Transcriptome alterations of mitochondrial and coagulation function in schizophrenia by cortical sequencing analysis

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.

What genes are differentially expressed in individuals with schizophrenia? A systematic review

Schizophrenia is a severe, complex mental disorder characterized by a combination of positive symptoms, negative symptoms, and impaired cognitive function. Schizophrenia is highly heritable (~80%) with multifactorial etiology and complex polygenic genetic architecture. Despite the large number of genetic variants associated with schizophrenia, few causal variants have been established. Gaining insight into the mechanistic influences of these genetic variants may facilitate our ability to apply these findings to prevention and treatment. Though there have been more than 300 studies of gene expression in schizophrenia over the past 15 years, none of the studies have yielded consistent evidence for specific genes that contribute to schizophrenia risk. The aim of this work is to conduct a systematic review and synthesis of case-control studies of genome-wide gene expression in schizophrenia. Comprehensive literature searches were completed in PubMed, EmBase, and Web of Science, and after a systematic review of the studies, data were extracted from those that met the following inclusion criteria: human case-control studies comparing the genome-wide transcriptome of individuals diagnosed with schizophrenia to healthy controls published between January 1, 2000 and June 30, 2020 in the English language. Genes differentially expressed in cases were extracted from these studies, and overlapping genes were compared to previous research findings from the genome-wide association, structural variation, and tissue-expression studies. The transcriptome-wide analysis identified different genes than those previously reported in genome-wide association, exome sequencing, and structural variation studies of schizophrenia. Only one gene, GBP2, was replicated in five studies. Previous work has shown that this gene may play a role in immune function in the etiology of schizophrenia, which in turn could have implications for risk profiling, prevention, and treatment. This review highlights the methodological inconsistencies that impede valid meta-analyses and synthesis across studies. Standardization of the use of covariates, gene nomenclature, and methods for reporting results could enhance our understanding of the potential mechanisms through which genes exert their influence on the etiology of schizophrenia. Although these results are promising, collaborative efforts with harmonization of methodology will facilitate the identification of the role of genes underlying schizophrenia.

Bioinformatics analysis of long non-coding RNA-associated competing endogenous RNA network in schizophrenia

Schizophrenia (SCZ) is a serious psychiatric condition with a 1% lifetime risk. SCZ is one of the top ten global causes of disabilities. Despite numerous attempts to understand the function of genetic factors in SCZ development, genetic components in SCZ pathophysiology remain unknown. The competing endogenous RNA (ceRNA) network has been demonstrated to be involved in the development of many kinds of diseases. The ceRNA hypothesis states that cross-talks between coding and non-coding RNAs, including long non-coding RNAs (lncRNAs), via miRNA complementary sequences known as miRNA response elements, creates a large regulatory network across the transcriptome. In the present study, we developed a lncRNA-related ceRNA network to elucidate molecular regulatory mechanisms involved in SCZ. Microarray datasets associated with brain regions (GSE53987) and lymphoblasts (LBs) derived from peripheral blood (sample set B from GSE73129) of SCZ patients and control subjects containing information about both mRNAs and lncRNAs were downloaded from the Gene Expression Omnibus database. The GSE53987 comprised 48 brain samples taken from SCZ patients (15 HPC: hippocampus, 15 BA46: Brodmann area 46, 18 STR: striatum) and 55 brain samples taken from control subjects (18 HPC, 19 BA46, 18 STR). The sample set B of GSE73129 comprised 30 LB samples (15 patients with SCZ and 15 controls). Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the limma package of the R software. Using DIANA-LncBase, Human MicroRNA Disease Database (HMDD), and miRTarBase, the lncRNA- associated ceRNA network was generated. Pathway enrichment of DEmRNAs was performed using the Enrichr tool. We developed a protein-protein interaction network of DEmRNAs and identified the top five hub genes by the use of STRING and Cytoscape, respectively. Eventually, the hub genes, DElncRNAs, and predictive miRNAs were chosen to reconstruct the subceRNA networks. Our bioinformatics analysis showed that twelve key DEmRNAs, including BDNF, VEGFA, FGF2, FOS, CD44, SOX2, NRAS, SPARC, ZFP36, FGG, ELAVL1, and STARD13, participate in the ceRNA network in SCZ. We also identified DLX6-AS1, NEAT1, MINCR, LINC01094, DLGAP1-AS1, BABAM2-AS1, PAX8-AS1, ZFHX4-AS1, XIST, and MALAT1 as key DElncRNAs regulating the genes mentioned above. Furthermore, expression of 15 DEmRNAs (e.g., ADM and HLA-DRB1) and one DElncRNA (XIST) were changed in both the brain and LB, suggesting that they could be regarded as candidates for future biomarker studies. The study indicated that ceRNAs could be research candidates for investigating SCZ molecular pathways.

