Pathway Analyses Implicate Glial Cells in Schizophrenia

Background: The quest to understand the neurobiology of schizophrenia and bipolar disorder is ongoing with multiple lines of evidence indicating abnormalities of glia, mitochondria, and glutamate in both disorders. Despite high heritability estimates of 81% for schizophrenia and 75% for bipolar disorder, compelling links between findings from neurobiological studies, and findings from large-scale genetic analyses, are only beginning to emerge. Method Ten publically available gene sets (pathways) related to glia, mitochondria, and glutamate were tested for association to schizophrenia and bipolar disorder using MAGENTA as the primary analysis method. To determine the robustness of associations, secondary analyses were performed with: ALIGATOR, INRICH, and Set Screen. Data from the Psychiatric Genomics Consortium (PGC) were used for all analyses. There were 1,068,286 SNP-level p-values for schizophrenia (9,394 cases/12,462 controls), and 2,088,878 SNP-level p-values for bipolar disorder (7,481 cases/9,250 controls). Results: The Glia-Oligodendrocyte pathway was associated with schizophrenia, after correction for multiple tests, according to primary analysis (MAGENTA p = 0.0005, 75% requirement for individual gene significance) and also achieved nominal levels of significance with INRICH (p = 0.0057) and ALIGATOR (p = 0.022). For bipolar disorder, Set Screen yielded nominally and method-wide significant associations to all three glial pathways, with strongest association to the Glia-Astrocyte pathway (p = 0.002). Conclusions: Consistent with findings of white matter abnormalities in schizophrenia by other methods of study, the Glia-Oligodendrocyte pathway was associated with schizophrenia in our genomic study. These findings suggest that the abnormalities of myelination observed in schizophrenia are at least in part due to inherited factors, contrasted with the alternative of purely environmental causes (e.g. medication effects or lifestyle). While not the primary purpose of our study, our results also highlight the consequential nature of alternative choices regarding pathway analysis, in that results varied somewhat across methods, despite application to identical datasets and pathways

Dysregulation of specialized delay/interference-dependent working memory following loss of dysbindin-1A in schizophrenia-related phenotypes

Dysbindin-1, a protein that regulates aspects of early and late brain development, has been implicated in the pathobiology of schizophrenia. As the functional roles of the three major isoforms of dysbindin-1, (A, B, and C) remain unknown, we generated a novel mutant mouse, dys-1A -/-, with selective loss of dysbindin-1A and investigated schizophrenia-related phenotypes in both males and females. Loss of dysbindin-1A resulted in heightened initial exploration and disruption in subsequent habituation to a novel environment, together with heightened anxiety-related behavior in a stressful environment. Loss of dysbindin-1A was not associated with disruption of either long-term (olfactory) memory or spontaneous alternation behavior. However, dys-1A -/-showed enhancement in delay-dependent working memory under high levels of interference relative to controls, ie, impairment in sensitivity to the disruptive effect of such interference. These findings in dys-1A -/-provide the first evidence for differential functional roles for dysbindin-1A vs dysbindin-1C isoforms among phenotypes relevant to the pathobiology of schizophrenia. Future studies should investigate putative sex differences in these phenotypic effects

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Molecular genetic models related to schizophrenia and psychotic illness: heuristics and challenges

Schizophrenia is a heritable disorder that may involve several common genes of small effect and/or rare copy number variation, with phenotypic heterogeneity across patients. Furthermore, any boundaries vis-à-vis other psychotic disorders are far from clear. Consequently, identification of informative animal models for this disorder, which typically relate to pharmacological and putative pathophysiological processes of uncertain validity, faces considerable challenges. In juxtaposition, the majority of mutant models for schizophrenia relate to the functional roles of a diverse set of genes associated with risk for the disorder or with such putative pathophysiological processes. This chapter seeks to outline the evidence from phenotypic studies in mutant models related to schizophrenia. These have commonly assessed the degree to which mutation of a schizophrenia-related gene is associated with the expression of several aspects of the schizophrenia phenotype or more circumscribed, schizophrenia-related endophenotypes; typically, they place specific emphasis on positive and negative symptoms and cognitive deficits, and extend to structural and other pathological features. We first consider the primary technological approaches to the generation of such mutants, to include their relative merits and demerits, and then highlight the diverse phenotypic approaches that have been developed for their assessment. The chapter then considers the application of mutant phenotypes to study pathobiological and pharmacological mechanisms thought to be relevant for schizophrenia, particularly in terms of dopaminergic and glutamatergic dysfunction, and to an increasing range of candidate susceptibility genes and copy number variants. Finally, we discuss several pertinent issues and challenges within the field which relate to both phenotypic evaluation and a growing appreciation of the functional genomics of schizophrenia and the involvement of gene × environment interactions

Manhattan plots illustrating data use decisions in pathway analyses.

