Transcriptome study of differential expression in schizophrenia

Differential microRNA expression in the SH-SY5Y human cell model as potential biomarkers for Huntington's disease

Huntington's disease (HD) is caused by an expansion of CAG trinucleotide repeat in the HTT gene; the exact pathogenesis of HD currently remains unclear. One of the promising directions in the study of HDs is to determine the molecular mechanism underlying the development and role of microRNAs (miRNAs). This study aimed to identify the profile of miRNAs in an HD human cell line model as diagnostic biomarkers for HD. To study HD, the human SH-SY5Y HD cell model is based on the expression of two different forms: pEGFP-Q23 and pEGFP-Q74 of HTT. The expression of Htt protein was confirmed using aggregation assays combined with immunofluorescence and Western blotting methods. miRNA levels were measured in SH-SY5Y neuronal cell model samples stably expressing Q23 and Q74 using the extraction-free HTG EdgeSeq protocol. A total of 2083 miRNAs were detected, and 354 (top 18 miRNAs) miRNAs were significantly differentially expressed (DE) (p < 0.05) in Q23 and Q74 cell lines. A majority of the miRNAs were downregulated in the HD cell model. Moreover, we revealed that six DE miRNAs target seven genes (ATN1, GEMIN4, EFNA5, CSMD2, CREBBP, ATXN1, and B3GNT) that play important roles in neurodegenerative disorders and showed significant expression differences in mutant Htt (Q74) when compared to wild-type Htt (Q23) using RT-qPCR (p < 0.05 and 0.01). We demonstrated the most important DE miRNA-mRNA profiles, interaction binding sites, and their related pathways in HD using experimental and bioinformatics methods. This will allow the development of novel diagnostic strategies and provide alternative therapeutic routes for treating HD.

Genetic network analysis indicate that individuals affected by neurodevelopmental conditions have genetic variations associated with ophthalmologic alterations: A critical review of literature

Changes in the nervous system are related to a wide range of mental disorders, which include neurodevelopmental disorders (NDD) that are characterized by early onset mental conditions, such as schizophrenia and autism spectrum disorders and correlated conditions (ASD). Previous studies have shown distinct genetic components associated with diverse schizophrenia and ASD phenotypes, with mostly focused on rescuing neural phenotypes and brain activity, but alterations related to vision are overlooked. Thus, as the vision is composed by the eyes that itself represents a part of the brain, with the retina being formed by neurons and cells originating from the glia, genetic variations affecting the brain can also affect the vision. Here, we performed a critical systematic literature review to screen for all genetic variations in individuals presenting NDD with reported alterations in vision. Using these restricting criteria, we found 20 genes with distinct types of genetic variations, inherited or de novo, that includes SNP, SNV, deletion, insertion, duplication or indel. The variations occurring within protein coding regions have different impact on protein formation, such as missense, nonsense or frameshift. Moreover, a molecular analysis of the 20 genes found revealed that 17 shared a common protein-protein or genetic interaction network. Moreover, gene expression analysis in samples from the brain and other tissues indicates that 18 of the genes found are highly expressed in the brain and retina, indicating their potential role in adult vision phenotype. Finally, we only found 3 genes from our study described in standard public databanks of ophthalmogenetics, suggesting that the other 17 genes could be novel target for vision diseases.

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

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

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.

A functional methylation signature to predict the prognosis of Chinese lung adenocarcinoma based on TCGA

Background

Lung cancer is the leading cause of cancer morbidity and mortality worldwide, however, the individualized treatment is still unsatisfactory. DNA methylation can affect gene regulation and may be one of the most valuable biomarkers in predicting the prognosis of lung adenocarcinoma. This study was aimed to identify methylation CpG sites that may be used to predict lung adenocarcinoma prognosis.

Methods

The Cancer Genome Atlas (TCGA) database was used to detect methylation CpG sites associated with lung adenocarcinoma prognosis and construct a methylation signature model. Then, a Chinese cohort was carried out to estimate the association between methylation and lung adenocarcinoma prognosis. Biological function studies, including demethylation treatment, cell proliferative capacity, and gene expression changes in lung adenocarcinoma cell lines, were further performed.

Results

In the TCGA set, three methylation CpG sites were selected that were associated with lung adenocarcinoma prognosis (cg14517217, cg15386964, and cg18878992). The risk of mortality was increased in lung adenocarcinoma patients with the gradual increase level of methylation signature based on three methylation sites levels (HR = 45.30, 95% CI = 26.69–66.83; p < 0.001). The C‐statistic value increased to 0.77 when age, gender, and other clinical variables were added to the signature to prediction model. A similar situation was confirmed in Chinese lung adenocarcinoma cohort. In the biological function studies, the proliferative capacity of cell lines was inhibited when the cells were demethylated with 5‐aza‐2'‐deoxycytidine (5‐aza‐2dC). The mRNA and protein expression levels of SEPT9 and HIST1H2BH (cg14517217 and cg15386964) were downregulated with different concentrations of 5‐aza‐2dC treatment, while cg18878992 showed the opposite result.

Conclusion

This study is the first to develop a three‐CpG‐based model for lung adenocarcinoma, which is a practical and useful tool for prognostic prediction that has been validated in a Chinese population.

Genetic pleiotropy and the shared pathological features of corticobasal degeneration and progressive supranuclear palsy: a case report and a review of the literature

Though distinct pathological entities, corticobasal degeneration (CBD) and progressive supranuclear palsy (PSP) share multiple biochemical and genetic features suggesting overlapping pathophysiology. We report the case of a patient with an 18-year clinical course consistent with behavioral variant frontotemporal dementia. The neuropathological assessment revealed unclassifiable frontotemporal lobar degeneration with tau-immunoreactive inclusions sharing features of both CBD and PSP. Whole-genome sequencing revealed a unique combination of pleiotropic genetic risk variants associated with both PSP and CBD. These findings support the observation that CBD and PSP share genetic co-expression networks that influence neurodegenerative pathogenesis common to 4R tauopathies.

Altered estradiol-dependent cellular Ca2+ homeostasis and endoplasmic reticulum stress response in Premenstrual Dysphoric Disorder

Premenstrual Dysphoric Disorder (PMDD) is characterized by debilitating mood symptoms in the luteal phase of the menstrual cycle. Prior studies of affected women have implicated a differential response to ovarian steroids. However, the molecular basis of these patients' differential response to hormone remains poorly understood. We performed transcriptomic analyses of lymphoblastoid cell lines (LCLs) derived from women with PMDD and asymptomatic controls cultured under untreated (steroid-free), estradiol-treated (E2), and progesterone-treated (P4) conditions. Weighted gene correlation network analysis (WGCNA) of transcriptomes identified four gene modules with significant diagnosis x hormone interactions, including one enriched for neuronal functions. Next, in a gene-level analysis comparing transcriptional response to hormone across diagnoses, a generalized linear model identified 1522 genes differentially responsive to E2 (E2-DRGs). Among the top 10 E2-DRGs was a physically interacting network (NUCB1, DST, GCC2, GOLGB1) involved in endoplasmic reticulum (ER)-Golgi function. qRT-PCR validation reproduced a diagnosis x E2 interaction (F(1,24)=7.01, p = 0.014) for NUCB1, a regulator of cellular Ca²⁺ and ER stress. Finally, we used a thapsigargin (Tg) challenge assay to test whether E2 induces differences in Ca²⁺ homeostasis and ER stress response in PMDD. PMDD LCLs had a 1.36-fold decrease in Tg-induced XBP1 splicing response compared to controls, and a 1.62-fold decreased response (p = 0.005), with a diagnosis x treatment interaction (F(3,33)=3.51, p = 0.026) in the E2-exposed condition. Altered hormone-dependent in cellular Ca²⁺ dynamics and ER stress may contribute to the pathophysiology of PMDD.

