A combined analysis of microarray gene expression studies of the human prefrontal cortex identifies genes implicated in schizophrenia

MicroRNAs as potential biomarkers for diagnosis of schizophrenia and influence of antipsychotic treatment

ABSTRACT

Characterized by positive symptoms (such as changes in behavior or thoughts, including delusions and hallucinations), negative symptoms (such as apathy, anhedonia, and social withdrawal), and cognitive impairments, schizophrenia is a chronic, severe, and disabling mental disorder with late adolescence or early adulthood onset. Antipsychotics are the most commonly used drugs to treat schizophrenia, but those currently in use do not fully reverse all three types of symptoms characterizing this condition. Schizophrenia is frequently misdiagnosed, resulting in a delay of or inappropriate treatment. Abnormal expression of microRNAs is connected to brain development and disease and could provide novel biomarkers for the diagnosis and prognosis of schizophrenia. The recent studies reviewed included microRNA profiling in blood- and urine-based materials and nervous tissue materials. From the studies that had validated the preliminary findings, potential candidate biomarkers for schizophrenia in adults could be miR-22-3p, -30e-5p, -92a-3p, -148b-5p, -181a-3p, -181a-5p, -181b-5p, -199b-5p, -137 in whole blood, and miR-130b, -193a-3p in blood plasma. Antipsychotic treatment of schizophrenia patients was found to modulate the expression of certain microRNAs including miR-130b, -193a-3p, -132, -195, -30e, -432 in blood plasma. Further studies are warranted with adolescents and young adults having schizophrenia and consideration should be given to using animal models of the disorder to investigate the effect of suppressing or overexpressing specific microRNAs.

Cell type-specific gene expression dynamics during human brain maturation

The human brain undergoes protracted post-natal maturation, guided by dynamic changes in gene expression. Most studies exploring these processes have used bulk tissue analyses, which mask cell type-specific gene expression dynamics. Here, using single nucleus (sn)RNA-seq on temporal lobe tissue, including samples of African ancestry, we build a joint paediatric and adult atlas of 75 cell subtypes, which we verify with spatial transcriptomics. We explore the differences between paediatric and adult cell types, revealing the genes and pathways that change during brain maturation. Our results highlight excitatory neuron subtypes, including the LTK and FREM subtypes, that show elevated expression of genes associated with cognition and synaptic plasticity in paediatric tissue. The new resources we present here improve our understanding of the brain during its development and contribute to global efforts to build an inclusive brain cell map.

Identifying Suitable Reference Gene Candidates for Quantification of DNA Damage-Induced Cellular Responses in Human U2OS Cell Culture System

DNA repair pathways trigger robust downstream responses, making it challenging to select suitable reference genes for comparative studies. In this study, our goal was to identify the most suitable housekeeping genes to perform comparable molecular analyses for DNA damage-related studies. Choosing the most applicable reference genes is important in any kind of target gene expression-related quantitative study, since using the housekeeping genes improperly may result in false data interpretation and inaccurate conclusions. We evaluated the expressional changes of eight well-known housekeeping genes (i.e., 18S rRNA, B2M, eEF1α1, GAPDH, GUSB, HPRT1, PPIA, and TBP) following treatment with the DNA-damaging agents that are most frequently used: ultraviolet B (UVB) non-ionizing irradiation, neocarzinostatin (NCS), and actinomycin D (ActD). To reveal the significant changes in the expression of each gene and to determine which appear to be the most acceptable ones for normalization of real-time quantitative polymerase chain reaction (RT-qPCR) data, comparative and statistical algorithms (such as absolute quantification, Wilcoxon Rank Sum Test, and independent samples T-test) were conducted. Our findings clearly demonstrate that the genes commonly employed as reference candidates exhibit substantial expression variability, and therefore, careful consideration must be taken when designing the experimental setup for an accurate and reproducible normalization of RT-qPCR data. We used the U2OS cell line since it is generally accepted and used in the field of DNA repair to study DNA damage-induced cellular responses. Based on our current data in U2OS cells, we suggest using 18S rRNA, eEF1α1, GAPDH, GUSB, and HPRT1 genes for UVB-induced DNA damage-related studies. B2M, HPRT1, and TBP genes are recommended for NCS treatment, while 18S rRNA, B2M, and PPIA genes can be used as suitable internal controls in RT-qPCR experiments for ActD treatment. In summary, this is the first systematic study using a U2OS cell culture system that offers convincing evidence for housekeeping gene selection following treatment with various DNA-damaging agents. Here, we unravel an indispensable issue for performing and assessing trustworthy DNA damage-related differential gene expressional analyses, and we create a "zero set" of potential reference gene candidates.

Up-Regulation of S100 Gene Family in Brain Samples of a Subgroup of Individuals with Schizophrenia: Meta-analysis

The S100 proteins family is known to affect neuroinflammation and astrocyte activation, which have been suggested to be contributors to the pathogenesis of schizophrenia. We conducted a systematic meta-analysis of S100 genes differential expression in postmortem samples of patients with schizophrenia vs. healthy controls, following the commonly used Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Twelve microarray datasets met the inclusion criteria (overall 511 samples, 253 schizophrenia and 258 controls were analyzed). Nine out of 21 genes were significantly up-regulated or with tendency for up-regulation. A per-sample fold change analysis indicated that the S100 genes' up-regulation was concentrated in a subgroup of the patients. None of the genes have been found to be down-regulated. ANXA3, which encodes Annexin 3 protein and was associated with neuroinflammation, was up-regulated and positively correlated with the S100 genes' expression pattern. In addition, astrocytes and endothelial cell markers were significantly correlated with S100A8 expression. S100 correlation with ANXA3 and endothelial cell markers suggests that the up-regulation we detected reflects increased inflammation. However, it might also reflect astrocytes abundance or activation. The fact that S100 proteins were shown to be up-regulated in blood samples and other body fluids of patients with schizophrenia suggests a potential role as biomarkers, which might help disease subtyping, and the development of etiological treatments for immune dysregulation in schizophrenia.

VDAC genes down-regulation in brain samples of individuals with schizophrenia is revealed by a systematic meta-analysis

Mitochondrial dysfunction was shown to be involved in schizophrenia pathophysiology. Abnormal energy states can lead to alterations in neural function and thereby to the cognitive and behavioral aberrations characteristics of schizophrenia. Voltage-dependent anion-selective channels (VDAC) are located in the outer mitochondrial membrane and are involved in mitochondrial energy production. Only few studies explored VDAC genes' expression in schizophrenia, and their results were not consistent. We conducted a systematic meta-analysis of ten brain samples gene expression datasets (overall 368 samples, 179 schizophrenia, 189 controls). In addition, we conducted a meta-analysis of three blood samples datasets (overall 300 samples, 167 schizophrenia, 133 controls). Pairwise correlation analysis was conducted between the VDAC and proteasome subunit genes' expression patterns. VDAC1, VDAC2 and VDAC3 showed significant down-regulation in brain samples of patients with schizophrenia. They also showed significant positive correlations with the proteasome subunit genes' expression levels. Our findings suggest that VDAC genes might play a role in mitochondrial dysfunction in schizophrenia. VDAC1 was down-regulated also in blood samples, which suggests its potential role as a biomarker for schizophrenia. The correlation with proteasome subunits, which were previously shown to be down-regulated in a subgroup of the patients, suggests that our findings might characterize a subgroup of the patients. This direction has the potential to lead to patients' stratification and more precisely-targeted therapy and necessitates further study.

A novel multi-class classification model for schizophrenia, bipolar disorder and healthy controls using comprehensive transcriptomic data

Two common psychiatric disorders, schizophrenia (SCZ) and bipolar disorder (BP), confer lifelong disability and collectively affect 2% of the world population. Because the diagnosis of psychiatry is based only on symptoms, developing more effective methods for the diagnosis of psychiatric disorders is a major international public health priority. Furthermore, SCZ and BP overlap considerably in terms of symptoms and risk genes. Therefore, the clarity of the underlying etiology and pathology remains lacking for these two disorders. Although many studies have been conducted, a classification model with higher accuracy and consistency was found to still be necessary for accurate diagnoses of SCZ and BP. In this study, a comprehensive dataset was combined from five independent transcriptomic studies. This dataset comprised 120 patients with SCZ, 101 patients with BP, and 149 healthy subjects. The partial least squares discriminant analysis (PLS-DA) method was applied to identify the gene signature among multiple groups, and 341 differentially expressed genes (DEGs) were identified. Then, the disease relevance of these DEGs was systematically performed, including (α) the great disease relevance of the identified signature, (β) the hub genes of the protein-protein interaction network playing a key role in psychiatric disorders, and (γ) gene ontology terms and enriched pathways playing a key role in psychiatric disorders. Finally, a popular multi-class classifier, support vector machine (SVM), was applied to construct a novel multi-class classification model using the identified signature for SCZ and BP. Using the independent test sets, the classification capacity of this multi-class model was assessed, which showed this model had a strong classification ability.

