Dataset Information

Impaired glutathione synthesis in schizophrenia: convergent genetic and functional evidence.

ABSTRACT: Schizophrenia is a complex multifactorial brain disorder with a genetic component. Convergent evidence has implicated oxidative stress and glutathione (GSH) deficits in the pathogenesis of this disease. The aim of the present study was to test whether schizophrenia is associated with a deficit of GSH synthesis. Cultured skin fibroblasts from schizophrenia patients and control subjects were challenged with oxidative stress, and parameters of the rate-limiting enzyme for the GSH synthesis, the glutamate cysteine ligase (GCL), were measured. Stressed cells of patients had a 26% (P = 0.002) decreased GCL activity as compared with controls. This reduction correlated with a 29% (P < 0.001) decreased protein expression of the catalytic GCL subunit (GCLC). Genetic analysis of a trinucleotide repeat (TNR) polymorphism in the GCLC gene showed a significant association with schizophrenia in two independent case-control studies. The most common TNR genotype 7/7 was more frequent in controls [odds ratio (OR) = 0.6, P = 0.003], whereas the rarest TNR genotype 8/8 was three times more frequent in patients (OR = 3.0, P = 0.007). Moreover, subjects with disease-associated genotypes had lower GCLC protein expression (P = 0.017), GCL activity (P = 0.037), and GSH contents (P = 0.004) than subjects with genotypes that were more frequent in controls. Taken together, the study provides genetic and functional evidence that an impaired capacity to synthesize GSH under conditions of oxidative stress is a vulnerability factor for schizophrenia.

SUBMITTER: Gysin R

PROVIDER: S-EPMC2034265 | biostudies-literature | 2007 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Impaired glutathione synthesis in schizophrenia: convergent genetic and functional evidence.

Gysin René R Kraftsik Rudolf R Sandell Julie J Bovet Pierre P Chappuis Céline C Conus Philippe P Deppen Patricia P Preisig Martin M Ruiz Viviane V Steullet Pascal P Tosic Mirjana M Werge Thomas T Cuénod Michel M Do Kim Q KQ

Proceedings of the National Academy of Sciences of the United States of America 20071005 42

Schizophrenia is a complex multifactorial brain disorder with a genetic component. Convergent evidence has implicated oxidative stress and glutathione (GSH) deficits in the pathogenesis of this disease. The aim of the present study was to test whether schizophrenia is associated with a deficit of GSH synthesis. Cultured skin fibroblasts from schizophrenia patients and control subjects were challenged with oxidative stress, and parameters of the rate-limiting enzyme for the GSH synthesis, the glu ...[more]

PMID: 17921251

Similar Datasets

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

Project description:The dysconnection hypothesis of schizophrenia (SZ) proposes that psychosis is best understood in terms of aberrant connectivity. Specifically, it suggests that dysconnectivity arises through aberrant synaptic modulation associated with deficits in GABAergic inhibition, excitation-inhibition balance and disturbances of high-frequency oscillations. Using a computational model combined with a graded-difficulty visual orientation discrimination paradigm, we demonstrate that, in SZ, perceptual performance is determined by the balance of excitation-inhibition in superficial cortical layers. Twenty-eight individuals with a DSM-IV diagnosis of SZ, and 30 age- and gender-matched healthy controls participated in a psychophysics orientation discrimination task, a visual grating magnetoencephalography (MEG) recording, and a magnetic resonance spectroscopy (MRS) scan for GABA. Using a neurophysiologically informed model, we quantified group differences in GABA, gamma measures, and the predictive validity of model parameters for orientation discrimination in the SZ group. MEG visual gamma frequency was reduced in SZ, with lower peak frequency associated with more severe negative symptoms. Orientation discrimination performance was impaired in SZ. Dynamic causal modeling of the MEG data showed that local synaptic connections were reduced in SZ and local inhibition correlated negatively with the severity of negative symptoms. The effective connectivity between inhibitory interneurons and superficial pyramidal cells predicted orientation discrimination performance within the SZ group; consistent with graded, behaviorally relevant, disease-related changes in local GABAergic connections. Occipital GABA levels were significantly reduced in SZ but did not predict behavioral performance or oscillatory measures. These findings endorse the importance, and behavioral relevance, of GABAergic synaptic disconnection in schizophrenia that underwrites excitation-inhibition balance.

