Thalamic transcriptome screening in three psychiatric states

Metergoline Shares Properties with Atypical Antipsychotic Drugs Identified by Gene Expression Signature Screen

Novel approaches are required to find new treatments for schizophrenia and other neuropsychiatric disorders. This study utilised a combination of in vitro transcriptomics and in silico analysis with the BROAD Institute's Connectivity Map to identify drugs that can be repurposed to treat psychiatric disorders. Human neuronal (NT2-N) cells were treated with a combination of atypical antipsychotic drugs commonly used to treat psychiatric disorders (such as schizophrenia, bipolar disorder, and major depressive disorder), and differential gene expression was analysed. Biological pathways with an increased gene expression included circadian rhythm and vascular endothelial growth factor signalling, while the adherens junction and cell cycle pathways were transcriptionally downregulated. The Connectivity Map (CMap) analysis screen highlighted drugs that affect global gene expression in a similar manner to these psychiatric disorder treatments, including several other antipsychotic drugs, confirming the utility of this approach. The CMap screen specifically identified metergoline, an ergot alkaloid currently used to treat seasonal affective disorder, as a drug of interest. In mice, metergoline dose-dependently reduced MK-801- or methamphetamine-induced locomotor hyperactivity confirming the potential of metergoline to treat positive symptoms of schizophrenia in an animal model. Metergoline had no effects on prepulse inhibition deficits induced by MK-801 or methamphetamine. Taken together, metergoline appears a promising drug for further studies to be repurposed as a treatment for schizophrenia and possibly other psychiatric disorders.

Genome-wide landscape of RNA-binding protein (RBP) networks as potential molecular regulators of psychiatric co-morbidities: a computational analysis

Background

Psychiatric disorders are a major burden on global health. These illnesses manifest as co-morbid conditions, further complicating the treatment. There is a limited understanding of the molecular and regulatory basis of psychiatric co-morbidities. The existing research in this regard has largely focused on epigenetic modulators, non-coding RNAs, and transcription factors. RNA-binding proteins (RBPs) functioning as multi-protein complexes are now known to be predominant controllers of multiple gene regulatory processes. However, their involvement in gene expression dysregulation in psychiatric co-morbidities is yet to be understood.

Results

Ten RBPs (QKI, ELAVL2, EIF2S1, SRSF3, IGF2BP2, EIF4B, SNRNP70, FMR1, DAZAP1, and MBNL1) were identified to be associated with psychiatric disorders such as schizophrenia, major depression, and bipolar disorders. Analysis of transcriptomic changes in response to individual depletion of these RBPs showed the potential influence of a large number of RBPs driving differential gene expression, suggesting functional cross-talk giving rise to multi-protein networks. Subsequent transcriptome analysis of post-mortem human brain samples from diseased and control individuals also suggested the involvement of ~ 100 RBPs influencing gene expression changes. These RBPs were found to regulate various processes including transcript splicing, mRNA transport, localization, stability, and translation. They were also found to form an extensive interactive network. Further, hnRNP, SRSF, and PCBP family RBPs, Matrin3, U2AF2, KHDRBS1, PTBP1, and also PABPN1 were found to be the hub proteins of the RBP network.

Conclusions

Extensive RBP networks involving a few hub proteins could result in transcriptome-wide dysregulation of post-transcriptional modifications, potentially driving multiple psychiatric disorders. Understanding the functional involvement of RBP networks in psychiatric disorders would provide insights into the molecular basis of psychiatric co-morbidities.

Transcriptomic analysis of isolated and pooled human postmortem cerebellar Purkinje cells in autism spectrum disorders

At present, the neuronal mechanisms underlying the diagnosis of autism spectrum disorder (ASD) have not been established. However, studies from human postmortem ASD brains have consistently revealed disruptions in cerebellar circuitry, specifically reductions in Purkinje cell (PC) number and size. Alterations in cerebellar circuitry would have important implications for information processing within the cerebellum and affect a wide range of human motor and non-motor behaviors. Laser capture microdissection was performed to obtain pure PC populations from a cohort of postmortem control and ASD cases and transcriptional profiles were compared. The 427 differentially expressed genes were enriched for gene ontology biological processes related to developmental organization/connectivity, extracellular matrix organization, calcium ion response, immune function and PC signaling alterations. Given the complexity of PCs and their far-ranging roles in response to sensory stimuli and motor function regulation, understanding transcriptional differences in this subset of cerebellar cells in ASD may inform on convergent pathways that impact neuronal function.

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

BACKGROUND

The main challenge in the study of schizophrenia is its high heterogeneity. While it is generally accepted that there exist several biological mechanisms that may define distinct schizophrenia subtypes, they have not been identified yet. We performed comprehensive gene expression analysis to search for molecular signals that differentiate schizophrenia patients from healthy controls and examined whether an identified signal was concentrated in a subgroup of the patients.

METHODS

Transcriptome sequencing of 14 superior temporal gyrus (STG) samples of subjects with schizophrenia and 15 matched controls from the Stanley Medical Research Institute (SMRI) was performed. Differential expression and pathway enrichment analysis results were compared to an independent cohort. Replicability was tested on 6 additional independent datasets.

RESULTS

The 2 STG cohorts showed high replicability. Pathway enrichment analysis of the down-regulated genes pointed to proteasome-related pathways. Meta-analysis of differential expression identified down-regulation of 12 of 39 proteasome subunit genes in schizophrenia. The signal of proteasome subunits down-regulation was replicated in 6 additional datasets (overall 8 cohorts with 267 schizophrenia and 266 control samples, from 5 brain regions). The signal was concentrated in a subgroup of patients with schizophrenia.

CONCLUSIONS

We detected global down-regulation of proteasome subunits in a subgroup of patients with schizophrenia. We hypothesize that the down-regulation of proteasome subunits leads to proteasome dysfunction that causes accumulation of ubiquitinated proteins, which has been recently detected in a subgroup of schizophrenia patients. Thus, down-regulation of proteasome subunits might define a biological subtype of schizophrenia.

