analysis of available genome-wide DNA methylation profiles in schizophrenia. In this work, an integration of multiple lines of evidence (top candidate genes from several EWAS and genome-wide expression and association data) was carried out, in order to identify top differentially methylated (DM) genes for SZ. In addition, functional enrichment and protein-protein interaction analyses were carried out. Several top differentially methylated genes, such as APC, CACNB2, and PRKN, were found, and an enrichment of binding sites for brain-expressed transcription factors, such as FOXO1, MYB, and ZIC3, was also observed. Moreover, a protein-protein interaction network showed a central role for DISC1 and ZNF688 genes, and experimentally validated targets of MIR-137, such as and KCNB2, NRXN1, and SYN2, were identified among DM genes. This is the first integrative in silico analysis of available genome-wide DNA methylation profiles in schizophrenia. This work identified novel candidate genes and pathways for SZ and provides the basis to explore their role in the pathogenesis of SZ in future studies.

Identifying novel associations in GWAS by hierarchical Bayesian latent variable detection of differentially misclassified phenotypes

Background

Heterogeneity in the definition and measurement of complex diseases in Genome-Wide Association Studies (GWAS) may lead to misdiagnoses and misclassification errors that can significantly impact discovery of disease loci. While well appreciated, almost all analyses of GWAS data consider reported disease phenotype values as is without accounting for potential misclassification.

Results

Here, we introduce Phenotype Latent variable Extraction of disease misdiagnosis (PheLEx), a GWAS analysis framework that learns and corrects misclassified phenotypes using structured genotype associations within a dataset. PheLEx consists of a hierarchical Bayesian latent variable model, where inference of differential misclassification is accomplished using filtered genotypes while implementing a full mixed model to account for population structure and genetic relatedness in study populations. Through simulations, we show that the PheLEx framework dramatically improves recovery of the correct disease state when considering realistic allele effect sizes compared to existing methodologies designed for Bayesian recovery of disease phenotypes. We also demonstrate the potential of PheLEx for extracting new potential loci from existing GWAS data by analyzing bipolar disorder and epilepsy phenotypes available from the UK Biobank. From the PheLEx analysis of these data, we identified new candidate disease loci not previously reported for these datasets that have value for supplemental hypothesis generation.

Conclusion

PheLEx shows promise in reanalyzing GWAS datasets to provide supplemental candidate loci that are ignored by traditional GWAS analysis methodologies.

Identification of Potential Long Noncoding RNA Biomarker of Mercury Compounds in Zebrafish Embryos

Heavy metal pollution elicits severe environmental concern and health problem worldwide. Mercury is considered as a ubiquitous pollutant due to its versatile application in medicine, industry, and cosmetics. Long noncoding RNAs (lncRNAs) are transcripts greater than 200 nt without protein-encoding function. However, little is known about the mechanism of heavy metals-induced noncoding RNA changes in aquatic organisms. To reveal the epigenetic mechanism of mercury toxicity in zebrafish embryos and explore novel specific mercury-toxicological biomarkers, several well-studied lncRNAs were screened by real-time PCR, and the spatial-temporal expression of lncRNAs biomarker was evaluated by in situ hybridization. The nerve systems of zebrafish embryos were evaluated by detecting locomotor behavior and the expression of neuro-genes. We identified a mercury responsive lncRNA, metastasis-associated lung adenocarcinoma transcript 1 (malat1), among five candidate lncRNAs. HgCl₂, MeHg, PbCl₂, CdCl₂, and K₂CrO₄ exposure assay showed that malat-1 was a mercury specific induced lncRNAs. Malat1 was highly expressed in the brain region, eyes, and notochord of developing zebrafish embryos after exposure to mercury compounds. HgCl₂ showed neurobehavior disturbance and changed neuro-genes expression pattern in zebrafish larvae. This study provides a biological method to detect inorganic or organic mercury using malat1 as a novel biomarker of mercury contamination and also clues for the exploration of neurotoxicity mechanism of mercury compounds.

Orphan Receptor GPR88 as an Emerging Neurotherapeutic Target

Although G protein-coupled receptors (GPCRs) are recognized as pivotal drug targets involved in multiple physiological and pathological processes, the majority of GPCRs including orphan GPCRs (oGPCRs) are unexploited. GPR88, a brain-specific oGPCR with particularly robust expression in the striatum, regulates diverse brain and behavioral functions, including cognition, mood, movement control, and reward-based learning, and is thus emerging as a novel drug target for central nervous system disorders including schizophrenia, Parkinson's disease, anxiety, and addiction. Nevertheless, no effective GPR88 synthetic ligands have yet entered into clinical trials, and GPR88 endogenous ligands remain unknown. Despite the recent discovery and early stage study of several GPR88 agonists, such as 2-PCCA, RTI-13951-33, and phenylglycinol derivatives, further research into GPR88 pharmacology, medicinal chemistry, and chemical biology is urgently needed to yield structurally diversified GPR88-specific ligands. Drug-like pharmacological tool function and relevant signaling elucidation will also accelerate the evaluation of this receptor as a viable neurotherapeutic target.

Towards precision medicine for pain: diagnostic biomarkers and repurposed drugs

We endeavored to identify objective blood biomarkers for pain, a subjective sensation with a biological basis, using a stepwise discovery, prioritization, validation, and testing in independent cohorts design. We studied psychiatric patients, a high risk group for co-morbid pain disorders and increased perception of pain. For discovery, we used a powerful within-subject longitudinal design. We were successful in identifying blood gene expression biomarkers that were predictive of pain state, and of future emergency department (ED) visits for pain, more so when personalized by gender and diagnosis. MFAP3, which had no prior evidence in the literature for involvement in pain, had the most robust empirical evidence from our discovery and validation steps, and was a strong predictor for pain in the independent cohorts, particularly in females and males with PTSD. Other biomarkers with best overall convergent functional evidence for involvement in pain were GNG7, CNTN1, LY9, CCDC144B, and GBP1. Some of the individual biomarkers identified are targets of existing drugs. Moreover, the biomarker gene expression signatures were used for bioinformatic drug repurposing analyses, yielding leads for possible new drug candidates such as SC-560 (an NSAID), and amoxapine (an antidepressant), as well as natural compounds such as pyridoxine (vitamin B6), cyanocobalamin (vitamin B12), and apigenin (a plant flavonoid). Our work may help mitigate the diagnostic and treatment dilemmas that have contributed to the current opioid epidemic.