Identification of DNA Methylation Changes That Predict Onset of Post-traumatic Stress Disorder and Depression Following Physical Trauma

Post-traumatic stress disorder (PTSD) and major depressive disorder (MDD) are commonly experienced after exposure to highly stressful events, including physical trauma, yet, biological predictors remain elusive. Methylation of DNA may provide key insights, as it likely is reflective of factors that may increase the risk in trauma patients, as DNA methylation is altered by previous stressors. Here, we compared DNA methylation patterns using bisulfite sequencing in patients with a physical trauma that required more than a 24-h hospitalization (n = 33). We then compared DNA methylation in patients who developed and compared the following groups (1) PTSD and MDD; n = 12), (2) MDD (patients with MDD only; n = 12), and (3) control (patients who did not have PTSD or MDD; n = 9), determined by the PTSD Checklist (PCL-5) and Quick Inventory of Depressive Symptomatology (QIDS) at 6-months follow-up. We identified 17 genes with hypermethylated cytosine sites and 2 genes with hypomethylated sites in comparison between PTSD and control group. In comparison between MDD and control group, we identified 12 genes with hypermethylated cytosine sites and 6 genes with hypomethylated sites. Demethylation of these genes altered the CREB signaling pathway in neurons and may represent a promising therapeutic development target for PTSD and MDD. Our findings suggest that epigenetic changes in these gene regions potentially relate to the onset and symptomology of PTSD and MDD and could be used as potential biomarkers in predicting the onset of PTSD or MDD following traumatic events.

Methylation factor MRPL15 identified as a potential biological target in Alzheimer's disease

Alzheimer’s disease (AD) is the most common form of dementia. However, the molecular basis of the development and progression of AD is still unclear. To elucidate the molecular processes related to AD, we obtained the expression profiles and analyzed the differentially expressed genes (DEGs). The genes potentially involved in the AD process were identified by PPI network and STEM analysis. The molecular mechanisms related to the recognition of AD were determined by GSEA and enrichment analysis. The differences from immune cells in AD were calculated. The methylation factors were identified by methylation difference analysis. Among them, MRPL15 was identified as suitable for diagnosing AD. Its expression trend had been verified in GSE5281. Importantly, MRPL15 was also a methylation factor. In addition, macrophages and neutrophils were up-regulated in AD patients. This was consistent with previous immune inflammation responses identified as being involved in the development of AD. The results of the present study revealed the genetic changes and molecular mechanisms involved in the process of the development and deterioration of AD patients. The potential AD risk genes and potential biological targets were identified. It provided evidence that immune inflammation and immune cells play an important role in AD.

Brain-immune interactions in neuropsychiatric disorders: Lessons from transcriptome studies for molecular targeting

Understanding the pathophysiological mechanisms of neuropsychiatric disorders has been a challenging quest for neurobiologists. Recent years have witnessed enormous technological advances in the field of neuroimmunology, blurring boundaries between the central nervous system and the periphery. Consequently, the discipline has expanded to cover interactions between the nervous and immune systems in health and diseases. The complex interplay between the peripheral and central immune pathways in neuropsychiatric disorders has recently been documented in various studies, but the genetic determinants remain elusive. Recent transcriptome studies have identified dysregulated genes involved in peripheral immune cell activation, blood-brain barrier integrity, glial cell activation, and synaptic plasticity in major depressive disorder, bipolar disorder, autism spectrum disorder, and schizophrenia. Herein, the key transcriptomic techniques applied in investigating differentially expressed genes and pathways responsible for altered brain-immune interactions in neuropsychiatric disorders are discussed. The application of transcriptomics that can aid in identifying molecular targets in various neuropsychiatric disorders is highlighted.