nMAGMA: a network-enhanced method for inferring risk genes from GWAS summary statistics and its application to schizophrenia

MOTIVATION

Annotating genetic variants from summary statistics of genome-wide association studies (GWAS) is crucial for predicting risk genes of various disorders. The multimarker analysis of genomic annotation (MAGMA) is one of the most popular tools for this purpose, where MAGMA aggregates signals of single nucleotide polymorphisms (SNPs) to their nearby genes. In biology, SNPs may also affect genes that are far away in the genome, thus missed by MAGMA. Although different upgrades of MAGMA have been proposed to extend gene-wise variant annotations with more information (e.g. Hi-C or eQTL), the regulatory relationships among genes and the tissue specificity of signals have not been taken into account.

RESULTS

We propose a new approach, namely network-enhanced MAGMA (nMAGMA), for gene-wise annotation of variants from GWAS summary statistics. Compared with MAGMA and H-MAGMA, nMAGMA significantly extends the lists of genes that can be annotated to SNPs by integrating local signals, long-range regulation signals (i.e. interactions between distal DNA elements), and tissue-specific gene networks. When applied to schizophrenia (SCZ), nMAGMA is able to detect more risk genes (217% more than MAGMA and 57% more than H-MAGMA) that are involved in SCZ compared with MAGMA and H-MAGMA, and more of nMAGMA results can be validated with known SCZ risk genes. Some disease-related functions (e.g. the ATPase pathway in Cortex) are also uncovered in nMAGMA but not in MAGMA or H-MAGMA. Moreover, nMAGMA provides tissue-specific risk signals, which are useful for understanding disorders with multitissue origins.

Widespread transcriptional disruption of the microRNA biogenesis machinery in brain and peripheral tissues of individuals with schizophrenia

In schizophrenia, altered transcription in brain and peripheral tissues may be due to altered expression of the microRNA biogenesis machinery genes. In this study, we explore the expression of these genes both at the cerebral and peripheral levels. We used shinyGEO application to analyze gene expression from ten Gene Expression Omnibus datasets, in order to perform differential expression analyses for eight genes encoding the microRNA biogenesis machinery. First, we compared expression of the candidate genes between control subjects and individuals with schizophrenia in postmortem cerebral samples from seven different brain regions. Then, we compared the expression of the candidate genes between control subjects and individuals with schizophrenia in three peripheral tissues. In brain and peripheral tissues of individuals with schizophrenia, we report distinct altered expression patterns of the microRNA biogenesis machinery genes. In the dorsolateral prefrontal cortex, associative striatum and cerebellum of individuals with schizophrenia, we observed an overexpression pattern of some candidate genes suggesting a heightened miRNA production in these brain regions. Additionally, mixed transcriptional abnormalities were identified in the hippocampus. Moreover, in the blood and olfactory epithelium of individuals with schizophrenia, we observed distinct aberrant transcription patterns of the candidate genes. Remarkably, in individuals with schizophrenia, we report DICER1 overexpression in the dorsolateral prefrontal cortex, hippocampus and cerebellum as well as a congruent DICER1 upregulation in the blood compartment suggesting that it may represent a peripheral marker. Transcriptional disruption of the miRNA biogenesis machinery may contribute to schizophrenia pathogenesis both in brain and peripheral tissues.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Identification of Reproducible BCL11A Alterations in Schizophrenia Through Individual-Level Prediction of Coexpression

Previous studies have provided evidence for an alteration of genetic coexpression in schizophrenia (SCZ). However, such analyses have thus far lacked biological specificity for individual genes, which may be critical for identifying illness-relevant effects. Therefore, we applied machine learning to identify gene-specific coexpression differences at the individual subject level and compared these between individuals with SCZ, bipolar disorder, major depressive disorder (MDD), autism spectrum disorder (ASD), and healthy controls. Utilizing transcriptome-wide gene expression data from 21 independent datasets, comprising a total of 9509 participants, we identified a reproducible decrease of BCL11A coexpression across 4 SCZ datasets that showed diagnostic specificity for SCZ when compared with ASD and MDD. We further demonstrate that individual-level coexpression differences can be combined in multivariate coexpression scores that show reproducible illness classification across independent datasets in SCZ and ASD. This study demonstrates that machine learning can capture gene-specific coexpression differences at the individual subject level for SCZ and identify novel biomarker candidates.

Regulation of Janus Kinase 2 by an Inflammatory Bowel Disease Causal Non-coding Single Nucleotide Polymorphism

BACKGROUND AND AIMS

Among the >240 genetic loci described to date which confer susceptibility to inflammatory bowel disease, a small subset have been fine-mapped to an individual, non-coding single nucleotide polymorphism [SNP]. To illustrate a model mechanism by which a presumed-causal non-coding SNP can function, we analysed rs1887428, located in the promoter region of the Janus kinase 2 [JAK2] gene.

METHODS

We utilized comparative affinity purification-mass spectrometry, DNA-protein binding assays, CRISPR/Cas9 genome editing, transcriptome sequencing and methylome quantitative trait locus methods to characterize the role of this SNP.

RESULTS

We determined that the risk allele of rs1887428 is bound by the transcription factor [TF] RBPJ, while the protective allele is bound by the homeobox TF CUX1. While rs188748 only has a very modest influence on JAK2 expression, this effect was amplified downstream through the expression of pathway member STAT5B and epigenetic modification of the JAK2 locus.

CONCLUSION

Despite the absence of a consensus TF-binding motif or expression quantitative trait locus, we have used improved methods to characterize a putatively causal SNP to yield insight into inflammatory bowel disease mechanisms.

PODCAST

This article has an associated podcast which can be accessed at https://academic.oup.com/ecco-jcc/pages/podcast.

Adaptive Fisher method detects dense and sparse signals in association analysis of SNV sets

BACKGROUND

With the development of next generation sequencing (NGS) technology and genotype imputation methods, statistical methods have been proposed to test a set of genomic variants together to detect if any of them is associated with the phenotype or disease. In practice, within the set, there is an unknown proportion of variants truly causal or associated with the disease. There is a demand for statistical methods with high power in both dense and sparse scenarios, where the proportion of causal or associated variants is large or small respectively.

RESULTS

We propose a new association test - weighted Adaptive Fisher (wAF) that can adapt to both dense and sparse scenarios by adding weights to the Adaptive Fisher (AF) method we developed before. Using simulation, we show that wAF enjoys comparable or better power to popular methods such as sequence kernel association tests (SKAT and SKAT-O) and adaptive SPU (aSPU) test. We apply wAF to a publicly available schizophrenia dataset, and successfully detect thirteen genes. Among them, three genes are supported by existing literature; six are plausible as they either relate to other neurological diseases or have relevant biological functions.

CONCLUSIONS

The proposed wAF method is a powerful disease-variants association test in both dense and sparse scenarios. Both simulation studies and real data analysis indicate the potential of wAF for new biological findings.