Decoding the transcriptional programs activated by psychotropic drugs in the brain

Analysis of drug-induced gene expression in the brain has long held the promise of revealing the molecular mechanisms of drug actions as well as predicting their long-term clinical efficacy. However, despite some successes, this promise has yet to be fulfilled. Here, we present an overview of the current state of understanding of drug-induced gene expression in the brain and consider the obstacles to achieving a robust prediction of the properties of psychoactive compounds based on gene expression profiles. We begin with a comprehensive overview of the mechanisms controlling drug-inducible transcription and the complexity resulting from expression of noncoding RNAs and alternative gene isoforms. Particular interest is placed on studies that examine the associations within drug classes with regard to the effects on gene transcription, alterations in cell signaling and neuropharmacological drug properties. While the ability of gene expression signatures to distinguish specific clinical classes of psychotropic and addictive drugs remains unclear, some reports show that under specific constraints, drug properties can be predicted based on gene expression. Such signatures offer a simple and effective way to classify psychotropic drugs and screen novel psychoactive compounds. Finally, we note that the amount of data regarding molecular programs activated in the brain by drug treatment has grown exponentially in recent years and that future advances may therefore come in large part from integrating the currently available high-throughput data sets.

Comprehensive integrative analyses identify GLT8D1 and CSNK2B as schizophrenia risk genes

Recent genome-wide association studies (GWAS) have identified multiple risk loci that show strong associations with schizophrenia. However, pinpointing the potential causal genes at the reported loci remains a major challenge. Here we identify candidate causal genes for schizophrenia using an integrative genomic approach. Sherlock integrative analysis shows that ALMS1, GLT8D1, and CSNK2B are schizophrenia risk genes, which are validated using independent brain expression quantitative trait loci (eQTL) data and integrative analysis method (SMR). Consistently, gene expression analysis in schizophrenia cases and controls further supports the potential role of these three genes in the pathogenesis of schizophrenia. Finally, we show that GLT8D1 and CSNK2B knockdown promote the proliferation and inhibit the differentiation abilities of neural stem cells, and alter morphology and synaptic transmission of neurons. These convergent lines of evidence suggest that the ALMS1, CSNK2B, and GLT8D1 genes may be involved in pathophysiology of schizophrenia.

More than 100 risk loci for schizophrenia have been identified by genome-wide association studies. Here, the authors apply an integrative genomic approach to prioritize risk genes and validate GLT8D1 and CSNK2B as candidate causal genes by in vitro studies in neural stem cells.

Meta-analyses of RELN variants in neuropsychiatric disorders

Reelin is a critical extracellular matrix glycoprotein and implicated in neurodevelopment and psychiatric disorders in animal model studies. The genetic polymorphism of RELN has also been reported to be associated with several psychiatric disorders, but the results remain controversial. Here, we conducted meta-analyses of RELN gene SNPs and related neuropsychiatric disorders (schizophrenia, autistic spectrum disorders, attention-deficit hyperactivity disorder, Alzheimer's disease and bipolar disorders). A total of 12 SNPs (rs736707, rs362691, rs607755, rs2229864, rs7341475, rs262355, rs362719, rs11496125, g.-888G>C, rs2299356, rs528528, and rs4298437) in RELN gene were included into meta-analyses. Subgroup analyses based on ethnicity were performed. We found that RELN rs736707 was significantly related with psychiatric disorders (schizophrenia, autism spectrum disorders and attention-deficit hyperactivity disorder) in Asian group (C vs T, OR=1.26, 95% CI=1.13-1.41, P<0.01, FDR<0.01), and rs7341475 was only significantly associated with reduced risk of schizophrenia in Caucasian (A vs G, OR=0.88, 95% CI=0.82-0.95, P<0.01, FDR<0.01). No association of other SNPs and psychiatric disorders is found. These findings suggest a role of RELN SNPs in psychiatric diseases, and indicate that further researches in populations with different genetic background and studies with larger sample size are of great value.

GABAA and GABAB receptor dysregulation in superior frontal cortex of subjects with schizophrenia and bipolar disorder

Schizophrenia and bipolar disorder are complex psychiatric disorders that affect millions of people worldwide. Evidence from gene association and postmortem studies has identified abnormalities of the gamma-aminobutyric acid (GABA) signaling system in both disorders. Abnormal GABAergic signaling and transmission could contribute to the symptomatology of these disorders, potentially through impaired gamma oscillations which normally occur during cognitive processing. In the current study, we examined the protein expression of 14 GABA_A and two GABA_B receptor subunits in the superior frontal cortex of subjects with schizophrenia, bipolar disorder, and healthy controls. Analyses of Variance (ANOVAs) identified significant group effects for protein levels for the α1, α6, β1, β3, δ, ɛ, and π GABA_A receptor subunits and R1 and R2 GABA_B receptor subunits. Follow-up t tests confirmed changes for these subunits in subjects with schizophrenia, subjects with bipolar disorder, or both groups. Alterations in stoichiometry of GABA receptor subunits could result in altered ligand binding, transmission, and pharmacology of GABA receptors in superior frontal cortex. Thus, impaired GABAergic transmission may negatively contribute to symptoms such as anxiety or panic as well as impaired learning and information processing, all of which are disrupted in schizophrenia and bipolar disorder. Taken together, these results provide additional evidence of GABAergic receptor abnormalities in these disorders.

Neuro-psychopharmacological perspective of Orphan receptors of Rhodopsin (class A) family of G protein-coupled receptors

BACKGROUND

In the central nervous system (CNS), G protein-coupled receptors (GPCRs) are the most fruitful targets for neuropsychopharmacological drug development. Rhodopsin (class A) is the most studied class of GPCR and includes orphan receptors for which the endogenous ligand is not known or is unclear. Characterization of orphan GPCRs has proven to be challenging, and the production pace of GPCR-based drugs has been incredibly slow.

OBJECTIVE

Determination of the functions of these receptors may provide unexpected insight into physiological and neuropathological processes. Advances in various methods and techniques to investigate orphan receptors including in situ hybridization and knockdown/knockout (KD/KO) showed extensive expression of these receptors in the mammalian brain and unmasked their physiological and neuropathological roles. Due to these rapid progress and development, orphan GPCRs are rising as a new and promising class of drug targets for neurodegenerative diseases and psychiatric disorders.

CONCLUSION

This review presents a neuropsychopharmacological perspective of 26 orphan receptors of rhodopsin (class A) family, namely GPR3, GPR6, GPR12, GPR17, GPR26, GPR35, GPR39, GPR48, GPR49, GPR50, GPR52, GPR55, GPR61, GPR62, GPR63, GPR68, GPR75, GPR78, GPR83, GPR84, GPR85, GPR88, GPR153, GPR162, GPR171, and TAAR6. We discussed the expression of these receptors in mammalian brain and their physiological roles. Furthermore, we have briefly highlighted their roles in neurodegenerative diseases and psychiatric disorders including Alzheimer's disease, Parkinson's disease, neuroinflammation, inflammatory pain, bipolar and schizophrenic disorders, epilepsy, anxiety, and depression.