Monocytic Subsets Impact Cerebral Cortex and Cognition: Differences Between Healthy Subjects and Patients With First-Episode Schizophrenia

Monocytes are a highly heterogeneous population subcategorized into classical, intermediate and nonclassical subsets. How monocytes and their subsets may shape brain structures and functions in schizophrenia remains unclear. The primary goal of this cross-sectional study was to investigate monocytic subsets and their specific signature genes in regulation of cerebral cortical thickness and cognitive functions in first-episode schizophrenia (FES) patients. Whole-blood RNA sequencing of 128 FES patients and 111 healthy controls (HCs) were conducted and monocyte-specific differentially expressed genes were further analyzed. The MATRICS Consensus Cognitive Battery (MCCB) test, cortical neuroimaging and flow cytometric staining of peripheral blood monocytic subsets were performed among the participants. Significant changes in expressions of 54 monocytic signature genes were found in patients, especially for intermediate and nonclassical monocytic subsets with the most outstanding alterations being downregulated S100 Calcium Binding Protein A (S100A) and upregulated Interferon Induced Transmembrane Protein (IFITM) family members, respectively. Meanwhile, percentage of blood nonclassical monocytes was decreased in patients. Cortical thicknesses and MCCB performance were expectantly reduced and weaker intra-relationships among monocytic signature genes and cortices, respectively, were noted in patients compared to HCs. Monocytic genes were negatively associated with both cortical thicknesses and cognition in HCs, which was interestingly weakened or even reversed in patients, with nonclassical monocytic genes showing the greatest statistical significance. This study reveals that while monocytes may have negative effects on brain structure and cognition, the ameliorated phenomenon observed in schizophrenia may reflect an (mal)adaptive change of monocytes at early stage of the disorder.

Transcriptomics and machine learning to advance schizophrenia genetics: A case-control study using post-mortem brain data

BACKGROUND AND OBJECTIVE

Alterations of the expression of a variety of genes have been reported in patients with schizophrenia (SCZ). Moreover, machine learning (ML) analysis of gene expression microarray data has shown promising preliminary results in the study of SCZ. Our objective was to evaluate the performance of ML in classifying SCZ cases and controls based on gene expression microarray data from the dorsolateral prefrontal cortex.

METHODS

We apply a state-of-the-art ML algorithm (XGBoost) to train and evaluate a classification model using 201 SCZ cases and 278 controls. We utilized 10-fold cross-validation for model selection, and a held-out testing set to evaluate the model. The performance metric utilizes to evaluate classification performance was the area under the receiver-operator characteristics curve (AUC).

RESULTS

We report an average AUC on 10-fold cross-validation of 0.76 and an AUC of 0.76 on testing data, not used during training. Analysis of the rolling balanced classification accuracy from high to low prediction confidence levels showed that the most certain subset of predictions ranged between 80-90%. The ML model utilized 182 gene expression probes. Further improvement to classification performance was observed when applying an automated ML strategy on the 182 features, which achieved an AUC of 0.79 on the same testing data. We found literature evidence linking all of the top ten ML ranked genes to SCZ. Furthermore, we leveraged information from the full set of microarray gene expressions available via univariate differential gene expression analysis. We then prioritized differentially expressed gene sets using the piano gene set analysis package. We augmented the ranking of the prioritized gene sets with genes from the complex multivariate ML model using hypergeometric tests to identify more robust gene sets. We identified two significant Gene Ontology molecular function gene sets: "oxidoreductase activity, acting on the CH-NH2 group of donors" and "integrin binding." Lastly, we present candidate treatments for SCZ based on findings from our study CONCLUSIONS: Overall, we observed above-chance performance from ML classification of SCZ cases and controls based on brain gene expression microarray data, and found that ML analysis of gene expressions could further our understanding of the pathophysiology of SCZ and help identify novel treatments.

Recent Reports on Redox Stress-Induced Mitochondrial DNA Variations, Neuroglial Interactions, and NMDA Receptor System in Pathophysiology of Schizophrenia

Schizophrenia (SZ) is a chronic psychiatric disorder affecting several people worldwide. Mitochondrial DNA (mtDNA) variations could invoke changes in the OXPHOS system, calcium buffering, and ROS production, which have significant implications for glial cell survival during SZ. Oxidative stress has been implicated in glial cells-mediated pathogenesis of SZ; the brain comparatively more prone to oxidative damage through NMDAR. A confluence of scientific evidence points to mtDNA alterations, Nrf2 signaling, dynamic alterations in dorsolateral prefrontal cortex (DLPFC), and provocation of oxidative stress that enhance pathophysiology of SZ. Furthermore, the alterations in excitatory signaling related to NMDAR signaling were particularly reported for SZ pathophysiology. Current review reported the recent evidence for the role of mtDNA variations and oxidative stress in relation to pathophysiology of SZ, NMDAR hypofunction, and glutathione deficiency. NMDAR system is influenced by redox dysregulation in oxidative stress, inflammation, and antioxidant mediators. Several studies have demonstrated the relationship of these variables on severity of pathophysiology in SZ. An extensive literature search was conducted using Medline, PubMed, PsycINFO, CINAHL PLUS, BIOSIS Preview, Google scholar, and Cochrane databases. We summarize consistent evidence pointing out a plausible model that may elucidate the crosstalk between mtDNA alterations in glial cells and redox dysregulation during oxidative stress and the perturbation of NMDA neurotransmitter system during current therapeutic modalities for the SZ treatment. This review can be beneficial for the development of promising novel diagnostics, and therapeutic modalities by ascertaining the mtDNA variations, redox state, and efficacy of pharmacological agents to mitigate redox dysregulation and augment NMDAR function to treat cognitive and behavioral symptoms in SZ.

Identification of key long non-coding RNA-associated competing endogenous RNA axes in Brodmann Area 10 brain region of schizophrenia patients

Schizophrenia (SCZ) is a serious mental condition with an unknown cause. According to the reports, Brodmann Area 10 (BA10) is linked to the pathology and cortical dysfunction of SCZ, which demonstrates a number of replicated findings related to research on SCZ and the dysfunction in tasks requiring cognitive control in particular. Genetics' role in the pathophysiology of SCZ is still unclear. Therefore, it may be helpful to understand the effects of these changes on the onset and progression of SCZ to find novel mechanisms involved in the regulation of gene transcription. In order to determine the molecular regulatory mechanisms affecting the SCZ, the long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) axes in the BA10 area were determined using a bioinformatics approach in the present work. A microarray dataset (GSE17612) consisted of brain post-mortem tissues of the BA10 area from SCZ patients and matched healthy subjects was downloaded from the Gene Expression Omnibus (GEO) database. This dataset included probes for both lncRNAs and mRNAs. Using the R software's limma package, the differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) were found. The RNA interactions were also discovered using the DIANA-LncBase and miRTarBase databases. In the ceRNA network, positive correlations between DEmRNAs and DElncRNAs were evaluated using the Pearson correlation coefficient. Finally, lncRNA-associated ceRNA axes were built by using the co-expression and DElncRNA-miRNA-DEmRNA connections. We identified the DElncRNA-miRNA-DEmRNA axes, which included two key lncRNAs (PEG3-AS1, MIR570HG), seven key miRNAs (hsa-miR-124-3p, hsa-miR-17-5p, hsa-miR-181a-5p, hsa-miR-191-5p, hsa-miR-26a-5p, hsa-miR-29a-3p, hsa-miR-29b-3p), and eight key mRNAs (EGR1, ETV1, DUSP6, PLOD2, CD93, SERPINB9, ANGPTL4, TGFB2). Furthermore, DEmRNAs were found to be enriched in the "AGE-RAGE signaling pathway in diabetic complications", "Amoebiasis", "Transcriptional misregulation in cancer", "Human T-cell leukemia virus 1 infection", and "MAPK signaling pathway". This study offers research targets for examining significant molecular pathways connected to the pathogenesis of SCZ, even though the function of these ceRNA axes still needs to be investigated.

