Altered Expression of PDE4 Genes in Schizophrenia: Insights from a Brain and Blood Sample Meta-Analysis and iPSC-Derived Neurons.

Schizophrenia symptomatology includes negative symptoms and cognitive impairment. Several studies have linked schizophrenia with the PDE4 family of enzymes due to their genetic association and function in cognitive processes such as long-term potentiation. We conducted a systematic gene expression meta-analysis of four PDE4 genes (PDE4A-D) in 10 brain sample datasets (437 samples) and three blood sample datasets (300 samples). Subsequently, we measured mRNA levels in iPSC-derived hippocampal dentate gyrus neurons generated from fibroblasts of three groups: healthy controls, healthy monozygotic twins (MZ), and their MZ siblings with schizophrenia. We found downregulation of PDE4B in brain tissues, further validated by independent data of the CommonMind consortium (515 samples). Interestingly, the downregulation signal was present in a subgroup of the patients, while the others showed no differential expression or even upregulation. Notably, PDE4A, PDE4B, and PDE4D exhibited upregulation in iPSC-derived neurons compared to healthy controls, whereas in blood samples, PDE4B was found to be upregulated while PDE4A was downregulated. While the precise mechanism and direction of altered PDE4 expression necessitate further investigation, the observed multilevel differential expression across the brain, blood, and iPSC-derived neurons compellingly suggests the involvement of PDE4 genes in the pathophysiology of schizophrenia.

Cannabinoid receptor gene CNR1 is downregulated in subcortical brain samples and upregulated in blood samples of individuals with schizophrenia: A participant data systematic meta-analysis.

Cannabis use leads to symptom exacerbation in schizophrenia patients, and endocannabinoid ligands have been studied as tentative schizophrenia therapeutics. Here, we aimed to characterise the connection between schizophrenia and the cannabinoid receptor 1 gene (CNR1) and explore possible mechanisms affecting its expression in schizophrenia. We performed a participant data systematic meta-analysis of CNR1 gene expression and additional endocannabinoid system genes in both brain (subcortical areas) and blood samples. We integrated eight brain sample datasets (overall 316 samples; 149 schizophrenia and 167 controls) and two blood sample datasets (overall 90 samples; 53 schizophrenia and 37 controls) while following the PRISMA meta-analysis guidelines. CNR1 was downregulated in subcortical regions and upregulated in blood samples of patients with schizophrenia. CNR2 and genes encoding endocannabinoids synthesis and degradation did not show differential expression in the brain or blood, except fatty acid amide hydrolase (FAAH), which showed a downregulation trend in blood. In addition, the brain expression levels of CNR1 and three GABA receptor genes, GABRA1, GABRA6 and GABRG2, were positively correlated (R = .57, .36, .54; p = 2.7 × 10-14 , 6.9 × 10-6 and 1.1 × 10-12 , respectively). Brain CNR1 downregulation and the positive correlation with three GABA receptor genes suggest an association with GABA neurotransmission and possible effects on negative schizophrenia symptoms. Further studies are required for clarifying the opposite CNR1 dysregulation in the brain and blood of schizophrenia patients and the potential of endocannabinoid ligands as schizophrenia therapeutics.

Ribosome subunits are upregulated in brain samples of a subgroup of individuals with schizophrenia: A systematic gene expression meta-analysis.

One of the new theories accounting for the underlying pathophysiology of schizophrenia is excitation/inhibition imbalance. Interestingly, perturbation in protein synthesis machinery as well as oxidative stress can lead to excitation/inhibition imbalance. We thus performed a systematic meta-analysis of the expression of 79 ribosome subunit genes and two oxidative-stress related genes, HIF1A and NQO1, in brain samples of individuals with schizophrenia vs. healthy controls. We integrated 12 gene expression datasets, following the PRISMA guidelines (overall 511 samples, 253 schizophrenia and 258 controls). Five ribosome subunit genes were significantly upregulated in a subgroup of the patients with schizophrenia, while 24 (30%) showed a tendency for upregulation. HIF1A and NQO1 were also found to be significantly upregulated. Moreover, HIF1A and NQO1 showed positive correlation with the expression of the upregulated ribosome subunit genes. Our results, together with previous findings, suggest a possible role for altered mRNA translation in the pathogenesis of schizophrenia, in association with markers of increased oxidative stress in a subgroup of patients. Further studies should define whether the upregulation of ribosome subunits result in altered mRNA translation, which proteins are modulated and how it characterizes a subgroup of the patients with schizophrenia.

