Putative psychosis genes in the prefrontal cortex: combined analysis of gene expression microarrays

Diagnostic Specificity and Association With Cognition of Molecular Alterations in Prefrontal Somatostatin Neurons in Schizophrenia

Importance

Individuals with schizophrenia (SZ) exhibit pronounced deficits in somatostatin (SST) messenger RNA (mRNA) levels in the dorsolateral prefrontal cortex (DLPFC). Molecularly distinct subtypes of SST neurons, located in the superficial and deep zones of the DLPFC, are thought to contribute to different functional processes of this region; understanding the specificity of SST alterations in SZ across these zones could inform the functional consequences of those alterations, including cognitive impairments characteristic of SZ.

Objective

To quantify mRNA levels of SST and related neuropeptides in the DLPFC in individuals with SZ, bipolar disorder (BPD), or major depressive disorder (MDD) and unaffected comparison individuals.

Design, Setting, and Participants

This case-control study, conducted from January 20, 2020, to March 30, 2022, used postmortem brain tissue specimens previously obtained from individuals with SZ, MDD, or BPD and unaffected individuals from a community population through 2 medical examiners' offices. Demographic, clinical, and educational information was ascertained through psychological autopsies.

Exposures

Diagnosis of SZ, BPD, or MDD.

Main Outcome and Measures

The main outcome was levels of SST and related neuropeptide mRNA in 2 DLPFC zones, examined using laser microdissection and quantitative polymerase chain reaction or fluorescent in situ hybridization (FISH). Findings were compared using educational attainment as a proxy measure of premorbid cognition.

Results

A total of 200 postmortem brain specimens were studied, including 65 from unaffected comparison individuals (42 [65%] male; mean [SD] age, 49.2 [14.1] years); 54 from individuals with SZ (37 [69%] male; mean [SD] age, 47.5 [13.3] years); 42 from individuals with MDD (24 [57%] male; mean [SD] age, 45.6 [12.1] years); and 39 from individuals with BPD (23 [59%] male; mean (SD) age, 46.2 [12.5] years). Compared with unaffected individuals, levels of SST mRNA were lower in both superficial (Cohen d, 0.68; 95% CI, 0.23-1.13; P = .004) and deep (Cohen d, 0.60; 95% CI, 0.16-1.04; P = .02) DLPFC zones in individuals with SZ; findings were confirmed using FISH. Levels of SST were lower only in the superficial zone in the group with MDD (Cohen d, 0.58; 95% CI, 0.14-1.02; P = .12), but the difference was not significant; SST levels were not lower in either zone in the BPD group. Levels of neuropeptide Y and tachykinin 1 showed similar patterns. Neuropeptide alterations in the superficial, but not deep, zone were associated with lower educational attainment only in the group with SZ (superficial: adjusted odds ratio, 1.71 [95% CI, 1.11-2.69]; P = .02; deep: adjusted odds ratio, 1.08 [95% CI, 0.64-1.84]; P = .77).

Conclusions and Relevance

The findings revealed diagnosis-specific patterns of molecular alterations in SST neurons in the DLPFC, suggesting that distinct disease processes are reflected in the differential vulnerability of SST neurons in individuals with SZ, MDD, and BPD. In SZ, alterations specifically in the superficial zone may be associated with cognitive dysfunction.

A Potential Biomarker for Predicting Schizophrenia: Metallothionein-1

It has been thought that oxidative damage may occur in the pathophysiology of schizophrenia; metallothioneins (MT) have strong antioxidant functions. In this study, we aimed to measure MT-1 levels in schizophrenia patients. A total of 52 patients diagnosed with schizophrenia and 38 healthy controls were included in the study. Serum MT-1 concentrations were measured using the Human Metallothionein-1 ELISA Kit. In addition, Cu and Zn levels were measured. PANSS (Positive and Negative Syndrome Scale) was used to determine the disease severity of patients with schizophrenia. The MT-1 levels of the schizophrenia group were lower than the MT-1 levels of the control group. When the correlation analyses were examined, a positive correlation was found between MT-1 and illness duration and Cu/Zn. A negative correlation was found between MT-1 levels and PANSS total scores and PANSS positive scores. In the regression analysis, it was seen that the decrease in MT-1 levels poses a risk for schizophrenia. It was observed that a decrease of 1 ng/mL in MT-1 levels increased the risk of schizophrenia 1.115 times. The low concentration of MT-1 is likely to cause a deficiency in antioxidant defense in patients with schizophrenia. MT-1 may be a useful biomarker for predicting schizophrenia.

Changes in nitric oxide, zinc and metallothionein levels in limbic regions at pre-pubertal and post-pubertal ages presented in an animal model of schizophrenia

Recent data suggest that rats with neonatal ventral hippocampal lesion (NVHL) show changes related to inflammatory processes and oxidative stress at the prefrontal cortex (PFC) level at post-pubertal age. The NVHL model is considered an animal model in schizophrenia. Here we analyzed the levels of nitrite, zinc, and metallothionein (MT) in cortical and subcortical regions of NVHL rats at pre-pubertal and post-pubertal ages. Nitric oxide (NO) levels were evaluated through measurement of nitrite levels. The locomotor activity was also evaluated in a novel environment. Animals with NVHL showed an increase in locomotor activity only at post-pubertal age. Furthermore, at pre-pubertal age, NVHL rats showed an increase in NO levels in ventral and dorsal hippocampus, thalamus, Caudate-putamen (CPu) and brainstem, in zinc levels in ventral and dorsal hippocampus, and CPu, and the MT level also in the ventral hippocampus and occipital cortex. In addition, at pre-pubertal age, a reduction in MT levels was also found in the PFC, parietal and temporal cortices, the CPu and the cerebellum. However, after puberty, NVHL caused an increase in NO levels in the PFC, and also zinc levels in the PFC and occipital and parietal cortices, with a reduction in MT levels in the thalamus and NAcc. Our results show the changes of these three molecules over time, among lesion (PD7), pre-pubertal and post-pubertal ages. This suggests changes at pre-pubertal age directly related to the site of the lesion, while at post-pubertal age, our data highlight changes in the PFC, a region mainly involved in schizophrenia.

Integrative In Silico Analysis of Genome-Wide DNA Methylation Profiles in Schizophrenia

Schizophrenia (SZ) is a complex and severe psychiatric disorder, which has a global lifetime prevalence of 0.4% and a heritability of around 0.81. A number of epigenome-wide association studies (EWAS) have been carried out for SZ, with discordant results. The main aim of this study was to carry out an integrative in silico analysis of available genome-wide DNA methylation profiles in schizophrenia. In this work, an integration of multiple lines of evidence (top candidate genes from several EWAS and genome-wide expression and association data) was carried out, in order to identify top differentially methylated (DM) genes for SZ. In addition, functional enrichment and protein-protein interaction analyses were carried out. Several top differentially methylated genes, such as APC, CACNB2, and PRKN, were found, and an enrichment of binding sites for brain-expressed transcription factors, such as FOXO1, MYB, and ZIC3, was also observed. Moreover, a protein-protein interaction network showed a central role for DISC1 and ZNF688 genes, and experimentally validated targets of MIR-137, such as and KCNB2, NRXN1, and SYN2, were identified among DM genes. This is the first integrative in silico analysis of available genome-wide DNA methylation profiles in schizophrenia. This work identified novel candidate genes and pathways for SZ and provides the basis to explore their role in the pathogenesis of SZ in future studies.