DNA Methylation and Schizophrenia: Current Literature and Future Perspective

Schizophrenia is a neuropsychiatric disorder characterized by dissociation of thoughts, idea, identity, and emotions. It has no central pathophysiological mechanism and precise diagnostic markers. Despite its high heritability, there are also environmental factors implicated in the development of schizophrenia. Epigenetic factors are thought to mediate the effects of environmental factors in the development of the disorder. Epigenetic modifications like DNA methylation are a risk factor for schizophrenia. Targeted gene approach studies attempted to find candidate gene methylation, but the results are contradictory. Genome-wide methylation studies are insufficient in literature and the available data do not cover different populations like the African populations. The current genome-wide studies have limitations related to the sample and methods used. Studies are required to control for these limitations. Integration of DNA methylation, gene expression, and their effects are important in the understanding of the development of schizophrenia and search for biomarkers. There are currently no precise and functional biomarkers for the disorder. Several epigenetic markers have been reported to be common in functional and peripheral tissue. This makes the peripheral tissue epigenetic changes a surrogate of functional tissue, suggesting common epigenetic alteration can be used as biomarkers of schizophrenia in peripheral tissue.

A combination of three plasma bile acids as a putative biomarker for schizophrenia

The aim of the present study is to determine whether plasma bile acids (BAs) could be used as an auxiliary diagnostic biomarker to distinguish patients with schizophrenia from healthy controls. Seventeen different BAs were quantitatively measured in plasma of 12 healthy participants and 12 patients with schizophrenia. Then, the data were subjected to correlation and linear discriminant analysis (LDA). The concentrations of cholic acid (CA), taurochenodeoxycholic acid (TCDCA) and taurodeoxycholic acid (TDCA) were significantly decreased in plasma of the schizophrenia patients. Correlation analysis showed the concentrations of CA, TCDCA and TDCA were negatively correlated with schizophrenia. In addition, LDA demonstrated that combination of CA, TCDCA and TDCA with a classification formula could predict correctly classified cases and the accuracy of prediction was up to 95.83%. Combination of the three BAs may be useful to diagnose schizophrenia in plasma samples.

Overexpression of complement component C4 in the dorsolateral prefrontal cortex, parietal cortex, superior temporal gyrus and associative striatum of patients with schizophrenia

BACKGROUND

In schizophrenia, abnormal synaptic pruning during adolescence may be due to altered expression of the Complement component 4 (C4). Overexpression of C4 genes has been identified in the total cerebral cortex and in 6 different brain regions of schizophrenic patients compared to controls. These alterations should be replicated and extended to other brain regions relevant to schizophrenia. Moreover, it remains unknown whether cerebral and peripheral C4 expression levels are related.

METHODS

We explored C4 genes expression both at the cerebral and peripheral levels. Using shinyGEO application we analyzed C4 expression from eight Gene Expression Omnibus datasets obtained from 196 schizophrenic patients and 182 control subjects. First, we compared C4 expression between schizophrenic patients and controls in postmortem cerebral samples from 7 different brain regions. Then, we compared C4 expression between schizophrenic patients and controls in 4 peripheral tissues.

RESULTS

At the cerebral level, we provide further evidence of C4 overexpression in schizophrenic patients. Consistently with a previous report, we found C4 overexpression in the dorsolateral prefrontal cortex and in the parietal cortex of schizophrenic patients. The observation of C4 overexpression was further extended to the superior temporal cortex and the associative striatum of schizophrenic patients. Conversely, no significant alteration of C4 expression was observed in peripheral tissues.

CONCLUSIONS

Our results support the hypothesis of an excessive Complement activity in various brain regions of schizophrenic patients which may disrupt the synaptic pruning process occurring during adolescence. C4 overexpression may be specific to the cerebral tissue while other alterations of the Complement system may be detected at the systemic level.

Early Growth Response Gene Upregulation in Epstein-Barr Virus (EBV)-Associated Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic multisystem disease exhibiting a variety of symptoms and affecting multiple systems. Psychological stress and virus infection are important. Virus infection may trigger the onset, and psychological stress may reactivate latent viruses, for example, Epstein-Barr virus (EBV). It has recently been reported that EBV induced gene 2 (EBI2) was upregulated in blood in a subset of ME/CFS patients. The purpose of this study was to determine whether the pattern of expression of early growth response (EGR) genes, important in EBV infection and which have also been found to be upregulated in blood of ME/CFS patients, paralleled that of EBI2. EGR gene upregulation was found to be closely associated with that of EBI2 in ME/CFS, providing further evidence in support of ongoing EBV reactivation in a subset of ME/CFS patients. EGR1, EGR2, and EGR3 are part of the cellular immediate early gene response and are important in EBV transcription, reactivation, and B lymphocyte transformation. EGR1 is a regulator of immune function, and is important in vascular homeostasis, psychological stress, connective tissue disease, mitochondrial function, all of which are relevant to ME/CFS. EGR2 and EGR3 are negative regulators of T lymphocytes and are important in systemic autoimmunity.

Gene expression meta-analysis reveals the up-regulation of CREB1 and CREBBP in Brodmann Area 10 of patients with schizophrenia

Cognitive impairments characterize individuals with schizophrenia, and are correlated to the patients' functional outcome. The transcription factor Cyclic AMP-responsive element-binding protein-1 (CREB1) is involved in learning and memory processes. CREB1 and both CREB-binding protein (CREBBP) and E1A Binding Protein P300 (EP300), co-activators of CREB1, have been associated with schizophrenia. We performed a systematic meta-analysis of CREB1, CREBBP and EP300 differential expression in post mortem Brodmann Area 10 (BA10) samples of patients with schizophrenia vs. healthy controls, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Two microarray datasets met the inclusion criteria (overall 41 schizophrenia samples and 38 controls were analyzed). We detect up-regulation of CREB1 and CREBBP in BA10 samples of patients with schizophrenia, while EP300 wasn't differentially expressed. The integration of two independent datasets and the positive correlation between the expression patterns of CREB1 and CREBBP increase the validity of the results. The up-regulation of CREB1 and its co-activator CREBBP might relate to BA10 altered activation that has been shown in schizophrenia. As BA10 was shown to be involved in the cognitive impairments associated with schizophrenia, this suggests involvement of CREB1 and CREBBP in the cognitive symptoms that characterize the disease.

Gene expression and response prediction to amisulpride in the OPTiMiSE first episode psychoses

A fundamental shortcoming in the current treatment of schizophrenia is the lack of valid criteria to predict who will respond to antipsychotic treatment. The identification of blood-based biological markers of the therapeutic response would enable clinicians to identify the subgroup of patients in whom conventional antipsychotic treatment is ineffective and offer alternative treatments. As part of the Optimisation of Treatment and Management of Schizophrenia in Europe (OPTiMiSE) programme, we conducted an RNA-Seq analysis on 188 subjects with first episode psychosis, all of whom were subsequently treated with amisulpride for 4 weeks. We compared gene expression on total RNA from patients' blood before and after treatment and identified 32 genes for which the expression changed after treatment in good responders only. These findings were replicated in an independent sample of 24 patients with first episode psychosis. Six genes showed a significant difference in expression level between good and poor responders before starting treatment, allowing to predict treatment outcome with a predictive value of 93.8% when combined with clinical features. Collectively, these findings identified new mechanisms to explain symptom improvement after amisulpride medication and highlight the potential of combining gene expression profiling with clinical data to predict treatment response in first episode psychoses.

Mitogen-activated protein kinase (MAPK) signalling corresponds with distinct behavioural profiles in a rat model of maternal immune activation

Dysfunction within the mitogen-activated protein kinase (MAPK) cascade has been recognised as a pathological feature of schizophrenia, however the possible mechanistic connection to the disease phenotype remains unexplored. Using the maternal immune activation (MIA) rat model of schizophrenia, the present study investigated the involvement of prefrontal cortex (PFC) MAPK in sensorimotor gating and adaptive learning deficits via western blot, pre-pulse inhibition (PPI) testing, and a contingency degradation operant task, respectively. Principle findings identified a negative relationship between basal MAPK expression and PPI exclusively in MIA rats, suggesting a modulatory role for MAPK in sensorimotor gating pathology. In addition, the correlation between MAPK and adaptive learning capacity observed in control rats was absent for rats exposed to MIA. Findings are considered with respect to the glutamatergic NMDA hypofunction theory of schizophrenia, as well as the critical role of PFC in contingency learning.