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.

Genetically Determined Levels of Serum Metabolites and Risk of Neuroticism: A Mendelian Randomization Study

BACKGROUND

Neuroticism is a strong predictor for a variety of social and behavioral outcomes, but the etiology is still unknown. Our study aims to provide a comprehensive investigation of causal effects of serum metabolome phenotypes on risk of neuroticism using Mendelian randomization (MR) approaches.

METHODS

Genetic associations with 486 metabolic traits were utilized as exposures, and data from a large genome-wide association study of neuroticism were selected as outcome. For MR analysis, we used the standard inverse-variance weighted (IVW) method for primary MR analysis and 3 additional MR methods (MR-Egger, weighted median, and MR pleiotropy residual sum and outlier) for sensitivity analyses.

RESULTS

Our study identified 31 metabolites that might have causal effects on neuroticism. Of the 31 metabolites, uric acid and paraxanthine showed robustly significant association with neuroticism in all MR methods. Using single nucleotide polymorphisms as instrumental variables, a 1-SD increase in uric acid was associated with approximately 30% lower risk of neuroticism (OR: 0.77; 95% CI: 0.62-0.95; PIVW = 0.0145), whereas a 1-SD increase in paraxanthine was associated with a 7% higher risk of neuroticism (OR: 1.07; 95% CI: 1.01-1.12; PIVW = .0145).

DISCUSSION

Our study suggested an increased level of uric acid was associated with lower risk of neuroticism, whereas paraxanthine showed the contrary effect. Our study provided novel insight by combining metabolomics with genomics to help understand the pathogenesis of neuroticism.

Two Thalamic Regions Screened Using Laser Capture Microdissection with Whole Human Genome Microarray in Schizophrenia Postmortem Samples

We used whole human genome microarray screening of highly enriched neuronal populations from two thalamic regions in postmortem samples from subjects with schizophrenia and controls to identify brain region-specific gene expression changes and possible transcriptional targets. The thalamic anterior nucleus is reciprocally connected to anterior cingulate, a schizophrenia-affected cortical region, and is also thought to be schizophrenia affected; the other thalamic region is not. Using two regions in the same subject to identify disease-relevant gene expression differences was novel and reduced intersubject heterogeneity of findings. We found gene expression differences related to miRNA-137 and other SZ-associated microRNAs, ELAVL1, BDNF, DISC-1, MECP2 and YWHAG associated findings, synapses, and receptors. Manual curation of our data may support transcription repression.

Intracellular compartment-specific proteasome dysfunction in postmortem cortex in schizophrenia subjects

Protein homeostasis is an emerging component of schizophrenia (SZ) pathophysiology. Proteomic alterations in SZ are well-documented and changes in transcript expression are frequently not associated with changes in protein expression in SZ brain. The underlying mechanism driving these changes remains unknown, though altered expression of ubiquitin proteasome system (UPS) components have implicated protein degradation. Previous studies have been limited to protein and transcript expression, however, and do not directly test the function of the proteasome. To address this gap in knowledge, we measured enzymatic activity associated with the proteasome (chymotrypsin-, trypsin-, and caspase-like) in the superior temporal gyrus (STG) of 25 SZ and 25 comparison subjects using flourogenic substrates. As localization regulates which cellular processes the proteasome contributes to, we measured proteasome activity and subunit expression in fractions enriched for nucleus, cytosolic, and membrane compartments. SZ subjects had decreased trypsin-like activity in total homogenate. This finding was specific to the nucleus-enriched fraction and was not associated with changes in proteasome subunit expression. Interestingly, both chymotrypsin-like activity and protein expression of 19S RP subunits, which facilitate ubiquitin-dependent degradation, were decreased in the cytosol-enriched fraction of SZ subjects. Intracellular compartment-specific proteasome dysfunction implicates dysregulation of protein expression both through altered ubiquitin-dependent degradation of cytosolic proteins and regulation of protein synthesis due to degradation of transcription factors and transcription machinery in the nucleus. Together, these findings implicate proteasome dysfunction in SZ, which likely has a broad impact on the proteomic landscape and cellular function in the pathophysiology of this illness.

The protocadherin 17 gene affects cognition, personality, amygdala structure and function, synapse development and risk of major mood disorders

Major mood disorders, which primarily include bipolar disorder and major depressive disorder, are the leading cause of disability worldwide and pose a major challenge in identifying robust risk genes. Here, we present data from independent large-scale clinical data sets (including 29 557 cases and 32 056 controls) revealing brain expressed protocadherin 17 (PCDH17) as a susceptibility gene for major mood disorders. Single-nucleotide polymorphisms (SNPs) spanning the PCDH17 region are significantly associated with major mood disorders; subjects carrying the risk allele showed impaired cognitive abilities, increased vulnerable personality features, decreased amygdala volume and altered amygdala function as compared with non-carriers. The risk allele predicted higher transcriptional levels of PCDH17 mRNA in postmortem brain samples, which is consistent with increased gene expression in patients with bipolar disorder compared with healthy subjects. Further, overexpression of PCDH17 in primary cortical neurons revealed significantly decreased spine density and abnormal dendritic morphology compared with control groups, which again is consistent with the clinical observations of reduced numbers of dendritic spines in the brains of patients with major mood disorders. Given that synaptic spines are dynamic structures which regulate neuronal plasticity and have crucial roles in myriad brain functions, this study reveals a potential underlying biological mechanism of a novel risk gene for major mood disorders involved in synaptic function and related intermediate phenotypes.