Meta-Analysis of Transcriptomic Data of Dorsolateral Prefrontal Cortex and of Peripheral Blood Mononuclear Cells Identifies Altered Pathways in Schizophrenia

Schizophrenia (SCZ) is a psychiatric disorder characterized by both positive and negative symptoms, including cognitive dysfunction, decline in motivation, delusion and hallucinations. Antipsychotic agents are currently the standard of care treatment for SCZ. However, only about one-third of SCZ patients respond to antipsychotic medications. In the current study, we have performed a meta-analysis of publicly available whole-genome expression datasets on Brodmann area 46 of the brain dorsolateral prefrontal cortex in order to prioritize potential pathways underlying SCZ pathology. Moreover, we have evaluated whether the differentially expressed genes in SCZ belong to specific subsets of cell types. Finally, a cross-tissue comparison at both the gene and functional level was performed by analyzing the transcriptomic pattern of peripheral blood mononuclear cells of SCZ patients. Our study identified a robust disease-specific set of dysfunctional biological pathways characterizing SCZ patients that could in the future be exploited as potential therapeutic targets.

Consistent gene signature of schizophrenia identified by a novel feature selection strategy from comprehensive sets of transcriptomic data

The etiology of schizophrenia (SCZ) is regarded as one of the most fundamental puzzles in current medical research, and its diagnosis is limited by the lack of objective molecular criteria. Although plenty of studies were conducted, SCZ gene signatures identified by these independent studies are found highly inconsistent. As one of the most important factors contributing to this inconsistency, the feature selection methods used currently do not fully consider the reproducibility among the signatures discovered from different datasets. Therefore, it is crucial to develop new bioinformatics tools of novel strategy for ensuring a stable discovery of gene signature for SCZ. In this study, a novel feature selection strategy (1) integrating repeated random sampling with consensus scoring and (2) evaluating the consistency of gene rank among different datasets was constructed. By systematically assessing the identified SCZ signature comprising 135 differentially expressed genes, this newly constructed strategy demonstrated significantly enhanced stability and better differentiating ability compared with the feature selection methods popular in current SCZ research. Based on a first-ever assessment on methods’ reproducibility cross-validated by independent datasets from three representative studies, the new strategy stood out among the popular methods by showing superior stability and differentiating ability. Finally, 2 novel and 17 previously reported transcription factors were identified and showed great potential in revealing the etiology of SCZ. In sum, the SCZ signature identified in this study would provide valuable clues for discovering diagnostic molecules and potential targets for SCZ.

Co-shared genetics and possible risk gene pathway partially explain the comorbidity of schizophrenia, major depressive disorder, type 2 diabetes, and metabolic syndrome

Schizophrenia (SCZ) and major depressive disorder (MDD) in treatment-naive patients are associated with increased risk for type 2 diabetes (T2D) and metabolic syndrome (MetS). SCZ, MDD, T2D, and MetS are often comorbid and their comorbidity increases cardiovascular risk: Some risk genes are likely co-shared by them. For instance, transcription factor 7-like 2 (TCF7L2) and proteasome 26S subunit, non-ATPase 9 (PSMD9) are two genes independently reported as contributing to T2D and SCZ, and PSMD9 to MDD as well. However, there are scarce data on the shared genetic risk among SCZ, MDD, T2D, and/or MetS. Here, we briefly describe T2D, MetS, SCZ, and MDD and their genetic architecture. Next, we report separately about the comorbidity of SCZ and MDD with T2D and MetS, and their respective genetic overlap. We propose a novel hypothesis that genes of the prolactin (PRL)-pathway may be implicated in the comorbidity of these disorders. The inherited predisposition of patients with SCZ and MDD to psychoneuroendocrine dysfunction may confer increased risk of T2D and MetS. We illustrate a strategy to identify risk variants in each disorder and in their comorbid psychoneuroendocrine and mental-metabolic dysfunctions, advocating for studies of genetically homogeneous and phenotype-rich families. The results will guide future studies of the shared predisposition and molecular genetics of new homogeneous endophenotypes of SCZ, MDD, and metabolic impairment.

Aberrant transcriptomes and DNA methylomes define pathways that drive pathogenesis and loss of brain laterality/asymmetry in schizophrenia and bipolar disorder

Although the loss of brain laterality is one of the most consistent modalities in schizophrenia (SCZ) and bipolar disorder (BD), its molecular basis remains elusive. Our limited previous studies indicated that epigenetic modifications are key to the asymmetric transcriptomes of brain hemispheres. We used whole-genome expression microarrays to profile postmortem brain samples from subjects with SCZ, psychotic BD [BD[+]] or non-psychotic BD [BD(-)], or matched controls (10/group) and performed whole-genome DNA methylation (DNAM) profiling of the same samples (3-4/group) to identify pathways associated with SCZ or BD[+] and genes/sites susceptible to epigenetic regulation. qRT-PCR and quantitative DNAM analysis were employed to validate findings in larger sample sets (35/group). Gene Set Enrichment Analysis (GSEA) demonstrated that BMP signaling and astrocyte and cerebral cortex development are significantly (FDR q < 0.25) coordinately upregulated in both SCZ and BD[+], and glutamate signaling and TGFβ signaling are significantly coordinately upregulated in SCZ. GSEA also indicated that collagens are downregulated in right versus left brain of controls, but not in SCZ or BD[+] patients. Ingenuity Pathway Analysis predicted that TGFB2 is an upstream regulator of these genes (p = .0012). While lateralized expression of TGFB2 in controls (p = .017) is associated with a corresponding change in DNAM (p ≤ .023), lateralized expression and DNAM of TGFB2 are absent in SCZ or BD. Loss of brain laterality in SCZ and BD corresponds to aberrant epigenetic regulation of TGFB2 and changes in TGFβ signaling, indicating potential avenues for disease prevention/treatment.

The Long Noncoding RNA Landscape in Amygdala Tissues from Schizophrenia Patients

To date, most transcriptome studies of schizophrenia focus on the analysis of protein-coding genes. Long noncoding RNAs (lncRNAs) are emerging as key tissue-specific regulators of cellular and disease processes. The amygdala brain region has been implicated in the pathophysiology of schizophrenia. We performed unbiased whole transcriptome profiling of amygdala tissues from 22 schizophrenia patients and 24 non-psychiatric controls using RNA-seq. We reconstructed amygdala transcriptome and employed systems biology approaches to annotating the functional roles of lncRNAs. As a result, we identified 839 novel lncRNAs in amygdala. We found in amygdala lncRNAs are more subtype-specific than protein-coding genes. We identified functional modules associated with "synaptic transmission", "ribosome", and "immune responses" which were related to schizophrenia pathophysiology that involved lncRNAs. Integrative functional analyses associating individual lncRNAs with specific pathways and functions further show that amygdala lncRNAs are connected with all of these pathways. Our study presents the first systematic landscape of lncRNAs in amygdala tissue from schizophrenia cases.

