Exploring Transcription Factors-microRNAs Co-regulation Networks in Schizophrenia

Influence of antipsychotic drugs on microRNA expression in schizophrenia patients - A systematic review

Schizophrenia (SCZ) is a severe psychiatric disorder with unclear pathophysiology. Moreover, there is no specific biological marker to help clinicians to define a diagnosis, and medication is decided according to the psychiatrist's experience. In this scenario, microRNAs (miRNAs), which are small noncoding RNA molecules that regulate several genes, emerge as potential peripheral biomarkers to help not only the evaluation of the disease state but also the treatment response. Here, we systematically reviewed indexed literature and evaluated follow-up studies investigating the changes in miRNA expression due to antipsychotic treatment. We also assessed target genes and performed pathway enrichment analysis of miRNAs listed in this systematic review. A total of 11 studies were selected according to research criteria, and we observed that 28 miRNAs play a relevant role in schizophrenia pathogenesis or response to antipsychotic treatment, seven of those of extreme interest as possible biomarkers either for condition or treatment. Predicted targets of the miRNAs reviewed here were previously associated with schizophrenia in genome-wide studies, and pathway analysis showed enrichment for genes related to neural processes. With this review, we expect to highlight the importance of miRNAs in schizophrenia pathogenesis and its treatment and point out interesting miRNAs to future studies.

Genetic determinants of coping, resilience and self-esteem in schizophrenia suggest a primary role for social factors and hippocampal neurogenesis

Schizophrenia is a severe psychiatric disorder, associated with a reduction in life expectancy of 15-20 years. Available treatments are at least partially effective in most affected individuals, and personal resources such as resilience (successful adaptation despite adversity) and coping abilities (strategies used to deal with stressful or threatening situations), are important determinants of disease outcomes and long-term sustained recovery. Published findings support the existence of a genetic background underlying resilience and coping, with variable heritability estimates. However, genome-wide analyses concerning the genetic determinants of these personal resources, especially in the context of schizophrenia, are lacking. Here, we performed a genome-wide association study coupled with accessory analyses to investigate potential genetic determinants of resilience, coping and self-esteem in 490 schizophrenia patients. Results revealed a complex genetic background partly overlapping with that of neuroticism, worry and schizophrenia itself and support the importance of social aspects in shapingthese psychological constructs. Hippocampal neurogenesis and lipid metabolism appear to be potentially relevant biological underpinnings, and specific miRNAs such as miR-124 and miR-137 may warrant further studies as potential biomarkers. In conclusion, this study represents an important first step in the identification of genetic and biological correlates shaping resilience, coping resources and self-esteem in schizophrenia.

Behavioral and transcriptional effects of repeated electroconvulsive seizures in the neonatal MK-801-treated rat model of schizophrenia

RATIONALE

Electroconvulsive therapy (ECT) is an effective treatment modality for schizophrenia. However, its antipsychotic-like mechanism remains unclear.

OBJECTIVES

To gain insight into the antipsychotic-like actions of ECT, this study investigated how repeated treatments of electroconvulsive seizure (ECS), an animal model for ECT, affect the behavioral and transcriptomic profile of a neurodevelopmental animal model of schizophrenia.

METHODS

Two injections of MK-801 or saline were administered to rats on postnatal day 7 (PN7), and either repeated ECS treatments (E10X) or sham shock was conducted daily from PN50 to PN59. Ultimately, the rats were divided into vehicle/sham (V/S), MK-801/sham (M/S), vehicle/ECS (V/E), and MK-801/ECS (M/E) groups. On PN59, prepulse inhibition and locomotor activity were tested. Prefrontal cortex transcriptomes were analyzed with mRNA sequencing and network and pathway analyses, and quantitative real-time polymerase chain reaction (qPCR) analyses were subsequently conducted.

RESULTS

Prepulse inhibition deficit was induced by MK-801 and normalized by E10X. In M/S vs. M/E model, Egr1, Mmp9, and S100a6 were identified as center genes, and interleukin-17 (IL-17), nuclear factor kappa B (NF-κB), and tumor necrosis factor (TNF) signaling pathways were identified as the three most relevant pathways. In the V/E vs. V/S model, mitophagy, NF-κB, and receptor for advanced glycation end products (RAGE) pathways were identified. qPCR analyses demonstrated that Igfbp6, Btf3, Cox6a2, and H2az1 were downregulated in M/S and upregulated in M/E.

CONCLUSIONS

E10X reverses the behavioral changes induced by MK-801 and produces transcriptional changes in inflammatory, insulin, and mitophagy pathways, which provide mechanistic insight into the antipsychotic-like mechanism of ECT.