Epigenomic Dysregulation in Schizophrenia: In Search of Disease Etiology and Biomarkers

Schizophrenia is a severe psychiatric disorder with a complex array of signs and symptoms that causes very significant disability in young people. While schizophrenia has a strong genetic component, with heritability around 80%, there is also a very significant range of environmental exposures and stressors that have been implicated in disease development and neuropathology, such as maternal immune infection, obstetric complications, childhood trauma and cannabis exposure. It is postulated that epigenetic factors, as well as regulatory non-coding RNAs, mediate the effects of these environmental stressors. In this review, we explore the most well-known epigenetic marks, including DNA methylation and histone modification, along with emerging RNA mediators of epigenomic state, including miRNAs and lncRNAs, and discuss their collective potential for involvement in the pathophysiology of schizophrenia implicated through the postmortem analysis of brain tissue. Given that peripheral tissues, such as blood, saliva, and olfactory epithelium have the same genetic composition and are exposed to many of the same environmental exposures, we also examine some studies supporting the application of peripheral tissues for epigenomic biomarker discovery in schizophrenia. Finally, we provide some perspective on how these biomarkers may be utilized to capture a signature of past events that informs future treatment.

Peripheral Blood Leukocyte RNA-Seq Identifies a Set of Genes Related to Abnormal Psychomotor Behavior Characteristics in Patients with Schizophrenia

BACKGROUND Schizophrenia is a multigene disease with a complex etiology and different clinical manifestations. It is of great significance to understand the etiology and pathogenesis of schizophrenia patients from different clinical dimensions and to interpret the potential molecular changes of schizophrenia patients from different clinical dimensions. MATERIAL AND METHODS RNA-Seq was performed on peripheral blood leukocytes of 50 patients with schizophrenia and 50 healthy controls. Phenotypic information of patients with schizophrenia was collected during blood sampling. Differentially expressed genes (DEGs) were screened by the edgeR package of R software. To better analyze the correlation between DEG expression values, explore the potential association between differential genes and clinical dimensions of schizophrenia, and identify hub genes, we constructed a DEG co-expression network using weighted gene co-expression network analysis (WGCNA). RESULTS We provide the transcription profiles of peripheral blood leukocytes in patients with schizophrenia and found a gene module (including 89 genes) closely related to the clinical dimension of abnormal psychomotor behavior in schizophrenia. CONCLUSIONS The findings enhance our understanding of the biological processes of schizophrenia, enabling us to identify specific clinical dimensions of genes for diagnosis and prognostic markers and possibly for targeted therapy.

The complement system in schizophrenia: where are we now and what's next?

The complement system is a set of immune proteins involved in first-line defense against pathogens and removal of waste materials. Recent evidence has implicated the complement cascade in diseases involving the central nervous system, including schizophrenia. Here, we provide an up-to-date narrative review and critique of the literature on the relationship between schizophrenia and complement gene polymorphisms, gene expression, protein concentration, and pathway activity. A literature search identified 23 new studies since the first review on this topic in 2008. Overall complement pathway activity appears to be elevated in schizophrenia. Recent studies have identified complement component 4 (C4) and CUB and Sushi Multiple Domains 1 (CSMD1) as potential genetic markers of schizophrenia. In particular, there is some evidence of higher rates of C4B/C4S deficiency, reduced peripheral C4B concentration, and elevated brain C4A mRNA expression in schizophrenia patients compared to controls. To better elucidate the additive effects of multiple complement genotypes, we also conducted gene- and gene-set analysis through MAGMA which supported the role of Human Leukocyte Antigen class (HLA) III genes and, to a lesser extent, CSMD1 in schizophrenia; however, the HLA-schizophrenia association was likely driven by the C4 gene. Lastly, we identified several limitations of the literature on the complement system and schizophrenia, including: small sample sizes, inconsistent methodologies, limited measurements of neural concentrations of complement proteins, little exploration of the link between complement and schizophrenia phenotype, and lack of studies exploring schizophrenia treatment response. Overall, recent findings highlight complement components-in particular, C4 and CSMD1-as potential novel drug targets in schizophrenia. Given the growing availability of complement-targeted therapies, future clinical studies evaluating their efficacy in schizophrenia hold the potential to accelerate treatment advances.

Gene Regulatory Network of Dorsolateral Prefrontal Cortex: a Master Regulator Analysis of Major Psychiatric Disorders

Despite the strong genetic component of psychiatric disorders, traditional genetic studies have failed to find individual genes of large effect size. Thus, alternative methods, using bioinformatics, have been proposed to solve these biological puzzles. Of these, here we employ systems biology-based approaches to identify potential master regulators (MRs) of bipolar disorder (BD), schizophrenia (SZ), and major depressive disorder (MDD), their association with biological processes and their capacity to differentiate disorders' phenotypes. High-throughput gene expression data was used to reconstruct standard human dorsolateral prefrontal cortex regulatory transcriptional network, which was then queried for regulatory units and MRs associated with the psychiatric disorders of interest. Furthermore, the activity status (active or repressed) of MR candidates was obtained and used in cluster analysis to characterize disease phenotypes. Finally, we explored the biological processes modulated by the MRs using functional enrichment analysis. Thirty-one, thirty-four, and fifteen MR candidates were identified in BD, SZ, and MDD, respectively. The activity state of these MRs grouped the illnesses in three clusters: MDD only, mostly BD, and a third one with BD and SZ. While BD and SZ share several biological processes related to ion transport and homeostasis, synapse, and immune function, SZ showed peculiar enrichment of processes related to cytoskeleton and neuronal structure. Meanwhile, MDD presented mostly processes related to glial development and fatty acid metabolism. Our findings suggest notable differences in functional enrichment between MDD and BD/SZ. Furthermore, similarities between BD and SZ may impose particular challenges in attempts to discriminate these pathologies based solely on their transcriptional profiles. Nevertheless, we believe that systems-oriented approaches are promising strategies to unravel the pathophysiology peculiarities underlying mental illnesses and reveal therapeutic targets.

Developmental abnormalities in cortical GABAergic system in mice lacking mGlu3 metabotropic glutamate receptors

Polymorphic variants of the gene encoding for metabotropic glutamate receptor 3 (mGlu3) are linked to schizophrenia. Because abnormalities of cortical GABAergic interneurons lie at the core of the pathophysiology of schizophrenia, we examined whether mGlu3 receptors influence the developmental trajectory of cortical GABAergic transmission in the postnatal life. mGlu3^-/- mice showed robust changes in the expression of interneuron-related genes in the prefrontal cortex (PFC), including large reductions in the expression of parvalbumin (PV) and the GluN1 subunit of NMDA receptors. The number of cortical cells enwrapped by perineuronal nets was increased in mGlu3^-/- mice, suggesting that mGlu3 receptors shape the temporal window of plasticity of PV⁺ interneurons. Electrophysiological measurements of GABA_A receptor-mediated responses revealed a more depolarized reversal potential of GABA currents in the somata of PFC pyramidal neurons in mGlu3^-/- mice at postnatal d 9 associated with a reduced expression of the K⁺/Cl^- symporter. Finally, adult mGlu3^-/- mice showed lower power in electroencephalographic rhythms at 1-45 Hz in quiet wakefulness as compared with their wild-type counterparts. These findings suggest that mGlu3 receptors have a strong impact on the development of cortical GABAergic transmission and cortical neural synchronization mechanisms corroborating the concept that genetic variants of mGlu3 receptors may predispose to psychiatric disorders.-Imbriglio, T., Verhaeghe, R., Martinello, K., Pascarelli, M. T., Chece, G., Bucci, D., Notartomaso, S., Quattromani, M., Mascio, G., Scalabrì, F., Simeone, A., Maccari, S., Del Percio, C., Wieloch, T., Fucile, S., Babiloni, C., Battaglia, G., Limatola, C., Nicoletti, F., Cannella, M. Developmental abnormalities in cortical GABAergic system in mice lacking mGlu3 metabotropic glutamate receptors.

