Decreased expression of Fyn protein and disbalanced alternative splicing patterns in platelets from patients with schizophrenia

Comparison of Oncogenes, Tumor Suppressors, and MicroRNAs Between Schizophrenia and Glioma: The Balance of Power

The risk of cancer in schizophrenia has been controversial. Confounders of the issue are cigarette smoking in schizophrenia, and antiproliferative effects of antipsychotic medications. The author has previously suggested comparison of a specific cancer like glioma to schizophrenia might help determine a more accurate relationship between cancer and schizophrenia. To accomplish this goal, the author performed three comparisons of data; the first a comparison of conventional tumor suppressors and oncogenes between schizophrenia and cancer including glioma. This comparison determined schizophrenia has both tumor-suppressive and tumor-promoting characteristics. A second, larger comparison between brain-expressed microRNAs in schizophrenia with their expression in glioma was then performed. This identified a core carcinogenic group of miRNAs in schizophrenia offset by a larger group of tumor-suppressive miRNAs. This proposed "balance of power" between oncogenes and tumor suppressors could cause neuroinflammation. This was assessed by a third comparison between schizophrenia, glioma and inflammation in asbestos-related lung cancer and mesothelioma (ALRCM). This revealed that schizophrenia shares more oncogenic similarity to ALRCM than glioma.

Bioinformatics and Network-based Approaches for Determining Pathways, Signature Molecules, and Drug Substances connected to Genetic Basis of Schizophrenia etiology

Knowledge of heterogeneous etiology and pathophysiology of schizophrenia (SZP) is reasonably inadequate and non-deterministic due to its inherent complexity and underlying vast dynamics related to genetic mechanisms. The evolution of large-scale transcriptome-wide datasets and subsequent development of relevant, robust technologies for their analyses show promises toward elucidating the genetic basis of disease pathogenesis, its early risk prediction, and predicting drug molecule targets for therapeutic intervention. In this research, we have scrutinized the genetic basis of SZP through functional annotation and network-based system biology approaches. We have determined 96 overlapping differentially expressed genes (DEGs) from 2 microarray datasets and subsequently identified their interconnecting networks to reveal transcriptome signatures like hub proteins (FYN, RAD51, SOCS3, XIAP, AKAP13, PIK3C2A, CBX5, GATA3, EIF3K, and CDKN2B), transcription factors and miRNAs. In addition, we have employed gene set enrichment to highlight significant gene ontology (e.g., positive regulation of microglial cell activation) and relevant pathways (such as axon guidance and focal adhesion) interconnected to the genes associated with SZP. Finally, we have suggested candidate drug substances like Luteolin HL60 UP as a possible therapeutic target based on these key molecular signatures.

The machine learning algorithm for the diagnosis of schizophrenia on the basis of gene expression in peripheral blood

BACKGROUND

Schizophrenia (SCZ) is a highly heritable mental disorder with a substantial disease burden. Machine learning (ML) method can be used to identify individuals with SCZ on the basis of blood gene expression data with high accuracy.

METHODS

This study aimed to differentiate patients with SCZ from healthy individuals by using the messenger RNA expression level in peripheral blood of 48 patients with SCZ and 50 controls via ML algorithms, namely, artificial neural networks, extreme gradient boosting, support vector machine (SVM), decision tree, and random forest. The expression of six mRNAs was detected using quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

The relative expression levels of GNAI1 (P < 0.001), PRKCA (P < 0.001), and PRKCB (P = 0.021) increased in the SCZ group, whereas those of FYN (P < 0.001), LYN (P = 0.022), and YWHAZ (P < 0.001) decreased in the SCZ group. We generated models with various combinations of genes based on five ML algorithms. The SVM model with six factors (GNAI1, FYN, PRKCA, YWHAZ, PRKCB, and LYN genes) was the best model for distinguishing patients with SCZ from healthy individuals (AUC = 0.993, sensitivity = 1.000, specificity = 0.895, and Youden index = 0.895).

CONCLUSIONS

This study suggested that the combination of genes using the ML method is better than the use of a single gene to discriminate patients with SCZ from healthy individuals. The combination of GNAI1, FYN, PRKCA, YWHAZ, PRKCB, and LYN under the SVM model can be used as a diagnostic biomarker for SCZ.