Patient-specific analysis of co-expression to measure biological network rewiring in individuals

To effectively understand the underlying mechanisms of disease and inform the development of personalized therapies, it is critical to harness the power of differential co-expression (DCE) network analysis. Despite the promise of DCE network analysis in precision medicine, current approaches have a major limitation: they measure an average differential network across multiple samples, which means the specific etiology of individual patients is often overlooked. To address this, we present Cosinet, a DCE-based single-sample network rewiring degree quantification tool. By analyzing two breast cancer datasets, we demonstrate that Cosinet can identify important differences in gene co-expression patterns between individual patients and generate scores for each individual that are significantly associated with overall survival, recurrence-free interval, and other clinical outcomes, even after adjusting for risk factors such as age, tumor size, HER2 status, and PAM50 subtypes. Cosinet represents a remarkable development toward unlocking the potential of DCE analysis in the context of precision medicine.

miR-9-5p deficiency contributes to schizophrenia

MicroRNA-9-5p (miR-9-5p) is highly expressed in the brain and has been implicated in the risk of schizophrenia. We compared the expression levels of miR-9-5p in schizophrenia cases and healthy controls and evaluated whether regulatory targets of miR-9-5p are enriched in schizophrenia genome-wide risk genes. Literature-based analysis was conducted to construct molecular pathways connecting miR-9-5p and schizophrenia. We found that the expression levels of miR-9-5p were down-regulated in the peripheral blood of schizophrenia patients compared with those in healthy controls. miR-9-5p can regulate 24 out of the 1136 genome-wide risk genes of schizophrenia, which was higher than by chance (hypergeometric test P = 4.09E-06). The literature-based analysis showed that quantitative genetic changes driven by miR-9 exert more inhibitory (the IL1B, ABCB1, FGFR1 genes) than promoting (the INS gene) effects on schizophrenia, suggesting that miR-9 may protect against schizophrenia. Our results suggest that miR-9-5p deficiency may contribute to the development of schizophrenia.

The emerging role of exosomes in Schizophrenia

Schizophrenia (SCZ), a serious mental disorder, is one of the leading causes of disease burden worldwide. Exosomes, as a natural nanocarrier, are able to cross the blood-brain barrier (BBB) and play a key bridging role in central nervous system (CNS) communication, participating in important physiological processes such as neural regeneration, prominent plasticity, axonal support, and neuroinflammation. In recent years, exosomes have received widespread attention in the field of neurodegenerative diseases and mental disorders, especially Alzheimer's disease. However, there are few reviews on exosomes and SCZ. Therefore, we conducted a literature search in PubMed and Web of Science using the following search terms: "schizophrenia", "mental disorder", "central system", "exosome", "extracellular vesicles" to identify publications from January 2010 to December 2022. Our review summarized exosomes secreted by different cell types in the CNS and the double-edged role of exosomes in the development of SCZ, and discussed their future potential as biomarkers and therapeutic targets. In conclusion, this article provides an up-to-date overview of the current research on the involvement of exosomes in SCZ, while also highlighting the challenges that are currently faced in this field.

MicroRNA schizophrenia: Etiology, biomarkers and therapeutic targets

The three sets of symptoms associated with schizophrenia-positive, negative, and cognitive-are burdensome and have serious effects on public health, which affects up to 1% of the population. It is now commonly believed that in addition to the traditional dopaminergic mesolimbic pathway, the etiology of schizophrenia also includes neuronal networks, such as glutamate, GABA, serotonin, BDNF, oxidative stress, inflammation and the immune system. Small noncoding RNA molecules called microRNAs (miRNAs) have come to light as possible participants in the pathophysiology of schizophrenia in recent years by having an impact on these systems. These small RNAs regulate the stability and translation of hundreds of target transcripts, which has an impact on the entire gene network. There may be improved approaches to treat and diagnose schizophrenia if it is understood how these changes in miRNAs alter the critical related signaling pathways that drive the development and progression of the illness.

Proteomic signatures of schizophrenia-sourced iPSC-derived neural cells and brain organoids are similar to patients' postmortem brains

BACKGROUND

Schizophrenia is a complex and severe neuropsychiatric disorder, with a wide range of debilitating symptoms. Several aspects of its multifactorial complexity are still unknown, and some are accepted to be an early developmental deficiency with a more specifically neurodevelopmental origin. Understanding the timepoints of disturbances during neural cell differentiation processes could lead to an insight into the development of the disorder. In this context, human brain organoids and neural cells differentiated from patient-derived induced pluripotent stem cells are of great interest as a model to study the developmental origins of the disease.

RESULTS

Here we evaluated the differential expression of proteins of schizophrenia patient-derived neural progenitors (NPCs), early neurons, and brain organoids in comparison to healthy individuals. Using bottom-up shotgun proteomics with a label-free approach for quantitative analysis, we found multiple dysregulated proteins since NPCs, modified, and disrupted the 21DIV neuronal differentiation, and cerebral organoids. Our experimental methods have shown impairments in pathways never before found in patient-derived induced pluripotent stem cells studies, such as spliceosomes and amino acid metabolism; but also, those such as axonal guidance and synaptogenesis, in line with postmortem tissue studies of schizophrenia patients.