Sex differences in DNA methylation of the cord blood are related to sex-bias psychiatric diseases

Sex differences in the prevalence of psychiatric disorders are well documented, with exposure to stress during gestation differentially impacting females and males. We explored sex-specific DNA methylation in the cord blood of 39 females and 32 males born at term and with appropriate weight at birth regarding their potential connection to psychiatric outcomes. Mothers were interviewed to gather information about environmental factors (gestational exposure) that could interfere with the methylation profiles in the newborns. Bisulphite converted DNA was hybridized to Illumina HumanMethylation450 BeadChips. Excluding XYS probes, there were 2,332 differentially methylated CpG sites (DMSs) between sexes, which were enriched within brain modules of co-methylated CpGs during brain development and also differentially methylated in the brains of boys and girls. Genes associated with the DMSs were enriched for neurodevelopmental disorders, particularly for CpG sites found differentially methylated in brain tissue between patients with schizophrenia and controls. Moreover, the DMS had an overlap of 890 (38%) CpG sites with a cohort submitted to toxic exposition during gestation. This study supports the evidences that sex differences in DNA methylation of autosomes act as a primary driver of sex differences that are found in psychiatric outcomes.

Joint sparse canonical correlation analysis for detecting differential imaging genetics modules

MOTIVATION

Imaging genetics combines brain imaging and genetic information to identify the relationships between genetic variants and brain activities. When the data samples belong to different classes (e.g. disease status), the relationships may exhibit class-specific patterns that can be used to facilitate the understanding of a disease. Conventional approaches often perform separate analysis on each class and report the differences, but ignore important shared patterns.

RESULTS

In this paper, we develop a multivariate method to analyze the differential dependency across multiple classes. We propose a joint sparse canonical correlation analysis method, which uses a generalized fused lasso penalty to jointly estimate multiple pairs of canonical vectors with both shared and class-specific patterns. Using a data fusion approach, the method is able to detect differentially correlated modules effectively and efficiently. The results from simulation studies demonstrate its higher accuracy in discovering both common and differential canonical correlations compared to conventional sparse CCA. Using a schizophrenia dataset with 92 cases and 116 controls including a single nucleotide polymorphism (SNP) array and functional magnetic resonance imaging data, the proposed method reveals a set of distinct SNP-voxel interaction modules for the schizophrenia patients, which are verified to be both statistically and biologically significant.

AVAILABILITY AND IMPLEMENTATION

The Matlab code is available at https://sites.google.com/site/jianfang86/JSCCA CONTACT: wyp@tulane.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Reversal of dendritic phenotypes in 16p11.2 microduplication mouse model neurons by pharmacological targeting of a network hub

The architecture of dendritic arbors contributes to neuronal connectivity in the brain. Conversely, abnormalities in dendrites have been reported in multiple mental disorders and are thought to contribute to pathogenesis. Rare copy number variations (CNVs) are genetic alterations that are associated with a wide range of mental disorders and are highly penetrant. The 16p11.2 microduplication is one of the CNVs most strongly associated with schizophrenia and autism, spanning multiple genes possibly involved in synaptic neurotransmission. However, disease-relevant cellular phenotypes of 16p11.2 microduplication and the driver gene(s) remain to be identified. We found increased dendritic arborization in isolated cortical pyramidal neurons from a mouse model of 16p11.2 duplication (dp/+). Network analysis identified MAPK3, which encodes ERK1 MAP kinase, as the most topologically important hub in protein-protein interaction networks within the 16p11.2 region and broader gene networks of schizophrenia-associated CNVs. Pharmacological targeting of ERK reversed dendritic alterations associated with dp/+ neurons, outlining a strategy for the analysis and reversal of cellular phenotypes in CNV-related psychiatric disorders.

Candidate gene networks and blood biomarkers of methamphetamine-associated psychosis: an integrative RNA-sequencing report

The clinical presentation, course and treatment of methamphetamine (METH)-associated psychosis (MAP) are similar to that observed in schizophrenia (SCZ) and subsequently MAP has been hypothesized as a pharmacological and environmental model of SCZ. However, several challenges currently exist in diagnosing MAP accurately at the molecular and neurocognitive level before the MAP model can contribute to the discovery of SCZ biomarkers. We directly assessed subcortical brain structural volumes and clinical parameters of MAP within the framework of an integrative genome-wide RNA-Seq blood transcriptome analysis of subjects diagnosed with MAP (N=10), METH dependency without psychosis (MA; N=10) and healthy controls (N=10). First, we identified discrete groups of co-expressed genes (that is, modules) and tested them for functional annotation and phenotypic relationships to brain structure volumes, life events and psychometric measurements. We discovered one MAP-associated module involved in ubiquitin-mediated proteolysis downregulation, enriched with 61 genes previously found implicated in psychosis and SCZ across independent blood and post-mortem brain studies using convergent functional genomic (CFG) evidence. This module demonstrated significant relationships with brain structure volumes including the anterior corpus callosum (CC) and the nucleus accumbens. Furthermore, a second MAP and psychoticism-associated module involved in circadian clock upregulation was also enriched with 39 CFG genes, further associated with the CC. Subsequently, a machine-learning analysis of differentially expressed genes identified single blood-based biomarkers able to differentiate controls from methamphetamine dependents with 87% accuracy and MAP from MA subjects with 95% accuracy. CFG evidence validated a significant proportion of these putative MAP biomarkers in independent studies including CLN3, FBP1, TBC1D2 and ZNF821 (RNA degradation), ELK3 and SINA3 (circadian clock) and PIGF and UHMK1 (ubiquitin-mediated proteolysis). Finally, focusing analysis on brain structure volumes revealed significantly lower bilateral hippocampal volumes in MAP subjects. Overall, these results suggest similar molecular and neurocognitive mechanisms underlying the pathophysiology of psychosis and SCZ regardless of substance abuse and provide preliminary evidence supporting the MAP paradigm as an exemplar for SCZ biomarker discovery.