Inference of cell type content from human brain transcriptomic datasets illuminates the effects of age, manner of death, dissection, and psychiatric diagnosis

Psychiatric illness is unlikely to arise from pathology occurring uniformly across all cell types in affected brain regions. Despite this, transcriptomic analyses of the human brain have typically been conducted using macro-dissected tissue due to the difficulty of performing single-cell type analyses with donated post-mortem brains. To address this issue statistically, we compiled a database of several thousand transcripts that were specifically-enriched in one of 10 primary cortical cell types in previous publications. Using this database, we predicted the relative cell type content for 833 human cortical samples using microarray or RNA-Seq data from the Pritzker Consortium (GSE92538) or publicly-available databases (GSE53987, GSE21935, GSE21138, CommonMind Consortium). These predictions were generated by averaging normalized expression levels across transcripts specific to each cell type using our R-package BrainInABlender (validated and publicly-released on github). Using this method, we found that the principal components of variation in the datasets strongly correlated with the predicted neuronal/glial content of the samples. This variability was not simply due to dissection–the relative balance of brain cell types appeared to be influenced by a variety of demographic, pre- and post-mortem variables. Prolonged hypoxia around the time of death predicted increased astrocytic and endothelial gene expression, illustrating vascular upregulation. Aging was associated with decreased neuronal gene expression. Red blood cell gene expression was reduced in individuals who died following systemic blood loss. Subjects with Major Depressive Disorder had decreased astrocytic gene expression, mirroring previous morphometric observations. Subjects with Schizophrenia had reduced red blood cell gene expression, resembling the hypofrontality detected in fMRI experiments. Finally, in datasets containing samples with especially variable cell content, we found that controlling for predicted sample cell content while evaluating differential expression improved the detection of previously-identified psychiatric effects. We conclude that accounting for cell type can greatly improve the interpretability of transcriptomic data.

Weighted Gene Co-Expression Network Analysis Reveals Dysregulation of Mitochondrial Oxidative Phosphorylation in Eating Disorders

The underlying mechanisms of eating disorders (EDs) are very complicated and still poorly understood. The pathogenesis of EDs may involve the interplay of multiple genes. To investigate the dysregulated gene pathways in EDs we analyzed gene expression profiling in dorsolateral prefrontal cortex (DLPFC) tissues from 15 EDs cases, including 3 with anorexia nervosa (AN), 7 with bulimia nervosa (BN), 2 AN-BN cases, 3 cases of EDs not otherwise specified, and 102 controls. We further used a weighted gene co-expression network analysis to construct a gene co-expression network and to detect functional modules of highly correlated genes. The functional enrichment analysis of genes in co-expression modules indicated that an altered mitochondrial oxidative phosphorylation process may be involved in the pathogenesis of EDs.

RNA-seq analysis of amygdala tissue reveals characteristic expression profiles in schizophrenia

The amygdala brain region has been implicated in the pathophysiology of schizophrenia through emotion processing. However, transcriptome messages in the amygdala of schizophrenia patients have not been well studied. We used RNA sequencing to investigate gene-expression profiling in the amygdala tissues, and identified 569 upregulated and 192 downregulated genes from 22 schizophrenia patients and 24 non-psychiatric controls. Gene functional enrichment analysis demonstrated that the downregulated genes were enriched in pathways such as 'synaptic transmission' and 'behavior', whereas the upregulated genes were significantly over-represented in gene ontology pathways such as 'immune response' and 'blood vessel development'. Co-expression-based gene network analysis identified seven modules including four modules significantly associated with 'synaptic transmission', 'blood vessel development' or 'immune responses'. Taken together, our study provides novel insights into the molecular mechanism of schizophrenia, suggesting that precision-tailored therapeutic approaches aimed at normalizing the expression/function of specific gene networks could be a promising option in schizophrenia.

Consistently altered expression of gene sets in postmortem brains of individuals with major psychiatric disorders

The measurement of gene expression in postmortem brain is an important tool for understanding the pathogenesis of serious psychiatric disorders. We hypothesized that major molecular deficits associated with psychiatric disease would affect the entire brain, and such deficits may be shared across disorders. We performed RNA sequencing and quantified gene expression in the hippocampus of 100 brains in the Stanley Array Collection followed by replication in the orbitofrontal cortex of 57 brains in the Stanley Neuropathology Consortium. We then identified genes and canonical pathway gene sets with significantly altered expression in schizophrenia and bipolar disorder in the hippocampus and in schizophrenia, bipolar disorder and major depression in the orbitofrontal cortex. Although expression of individual genes varied, gene sets were significantly enriched in both of the brain regions, and many of these were consistent across diagnostic groups. Further examination of core gene sets with consistently increased or decreased expression in both of the brain regions and across target disorders revealed that ribosomal genes are overexpressed while genes involved in neuronal processes, GABAergic signaling, endocytosis and antigen processing have predominantly decreased expression in affected individuals compared to controls without a psychiatric disorder. Our results highlight pathways of central importance to psychiatric health and emphasize messenger RNA processing and protein synthesis as potential therapeutic targets for all three of the disorders.

Regulators of mitochondrial complex I activity: A review of literature and evaluation in postmortem prefrontal cortex from patients with bipolar disorder

Phenomenologically, bipolar disorder (BD) is characterized by biphasic increases and decreases in energy. As this is a state-related phenomenon, identifying regulators responsible for this phasic dysregulation has the potential to uncover key elements in the pathophysiology of BD. Given the evidence suggesting mitochondrial complex I dysfunction in BD, we aimed to identify the main regulators of complex I in BD by reviewing the literature and using the published microarray data to examine their gene expression profiles. We also validated protein expression levels of the main complex I regulators by immunohistochemistry. Upon reviewing the literature, we found PARK-7, STAT-3, SIRT-3 and IMP-2 play an important role in regulating complex I activity. Published microarray studies however revealed no significant direction of regulation of STAT-3, SIRT-3, and IMP-2, but a trend towards downregulation of PARK-7 was observed in BD. Immunocontent of DJ-1 (PARK-7-encoded protein) were not elevated in post mortem prefrontal cortex from patients with BD. We also found a trend towards upregulation of DJ-1 expression with age. Our results suggest that DJ-1 is not significantly altered in BD subjects, however further studies are needed to examine DJ-1 expression levels in a cohort of older patients with BD.

Meta-Analysis of Gene Expression in Autism Spectrum Disorder

Autism spectrum disorders (ASD) are clinically heterogeneous and biologically complex. In general it remains unclear, what biological factors lead to changes in the brains of autistic individuals. A considerable number of transcriptome analyses have been performed in attempts to address this question, but their findings lack a clear consensus. As a result, each of these individual studies has not led to any significant advance in understanding the autistic phenotype as a whole. Here, we report a meta-analysis of more than 1000 microarrays across twelve independent studies on expression changes in ASD compared to unaffected individuals, in both blood and brain tissues. We identified a number of known and novel genes that are consistently differentially expressed across three studies of the brain (71 samples in total). A subset of the highly ranked genes is suggestive of effects on mitochondrial function. In blood, consistent changes were more difficult to identify, despite individual studies tending to exhibit larger effects than the brain studies. Our results are the strongest evidence to date of a common transcriptome signature in the brains of individuals with ASD.

Mesial temporal lobe epilepsy with psychiatric comorbidities: a place for differential neuroinflammatory interplay

BACKGROUND

Despite the strong association between epilepsy and psychiatric comorbidities, few biological substrates are currently described. We have previously reported neuropathological alterations in mesial temporal lobe epilepsy (MTLE) patients with major depression and psychosis that suggest a morphological and neurochemical basis for psychopathological symptoms. Neuroinflammatory-related structures and molecules might be part of the altered neurochemical milieu underlying the association between epilepsy and psychiatric comorbidities, and such features have not been previously investigated in humans.

METHODS

MTLE hippocampi of subjects without psychiatric history (MTLEW), MTLE + major depression (MTLE + D), and MTLE + interictal psychosis (MTLE + P) derived from epilepsy surgery and control necropsies were investigated for reactive astrocytes (glial fibrillary acidic protein (GFAP)), activated microglia (human leukocyte antigen, MHC class II (HLA-DR)), glial metallothionein-I/II (MT-I/II), and aquaporin 4 (AQP4) immunohistochemistry.

RESULTS

We found an increased GFAP immunoreactive area in the molecular layers, granule cell layer, and cornus ammonis region 2 (CA2) and cornus ammonis region 1 (CA1) of MTLEW and MTLE + P, respectively, compared to MTLE + D. HLA-DR immunoreactive area was higher in cornus ammonis region 3 (CA3) of MTLE + P, compared to MTLE + D and MTLEW, and in the hilus, when compared to MTLEW. MTLEW cases showed increased MT-I/II area in the granule cell layer and CA1, compared to MTLE + P, and in the parasubiculum, when compared to MTLE + D and MTLE + P. Differences between MTLE and control, such as astrogliosis, microgliosis, increased MT-I/II, and decreased perivascular AQP4 in the epileptogenic hippocampus, were in agreement to what is currently described in the literature.

CONCLUSIONS

Neuroinflammatory-related molecules in MTLE hippocampus show a distinct pattern of expression when patients present with a comorbid psychiatric diagnosis, similar to what is found in the pure forms of schizophrenia and major depression. Future studies focusing on inflammatory characteristics of MTLE with psychiatric comorbidities might help in the design of better therapeutic strategies.

Innate immune response is differentially dysregulated between bipolar disease and schizophrenia

Schizophrenia (SZ) and bipolar disorder (BD) are severe psychiatric conditions with a neurodevelopmental component. Genetic findings indicate the existence of an overlap in genetic susceptibility across the disorders. Also, image studies provide evidence for a shared neurobiological basis, contributing to a dimensional diagnostic approach. This study aimed to identify the molecular mechanisms that differentiate SZ and BD patients from health controls but also that distinguish both from health individuals. Comparison of gene expression profiling in post-mortem brains of both disorders and health controls (30 cases), followed by a further comparison between 29 BD and 29 SZ revealed 28 differentially expressed genes. These genes were used in co-expression analysesthat revealed the pairs CCR1/SERPINA1, CCR5/HCST, C1QA/CD68, CCR5/S100A11 and SERPINA1/TLR1 as presenting the most significant difference in co-expression between SZ and BD. Next, a protein-protein interaction (PPI) network using the 28 differentially expressed genes as seeds revealed CASP4, TYROBP, CCR1, SERPINA1, CCR5 and C1QA as having a central role in the diseases manifestation. Both co-expression and network topological analyses pointed to genes related to microglia functions. Based on this data, we suggest that differences between SZ and BP are due to genes involved with response to stimulus, defense response, immune system process and response to stress biological processes, all having a role in the communication of environmental factors to the cells and associated to microglia.

Brain regions associated with risk and resistance for bipolar I disorder: a voxel-based MRI study of patients with bipolar disorder and their healthy siblings

OBJECTIVE

Bipolar I disorder is a highly heritable disorder but not all siblings manifest with the illness, even though they may share similar genetic and environmental risk factors. Thus, sibling studies may help to identify brain structural endophenotypes associated with risk and resistance for the disorder.

METHODS

Structural magnetic resonance imaging (MRI) scans were acquired for 28 euthymic patients with bipolar disorder, their healthy siblings, and 30 unrelated healthy controls. Statistical Parametric Mapping 8 (SPM8) was used to identify group differences in regional gray matter volume by voxel-based morphometry (VBM).

RESULTS

Using analysis of covariance, gray matter analysis of the groups revealed a group effect indicating that the left orbitofrontal cortex [Brodmann area (BA) 11] was smaller in patients with bipolar disorder than in unrelated healthy controls [F = 14.83, p < 0.05 (family-wise error); 7 mm(3) ]. Paired t-tests indicated that the orbitofrontal cortex of patients with bipolar disorder [t = 5.19, p < 0.05 (family-wise error); 37 mm(3) ] and their healthy siblings [t = 3.89, p < 0.001 (uncorrected); 63 mm(3) ] was smaller than in unrelated healthy controls, and that the left dorsolateral prefrontal cortex was larger in healthy siblings than in patients with bipolar disorder [t = 4.28, p < 0.001 (uncorrected); 323 mm(3) ] and unrelated healthy controls [t = 4.36, p < 0.001 (uncorrected); 245 mm(3) ]. Additional region-of-interest analyses also found volume deficits in the right cerebellum of patients with bipolar disorder [t = 3.92, p < 0.001 (uncorrected); 178 mm(3) ] and their healthy siblings [t = 4.23, p < 0.001 (uncorrected); 489 mm(3) ], and in the left precentral gyrus of patients with bipolar disorder [t = 3.61, p < 0.001 (uncorrected); 115 mm(3) ] compared to unrelated healthy controls.

CONCLUSIONS

The results of this study suggest that a reduction in the volume of the orbitofrontal cortex, which plays a role in the automatic regulation of emotions and is a part of the medial prefrontal network, is associated with the heritability of bipolar disorder. Conversely, increased dorsolateral prefrontal cortex volume may be a neural marker of a resistance factor as it is part of a network of voluntary emotion regulation and balances the effects of the disrupted automatic emotion regulation system.

Schizophrenia and bipolar disorder show both common and distinct changes in cortical interneuron markers

Schizophrenia and bipolar disorder are often viewed as distinct clinical disorders, however there is substantial overlap in their neuropathologies. While compromised cortical interneurons are implicated in both diseases, few studies have examined the relative contribution of the distinct interneuron populations to each psychotic disorder. We report reductions in somatostatin and vasoactive intestinal peptide mRNAs in prefrontal and orbitofrontal cortices in bipolar disorder (n=31) and schizophrenia (n=35) compared to controls (n=34) and increased calbindin mRNA in schizophrenia. We show, at the molecular level, shared deficits in interneuron markers in schizophrenia and bipolar disorder, and a unique interneuron marker increase in schizophrenia.

Genome-wide association study of bipolar disorder in Canadian and UK populations corroborates disease loci including SYNE1 and CSMD1

BACKGROUND

Recently, genome-wide association studies (GWAS) for cases versus controls using single nucleotide polymorphism microarray data have shown promising findings for complex neuropsychiatric disorders, including bipolar disorder (BD).

METHODS

Here we describe a comprehensive genome-wide study of bipolar disorder (BD), cross-referencing analysis from a family-based study of 229 small families with association analysis from over 950 cases and 950 ethnicity-matched controls from the UK and Canada. Further, loci identified in these analyses were supported by pathways identified through pathway analysis on the samples.

RESULTS

Although no genome-wide significant markers were identified, the combined GWAS findings have pointed to several genes of interest that support GWAS findings for BD from other groups or consortia, such as at SYNE1 on 6q25, PPP2R2C on 4p16.1, ZNF659 on 3p24.3, CNTNAP5 (2q14.3), and CDH13 (16q23.3). This apparent corroboration across multiple sites gives much confidence to the likelihood of genetic involvement in BD at these loci. In particular, our two-stage strategy found association in both our combined case/control analysis and the family-based analysis on 1q21.2 (closest gene: sphingosine-1-phosphate receptor 1 gene, S1PR1) and on 1q24.1 near the gene TMCO1, and at CSMD1 on 8p23.2, supporting several previous GWAS reports for BD and for schizophrenia. Pathway analysis suggests association of pathways involved in calcium signalling, neuropathic pain signalling, CREB signalling in neurons, glutamate receptor signalling and axonal guidance signalling.

CONCLUSIONS

The findings presented here show support for a number of genes previously implicated genes in the etiology of BD, including CSMD1 and SYNE1, as well as evidence for previously unreported genes such as the brain-expressed genes ADCY2, NCALD, WDR60, SCN7A and SPAG16.

Two gene co-expression modules differentiate psychotics and controls

Schizophrenia (SCZ) and bipolar disorder (BD) are highly heritable psychiatric disorders. Associated genetic and gene expression changes have been identified, but many have not been replicated and have unknown functions. We identified groups of genes whose expressions varied together, that is co-expression modules, then tested them for association with SCZ. Using weighted gene co-expression network analysis, we show that two modules were differentially expressed in patients versus controls. One, upregulated in cerebral cortex, was enriched with neuron differentiation and neuron development genes, as well as disease genome-wide association study genetic signals; the second, altered in cerebral cortex and cerebellum, was enriched with genes involved in neuron protection functions. The findings were preserved in five expression data sets, including sets from three brain regions, from a different microarray platform, and from BD patients. From those observations, we propose neuron differentiation and development pathways may be involved in etiologies of both SCZ and BD, and neuron protection function participates in pathological process of the diseases.

Systematic review of genome-wide gene expression studies of bipolar disorder

BACKGROUND

Numerous genome-wide gene expression studies of bipolar disorder (BP) have been carried out. These studies are heterogeneous, underpowered and use overlapping samples. We conducted a systematic review of these studies to synthesize the current findings.

METHODS

We identified all genome-wide gene expression studies on BP in humans. We then carried out a quantitative mega-analysis of studies done with post-mortem brain tissue. We obtained raw data from each study and used standardized procedures to process and analyze the data. We then combined the data and conducted three separate mega-analyses on samples from 1) any region of the brain (9 studies); 2) the prefrontal cortex (PFC) (6 studies); and 3) the hippocampus (2 studies). To minimize heterogeneity across studies, we focused primarily on the most numerous, recent and comprehensive studies.

RESULTS

A total of 30 genome-wide gene expression studies of BP done with blood or brain tissue were identified. We included 10 studies with data on 211 microarrays on 57 unique BP cases and 229 microarrays on 60 unique controls in the quantitative mega-analysis. A total of 382 genes were identified as significantly differentially expressed by the three analyses. Eleven genes survived correction for multiple testing with a q-value < 0.05 in the PFC. Among these were FKBP5 and WFS1, which have been previously implicated in mood disorders. Pathway analyses suggested a role for metallothionein proteins, MAP Kinase phosphotases, and neuropeptides.

CONCLUSION

We provided an up-to-date summary of results from gene expression studies of the brain in BP. Our analyses focused on the highest quality data available and provided results by brain region so that similarities and differences can be examined relative to disease status. The results are available for closer inspection on-line at Metamoodics [http://metamoodics.igm.jhmi.edu/], where investigators can look up any genes of interest and view the current results in their genomic context and in relation to leading findings from other genomic experiments in bipolar disorder.

Biomarker investigations related to pathophysiological pathways in schizophrenia and psychosis

Post-mortem brain investigations of schizophrenia have generated swathes of data in the last few decades implicating candidate genes and protein. However, the relation of these findings to peripheral biomarker indicators and symptomatology remain to be elucidated. While biomarkers for disease do not have to be involved with underlying pathophysiology and may be largely indicative of diagnosis or prognosis, the ideal may be a biomarker that is involved in underlying disease processes and which is therefore more likely to change with progression of the illness as well as potentially being more responsive to treatment. One of the main difficulties in conducting biomarker investigations for major psychiatric disorders is the relative inconsistency in clinical diagnoses between disorders such as bipolar and schizophrenia. This has led some researchers to investigate biomarkers associated with core symptoms of these disorders, such as psychosis. The aim of this review is to evaluate the contribution of post-mortem brain investigations to elucidating the pathophysiology pathways involved in schizophrenia and psychosis, with an emphasis on major neurotransmitter systems that have been implicated. This data will then be compared to functional neuroimaging findings as well as findings from blood based gene expression investigations in schizophrenia in order to highlight the relative overlap in pathological processes between these different modalities used to elucidate pathogenesis of schizophrenia. In addition we will cover some recent and exciting findings demonstrating microRNA (miRNA) dysregulation in both the blood and the brain in patients with schizophrenia. These changes are pertinent to the topic due to their known role in post-transcriptional modification of gene expression with the potential to contribute or underlie gene expression changes observed in schizophrenia. Finally, we will discuss how post-mortem studies may aid future biomarker investigations.

A comparative genomic study in schizophrenic and in bipolar disorder patients, based on microarray expression profiling meta-analysis

Schizophrenia affecting almost 1% and bipolar disorder affecting almost 3%–5% of the global population constitute two severe mental disorders. The catecholaminergic and the serotonergic pathways have been proved to play an important role in the development of schizophrenia, bipolar disorder, and other related psychiatric disorders. The aim of the study was to perform and interpret the results of a comparative genomic profiling study in schizophrenic patients as well as in healthy controls and in patients with bipolar disorder and try to relate and integrate our results with an aberrant amino acid transport through cell membranes. In particular we have focused on genes and mechanisms involved in amino acid transport through cell membranes from whole genome expression profiling data. We performed bioinformatic analysis on raw data derived from four different published studies. In two studies postmortem samples from prefrontal cortices, derived from patients with bipolar disorder, schizophrenia, and control subjects, have been used. In another study we used samples from postmortem orbitofrontal cortex of bipolar subjects while the final study was performed based on raw data from a gene expression profiling dataset in the postmortem superior temporal cortex of schizophrenics. The data were downloaded from NCBI's GEO datasets.