CONCLUSION

In conclusion, here we provide comprehensive, large-scale, protein-level data of different neural cell models that may uncover early events in brain development, underlying several of the mechanisms within the origins of schizophrenia.

Identifying crucial biomarkers in peripheral blood of schizophrenia and screening therapeutic agents by comprehensive bioinformatics analysis

Schizophrenia (SCZ) is a sophisticated neurodevelopmental disorder, but the mechanisms remain ambiguous. Thus, we analyzed the transcriptomic datasets to investigate the molecular mechanisms of SCZ to pinpoint novel biomarkers and suggest treatment agents. Four peripheral blood datasets were retrieved from the Gene Expression Omnibus (GEO) database, altogether 27 robust Differentially Expressed Genes (DEGs) were ascertained by robust rank aggregation (RRA) methodology. Enrichment analysis, which performed by Enrichr platform, demonstrated that DEGs are predominantly engaged in immune and inflammatory. Protein-protein interaction (PPI) network was constructed by STRING then visualized by Cytoscape. Hub genes identified by cytohubba plug-in were CXCL2, TLR9, SLPI, LY96, G0S2, EGR2, SELENBP1, NDUFA4, GNLY, CCL22. CIBERSORT algorithm was applied to evaluate the situation of immune infiltration, which revealed differences in T-cell CD8, T-cell CD4 memory resting and macrophage M0. The NetworkAnalyst platform was adopted to detect transcription factors (TFs), microRNAs (miRNAs), diseases and chemicals that interact with DEGs, while drugs interacted with DEGs were detected by Enrichr. TFs such as FOXC1, GATA2, NFIC, USF2, E2F1, miRNAs like mir-16-5p, mir-1-3p, mir-124-3p, mir-155-5p, mir-27a-3p are essential in the regulation of DEGs. mir-367-SMAD7-EGR1, mir-367-SMAD7-ARNT, mir-21-SMAD7-EGR1 may be promising biomarkers for SCZ. DEGs were intimately associated with Myocardial Ischemia, Inflammation, Reperfusion Injury. Chemicals such as VPA, cyclosporine, Aflatoxin B1, arsenic trioxide, drugs like diphenylpyraline, trimethoprim, 4-Aminobenzohydrazide, lanatoside C, may have significant implications for treatment of SCZ. These results would shed light on the molecular mechanisms of SCZ and suggest promising diagnostic biomarkers in peripheral blood and therapeutic tactics.

Convergent lines of evidence supporting involvement of NFKB1 in schizophrenia

OBJECTIVES

NFKB1 was associated with treatment-refractory schizophrenia (SZ) and response to antipsychotics; however, the underlying mechanisms through which NFKB1 confers its risk for SZ are largely unknown. We aimed to investigate the potential role of NFKB1 in SZ.

METHODS

In the present study, we investigated the association of the risk SNP rs230529 of NFKB1 with gray matter density and with NFKB1 mRNA levels in various human brain regions. The spatiotemporal expression pattern of NFKB1 in human brains was explored. We constructed a miRNA-NFKB1-target gene regulatory network and analyzed its druggability through targeting NFKB1 for SZ treatment.

RESULTS

NFKB1 showed the highest expression levels in the cerebellum, in which these levels were stratified by genotypes of rs230529. Interestingly, the allelic state of rs230529 was significantly associated with regional gray matter density in multiple brain regions (including the cerebellum), which also differed between patients with schizophrenia and controls. Furthermore, regulatory targets of NFKB1 were enriched among SZ susceptibility genes. A substantial proportion of NFKB1 target genes were subject to combinatorial regulation by NFKB1 and miRNAs, constituting a hybrid NFKB1-miRNA-gene regulatory network. Some components of this network showed expression changes relevant to both the disease and the treatment. Finally, we detected the dynamic changes of NFKB1-miR-155-5p-GSK3B and NFKB1-miR-155-5p/let-7a-5p-IL6 networks in course of the treatment of SZ.

CONCLUSION

Taken together, our findings support the involvement of NFKB1-mediated dysregulation in the development of SZ.