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

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

Psychosis-associated DNA methylomic variation in Alzheimer's disease cortex

Psychotic symptoms are a common and debilitating feature of Alzheimer's disease (AD) and are associated with a more rapid course of decline. Current evidence from postmortem and neuroimaging studies implicates frontal, temporal, and parietal lobes, with reported disruptions in monoaminergic pathways. However, the molecular mechanisms underlying this remain unclear. In the present study, we investigated methylomic variation associated with AD psychosis in 3 key brain regions implicated in the etiology of psychosis (prefrontal cortex, entorhinal cortex, and superior temporal gyrus) in postmortem brain samples from 29 AD donors with psychosis and 18 matched AD donors without psychosis. We identified psychosis-associated methylomic changes in a number of loci, with these genes being enriched in known schizophrenia-associated genetic and epigenetic variants. One of these known loci resided in the AS3MT gene-previously implicated in schizophrenia in a large GWAS meta-analysis. We used bisulfite-pyrosequencing to confirm hypomethylation across 4 neighboring CpG sites in the ASM3T gene. Finally, our regional analysis nominated multiple CpG sites in TBX15 and WT1, which are genes that have been previously implicated in AD. Thus one potential implication from our study is whether psychosis-associated variation drives reported associations in AD case-control studies.

Altered Expression of a Unique Set of Genes Reveals Complex Etiology of Schizophrenia

Background: The etiology of schizophrenia is extensively debated, and multiple factors have been contended to be involved. A panoramic view of the contributing factors in a genome-wide study can be an effective strategy to provide a comprehensive understanding of its causality. Materials and Methods: GSE53987 dataset downloaded from GEO-database, which comprised mRNA expression data of post-mortem brain tissue across three regions from control (C) and age-matched subjects (T) of schizophrenia (N = Hippocampus [HIP]: C-15, T-18, Prefrontal cortex [PFC]: C-15, T-19, Associative striatum [STR]: C-18, T-18). Bio-conductor-affy-package used to compute mRNA expression, and further t-test applied to investigate differential gene expression. The analysis of the derived genes performed using the PANTHER Classification System and NCBI database. Further, a protein interactome analysis of the derived gene set was performed using STRING v10 database (https://string-db.org/) Results: A set of 40 genes showed significantly altered (p < 0.01) expression across all three brain regions. The analyses unraveled genes implicated in biological processes and events, and molecular pathways relating basic neuronal functions. Conclusions: The aberrant expression of genes maintaining basic cell machinery explains compromised neuronal processing in SCZ.

The difference in serum proteomes in schizophrenia and bipolar disorder

BACKGROUND

Purpose of study is revealing significant differences in serum proteomes in schizophrenia and bipolar disorder (BD).

RESULTS

Quantitative mass-spectrometry based proteomic analysis was used to quantify proteins in the blood serum samples after the depletion of six major blood proteins. Comparison of proteome profiles of different groups revealed 27 proteins being specific for schizophrenia, and 18 - for BD. Protein set in schizophrenia was mostly associated with immune response, cell communication, cell growth and maintenance, protein metabolism and regulation of nucleic acid metabolism. Protein set in BD was mostly associated with immune response, regulating transport processes across cell membrane and cell communication, development of neurons and oligodendrocytes and cell growth. Concentrations of ankyrin repeat domain-containing protein 12 (ANKRD12) and cadherin 5 in serum samples were determined by ELISA. Significant difference between three groups was revealed in ANKRD12 concentration (p = 0.02), with maximum elevation of ANKRD12 concentration (median level) in schizophrenia followed by BD. Cadherin 5 concentration differed significantly (p = 0.035) between schizophrenic patients with prevailing positive symptoms (4.78 [2.71, 7.12] ng/ml) and those with prevailing negative symptoms (1.86 [0.001, 4.11] ng/ml).

CONCLUSIONS

Our results are presumably useful for discovering the new pathways involved in endogenous psychotic disorders.

Gene expression study of mitochondrial complex I in schizophrenia and paranoid personality disorder

OBJECTIVES

The aetiology and molecular mechanisms of schizophrenia (SCZ) and paranoid personality disorder (PPD) are not yet clarified. The present study aimed to assess the role of mitochondrial complex I and cell bioenergetic pathways in the aetiology and characteristics of SCZ and PPD.

METHODS

mRNA levels of all genomic and mitochondrial genes which encode mitochondrial complex I subunits (44 genes) were assessed in blood in 634 SCZ, 340 PPD patients and 528 non-psychiatric subjects using quantitative real-time PCR, and associated comprehensive psychiatric, neurological and biochemical assessments.