Genome-wide expression profiling of schizophrenia using a large combined cohort

Numerous studies have examined gene expression profiles in post-mortem human brain samples from individuals with schizophrenia compared with healthy controls, to gain insight into the molecular mechanisms of the disease. Although some findings have been replicated across studies, there is a general lack of consensus on which genes or pathways are affected. It has been unclear if these differences are due to the underlying cohorts or methodological considerations. Here, we present the most comprehensive analysis to date of expression patterns in the prefrontal cortex of schizophrenic, compared with unaffected controls. Using data from seven independent studies, we assembled a data set of 153 affected and 153 control individuals. Remarkably, we identified expression differences in the brains of schizophrenics that are validated by up to seven laboratories using independent cohorts. Our combined analysis revealed a signature of 39 probes that are upregulated in schizophrenia and 86 that are downregulated. Some of these genes were previously identified in studies that were not included in our analysis, while others are novel to our analysis. In particular, we observe gene expression changes associated with various aspects of neuronal communication and alterations of processes affected as a consequence of changes in synaptic functioning. A gene network analysis predicted previously unidentified functional relationships among the signature genes. Our results provide evidence for a common underlying expression signature in this heterogeneous disorder.

A combined analysis of microarray gene expression studies of the human prefrontal cortex identifies genes implicated in schizophrenia

Small cohort sizes and modest levels of gene expression changes in brain tissue have plagued the statistical approaches employed in microarray studies investigating the mechanism of schizophrenia. To combat these problems a combined analysis of six prior microarray studies was performed to facilitate the robust statistical analysis of gene expression data from the dorsolateral prefrontal cortex of 107 patients with schizophrenia and 118 healthy subjects. Multivariate permutation tests identified 144 genes that were differentially expressed between schizophrenia and control groups. Seventy of these genes were identified as differentially expressed in at least one component microarray study but none of these individual studies had the power to identify the remaining 74 genes, demonstrating the utility of a combined approach. Gene ontology terms and biological pathways that were significantly enriched for differentially expressed genes were related to neuronal cell-cell signaling, mesenchymal induction, and mitogen-activated protein kinase signaling, which have all previously been associated with the etiopathogenesis of schizophrenia. The differential expression of BAG3, C4B, EGR1, MT1X, NEUROD6, SST and S100A8 was confirmed by real-time quantitative PCR in an independent cohort using postmortem human prefrontal cortex samples. Comparison of gene expression between schizophrenic subjects with and without detectable levels of antipsychotics in their blood suggests that the modulation of MT1X and S100A8 may be the result of drug exposure. In conclusion, this combined analysis has resulted in a statistically robust identification of genes whose dysregulation may contribute to the mechanism 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.

Expression pattern of the cannabinoid receptor genes in the frontal cortex of mood disorder patients and mice selectively bred for high and low fear

Although the endocannabinoid system (ECS) has been implicated in brain development and various psychiatric disorders, precise mechanisms of the ECS on mood and anxiety disorders remain unclear. Here, we have investigated developmental and disease-related expression pattern of the cannabinoid receptor 1 (CB1) and the cannabinoid receptor 2 (CB2) genes in the dorsolateral prefrontal cortex (PFC) of humans. Using mice selectively bred for high and low fear, we further investigated potential association between fear memory and the cannabinoid receptor expression in the brain. The CB1, not the CB2, mRNA levels in the PFC gradually decrease during postnatal development ranging in age from birth to 50 years (r2 > 0.6 & adj. p < 0.05). The CB1 levels in the PFC of major depression patients were higher when compared to the age-matched controls (adj. p < 0.05). In mice, the CB1, not the CB2, levels in the PFC were positively correlated with freezing behavior in classical fear conditioning (p < 0.05). These results suggest that the CB1 in the PFC may play a significant role in regulating mood and anxiety symptoms. Our study demonstrates the advantage of utilizing data from postmortem brain tissue and a mouse model of fear to enhance our understanding of the role of the cannabinoid receptors in mood and anxiety disorders.

Construction and analysis of the protein-protein interaction networks for schizophrenia, bipolar disorder, and major depression

BACKGROUND

Schizophrenia, bipolar disorder, and major depression are devastating mental diseases, each with distinctive yet overlapping epidemiologic characteristics. Microarray and proteomics data have revealed genes which expressed abnormally in patients. Several single nucleotide polymorphisms (SNPs) and mutations are associated with one or more of the three diseases. Nevertheless, there are few studies on the interactions among the disease-associated genes and proteins.

RESULTS

This study, for the first time, incorporated microarray and protein-protein interaction (PPI) databases to construct the PPI network of abnormally expressed genes in postmortem brain samples of schizophrenia, bipolar disorder, and major depression patients. The samples were collected from Brodmann area (BA) 10 of the prefrontal cortex. Abnormally expressed disease genes were selected by t-tests comparing the disease and control samples. These genes were involved in housekeeping functions (e.g. translation, transcription, energy conversion, and metabolism), in brain specific functions (e.g. signal transduction, neuron cell differentiation, and cytoskeleton), or in stress responses (e.g. heat shocks and biotic stress).The diseases were interconnected through several "switchboard"-like nodes in the PPI network or shared abnormally expressed genes. A "core" functional module which consisted of a tightly knitted sub-network of clique-5 and -4s was also observed. These cliques were formed by 12 genes highly expressed in both disease and control samples.

CONCLUSIONS

Several previously unidentified disease marker genes and drug targets, such as SBNO2 (schizophrenia), SEC24C (bipolar disorder), and SRRT (major depression), were identified based on statistical and topological analyses of the PPI network. The shared or interconnecting marker genes may explain the shared symptoms of the studied diseases. Furthermore, the "switchboard" genes, such as APP, UBC, and YWHAZ, are proposed as potential targets for developing new treatments due to their functional and topological significance.

The transcription factor SP4 is reduced in postmortem cerebellum of bipolar disorder subjects: control by depolarization and lithium

OBJECTIVES

  Regulation of gene expression is important for the development and function of the nervous system. However, the transcriptional programs altered in psychiatric diseases are not completely characterized. Human gene association studies and analysis of mutant mice suggest that the transcription factor specificity protein 4 (SP4) may be implicated in the pathophysiology of psychiatric diseases. We hypothesized that SP4 levels may be altered in the brain of bipolar disorder (BD) subjects and regulated by neuronal activity and drug treatment.

METHODS

  We analyzed messenger RNA (mRNA) and protein levels of SP4 and SP1 in the postmortem prefrontal cortex and cerebellum of BD subjects (n = 10) and controls (n = 10). We also examined regulation of SP4 mRNA and protein levels by neuronal activity and lithium in rat cerebellar granule neurons.

RESULTS

  We report a reduction of SP4 and SP1 proteins, but not mRNA levels, in the cerebellum of BD subjects. SP4 protein and mRNA levels were also reduced in the prefrontal cortex. Moreover, we found in rat cerebellar granule neurons that under non-depolarizing conditions SP4, but not SP1, was polyubiquitinated and degraded by the proteasome while lithium stabilized SP4 protein.