ATAD3B and SKIL polymorphisms associated with antipsychotic-induced QTc interval change in patients with schizophrenia: a genome-wide association study

QTc interval prolongation is one of the most common antipsychotic-induced side effects which could lead to ventricular tachycardia or Torsade de Pointes, even cardiac arrest. There is very limited understanding on the genetic factors that associated with antipsychotic-induced QTc interval change. We conducted a genome-wide association study (GWAS) of antipsychotic-induced QTc interval change among patients with schizophrenia. A total of 2040 patients with schizophrenia were randomly assigned to six groups (olanzapine, risperidone, quetiapine, aripiprazole, ziprasidone, and first-generation antipsychotics; first-generation antipsychotics including haloperidol or perphenazine were also assigned randomly) and received 6-week antipsychotic treatment. We identified two novel loci (rs200050752 in ATAD3B and rs186507741 in SKIL) that were associated with antipsychotic-induced QTc interval change at a genome-wide significance level. The combination of polygenic risk score (PRS), based the GWAS of myocardial infarction from BioBank Japan project, and clinical data (sex, heart rate and QTc interval at baseline) could be applied to predict whether patients with schizophrenia have QTc interval prolongation (10 ms was applied as threshold, P < 0.001, area under the curve [AUC] was 0.797), especially for the first episode patients (P < 0.001, AUC was 0.872). We identified two loci located within genes related to mitochondrial function and cell growth and differentiation, which were both associated with schizophrenia and heart function. The combination of PRS and clinical data could predict whether patients with schizophrenia have the side effect of QTc interval prolongation, which could fundamentally guide the choice of antipsychotic in patients with schizophrenia, especially for the first-episode patients.

Deregulatory miRNA-BDNF Network Inferred from Dynamic Expression Changes in Schizophrenia

(1) Background: Brain-derived neurotrophic factor (BDNF) is one of the promising risk genes for schizophrenia (SZ), a disease with prominent dysregulation of miRNA networks. Here, we present a study of miRNA-BDNF co-expression changes in peripheral blood of SZ patients. (2) Methods: The expression levels of the BDNF mRNA and three validated binding miRNAs—miR-124-3p, miR-132-3p, and miR-206—were quantified in the blood of 48 healthy controls and 32 SZ patients before and after 12 weeks of treatment. The co-expression patterns were evaluated in the three groups. (3) Results: The expression levels of BDNF were significantly downregulated in SZ patients compared to the controls. After the treatment, the expression levels of BDNF were upregulated, while the expression levels of the three miRNAs were downregulated. Co-expression analyses showed positive correlations of this network in the SZ patients, while weak negative correlations were observed in the healthy controls. After the 12-week treatment, the overall correlation between BDNF and the three miRNAs reached the levels comparable to the healthy controls. (4) Conclusions: Our findings suggest the involvement of the miRNA-BDNF network in the onset and treatment of 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.

Rewired Pathways and Disrupted Pathway Crosstalk in Schizophrenia Transcriptomes by Multiple Differential Coexpression Methods

Transcriptomic studies of mental disorders using the human brain tissues have been limited, and gene expression signatures in schizophrenia (SCZ) remain elusive. In this study, we applied three differential co-expression methods to analyze five transcriptomic datasets (three RNA-Seq and two microarray datasets) derived from SCZ and matched normal postmortem brain samples. We aimed to uncover biological pathways where internal correlation structure was rewired or inter-coordination was disrupted in SCZ. In total, we identified 60 rewired pathways, many of which were related to neurotransmitter, synapse, immune, and cell adhesion. We found the hub genes, which were on the center of rewired pathways, were highly mutually consistent among the five datasets. The combinatory list of 92 hub genes was generally multi-functional, suggesting their complex and dynamic roles in SCZ pathophysiology. In our constructed pathway crosstalk network, we found "Clostridium neurotoxicity" and "signaling events mediated by focal adhesion kinase" had the highest interactions. We further identified disconnected gene links underlying the disrupted pathway crosstalk. Among them, four gene pairs (PAK1:SYT1, PAK1:RFC5, DCTN1:STX1A, and GRIA1:MAP2K4) were normally correlated in universal contexts. In summary, we systematically identified rewired pathways, disrupted pathway crosstalk circuits, and critical genes and gene links in schizophrenia transcriptomes.

MicroRNA-195 predicts olanzapine response in drug-free patients with schizophrenia: A prospective cohort study

BACKGROUND

Disturbances of microRNA-195 have been implicated in the pathogenesis of schizophrenia. However, microRNA-195 levels in schizophrenia are controversial.

AIMS

To the best of our knowledge, this is the first study to examine microRNA-195 levels in untreated schizophrenia patients and their relationship to olanzapine response.

METHODS

We recruited 81 untreated schizophrenia patients and 96 healthy controls. The patients received 2 months olanzapine treatment. MicroRNA-195 levels in peripheral blood mononuclear cells were measured using quantitative real-time polymerase chain reaction testing. Psychiatric symptoms were assessed using the Positive and Negative Syndrome Scale.