Identification of the gene signature reflecting schizophrenia's etiology by constructing artificial intelligence-based method of enhanced reproducibility

Aims

As one of the most fundamental questions in modern science, “what causes schizophrenia (SZ)” remains a profound mystery due to the absence of objective gene markers. The reproducibility of the gene signatures identified by independent studies is found to be extremely low due to the incapability of available feature selection methods and the lack of measurement on validating signatures’ robustness. These irreproducible results have significantly limited our understanding of the etiology of SZ.

Methods

In this study, a new feature selection strategy was developed, and a comprehensive analysis was then conducted to ensure a reliable signature discovery. Particularly, the new strategy (a) combined multiple randomized sampling with consensus scoring and (b) assessed gene ranking consistency among different datasets, and a comprehensive analysis among nine independent studies was conducted.

Results

Based on a first‐ever evaluation of methods’ reproducibility that was cross‐validated by nine independent studies, the newly developed strategy was found to be superior to the traditional ones. As a result, 33 genes were consistently identified from multiple datasets by the new strategy as differentially expressed, which might facilitate our understanding of the mechanism underlying the etiology of SZ.

Conclusion

A new strategy capable of enhancing the reproducibility of feature selection in current SZ research was successfully constructed and validated. A group of candidate genes identified in this study should be considered as great potential for revealing the etiology of SZ.

Consistent gene signature of schizophrenia identified by a novel feature selection strategy from comprehensive sets of transcriptomic data

The etiology of schizophrenia (SCZ) is regarded as one of the most fundamental puzzles in current medical research, and its diagnosis is limited by the lack of objective molecular criteria. Although plenty of studies were conducted, SCZ gene signatures identified by these independent studies are found highly inconsistent. As one of the most important factors contributing to this inconsistency, the feature selection methods used currently do not fully consider the reproducibility among the signatures discovered from different datasets. Therefore, it is crucial to develop new bioinformatics tools of novel strategy for ensuring a stable discovery of gene signature for SCZ. In this study, a novel feature selection strategy (1) integrating repeated random sampling with consensus scoring and (2) evaluating the consistency of gene rank among different datasets was constructed. By systematically assessing the identified SCZ signature comprising 135 differentially expressed genes, this newly constructed strategy demonstrated significantly enhanced stability and better differentiating ability compared with the feature selection methods popular in current SCZ research. Based on a first-ever assessment on methods’ reproducibility cross-validated by independent datasets from three representative studies, the new strategy stood out among the popular methods by showing superior stability and differentiating ability. Finally, 2 novel and 17 previously reported transcription factors were identified and showed great potential in revealing the etiology of SCZ. In sum, the SCZ signature identified in this study would provide valuable clues for discovering diagnostic molecules and potential targets for SCZ.

DLPFC transcriptome defines two molecular subtypes of schizophrenia

Little is known about the molecular pathogenesis of schizophrenia, possibly because of unrecognized heterogeneity in diagnosed patient populations. We analyzed gene expression data collected from the dorsolateral prefrontal cortex (DLPFC) of post-mortem frozen brains of 189 adult diagnosed schizophrenics and 206 matched controls. Transcripts from 633 genes are differentially expressed in the DLPFC of schizophrenics as compared to controls at Bonferroni-corrected significance levels. Seventeen of those genes are differentially expressed at very high significance levels (<10-8 after Bonferroni correction). The findings were closely replicated in a dataset from an entirely unrelated source. The statistical significance of this differential gene expression is being driven by about half of the schizophrenic DLPFC samples, and importantly, it is the same half of the samples that is driving the significance for almost all of the differentially expressed transcripts. Weighted gene co-expression network analysis (WGCNA) of the schizophrenic subjects, based on the transcripts differentially expressed in the schizophrenics as compared to controls, divides them into two groups. "Type 1" schizophrenics have a DLPFC transcriptome similar to that of controls with only four differentially expressed genes identified. "Type 2" schizophrenics have a DLPFC transcriptome dramatically different from that of controls, with 3529 expression array probes to 3092 genes detecting transcripts that are differentially expressed at very high significance levels. These findings were re-tested and replicated in a separate independent cohort, using the RNAseq data from the DLPFC of an independent set of schizophrenics and control subjects. We suggest the hypothesis that these striking differences in DLPFC transcriptomes, identified and replicated in two populations, imply a fundamental biologic difference between these two groups of diagnosed schizophrenics, and we propose specific paths for further testing and expanding the hypothesis.

Functional analyses and effect of DNA methylation on the EGR1 gene in patients with schizophrenia

EGR1, involved in the regulation of synaptic plasticity, learning, and memory, is considered a candidate gene for schizophrenia. We resequenced the exonic regions of EGR1 in 516 patients with schizophrenia and conducted a reporter gene assay. We found two mutations including a rare mutation (c.-8C>T, rs561524195) and one common SNP (c.308-42C>T, rs11743810). The reporter gene assay showed c.-8C>T mutant did not affect promoter activity. Gene expression analyses showed that the average EGR1 mRNA and protein levels in lymphoblastoid cell lines of schizophrenia in male, but not female, were significantly higher than those in controls. We conducted in vitro DNA methylation reaction, luciferase activity assay, and pyrosequencing to assess DNA methylation of EGR1 expression underlying the pathophysiology of schizophrenia. DNA methylation of the EGR1 promoter region attenuated reporter activity, suggesting that DNA methylation regulates EGR1 expression. There were no statistically significant differences in DNA methylation levels of 17 CpG sites at the EGR1 promoter region between 64 patients with schizophrenia compared with 64 controls. These results suggest that the exonic mutations in EGR1 and DNA methylation regulating EGR1 expression might not be associated with schizophrenia. However, the gender-specific association of elevated EGR1 expression might be involved in the pathophysiology of schizophrenia.

Transcriptome alterations of prefrontal cortical parvalbumin neurons in schizophrenia

Schizophrenia (SZ) is associated with dysfunction of the dorsolateral prefrontal cortex (DLPFC). This dysfunction is manifest as cognitive deficits that appear to arise from disturbances in gamma frequency oscillations. These oscillations are generated in DLPFC layer 3 (L3) via reciprocal connections between pyramidal cells (PCs) and parvalbumin (PV)-containing interneurons. The density of cortical PV neurons is not altered in SZ, but expression levels of several transcripts involved in PV cell function, including PV, are lower in the disease. However, the transcriptome of PV cells has not been comprehensively assessed in a large cohort of subjects with SZ. In this study, we combined an immunohistochemical approach, laser microdissection, and microarray profiling to analyze the transcriptome of DLPFC L3 PV cells in 36 matched pairs of SZ and unaffected comparison subjects. Over 800 transcripts in PV neurons were identified as differentially expressed in SZ subjects; most of these alterations have not previously been reported. The altered transcripts were enriched for pathways involved in mitochondrial function and tight junction signaling. Comparison with the transcriptome of L3 PCs from the same subjects revealed both shared and distinct disease-related effects on gene expression between cell types. Furthermore, network structures of gene pathways differed across cell types and subject groups. These findings provide new insights into cell type-specific molecular alterations in SZ which may point toward novel strategies for identifying therapeutic targets.

Immediate Early Genes, Memory and Psychiatric Disorders: Focus on c-Fos, Egr1 and Arc

Many psychiatric disorders, despite their specific characteristics, share deficits in the cognitive domain including executive functions, emotional control and memory. However, memory deficits have been in many cases undervalued compared with other characteristics. The expression of Immediate Early Genes (IEGs) such as, c-fos, Egr1 and arc are selectively and promptly upregulated in learning and memory among neuronal subpopulations in regions associated with these processes. Changes in expression in these genes have been observed in recognition, working and fear related memories across the brain. Despite the enormous amount of data supporting changes in their expression during learning and memory and the importance of those cognitive processes in psychiatric conditions, there are very few studies analyzing the direct implication of the IEGs in mental illnesses. In this review, we discuss the role of some of the most relevant IEGs in relation with memory processes affected in psychiatric conditions.