Overdispersed gene expression in schizophrenia

Schizophrenia (SCZ) is a severe, highly heterogeneous psychiatric disorder with varied clinical presentations. The polygenic genetic architecture of SCZ makes identification of causal variants a daunting task. Gene expression analyses hold the promise of revealing connections between dysregulated transcription and underlying variants in SCZ. However, the most commonly used differential expression analysis often assumes grouped samples are from homogeneous populations and thus cannot be used to detect expression variance differences between samples. Here, we applied the test for equality of variances to normalized expression data, generated by the CommonMind Consortium (CMC), from brains of 212 SCZ and 214 unaffected control (CTL) samples. We identified 87 genes, including VEGFA (vascular endothelial growth factor) and BDNF (brain-derived neurotrophic factor), that showed a significantly higher expression variance among SCZ samples than CTL samples. In contrast, only one gene showed the opposite pattern. To extend our analysis to gene sets, we proposed a Mahalanobis distance-based test for multivariate homogeneity of group dispersions, with which we identified 110 gene sets with a significantly higher expression variability in SCZ, including sets of genes encoding phosphatidylinositol 3-kinase (PI3K) complex and several others involved in cerebellar cortex morphogenesis, neuromuscular junction development, and cerebellar Purkinje cell layer development. Taken together, our results suggest that SCZ brains are characterized by overdispersed gene expression-overall gene expression variability among SCZ samples is significantly higher than that among CTL samples. Our study showcases the application of variability-centric analyses in SCZ research.

The role of genes affected by human evolution marker GNA13 in schizophrenia

Numerous variants associated with increased risk for SCZ have undergone positive selection and were associated with human brain development, but which brain regions and developmental stages were influenced by the positive selection for SCZ risk alleles are unclear. We analyzed SCZ using summary statistics from a genome-wide association study (GWAS) from the Psychiatric Genomics Consortium (PGC). Machine-learning scores were used to investigate two natural-selection scenarios: complete selection (loci where a selected allele has reached fixation) and incomplete selection (loci where a selected allele has not yet reached fixation). Based on the p value of single nucleotide polymorphisms (SNPs) with selection scores in the top 5%, we formed five subgroups: p < 0.0001, 0.001, 0.01, 0.05, or 0.1. We found that 48 and 29 genes (p < 0.0001) in complete and incomplete selection, respectively, were enrichedfor the transcriptionalco-expressionprofilein theprenatal dorsolateral prefrontal cortex (DFC), inferior parietal cortex (IPC), and ventrolateral prefrontal cortex (VFC). Core genes (GNA13, TBC1D19, and ZMYM4) involved in regulating early brain development were identified in these three brain regions. RNA sequencing for primary cortical neurons that were transfected Gna13 overexpressed lentivirus demonstrated that 135 gene expression levels changed in the Gna13 overexpressed groups compared with the controls. Gene-set analysis identified important associations among common variants of these 13 genes, which were associated with neurodevelopment and putamen volume [p = 0.031; family-wise error correction (FWEC)], SCZ (p = 0.022; FWEC). The study indicate that certain SCZ risk alleles were likely to undergo positive selection during human evolution due to their involvement in the development of prenatal DFC, IPC and VFC, and suggest that SCZ is related to abnormal neurodevelopment.

Predicting novel genomic regions linked to genetic disorders using GWAS and chromosome conformation data - a case study of schizophrenia

Genome-wide association studies identified numerous loci harbouring single nucleotide polymorphisms (SNPs) associated with various human diseases, although the causal role of many of them remains unknown. In this paper, we postulate that co-location and shared biological function of novel genes with genes known to associate with a specific phenotype make them potential candidates linked to the same phenotype (“guilt-by-proxy”). We propose a novel network-based approach for predicting candidate genes/genomic regions utilising the knowledge of the 3D architecture of the human genome and GWAS data. As a case study we used a well-studied polygenic disorder ‒ schizophrenia ‒ for which we compiled a comprehensive dataset of SNPs. Our approach revealed 634 novel regions covering ~398 Mb of the human genome and harbouring ~9000 genes. Using various network measures and enrichment analysis, we identified subsets of genes and investigated the plausibility of these genes/regions having an association with schizophrenia using literature search and bioinformatics resources. We identified several genes/regions with previously reported associations with schizophrenia, thus providing proof-of-concept, as well as novel candidates with no prior known associations. This approach has the potential to identify novel genes/genomic regions linked to other polygenic disorders and provide means of aggregating genes/SNPs for further investigation.

From Schizophrenia Genetics to Disease Biology: Harnessing New Concepts and Technologies

Schizophrenia (SZ) is a severe mental disorder afflicting around 1% of the population. It is highly heritable but with complex genetics. Recent research has unraveled a plethora of risk loci for SZ. Accordingly, our conceptual understanding of SZ genetics has been rapidly evolving, from oligogenic models towards polygenic or even omnigenic models. A pressing challenge to the field, however, is the translation of the many genetic findings of SZ into disease biology insights leading to more effective treatments. Bridging this gap requires the integration of genetic findings and functional genomics using appropriate cellular models. Harnessing new technologies, such as the development of human induced pluripotent stem cells (hiPSC) and the CRISPR/Cas-based genome/epigenome editing approach are expected to change our understanding of SZ disease biology to a fundamentally higher level. Here, we discuss some new developments.

Genome-wide association meta-analysis of cocaine dependence: Shared genetics with comorbid conditions

Cocaine dependence is a complex psychiatric disorder that is highly comorbid with other psychiatric traits. Twin and adoption studies suggest that genetic variants contribute substantially to cocaine dependence susceptibility, which has an estimated heritability of 65-79%. Here we performed a meta-analysis of genome-wide association studies of cocaine dependence using four datasets from the dbGaP repository (2085 cases and 4293 controls, all of them selected by their European ancestry). Although no genome-wide significant hits were found in the SNP-based analysis, the gene-based analysis identified HIST1H2BD as associated with cocaine-dependence (10% FDR). This gene is located in a region on chromosome 6 enriched in histone-related genes, previously associated with schizophrenia (SCZ). Furthermore, we performed LD Score regression analysis with comorbid conditions and found significant genetic correlations between cocaine dependence and SCZ, ADHD, major depressive disorder (MDD) and risk taking. We also found, through polygenic risk score analysis, that all tested phenotypes are significantly associated with cocaine dependence status: SCZ (R² = 2.28%; P = 1.21e-26), ADHD (R² = 1.39%; P = 4.5e-17), risk taking (R² = 0.60%; P = 2.7e-08), MDD (R² = 1.21%; P = 4.35e-15), children's aggressive behavior (R² = 0.3%; P = 8.8e-05) and antisocial behavior (R² = 1.33%; P = 2.2e-16). To our knowledge, this is the largest reported cocaine dependence GWAS meta-analysis in European-ancestry individuals. We identified suggestive associations in regions that may be related to cocaine dependence and found evidence for shared genetic risk factors between cocaine dependence and several comorbid psychiatric traits. However, the sample size is limited and further studies are needed to confirm these results.

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.

Proteomic analysis of lymphoblastoid cell lines from schizophrenic patients

Although a number of studies have identified several convincing candidate genes or molecules, the pathophysiology of schizophrenia (SCZ) has not been completely elucidated. Therapeutic optimization based on pathophysiology should be performed as early as possible to improve functional outcomes and prognosis; to detect useful biomarkers for SCZ, which reflect pathophysiology and can be utilized for timely diagnosis and effective therapy. To explore biomarkers for SCZ, we employed fluorescence two-dimensional differential gel electrophoresis (2D-DIGE) of lymphoblastoid cell lines (LCLs) (1st sample set: 30 SCZ and 30 CON). Differentially expressed proteins were sequenced by liquid chromatography tandem-mass spectrometry (LC-MS/MS) and identified proteins were confirmed by western blotting (WB) (1st and 2nd sample set: 60 SCZ and 60 CON). Multivariate logistic regression analysis was performed to identify an optimal combination of biomarkers to create a prediction model for SCZ. Twenty protein spots were differentially expressed between SCZ and CON in 2D-DIGE analysis and 22 unique proteins were identified by LC-MS/MS. Differential expression of eight of 22 proteins was confirmed by WB. Among the eight candidate proteins (HSPA4L, MX1, GLRX3, UROD, MAPRE1, TBCB, IGHM, and GART), we successfully constructed logistic regression models comprised of 4- and 6-markers with good discriminative ability between SCZ and CON. In both WB and gene expression analysis of LCL, MX1 showed reproducibly significant associations. Moreover, Mx1 and its related proinflamatory genes (Mx2, Il1b, and Tnf) were also up-regulated in poly I:C-treated mice. Differentially expressed proteins might be associated with molecular pathophysiology of SCZ, including dysregulation of immunological reactions and potentially provide diagnostic and prognostic biomarkers.

Intracellular Peptides in Cell Biology and Pharmacology

Intracellular peptides are produced by proteasomes following degradation of nuclear, cytosolic, and mitochondrial proteins, and can be further processed by additional peptidases generating a larger pool of peptides within cells. Thousands of intracellular peptides have been sequenced in plants, yeast, zebrafish, rodents, and in human cells and tissues. Relative levels of intracellular peptides undergo changes in human diseases and also when cells are stimulated, corroborating their biological function. However, only a few intracellular peptides have been pharmacologically characterized and their biological significance and mechanism of action remains elusive. Here, some historical and general aspects on intracellular peptides' biology and pharmacology are presented. Hemopressin and Pep19 are examples of intracellular peptides pharmacologically characterized as inverse agonists to cannabinoid type 1 G-protein coupled receptors (CB1R), and hemopressin fragment NFKF is shown herein to attenuate the symptoms of pilocarpine-induced epileptic seizures. Intracellular peptides EL28 (derived from proteasome 26S protease regulatory subunit 4; Rpt2), PepH (derived from Histone H2B type 1-H), and Pep5 (derived from G1/S-specific cyclin D2) are examples of peptides that function intracellularly. Intracellular peptides are suggested as biological functional molecules, and are also promising prototypes for new drug development.

Fine-mapping scan of bipolar disorder susceptibility loci in Latino pedigrees

We previously identified bipolar disorder (BD) susceptibility loci on 8q24, 14q32, and 2q12-14 in a genome-wide nonparametric linkage screen in a Latino cohort. We now perform a fine mapping analysis using a dense map of additional SNPs to identify BD susceptibility genes within these regions. One thousand nine hundred and thirty-eight individuals with Latino ancestry (880 individuals with BD Type I or Schizoaffective, Bipolar Type) from 416 Latino pedigrees from the United States, Mexico, Costa Rica, and Guatemala were genotyped with 3,074 SNPs to provide dense coverage of the 8q24 (11.5 cM), 14q32 (7.5 cM), and 2q12-14 (6.5 cM) chromosomal loci. Single-marker association tests in the presence of linkage were performed using the LAMP software. The top linkage peak (rs7834818; LOD = 5.08, p = 3.30E - 5) and associated single marker (rs2280915, p = 2.70E - 12) were located within FBXO32 on 8q24. On chromosome 2, the top linkage peak (rs6750326; LOD = 5.06, p = 3.50E - 5) and associated single marker (rs11887088, p = 2.90E - 6) were located in intragenic regions near ACTR3 and DPP10. None of the additional markers in the region around chromosome 14q32 met significance levels for linkage or association. We identified six SNPs on 2q12-q14 and one SNP in FBXO32 on 8q24 that were significantly associated with BD in this Latino cohort.

Double-Edged Sword of Tumour Suppressor Genes in Schizophrenia

Schizophrenia (SCZ) is a common psychiatric disorder with polygenetic pathogenesis. Among the many identified candidate genes and loci, the group of tumour suppressor genes has drawn our interest. In this mini-review article, we describe evidence of a correlation between major tumour suppressor genes and SCZ development. Genetic mutations ranging from single nucleotide polymorphisms to large structural alterations have been found in tumour-related genes in patients with SCZ. Epigenetic mechanisms, including DNA methylation/acetylation and microRNA regulation of tumour suppressor genes, have also been implicated in SCZ. Beyond genetic correlations, we hope to establish causal relationships between tumour suppressor gene function and SCZ risk. Accumulating evidence shows that tumour suppressor genes may mediate cell survival and neural development, both of which contribute to SCZ aetiology. Moreover, converging intracellular signalling pathways indicate a role of tumour suppressor genes in SCZ pathogenesis. Tumour suppressor gene function may mediate a direct link between neural development and function and psychiatric disorders, including SCZ. A deeper understanding of how neural cell development is affected by tumour suppressors may lead to improved anti-psychotic drugs.

Dopamine perturbation of gene co-expression networks reveals differential response in schizophrenia for translational machinery

The dopaminergic hypothesis of schizophrenia (SZ) postulates that positive symptoms of SZ, in particular psychosis, are due to disturbed neurotransmission via the dopamine (DA) receptor D2 (DRD2). However, DA is a reactive molecule that yields various oxidative species, and thus has important non-receptor-mediated effects, with empirical evidence of cellular toxicity and neurodegeneration. Here we examine non-receptor-mediated effects of DA on gene co-expression networks and its potential role in SZ pathology. Transcriptomic profiles were measured by RNA-seq in B-cell transformed lymphoblastoid cell lines from 514 SZ cases and 690 controls, both before and after exposure to DA ex vivo (100 μM). Gene co-expression modules were identified using Weighted Gene Co-expression Network Analysis for both baseline and DA-stimulated conditions, with each module characterized for biological function and tested for association with SZ status and SNPs from a genome-wide panel. We identified seven co-expression modules under baseline, of which six were preserved in DA-stimulated data. One module shows significantly increased association with SZ after DA perturbation (baseline: P = 0.023; DA-stimulated: P = 7.8 × 10^-5; ΔAIC = -10.5) and is highly enriched for genes related to ribosomal proteins and translation (FDR = 4 × 10^-141), mitochondrial oxidative phosphorylation, and neurodegeneration. SNP association testing revealed tentative QTLs underlying module co-expression, notably at FASTKD2 (top P = 2.8 × 10^-6), a gene involved in mitochondrial translation. These results substantiate the role of translational machinery in SZ pathogenesis, providing insights into a possible dopaminergic mechanism disrupting mitochondrial function, and demonstrates the utility of disease-relevant functional perturbation in the study of complex genetic etiologies.

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.