RESULTS

No significant differences in microRNA-195 levels were found between patients and healthy controls (p > 0.05). Olanzapine significantly reduced microRNA-195 levels after 2 months treatment (p = 0.003). Interestingly, microRNA-195 levels decreased significantly in responders (p = 0.010), but not in non-responders (p > 0.05). Both baseline microRNA-195 levels (p = 0.027, p = 0.030) and the reduction rate of microRNA-195 levels (p = 0.034, p = 0.044) were positively associated with the reduction rate of Positive and Negative Syndrome Scale total score and general psychopathological subscale score. Multiple stepwise regression analysis revealed that baseline microRNA-195 level was an independent contributor to the reduction in Positive and Negative Syndrome Scale total score and the general psychopathological subscale score (p = 0.018, p = 0.030). Finally, logistic regression analysis suggested that baseline microRNA-195 level can serve as a biomarker for response to olanzapine (p = 0.037).

CONCLUSIONS

Our data indicate that microRNA-195 level may predict symptomatic improvement and olanzapine response in schizophrenia patients, suggesting that microRNA-195 should be considered as a potential therapeutic target for antipsychotics.

Epigenetic mechanisms in schizophrenia and other psychotic disorders: a systematic review of empirical human findings

Schizophrenia and other psychotic disorders are highly debilitating psychiatric conditions that lack a clear etiology and exhibit polygenic inheritance underlain by pleiotropic genes. The prevailing explanation points to the interplay between predisposing genes and environmental exposure. Accumulated evidence suggests that epigenetic regulation of the genome may mediate dynamic gene-environment interactions at the molecular level by modulating the expression of psychiatric phenotypes through transcription factors. This systematic review summarizes the current knowledge linking schizophrenia and other psychotic disorders to epigenetics, based on PubMed and Web of Science database searches conducted according to the PRISMA guidelines. Three groups of mechanisms in case-control studies  of human tissue (i.e., postmortem brain and bio-fluids) were considered: DNA methylation, histone modifications, and non-coding miRNAs. From the initial pool of 3,204 records, 152 studies met our inclusion criteria (11,815/11,528, 233/219, and 2,091/1,827 cases/controls for each group, respectively). Many of the findings revealed associations with epigenetic modulations of genes regulating neurotransmission, neurodevelopment, and immune function, as well as differential miRNA expression (e.g., upregulated miR-34a, miR-7, and miR-181b). Overall, actual evidence moderately supports an association between epigenetics and schizophrenia and other psychotic disorders. However, heterogeneous results and cross-tissue extrapolations call for future work. Integrating epigenetics into systems biology may critically enhance research on psychosis and thus our understanding of the disorder. This may have implications for psychiatry in risk stratification, early recognition, diagnostics, precision medicine, and other interventional approaches targeting epigenetic fingerprints.

Post-translational protein modifications in schizophrenia

Research investigating the pathophysiology of schizophrenia has not yet precisely defined the molecular phenotype of this disorder. Many studies have investigated cellular dysfunction by examining expression levels of molecular targets in postmortem patient brain; however, inconsistencies between transcript and protein measures in schizophrenia are common in the field and represent a challenge to the identification of a unified model of schizophrenia pathogenesis. In humans, >4800 unique proteins are expressed, and the majority of these are modified by glycans and/or lipids. Estimates indicate ~70% of all eukaryotic proteins are modified by at least one type of glycosylation, while nearly 20% of all proteins are known to be lipid-modified. Protein post-translational modification (PTM) by glycosylation and lipidation rely on the spatiotemporal colocalization of enzyme, substrate, and glycan or lipid donor molecule and do not require an upstream “blueprint” or specialized processing machinery for synthesis. Glycan and lipid PTMs can thus facilitate cellular adaptation to environmental signals more rapidly than changes of gene or protein expression, and can significantly impact the localization, function, and interactions of modified substrates, though relatively few studies in schizophrenia have evaluated the PTM status of target proteins. A growing body of literature reports glycosylation and lipidation abnormalities in schizophrenia brain as well as in patient peripheral fluids. In this review, we explain the functional significance of key glycan and lipid PTMs and summarize current findings associated with abnormal glycosylation and lipidation in this illness.

Weighted gene co-expression network analysis identifies specific modules and hub genes related to subsyndromal symptomatic depression

Objectives: The identification of the potential molecule targets for subsyndromal symptomatic depression (SSD) is critical for improving the effective clinical treatment on the mental illness. In the current study, we mined the genome-wide expression profiling and investigated the novel biological pathways associated with SSD.Methods: Expression of differentially expressed genes (DEGs) were analysed with microarrays of blood tissue cohort of eight SSD patients and eight healthy subjects. The gene co-expression is calculated by WGCNA, an R package software. The function of the genes was annotated by gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.Results: We identified 11 modules from the 9,427 DEGs. Three co-expression modules (blue, cyan and red) showed striking correlation with the phenotypic trait between SSD and healthy controls. Gene ontology and KEGG pathway analysis demonstrated that the function of these three modules was enriched with the pathway of inflammatory response and type II diabetes mellitus. Finally, three hub genes, NT5DC1, SGSM2 and MYCBP, were identified from the blue module as significant genes.Conclusions: This first blood gene expression study in SSD observed distinct patterns between cases and controls which may provide novel insight into understanding the molecular mechanisms of SSD.