Developmental and adult expression patterns of the G-protein-coupled receptor GPR88 in the rat: Establishment of a dual nuclear-cytoplasmic localization

GPR88 is a neuronal cerebral orphan G-protein-coupled receptor (GPCR) that has been linked to various psychiatric disorders. However, no extensive description of its localization has been provided so far. Here, we investigate the spatiotemporal expression of the GPR88 in prenatal and postnatal rat tissues by using in situ hybridization and immunohistochemistry. GPR88 protein was initially detected at embryonic day 16 (E16) in the striatal primordium. From E16-E20 to adulthood, the highest expression levels of both protein and mRNA were observed in striatum, olfactory tubercle, nucleus accumbens, amygdala, and neocortex, whereas in spinal cord, pons, and medulla GPR88 expression remains discrete. We observed an intracellular redistribution of GPR88 during cortical lamination. In the cortical plate of the developing cortex, GPR88 presents a classical GPCR plasma membrane/cytoplasmic localization that shifts, on the day of birth, to nuclei of neurons progressively settling in layers V to II. This intranuclear localization remains throughout adulthood and was also detected in monkey and human cortex as well as in the amygdala and hypothalamus of rats. Apart from the central nervous system, GPR88 was transiently expressed at high levels in peripheral tissues, including adrenal cortex (E16-E21) and cochlear ganglia (E19-P3), and also at moderate levels in retina (E18-E19) and spleen (E21-P7). The description of the GPR88 anatomical expression pattern may provide precious functional insights into this novel receptor. Furthermore, the GRP88 nuclear localization suggests nonclassical GPCR modes of action of the protein that could be relevant for cortical development and psychiatric disorders. J. Comp. Neurol. 524:2776-2802, 2016. © 2016 Wiley Periodicals, Inc.

Malat1 as an evolutionarily conserved lncRNA, plays a positive role in regulating proliferation and maintaining undifferentiated status of early-stage hematopoietic cells

Background

The metastasis-associated lung adenocarcinoma transcription 1 (Malat1) is a highly conserved long non-coding RNA (lncRNA) gene. Previous studies showed that Malat1 is abundantly expressed in many tissues and involves in promoting tumor growth and metastasis by modulating gene expression and target protein activities. However, little is known about the biological function and regulation mechanism of Malat1 in normal cell proliferation.

Results

In this study we conformed that Malat1 is highly conserved across vast evolutionary distances amongst 20 species of mammals in terms of sequence, and found that mouse Malat1 expresses in tissues of liver, kidney, lung, heart, testis, spleen and brain, but not in skeletal muscle. After treating erythroid myeloid lymphoid (EML) cells with All-trans Retinoic Acid (ATRA), we investigated the expression and regulation of Malat1 during hematopoietic differentiation, the results showed that ATRA significantly down regulates Malat1 expression during the differentiation of EML cells. Mouse LRH (Lin-Rhodamine^low Hoechst^low) cells that represent the early-stage progenitor cells show a high level of Malat1 expression, while LRB (Lin − Hoechst^Low Rhodamine^Bright) cells that represent the late-stage progenitor cells had no detectable expression of Malat1.

Knockdown experiment showed that depletion of Malat1 inhibits the EML cell proliferation. Along with the down regulation of Malat1, the tumor suppressor gene p53 was up regulated during the differentiation. Interestingly, we found two p53 binding motifs with help of bioinformatic tools, and the following chromatin immunoprecipitation (ChIP) test conformed that p53 acts as a transcription repressor that binds to Malat1’s promoter. Furthermore, we testified that p53 over expression in EML cells causes down regulation of Malat1.

Conclusions

In summary, this study indicates Malat1 plays a critical role in maintaining the proliferation potential of early-stage hematopoietic cells. In addition to its biological function, the study also uncovers the regulation pattern of Malat1 expression mediated by p53 in hematopoietic differentiation. Our research shed a light on exploring the Malat1 biological role including therapeutic significance to inhibit the proliferation potential of malignant cells.

Decreased Na(+) influx lowers hippocampal neuronal excitability in a mouse model of neonatal influenza infection

Influenza virus infection is one of common infectious diseases occurring worldwide. The human influenza virus can infect the central nervous system and cause brain dysfunctions affecting cognition and spatial memory. It has been previously shown that infection with the influenza viral protein within the hippocampus decreases Ca(2+) influx and reduces excitatory postsynaptic currents. However, the neuronal properties of animals surviving neonatal infection have not been investigated. Using a mouse model of neonatal influenza infection, we performed thorough electrophysiological analyses of hippocampal neurotransmission. We found that animals surviving the infection exhibited reduced spontaneous transmission with no significant defects in evoked neurotransmission. Interestingly, the hippocampus of the infected group conducted synaptic transmission with less fidelity upon repeated stimulations and failed to generate action potentials faithfully upon step current injections primarily due to reduced Na(+) influx. The reversal potential for the Na(+) current was hyperpolarized and the activation of Na(+) channels was slower in the infected group while the inactivation process was minimally disturbed. Taken together, our observations suggest that neonatally infected offsprings exhibit noticeable deficits at rest and severe failures when higher activity is required. This study provides insight into understanding the cellular mechanisms of influenza infection-associated functional changes in the brain.

The discovery of potent agonists for GPR88, an orphan GPCR, for the potential treatment of CNS disorders

Modulating GPR88 activity is suggested to have therapeutic utility in the treatment of CNS disorders, such as schizophrenia. This Letter will describe the discovery and SAR development of a class of potent GPR88 agonists.

Altered gene expression in schizophrenia: findings from transcriptional signatures in fibroblasts and blood

BACKGROUND

Whole-genome expression studies in the peripheral tissues of patients affected by schizophrenia (SCZ) can provide new insight into the molecular basis of the disorder and innovative biomarkers that may be of great utility in clinical practice. Recent evidence suggests that skin fibroblasts could represent a non-neural peripheral model useful for investigating molecular alterations in psychiatric disorders.

METHODS

A microarray expression study was conducted comparing skin fibroblast transcriptomic profiles from 20 SCZ patients and 20 controls. All genes strongly differentially expressed were validated by real-time quantitative PCR (RT-qPCR) in fibroblasts and analyzed in a sample of peripheral blood cell (PBC) RNA from patients (n = 25) and controls (n = 22). To evaluate the specificity for SCZ, alterations in gene expression were tested in additional samples of fibroblasts and PBCs RNA from Major Depressive Disorder (MDD) (n = 16; n = 21, respectively) and Bipolar Disorder (BD) patients (n = 15; n = 20, respectively).

RESULTS

Six genes (JUN, HIST2H2BE, FOSB, FOS, EGR1, TCF4) were significantly upregulated in SCZ compared to control fibroblasts. In blood, an increase in expression levels was confirmed only for EGR1, whereas JUN was downregulated; no significant differences were observed for the other genes. EGR1 upregulation was specific for SCZ compared to MDD and BD.