RESULTS

Significant expression changes of 18 genes in SCZ patients and 11 genes in PPD patients were detected in mitochondrial complex I. Most of these genes were novel candidate genes for SCZ and PPD. Several correlations between mRNA levels and severity of symptoms, drug response, deficits in attention, working memory, executive functions and brain activities were found.

CONCLUSIONS

Deregulations of both core and supernumerary subunits of complex I are involved in the aetiology of SCZ and PPD. These deregulations have effects on brain activity as well as disorder characteristics.

Polygenic risk score, genome-wide association, and gene set analyses of cognitive domain deficits in schizophrenia

This study assessed genetic contributions to six cognitive domains, identified by the MATRICS Cognitive Consensus Battery as relevant for schizophrenia, cognition-enhancing, clinical trials. Psychiatric Genomics Consortium Schizophrenia polygenic risk scores showed significant negative correlations with each cognitive domain. Genome-wide association analyses identified loci associated with attention/vigilance (rs830786 within HNF4G), verbal memory (rs67017972 near NDUFS4), and reasoning/problem solving (rs76872642 within HDAC9). Gene set analysis identified unique and shared genes across cognitive domains. These findings suggest involvement of common and unique mechanisms across cognitive domains and may contribute to the discovery of new therapeutic targets to treat cognitive deficits in schizophrenia.

Frequency and association of mitochondrial genetic variants with neurological disorders

Mitochondria are small cytosolic organelles and the main source of energy production for the cells, especially in the brain. This organelle has its own genome, the mitochondrial DNA (mtDNA), and genetic variants in this molecule can alter the normal energy metabolism in the brain, contributing to the development of a wide assortment of Neurological Disorders (ND), including neurodevelopmental syndromes, neurodegenerative diseases and neuropsychiatric disorders. These ND are comprised by a heterogeneous group of syndromes and diseases that encompass different cognitive phenotypes and behavioral disorders, such as autism, Asperger's syndrome, pervasive developmental disorder, attention deficit hyperactivity disorder, Huntington disease, Leigh Syndrome and bipolar disorder. In this work we carried out a Systematic Literature Review (SLR) to identify and describe the mitochondrial genetic variants associated with the occurrence of ND. Most of genetic variants found in mtDNA were associated with Single Nucleotide Polimorphisms (SNPs), ~79%, with ~15% corresponding to deletions, ~3% to Copy Number Variations (CNVs), ~2% to insertions and another 1% included mtDNA replication problems and genetic rearrangements. We also found that most of the variants were associated with coding regions of mitochondrial proteins but were also found in regulatory transcripts (tRNA and rRNA) and in the D-Loop replication region of the mtDNA. After analysis of mtDNA deletions and CNV, none of them occur in the D-Loop region. This SLR shows that all transcribed mtDNA molecules have mutations correlated with ND. Finally, we describe that all mtDNA variants found were associated with deterioration of cognitive (dementia) and intellectual functions, learning disabilities, developmental delays, and personality and behavior problems.

Transcriptomic analysis reveals oxidative phosphorylation activation in an adolescent social isolation rat model

Complex interactions between genetic and environmental factors exert a sustained influence on the pathogenesis of schizophrenia (SCZ). Adolescent social isolation is regarded as a typical paradigm for SCZ. However, the underlying pathological mechanisms are not fully understood. In this study, adolescent Sprague-Dawley (SD) rats were placed in isolation rearing (IR) or social rearing (SR) conditions from postnatal day (PND) 21 to 34 to establish a SCZ disease model and a control model, respectively. Prepulse inhibition (PPI) assays and elevated plus maze tests were performed on PND 56. Next, prefrontal cortex (PFC) tissues were isolated for transcriptomic sequencing and RT-qPCR analyses. The results indicated that adolescent social isolation induced anxious behaviors and disrupted PPIs as well as specific PFC gene expression patterns in adult SD rats. A total of 196 genes were identified as upregulated, and 748 genes were identified as down-regulated in the IR group compared with those in the SR group. Differentially expressed genes (DEGs) were highly enriched in the KEGG pathways associated with the comorbidity of neurological disorder and oxidative phosphorylation (OXPHOS); 26 out of 27 comorbid neurological disorder-associated DEGs overlapped with 31 OXPHOS-associated DEGs. Those 26 overlapping DEGs were all upregulated in the IR group and could easily distinguish the IR group from the SR group; 6 of these DEGs (COX7C, NDUFB11, NDUFA2, NDUFC2, ATP5C1, and COX6A1) were verified by RT-qPCR. Here, we provide a systematic overview of gene expression alterations in adolescent-social-isolation-induced SCZ (ASI-SCZ), which suggests that genes that are associated with the comorbidity of neurological disorders, especially OXPHOS-related genes, contribute to the pathogenesis of ASI-SCZ.