The Isolation of Pure Populations of Neurons by Laser Capture Microdissection: Methods and Application in Neuroscience

In mammals, the central nervous system (CNS) is constituted of various cellular elements, posing a challenge to isolating specific cell types to investigate their expression profile. As a result, tissue homogenization is not amenable to analyses of motor neurons profiling as these represent less than 10% of the total spinal cord cell population. One way to tackle the problem of tissue heterogeneity and obtain meaningful genomic, proteomic, and transcriptomic profiling is to use laser capture microdissection technology (LCM). In this chapter, we describe protocols for the capture of isolated populations of motor neurons from spinal cord tissue sections and for downstream transcriptomic analysis of motor neurons with RT-PCR. We have also included a protocol for the immunological confirmation that the captured neurons are indeed motor neurons. Although focused on spinal cord motor neurons, these protocols can be easily optimized for the isolation of any CNS neurons.

Identification of plasma biomarkers for distinguishing bipolar depression from major depressive disorder by iTRAQ-coupled LC-MS/MS and bioinformatics analysis

It is important to differentiate between bipolar disorder (BD) and major depressive disorder (MDD) in the first depressive episode because of the potential treatment implications. Previous studies have mainly focused on the different clinical features or pathological biomarkers to distinguish these two diseases; however, a better understanding of the proteomics profiling of BD may help aid future therapeutic strategies. Here, we applied isobaric tags for relative and absolute quantification (iTRAQ) technology combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify differentially expressed proteins between MDD and bipolar depression (BP). In total, 30 MDD, 30 BP and 30 healthy subjects were included. Proteins from depleted plasma samples were digested into peptides, individually labeled with iTRAQ reagents, combined and subjected to LC-MS/MS and further bioinformatics analyses. Our results showed that 9 proteins were significantly altered between MDD and BP. Briefly, B2RAN2, B4E1B2, APOA1, ENG, SBSN and QSOX2 were up-regulated, whereas ORM1, MRC2 and SLPI were down-regulated. Most identified proteins were related to the immune system. The bioinformatics analysis showed that B2RAN2 (highly similar to vanin-1) was involved in the significantly enriched KEGG pathways "pantothenate and CoA biosynthesis" (P=0.009). B2RAN2 and ENG may play important roles in depression. They may serve as candidate biomarkers for distinguishing MDD and BP. Further validation and investigation are required to illuminate the roles of B2RAN2 and ENG in MDD and BP. The current study provided a potential and novel biomarker panel that may, in turn, aid the diagnosis of BD.

Transcriptome Alterations in Prefrontal Pyramidal Cells Distinguish Schizophrenia From Bipolar and Major Depressive Disorders

BACKGROUND

Impairments in certain cognitive processes (e.g., working memory) are typically most pronounced in schizophrenia (SZ), intermediate in bipolar disorder, and least in major depressive disorder. Given that working memory depends, in part, on neural circuitry that includes pyramidal cells in layer 3 (L3) and layer 5 (L5) of the dorsolateral prefrontal cortex (DLPFC), we sought to determine if transcriptome alterations in these neurons were shared or distinctive for each diagnosis.

METHODS

Pools of L3 and L5 pyramidal cells in the DLPFC were individually captured by laser microdissection from 19 matched tetrads of unaffected comparison subjects and subjects with SZ, bipolar disorder, and major depressive disorder, and the messenger RNA was subjected to transcriptome profiling by microarray.

RESULTS

In DLPFC L3 and L5 pyramidal cells, transcriptome alterations were numerous in subjects with SZ, but rare in subjects with bipolar disorder and major depressive disorder. The leading molecular pathways altered in subjects with SZ involved mitochondrial energy production and the regulation of protein translation. In addition, we did not find any significant transcriptome signatures related to psychosis or suicide.

CONCLUSIONS

In concert, these findings suggest that molecular alterations in DLPFC L3 and L5 pyramidal cells might be characteristic of the disease processes operative in individuals diagnosed with SZ and thus might contribute to the circuitry alterations underlying cognitive dysfunction in individuals with SZ.

Gene expression associated with suicide attempts in US veterans

According to a recent report from the Office of Suicide Prevention in the US Department of Veterans Affairs, veterans represent 8.5% of the US population, but account for 18% of all deaths from suicide. The aim of this study of psychiatric patients (n=39; 87% male) was to compare blood gene expression data from veterans with a history of one or more suicide attempts to veterans who had never attempted suicide. The attempter and non-attempter groups were matched for age and race/ethnicity, and both groups included veterans with a diverse psychiatric history that included posttraumatic stress disorder (PTSD) and substance-use disorders. Veterans were interviewed for lifetime psychiatric history, including a detailed assessment of prior suicide attempts and provided a blood sample. Results of Ingenuity Pathway Analysis (IPA) identified several pathways associated with suicide attempts, including the mammalian target of rapamycin (mTOR) and WNT signaling pathways. These pathways are of particular interest, given their role in explaining pharmacological treatments for suicidal behavior, including the use of ketamine and lithium. These results suggest that findings observed in civilians are also relevant for veterans and provide a context for interpreting results observed in post-mortem samples. In conclusion, an emerging body of work that shows consistency in findings across blood and brain samples suggests that it might be possible to identify molecular predictors of suicide attempts.

Metabolomics and lipidomics analyses by 1H nuclear magnetic resonance of schizophrenia patient serum reveal potential peripheral biomarkers for diagnosis

Using ¹H NMR-based metabolomics in association to chemometrics analysis, we analyzed here the metabolic differences between schizophrenia patients (SCZ) compared to healthy controls (HCs). HCs and SCZ patients underwent clinical interview using the Structured Clinical Interview for DSM Disorders (SCID). SCZ patients were further assessed by Positive and Negative Syndrome Scale (PANSS), Calgary Depression Scale, Global Assessment of Functioning Scale (GAF), and Clinical Global Impressions Scale (CGI). Using the principal component analysis (PCA) and supervised partial least-squares discriminate analysis (PLS-DA) in obtained NMR data, a clear group separation between HCs and SCZ patients was achieved. Interestingly, all metabolite compounds identified as exclusively present in the SCZ group, except for the gamma-aminobutyric acid (GABA), were never previously associated with mental disorders. Although the initial perception of an absence of obvious biological link among the different key molecules exclusively observed in each group, and no identification of any specific pathway yet, the present work represents an important contribution for the identification of potential biomarkers to inform diagnosis, as it was possible to completely separate the affected SCZ patients from HCs, with no outliers or exceptions. In addition, the data presented here reinforced the role of the modulation of glycolysis pathway and the loss of GABA interneuron/hyperglutamate hypothesis in SCZ.