Multiple genes encoding mitochondrial ribosomes are downregulated in brain and blood samples of individuals with schizophrenia.

OBJECTIVES: Schizophrenia is a chronic, debilitating mental disorder whose pathophysiology is complex and not fully understood. Numerous studies suggest mitochondrial dysfunction may contribute to the development of schizophrenia. While mitochondrial ribosomes (mitoribosomes) are essential for proper mitochondrial functioning, their gene expression levels have not been studied yet in schizophrenia. METHODS: We performed a systematic meta-analysis of the expression of 81 mitoribosomes subunits encoding genes, integrating ten brain samples datasets of patients with schizophrenia compared to healthy controls (overall 422 samples, 211 schizophrenia, and 211 controls). We also performed a meta-analysis of their expression in blood, integrating two blood sample datasets (overall 90 samples, 53 schizophrenia, and 37 controls). RESULTS: Multiple mitoribosomes subunits were significantly downregulated in brain samples (18 genes) and in blood samples (11 genes) of individuals with schizophrenia, where two showed significant downregulation in both brain and blood, MRPL4 and MRPS7. CONCLUSIONS: Our results support the accumulating evidence of impaired mitochondrial activity in schizophrenia. While further research is needed to validate mitoribosomes' role as biomarkers, this direction has the potential to promote patients' stratification and personalised treatment for schizophrenia.

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.

SMAD genes are up-regulated in brain and blood samples of individuals with schizophrenia.

Schizophrenia is a severe psychiatric disorder, with heritability around 80%, but a not fully understood pathophysiology. Signal transduction through the mothers against decapentaplegic (SMADs) are eight different proteins involved in the regulation of inflammatory processes, cell cycle, and tissue patterning. The literature is not consistent regarding the differential expression of SMAD genes among subjects with schizophrenia. In this article, we performed a systematic meta-analysis of the expression of SMAD genes in 423 brain samples (211 schizophrenia vs. 212 healthy controls), integrating 10 datasets from two public repositories, following the PRISMA guidelines. We found a statistically significant up-regulation of SMAD1, SMAD4, SMAD5, and SMAD7, and a tendency for up-regulation of SMAD3 and SMAD9 in brain samples of patients with schizophrenia. Overall, six of the eight genes showed a tendency for up-regulation, and none of them was found to have a tendency for down-regulation. SMAD1 and SMAD4 were up-regulated also in blood samples of 13 individuals with schizophrenia versus eight healthy controls, suggesting the SMAD genes' potential role as biomarkers of schizophrenia. Furthermore, SMAD genes' expression levels were significantly correlated with those of Sphingosine-1-phosphate receptor-1 (S1PR1), which is known to regulate inflammatory processes. Our meta-analysis supports the involvement of SMAD genes in the pathophysiology of schizophrenia through their role in inflammatory processes, as well as demonstrates the importance of gene expression meta-analysis for improving our understanding of psychiatric diseases.

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.

Meta-analysis of brain samples of individuals with schizophrenia detects down-regulation of multiple ATP synthase encoding genes in both females and males.

Schizophrenia is a chronic and debilitating mental disorder, with unknown pathophysiology. Converging lines of evidence suggest that mitochondrial functioning may be compromised in schizophrenia. Postmortem brain samples of individuals with schizophrenia showed dysregulated expression levels of genes encoding enzyme complexes comprising the mitochondrial electron transport chain (ETC), including ATP synthase, the fifth ETC complex. However, there are inconsistencies regarding the direction of change, i.e., up- or down-regulation, and differences between female and male patients were hardly examined. We have performed a systematic meta-analysis of the expression of 16 ATP synthase encoding genes in postmortem brain samples of individuals with schizophrenia vs. healthy controls of three regions: Brodmann Area 10 (BA10), BA22/Superior Temporal Gyrus (STG) and the cerebellum. Eight independent datasets were integrated (overall 294brain samples, 145 of individuals with schizophrenia and 149 controls). The meta-analysis was applied to all individuals with schizophrenia vs. the controls, and also to female and male patients vs. age-matched controls, separately. A significant down-regulation of two ATP synthase encoding genes was detected in schizophrenia, ATP5A1 and ATP5H, and a trend towards down-regulation of five further ATP synthase genes. The down-regulation tendency was shown for both females and males with schizophrenia. Our findings support the hypothesis that schizophrenia is associated with reduced ATP synthesis via the oxidative phosphorylation system, which is caused by reduced cellular demand of ATP. Abnormal cellular energy metabolism can lead to alterations in neural function and brain circuitry, and thereby to the cognitive and behavioral aberrations characteristic of schizophrenia.

Gene expression meta-analysis in patients with schizophrenia reveals up-regulation of RGS2 and RGS16 in Brodmann Area 10.

Regulator of G-protein signalling (RGS) proteins inhibit signalling by G-protein-coupled receptors (GPCRs). GPCRs mediate the functions of several important neurotransmitters and serve as targets of many anti-psychotics. RGS2, RGS4, RGS5 and RGS16 are located on chromosome 1q23.3-31, a locus found to be associated with schizophrenia. Although previous gene expression analysis detected down-regulation of RGS4 expression in brain samples of patients with schizophrenia, the results were not consistent. In the present study, we performed a systematic meta-analysis of differential RGS2, RGS4, RGS5 and RGS16 expression in Brodmann Area 10 (BA10) samples of patients with schizophrenia and from healthy controls. Two microarray datasets met the inclusion criteria (overall, 41 schizophrenia samples and 38 controls were analysed). RGS2 and RGS16 were found to be up-regulated in BA10 samples of individuals with schizophrenia, whereas no differential expression of RGS4 and RGS5 was detected. Analysis of dorso-lateral prefrontal cortex samples of the CommonMind Consortium (258 schizophrenia samples vs. 279 controls) further validated the results. Given their central role in inactivating G-protein-coupled signalling pathways, our results suggest that differential gene expression might lead to enhanced inactivation of G-protein signalling in schizophrenia. This, in turn, suggests that additional studies are needed to further explore the consequences of the differential expression we detected, this time at the protein and functional levels.

Gene Expression Meta-Analysis of Cerebellum Samples Supports the FKBP5 Gene-Environment Interaction Model for Schizophrenia.

BACKGROUND: One of the most studied molecular models of gene-environment interactions is that of FKBP5, which has been shown to interact with childhood adversity to increase the risk of psychiatric disorders, and has been implicated in schizophrenia. While the model predicts up-regulation of FKBP5, previous brain samples gene expression studies yielded inconsistent results. METHODS: We performed a systematic gene expression meta-analysis of FKBP5 and NR3C1, a glucocorticoid receptor inhibited by FKBP5, in cerebellum samples of patients with schizophrenia. The gene expression databases GEO, SMRI and those of NIMH were searched, and out of six screened datasets, three were eligible for the meta-analysis (overall 69 with schizophrenia and 78 controls). RESULTS: We detected up-regulation of FKBP5 and down-regulation of NR3C1 in schizophrenia, and a negative correlation between their expression patterns. Correlation analysis suggested that the detected differential expression did not result from potential confounding factors. CONCLUSIONS: Our results give significant support to the FKBP5 gene-environment interaction model for schizophrenia, which provides a molecular mechanism by which childhood adversity is involved in the development of the disorder. To explore FKBP5's potential as a therapeutic target, a mapping of its differential expression patterns in different brain regions of schizophrenia patients is needed.

Comprehensive Gene Expression Analysis Detects Global Reduction of Proteasome Subunits in Schizophrenia.