CONCLUSIONS

Our study reports the upregulation of JUN, HIST2H2BE, FOSB, FOS, EGR1 and TCF4 in the fibroblasts of SCZ patients. A significant alteration in EGR1 expression is also present in SCZ PBCs compared to controls and to MDD and BD patients, suggesting that this gene could be a specific biomarker helpful in the differential diagnosis of major psychoses.

Design, synthesis, and evaluation of phenylglycinols and phenyl amines as agonists of GPR88

Small molecule modulators of GPR88 activity (agonists, antagonists, or modulators) are of interest as potential agents for the treatment of a variety of psychiatric disorders including schizophrenia. A series of phenylglycinol and phenylamine analogs have been prepared and evaluated for their GPR88 agonist activity and pharmacokinetic (PK) properties.

Prenatal stress-induced programming of genome-wide promoter DNA methylation in 5-HTT-deficient mice

The serotonin transporter gene (5-HTT/SLC6A4)-linked polymorphic region has been suggested to have a modulatory role in mediating effects of early-life stress exposure on psychopathology rendering carriers of the low-expression short (s)-variant more vulnerable to environmental adversity in later life. The underlying molecular mechanisms of this gene-by-environment interaction are not well understood, but epigenetic regulation including differential DNA methylation has been postulated to have a critical role. Recently, we used a maternal restraint stress paradigm of prenatal stress (PS) in 5-HTT-deficient mice and showed that the effects on behavior and gene expression were particularly marked in the hippocampus of female 5-Htt+/- offspring. Here, we examined to which extent these effects are mediated by differential methylation of DNA. For this purpose, we performed a genome-wide hippocampal DNA methylation screening using methylated-DNA immunoprecipitation (MeDIP) on Affymetrix GeneChip Mouse Promoter 1.0 R arrays. Using hippocampal DNA from the same mice as assessed before enabled us to correlate gene-specific DNA methylation, mRNA expression and behavior. We found that 5-Htt genotype, PS and their interaction differentially affected the DNA methylation signature of numerous genes, a subset of which showed overlap with the expression profiles of the corresponding transcripts. For example, a differentially methylated region in the gene encoding myelin basic protein (Mbp) was associated with its expression in a 5-Htt-, PS- and 5-Htt × PS-dependent manner. Subsequent fine-mapping of this Mbp locus linked the methylation status of two specific CpG sites to Mbp expression and anxiety-related behavior. In conclusion, hippocampal DNA methylation patterns and expression profiles of female prenatally stressed 5-Htt+/- mice suggest that distinct molecular mechanisms, some of which are promoter methylation-dependent, contribute to the behavioral effects of the 5-Htt genotype, PS exposure and their interaction.

Use of translational pharmacodynamic biomarkers in early-phase clinical studies for schizophrenia

Schizophrenia is a severe mental disorder characterized by cognitive deficits, and positive and negative symptoms. The development of effective pharmacological compounds for the treatment of schizophrenia has proven challenging and costly, with many compounds failing during clinical trials. Many failures occur due to disease heterogeneity and lack of predictive preclinical models and biomarkers that readily translate to humans during early characterization of novel antipsychotic compounds. Traditional early-phase trials consist of single- or multiple-dose designs aimed at determining the safety and tolerability of an investigational compound in healthy volunteers. However, by incorporating a translational approach employing methodologies derived from preclinical studies, such as EEG measures and imaging, into the traditional Phase I program, critical information regarding a compound's dose-response effects on pharmacodynamic biomarkers can be acquired. Furthermore, combined with the use of patients with stable schizophrenia in early-phase clinical trials, significant 'de-risking' and more confident 'go/no-go' decisions are possible.

Convergent lines of evidence support CAMKK2 as a schizophrenia susceptibility gene

Genes that are differentially expressed between schizophrenia patients and healthy controls may have key roles in the pathogenesis of schizophrenia. We analyzed two large-scale genome-wide expression studies, which examined changes in gene expression in schizophrenia patients and their matched controls. We found calcium/calmodulin (CAM)-dependent protein kinase kinase 2 (CAMKK2) is significantly downregulated in individuals with schizophrenia in both studies. To seek the potential genetic variants that may regulate the expression of CAMKK2, we investigated the association between single-nucleotide polymorphisms (SNPs) within CAMKK2 and the expression level of CAMKK2. We found one SNP, rs1063843, which is located in intron 17 of CAMKK2, is strongly associated with the expression level of CAMKK2 in human brains (P=1.1 × 10(-6)) and lymphoblastoid cell lines (the lowest P=8.4 × 10(-6)). We further investigated the association between rs1063843 and schizophrenia in multiple independent populations (a total of 130 623 subjects) and found rs1063843 is significantly associated with schizophrenia (P=5.17 × 10(-5)). Interestingly, we found the T allele of rs1063843, which is associated with lower expression level of CAMKK2, has a higher frequency in individuals with schizophrenia in all of the tested samples, suggesting rs1063843 may be a causal variant. We also found that rs1063843 is associated with cognitive function and personality in humans. In addition, protein-protein interaction (PPI) analysis revealed that CAMKK2 participates in a highly interconnected PPI network formed by top schizophrenia genes, which further supports the potential role of CAMKK2 in the pathogenesis of schizophrenia. Taken together, these converging lines of evidence strongly suggest that CAMKK2 may have pivotal roles in schizophrenia susceptibility.

Antipsychotic drug-associated gene-miRNA interaction in T-lymphocytes

Antipsychotic drugs (APDs) can have a profound effect on the human body that extends well beyond our understanding of their neuropsychopharmacology. Some of these effects manifest themselves in peripheral blood lymphocytes, and in some cases, particularly in clozapine treatment, result in serious complications. To better understand the molecular biology of APD action in lymphocytes, we investigated the influence of chlorpromazine, haloperidol and clozapine in vitro, by microarray-based gene and microRNA (miRNA) expression analysis. JM-Jurkat T-lymphocytes were cultured in the presence of the APDs or vehicle alone over 2 wk to model the early effects of APDs on expression. Interestingly both haloperidol and clozapine appear to regulate the expression of a large number of genes. Functional analysis of APD-associated differential expression revealed changes in genes related to oxidative stress, metabolic disease and surprisingly also implicated pathways and biological processes associated with neurological disease consistent with current understanding of the activity of APDs. We also identified miRNA-mRNA interaction associated with metabolic pathways and cell death/survival, all which could have relevance to known side effects of APDs. These results indicate that APDs have a significant effect on expression in peripheral tissue that relate to both known mechanisms as well as poorly characterized side effects.