Fyn Tyrosine Kinase as Harmonizing Factor in Neuronal Functions and Dysfunctions

Fyn is a non-receptor or cytoplasmatic tyrosine kinase (TK) belonging to the Src family kinases (SFKs) involved in multiple transduction pathways in the central nervous system (CNS) including synaptic transmission, myelination, axon guidance, and oligodendrocyte formation. Almost one hundred years after the original description of Fyn, this protein continues to attract extreme interest because of its multiplicity of actions in the molecular signaling pathways underlying neurodevelopmental as well as neuropathologic events. This review highlights and summarizes the most relevant recent findings pertinent to the role that Fyn exerts in the brain, emphasizing aspects related to neurodevelopment and synaptic plasticity. Fyn is a common factor in healthy and diseased brains that targets different proteins and shapes different transduction signals according to the neurological conditions. We will primarily focus on Fyn-mediated signaling pathways involved in neuronal differentiation and plasticity that have been subjected to considerable attention lately, opening the fascinating scenario to target Fyn TK for the development of potential therapeutic interventions for the treatment of CNS injuries and certain neurodegenerative disorders like Alzheimer’s disease.

Weighted Burden Analysis of Exome-Sequenced Case-Control Sample Implicates Synaptic Genes in Schizophrenia Aetiology

A previous study of exome-sequenced schizophrenia cases and controls reported an excess of singleton, gene-disruptive variants among cases, concentrated in particular gene sets. The dataset included a number of subjects with a substantial Finnish contribution to ancestry. We have reanalysed the same dataset after removal of these subjects and we have also included non-singleton variants of all types using a weighted burden test which assigns higher weights to variants predicted to have a greater effect on protein function. We investigated the same 31 gene sets as previously and also 1454 GO gene sets. The reduced dataset consisted of 4225 cases and 5834 controls. No individual variants or genes were significantly enriched in cases but 13 out of the 31 gene sets were significant after Bonferroni correction and the “FMRP targets” set produced a signed log p value (SLP) of 7.1. The gene within this set with the highest SLP, equal to 3.4, was FYN, which codes for a tyrosine kinase which phosphorylates glutamate metabotropic receptors and ionotropic NMDA receptors, thus modulating their trafficking, subcellular distribution and function. In the most recent GWAS of schizophrenia it was identified as a “prioritized candidate gene”. Two of the subunits of the NMDA receptor which are substrates of FYN are coded for by GRIN1 (SLP = 1.7) and GRIN2B (SLP = 2.1). Of note, for some sets there was a substantial enrichment of non-singleton variants. Of 1454 GO gene sets, three were significant after Bonferroni correction. Identifying specific genes and variants will depend on genotyping them in larger samples and/or demonstrating that they cosegregate with illness within pedigrees.

Genome-wide association analysis identifies 30 new susceptibility loci for schizophrenia

We conducted a genome-wide association study (GWAS) with replication in 36,180 Chinese individuals and performed further transancestry meta-analyses with data from the Psychiatry Genomics Consortium (PGC2). Approximately 95% of the genome-wide significant (GWS) index alleles (or their proxies) from the PGC2 study were overrepresented in Chinese schizophrenia cases, including ∼50% that achieved nominal significance and ∼75% that continued to be GWS in the transancestry analysis. The Chinese-only analysis identified seven GWS loci; three of these also were GWS in the transancestry analyses, which identified 109 GWS loci, thus yielding a total of 113 GWS loci (30 novel) in at least one of these analyses. We observed improvements in the fine-mapping resolution at many susceptibility loci. Our results provide several lines of evidence supporting candidate genes at many loci and highlight some pathways for further research. Together, our findings provide novel insight into the genetic architecture and biological etiology of schizophrenia.

Patterns and functional implications of platelets upon tumor "education"

While platelets are traditionally recognized to play a predominant role in hemostasis and thrombosis, increasing evidence verifies its involvement in malignancies. As a component of the tumor microenvironment, platelets influence carcinogenesis, tumor metastasis and chemotherapy efficiency. Platelets status is thus predictable as a hematological biomarker of cancer prognosis and a hot target for therapeutic intervention. On the other hand, the role of circulating tumor cells (CTCs) as an inducer of platelet activation and aggregation has been well acknowledged. The cross-talk between platelets and CTCs is reciprocal on that the CTCs activate platelets while platelets contribute to CTCs' survival and dissemination. This review covers some of the current issues related to the loop between platelets and tumor aggression, including the manners of tumor cells in "educating" platelets and biofunctional alterations of platelets upon tumor "education". We also highlight the potential clinical applications on the interplay between tumors and platelets. Further studies with well-designed prospective multicenter trials may contribute to clinical "liquid biopsy" diagnosis by evaluating the global changes of platelets.

Biomarker investigations related to pathophysiological pathways in schizophrenia and psychosis

Post-mortem brain investigations of schizophrenia have generated swathes of data in the last few decades implicating candidate genes and protein. However, the relation of these findings to peripheral biomarker indicators and symptomatology remain to be elucidated. While biomarkers for disease do not have to be involved with underlying pathophysiology and may be largely indicative of diagnosis or prognosis, the ideal may be a biomarker that is involved in underlying disease processes and which is therefore more likely to change with progression of the illness as well as potentially being more responsive to treatment. One of the main difficulties in conducting biomarker investigations for major psychiatric disorders is the relative inconsistency in clinical diagnoses between disorders such as bipolar and schizophrenia. This has led some researchers to investigate biomarkers associated with core symptoms of these disorders, such as psychosis. The aim of this review is to evaluate the contribution of post-mortem brain investigations to elucidating the pathophysiology pathways involved in schizophrenia and psychosis, with an emphasis on major neurotransmitter systems that have been implicated. This data will then be compared to functional neuroimaging findings as well as findings from blood based gene expression investigations in schizophrenia in order to highlight the relative overlap in pathological processes between these different modalities used to elucidate pathogenesis of schizophrenia. In addition we will cover some recent and exciting findings demonstrating microRNA (miRNA) dysregulation in both the blood and the brain in patients with schizophrenia. These changes are pertinent to the topic due to their known role in post-transcriptional modification of gene expression with the potential to contribute or underlie gene expression changes observed in schizophrenia. Finally, we will discuss how post-mortem studies may aid future biomarker investigations.

Platelets: A possible glance into brain biological processes in schizophrenia

Schizophrenia is a severe mental disorder, characterized by behavioral, emotional and cognitive disturbances, which commonly follows a chronic course. Diagnostic accuracy, management plans, treatment evaluation and prognosis are dependent on relatively subjective assessments. Despite extensive research and improvement in imaging technology, as well as modern genetic and molecular methodologies, the biological basis of this disease is still unclear. Therefore, there is a need for objective and valid biological markers. Platelets have often been used as a model in neurobiological research. The accessibility of platelets and their similarities with neurons turns them into an attractive candidate to search for biological markers for diagnosis and for unraveling pathophysiological processes relevant to the etiology of brain disorders, including schizophrenia. The present review addresses the main changes in platelet physiology observed in schizophrenia and its response to antipsychotic medication. We summarize numerous studies demonstrating impaired metabolism, uptake and receptor kinetics of schizophrenia-relevant neurotransmitters, abnormalities in membrane derived phospholipids and polyunsaturated fatty acids, as well as dysfunctions in the mitochondria. These changes fit with the various hypotheses raised for the etiology of schizophrenia, including the dopamine-glutamate hypothesis, the autoimmune hypothesis, the polyunsaturated fatty acid hypothesis and the impaired energy metabolism hypothesis. Despite extensive research in platelets, no conclusive reliable biomarker has been identified yet. This review suggests that the clinical heterogeneity and the biological complexity of schizophrenia lead to the inevitable conclusion that biomarkers will be identified only for subgroups characterized according to the different diagnostic criteria. Moreover, any biomarker would have to be an array of interrelated factors or even a set of several such arrays.

Hypothesis review: are clathrin-mediated endocytosis and clathrin-dependent membrane and protein trafficking core pathophysiological processes in schizophrenia and bipolar disorder?

Clathrin-mediated endocytosis (CME) is the best-characterized mechanism governing cellular membrane and protein trafficking. In this hypothesis review, we integrate recent evidence implicating CME and related cellular trafficking mechanisms in the pathophysiology of psychotic disorders such as schizophrenia and bipolar disorder. The evidence includes proteomic and genomic findings implicating proteins and genes of the clathrin interactome. Additionally, several important candidate genes for schizophrenia, such as dysbindin, are involved in processes closely linked to CME and membrane trafficking. We discuss that key aspects of psychosis neuropathology such as synaptic dysfunction, white matter changes and aberrant neurodevelopment are all influenced by clathrin-dependent processes, and that other cellular trafficking mechanisms previously linked to psychoses interact with the clathrin interactome in important ways. Furthermore, many antipsychotic drugs have been shown to affect clathrin-interacting proteins. We propose that the targeted pharmacological manipulation of the clathrin interactome may offer fruitful opportunities for novel treatments of schizophrenia.