Genome-wide Association Analysis of Eye Movement Dysfunction in Schizophrenia

Eye movements are considered endophenotypes of schizophrenia. However, the genetic factors underlying eye movement are largely unknown. In this study, we explored the susceptibility loci for four eye movement scores: the scanpath length during the free viewing test (SPL), the horizontal position gain during the fast Lissajous paradigm of the smooth pursuit test (HPG), the duration of fixations during the far distractor paradigm of the fixation stability test (DF) and the integrated eye movement score of those three scores (EMS). We found 16 SNPs relevant to the HPG that were located in 3 genomic regions (1q21.3, 7p12.1 and 20q13.12) in the patient group; however, these SNPs were intronic or intergenic SNPs. To determine whether these SNPs occur in functional non-coding regions (i.e., enhancer or promoter regions), we examined the chromatin status on the basis of publicly available epigenomic data from 127 tissues or cell lines. This analysis suggested that the SNPs on 1q21.3 and 20q13.12 are in enhancer or promoter regions. Moreover, we performed an analysis of expression quantitative trait loci (eQTL) in human brain tissues using a public database. Finally, we identified significant eQTL effects for all of the SNPs at 1q21.3 and 20q13.12 in particular brain regions.

Transcriptomic signatures of schizophrenia revealed by dopamine perturbation in an ex vivo model

The dopaminergic hypothesis of schizophrenia (SZ) postulates that dopaminergic over activity causes psychosis, a central feature of SZ, based on the observation that blocking dopamine (DA) improves psychotic symptoms. DA is known to have both receptor- and non-receptor-mediated effects, including oxidative mechanisms that lead to apoptosis. The role of DA-mediated oxidative processes in SZ has been little studied. Here, we have used a cell perturbation approach and measured transcriptomic profiles by RNAseq to study the effect of DA exposure on transcription in B-cell transformed lymphoblastoid cell lines (LCLs) from 514 SZ cases and 690 controls. We found that DA had widespread effects on both cell growth and gene expression in LCLs. Overall, 1455 genes showed statistically significant differential DA response in SZ cases and controls. This set of differentially expressed genes is enriched for brain expression and for functions related to immune processes and apoptosis, suggesting that DA may play a role in SZ pathogenesis through modulating those systems. Moreover, we observed a non-significant enrichment of genes near genome-wide significant SZ loci and with genes spanned by SZ-associated copy number variants (CNVs), which suggests convergent pathogenic mechanisms detected by both genetic association and gene expression. The study suggests a novel role of DA in the biological processes of immune and apoptosis that may be relevant to SZ pathogenesis. Furthermore, our results show the utility of pathophysiologically relevant perturbation experiments to investigate the biology of complex mental disorders.

Recent Advances in the Genetics of Schizophrenia

The last decade brought tremendous progress in the field of schizophrenia genetics. As a result of extensive collaborations and multiple technological advances, we now recognize many types of genetic variants that increase the risk. These include large copy number variants, rare coding inherited and de novο variants, and over 100 loci harboring common risk variants. While the type and contribution to the risk vary among genetic variants, there is concordance in the functions of genes they implicate, such as those whose RNA binds the fragile X-related protein FMRP and members of the activity-regulated cytoskeletal complex involved in learning and memory. Gene expression studies add important information on the biology of the disease and recapitulate the same functional gene groups. Studies of alternative phenotypes help us widen our understanding of the genetic architecture of mental function and dysfunction, how diseases overlap not only with each other but also with non-disease phenotypes. The challenge is to apply this new knowledge to prevention and treatment and help patients. The data generated so far and emerging technologies, including new methods in cell engineering, offer significant promise that in the next decade we will unlock the translational potential of these significant discoveries.

Exon Array Biomarkers for the Differential Diagnosis of Schizophrenia and Bipolar Disorder

This study developed potential blood-based biomarker tests for diagnosing and differentiating schizophrenia (SZ), bipolar disorder type I (BD), and normal control (NC) subjects using mRNA gene expression signatures. A total of 90 subjects (n = 30 each for the three groups of subjects) provided blood samples at two visits. The Affymetrix exon microarray was used to profile the expression of over 1.4 million probesets. We selected potential biomarker panels using the temporal stability of the probesets and also back-tested them at two different visits for each subject. The 18-gene biomarker panels, using logistic regression modeling, correctly differentiated the three groups of subjects with high accuracy across the two different clinical visits (83-88% accuracy). The results are also consistent with the actual data and the "leave-one-out" analyses, indicating that the models should be predictive when applied to independent data cohorts. Many of the SZ and BD subjects were taking antipsychotic and mood stabilizer medications at the time of blood draw, raising the possibility that these drugs could have affected some of the differential transcription signatures. Using an independent Illumina data set of gene expression data from antipsychotic medication-free SZ subjects, the 18-gene biomarker panels produced a receiver operating characteristic curve accuracy greater than 0.866 in patients that were less than 30 years of age and medication free. We confirmed select transcripts by quantitative PCR and the nCounter® System. The episodic nature of psychiatric disorders might lead to highly variable results depending on when blood is collected in relation to the severity of the disease/symptoms. We have found stable trait gene panel markers for lifelong psychiatric disorders that may have diagnostic utility in younger undiagnosed subjects where there is a critical unmet need. The study requires replication in subjects for ultimate proof of the utility of the differential diagnosis.

Regional enrichment analyses on genetic profiles for schizophrenia and bipolar disorder

Both schizophrenia (SZ) and bipolar disorder (BD) are highly heritable psychiatric disorders. The significant genomic risk loci are of great importance but with no guarantee of known functional impact and they cannot totally explain the genetic inheritance. In this study we present regional enrichment analyses across the genome, aiming to strike a balance between individual risk loci and integrated regional effects. Chromosomes were partitioned into 2 million base-pair regions (indicated by an underscore sign in the cytogenetic bands) on which enrichment tests are performed. In the discovery phase, we leverage the Psychiatric Genomics Consortium SZ and BD initial association test results for European Ancestry (EA) population and dbGAP SNP data for African Ancestry (AA) population. 78 and 48 regions show significantly enriched associations with SZ and BD respectively in the EA population, and nine are in common including MHC, 3p21.1, 7p22.3_2, 2q32.3_2, 8q24.3_4, and 19q13.33_1. The most unique SZ associated region is 1p21.3_3, while the most unique BD associated region is 6q25.2_1. For the AA population fewer regions are discovered with only 10% overlapping with that of EA population. A replication test using Wellcome Trust Case Control Consortium data for EA population verified 9% of the SZ enriched regions and 40% of the BD enriched regions. In summary, we showed that regional enrichment analyses produce reliable genetic association profiles using about one tenth of samples compared to single base-pair genome wide association approach. The identified association regions will be useful for further genetic functional studies.