Abnormalities in Prefrontal Cortical Gene Expression Profiles Relevant to Schizophrenia in MK-801-Exposed C57BL/6 Mice

MK-801, a non-competitive NMDA receptor (NMDAR) antagonist, disturbs NMDAR function in rodents and induces psychological and behavioral changes similar to schizophrenia (SCZ). However, the effects of MK-801 treatment on gene expression are largely unknown. Here we performed RNA-sequencing on the prefrontal cortex of MK-801-exposed male mice in order to analyze gene expression and co-expression patterns related to SCZ and to identify mechanisms that underlie the molecular etiology of this disorder. Transcriptome analysis revealed that the differentially expressed genes were more often associated with biological processes that included postsynaptic transmission, immune system process, response to external stimulus and hemostasis. In order to extract comprehensive biological information, we used an approach for biclustering, called FABIA, to simultaneously cluster transcriptomic data across genes and conditions. When combined with analyses using DAVID and STRING databases, we found that co-expression patterns were altered in synapse-related genes and genes central to the mitochondrial network. Abnormal co-expression of genes mediating synaptic vesicle cycling could disturb release, uptake and reuptake of glutamate, and the perturbation in co-expression patterns for mitochondrial respiratory chain complexes was extensive. Our study supports the hypothesis that research using MK-801-exposed male mice as an animal model of SCZ offers important insights into the pathogenesis of SCZ.

Transcriptome alterations of prefrontal cortical parvalbumin neurons in schizophrenia

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

How American Nurses Association Code of Ethics informs genetic/genomic nursing

Members of the Ethics and Public Policy Committee of the International Society of Nurses in Genetics prepared this article to assist nurses in interpreting the American Nurses Association (2015) Code of Ethics for Nurses with Interpretive Statements (Code) within the context of genetics/genomics. The Code explicates the nursing profession's norms and responsibilities in managing ethical issues. The nearly ubiquitous application of genetic/genomic technologies in healthcare poses unique ethical challenges for nursing. Therefore, authors conducted literature searches that drew from various professional resources to elucidate implications of the code in genetic/genomic nursing practice, education, research, and public policy. We contend that the revised Code coupled with the application of genomic technologies to healthcare creates moral obligations for nurses to continually refresh their knowledge and capacities to translate genetic/genomic research into evidence-based practice, assure the ethical conduct of scientific inquiry, and continually develop or revise national/international guidelines that protect the rights of individuals and populations within the context of genetics/genomics. Thus, nurses have an ethical responsibility to remain knowledgeable about advances in genetics/genomics and incorporate emergent evidence into their work.

Blood-Based Protein Changes in Childhood Are Associated With Increased Risk for Later Psychotic Disorder: Evidence From a Nested Case-Control Study of the ALSPAC Longitudinal Birth Cohort

The identification of early biological changes associated with the psychotic disorder (PD) is important as it may provide clues to the underlying pathophysiological mechanisms. We undertook the first proteomic profiling of blood plasma samples of children who later develop a PD. Participants were recruited from the UK Avon Longitudinal Study of Parents and Children (ALSPAC) cohort who also participated in psychiatric assessment interviews at age 18. Protein expression levels at age 11 were compared between individuals who developed PD at age 18 (n = 37) with population-based age-matched controls (n = 38). Sixty out of 181 plasma proteins profiled were found to be differentially expressed (P < .05) in children with an outcome of the PD. Thirty-four of these proteins were found to be differentially expressed following correction for multiple comparisons. Pathway analysis implicated the complement and coagulation cascade. A second, targeted proteomic approach was used to verify these findings in age 11 plasma from subjects who reported psychotic experiences at age 18 (n = 40) in comparison to age-matched controls (n = 66). Our findings indicate that the complement and coagulation system is dysregulated in the blood during childhood before the development of the PD.