Loss of function studies in mice and genetic association link receptor protein tyrosine phosphatase α to schizophrenia

BACKGROUND

Solid evidence links schizophrenia (SZ) susceptibility to neurodevelopmental processes involving tyrosine phosphorylation-mediated signaling. Mouse studies implicate the Ptpra gene, encoding protein tyrosine phosphatase RPTPα, in the control of radial neuronal migration, cortical cytoarchitecture, and oligodendrocyte differentiation. The human gene encoding RPTPα, PTPRA, maps to a chromosomal region (20p13) associated with susceptibility to psychotic illness.

METHODS

We characterized neurobehavioral parameters, as well as gene expression in the central nervous system, of mice with a null mutation in the Ptpra gene. We searched for genetic association between polymorphisms in PTPRA and schizophrenia risk (two independent cohorts, 1420 cases and 1377 controls), and we monitored PTPRA expression in prefrontal dorsolateral cortex of SZ patients (35 cases, 2 control groups of 35 cases).

RESULTS

We found that Ptpra⁻/⁻ mice reproduce neurobehavioral endophenotypes of human SZ: sensitization to methamphetamine-induced hyperactivity, defective sensorimotor gating, and defective habituation to a startle response. Ptpra loss of function also leads to reduced expression of multiple myelination genes, mimicking the hypomyelination-associated changes in gene expression observed in postmortem patient brains. We further report that a polymorphism at the PTPRA locus is genetically associated with SZ, and that PTPRA mRNA levels are reduced in postmortem dorsolateral prefrontal cortex of subjects with SZ.

CONCLUSIONS

The implication of this well-studied signaling protein in SZ risk and endophenotype manifestation provides novel entry points into the etiopathology of this disease.

Genomics and pharmacogenomics of schizophrenia

Schizophrenia (SCZ) is among the most disabling of mental disorders. Several neurobiological hypotheses have been postulated as responsible for SCZ pathogenesis: polygenic/multifactorial genomic defects, intrauterine and perinatal environment-genome interactions, neurodevelopmental defects, dopaminergic, cholinergic, serotonergic, gamma-aminobutiric acid (GABAergic), neuropeptidergic and glutamatergic/N-Methyl-D-Aspartate (NMDA) dysfunctions, seasonal infection, neuroimmune dysfunction, and epigenetic dysregulation. SCZ has a heritability estimated at 60-90%. Genetic studies in SCZ have revealed the presence of chromosome anomalies, copy number variants, multiple single-nucleotide polymorphisms of susceptibility distributed across the human genome, aberrant single nucleotide polymorphisms (SNPs) in microRNA genes, mitochondrial DNA mutations, and epigenetic phenomena. Pharmacogenetic studies of psychotropic drug response have focused on determining the relationship between variation in specific candidate genes and the positive and adverse effects of drug treatment. Approximately, 18% of neuroleptics are major substrates of CYP1A2 enzymes, 40% of CYP2D6, and 23% of CYP3A4; 24% of antidepressants are major substrates of CYP1A2 enzymes, 5% of CYP2B6, 38% of CYP2C19, 85% of CYP2D6, and 38% of CYP3A4; 7% of benzodiazepines are major substrates of CYP2C19 enzymes, 20% of CYP2D6, and 95% of CYP3A4. About 10-20% of Western populations are defective in genes of the CYP superfamily. Only 26% of Southern Europeans are pure extensive metabolizers for the trigenic cluster integrated by the CYP2D6+CYP2C19+CYP2C9 genes. The pharmacogenomic response of SCZ patients to conventional psychotropic drugs also depends on genetic variants associated with SCZ-related genes. Consequently, the incorporation of pharmacogenomic procedures both to drugs in development and drugs on the market would help to optimize therapeutics in SCZ and other central nervous system (CNS) disorders.

Cross-domain neurobiology data integration and exploration

Background

Understanding the biomedical implications of data from high throughput experiments requires solutions for effective cross-scale and cross-domain data exploration. However, existing solutions do not provide sufficient support for linking molecular level data to neuroanatomical structures, which is critical for understanding high level neurobiological functions.

Results

Our work integrates molecular level data with high level biological functions and we present results using anatomical structure as a scaffold. Our solution also allows the sharing of intermediate data exploration results with other web applications, greatly increasing the power of cross-domain data exploration and mining.

Conclusions

The Flex-based PubAnatomy web application we developed enables highly interactive visual exploration of literature and experimental data for understanding the relationships between molecular level changes, pathways, brain circuits and pathophysiological processes. The prototype of PubAnatomy is freely accessible at: [http://brainarray.mbni.med.umich.edu/Brainarray/prototype/PubAnatomy]