The myelin membrane-associated enzyme 2',3'-cyclic nucleotide 3'-phosphodiesterase: on a highway to structure and function

The membrane-anchored myelin enzyme 2',3'-cyclic nucleotide 3'-phosphodiesterase (CNPase) was discovered in the early 1960s and has since then troubled scientists with its peculiar catalytic activity and high expression levels in the central nervous system. Despite decades of research, the actual physiological relevance of CNPase has only recently begun to unravel. In addition to a role in myelination, CNPase is also involved in local adenosine production in traumatic brain injury and possibly has a regulatory function in mitochondrial membrane permeabilization. Although research focusing on the CNPase phosphodiesterase activity has been helpful, several open questions concerning the protein function in vivo remain unanswered. This review is focused on past research on CNPase, especially in the fields of structural biology and enzymology, and outlines the current understanding regarding the biochemical and physiological significance of CNPase, providing ideas and directions for future research.

Immune system disturbances in schizophrenia

Epidemiological, genetic, transcriptome, postmortem, peripheral biomarker, and therapeutic studies of schizophrenia all point to a dysregulation of both innate and adaptive immune systems in the disease, and it is likely that these immune changes actively contribute to disease symptoms. Gene expression disturbances in the brain of subjects with schizophrenia show complex, region-specific changes with consistently replicated and potentially interdependent induction of serpin peptidase inhibitor, clade A member 3 (SERPINA3) and interferon inducible transmembrane protein (IFITM) family transcripts in the prefrontal cortex. Recent data suggest that IFITM3 expression is a critical mediator of maternal immune activation. Because the IFITM gene family is primarily expressed in the endothelial cells and meninges, and because the meninges play a critical role in interneuron development, we suggest that these two non-neuronal cell populations might play an important role in the disease pathophysiology. Finally, we propose that IFITM3 in particular might be a novel, appealing, knowledge-based drug target for treatment of schizophrenia.

Discovery and validation of blood biomarkers for suicidality

Suicides are a leading cause of death in psychiatric patients, and in society at large. Developing more quantitative and objective ways (biomarkers) for predicting and tracking suicidal states would have immediate practical applications and positive societal implications. We undertook such an endeavor. First, building on our previous blood biomarker work in mood disorders and psychosis, we decided to identify blood gene expression biomarkers for suicidality, looking at differential expression of genes in the blood of subjects with a major mood disorder (bipolar disorder), a high-risk population prone to suicidality. We compared no suicidal ideation (SI) states and high SI states using a powerful intrasubject design, as well as an intersubject case-case design, to generate a list of differentially expressed genes. Second, we used a comprehensive Convergent Functional Genomics (CFG) approach to identify and prioritize from the list of differentially expressed gene biomarkers of relevance to suicidality. CFG integrates multiple independent lines of evidence-genetic and functional genomic data-as a Bayesian strategy for identifying and prioritizing findings, reducing the false-positives and false-negatives inherent in each individual approach. Third, we examined whether expression levels of the blood biomarkers identified by us in the live bipolar subject cohort are actually altered in the blood in an age-matched cohort of suicide completers collected from the coroner's office, and report that 13 out of the 41 top CFG scoring biomarkers (32%) show step-wise significant change from no SI to high SI states, and then to the suicide completers group. Six out of them (15%) remained significant after strict Bonferroni correction for multiple comparisons. Fourth, we show that the blood levels of SAT1 (spermidine/spermine N1-acetyltransferase 1), the top biomarker identified by us, at the time of testing for this study, differentiated future as well as past hospitalizations with suicidality, in a live cohort of bipolar disorder subjects, and exhibited a similar but weaker pattern in a live cohort of psychosis (schizophrenia/schizoaffective disorder) subjects. Three other (phosphatase and tensin homolog (PTEN), myristoylated alanine-rich protein kinase C substrate (MARCKS), and mitogen-activated protein kinase kinase kinase 3 (MAP3K3)) of the six biomarkers that survived Bonferroni correction showed similar but weaker effects. Taken together, the prospective and retrospective hospitalization data suggests SAT1, PTEN, MARCKS and MAP3K3 might be not only state biomarkers but trait biomarkers as well. Fifth, we show how a multi-dimensional approach using SAT1 blood expression levels and two simple visual-analog scales for anxiety and mood enhances predictions of future hospitalizations for suicidality in the bipolar cohort (receiver-operating characteristic curve with area under the curve of 0.813). Of note, this simple approach does not directly ask about SI, which some individuals may deny or choose not to share with clinicians. Lastly, we conducted bioinformatic analyses to identify biological pathways, mechanisms and medication targets. Overall, suicidality may be underlined, at least in part, by biological mechanisms related to stress, inflammation and apoptosis.

Convergent functional genomics of stem cell-derived cells

Stem cell technologies provide an exciting avenue to directly access the transcriptome of patients in neuronal-like cell types, which might have more direct relevance to brain research than other peripheral tissues (blood, fibroblasts). Enthusiasm should be tempered by concerns that artifacts and noise might be generated as part of the in vitro process of creating and maintaining these cell type. A solution may be to apply a Convergent Functional Genomics approach, where the data from stem cell-derived neuronal cells are integrated, cross-validated and prioritized using independent lines of evidence from other approaches and platforms (human genetic data, human postmortem brain data, animal model data). I provide a brief overview and an example in support of such an approach.

Proneural genes in neocortical development

Neurons, astrocytes and oligodendrocytes arise from CNS progenitor cells at defined times and locations during development, with transcription factors serving as key determinants of these different neural cell fates. An emerging theme is that the transcription factors that specify CNS cell fates function in a context-dependent manner, regulated by post-translational modifications and epigenetic alterations that partition the genome (and hence target genes) into active or silent domains. Here we profile the critical roles of the proneural genes, which encode basic-helix-loop-helix (bHLH) transcription factors, in specifying neural cell identities in the developing neocortex. In particular, we focus on the proneural genes Neurogenin 1 (Neurog1), Neurog2 and Achaete scute-like 1 (Ascl1), which are each expressed in a distinct fashion in the progenitor cell pools that give rise to all of the neuronal and glial cell types of the mature neocortex. Notably, while the basic functions of these proneural genes have been elucidated, it is becoming increasingly evident that tight regulatory controls dictate when, where and how they function. Current efforts to better understand how proneural gene function is regulated will not only improve our understanding of neocortical development, but are also critical to the future development of regenerative therapies for the treatment of neuronal degeneration or disease.