Microvascular anomaly conditions in psychiatric disease. Schizophrenia - angiogenesis connection

Schizophrenia (SZ) is a severe mental disorder with unknown etiology and elusive neuropathological and neurobiological features have been a focus of many theoretical hypotheses and empirical studies. Current genetic and neurobiology information relevant to SZ implicates neuronal developmental and synaptic plasticity abnormalities, and neurotransmitter, microglial and oligodendrocytes dysfunction. Several recent theories have highlighted the neurovascular unit as a potential contributor to the pathophysiology of SZ. We explored the biological plausibility of a link between SZ and the neurovascular system by examining insights gained from genetic, neuroimaging and postmortem studies, which include gene expression and neuropathology analyses. We also reviewed information from animal models of cerebral angiogenesis in order to understand better the complex interplay between angiogenic and neurotrophic factors in development, vascular endothelium/blood brain barrier remodeling and maintenance, all of which contribute to sustaining adequate regional blood flow and safeguarding normal brain function. Microvascular and hemodynamic alterations in SZ highlight the importance of further research and reveal the neurovascular unit as a potential therapeutic target in SZ.

Association of sFlt-1 and worsening psychopathology in relatives at high risk for psychosis: A longitudinal study

BACKGROUND

Angiogenic dysfunction and abnormalities in psychopathology and brain structure have been reported in schizophrenia, but their relationships are mostly unknown. We recently demonstrated that sFlt-1, anti-angiogenic factor, was significantly elevated in patients at familial high-risk for psychosis (FHR). We hypothesized that elevated sFlt-1 correlates with baseline and longitudinal changes in psychopathology, cognition, and brain structure.

METHODS

Plasma sFlt-1 in FHR (n=35) and HC (n=39) was obtained at baseline. Schizotypal, cognitive, soft neurologic signs, and structural brain imaging (1.5T T1-weighted MRI, FreeSurfer software) measures were obtained in both groups. Longitudinal clinical and brain structural measures were obtained in a subgroup of FHR patients. Baseline data analysis used correlations between sFlt-1 and clinical/imaging measures and adjusted for multiple corrections. Linear mixed-effects models described differences in trajectories between high sFlt-1 and low sFlt-1.

RESULTS

Baseline sFlt-1 was significantly correlated with soft neurologic signs (r=0.27, p=0.02) and right entorhinal volume (r=0.50, p=0.02), but not other baseline clinical/brain structural measures. Longitudinal examination of the FHR group (sFlt-1 high, n=14; sFlt-1 low, n=14) demonstrated that high sFlt-1 was significantly associated with worsening schizotypal symptoms (t=2.4, p=0.018). Reduced right hippocampal/parahippocampal volume/thickness trajectories were observed in high versus low sFlt-1 groups.

CONCLUSIONS

The findings from this FHR study demonstrate that peripheral markers of angiogenic dysfunction can predict longitudinal clinical and brain structural changes. Also, these findings further support the hypothesis of altered microvascular circulation in schizophrenia and those at risk.

Production of high quality brain-derived neurotrophic factor (BDNF) and tropomyosin receptor kinase B (TrkB) RNA from isolated populations of rat spinal cord motor neurons obtained by Laser Capture Microdissection (LCM)

The mammalian central nervous system (CNS) is composed of multiple cellular elements, making it challenging to segregate one particular cell type to study their gene expression profile. For instance, as motor neurons represent only 5-10% of the total cell population of the spinal cord, meaningful transcriptional analysis on these neurons is almost impossible to achieve from homogenized spinal cord tissue. A major challenge faced by scientists is to obtain good quality RNA from small amounts of starting material. In this paper, we used Laser Capture Microdissection (LCM) techniques to identify and isolate spinal cord motor neurons. The present analysis revealed that perfusion with paraformaldehyde (PFA) does not alter RNA quality. RNA integrity numbers (RINs) of tissue samples from rubrospinal tract (RST)-transected, intact spinal cord or from whole spinal cord homogenate were all above 8, which indicates intact, high-quality RNA. Levels of mRNA for brain-derived neurotrophic factor (BDNF) or for its tropomyosin receptor kinase B (TrkB) were not affected by rubrospinal tract (RST) transection, a surgical procedure that deprive motor neurons from one of their main supraspinal input. The isolation of pure populations of neurons with LCM techniques allows for robust transcriptional characterization that cannot be achieved with spinal cord homogenates. Such preparations of pure population of motor neurons will provide valuable tools to advance our understanding of the molecular mechanisms underlying spinal cord injury and neuromuscular diseases. In the near future, LCM techniques might be instrumental to the success of gene therapy for these debilitating conditions.

Protein Expression of Proteasome Subunits in Elderly Patients with Schizophrenia

The ubiquitin proteasome system (UPS) is a major regulator of protein processing, trafficking, and degradation. While protein ubiquitination is utilized for many cellular processes, one major function of this system is to target proteins to the proteasome for degradation. In schizophrenia, studies have found UPS transcript abnormalities in both blood and brain, and we have previously reported decreased protein expression of ubiquitin-associated proteins in brain. To test whether the proteasome is similarly dysregulated, we measured the protein expression of proteasome catalytic subunits as well as essential subunits from proteasome regulatory complexes in 14 pair-matched schizophrenia and comparison subjects in superior temporal cortex. We found decreased expression of Rpt1, Rpt3, and Rpt6, subunits of the 19S regulatory particle essential for ubiquitin-dependent degradation by the proteasome. Additionally, the α subunit of the 11S αβ regulatory particle, which enhances proteasomal degradation of small peptides and unfolded proteins, was also decreased. Haloperidol-treated rats did not have altered expression of these subunits, suggesting the changes we observed in schizophrenia are likely not due to chronic antipsychotic treatment. Interestingly, expression of the catalytic subunits of both the standard and immunoproteasome were unchanged, suggesting the abnormalities we observed may be specific to the complexed state of the proteasome. Aging has significant effects on the proteasome, and several subunits (20S β2, Rpn10, Rpn13, 11Sβ, and 11Sγ) were significantly correlated with subject age. These data provide further evidence of dysfunction of the ubiquitin-proteasome system in schizophrenia, and suggest that altered proteasome activity may be associated with the pathophysiology of this illness.

Meta-analysis of sex differences in gene expression in schizophrenia

Schizophrenia is a severe psychiatric disorder which influences around 1 % of the worldwide population. Differences between male and female patients with schizophrenia have been noted. There is an earlier age of onset in males compared with females with this diagnosis, and in addition, there are differences in symptom profiles between the sexes. The underlying molecular mechanism of sex difference remains unclear. Here we present a comprehensive analysis to reveal the sex differences in gene expression in schizophrenia with stringent statistics criteria. We compiled a data set consisting of 89 male controls, 90 male schizophrenia patients, 35 female controls and 32 female schizophrenia patients from six independent studies of the prefrontal cortex (PFC) in postmortem brain. When we tested for a sex by diagnosis interaction on gene expression, 23 genes were up-regulated and 23 genes were down-regulated in the male group (q-value < 0.05), several genes are related to energy metabolism, while 4 genes are located on sex chromosome. No genes were statistically significant in the female group when multiple testing correction were conducted (q-value <0.05), most likely due to the small sample size. Our protocol and results from the male group provide a starting point for identifying the underlying different mechanism between male and female schizophrenia patients.

Angiogenic and immune signatures in plasma of young relatives at familial high-risk for psychosis and first-episode patients: A preliminary study

Schizophrenia (SZ) is a heterogeneous disorder that presents in adolescence, persists into adulthood, and has many clinical features. Recent evidence suggests that abnormalities in inflammatory, neurotrophic, and angiogenic processes may play a role in the etiology of SZ. The identification of molecular biomarkers early in the course of disease is crucial to transforming diagnostic and therapeutic avenues. We investigated 14 molecular analytes focusing on inflammatory, neurotrophic and angiogenic pathways from the plasma of antipsychotic-naïve familial high risk for SZ (FHR; n=35) and first-episode psychosis (FEP; n=45) subjects, in comparison to healthy controls (HC, n=39). We identified distinct alterations in molecular signatures in young relatives at FHR for SZ prior to psychosis onset and FEP subjects. Firstly, the expression of soluble fms-like tyrosine kinase (sFlt-1), an anti-angiogenic factor that binds vascular endothelial growth factor (VEGF), was significantly increased in the FHR group compared to HC, but not in FEP. Secondly, interferon gamma (IFNγ) was significantly reduced in the FEP group compared to HC. Thirdly, network analysis revealed a positive correlation between sFlt-1 and VEGF, suggesting an activation of the angiogenic cascade in the FHR group, which persists in FEP. Our results indicate an angiogenesis and immunological dysfunction early in the course of disease, shifting the balance towards anti-angiogenesis and inflammation.

Systems Genomics Support for Immune and Inflammation Hypothesis of Depression

BACKGROUND

Immune system plays an important role in brain development and function. With the discovery of increased circulating inflammatory cytokine levels in depression over two decades ago, evidence implicating immune system alterations in the disease has increasingly accumulated.

OBJECTIVE

To assess the underlying etiology and pathophysiology, a brief overview of the hypothesis free genomic, transcriptomic and proteomic studies in depression is presented here in order to specifically examine if the immune and inflammation hypothesis of depression is supported.

RESULTS

It is observed that genes identified in genome-wide association studies, and genes showing differential expression in transcriptomic studies in human depression do separately overrepresent processes related to both development as well as functioning of the immune system, and inflammatory response. These processes are also enriched in differentially expressed genes reported in animal models of antidepressant treatment. It is further noted that some of the genes identified in genome sequencing and proteomic analyses in human depression, and transcriptomic studies in chronic social defeat stress, an established animal model of depression, relate to immune and inflammatory pathways.

CONCLUSION

In conclusion, integrative genomics evidence supports the immune and inflammation hypothesis of depression.

CX3CR1 is dysregulated in blood and brain from schizophrenia patients

The molecular mechanisms underlying schizophrenia remain largely unknown. Although schizophrenia is a mental disorder, there is increasing evidence to indicate that inflammatory processes driven by diverse environmental factors play a significant role in its development. With gene expression studies having been conducted across a variety of sample types, e.g., blood and postmortem brain, it is possible to investigate convergent signatures that may reveal interactions between the immune and nervous systems in schizophrenia pathophysiology. We conducted two meta-analyses of schizophrenia microarray gene expression data (N=474) and non-psychiatric control (N=485) data from postmortem brain and blood. Then, we assessed whether significantly dysregulated genes in schizophrenia could be shared between blood and brain. To validate our findings, we selected a top gene candidate and analyzed its expression by RT-qPCR in a cohort of schizophrenia subjects stabilized by atypical antipsychotic monotherapy (N=29) and matched controls (N=31). Meta-analyses highlighted inflammation as the major biological process associated with schizophrenia and that the chemokine receptor CX3CR1 was significantly down-regulated in schizophrenia. This differential expression was also confirmed in our validation cohort. Given both the recent data demonstrating selective CX3CR1 expression in subsets of neuroimmune cells, as well as behavioral and neuropathological observations of CX3CR1 deficiency in mouse models, our results of reduced CX3CR1 expression adds further support for a role played by monocyte/microglia in the neurodevelopment of schizophrenia.