A Two-Stage Whole-Genome Gene Expression Association Study of Young-Onset Hypertension in Han Chinese Population of Taiwan

Hypertension is an important public health problem in the world. Since the intermediate position of the gene expression between genotype and phenotype makes it suitable to link genotype to phenotype, we carried out a two-stage whole-genome gene expression association study to find differentially expressed genes and pathways for hypertension. In the first stage, 126 cases and 149 controls were used to find out the differentially expressed genes. In the second stage, an independent set of samples (127 cases and 150 controls) was used to validate the results. Additionally, we conducted a gene set enrichment analysis (GSEA) to search for differentially affected pathways. A total of nine genes were implicated in the first stage (Bonferroni-corrected p-value < 0.05). Among these genes, ZRANB1, FAM110A, PREP, ANKRD9 and LAMB2 were also differentially expressed in an existing database of hypertensive mouse model (GSE19817). A total of 16 pathways were identified by the GSEA. ZRANB1 and six pathways identified are related to TNF-α. Three pathways are related to interleukin, one to metabolic syndrome, and one to Hedgehog signaling. Identification of these genes and pathways suggest the importance of 1. inflammation, 2. visceral fat metabolism, and 3. adipocytes and osteocytes homeostasis in hypertension mechanisms and complications.

Accessing Gene Expression in Treatment-Resistant Schizophrenia

Schizophrenia (SCZ) is a mental disorder arising from a complex interaction of genetic and environmental factors. It has been suggested that treatment-resistant schizophrenia (TRS) is a distinct, more severe, and homogenous subgroup of schizophrenia that could present specific biological markers. Our aim was to characterize expression of target genes in blood of TRS patients compared with non-TRS (NTRS) patients and healthy controls (HC). TRS has been defined using failure to respond to two previous antipsychotic trials. We hypothesized that genes involved in neurodevelopment, myelination, neuroplasticity, neurotransmission, and miRNA processing could be involved in treatment resistance; then, we investigated 13 genes related to those processes in 256 subjects, being 94 healthy controls and 162 schizophrenia patients treated with antipsychotics. Of those, 78 were TRS patients and 84 were NTRS patients. Peripheral blood samples were collected from all subjects and RNA was isolated. Gene expression analysis was performed using the TaqMan low-density array (TLDA) technology. To verify the influence of expression quantitative trait loci (eQTLs), we evaluated single-nucleotide polymorphism (SNP) of all genes using data from GTEx Project. SNP genotypes were obtained from HumanOmniExpress BeadChip. We did not detect gene expression differences between TRS and NTRS subjects, indicating candidate genes specific to treatment resistance. We detected an upregulation of CNR1 and UFD1L gene expression in patients (TRS and NTRS groups) when compared to controls, that may be associated with the release of neurotransmitters, which can influence neuronal plasticity, or with a stress response-activating protein degradation. DICER1 and AKT1 expression increased slightly across the groups and could differentiate only the extreme opposite groups, HC and TRS. Both genes act in heterogeneous pathways, such as cell signaling and miRNA processing, and seem to have an increased demand in the TRS group. We did not detect any eQTLs in our sample that could explain differences in mRNA levels, suggesting a possible regulation by other mechanism, not driven by genotypes. Our data strengthen the importance of several biological pathways involved in the schizophrenia refractoriness and severity, adding knowledge to develop more effective treatments in the future.

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

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

Associations between SNPs and immune-related circulating proteins in schizophrenia

Genome-wide association studies (GWAS) and proteomic studies have provided convincing evidence implicating alterations in immune/inflammatory processes in schizophrenia. However, despite the convergence of evidence, direct links between the genetic and proteomic findings are still lacking for schizophrenia. We investigated associations between single nucleotide polymorphisms (SNPs) from the custom-made PsychArray and the expression levels of 190 multiplex immunoassay profiled serum proteins in 149 schizophrenia patients and 198 matched controls. We identified associations between 81 SNPs and 29 proteins, primarily involved in immune/inflammation responses. Significant SNPxDiagnosis interactions were identified for eight serum proteins including Factor-VII[rs555212], Alpha-1-Antitrypsin[rs11846959], Interferon-Gamma Induced Protein 10[rs4256246] and von-Willebrand-Factor[rs12829220] in the control group; Chromogranin-A[rs9658644], Cystatin-C[rs2424577] and Vitamin K-Dependent Protein S[rs6123] in the schizophrenia group; Interleukin-6 receptor[rs7553796] in both the control and schizophrenia groups. These results suggested that the effect of these SNPs on expression of the respective proteins varies with diagnosis. The combination of patient-specific genetic information with blood biomarker data opens a novel approach to investigate disease mechanisms in schizophrenia and other psychiatric disorders. Our findings not only suggest that blood protein expression is influenced by polymorphisms in the corresponding gene, but also that the effect of certain SNPs on expression of proteins can vary with diagnosis.

Schizophrenia-associated methylomic variation: molecular signatures of disease and polygenic risk burden across multiple brain regions

Genetic association studies provide evidence for a substantial polygenic component to schizophrenia, although the neurobiological mechanisms underlying the disorder remain largely undefined. Building on recent studies supporting a role for developmentally regulated epigenetic variation in the molecular aetiology of schizophrenia, this study aimed to identify epigenetic variation associated with both a diagnosis of schizophrenia and elevated polygenic risk burden for the disease across multiple brain regions. Genome-wide DNA methylation was quantified in 262 post-mortem brain samples, representing tissue from four brain regions (prefrontal cortex, striatum, hippocampus and cerebellum) from 41 schizophrenia patients and 47 controls. We identified multiple disease-associated and polygenic risk score-associated differentially methylated positions and regions, which are not enriched in genomic regions identified in genetic studies of schizophrenia and do not reflect direct genetic effects on DNA methylation. Our study represents the first analysis of epigenetic variation associated with schizophrenia across multiple brain regions and highlights the utility of polygenic risk scores for identifying molecular pathways associated with aetiological variation in complex disease.

Diverse gene expression patterns in response to anticancer drugs between human and mouse cell lines revealed by a comparative transcriptomic analysis

The aim of the present study was to perform comparative genomics using gene expression profile datasets of mice and humans who had been treated with anticancer drugs, to determine the similarities and differences in the antitumor mechanisms in the two mammals. This involved data mining of antitumor gene expression regulation, and screening of genetic loci from experimental mouse models of antitumor targets, to provide a theoretical basis of drug design. Subsequently, 9 overlapping genes with opposite expression patterns were identified across mouse and human cell lines that were treated with a specific cyclin-dependent kinase 4/6 inhibitor, PD0332991. These genes included LIM homeobox 2, adenomedullin, bone marrow stromal cell antigen 1, caveolin 1, histone cluster 1 (HIST1) H2B family member C, HIST1 H3 family member F, low density lipoprotein-receptor related protein 11, prolyl 4-hydroxylase subunit α1 and torsin family 3 member A. In addition, the janus kinase-signal transducer and activator of transcription signaling pathway, Toll-like receptor signaling pathway, T cell receptor signaling pathway and the nucleotide-binding oligomerization domain-like receptor signaling pathway were identified as candidate pathways for explaining antitumor mechanisms.