BACKGROUND: The main challenge in the study of schizophrenia is its high heterogeneity. While it is generally accepted that there exist several biological mechanisms that may define distinct schizophrenia subtypes, they have not been identified yet. We performed comprehensive gene expression analysis to search for molecular signals that differentiate schizophrenia patients from healthy controls and examined whether an identified signal was concentrated in a subgroup of the patients. METHODS: Transcriptome sequencing of 14 superior temporal gyrus (STG) samples of subjects with schizophrenia and 15 matched controls from the Stanley Medical Research Institute (SMRI) was performed. Differential expression and pathway enrichment analysis results were compared to an independent cohort. Replicability was tested on 6 additional independent datasets. RESULTS: The 2 STG cohorts showed high replicability. Pathway enrichment analysis of the down-regulated genes pointed to proteasome-related pathways. Meta-analysis of differential expression identified down-regulation of 12 of 39 proteasome subunit genes in schizophrenia. The signal of proteasome subunits down-regulation was replicated in 6 additional datasets (overall 8 cohorts with 267 schizophrenia and 266 control samples, from 5 brain regions). The signal was concentrated in a subgroup of patients with schizophrenia. CONCLUSIONS: We detected global down-regulation of proteasome subunits in a subgroup of patients with schizophrenia. We hypothesize that the down-regulation of proteasome subunits leads to proteasome dysfunction that causes accumulation of ubiquitinated proteins, which has been recently detected in a subgroup of schizophrenia patients. Thus, down-regulation of proteasome subunits might define a biological subtype of schizophrenia.

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 meta-analysis reveals the down-regulation of three GABA receptor subunits in the superior temporal gyrus of patients with schizophrenia.

One of the main theories accounting for the underlying pathophysiology of schizophrenia posits alterations in GABAergic neurotransmission. While previous gene expression studies of postmortem brain samples typically report the down-regulation of GABA related genes in schizophrenia, the results are often inconsistent and not uniform across studies. We performed a systematic gene expression analysis of 22 GABA related genes in postmortem superior temporal gyrus (STG) samples of 19 elderly subjects with schizophrenia (mean age: 77) and 14 matched controls from the Icahn school of Medicine at Mount Sinai (MSSM) cohort. To test the validity and robustness of the resulting differentially expressed genes, we then conducted a meta-analysis of the MSSM and an independent dataset from the Stanley Consortium of 14 STG samples of relatively young subjects with schizophrenia (mean age: 44) and 15 matched controls. For the first time, the findings showed the down-regulation of three GABA-receptor subunits of type A, GABRA1, GABRA2 and GABRB3, in the STG samples of subjects with schizophrenia, in both the elderly and the relatively young patients. These findings, as well as previous results, lend weight to the notion of a common upstream pathology that alters GABAergic neurotransmission in schizophrenia. GABRA1, GABRA2 and GABRB3 down-regulation may contribute to the pathophysiology and clinical manifestations of schizophrenia through altered oscillation synchronization in the STG.

Navigator-3, a modulator of cell migration, may act as a suppressor of breast cancer progression.

Dissemination of primary tumor cells depends on migratory and invasive attributes. Here, we identify Navigator-3 (NAV3), a gene frequently mutated or deleted in human tumors, as a regulator of epithelial migration and invasion. Following induction by growth factors, NAV3 localizes to the plus ends of microtubules and enhances their polarized growth. Accordingly, NAV3 depletion trimmed microtubule growth, prolonged growth factor signaling, prevented apoptosis and enhanced random cell migration. Mathematical modeling suggested that NAV3-depleted cells acquire an advantage in terms of the way they explore their environment. In animal models, silencing NAV3 increased metastasis, whereas ectopic expression of the wild-type form, unlike expression of two, relatively unstable oncogenic mutants from human tumors, inhibited metastasis. Congruently, analyses of > 2,500 breast and lung cancer patients associated low NAV3 with shorter survival. We propose that NAV3 inhibits breast cancer progression by regulating microtubule dynamics, biasing directionally persistent rather than random migration, and inhibiting locomotion of initiated cells.

Epidermal growth-factor-induced transcript isoform variation drives mammary cell migration.

Signal-induced transcript isoform variation (TIV) includes alternative promoter usage as well as alternative splicing and alternative polyadenylation of mRNA. To assess the phenotypic relevance of signal-induced TIV, we employed exon arrays and breast epithelial cells, which migrate in response to the epidermal growth factor (EGF). We show that EGF rapidly--within one hour--induces widespread TIV in a significant fraction of the transcriptome. Importantly, TIV characterizes many genes that display no differential expression upon stimulus. In addition, similar EGF-dependent changes are shared by a panel of mammary cell lines. A functional screen, which utilized isoform-specific siRNA oligonucleotides, indicated that several isoforms play essential, non-redundant roles in EGF-induced mammary cell migration. Taken together, our findings highlight the importance of TIV in the rapid evolvement of a phenotypic response to extracellular signals.