<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0089441#pone-0089441-g001" target="_blank">Figure 1</a> utilizes a Manhattan plot of 22 chromosomes (A) and a detailed Manhattan plot for a region of chromosome 7 (B) to illustrate differences in pathway analytic methods. One major distinction among pathway analysis methods designed for GWAS data concerns the use of raw data (i.e. individual level genotypes) versus summary statistics (i.e. p-value, odds ratios, betas, etc. per SNP). For example, the paper recently published by Goudriaan et al (2013) used raw genotype data. In contrast, the four methods used in this report all use SNP-level summary statistics as input data. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0089441#pone-0089441-g001" target="_blank">Figure 1A</a> is a 'Manhattan plot, in which each point represents one SNP. The x-axis denotes chromosomal position and the y-axis denotes significance of each SNP's association to the phenotype (units of -log₁₀p-value). The horizontal red line denotes genome-wide significance (p<5×10⁻⁸). In <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0089441#pone-0089441-g001" target="_blank">Figure 1B</a>, a section of the Manhattan plot on chromosome 7 is expanded, and the location of genes is given in the lower portion of section 1B. As seen in 1B, individual genes may contain many SNPs (colored diamonds in figure). Three of the pathway analytic methods used in this report use a ‘best SNP per gene/region’ approach, meaning that they ‘count’ only the most significant SNP in a gene or region of interest (methods MAGENTA, ALIGATOR, and INRICH). In contrast, Set Screen utilizes information from all SNPs within a gene or region of interest in the calculation of pathway-level statistics. Another aspect of the design of pathway analyses is illustrated in 1B: correlation among SNPs. Due to the haplotype structure of chromosomes, many genetic variants are correlated with one another, and are said to be in ‘linkage disequilibrium’ or ‘LD’. Thus, each method used in this report has analytic procedures for handling LD, so that correlated signals are not inappropriately counted multiple times. As stated in the text, correlation among SNPs is so extensive in the HLA region of chromosome 6, that pathway analytic methods currently exclude this region from analysis. In the past, failure to exclude the HLA from pathway analyses led to the reporting of spurious associations. Finally, we note that assigning of SNPs to genes is an imprecise task. Two complications are overlapping genes and correlated variants that may span many genes. A more daunting challenge is capturing the regulatory elements that impact genes. Such elements may be located far from genes, sometimes even on different chromosomes. Future developments in pathway analytic methods will likely make use of information about tissue and gene-specific regulatory elements (e.g. derived from the ENCODE project), but such information is not currently implemented in these pathway analytic methods.</p

Ethologically based behavioural and neurochemical characterisation of mice with isoform-specific loss of dysbindin-1A in the context of schizophrenia

Dysbindin-1 is implicated in several aspects of schizophrenia, including cognition and both glutamatergic and dopaminergic neurotransmission. Targeted knockout of dysbindin-1A (Dys-1A KO), the most abundant and widely expressed isoform in the brain, is associated with deficits in delay/interference-dependent working memory. Using an ethologically based approach, the following behavioural phenotypes were examined in Dys-1A KO mice: exploratory activity, social interaction, anxiety and problem-solving ability. Levels of monoamines and their metabolites were measured in striatum, hippocampus and prefrontal cortex using high-performance liquid chromatography with electrochemical detection. The ethogram of initial exploration in Dys-1A KO mice was characterised by increased rearing from a seated position; over subsequent habituation, stillness was decreased relative to wildtype. In a test of dyadic social interaction with an unfamiliar conspecific in a novel environment, female KO mice showed an increase in investigative social behaviours. Marble burying behaviour was unchanged. Using the puzzle-box test to measure general problem-solving performance, no effect of genotype was observed across nine trials of increasing complexity. Dys-1A KO demonstrated lower levels of 5-HT in ratio to its metabolite 5-HIAA in the prefrontal cortex. These studies elaborate the behavioural and neurochemical phenotype of Dys-1A KO mice, revealing subtle genotype-related differences in non-social and social exploratory behaviours and habituation of exploration in a novel environment, as well as changes in 5-HT activity in brain areas related to schizophrenia

Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

Schizophrenia is a severe mental disorder with a lifetime risk of about 1%, characterized by hallucinations, delusions and cognitive deficits, with heritability estimated at up to 80%1, 2. We performed a genome-wide association study of 3,322 European individuals with schizophrenia and 3,587 controls. Here we show, using two analytic approaches, the extent to which common genetic variation underlies the risk of schizophrenia. First, we implicate the major histocompatibility complex. Second, we provide molecular genetic evidence for a substantial polygenic component to the risk of schizophrenia involving thousands of common alleles of very small effect. We show that this component also contributes to the risk of bipolar disorder, but not to several non-psychiatric diseases