Combined application of NMR- and GC-MS-based metabonomics yields a superior urinary biomarker panel for bipolar disorder

Bipolar disorder (BD) is a debilitating mental disorder that cannot be diagnosed by objective laboratory-based modalities. Our previous studies have independently used nuclear magnetic resonance (NMR)-based and gas chromatography-mass spectrometry (GC-MS)-based metabonomic methods to characterize the urinary metabolic profiles of BD subjects and healthy controls (HC). However, the combined application of NMR spectroscopy and GC-MS may identify a more comprehensive metabolite panel than any single metabonomic platform alone. Therefore, here we applied a dual platform (NMR spectroscopy and GC-MS) that generated a panel of five metabolite biomarkers for BD-four GC-MS-derived metabolites and one NMR-derived metabolite. This composite biomarker panel could effectively discriminate BD subjects from HC, achieving an area under receiver operating characteristic curve (AUC) values of 0.974 in a training set and 0.964 in a test set. Moreover, the diagnostic performance of this panel was significantly superior to the previous single platform-derived metabolite panels. Thus, the urinary biomarker panel identified here shows promise as an effective diagnostic tool for BD. These findings also demonstrate the complementary nature of NMR spectroscopy and GC-MS for metabonomic analysis, suggesting that the combination of NMR spectroscopy and GC-MS can identify a more comprehensive metabolite panel than applying each platform in isolation.

Identification of novel loci for bipolar I disorder in a multi-stage genome-wide association study

OBJECTIVE

Identification of genetic variants that influence bipolar I disorder (BPD-I) through genome-wide association (GWA) studies is limited in Asian populations. The current study aimed to identify novel common variants for BPD-I in an ethnically homogeneous Taiwanese sample using a multi-stage GWA study design.

METHOD

At the discovery stage, 200 BPD-I patients and 200 controls that combined to form 16 pools were genotyped with 1 million markers. Utilizing a newly developed rank-based method, top-ranked markers were selected. After validation with individual genotyping, a fine-mapping association study was conducted to identify associated loci using 240 patients and 240 controls. At the last stage, independent samples were collected (351 cases and 341 controls) for replication.

RESULTS

Among the top-ranked markers from the discovery stage, eight genes and 15 individual SNPs were evaluated in the fine-mapping stage. At this stage, rs7619173, which is not in a gene coding region, showed the most significant association (P = 2 ∗ 10(-5)) with BPD-I. Four genes had empirical P-values<0.05, including KCNH7 (P = 0.0047), MYST4 (P = 0.0047), NRXN3 (P = 0.0095), and SEMA3D (P = 0.037). For markers genotyped in replication samples, rs7619173 exhibited a significant association (P(combined) = 2 ∗ 10(-4)) after multiple testing correction, while markers rs11001178 (MYST4) and rs2217887 (NRXN3) showed weak associations (P(combined) = 0.02) with BPD-I.

CONCLUSION

A multi-stage GWA design has the potential to uncover the underlying pathogenesis of a complex trait. Findings in the present study highlight three loci that warrant further investigation for bipolar.

Gene expression alterations in bipolar disorder postmortem brains

OBJECTIVES

  Bipolar disorder (BD) is a mental illness of unknown neuropathology and has several genetic associations. Antipsychotics are effective for the treatment of acute mania, psychosis, or mixed states in individuals with BD. We aimed to identify gene transcripts differentially expressed in postmortem brains from antipsychotics-exposed individuals with BD (hereafter the 'exposed' group), non-exposed individuals with BD (hereafter the 'non-exposed' group), and controls.

METHODS

  We quantified the abundance of gene transcripts in postmortem brains from seven exposed individuals, seven non-exposed individuals, and 12 controls with the Affymetrix U133P2 GeneChip microarrays and technologies. We applied a q-value of ≤0.005 to identify statistically significant transcripts with mean abundance differences between the exposed, non-exposed and control groups.

RESULTS

  We identified 2191 unique genes with significantly altered expression levels in non-exposed brains compared to those in the control and exposed groups. The expression levels of these genes were not significantly different between exposed brains and controls, suggesting a normalization effect of antipsychotics on the expression of these genes. Gene ontology (GO) enrichment analysis showed significant (Bonferroni p ≤ 0.05) clustering of subgroups of the 2191 genes under many GO terms; notably, the protein products of genes enriched are critical to the function of synapses, affecting, for example, intracellular trafficking and synaptic vesicle biogenesis, transport, release and recycling, as well as organization and stabilization of the node of Ranvier.

CONCLUSIONS

  These results support a hypothesis of synaptic and intercellular communication impairment in BD. The apparent normalization of expression patterns with exposure to antipsychotic medication may represent a physiological process that relates both to etiology and improvement patterns of the disorder.

Pathway analysis of the human brain transcriptome in disease

Pathway analysis is a powerful method for discerning differentially regulated genes and elucidating their biological importance. It allows for the identification of perturbed or aberrantly expressed genes within a biological context from extensive data sets and offers a simplistic approach for interrogating such data sets. With the growing use of microarrays and RNA-Seq, data for genome-wide studies are growing at an alarming rate, and the use of deep sequencing is revealing elements of the genome previously uncharacterised. Through the employment of pathway analysis, mechanisms in complex diseases may be explored and novel causatives found primarily through differentially regulated genes. Further, with the implementation of next generation sequencing, a deeper resolution may be attained, particularly in identification of isoform diversity and SNPs. Here, we look at a broad overview of pathway analysis in the human brain transcriptome and its relevance in teasing out underlying causes of complex diseases. We will outline processes in data gathering and analysis of particular diseases in which these approaches have been successful.