The involvement of Reelin in neurodevelopmental disorders

Reelin is a glycoprotein that serves important roles both during development (regulation of neuronal migration and brain lamination) and in adulthood (maintenance of synaptic function). A number of neuropsychiatric disorders including autism, schizophrenia, bipolar disorder, major depression, Alzheimer's disease and lissencephaly share a common feature of abnormal Reelin expression in the brain. Altered Reelin expression has been hypothesized to impair neuronal connectivity and synaptic plasticity, leading ultimately to the cognitive deficits present in these disorders. The mechanisms for abnormal Reelin expression in some of these disorders are currently unknown although possible explanations include early developmental insults, mutations, hypermethylation of the promoter for the Reelin gene (RELN), miRNA silencing of Reelin mRNA, FMRP underexpression and Reelin processing abnormalities. Increasing Reelin expression through pharmacological therapies may help ameliorate symptoms resulting from Reelin deficits. This article is part of the Special Issue entitled 'Neurodevelopmental Disorders'.

Gene expression alterations in bipolar disorder postmortem brains

OBJECTIVES

  Bipolar disorder (BD) is a mental illness of unknown neuropathology and has several genetic associations. Antipsychotics are effective for the treatment of acute mania, psychosis, or mixed states in individuals with BD. We aimed to identify gene transcripts differentially expressed in postmortem brains from antipsychotics-exposed individuals with BD (hereafter the 'exposed' group), non-exposed individuals with BD (hereafter the 'non-exposed' group), and controls.

METHODS

  We quantified the abundance of gene transcripts in postmortem brains from seven exposed individuals, seven non-exposed individuals, and 12 controls with the Affymetrix U133P2 GeneChip microarrays and technologies. We applied a q-value of ≤0.005 to identify statistically significant transcripts with mean abundance differences between the exposed, non-exposed and control groups.

RESULTS

  We identified 2191 unique genes with significantly altered expression levels in non-exposed brains compared to those in the control and exposed groups. The expression levels of these genes were not significantly different between exposed brains and controls, suggesting a normalization effect of antipsychotics on the expression of these genes. Gene ontology (GO) enrichment analysis showed significant (Bonferroni p ≤ 0.05) clustering of subgroups of the 2191 genes under many GO terms; notably, the protein products of genes enriched are critical to the function of synapses, affecting, for example, intracellular trafficking and synaptic vesicle biogenesis, transport, release and recycling, as well as organization and stabilization of the node of Ranvier.

CONCLUSIONS

  These results support a hypothesis of synaptic and intercellular communication impairment in BD. The apparent normalization of expression patterns with exposure to antipsychotic medication may represent a physiological process that relates both to etiology and improvement patterns of the disorder.

GABBR1 has a HERV-W LTR in its regulatory region--a possible implication for schizophrenia

Schizophrenia is a complex disease with uncertain aetiology. We suggest GABBR1, GABA receptor B1 implicated in schizophrenia based on a HERV-W LTR in the regulatory region of GABBR1. Our hypothesis is supported by: (i) GABBR1 is in the 6p22 genomic region most often implicated in schizophrenia; (ii) microarray studies found that only presynaptic pathway-related genes, including GABA receptors, have altered expression in schizophrenic patients and (iii) it explains how HERV-W elements, expressed in schizophrenia, play a role in the disease: by altering the expression of GABBR1 via a long terminal repeat that is also a regulatory element to GABBR1.

Systems biology, bioinformatics, and biomarkers in neuropsychiatry

Although neuropsychiatric (NP) disorders are among the top causes of disability worldwide with enormous financial costs, they can still be viewed as part of the most complex disorders that are of unknown etiology and incomprehensible pathophysiology. The complexity of NP disorders arises from their etiologic heterogeneity and the concurrent influence of environmental and genetic factors. In addition, the absence of rigid boundaries between the normal and diseased state, the remarkable overlap of symptoms among conditions, the high inter-individual and inter-population variations, and the absence of discriminative molecular and/or imaging biomarkers for these diseases makes difficult an accurate diagnosis. Along with the complexity of NP disorders, the practice of psychiatry suffers from a "top-down" method that relied on symptom checklists. Although checklist diagnoses cost less in terms of time and money, they are less accurate than a comprehensive assessment. Thus, reliable and objective diagnostic tools such as biomarkers are needed that can detect and discriminate among NP disorders. The real promise in understanding the pathophysiology of NP disorders lies in bringing back psychiatry to its biological basis in a systemic approach which is needed given the NP disorders' complexity to understand their normal functioning and response to perturbation. This approach is implemented in the systems biology discipline that enables the discovery of disease-specific NP biomarkers for diagnosis and therapeutics. Systems biology involves the use of sophisticated computer software "omics"-based discovery tools and advanced performance computational techniques in order to understand the behavior of biological systems and identify diagnostic and prognostic biomarkers specific for NP disorders together with new targets of therapeutics. In this review, we try to shed light on the need of systems biology, bioinformatics, and biomarkers in neuropsychiatry, and illustrate how the knowledge gained through these methodologies can be translated into clinical use providing clinicians with improved ability to diagnose, manage, and treat NP patients.

Impact on intracortical myelination trajectory of long acting injection versus oral risperidone in first-episode schizophrenia

CONTEXT

Imaging and post-mortem studies suggest that frontal lobe intracortical myelination is dysregulated in schizophrenia (SZ). Prior MRI studies suggested that early in the treatment of SZ, antipsychotic medications initially increase frontal lobe intracortical myelin (ICM) volume, which subsequently declines prematurely in chronic stages of the disease. Insofar as the trajectory of ICM decline in chronic SZ is due to medication non-adherence or pharmacokinetics, it may be modifiable by long acting injection (LAI) formulations.

OBJECTIVES

Assess the effect of risperidone formulation on the ICM trajectory during a six-month randomized trial of LAI (RLAI) versus oral (RisO) in first-episode SZ subjects.

DESIGN

Two groups of SZ subjects (RLAI, N=9; and RisO, N=13) matched on pre-randomization oral medication exposure were prospectively examined at baseline and 6 months later, along with 12 healthy controls (HCs). Frontal lobe ICM volume was assessed using inversion recovery (IR) and proton density (PD) MRI images. Medication adherence was tracked.

MAIN OUTCOME MEASURE

ICM volume change scores were adjusted for the change in the HCs.

RESULTS

ICM volume increased significantly (p=.005) in RLAI and non-significantly (p=.39) in the RisO groups compared with that of the healthy controls. A differential between-group treatment effect was at a trend level (p=.093). SZ subjects receiving RLAI had better medication adherence and more ICM increases (chi-square p<.05).