CONCLUSIONS

  Our study provides the first evidence of altered SP4 protein in the cerebellum and prefrontal cortex in BD subjects supporting a possible role of transcription factor SP4 in the pathogenesis of the disease. In addition, our finding that SP4 stability is regulated by depolarization and lithium provides a pathway through which neuronal activity and lithium could control gene expression suggesting that normalization of SP4 levels could contribute to treatment of affective disorders.

Analysis of kinase gene expression in the frontal cortex of suicide victims: implications of fear and stress

Suicide is a serious public health issue that results from an interaction between multiple risk factors including individual vulnerabilities to complex feelings of hopelessness, fear, and stress. Although kinase genes have been implicated in fear and stress, including the consolidation and extinction of fearful memories, expression profiles of those genes in the brain of suicide victims are less clear. Using gene expression microarray data from the Online Stanley Genomics Database and a quantitative PCR, we investigated the expression profiles of multiple kinase genes including the calcium calmodulin-dependent kinase (CAMK), the cyclin-dependent kinase, the mitogen-activated protein kinase (MAPK), and the protein kinase C (PKC) in the prefrontal cortex (PFC) of mood disorder patients died with suicide (N = 45) and without suicide (N = 38). We also investigated the expression pattern of the same genes in the PFC of developing humans ranging in age from birth to 49 year (N = 46). The expression levels of CAMK2B, CDK5, MAPK9, and PRKCI were increased in the PFC of suicide victims as compared to non-suicide controls (false discovery rate, FDR-adjusted p < 0.05, fold change >1.1). Those genes also showed changes in expression pattern during the postnatal development (FDR-adjusted p < 0.05). These results suggest that multiple kinase genes undergo age-dependent changes in normal brains as well as pathological changes in suicide brains. These findings may provide an important link to protein kinases known to be important for the development of fear memory, stress associated neural plasticity, and up-regulation in the PFC of suicide victims. More research is needed to better understand the functional role of these kinase genes that may be associated with the pathophysiology of suicide.

BioGraph: unsupervised biomedical knowledge discovery via automated hypothesis generation

We present BioGraph, a data integration and data mining platform for the exploration and discovery of biomedical information. The platform offers prioritizations of putative disease genes, supported by functional hypotheses. We show that BioGraph can retrospectively confirm recently discovered disease genes and identify potential susceptibility genes, outperforming existing technologies, without requiring prior domain knowledge. Additionally, BioGraph allows for generic biomedical applications beyond gene discovery. BioGraph is accessible at http://www.biograph.be.

BioGraph: unsupervised biomedical knowledge discovery via automated hypothesis generation

High-throughput technologies for DNA sequencing and for analyses of transcriptomes, proteomes and metabolomes have provided the foundations for deciphering the structure, variation and function of the human genome and relating them to health and disease states. The increased efficiency of DNA sequencing opens up the possibility of analyzing a large number of individual genomes and transcriptomes, and complete reference proteomes and metabolomes are within reach using powerful analytical techniques based on chromatography, mass spectrometry and nuclear magnetic resonance. Computational and mathematical tools have enabled the development of systems approaches for deciphering the functional and regulatory networks underlying the behavior of complex biological systems. Further conceptual and methodological developments of these tools are needed for the integration of various data types across the multiple levels of organization and time frames that are characteristic of human development, physiology and disease. Medical genomics has attempted to overcome the initial limitations of genome-wide association studies and has identified a limited number of susceptibility loci for many complex and common diseases. Iterative systems approaches are starting to provide deeper insights into the mechanisms of human diseases, and to facilitate the development of better diagnostic and prognostic biomarkers for cancer and many other diseases. Systems approaches will transform the way drugs are developed through academy-industry partnerships that will target multiple components of networks and pathways perturbed in diseases. They will enable medicine to become predictive, personalized, preventive and participatory, and, in the process, concepts and methods from Western and oriental cultures can be combined. We recommend that systems medicine should be developed through an international network of systems biology and medicine centers dedicated to inter-disciplinary training and education, to help reduce the gap in healthcare between developed and developing countries.

Meta-analysis of heterogeneous Down Syndrome data reveals consistent genome-wide dosage effects related to neurological processes

Background

Down syndrome (DS; trisomy 21) is the most common genetic cause of mental retardation in the human population and key molecular networks dysregulated in DS are still unknown. Many different experimental techniques have been applied to analyse the effects of dosage imbalance at the molecular and phenotypical level, however, currently no integrative approach exists that attempts to extract the common information.

Results

We have performed a statistical meta-analysis from 45 heterogeneous publicly available DS data sets in order to identify consistent dosage effects from these studies. We identified 324 genes with significant genome-wide dosage effects, including well investigated genes like SOD1, APP, RUNX1 and DYRK1A as well as a large proportion of novel genes (N = 62). Furthermore, we characterized these genes using gene ontology, molecular interactions and promoter sequence analysis. In order to judge relevance of the 324 genes for more general cerebral pathologies we used independent publicly available microarry data from brain studies not related with DS and identified a subset of 79 genes with potential impact for neurocognitive processes. All results have been made available through a web server under http://ds-geneminer.molgen.mpg.de/.

Conclusions

Our study represents a comprehensive integrative analysis of heterogeneous data including genome-wide transcript levels in the domain of trisomy 21. The detected dosage effects build a resource for further studies of DS pathology and the development of new therapies.

P11 (S100A10) as a potential biomarker of psychiatric patients at risk of suicide

Although suicide represents 1.8% of the global burden of disease, there are few objective assays for suicide risk. Being associated with depressive disorders, which have a high risk of suicide, the proteins P11, P2RX7, and S100β may be biomarkers for a suicidal disposition. We measured levels of p11 and P2RX7 mRNA in peripheral blood mononuclear cells (PBMCs) of 26 psychiatric patients (11 suicide attempters, 15 suicide non-attempters) with post-traumatic stress disorder (PTSD) and major depressive disorder (MDD), and 14 normal controls, using quantitative real-time PCR. We also conducted a meta-analysis of microarray data of p11, P2RX7 and S100β from post-mortem prefrontal cortex (PFC) of patients who committed suicide (n = 56) and non-suicide controls (n = 61). We found that PBMC p11 mRNA levels were significantly lower in suicide attempters and higher in suicide non-attempters, when compared to normal controls. The PFC p11 mRNA levels in suicide completers were also lower than non-suicide controls (adjusted p = 0.007). Unlike p11, PBMC P2RX7 mRNA levels were significantly lower than normal controls in all patients including suicide attempters, suicide non-attempters, and suicide completers. In addition, levels of S100β in PFC did not differ between suicide completers and non-suicide controls. These results suggest that PBMC p11 mRNA levels may be a potential adjunctive biomarker for the assessment of suicide risk in mental disorders and warrants a larger translational study to determine its clinical utility.

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.

Gene expression and genetic variation data implicate PCLO in bipolar disorder

BACKGROUND

Genetic variation may contribute to differential gene expression in the brain of individuals with psychiatric disorders. To test this hypothesis, we identified genes that were differentially expressed in individuals with bipolar disorder, along with nearby single nucleotide polymorphisms (SNPs) that were associated with expression of the same genes. We then tested these SNPs for association with bipolar disorder in large case-control samples.