Immediate Early Genes Anchor a Biological Pathway of Proteins Required for Memory Formation, Long-Term Depression and Risk for Schizophrenia

While the causes of myriad medical and infectious illnesses have been identified, the etiologies of neuropsychiatric illnesses remain elusive. This is due to two major obstacles. First, the risk for neuropsychiatric disorders, such as schizophrenia, is determined by both genetic and environmental factors. Second, numerous genes influence susceptibility for these illnesses. Genome-wide association studies have identified at least 108 genomic loci for schizophrenia, and more are expected to be published shortly. In addition, numerous biological processes contribute to the neuropathology underlying schizophrenia. These include immune dysfunction, synaptic and myelination deficits, vascular abnormalities, growth factor disruption, and N-methyl-D-aspartate receptor (NMDAR) hypofunction. However, the field of psychiatric genetics lacks a unifying model to explain how environment may interact with numerous genes to influence these various biological processes and cause schizophrenia. Here we describe a biological cascade of proteins that are activated in response to environmental stimuli such as stress, a schizophrenia risk factor. The central proteins in this pathway are critical mediators of memory formation and a particular form of hippocampal synaptic plasticity, long-term depression (LTD). Each of these proteins is also implicated in schizophrenia risk. In fact, the pathway includes four genes that map to the 108 loci associated with schizophrenia: GRIN2A, nuclear factor of activated T-cells (NFATc3), early growth response 1 (EGR1) and NGFI-A Binding Protein 2 (NAB2); each of which contains the "Index single nucleotide polymorphism (SNP)" (most SNP) at its respective locus. Environmental stimuli activate this biological pathway in neurons, resulting in induction of EGR immediate early genes: EGR1, EGR3 and NAB2. We hypothesize that dysfunction in any of the genes in this pathway disrupts the normal activation of Egrs in response to stress. This may result in insufficient electrophysiologic, immunologic, and neuroprotective, processes that these genes normally mediate. Continued adverse environmental experiences, over time, may thereby result in neuropathology that gives rise to the symptoms of schizophrenia. By combining multiple genes associated with schizophrenia susceptibility, in a functional cascade triggered by neuronal activity, the proposed biological pathway provides an explanation for both the polygenic and environmental influences that determine the complex etiology of this mental illness.

Microarray gene-expression study in fibroblast and lymphoblastoid cell lines from antipsychotic-naïve first-episode schizophrenia patients

Schizophrenia (SZ) is a chronic psychiatric disorder whose onset of symptoms occurs in late adolescence and early adulthood. The etiology is complex and involves important gene-environment interactions. Microarray gene-expression studies on SZ have identified alterations in several biological processes. The heterogeneity in the results can be attributed to the use of different sample types and other important confounding factors including age, illness chronicity and antipsychotic exposure. The aim of the present microarray study was to analyze, for the first time to our knowledge, differences in gene expression profiles in 18 fibroblast (FCLs) and 14 lymphoblastoid cell lines (LCLs) from antipsychotic-naïve first-episode schizophrenia (FES) patients and healthy controls. We used an analytical approach based on protein-protein interaction network construction and functional annotation analysis to identify the biological processes that are altered in SZ. Significant differences in the expression of 32 genes were found when LCLs were assessed. The network and gene set enrichment approach revealed the involvement of similar biological processes in FCLs and LCLs, including apoptosis and related biological terms such as cell cycle, autophagy, cytoskeleton organization and response to stress and stimulus. Metabolism and other processes, including signal transduction, kinase activity and phosphorylation, were also identified. These results were replicated in two independent cohorts using the same analytical approach. This provides more evidence for altered apoptotic processes in antipsychotic-naïve FES patients and other important biological functions such as cytoskeleton organization and metabolism. The convergent results obtained in both peripheral cell models support their usefulness for transcriptome studies on SZ.

Pattern of gene expression in different stages of schizophrenia: Down-regulation of NPTX2 gene revealed by a meta-analysis of microarray datasets

Schizophrenia (SCZ) is a severe psychiatric disorder with a genetic susceptibility. Alterations in neurochemical signaling, as well as changes in brain structure and function, manifest during the course of SCZ and are likely causative of the symptoms shown by affected individuals. However, little is known about the timing of these changes, particularly in the pre-morbid and prodromal phases of SCZ. Here, we performed a gene-based and pathway-based meta-analysis of 5 microarray datasets from human induced pluripotent stem cells (hiPSCs)-derived neurons and post-mortem brain tissue from SCZ and healthy controls (HC), with the underlying assumption they might represent the neurobiological make-up of SCZ in the pre-morbid and chronic stages of illness, respectively. Thus, we identified 1 microarray expression profiling dataset of hiPSCs-derived neurons (GSE25673) and performed a systematic search of microarray expression profiling datasets from SCZ post-mortem brain publicly available on the Gene Expression Omnibus (GEO) repository. We selected 4 different SCZ post-mortem brain microarray expression profiling datasets (GSE17612, GSE21935, GSE12649, and GSE21338) according to specific inclusion and exclusion criteria. We downloaded raw data and performed quality controls, differential expression analysis, and gene-based, as well as pathway-based meta-analysis. Neuronal pentraxin 2 (NPTX2) gene was consistently down-regulated across all datasets, with highly significant association in the meta-analysis (FDR<1.0E-04). These results highlight the heuristic value of microarray meta-analysis and suggest a role of NPTX2 as a disease biomarker, provided that it achieves biological validation in future studies examining whether this down-regulation has predictive value with respect to the developmental trajectory of SCZ.

Modeling a linkage between blood transcriptional expression and activity in brain regions to infer the phenotype of schizophrenia patients

Hundreds of genetic loci participate to schizophrenia liability. It is also known that impaired cerebral connectivity is directly related to the cognitive and affective disturbances in schizophrenia. How genetic susceptibility and brain neural networks interact to specify a pathological phenotype in schizophrenia remains elusive. Imaging genetics, highlighting brain variations, has proven effective to establish links between vulnerability loci and associated clinical traits. As previous imaging genetics works in schizophrenia have essentially focused on structural DNA variants, these findings could be blurred by epigenetic mechanisms taking place during gene expression. We explored the meaningful links between genetic data from peripheral blood tissues on one hand, and regional brain reactivity to emotion task assayed by blood oxygen level-dependent functional magnetic resonance imaging on the other hand, in schizophrenia patients and matched healthy volunteers. We applied Sparse Generalized Canonical Correlation Analysis to identify joint signals between two blocks of variables: (i) the transcriptional expression of 33 candidate genes, and (ii) the blood oxygen level-dependent activity in 16 region of interest. Results suggested that peripheral transcriptional expression is related to brain imaging variations through a sequential pathway, ending with the schizophrenia phenotype. Generalization of such an approach to larger data sets should thus help in outlining the pathways involved in psychiatric illnesses such as schizophrenia.

IMAGING

SEARCHING FOR LINKS TO AID DIAGNOSIS: Researchers explore links between the expression of genes associated with schizophrenia in blood cells and variations in brain activity during emotion processing. El Chérif Ibrahim and Eric Fakra at Aix-Marseille Université, France, and colleagues have developed a method to relate the expression levels of 33 schizophrenia susceptibility genes in blood cells and functional magnetic resonance imaging (fMRI) data obtained as individuals carry out a task that triggers emotional responses. Although they found no significant differences in the expression of genes between the 26 patients with schizophrenia and 26 healthy controls they examined, variations in activity in the superior temporal gyrus were strongly linked to schizophrenia-associated gene expression and presence of disease. Similar analyses of larger data sets will shed further light on the relationship between peripheral molecular changes and disease-related behaviors and ultimately, aid the diagnosis of neuropsychiatric disease.

Post-mortem molecular profiling of three psychiatric disorders

BACKGROUND

Psychiatric disorders are multigenic diseases with complex etiology that contribute significantly to human morbidity and mortality. Although clinically distinct, several disorders share many symptoms, suggesting common underlying molecular changes exist that may implicate important regulators of pathogenesis and provide new therapeutic targets.

METHODS

We performed RNA sequencing on tissue from the anterior cingulate cortex, dorsolateral prefrontal cortex, and nucleus accumbens from three groups of 24 patients each diagnosed with schizophrenia, bipolar disorder, or major depressive disorder, and from 24 control subjects. We identified differentially expressed genes and validated the results in an independent cohort. Anterior cingulate cortex samples were also subjected to metabolomic analysis. ChIP-seq data were used to characterize binding of the transcription factor EGR1.

RESULTS

We compared molecular signatures across the three brain regions and disorders in the transcriptomes of post-mortem human brain samples. The most significant disease-related differences were in the anterior cingulate cortex of schizophrenia samples compared to controls. Transcriptional changes were assessed in an independent cohort, revealing the transcription factor EGR1 as significantly down-regulated in both cohorts and as a potential regulator of broader transcription changes observed in schizophrenia patients. Additionally, broad down-regulation of genes specific to neurons and concordant up-regulation of genes specific to astrocytes was observed in schizophrenia and bipolar disorder patients relative to controls. Metabolomic profiling identified disruption of GABA levels in schizophrenia patients.