The Role of Biomarkers in Psychiatry

Psychiatric illnesses are cognitive and behavioral disorders of the brain. At present, psychiatric diagnosis is based on DSM-5 criteria. Even if endophenotype specificity for psychiatric disorders is discussed, it is difficult to study and identify psychiatric biomarkers to support diagnosis, prognosis, or clinical response to treatment. This chapter investigates the innovative biomarkers of psychiatric diseases for diagnosis and personalized treatment, in particular post-genomic data and proteomic analyses.

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.

Co-expression network modeling identifies key long non-coding RNA and mRNA modules in altering molecular phenotype to develop stress-induced depression in rats

Long non-coding RNAs (lncRNAs) have recently emerged as one of the critical epigenetic controllers, which participate in several biological functions by regulating gene transcription, mRNA splicing, protein interaction, etc. In a previous study, we reported that lncRNAs may play a role in developing depression pathophysiology. In the present study, we have examined how lncRNAs are co-expressed with gene transcripts and whether specific lncRNA/mRNA modules are associated with stress vulnerability or resiliency to develop depression. Differential regulation of lncRNAs and coding RNAs were determined in hippocampi of three group of rats comprising learned helplessness (LH, depression vulnerable), non-learned helplessness (NLH, depression resilient), and tested controls (TC) using a single-microarray-based platform. Weighted gene co-expression network analysis (WGCNA) was conducted to correlate the expression status of protein-coding transcripts with lncRNAs. The associated co-expression modules, hub genes, and biological functions were analyzed. We found signature co-expression networks as well as modules that underlie normal as well as aberrant response to stress. We also identified specific hub and driver genes associated with vulnerability and resilience to develop depression. Altogether, our study provides evidence that lncRNA associated complex trait-specific networks may play a crucial role in developing depression.

Differential Connectivity in Colorectal Cancer Gene Expression Network

BACKGROUND

Colorectal cancer (CRC) is one of the challenging types of cancers; thus, exploring effective biomarkers related to colorectal could lead to significant progresses toward the treatment of this disease.

METHODS

In the present study, CRC gene expression datasets have been reanalyzed. Mutual differentially expressed genes across 294 normal mucosa and adjacent tumoral samples were then utilized in order to build two independent transcriptional regulatory networks. By analyzing the networks topologically, genes with differential global connectivity related to cancer state were determined for which the potential transcriptional regulators including transcription factors were identified.

RESULTS

The majority of differentially connected genes (DCGs) were up-regulated in colorectal transcriptome experiments. Moreover, a number of these genes have been experimentally validated as cancer or CRC-associated genes. The DCGs, including GART, TGFB1, ITGA2, SLC16A5, SOX9, and MMP7, were investigated across 12 cancer types. Functional enrichment analysis followed by detailed data mining exhibited that these candidate genes could be related to CRC by mediating in metastatic cascade in addition to shared pathways with 12 cancer types by triggering the inflammatory events.

DISCUSSION

Our study uncovered correlated alterations in gene expression related to CRC susceptibility and progression that the potent candidate biomarkers could provide a link to disease.

Implications of Newly Identified Brain eQTL Genes and Their Interactors in Schizophrenia

Schizophrenia (SCZ) is a devastating genetic mental disorder. Identification of the SCZ risk genes in brains is helpful to understand this disease. Thus, we first used the minimum Redundancy-Maximum Relevance (mRMR) approach to integrate the genome-wide sequence analysis results on SCZ and the expression quantitative trait locus (eQTL) data from ten brain tissues to identify the genes related to SCZ. Second, we adopted the variance inflation factor regression algorithm to identify their interacting genes in brains. Third, using multiple analysis methods, we explored and validated their roles. By means of the aforementioned procedures, we have found that (1) the cerebellum may play a crucial role in the pathogenesis of SCZ and (2) ITIH4 may be utilized as a clinical biomarker for the diagnosis of SCZ. These interesting findings may stimulate novel strategy for developing new drugs against SCZ. It has not escaped our notice that the approach reported here is of use for studying many other genome diseases as well.