METHODS

We used the Stanley Genomics Database to extract gene expression and SNP microarray data from individuals with bipolar disorder (n = 40) and unaffected controls (n = 43). We identified 367 genes that were differentially expressed in the prefrontal cortex of cases vs. controls (fold change > 1.3 and FDR q-value < .05) and 45 nearby SNPs that were associated with expression of those same genes (FDR q-value < .05). We tested these SNPs for association with bipolar disorder in a meta-analysis of genome-wide association studies (GWAS) including 4,936 cases and 6,654 healthy controls.

RESULTS

We identified 45 SNPs that were associated with expression of differentially expressed genes, including HBS1L (15 SNPs), HLA-DPB1 (15 SNPs), AMFR (8 SNPs), PCLO (2 SNPs) and WDR41 (2 SNPs). Of these, one SNP (rs13438494), in an intron of the piccolo (PCLO) gene, was significantly associated with bipolar disorder (FDR adjusted p < .05) in the meta-analysis of GWAS.

CONCLUSIONS

These results support the previous findings implicating PCLO in mood disorders and demonstrate the utility of combining gene expression and genetic variation data to improve our understanding of the genetic contribution to bipolar disorder.

Acoustic startle response and sensorimotor gating in a genetic mouse model for the Y1 receptor

Recent research has highlighted a potential role for neuropeptide Y (NPY) and its Y(1) receptor in the development of schizophrenia. Genetic as well as molecular biological studies have demonstrated reduced levels of NPY in schizophrenia patients. Importantly, Y(1) receptors may mediate some of the potential effects of NPY on schizophrenia, as decreased Y(1) receptor expression has been found in the lymphocytes of schizophrenia patients. To clarify NPY's role in schizophrenia, we investigated a genetic animal model for Y(1) deficiency in regard to (i) acoustic startle response (ASR), (ii) habituation to ASR and (iii) sensorimotor gating [i.e. prepulse inhibition (PPI)] using two different PPI protocols. Mutant and wild type-like mice were screened for baseline behaviours and after pharmacological challenge with the psychotropic drugs dexamphetamine (DEX) and MK-801. Y(1) knockout mice (Y(1)(-/-)) showed a moderate reduction of the ASR and an impaired ASR habituation at baseline and after DEX treatment. The baseline PPI performance of Y(1) mutant mice was unaltered their response to DEX and MK-801 challenge was moderately different compared to control mice, which was dependent on the PPI protocol used. MK-801 challenge had a protocol-dependent differential effect in Y(1)(-/-) mice and DEX a more pronounced impact at the highest prepulse intensities. In conclusion, it appears that the Y(1) receptor influences the acoustic startle response and its habituation but does not play a major role in sensorimotor gating. Further explorations into the effects of Y(1) deficiency seem valid.

Uncovering molecular biomarkers that correlate cognitive decline with the changes of hippocampus' gene expression profiles in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is characterized by a neurodegenerative progression that alters cognition. On a phenotypical level, cognition is evaluated by means of the MiniMental State Examination (MMSE) and the post-mortem examination of Neurofibrillary Tangle count (NFT) helps to confirm an AD diagnostic. The MMSE evaluates different aspects of cognition including orientation, short-term memory (retention and recall), attention and language. As there is a normal cognitive decline with aging, and death is the final state on which NFT can be counted, the identification of brain gene expression biomarkers from these phenotypical measures has been elusive.

METHODOLOGY/PRINCIPAL FINDINGS

We have reanalysed a microarray dataset contributed in 2004 by Blalock et al. of 31 samples corresponding to hippocampus gene expression from 22 AD subjects of varying degree of severity and 9 controls. Instead of only relying on correlations of gene expression with the associated MMSE and NFT measures, and by using modern bioinformatics methods based on information theory and combinatorial optimization, we uncovered a 1,372-probe gene expression signature that presents a high-consensus with established markers of progression in AD. The signature reveals alterations in calcium, insulin, phosphatidylinositol and wnt-signalling. Among the most correlated gene probes with AD severity we found those linked to synaptic function, neurofilament bundle assembly and neuronal plasticity.

CONCLUSIONS/SIGNIFICANCE

A transcription factors analysis of 1,372-probe signature reveals significant associations with the EGR/KROX family of proteins, MAZ, and E2F1. The gene homologous of EGR1, zif268, Egr-1 or Zenk, together with other members of the EGR family, are consolidating a key role in the neuronal plasticity in the brain. These results indicate a degree of commonality between putative genes involved in AD and prion-induced neurodegenerative processes that warrants further investigation.

A cross-laboratory comparison of expression profiling data from normal human postmortem brain

Expression profiling of post-mortem human brain tissue has been widely used to study molecular changes associated with neuropsychiatric diseases as well as normal processes such as aging. Changes in expression associated with factors such as age, gender or postmortem interval are often more pronounced than changes associated with disease. Therefore in addition to being of interest in their own right, careful consideration of these effects are important in the interpretation of disease studies. We performed a large meta-analysis of genome-wide expression studies of normal human cortex to more fully catalogue the effects of age, gender, postmortem interval and brain pH, yielding a "meta-signature" of gene expression changes for each factor. We validated our results by showing a significant overlap with independent gene lists extracted from the literature. Importantly, meta-analysis identifies genes which are not significant in any individual study. Finally, we show that many schizophrenia candidate genes appear in the meta-signatures, reinforcing the idea that studies must be carefully controlled for interactions between these factors and disease. In addition to the inherent value of the meta-signatures, our results provide critical information for future studies of disease effects in the human brain.

Effects of typical and atypical antipsychotic drugs on gene expression profiles in the liver of schizophrenia subjects

BACKGROUND

Although much progress has been made on antipsychotic drug development, precise mechanisms behind the action of typical and atypical antipsychotics are poorly understood.

METHODS

We performed genome-wide expression profiling to study effects of typical antipsychotics and atypical antipsychotics in the postmortem liver of schizophrenia patients using microarrays (Affymetrix U133 plus2.0). We classified the subjects into typical antipsychotics (n = 24) or atypical antipsychotics (n = 26) based on their medication history, and compared gene expression profiles with unaffected controls (n = 34). We further analyzed individual antipsychotic effects on gene expression by sub-classifying the subjects into four major antipsychotic groups including haloperidol, phenothiazines, olanzapine and risperidone.

RESULTS

Typical antipsychotics affected genes associated with nuclear protein, stress responses and phosphorylation, whereas atypical antipsychotics affected genes associated with golgi/endoplasmic reticulum and cytoplasm transport. Comparison between typical antipsychotics and atypical antipsychotics further identified genes associated with lipid metabolism and mitochondrial function. Analyses on individual antipsychotics revealed a set of genes (151 transcripts, FDR adjusted p < 0.05) that are differentially regulated by four antipsychotics, particularly by phenothiazines, in the liver of schizophrenia patients.

CONCLUSION

Typical antipsychotics and atypical antipsychotics affect different genes and biological function in the liver. Typical antipsychotic phenothiazines exert robust effects on gene expression in the liver that may lead to liver toxicity. The genes found in the current study may benefit antipsychotic drug development with better therapeutic and side effect profiles.