CONCLUSIONS

We provide a comprehensive post-mortem transcriptome profile of three psychiatric disorders across three brain regions. We highlight a high-confidence set of independently validated genes differentially expressed between schizophrenia and control patients in the anterior cingulate cortex and integrate transcriptional changes with untargeted metabolite profiling.

The Role of Early Growth Response 1 (EGR1) in Brain Plasticity and Neuropsychiatric Disorders

It is now clearly established that complex interactions between genes and environment are involved in multiple aspects of neuropsychiatric disorders, from determining an individual's vulnerability to onset, to influencing its response to therapeutic intervention. In this perspective, it appears crucial to better understand how the organism reacts to environmental stimuli and provide a coordinated and adapted response. In the central nervous system, neuronal plasticity and neurotransmission are among the major processes integrating such complex interactions between genes and environmental stimuli. In particular, immediate early genes (IEGs) are critical components of these interactions as they provide the molecular framework for a rapid and dynamic response to neuronal activity while opening the possibility for a lasting and sustained adaptation through regulation of the expression of a wide range of genes. As a result, IEGs have been tightly associated with neuronal activity as well as a variety of higher order processes within the central nervous system such as learning, memory and sensitivity to reward. The immediate early gene and transcription factor early growth response 1 (EGR1) has thus been revealed as a major mediator and regulator of synaptic plasticity and neuronal activity in both physiological and pathological conditions. In this review article, we will focus on the role of EGR1 in the central nervous system. First, we will summarize the different factors influencing its activity. Then, we will analyze the amount of data, including genome-wide, that has emerged in the recent years describing the wide variety of genes, pathways and biological functions regulated directly or indirectly by EGR1. We will thus be able to gain better insights into the mechanisms underlying EGR1's functions in physiological neuronal activity. Finally, we will discuss and illustrate the role of EGR1 in pathological states with a particular interest in cognitive functions and neuropsychiatric disorders.

Genome-wide DNA Methylation Changes in a Mouse Model of Infection-Mediated Neurodevelopmental Disorders

BACKGROUND

Prenatal exposure to infectious or inflammatory insults increases the risk of neurodevelopmental disorders. Using a well-established mouse model of prenatal viral-like immune activation, we examined whether this pathological association involves genome-wide DNA methylation differences at single nucleotide resolution.

METHODS

Prenatal immune activation was induced by maternal treatment with the viral mimetic polyriboinosinic-polyribocytidylic acid in middle or late gestation. Following behavioral and cognitive characterization of the adult offspring (n = 12 per group), unbiased capture array bisulfite sequencing was combined with subsequent matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and quantitative real-time polymerase chain reaction analyses to quantify DNA methylation changes and transcriptional abnormalities in the medial prefrontal cortex of immune-challenged and control offspring. Gene ontology term enrichment analysis was used to explore shared functional pathways of genes with differential DNA methylation.

RESULTS

Adult offspring of immune-challenged mothers displayed hyper- and hypomethylated CpGs at numerous loci and at distinct genomic regions, including genes relevant for gamma-aminobutyric acidergic differentiation and signaling (e.g., Dlx1, Lhx5, Lhx8), Wnt signaling (Wnt3, Wnt8a, Wnt7b), and neural development (e.g., Efnb3, Mid1, Nlgn1, Nrxn2). Altered DNA methylation was associated with transcriptional changes of the corresponding genes. The epigenetic and transcriptional effects were dependent on the offspring's age and were markedly influenced by the precise timing of prenatal immune activation.

CONCLUSIONS

Prenatal viral-like immune activation is capable of inducing stable DNA methylation changes in the medial prefrontal cortex. These long-term epigenetic modifications are a plausible mechanism underlying the disruption of prefrontal gene transcription and behavioral functions in subjects with prenatal infectious histories.

The early growth response protein 1-miR-30a-5p-neurogenic differentiation factor 1 axis as a novel biomarker for schizophrenia diagnosis and treatment monitoring

To date, diagnosis of schizophrenia is still based on clinical interviews and careful observations, which is subjective and variable, and can lead to misdiagnosis and/or delay in diagnosis. As early intervention in schizophrenia is important in improving outcomes, objective tests that can be used for schizophrenia diagnosis or treatment monitoring are thus in great need. MicroRNAs (miRNAs) negatively regulate target gene expression and their biogenesis is tightly controlled by various factors including transcription factors (TFs). Dysregulation of miRNAs in brain tissue and peripheral blood mononuclear cells (PBMNCs) from patients with schizophrenia has been well documented, but analysis of the sensitivity and specificity for potential diagnostic utility of these alternations is limited. In this study, we explored the TF-miRNA-30-target gene axis as a novel biomarker for schizophrenia diagnosis and treatment monitoring. Using bioinformatics analysis, we retrieved all TFs that control the biogenesis of miRNA 30 members as well as all target genes that are regulated by miRNA-30 members. Further, reverse transcription-quantitative PCR analysis revealed that the early growth response protein 1 (EGR1) and miR-30a-5p were remarkably downregulated, whereas neurogenic differentiation factor 1 (NEUROD1) was significantly upregulated in PBMNCs from patients in acute psychotic state. Antipsychotics treatment resulted in the elevation of EGR1 and miR-30a-5p but the reduction of NEUROD1. Receiver operating characteristic analysis showed that the EGR1-miR-30a-5p-NEUROD1 axis possessed significantly greater diagnostic value than miR-30a-5p alone. Our data suggest the EGR1-miR-30a-5p-NEUROD1 axis might serve as a promising biomarker for diagnosis and treatment monitoring for those patients in acute psychotic state.

Transcriptome-wide mega-analyses reveal joint dysregulation of immunologic genes and transcription regulators in brain and blood in schizophrenia

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

Bridging the Gap between Genes and Language Deficits in Schizophrenia: An Oscillopathic Approach

Schizophrenia is characterized by marked language deficits, but it is not clear how these deficits arise from the alteration of genes related to the disease. The goal of this paper is to aid the bridging of the gap between genes and schizophrenia and, ultimately, give support to the view that the abnormal presentation of language in this condition is heavily rooted in the evolutionary processes that brought about modern language. To that end we will focus on how the schizophrenic brain processes language and, particularly, on its distinctive oscillatory profile during language processing. Additionally, we will show that candidate genes for schizophrenia are overrepresented among the set of genes that are believed to be important for the evolution of the human faculty of language. These genes crucially include (and are related to) genes involved in brain rhythmicity. We will claim that this translational effort and the links we uncover may help develop an understanding of language evolution, along with the etiology of schizophrenia, its clinical/linguistic profile, and its high prevalence among modern populations.

Exploring Transcription Factors-microRNAs Co-regulation Networks in Schizophrenia

BACKGROUND

Transcriptional factors (TFs) and microRNAs (miRNAs) have been recognized as 2 classes of principal gene regulators that may be responsible for genome coexpression changes observed in schizophrenia (SZ).

METHODS

This study aims to (1) identify differentially coexpressed genes (DCGs) in 3 mRNA expression microarray datasets; (2) explore potential interactions among the DCGs, and differentially expressed miRNAs identified in our dataset composed of early-onset SZ patients and healthy controls; (3) validate expression levels of some key transcripts; and (4) explore the druggability of DCGs using the curated database.

RESULTS

We detected a differential coexpression network associated with SZ and found that 9 out of the 12 regulators were replicated in either of the 2 other datasets. Leveraging the differentially expressed miRNAs identified in our previous dataset, we constructed a miRNA-TF-gene network relevant to SZ, including an EGR1-miR-124-3p-SKIL feed-forward loop. Our real-time quantitative PCR analysis indicated the overexpression of miR-124-3p, the under expression of SKIL and EGR1 in the blood of SZ patients compared with controls, and the direction of change of miR-124-3p and SKIL mRNA levels in SZ cases were reversed after a 12-week treatment cycle. Our druggability analysis revealed that many of these genes have the potential to be drug targets.

CONCLUSIONS

Together, our results suggest that coexpression network abnormalities driven by combinatorial and interactive action from TFs and miRNAs may contribute to the development of SZ and be relevant to the clinical treatment of the disease.

Meta-analysis of sex differences in gene expression in schizophrenia

Schizophrenia is a severe psychiatric disorder which influences around 1 % of the worldwide population. Differences between male and female patients with schizophrenia have been noted. There is an earlier age of onset in males compared with females with this diagnosis, and in addition, there are differences in symptom profiles between the sexes. The underlying molecular mechanism of sex difference remains unclear. Here we present a comprehensive analysis to reveal the sex differences in gene expression in schizophrenia with stringent statistics criteria. We compiled a data set consisting of 89 male controls, 90 male schizophrenia patients, 35 female controls and 32 female schizophrenia patients from six independent studies of the prefrontal cortex (PFC) in postmortem brain. When we tested for a sex by diagnosis interaction on gene expression, 23 genes were up-regulated and 23 genes were down-regulated in the male group (q-value < 0.05), several genes are related to energy metabolism, while 4 genes are located on sex chromosome. No genes were statistically significant in the female group when multiple testing correction were conducted (q-value <0.05), most likely due to the small sample size. Our protocol and results from the male group provide a starting point for identifying the underlying different mechanism between male and female schizophrenia patients.

Distinctive transcriptome alterations of prefrontal pyramidal neurons in schizophrenia and schizoaffective disorder

Schizophrenia is associated with alterations in working memory that reflect dysfunction of dorsolateral prefrontal cortex (DLPFC) circuitry. Working memory depends on the activity of excitatory pyramidal cells in DLPFC layer 3 and, to a lesser extent, in layer 5. Although many studies have profiled gene expression in DLPFC gray matter in schizophrenia, little is known about cell-type-specific transcript expression in these two populations of pyramidal cells. We hypothesized that interrogating gene expression, specifically in DLPFC layer 3 or 5 pyramidal cells, would reveal new and/or more robust schizophrenia-associated differences that would provide new insights into the nature of pyramidal cell dysfunction in the illness. We also sought to determine the impact of other variables, such as a diagnosis of schizoaffective disorder or medication use at the time of death, on the patterns of gene expression in pyramidal neurons. Individual pyramidal cells in DLPFC layers 3 or 5 were captured by laser microdissection from 36 subjects with schizophrenia or schizoaffective disorder and matched normal comparison subjects. The mRNA from cell collections was subjected to transcriptome profiling by microarray followed by quantitative PCR validation. Expression of genes involved in mitochondrial (MT) or ubiquitin-proteasome system (UPS) functions were markedly downregulated in the patient group (P-values for MT-related and UPS-related pathways were <10(-7) and <10(-5), respectively). MT-related gene alterations were more prominent in layer 3 pyramidal cells, whereas UPS-related gene alterations were more prominent in layer 5 pyramidal cells. Many of these alterations were not present, or found to a lesser degree, in samples of DLPFC gray matter from the same subjects, suggesting that they are pyramidal cell specific. Furthermore, these findings principally reflected alterations in the schizophrenia subjects were not present or present to a lesser degree in the schizoaffective disorder subjects (diagnosis of schizoaffective disorder was the most significant covariate, P<10(-6)) and were not attributable to factors frequently comorbid with schizophrenia. In summary, our findings reveal expression deficits in MT- and UPS-related genes specific to layer 3 and/or layer 5 pyramidal cells in the DLPFC of schizophrenia subjects. These cell type-specific transcriptome signatures are not characteristic of schizoaffective disorder, providing a potential molecular-cellular basis of differences in clinical phenotypes.

CX3CR1 is dysregulated in blood and brain from schizophrenia patients

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

Alterations in cortical network oscillations and parvalbumin neurons in schizophrenia

Cognitive deficits are a core clinical feature of schizophrenia but respond poorly to available medications. Thus, understanding the neural basis of these deficits is crucial for the development of new therapeutic interventions. The types of cognitive processes affected in schizophrenia are thought to depend on the precisely timed transmission of information in cortical regions via synchronous oscillations at gamma band frequency. Here, we review 1) data from clinical studies suggesting that induction of frontal cortex gamma oscillations during tasks that engage cognitive or complex perceptual functions is attenuated in schizophrenia; 2) findings from basic neuroscience studies highlighting the features of parvalbumin-positive interneurons that are critical for gamma oscillation production; and 3) results from recent postmortem human brain studies providing additional molecular bases for parvalbumin-positive interneuron alterations in prefrontal cortical circuitry in schizophrenia.

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.

Schizophrenia biomarkers: translating the descriptive into the diagnostic

While schizophrenia and mental health are qualitatively distinct at the level of clinical presentation, the specific molecular signatures that underlie, or associate with, illness are not. Biomarker identification in schizophrenia is intended to offer a number of important benefits to patient well-being including prediction of future illness, diagnostic clarity and a level of disease description that would guide treatment choice. However, the choice of sample and form of analysis used to produce useful biomarkers is still uncertain. In this review, advances from recent studies spanning the technical spectrum are presented together with comment on their comparative strengths and weaknesses. To date, these studies have aided our understanding of the pathological processes associated with illness much more than they have provided robust biomarkers. A number of reasons for this observation are suggested, as are new strategies for the extraction of biomarkers from large '-omics' datasets.

The synapse in schizophrenia

It has been several decades since synaptic dysfunction was first suggested to play a role in schizophrenia, but only in the last few years has convincing evidence been obtained as progress has been made in elucidating the genetic underpinnings of the disorder. In the intervening years much has been learned concerning the complex macromolecular structure of the synapse itself, and genetic studies are now beginning to draw upon these advances. Here we outline our current understanding of the genetic architecture of schizophrenia and examine the evidence for synaptic involvement. A strong case can now be made that disruption of glutamatergic signalling pathways regulating synaptic plasticity contributes to the aetiology of schizophrenia.

RNA-sequencing of the brain transcriptome implicates dysregulation of neuroplasticity, circadian rhythms and GTPase binding in bipolar disorder

RNA-sequencing (RNA-seq) is a powerful technique to investigate the complexity of gene expression in the human brain. We used RNA-seq to survey the brain transcriptome in high-quality postmortem dorsolateral prefrontal cortex from 11 individuals diagnosed with bipolar disorder (BD) and from 11 age- and gender-matched controls. Deep sequencing was performed, with over 350 million reads per specimen. At a false discovery rate of <5%, we detected five differentially expressed (DE) genes and 12 DE transcripts, most of which have not been previously implicated in BD. Among these, Prominin 1/CD133 and ATP-binding cassette-sub-family G-member2 (ABCG2) have important roles in neuroplasticity. We also show for the first time differential expression of long noncoding RNAs (lncRNAs) in BD. DE transcripts include those of serine/arginine-rich splicing factor 5 (SRSF5) and regulatory factor X4 (RFX4), which along with lncRNAs have a role in mammalian circadian rhythms. The DE genes were significantly enriched for several Gene Ontology categories. Of these, genes involved with GTPase binding were also enriched for BD-associated SNPs from previous genome-wide association studies, suggesting that differential expression of these genes is not simply a consequence of BD or its treatment. Many of these findings were replicated by microarray in an independent sample of 60 cases and controls. These results highlight common pathways for inherited and non-inherited influences on disease risk that may constitute good targets for novel therapies.

The developmental transcriptome of the human brain: implications for neurodevelopmental disorders

PURPOSE OF REVIEW

Recent characterizations of the transcriptome of the developing human brain by several groups have generated comprehensive datasets on coding and noncoding RNAs that will be instrumental for illuminating the underlying biology of complex neurodevelopmental disorders. This review summarizes recent studies successfully utilizing these data to increase our understanding of the molecular mechanisms of pathogenesis.

RECENT FINDINGS

Several approaches have successfully integrated developmental transcriptome data with gene discovery to generate testable hypotheses about when and where in the developing human brain disease-associated genes converge. Specifically, these include the projection neurons in the prefrontal and primary motor--somatosensory cortex during mid-fetal development in autism spectrum disorder and the frontal cortex during fetal development in schizophrenia.

SUMMARY

Developmental transcriptome data is a key to interpreting disease-associated mutations and transcriptional changes. Novel approaches integrating the spatial and temporal dimensions of these data have increased our understanding of when and where disease occurs. Refinement of spatial and temporal properties and expanding these findings to other neurodevelopmental disorders will provide critical insights for understanding disease biology.