Responder and nonresponder patients exhibit different peripheral transcriptional signatures during major depressive episode

To date, it remains impossible to guarantee that short-term treatment given to a patient suffering from a major depressive episode (MDE) will improve long-term efficacy. Objective biological measurements and biomarkers that could help in predicting the clinical evolution of MDE are still warranted. To better understand the reason nearly half of MDE patients respond poorly to current antidepressive treatments, we examined the gene expression profile of peripheral blood samples collected from 16 severe MDE patients and 13 matched controls. Using a naturalistic and longitudinal design, we ascertained mRNA and microRNA (miRNA) expression at baseline, 2 and 8 weeks later. On a genome-wide scale, we detected transcripts with roles in various biological processes as significantly dysregulated between MDE patients and controls, notably those involved in nucleotide binding and chromatin assembly. We also established putative interactions between dysregulated mRNAs and miRNAs that may contribute to MDE physiopathology. We selected a set of mRNA candidates for quantitative reverse transcriptase PCR (RT-qPCR) to validate that the transcriptional signatures observed in responders is different from nonresponders. Furthermore, we identified a combination of four mRNAs (PPT1, TNF, IL1B and HIST1H1E) that could be predictive of treatment response. Altogether, these results highlight the importance of studies investigating the tight relationship between peripheral transcriptional changes and the dynamic clinical progression of MDE patients to provide biomarkers of MDE evolution and prognosis.

Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction

We have used a translational convergent functional genomics (CFG) approach to identify and prioritize genes involved in schizophrenia, by gene-level integration of genome-wide association study data with other genetic and gene expression studies in humans and animal models. Using this polyevidence scoring and pathway analyses, we identify top genes (DISC1, TCF4, MBP, MOBP, NCAM1, NRCAM, NDUFV2, RAB18, as well as ADCYAP1, BDNF, CNR1, COMT, DRD2, DTNBP1, GAD1, GRIA1, GRIN2B, HTR2A, NRG1, RELN, SNAP-25, TNIK), brain development, myelination, cell adhesion, glutamate receptor signaling, G-protein-coupled receptor signaling and cAMP-mediated signaling as key to pathophysiology and as targets for therapeutic intervention. Overall, the data are consistent with a model of disrupted connectivity in schizophrenia, resulting from the effects of neurodevelopmental environmental stress on a background of genetic vulnerability. In addition, we show how the top candidate genes identified by CFG can be used to generate a genetic risk prediction score (GRPS) to aid schizophrenia diagnostics, with predictive ability in independent cohorts. The GRPS also differentiates classic age of onset schizophrenia from early onset and late-onset disease. We also show, in three independent cohorts, two European American and one African American, increasing overlap, reproducibility and consistency of findings from single-nucleotide polymorphisms to genes, then genes prioritized by CFG, and ultimately at the level of biological pathways and mechanisms. Finally, we compared our top candidate genes for schizophrenia from this analysis with top candidate genes for bipolar disorder and anxiety disorders from previous CFG analyses conducted by us, as well as findings from the fields of autism and Alzheimer. Overall, our work maps the genomic and biological landscape for schizophrenia, providing leads towards a better understanding of illness, diagnostics and therapeutics. It also reveals the significant genetic overlap with other major psychiatric disorder domains, suggesting the need for improved nosology.

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

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

Finding the needle in the haystack: a review of microarray gene expression research into schizophrenia

BACKGROUND

With an estimated 80% heritability, molecular genetic research into schizophrenia has remained inconclusive. Recent large-scale, genome-wide association studies only identified a small number of susceptibility genes with individually very small effect sizes. However, the variable expression of the phenotype is not well captured in diagnosis-based research as well as when assuming a 'heterogenic risk model' (as apposed to a monogenic or polygenic model). Hence, the expression of susceptibility genes in response to environmental factors in concert with other disease-promoting or protecting genes has increasingly attracted attention.

METHOD

The current review summarises findings of microarray gene expression research with relevance to schizophrenia as they emerged over the past decade.

RESULTS

Most findings from post mortem, peripheral tissues and animal models to date have linked altered gene expression in schizophrenia to presynaptic function, signalling, myelination, neural migration, cellular immune mechanisms, and response to oxidative stress consistent with multiple small effects of many individual genes. However, the majority of results are difficult to interpret due to small sample sizes (i.e. potential type-2 errors), confounding factors (i.e. medication effects) or lack of plausible neurobiological theory.

CONCLUSION

Nevertheless, microarray gene expression research is likely to play an important role in the future when investigating gene/gene and gene/environment interactions by adopting a neurobiologically sound theoretical framework.

Better understanding of mechanisms of schizophrenia and bipolar disorder: from human gene expression profiles to mouse models

The molecular mechanisms of major mental illnesses, such as schizophrenia and bipolar disorder, are unclear. To address this fundamental question, many groups have studied molecular expression profiles in postmortem brains and other tissues from patients compared with those from normal controls. Development of unbiased high-throughput approaches, such as microarray, RNA-seq, and proteomics, have supported and facilitated this endeavor. In addition to genes directly involved in neuron/glia signaling, especially those encoding for synaptic proteins, genes for metabolic cascades are differentially expressed in the brains of patients with schizophrenia and bipolar disorder, compared with those from normal controls in DNA microarray studies. Here we propose the importance and usefulness of genetic mouse models in which such differentially expressed molecules are modulated. These animal models allow us to dissect the mechanisms of how such molecular changes in patient brains may play a role in neuronal circuitries and overall behavioral phenotypes. We also point out that models in which the metabolic genes are modified are obviously untested from mental illness viewpoints, suggesting the potential to re-address these models with behavioral assays and neurochemical assessments.