Investigating the Molecular Mechanism of Aqueous Extract of Cyclocarya paliurus on Ameliorating Diabetes by Transcriptome Profiling

Diabetes is generally regarded as a metabolic disorder disease caused by various reasons, including pancreas islet injury and lipid metabolism disorders. The aqueous extract of Cyclocarya paliurus leaves (CPAE) was reported to be anti-diabetic. However, the possible molecular mechanisms have not been investigated. To elucidate the anti-diabetic effects of CPAE and the underlying potential mechanisms, we performed transcriptome profiling (RNA-Seq and miRNA-Seq) on the pancreas and liver from non-diabetic, diabetic and diabetic-CPAE rats. Our results demonstrated the CPAE could reduce excessive oxidative stress and inflammation in the pancreas, and maintain the balance of glucose and lipid metabolism in the liver. Transcriptome profiling and regulatory network analysis indicated that CPAE may ameliorate diabetes through improving β-cell survival and strengthening insulin secretion in the pancreas. Meanwhile, CPAE could improve impaired lipid metabolism and reduce excessive oxidative damage in the liver probably through miR-200/375-Aldh1b1/Hps5-Hes1 co-regulatory network. Taken together, our biochemical experiments combined with transcriptome profiling showed that the effects of CPAE on anti-diabetes may work through protecting pancreatic β-cell, improving dyslipidaemia and lipid metabolism disorders.

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.

Exploring Potential Biomarkers Underlying Pathogenesis of Alzheimer's Disease by Differential Co-expression Analysis

BACKGROUND

Alzheimer's Disease (AD) is the most common form of dementia in the elderly. Due to the facts that biological causes of AD are complex in addition to increasing rates of AD worldwide, a deeper understanding of AD etiology is required for AD treatment and diagnosis.

METHODS

To identify molecular pathological alterations in AD brains, GSE36980 series containing microarray data samples from temporal cortex, frontal cortex and hippocampus were downloaded from Gene Expression Omnibus (GEO) database and valid gene symbols were subjected to building a gene co-expression network by a bioinformatics tool known as differential regulation from differential co-expression (DCGL) software package. Then, a network-driven integrative analysis was performed to find significant genes and underlying biological terms.

RESULTS

A total of 17088 unique genes were parsed into three independent differential co-expression networks. As a result, a small number of differentially co-regulated genes mostly in frontal and hippocampus lobs were detected as potential biomarkers related to AD brains. Ultimately differentially co-regulated genes were enriched in biological terms including response to lipid and fatty acid and pathways mainly signaling pathway such as G-protein signaling pathway and glutamate receptor groups II and III. By conducting co-expression analysis, our study identified multiple genes that may play an important role in the pathogenesis of AD.

CONCLUSION

The study aimed to provide a systematic understanding of the potential relationships among these genes and it is hoped that it could aid in AD biomarker discovery.

Diagnostic value of blood-derived microRNAs for schizophrenia: results of a meta-analysis and validation

There is an increasing interest in searching biomarkers for schizophrenia (SZ) diagnosis, which overcomes the drawbacks inherent with the subjective diagnostic methods. MicroRNA (miRNA) fingerprints have been explored for disease diagnosis. We performed a meta-analysis to examine miRNA diagnostic value for SZ and further validated the meta-analysis results. Using following terms: schizophrenia/SZ, microRNA/miRNA, diagnosis, sensitivity and specificity, we searched databases restricted to English language and reviewed all articles published from January 1990 to October 2016. All extracted data were statistically analyzed and the results were further validated with peripheral blood mononuclear cells (PBMNCs) isolated from patients and healthy controls using RT-qPCR and receiver operating characteristic (ROC) analysis. A total of 6 studies involving 330 patients and 202 healthy controls were included for meta-analysis. The pooled sensitivity, specificity and diagnostic odds ratio were 0.81 (95% CI: 0.75-0.86), 0.81 (95% CI: 0.72-0.88) and 18 (95% CI: 9-34), respectively; the positive and negative likelihood ratio was 4.3 and 0.24 respectively; the area under the curve in summary ROC was 0.87 (95% CI: 0.84-0.90). Validation revealed that miR-181b-5p, miR-21-5p, miR-195-5p, miR-137, miR-346 and miR-34a-5p in PBMNCs had high diagnostic sensitivity and specificity in the context of schizophrenia. In conclusion, blood-derived miRNAs might be promising biomarkers for SZ diagnosis.

Progress in genome-wide association studies of schizophrenia in Han Chinese populations

Since 2006, genome-wide association studies of schizophrenia have led to the identification of numerous novel risk loci for this disease. However, there remains a geographical imbalance in genome-wide association studies, which to date have primarily focused on Western populations. During the last 6 years, genome-wide association studies in Han Chinese populations have identified both the sharing of susceptible loci across ethnicities and genes unique to Han Chinese populations. Here, we review recent progress in genome-wide association studies of schizophrenia in Han Chinese populations. Researchers have identified and replicated the sharing of susceptible genes, such as within the major histocompatibility complex, microRNA 137 (MIR137), zinc finger protein 804A (ZNF804A), vaccinia related kinase 2 (VRK2), and arsenite methyltransferase (AS3MT), across both European and East Asian populations. Several copy number variations identified in European populations have also been validated in the Han Chinese, including duplications at 16p11.2, 15q11.2-13.1, 7q11.23, and VIPR2 and deletions at 22q11.2, 1q21.1-q21.2, and NRXN1. However, these studies have identified some potential confounding factors, such as genetic heterogeneity and the effects of natural selection on tetraspanin 18 (TSPAN18) or zinc finger protein 323 (ZNF323), which may explain the population differences in genome-wide association studies. In the future, genome-wide association studies in Han Chinese populations should include meta-analyzes or mega-analyses with enlarged sample sizes across populations, deep sequencing, precision medicine treatment, and functional exploration of the risk genes for schizophrenia.

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.

miRNAs and their role in the correlation between schizophrenia and cancer (Review)

Schizophrenia (SZ) and cancer (Ca) have a broad spectrum of clinical phenotypes and a complex biological background, implicating a large number of genetic and epigenetic factors. SZ is a chronic neurodevelopmental disorder signified by an increase in the expression of apoptotic molecular signals, whereas Ca is conversely characterized by an increase in appropriate molecular signaling that stimulates uncontrolled cell proliferation. The rather low risk of developing Ca in patients suffering from SZ is a hypothesis that is still under debate. Recent evidence has indicated that microRNAs (miRNAs or miRs), a large group of small non-coding oligonoucleotides, may play a significant role in the development of Ca and major psychiatric disorders, such as SZ, bipolar disorder, autism spectrum disorders, suicidality and depression, through their interference with the expression of multiple genes. For instance, the possible role of let-7, miR-98 and miR-183 as biomarkers for Ca and SZ was investigated in our previous research studies. Therefore, further investigations on the expression profiles of these regulatory, small RNA molecules and the molecular pathways through which they exert their control may provide a plausible explanation as to whether there is a correlation between psychiatric disorders and low risk of developing Ca.

Predisposition to treatment response in major depressive episode: A peripheral blood gene coexpression network analysis

Antidepressant efficacy is insufficient, unpredictable and poorly understood in major depressive episode (MDE). Gene expression studies allow for the identification of significantly dysregulated genes but can limit the exploration of biological pathways. In the present study, we proposed a gene coexpression analysis to investigate biological pathways associated with treatment response predisposition and their regulation by microRNAs (miRNAs) in peripheral blood samples of MDE and healthy control subjects. We used a discovery cohort that included 34 MDE patients that were given 12-week treatment with citalopram and 33 healthy controls. Two replication cohorts with similar design were also analyzed. Expression-based gene network was built to define clusters of highly correlated sets of genes, called modules. Association between each module's first principal component of the expression data and clinical improvement was tested in the three cohorts. We conducted gene ontology analysis and miRNA prediction based on the module gene list. Nine of the 59 modules from the gene coexpression network were associated with clinical improvement. The association was partially replicated in other cohorts. Gene ontology analysis demonstrated that 4 modules were associated with cytokine production, acute inflammatory response or IL-8 functions. Finally, we found 414 miRNAs that may regulate one or several modules associated with clinical improvement. By contrast, only 12 miRNAs were predicted to specifically regulate modules unrelated to clinical improvement. Our gene coexpression analysis underlines the importance of inflammation-related pathways and the involvement of a large miRNA program as biological processes predisposing associated with antidepressant response.

MicroRNAs and psychiatric disorders: From aetiology to treatment

The emergence of psychiatric disorders relies on the interaction between genetic vulnerability and environmental adversities. Several studies have demonstrated a crucial role for epigenetics (e.g. DNA methylation, post-translational histone modifications and microRNA-mediated post-transcriptional regulation) in the translation of environmental cues into adult behavioural outcome, which can prove to be harmful thus increasing the risk to develop psychopathology. Within this frame, non-coding RNAs, especially microRNAs, came to light as pivotal regulators of many biological processes occurring in the Central Nervous System, both during the neuronal development as well as in the regulation of adult function, including learning, memory and neuronal plasticity. On these basis, in recent years it has been hypothesised a central role for microRNA modulation and expression regulation in many brain disorders, including neurodegenerative disorders and mental illnesses. Indeed, the aim of the present review is to present the most recent state of the art regarding microRNA involvement in psychiatric disorders. We will first describe the mechanisms that regulate microRNA biogenesis and we will report evidences of microRNA dysregulation in peripheral body fluids, in postmortem brain tissues from patients suffering from psychopathology as well as in animal models. Last, we will discuss the potential to consider microRNAs as putative target for pharmacological intervention, using common psychotropic drugs or more specific tools, with the aim to normalize functions that are disrupted in different psychiatric conditions.