CONCLUSIONS

The results suggest that RLAI may promote ICM development in first-episode SZ patients. Better adherence and/or pharmacokinetics provided by LAI may modify the ICM trajectory. In vivo MRI myelination measures can help clarify pharmacotherapeutic mechanisms of action.

A gene expression and systems pathway analysis of the effects of clozapine compared to haloperidol in the mouse brain implicates susceptibility genes for schizophrenia

Clozapine has markedly superior clinical properties compared to other antipsychotic drugs but the side effects of agranulocytosis, weight gain and diabetes limit its use. The reason why clozapine is more effective is not well understood. We studied messenger RNA (mRNA) gene expression in the mouse brain to identify pathways changed by clozapine compared to those changed by haloperidol so that we could identify which changes were specific to clozapine. Data interpretation was performed using an over-representation analysis (ORA) of gene ontology (GO), pathways and gene-by-gene differences. Clozapine significantly changed gene expression in pathways related to neuronal growth and differentiation to a greater extent than haloperidol; including the microtubule-associated protein kinase (MAPK) signalling and GO terms related to axonogenesis and neuroblast proliferation. Several genes implicated genetically or functionally in schizophrenia such as frizzled homolog 3 (FZD3), U2AF homology motif kinase 1 (UHMK1), pericentriolar material 1 (PCM1) and brain-derived neurotrophic factor (BDNF) were changed by clozapine but not by haloperidol. Furthermore, when compared to untreated controls clozapine specifically regulated transcripts related to the glutamate system, microtubule function, presynaptic proteins and pathways associated with synaptic transmission such as clathrin cage assembly. Compared to untreated controls haloperidol modulated expression of neurotoxic and apoptotic responses such as NF-kappa B and caspase pathways, whilst clozapine did not. Pathways involving lipid and carbohydrate metabolism and appetite regulation were also more affected by clozapine than by haloperidol.

Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction

We have used a translational convergent functional genomics (CFG) approach to identify and prioritize genes involved in schizophrenia, by gene-level integration of genome-wide association study data with other genetic and gene expression studies in humans and animal models. Using this polyevidence scoring and pathway analyses, we identify top genes (DISC1, TCF4, MBP, MOBP, NCAM1, NRCAM, NDUFV2, RAB18, as well as ADCYAP1, BDNF, CNR1, COMT, DRD2, DTNBP1, GAD1, GRIA1, GRIN2B, HTR2A, NRG1, RELN, SNAP-25, TNIK), brain development, myelination, cell adhesion, glutamate receptor signaling, G-protein-coupled receptor signaling and cAMP-mediated signaling as key to pathophysiology and as targets for therapeutic intervention. Overall, the data are consistent with a model of disrupted connectivity in schizophrenia, resulting from the effects of neurodevelopmental environmental stress on a background of genetic vulnerability. In addition, we show how the top candidate genes identified by CFG can be used to generate a genetic risk prediction score (GRPS) to aid schizophrenia diagnostics, with predictive ability in independent cohorts. The GRPS also differentiates classic age of onset schizophrenia from early onset and late-onset disease. We also show, in three independent cohorts, two European American and one African American, increasing overlap, reproducibility and consistency of findings from single-nucleotide polymorphisms to genes, then genes prioritized by CFG, and ultimately at the level of biological pathways and mechanisms. Finally, we compared our top candidate genes for schizophrenia from this analysis with top candidate genes for bipolar disorder and anxiety disorders from previous CFG analyses conducted by us, as well as findings from the fields of autism and Alzheimer. Overall, our work maps the genomic and biological landscape for schizophrenia, providing leads towards a better understanding of illness, diagnostics and therapeutics. It also reveals the significant genetic overlap with other major psychiatric disorder domains, suggesting the need for improved nosology.

Animal models of prenatal immune challenge and their contribution to the study of schizophrenia: a systematic review

Prenatal immune challenge (PIC) in pregnant rodents produces offspring with abnormalities in behavior, histology, and gene expression that are reminiscent of schizophrenia and autism. Based on this, the goal of this article was to review the main contributions of PIC models, especially the one using the viral-mimetic particle polyriboinosinic-polyribocytidylic acid (poly-I:C), to the understanding of the etiology, biological basis and treatment of schizophrenia. This systematic review consisted of a search of available web databases (PubMed, SciELO, LILACS, PsycINFO, and ISI Web of Knowledge) for original studies published in the last 10 years (May 2001 to October 2011) concerning animal models of PIC, focusing on those using poly-I:C. The results showed that the PIC model with poly-I:C is able to mimic the prodrome and both the positive and negative/cognitive dimensions of schizophrenia, depending on the specific gestation time window of the immune challenge. The model resembles the neurobiology and etiology of schizophrenia and has good predictive value. In conclusion, this model is a robust tool for the identification of novel molecular targets during prenatal life, adolescence and adulthood that might contribute to the development of preventive and/or treatment strategies (targeting specific symptoms, i.e., positive or negative/cognitive) for this devastating mental disorder, also presenting biosafety as compared to viral infection models. One limitation of this model is the incapacity to model the full spectrum of immune responses normally induced by viral exposure.

Schizophrenia susceptibility alleles are enriched for alleles that affect gene expression in adult human brain

It is widely thought that alleles that influence susceptibility to common diseases, including schizophrenia, will frequently do so through effects on gene expression. As only a small proportion of the genetic variance for schizophrenia has been attributed to specific loci, this remains an unproven hypothesis. The International Schizophrenia Consortium (ISC) recently reported a substantial polygenic contribution to that disorder, and that schizophrenia risk alleles are enriched among single-nucleotide polymorphisms (SNPs) selected for marginal evidence for association (P<0.5) from genome-wide association studies (GWAS). It follows that if schizophrenia susceptibility alleles are enriched for those that affect gene expression, those marginally associated SNPs, which are also expression quantitative trait loci (eQTLs), should carry more true association signals compared with SNPs that are not marginally associated. To test this, we identified marginally associated (P<0.5) SNPs from two of the largest available schizophrenia GWAS data sets. We assigned eQTL status to those SNPs based upon an eQTL data set derived from adult human brain. Using the polygenic score method of analysis reported by the ISC, we observed and replicated the observation that higher probability cis-eQTLs predicted schizophrenia better than those with a lower probability for being a cis-eQTL. Our data support the hypothesis that alleles conferring risk of schizophrenia are enriched among those that affect gene expression. Moreover, our data show that notwithstanding the likely developmental origin of schizophrenia, studies of adult brain tissue can, in principle, allow relevant susceptibility eQTLs to be identified.