Insulin-regulated aminopeptidase immunoreactivity is abundantly present in human hypothalamus and posterior pituitary gland, with reduced expression in paraventricular and suprachiasmatic neurons in chronic schizophrenia

The vasopressin- and oxytocin-degrading enzyme insulin-regulated aminopeptidase (IRAP) is expressed in various organs including the brain. However, knowledge about its presence in human hypothalamus is fragmentary. Functionally, for a number of reasons (genetic linkage, hydrolysis of oxytocin and vasopressin, its role as angiotensin IV receptor in learning and memory and others) IRAP might play a role in schizophrenia. We studied the regional and cellular localization of IRAP in normal human brain with special emphasis on the hypothalamus and determined numerical densities of IRAP-expressing cells in the paraventricular, supraoptic and suprachiasmatic nuclei in schizophrenia patients and controls. By using immunohistochemistry and Western blot analysis, IRAP was immunolocalized in postmortem human brains. Cell countings were performed to estimate numbers and numerical densities of IRAP immunoreactive hypothalamic neurons in schizophrenia patients and control cases. Shape, size and regional distribution of IRAP-expressing cells, as well the lack of co-localization with the glia marker glutamine synthetase, show that IRAP is expressed in neurons. IRAP immunoreactive cells were observed in the hippocampal formation, cerebral cortex, thalamus, amygdala and, abundantly, hypothalamus. Double labeling experiments (IRAP and oxytocin/neurophysin 1, IRAP with vasopressin/neurophysin 2) revealed that IRAP is present in oxytocinergic and in vasopressinergic neurons. In schizophrenia patients, the numerical density of IRAP-expressing neurons in the paraventricular and the suprachiasmatic nuclei is significantly reduced, which might be associated with the reduction in neurophysin-containing neurons in these nuclei in schizophrenia. The pathophysiological role of lowered hypothalamic IRAP expression in schizophrenia remains to be established.

Transcriptome sequencing study implicates immune-related genes differentially expressed in schizophrenia: new data and a meta-analysis

We undertook an RNA sequencing (RNAseq)-based transcriptomic profiling study on lymphoblastoid cell lines of a European ancestry sample of 529 schizophrenia cases and 660 controls, and found 1058 genes to be differentially expressed by affection status. These differentially expressed genes were enriched for involvement in immunity, especially the 697 genes with higher expression in cases. Comparing the current RNAseq transcriptomic profiling to our previous findings in an array-based study of 268 schizophrenia cases and 446 controls showed a highly significant positive correlation over all genes. Fifteen (18%) of the 84 genes with significant (false discovery rate<0.05) expression differences between cases and controls in the previous study and analyzed here again were differentially expressed by affection status here at a genome-wide significance level (Bonferroni P<0.05 adjusted for 8141 analyzed genes in total, or P<~6.1 × 10^-6), all with the same direction of effect, thus providing corroborative evidence despite each sample of fully independent subjects being studied by different technological approaches. Meta-analysis of the RNAseq and array data sets (797 cases and 1106 controls) showed 169 additional genes (besides those found in the primary RNAseq-based analysis) to be differentially expressed, and provided further evidence of immune gene enrichment. In addition to strengthening our previous array-based gene expression differences in schizophrenia cases versus controls and providing transcriptomic support for some genes implicated by other approaches for schizophrenia, our study detected new genes differentially expressed in schizophrenia. We highlight RNAseq-based differential expression of various genes involved in neurodevelopment and/or neuronal function, and discuss caveats of the approach.

An Intrinsic Transcriptional Program Underlying Synaptic Scaling during Activity Suppression

Homeostatic scaling allows neurons to maintain stable activity patterns by globally altering their synaptic strength in response to changing activity levels. Suppression of activity by the blocking of action potentials increases synaptic strength through an upregulation of surface α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors. Although this synaptic upscaling was shown to require transcription, the molecular nature of the intrinsic transcription program underlying this process and its functional significance have been unclear. Using RNA-seq, we identified 73 genes that were specifically upregulated in response to activity suppression. In particular, Neuronal pentraxin-1 (Nptx1) increased within 6 hr of activity blockade, and knockdown of this gene blocked the increase in synaptic strength. Nptx1 induction is mediated by calcium influx through the T-type voltage-gated calcium channel, as well as two transcription factors, SRF and ELK1. Altogether, these results uncover a transcriptional program that specifically operates when neuronal activity is suppressed to globally coordinate the increase in synaptic strength.

Joint sparse canonical correlation analysis for detecting differential imaging genetics modules

MOTIVATION

Imaging genetics combines brain imaging and genetic information to identify the relationships between genetic variants and brain activities. When the data samples belong to different classes (e.g. disease status), the relationships may exhibit class-specific patterns that can be used to facilitate the understanding of a disease. Conventional approaches often perform separate analysis on each class and report the differences, but ignore important shared patterns.

RESULTS

In this paper, we develop a multivariate method to analyze the differential dependency across multiple classes. We propose a joint sparse canonical correlation analysis method, which uses a generalized fused lasso penalty to jointly estimate multiple pairs of canonical vectors with both shared and class-specific patterns. Using a data fusion approach, the method is able to detect differentially correlated modules effectively and efficiently. The results from simulation studies demonstrate its higher accuracy in discovering both common and differential canonical correlations compared to conventional sparse CCA. Using a schizophrenia dataset with 92 cases and 116 controls including a single nucleotide polymorphism (SNP) array and functional magnetic resonance imaging data, the proposed method reveals a set of distinct SNP-voxel interaction modules for the schizophrenia patients, which are verified to be both statistically and biologically significant.

AVAILABILITY AND IMPLEMENTATION

The Matlab code is available at https://sites.google.com/site/jianfang86/JSCCA CONTACT: wyp@tulane.eduSupplementary information: Supplementary data are available at Bioinformatics online.

SZGR 2.0: a one-stop shop of schizophrenia candidate genes

SZGR 2.0 is a comprehensive resource of candidate variants and genes for schizophrenia, covering genetic, epigenetic, transcriptomic, translational and many other types of evidence. By systematic review and curation of multiple lines of evidence, we included almost all variants and genes that have ever been reported to be associated with schizophrenia. In particular, we collected ∼4200 common variants reported in genome-wide association studies, ∼1000 de novo mutations discovered by large-scale sequencing of family samples, 215 genes spanning rare and replication copy number variations, 99 genes overlapping with linkage regions, 240 differentially expressed genes, 4651 differentially methylated genes and 49 genes as antipsychotic drug targets. To facilitate interpretation, we included various functional annotation data, especially brain eQTL, methylation QTL, brain expression featured in deep categorization of brain areas and developmental stages and brain-specific promoter and enhancer annotations. Furthermore, we conducted cross-study, cross-data type and integrative analyses of the multidimensional data deposited in SZGR 2.0, and made the data and results available through a user-friendly interface. In summary, SZGR 2.0 provides a one-stop shop of schizophrenia variants and genes and their function and regulation, providing an important resource in the schizophrenia and other mental disease community. SZGR 2.0 is available at https://bioinfo.uth.edu/SZGR/.

Gene expression alterations related to mania and psychosis in peripheral blood of patients with a first episode of psychosis

Psychotic disorders affect ~3% of the general population and are among the most severe forms of mental diseases. In early stages of psychosis, clinical aspects may be difficult to distinguish from one another. Undifferentiated psychopathology at the first-episode of psychosis (FEP) highlights the need for biomarkers that can improve and refine differential diagnosis. We investigated gene expression differences between patients with FEP-schizophrenia spectrum (SCZ; N=53) or FEP-Mania (BD; N=16) and healthy controls (N=73). We also verified whether gene expression was correlated to severity of psychotic, manic, depressive symptoms and/or functional impairment. All participants were antipsychotic-naive. After the psychiatric interview, blood samples were collected and the expression of 12 psychotic-disorder-related genes was evaluated by quantitative PCR. AKT1 and DICER1 expression levels were higher in BD patients compared with that in SCZ patients and healthy controls, suggesting that expression of these genes is associated more specifically to manic features. Furthermore, MBP and NDEL1 expression levels were higher in SCZ and BD patients than in healthy controls, indicating that these genes are psychosis related (independent of diagnosis). No correlation was found between gene expression and severity of symptoms or functional impairment. Our findings suggest that genes related to neurodevelopment are altered in psychotic disorders, and some might support the differential diagnosis between schizophrenia and bipolar disorder, with a potential impact on the treatment of these disorders.