Epigenetic profiling of human brain differential DNA methylation networks in schizophrenia

Background

Epigenetics of schizophrenia provides important information on how the environmental factors affect the genetic architecture of the disease. DNA methylation plays a pivotal role in etiology for schizophrenia. Previous studies have focused mostly on the discovery of schizophrenia-associated SNPs or genetic variants. As postmortem brain samples became available, more and more recent studies surveyed transcriptomics of the diseases. In this study, we constructed protein-protein interaction (PPI) network using the disease associated SNP (or genetic variants), differentially expressed disease genes and differentially methylated disease genes (or promoters). By combining the different datasets and topological analyses of the PPI network, we established a more comprehensive understanding of the development and genetics of this devastating mental illness.

Results

We analyzed the previously published DNA methylation profiles of prefrontal cortex from 335 healthy controls and 191 schizophrenic patients. These datasets revealed 2014 CpGs identified as GWAS risk loci with the differential methylation profile in schizophrenia, and 1689 schizophrenic differential methylated genes (SDMGs) identified with predominant hypomethylation. These SDMGs, combined with the PPIs of these genes, were constructed into the schizophrenic differential methylation network (SDMN). On the SDMN, there are 10 hypermethylated SDMGs, including GNA13, CAPNS1, GABPB2, GIT2, LEFTY1, NDUFA10, MIOS, MPHOSPH6, PRDM14 and RFWD2. The hypermethylation to differential expression network (HyDEN) were constructed to determine how the hypermethylated promoters regulate gene expression. The enrichment analyses of biochemical pathways in HyDEN, including TNF alpha, PDGFR-beta signaling, TGF beta Receptor, VEGFR1 and VEGFR2 signaling, regulation of telomerase, hepatocyte growth factor receptor signaling, ErbB1 downstream signaling and mTOR signaling pathway, suggested that the malfunctioning of these pathways contribute to the symptoms of schizophrenia.

Conclusions

The epigenetic profiles of DNA differential methylation from schizophrenic brain samples were investigated to understand the regulatory roles of SDMGs. The SDMGs interplays with SCZCGs in a coordinated fashion in the disease mechanism of schizophrenia. The protein complexes and pathways involved in SDMN may be responsible for the etiology and potential treatment targets. The SDMG promoters are predominantly hypomethylated. Increasing methylation on these promoters is proposed as a novel therapeutic approach for schizophrenia.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-016-0229-y) contains supplementary material, which is available to authorized users.

Gene expression profiling of the dorsolateral and medial orbitofrontal cortex in schizophrenia

Schizophrenia is a complex polygenic disorder of unknown etiology. Over 3,000 candidate genes associated with schizophrenia have been reported, most of which being mentioned only once. Alterations in cognitive processing - working memory, metacognition and mentalization - represent a core feature of schizophrenia, which indicates the involvement of the prefrontal cortex in the pathophysiology of this disorder. Hence we compared the gene expression in postmortem tissue from the left and right dorsolateral prefrontal cortex (DLPFC, Brodmann's area 46), and the medial part of the orbitofrontal cortex (MOFC, Brodmann's area 11/12), in six patients with schizophrenia and six control brains. Although in the past decade several studies performed transcriptome profiling in schizophrenia, this is the first study to investigate both hemispheres, providing new knowledge about possible brain asymmetry at the level of gene expression and its relation to schizophrenia. We found that in the left hemisphere, twelve genes from the DLPFC and eight genes from the MOFC were differentially expressed in patients with schizophrenia compared to controls. In the right hemisphere there was only one gene differentially expressed in the MOFC. We reproduce the involvement of previously reported genes TARDBP and HNRNPC in the pathogenesis of schizophrenia, and report seven novel genes: SART1, KAT7, C1D, NPM1, EVI2A, XGY2, and TTTY15. As the differentially expressed genes only partially overlap with previous studies that analyzed other brain regions, our findings indicate the importance of considering prefrontal cortical regions, especially those in the left hemisphere, for obtaining disease-relevant insights.

The cell cycle-related genes as biomarkers for schizophrenia

BACKGROUND

Recent studies suggest that genomic abnormalities such as single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) may elevate the risk of schizophrenia. Such genomic abnormalities often occur during chromosomal DNA replication in the S phase of cell cycle. In addition, several studies showed that abnormal expressions of several cell cycle-related genes are associated with schizophrenia. Therefore, here we compared mRNA expression levels of cell cycle-related genes in peripheral blood cells between patients with schizophrenia and healthy controls.

METHOD

mRNA expression levels of cell cycle-related genes in peripheral blood cells from patients with schizophrenia and healthy controls were measured with quantitative reverse transcription polymerase chain reaction (Q-RT-PCR). The discovery, replication and intervention studies with Q-RT-PCR were performed as follows: discovery (40 cases and 20 controls), replication (82 cases and 74 controls) and intervention (22 cases and 18 controls).

RESULT

Nine genes were identified in the discovery and replication stages as schizophrenia-associated genes. Moreover, the combination of mRNA expression levels of CDK4, MCM7 and POLD4 was identified as a potential biomarker for schizophrenia with multivariate logistic regression analysis. The intervention stage revealed that the mRNA expression levels of these three genes were significantly decreased in the acute state of schizophrenia, and CDK4 was significantly recovered in the remission state of schizophrenia.

CONCLUSION

The combination of mRNA expression levels of three cell cycle-related genes such as CDK4, MCM7 and POLD4 is expected to be a candidate for useful biomarkers for schizophrenia. Especially, the mRNA expression changes of CDK4 may be potential as both trait and state markers for schizophrenia.

Gene expression profiling of the dorsolateral and medial orbitofrontal cortex in schizophrenia

Schizophrenia is a complex polygenic disorder of unknown etiology. Over 3,000 candidate genes associated with schizophrenia have been reported, most of which being mentioned only once. Alterations in cognitive processing - working memory, metacognition and mentalization - represent a core feature of schizophrenia, which indicates the involvement of the prefrontal cortex in the pathophysiology of this disorder. Hence we compared the gene expression in postmortem tissue from the left and right dorsolateral prefrontal cortex (DLPFC, Brodmann's area 46), and the medial part of the orbitofrontal cortex (MOFC, Brodmann's area 11/12), in six patients with schizophrenia and six control brains. Although in the past decade several studies performed transcriptome profiling in schizophrenia, this is the first study to investigate both hemispheres, providing new knowledge about possible brain asymmetry at the level of gene expression and its relation to schizophrenia. We found that in the left hemisphere, twelve genes from the DLPFC and eight genes from the MOFC were differentially expressed in patients with schizophrenia compared to controls. In the right hemisphere there was only one gene differentially expressed in the MOFC. We reproduce the involvement of previously reported genes TARDBP and HNRNPC in the pathogenesis of schizophrenia, and report seven novel genes: SART1, KAT7, C1D, NPM1, EVI2A, XGY2, and TTTY15. As the differentially expressed genes only partially overlap with previous studies that analyzed other brain regions, our findings indicate the importance of considering prefrontal cortical regions, especially those in the left hemisphere, for obtaining disease-relevant insights.

RNA Sequencing in Schizophrenia

Schizophrenia (SCZ) is a serious psychiatric disorder that affects 1% of general population and places a heavy burden worldwide. The underlying genetic mechanism of SCZ remains unknown, but studies indicate that the disease is associated with a global gene expression disturbance across many genes. Next-generation sequencing, particularly of RNA sequencing (RNA-Seq), provides a powerful genome-scale technology to investigate the pathological processes of SCZ. RNA-Seq has been used to analyze the gene expressions and identify the novel splice isoforms and rare transcripts associated with SCZ. This paper provides an overview on the genetics of SCZ, the advantages of RNA-Seq for transcriptome analysis, the accomplishments of RNA-Seq in SCZ cohorts, and the applications of induced pluripotent stem cells and RNA-Seq in SCZ research.

InCoB2014: mining biological data from genomics for transforming industry and health

The 13th International Conference on Bioinformatics (InCoB2014) was held for the first time in Australia, at Sydney, July 31-2 August, 2014. InCoB is the annual scientific gathering of the Asia-Pacific Bioinformatics Network (APBioNet), hosted since 2002 in the Asia-Pacific region. Of 106 full papers submitted to the BMC track of InCoB2014, 50 (47.2%) were accepted in BMC Bioinformatics, BMC Genomics and BMC Systems Biology supplements, with three papers in a new BMC Medical Genomics supplement. While the majority of presenters and authors were from Asia and Australia, the increasing number of US and European conference attendees augurs well for the international flavour of InCoB. Next year's InCoB will be held jointly with the Genome Informatics Workshop (GIW), September 9-11, 2015 in Tokyo, Japan, with a view to integrate bioinformatics communities in the region.