Convergent functional genomic studies of ω-3 fatty acids in stress reactivity, bipolar disorder and alcoholism

Omega-3 fatty acids have been proposed as an adjuvant treatment option in psychiatric disorders. Given their other health benefits and their relative lack of toxicity, teratogenicity and side effects, they may be particularly useful in children and in females of child-bearing age, especially during pregnancy and postpartum. A comprehensive mechanistic understanding of their effects is needed. Here we report translational studies demonstrating the phenotypic normalization and gene expression effects of dietary omega-3 fatty acids, specifically docosahexaenoic acid (DHA), in a stress-reactive knockout mouse model of bipolar disorder and co-morbid alcoholism, using a bioinformatic convergent functional genomics approach integrating animal model and human data to prioritize disease-relevant genes. Additionally, to validate at a behavioral level the novel observed effects on decreasing alcohol consumption, we also tested the effects of DHA in an independent animal model, alcohol-preferring (P) rats, a well-established animal model of alcoholism. Our studies uncover sex differences, brain region-specific effects and blood biomarkers that may underpin the effects of DHA. Of note, DHA modulates some of the same genes targeted by current psychotropic medications, as well as increases myelin-related gene expression. Myelin-related gene expression decrease is a common, if nonspecific, denominator of neuropsychiatric disorders. In conclusion, our work supports the potential utility of omega-3 fatty acids, specifically DHA, for a spectrum of psychiatric disorders such as stress disorders, bipolar disorder, alcoholism and beyond.

Single-cell Tsc1 knockout during corticogenesis generates tuber-like lesions and reduces seizure threshold in mice

Tuberous sclerosis complex (TSC) is an autosomal dominant disorder characterized by mutations in Tsc1 or Tsc2 that lead to mammalian target of rapamycin (mTOR) hyperactivity. Patients with TSC suffer from intractable seizures resulting from cortical malformations known as tubers, but research into how these tubers form has been limited because of the lack of an animal model. To address this limitation, we used in utero electroporation to knock out Tsc1 in selected neuronal populations in mice heterozygous for a mutant Tsc1 allele that eliminates the Tsc1 gene product at a precise developmental time point. Knockout of Tsc1 in single cells led to increased mTOR activity and soma size in the affected neurons. The mice exhibited white matter heterotopic nodules and discrete cortical tuber-like lesions containing cytomegalic and multinucleated neurons with abnormal dendritic trees resembling giant cells. Cortical tubers in the mutant mice did not exhibit signs of gliosis. Furthermore, phospho-S6 immunoreactivity was not upregulated in Tsc1-null astrocytes despite a lower seizure threshold. Collectively, these data suggest that a double-hit strategy to eliminate Tsc1 in discrete neuronal populations generates TSC-associated cortical lesions, providing a model to uncover the mechanisms of lesion formation and cortical hyperexcitability. In addition, the absence of glial reactivity argues against a contribution of astrocytes to lesion-associated hyperexcitability.

The first decade and beyond of transcriptional profiling in schizophrenia

Gene expression changes in brains of individuals with schizophrenia (SZ) have been hypothesized to reflect possible pathways related to pathophysiology and/or medication. Other factors having robust effects on gene expression profiling in brain and possibly influence the schizophrenia transcriptome such as age and pH are examined. Pathways of curated gene expression or gene correlation networks reported in SZ (white matter, apoptosis, neurogenesis, synaptic plasticity, glutamatergic and GABAergic neurotransmission, immune and stress-response, mitochondrial, and neurodevelopment) are not unique to SZ and have been associated with other psychiatric disorders. Suggestions going forward to improve the next decade of profiling: consider multiple brain regions that are carefully dissected, release large datasets from multiple brain regions in controls to better understand neurocircuitry, integrate genetics and gene expression, measure expression variants on genome wide level, peripheral biomarker studies, and analyze the transcriptome across a developmental series of brains. Gene expression, while an important feature of the genomic landscape, requires further systems biology to advance from control brains to a more precise definition of the schizophrenia interactome.

Analyzing schizophrenia by DNA microarrays

To understand the pathological processes of schizophrenia, we must embrace the analysis of the diseased human brain: we will never be able to recapitulate the pathology of uniquely human disorders in an animal model. Based on the outcome of the transcriptome profiling experiments performed to date, it appears that schizophrenia is associated with a global gene expression disturbance across many cortical regions. In addition, transcriptome changes are present in multiple cell types, including specific subclasses of principal neurons, interneurons, and oligodendrocytes. Furthermore, transcripts related to synaptic transmission, energy metabolism, and inhibitory neurotransmission are routinely found underexpressed in the postmortem brain tissue of subjects with schizophrenia. To put these transcriptome data in biological context, we must make our data publicly available and report our findings in a proper, expanded Minimum Information About a Microarray Experiment format. Cell-type specific expression profiling and sequencing-based transcript assessments should be expanded, with particular attention to understanding splice-variant changes in various mental disorders. Deciphering the pathophysiology of mental disorders depends on integrating data from across many research fields and techniques. Leads from postmortem transcriptome profiling will be essential to generate model animals, perform tissue culture experiments, and develop or evaluate novel drugs to treat this devastating disorder.

An integrated genomic analysis of gene-function correlation on schizophrenia susceptibility genes

Schizophrenia is a highly complex inheritable disease characterized by numerous genetic susceptibility elements, each contributing a modest increase in risk for the disease. Although numerous linkage or association studies have identified a large set of schizophrenia-associated loci, many are controversial. In addition, only a small portion of these loci overlaps with the large cumulative pool of genes that have shown changes of expression in schizophrenia. Here, we applied a genomic gene-function approach to identify susceptibility loci that show direct effect on gene expression, leading to functional abnormalities in schizophrenia. We carried out an integrated analysis by cross-examination of the literature-based susceptibility loci with the schizophrenia-associated expression gene list obtained from our previous microarray study (Journal of Human Genetics (2009) 54: 665-75) using bioinformatic tools, followed by confirmation of gene expression changes using qPCR. We found nine genes (CHGB, SLC18A2, SLC25A27, ESD, C4A/C4B, TCP1, CHL1 and CTNNA2) demonstrate gene-function correlation involving: synapse and neurotransmission; energy metabolism and defense mechanisms; and molecular chaperone and cytoskeleton. Our findings further support the roles of these genes in genetic influence and functional consequences on the development of schizophrenia. It is interesting to note that four of the nine genes are located on chromosome 6, suggesting a special chromosomal vulnerability in schizophrenia.