Project description:Abstract Background: Schizophrenia is a severe, highly heritable, neuropsychiatric disorder characterized by episodic psychosis and altered cognitive function. Despite success in identifying genetic variants associated with schizophrenia, there remains uncertainty about the causal genes involved in disease pathogenesis and how their function is regulated. Insights into the functional complexity of the genome have focussed attention on the role of non-sequence-based genomic variation in health and disease. Although a better understanding of the molecular mechanisms underlying disease phenotypes is best achieved using an integrated functional genomics strategy, few studies have attempted to systematically integrate genetic and epigenetic epidemiological approaches. Results: We performed a multi-stage epigenome-wide association study (EWAS), quantifying genome-wide patterns of DNA methylation in a total of 1,801 individuals from three independent sample cohorts. We identified multiple differentially methylated positions (DMPs) and region (DMRs) associated with schizophrenia, independently of important confounders such as smoking, with consistent effects across the three independent cohorts. We also show that polygenic burden for schizophrenia is associated with epigenetic variation at multiple loci across the genome, independently of loci implicated in the analysis of diagnosed schizophrenia. Finally, we show how DNA methylation quantitative trait loci (mQTL) analyses can be used to annotate the extended genomic regions nominated by genetic studies of schizophrenia, with Bayesian co-localization analyses highlighting potential regulatory variation causally involved in disease. Conclusion: This study represents the first systematic integrated analysis of genetic and epigenetic variation in schizophrenia, introducing a methodological pipeline that can be used to inform EWAS analyses of other complex traits and diseases. We demonstrate the utility of using polygenic risk score (PRS) for identifying molecular variation associated with etiological variation, and mQTLs for refining the functional/regulatory variation associated with schizophrenia risk variants. Finally, we present strong evidence for the co-localization of genetic associations for schizophrenia and differential DNA methylation. 847 whole blood derived DNA samples (414 schizophrenia cases and 433 controls) representing phase 2 of our meta-analysis. Bisulfite converted DNA from these samples were hybridised to the Illumina Infinium 450k Human Methylation Beadchip v1.0.

Project description:Background: Schizophrenia is a severe, highly heritable, neuropsychiatric disorder characterized by episodic psychosis and altered cognitive function. Despite success in identifying genetic variants associated with schizophrenia, there remains uncertainty about the causal genes involved in disease pathogenesis and how their function is regulated. Insights into the functional complexity of the genome have focussed attention on the role of non-sequence-based genomic variation in health and disease. Although a better understanding of the molecular mechanisms underlying disease phenotypes is best achieved using an integrated functional genomics strategy, few studies have attempted to systematically integrate genetic and epigenetic epidemiological approaches. Results: We performed a multi-stage epigenome-wide association study (EWAS), quantifying genome-wide patterns of DNA methylation in a total of 1,801 individuals from three independent sample cohorts. We identified multiple differentially methylated positions (DMPs) and region (DMRs) associated with schizophrenia, independently of important confounders such as smoking, with consistent effects across the three independent cohorts. We also show that polygenic burden for schizophrenia is associated with epigenetic variation at multiple loci across the genome, independently of loci implicated in the analysis of diagnosed schizophrenia. Finally, we show how DNA methylation quantitative trait loci (mQTL) analyses can be used to annotate the extended genomic regions nominated by genetic studies of schizophrenia, with Bayesian co-localization analyses highlighting potential regulatory variation causally involved in disease. Conclusion: This study represents the first systematic integrated analysis of genetic and epigenetic variation in schizophrenia, introducing a methodological pipeline that can be used to inform EWAS analyses of other complex traits and diseases. We demonstrate the utility of using polygenic risk score (PRS) for identifying molecular variation associated with etiological variation, and mQTLs for refining the functional/regulatory variation associated with schizophrenia risk variants. Finally, we present strong evidence for the co-localization of genetic associations for schizophrenia and differential DNA methylation. 675 whole blood derived DNA samples (353 schizophrenia cases and 322 controls) representing phase 1 of our meta-analysis. Bisulfite converted DNA from these samples were hybridized to the Illumina Infinium 450k Human Methylation Beadchip v1.0.

Dataset Information

Impaired glutathione synthesis in schizophrenia: convergent genetic and functional evidence.

Publications

Impaired glutathione synthesis in schizophrenia: convergent genetic and functional evidence.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets