Transcriptomic abnormalities in peripheral blood in bipolar disorder, and discrimination of the major psychoses.

We performed a transcriptome-wide meta-analysis and gene co-expression network analysis to identify genes and gene networks dysregulated in the peripheral blood of bipolar disorder (BD) cases relative to unaffected comparison subjects, and determined the specificity of the transcriptomic signatures of BD and schizophrenia (SZ). Nineteen genes and 4 gene modules were significantly differentially expressed in BD cases. Thirteen gene modules were shown to be differentially expressed in a combined case-group of BD and SZ subjects called "major psychosis", including genes biologically linked to apoptosis, reactive oxygen, chromatin remodeling, and immune signaling. No modules were differentially expressed between BD and SZ cases. Machine-learning classifiers trained to separate diagnostic classes based solely on gene expression profiles could distinguish BD cases from unaffected comparison subjects with an area under the curve (AUC) of 0.724, as well as BD cases from SZ cases with AUC = 0.677 in withheld test samples. We introduced a novel and straightforward method called "polytranscript risk scoring" that could distinguish BD cases from unaffected subjects (AUC = 0.672) and SZ cases (AUC = 0.607) significantly better than expected by chance. Taken together, our results highlighted gene expression alterations common to BD and SZ that involve biological processes of inflammation, oxidative stress, apoptosis, and chromatin regulation, and highlight disorder-specific changes in gene expression that discriminate the major psychoses.

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.

Altered neural signaling and immune pathways in peripheral blood mononuclear cells of schizophrenia patients with cognitive impairment: A transcriptome analysis.

Cognitive deficits are a core feature of schizophrenia and contribute significantly to functional disability. We investigated the molecular pathways associated with schizophrenia (SZ; n=47) cases representing both 'cognitive deficit' (CD; n=22) and 'cognitively spared' (CS; n=25) subtypes of schizophrenia (based on latent class analysis of 9 cognitive performance indicators), compared with 49 healthy controls displaying 'normal' cognition. This was accomplished using gene-set analysis of transcriptome data derived from peripheral blood mononuclear cells (PBMCs). We detected 27 significantly altered pathways (19 pathways up-regulated and 8 down-regulated) in the combined SZ group and a further 6 pathways up-regulated in the CS group and 5 altered pathways (4 down-regulated and 1 up-regulated) in the CD group. The transcriptome profiling in SZ and cognitive subtypes were characterized by the up-regulated pathways involved in immune dysfunction (e.g., antigen presentation in SZ), energy metabolism (e.g., oxidative phosphorylation), and down-regulation of the pathways involved in neuronal signaling (e.g., WNT in SZ/CD and ERBB in SZ). When we looked for pathways that differentiated the two cognitive subtypes we found that the WNT signaling was significantly down-regulated (FDR<0.05) in the CD group in accordance with the combined SZ cohort, whereas it was unaffected in the CS group. This suggested suppression of WNT signaling was a defining feature of cognitive decline in schizophrenia. The WNT pathway plays a role in both the development/function of the central nervous system and peripheral tissues, therefore its alteration in PBMCs may be indicative of an important genomic axis relevant to cognition in the neuropathology of schizophrenia.

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.

Optimal consistency in microRNA expression analysis using reference-gene-based normalization.

Normalization of high-throughput molecular expression profiles secures differential expression analysis between samples of different phenotypes or biological conditions, and facilitates comparison between experimental batches. While the same general principles apply to microRNA (miRNA) normalization, there is mounting evidence that global shifts in their expression patterns occur in specific circumstances, which pose a challenge for normalizing miRNA expression data. As an alternative to global normalization, which has the propensity to flatten large trends, normalization against constitutively expressed reference genes presents an advantage through their relative independence. Here we investigated the performance of reference-gene-based (RGB) normalization for differential miRNA expression analysis of microarray expression data, and compared the results with other normalization methods, including: quantile, variance stabilization, robust spline, simple scaling, rank invariant, and Loess regression. The comparative analyses were executed using miRNA expression in tissue samples derived from subjects with schizophrenia and non-psychiatric controls. We proposed a consistency criterion for evaluating methods by examining the overlapping of differentially expressed miRNAs detected using different partitions of the whole data. Based on this criterion, we found that RGB normalization generally outperformed global normalization methods. Thus we recommend the application of RGB normalization for miRNA expression data sets, and believe that this will yield a more consistent and useful readout of differentially expressed miRNAs, particularly in biological conditions characterized by large shifts in miRNA expression.

Antipsychotic drug-associated gene-miRNA interaction in T-lymphocytes.

Antipsychotic drugs (APDs) can have a profound effect on the human body that extends well beyond our understanding of their neuropsychopharmacology. Some of these effects manifest themselves in peripheral blood lymphocytes, and in some cases, particularly in clozapine treatment, result in serious complications. To better understand the molecular biology of APD action in lymphocytes, we investigated the influence of chlorpromazine, haloperidol and clozapine in vitro, by microarray-based gene and microRNA (miRNA) expression analysis. JM-Jurkat T-lymphocytes were cultured in the presence of the APDs or vehicle alone over 2 wk to model the early effects of APDs on expression. Interestingly both haloperidol and clozapine appear to regulate the expression of a large number of genes. Functional analysis of APD-associated differential expression revealed changes in genes related to oxidative stress, metabolic disease and surprisingly also implicated pathways and biological processes associated with neurological disease consistent with current understanding of the activity of APDs. We also identified miRNA-mRNA interaction associated with metabolic pathways and cell death/survival, all which could have relevance to known side effects of APDs. These results indicate that APDs have a significant effect on expression in peripheral tissue that relate to both known mechanisms as well as poorly characterized side effects.

Gene expression profiling in treatment-naive schizophrenia patients identifies abnormalities in biological pathways involving AKT1 that are corrected by antipsychotic medication.

Distinct gene expression profiles can be detected in peripheral blood mononuclear cells (PBMCs) in patients with schizophrenia; however, little is known about the effects of antipsychotic medication. This study compared gene expression profiles in PMBCs from treatment-naive patients with schizophrenia before and after antipsychotic drug treatment. PBMCs were obtained from 10 treatment-naive schizophrenia patients before and 6 wk after initiating antipsychotic drug treatment and compared to PMBCs collected from 11 healthy community volunteers. Genome-wide expression profiling was conducted using Illumina HumanHT-12 expression bead arrays and analysed using significance analysis of microarrays. This analysis identified 624 genes with altered expression (208 up-regulated, 416 down-regulated) prior to antipsychotic treatment (p < 0.05) including schizophrenia-associated genes AKT1, DISC1 and DGCR6. After 6-8 wk treatment of patients with risperidone or risperidone in combination with haloperidol, only 106 genes were altered, suggesting that the treatment corrected the expression of a large proportion of genes back to control levels. However, 67 genes continued to show the same directional change in expression after treatment. Ingenuity® pathway analysis and gene set enrichment analysis implicated dysregulation of biological functions and pathways related to inflammation and immunity in patients with schizophrenia. A number of the top canonical pathways dysregulated in treatment-naive patients signal through AKT1 that was up-regulated. After treatment, AKT1 returned to control levels and less dysregulation of these canonical pathways was observed. This study supports immune dysfunction and pathways involving AKT1 in the aetiopathophysiology of schizophrenia and their response to antipsychotic medication.

Gene expression analysis reveals schizophrenia-associated dysregulation of immune pathways in peripheral blood mononuclear cells.

Peripheral blood mononuclear cells (PBMCs) represent an accessible tissue source for gene expression profiling in schizophrenia that could provide insight into the molecular basis of the disorder. This study used the Illumina HT_12 microarray platform and quantitative real time PCR (QPCR) to perform mRNA expression profiling on 114 patients with schizophrenia or schizoaffective disorder and 80 non-psychiatric controls from the Australian Schizophrenia Research Bank (ASRB). Differential expression analysis revealed altered expression of 164 genes (59 up-regulated and 105 down-regulated) in the PBMCs from patients with schizophrenia compared to controls. Bioinformatic analysis indicated significant enrichment of differentially expressed genes known to be involved or associated with immune function and regulating the immune response. The differential expression of 6 genes, EIF2C2 (Ago 2), MEF2D, EVL, PI3, S100A12 and DEFA4 was confirmed by QPCR. Genome-wide expression analysis of PBMCs from individuals with schizophrenia was characterized by the alteration of genes with immune system function, supporting the hypothesis that the disorder has a significant immunological component in its etiology.

Dysregulation of miRNA 181b in the temporal cortex in schizophrenia.

Analysis of global microRNA (miRNA) expression in postmortem cortical grey matter from the superior temporal gyrus, revealed significant up-regulation of miR-181b expression in schizophrenia. This finding was supported by quantitative real-time RT-PCR analysis of miRNA expression in a cohort of 21 matched pairs of schizophrenia and non-psychiatric controls. The implications of this finding are substantial, as this miRNA is predicted to regulate many target genes with potential significance to the development of schizophrenia. They include the calcium sensor gene visinin-like 1 (VSNL1) and the ionotropic AMPA glutamate receptor subunit (GRIA2), which were found to be down-regulated in the same cortical tissue from the schizophrenia group. Both of these genes were also suppressed in miR-181b transfected cells and shown to contain functional miR-181b miRNA recognition elements by reporter gene assay. This study suggests altered miRNA levels could be a significant factor in the dysregulation of cortical gene expression in schizophrenia.