Automated long-term tracking and social behavioural phenotyping of animal colonies within a semi-natural environment.

Social behaviour has a key role in animal survival across species, ranging from insects to primates and humans. However, the biological mechanisms driving natural interactions between multiple animals, over long-term periods, are poorly studied and remain elusive. Rigorous and objective quantification of behavioural parameters within a group poses a major challenge as it requires simultaneous monitoring of the positions of several individuals and comprehensive consideration of many complex factors. Automatic tracking and phenotyping of interacting animals could thus overcome the limitations of manual tracking methods. Here we report a broadly applicable system that automatically tracks the locations of multiple, uniquely identified animals, such as mice, within a semi-natural setting. The system combines video and radio frequency identified tracking data to obtain detailed behavioural profiles of both individuals and groups. We demonstrate the usefulness of these data in characterizing individual phenotypes, interactions between pairs and the collective social organization of groups.

An accessible database for mouse and human whole transcriptome qPCR primers.

MOTIVATION: Real time quantitative polymerase chain reaction (qPCR) is an important tool in quantitative studies of DNA and RNA molecules; especially in transcriptome studies, where different primer combinations allow identification of specific transcripts such as splice variants or precursor messenger RNA. Several softwares that implement various rules for optimal primer design are available. Nevertheless, as designing qPCR primers needs to be done manually, the repeated task is tedious, time consuming and prone to errors. RESULTS: We used a set of rules to automatically design all possible exon-exon and intron-exon junctions in the human and mouse transcriptomes. The resulting database is included as a track in the UCSC genome browser, making it widely accessible and easy to use. AVAILABILITY: The database is available from the UCSC genome browser (http://genome.ucsc.edu/), track name 'Whole Transcriptome qPCR Primers' for the hg19 (Human) and mm10 (Mouse) genome versions. Batch query is available in the following: http://www.weizmann.ac.il/complex/compphys/software/Amit/primers/batch_query_qpcr_primers.htm CONTACT: amit.zeisel@weizmann.ac.il or eytan.domany@weizmann.ac.il SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

qCMA: a desktop application for quantitative collective cell migration analysis.

Collective migration is an important cellular trait, which is intensely studied by both basic and translational researchers. Investigation of the underlying mechanisms necessitates high-throughput assays and computational algorithms capable of generating reproducible quantitative measurements of cell migration. We present a desktop tool that can be used easily by any researcher, to quantify both fluorescent and phase-contrast images produced in the course of commonly used gap closure ("scratch," "wound healing") collective migration assays. The software has a simple graphical interface that allows the user to tune the relevant parameters and process large numbers of images (or movies). The output contains segmented images and the numerical values inferred from them, allowing easy quantitative analysis of the results.

Context-specific microRNA analysis: identification of functional microRNAs and their mRNA targets.

MicroRNAs (miRs) function primarily as post-transcriptional negative regulators of gene expression through binding to their mRNA targets. Reliable prediction of a miR's targets is a considerable bioinformatic challenge of great importance for inferring the miR's function. Sequence-based prediction algorithms have high false-positive rates, are not in agreement, and are not biological context specific. Here we introduce CoSMic (Context-Specific MicroRNA analysis), an algorithm that combines sequence-based prediction with miR and mRNA expression data. CoSMic differs from existing methods--it identifies miRs that play active roles in the specific biological system of interest and predicts with less false positives their functional targets. We applied CoSMic to search for miRs that regulate the migratory response of human mammary cells to epidermal growth factor (EGF) stimulation. Several such miRs, whose putative targets were significantly enriched by migration processes were identified. We tested three of these miRs experimentally, and showed that they indeed affected the migratory phenotype; we also tested three negative controls. In comparison to other algorithms CoSMic indeed filters out false positives and allows improved identification of context-specific targets. CoSMic can greatly facilitate miR research in general and, in particular, advance our understanding of individual miRs' function in a specific context.