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

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

Currently recognized genes for schizophrenia: High-resolution chromosome ideogram representation

A large body of genetic data from schizophrenia-related research has identified an assortment of genes and disturbed pathways supporting involvement of complex genetic components for schizophrenia spectrum and other psychotic disorders. Advances in genetic technology and expanding studies with searchable genomic databases have led to multiple published reports, allowing us to compile a master list of known, clinically relevant, or susceptibility genes contributing to schizophrenia. We searched key words related to schizophrenia and genetics from peer-reviewed medical literature sources, authoritative public access psychiatric websites and genomic databases dedicated to gene discovery and characterization of schizophrenia. Our list of 560 genes were arranged in alphabetical order in tabular form with gene symbols placed on high-resolution human chromosome ideograms. Genome wide pathway analysis using GeneAnalytics was carried out on the resulting list of genes to assess the underlying genetic architecture for schizophrenia. Recognized genes of clinical relevance, susceptibility or causation impact a broad range of biological pathways and mechanisms including ion channels (e.g., CACNA1B, CACNA1C, CACNA1H), metabolism (e.g., CYP1A2, CYP2C19, CYP2D6), multiple targets of neurotransmitter pathways impacting dopamine, GABA, glutamate, and serotonin function, brain development (e.g., NRG1, RELN), signaling peptides (e.g., PIK3CA, PIK4CA) and immune function (e.g., HLA-DRB1, HLA-DQA1) and interleukins (e.g., IL1A, IL10, IL6). This summary will enable clinical and laboratory geneticists, genetic counselors, and other clinicians to access convenient pictorial images of the distribution and location of contributing genes to inform diagnosis and gene-based treatment as well as provide risk estimates for genetic counseling of families with affected relatives.

Altered expression of mRNA profiles in blood of early-onset schizophrenia

To identify gene expression abnormalities in schizophrenia (SZ), we generated whole-genome gene expression profiles using microarrays on peripheral blood mononuclear cells (PBMCs) from 18 early-onset SZ cases and 12 controls. We detected 84 transcripts differentially expressed by diagnostic status, with 82 genes being upregulated and 2 downregulated. We identified two SZ associated gene coexpression modules (green and red), including 446 genes . The green module is positively correlated with SZ, encompassing predominantly up-regulated genes in SZ; while the red module was negatively correlated with disease status, involving mostly nominally down-regulated genes in SZ. The olfactory transduction pathway was the most enriched pathways for the genes within the two modules. The expression levels of several hub genes, including AKT1, BRCA1, CCDC134, UBD, and ZIC2 were validated using real-time quantitative PCR. Our findings indicate that mRNA coexpression abnormalities may serve as a promising mechanism underlying the development of SZ.

Increased co-expression of genes harboring the damaging de novo mutations in Chinese schizophrenic patients during prenatal development

Schizophrenia is a heritable, heterogeneous common psychiatric disorder. In this study, we evaluated the hypothesis that de novo variants (DNVs) contribute to the pathogenesis of schizophrenia. We performed exome sequencing in Chinese patients (N = 45) with schizophrenia and their unaffected parents (N = 90). Forty genes were found to contain DNVs. These genes had enriched transcriptional co-expression profile in prenatal frontal cortex (Bonferroni corrected p < 9.1 × 10⁻³), and in prenatal temporal and parietal regions (Bonferroni corrected p < 0.03). Also, four prenatal anatomical subregions (VCF, MFC, OFC and ITC) have shown significant enrichment of connectedness in co-expression networks. Moreover, four genes (LRP1, MACF1, DICER1 and ABCA2) harboring the damaging de novo mutations are strongly prioritized as susceptibility genes by multiple evidences. Our findings in Chinese schizophrenic patients indicate the pathogenic role of DNVs, supporting the hypothesis that schizophrenia is a neurodevelopmental disease.

DICER1 and microRNA regulation in post-traumatic stress disorder with comorbid depression

DICER1 is an enzyme that generates mature microRNAs (miRNAs), which regulate gene expression post-transcriptionally in brain and other tissues and is involved in synaptic maturation and plasticity. Here, through genome-wide differential gene expression survey of post-traumatic stress disorder (PTSD) with comorbid depression (PTSD&Dep), we find that blood DICER1 expression is significantly reduced in cases versus controls, and replicate this in two independent cohorts. Our follow-up studies find that lower blood DICER1 expression is significantly associated with increased amygdala activation to fearful stimuli, a neural correlate for PTSD. Additionally, a genetic variant in the 3′ un-translated region of DICER1, rs10144436, is significantly associated with DICER1 expression and with PTSD&Dep, and the latter is replicated in an independent cohort. Furthermore, genome-wide differential expression survey of miRNAs in blood in PTSD&Dep reveals miRNAs to be significantly downregulated in cases versus controls. Together, our novel data suggest DICER1 plays a role in molecular mechanisms of PTSD&Dep through the DICER1 and the miRNA regulation pathway.

DICER1 is required for the maturation of miRNAs which regulate expression of thousands of genes. Here the authors show significantly reduced levels of DICER1 in individuals having post-traumatic stress disorder and comorbid depression suggestive of a role in the molecular mechanism of the condition.

Depression, Cytokine, and Cytokine by Treatment Interactions Modulate Gene Expression in Antipsychotic Naïve First Episode Psychosis

In schizophrenia, genetic and environmental factors affect neurodevelopment and neuroprogressive trajectory. Altered expression of neuro-immune genes and increased levels of cytokines are observed, especially in patients with comorbid depression. However, it remains unclear whether circulating levels of cytokines and expression of these genes are associated, and how antipsychotic treatments impact this association. Relationships between messenger RNA (mRNA) expression of 11 schizophrenia-related genes and circulating levels of cytokines (interleukin (IL)-6, IL-10, and tumor necrosis factor (TNF)-α) were analyzed in 174 antipsychotic naïve first episode psychosis (FEP) and in 77 healthy controls. A subgroup of 72 patients was reassessed after treatment with risperidone. FEP patients were divided into those with and without depression. FEP patients with depression showed increased COMT expression and decreased NDEL1 expression. Increased IL-6 was associated with lowered AKT1 and DROSHA expression, while increased IL-10 was associated with increased NDEL1, DISC1, and MBP expression. IL-6 levels significantly increased the risperidone-induced expression of AKT1, DICER1, DROSHA, and COMT mRNA. The differential mRNA gene expression in FEP is largely associated with increased cytokine levels. While increased IL-6 may downregulate AKT-mediated cellular functions and dysregulate genes involved in microRNA (miRNA) machinery, increased IL-10 has neuroprotective properties. Increased IL-6 levels may prime the expression of genes (AKT1, DICER1, DROSHA, and COMT) in response to risperidone, suggesting that cytokine × treatment × gene interactions may improve cell function profiles. FEP patients with depression show a different gene expression profile reinforcing the theory that depression in FEP is a different phenotype.