90 research outputs found
The proteomes of neurotransmitter receptor complexes form modular networks with distributed functionality underlying plasticity and behaviour
Neuronal synapses play fundamental roles in information processing, behaviour and disease. Neurotransmitter receptor complexes, such as the mammalian N-methyl-D-aspartate receptor complex (NRC/MASC) comprising 186 proteins, are major components of the synapse proteome. Here we investigate the organisation and function of NRC/MASC using a systems biology approach. Systematic annotation showed that the complex contained proteins implicated in a wide range of cognitive processes, synaptic plasticity and psychiatric diseases. Protein domains were evolutionarily conserved from yeast, but enriched with signalling domains associated with the emergence of multicellularity. Mapping of protein–protein interactions to create a network representation of the complex revealed that simple principles underlie the functional organisation of both proteins and their clusters, with modularity reflecting functional specialisation. The known functional roles of NRC/MASC proteins suggest the complex co-ordinates signalling to diverse effector pathways underlying neuronal plasticity. Importantly, using quantitative data from synaptic plasticity experiments, our model correctly predicts robustness to mutations and drug interference. These studies of synapse proteome organisation suggest that molecular networks with simple design principles underpin synaptic signalling properties with important roles in physiology, behaviour and disease
Dynamic expression of genes associated with schizophrenia and bipolar disorder across development
Common genetic variation contributes a substantial proportion of risk for both schizophrenia and bipolar disorder. Furthermore, there is evidence of significant, but not complete, overlap in genetic risk between the two disorders. It has been hypothesised that genetic variants conferring risk for these disorders do so by influencing brain development, leading to the later emergence of symptoms. The comparative profile of risk gene expression for schizophrenia and bipolar disorder across development over different brain regions however remains unclear. Using genotypes derived from genome-wide associations studies of the largest available cohorts of patients and control subjects, we investigated whether genes enriched for schizophrenia and bipolar disorder association show a bias for expression across any of 13 developmental stages in prefrontal cortical and subcortical brain regions. We show that genetic association with schizophrenia is positively correlated with expression in the prefrontal cortex during early midfetal development and early infancy, and negatively correlated with expression during late childhood, which stabilises in adolescence. In contrast, risk-associated genes for bipolar disorder did not exhibit a bias towards expression at any prenatal stage, although the pattern of postnatal expression was similar to that of schizophrenia. These results highlight the dynamic expression of genes harbouring risk for schizophrenia and bipolar disorder across prefrontal cortex development and support the hypothesis that prenatal neurodevelopmental events are more strongly associated with schizophrenia than bipolar disorder
Neurotransmitters Drive Combinatorial Multistate Postsynaptic Density Networks
The mammalian postsynaptic density (PSD) comprises a complex collection of ~1100 proteins. Despite extensive knowledge of individual proteins, the overall organization of the PSD is poorly understood. Here, we define maps of molecular circuitry within the PSD based on phosphorylation of postsynaptic proteins. Activation of a single neurotransmitter receptor, the N-methyl-D-aspartate receptor (NMDAR), changed the phosphorylation status of 127 proteins. Stimulation of ionotropic and metabotropic glutamate receptors and dopamine receptors activated overlapping networks with distinct combinatorial phosphorylation signatures. Using peptide array technology, we identified specific phosphorylation motifs and switching mechanisms responsible for the integration of neurotransmitter receptor pathways and their coordination of multiple substrates in these networks. These combinatorial networks confer high information-processing capacity and functional diversity on synapses, and their elucidation may provide new insights into disease mechanisms and new opportunities for drug discover
Pharmacogenomic variants and drug interactions identified through the genetic analysis of clozapine metabolism
Objective: Clozapine is the only effective medication for treatment-resistant schizophrenia, but its worldwide use is still limited because of its complex titration protocols. While the discovery of pharmacogenomic variants of clozapine metabolism may improve clinical management, no robust findings have yet been reported. This study is the first to adopt the framework of genome-wide association studies (GWASs) to discover genetic markers of clozapine plasma concentrations in a large sample of patients with treatment-resistant schizophrenia. Methods: The authors used mixed-model regression to combine data from multiple assays of clozapine metabolite plasma concentrations from a clozapine monitoring service and carried out a genome-wide analysis of clozapine, norclozapine, and their ratio on 10,353 assays from 2,989 individuals. These analyses were adjusted for demographic factors known to influence clozapine metabolism, although it was not possible to adjust for all potential mediators given the available data. GWAS results were used to pinpoint specific enzymes and metabolic pathways and compounds that might interact with clozapine pharmacokinetics. Results: The authors identified four distinct genome-wide significant loci that harbor common variants affecting the metabolism of clozapine or its metabolites. Detailed examination pointed to coding and regulatory variants at several CYP* and UGT* genes as well as corroborative evidence for interactions between the metabolism of clozapine, coffee, and tobacco. Individual effects of single single-nucleotide polymorphisms (SNPs) fine-mapped from these loci were large, such as the minor allele of rs2472297, which was associated with a reduction in clozapine concentrations roughly equivalent to a decrease of 50 mg/day in clozapine dosage. On their own, these single SNPs explained from 1.15% to 9.48% of the variance in the plasma concentration data. Conclusions: Common genetic variants with large effects on clozapine metabolism exist and can be found via genome-wide approaches. Their identification opens the way for clinical studies assessing the use of pharmacogenomics in the clinical management of patients with treatment-resistant schizophrenia
Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis:Evidence from population sample stratified for polygenic risk
A transcriptome-wide association study implicates specific pre- and post-synaptic abnormalities in schizophrenia
chizophrenia is a complex highly heritable disorder. Genome-wide association studies (GWAS) have identified multiple loci that influence the risk of developing schizophrenia, although the causal variants driving these associations and their impacts on specific genes are largely unknown. We identify a significant correlation between schizophrenia risk and expression at 89 genes in dorsolateral prefrontal cortex (P ≤ 9.43x10−6), including 20 novel genes. Genes whose expression correlate with schizophrenia were enriched for those involved in abnormal CNS synaptic transmission (PFDR = 0.02) and antigen processing and presentation of peptide antigen via MHC class I (PFDR = 0.02). Within the CNS synaptic transmission set, we identify individual significant candidate genes to which we assign direction of expression changes in schizophrenia. The findings provide strong candidates for experimentally probing the molecular basis of synaptic pathology in schizophrenia
Novel insight into the etiology of autism spectrum disorder gained by integrating expression data with genome-wide association statistics
Background A recent genome-wide association study (GWAS) of autism spectrum disorders (ASD) (Ncases=18,381, Ncontrols=27,969) has provided novel opportunities for investigating the aetiology of ASD. Here, we integrate the ASD GWAS summary statistics with summary-level gene expression data to infer differential gene expression in ASD, an approach called transcriptome-wide association study (TWAS). Methods Using FUSION software, ASD GWAS summary statistics were integrated with predictors of gene expression from 16 human datasets, including adult and fetal brain. A novel adaptation of established statistical methods was then used to test for enrichment within candidate pathways, specific tissues, and at different stages of brain development. The proportion of ASD heritability explained by predicted expression of genes in the TWAS was estimated using stratified linkage disequilibrium-score regression. Results This study identified 14 genes as significantly differentially expressed in ASD, 13 of which were outside of known genome-wide significant loci (±500kb). XRN2, a gene proximal to an ASD GWAS locus, was inferred to be significantly upregulated in ASD, providing insight into functional consequence of this associated locus. One novel transcriptome-wide significant association from this study is the downregulation of PDIA6, which showed minimal evidence of association in the GWAS, and in gene-based analysis using MAGMA. Predicted gene expression in this study accounted for 13.0% of the total ASD SNP-heritability. Conclusion This study has implicated several genes as significantly up-/down-regulated in ASD providing novel and useful information for subsequent functional studies. This study also explores the utility of TWAS-based enrichment analysis and compares TWAS results with a functionally agnostic approach
Rare copy number variations are associated with poorer cognition in schizophrenia
Background
Cognitive impairment in schizophrenia is a major contributor to poor outcomes yet its causes are poorly understood. Some rare copy number variants (CNVs) are associated with schizophrenia risk and impact cognition in healthy populations but their contribution to cognitive impairment in schizophrenia has not been investigated. We examined the effect of 12 schizophrenia CNVs on cognition in those with schizophrenia.
Methods
General cognitive ability was measured using the MATRICS composite z-score in 875 schizophrenia cases, and in a replication sample of 519 schizophrenia cases using WAIS Full-Scale IQ. Using linear regression we tested for association between cognition and schizophrenia CNV status, covarying for age and sex. In addition, we tested whether CNVs hitting genes in schizophrenia enriched gene sets (loss of function intolerant or synaptic gene sets) were associated with cognitive impairment.
Results
23 schizophrenia CNV carriers were identified. Schizophrenia CNV carriers had lower general cognitive ability than non-schizophrenia CNV carriers in discovery (β=-0.66, 95%CI = -1.31 to -0.01) and replication samples (β=-0.91, 95%CI =-1.71 to -0.11), and after meta-analysis (β=-0.76, 95%CI=-1.26 to -0.25, p=0.003). CNVs hitting loss of function intolerant genes were associated with lower cognition (β= -0.15, 95%CI=-0.29 to -0.001, p=0.048).
Conclusions
In those with schizophrenia, cognitive ability in schizophrenia CNV carriers is 0.5-1.0 standard deviations below non-CNV carriers, which may have implications for clinical assessment and management. We also demonstrate that rare CNVs hitting genes intolerant to loss of function variation lead to more severe cognitive impairment, above and beyond the effect of known schizophrenia CNVs
Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia-related genes.
Schizophrenia has been conceived as a disorder of brain connectivity, but it is unclear how this network phenotype is related to the underlying genetics. We used morphometric similarity analysis of MRI data as a marker of interareal cortical connectivity in three prior case-control studies of psychosis: in total, n = 185 cases and n = 227 controls. Psychosis was associated with globally reduced morphometric similarity in all three studies. There was also a replicable pattern of case-control differences in regional morphometric similarity, which was significantly reduced in patients in frontal and temporal cortical areas but increased in parietal cortex. Using prior brain-wide gene expression data, we found that the cortical map of case-control differences in morphometric similarity was spatially correlated with cortical expression of a weighted combination of genes enriched for neurobiologically relevant ontology terms and pathways. In addition, genes that were normally overexpressed in cortical areas with reduced morphometric similarity were significantly up-regulated in three prior post mortem studies of schizophrenia. We propose that this combined analysis of neuroimaging and transcriptional data provides insight into how previously implicated genes and proteins as well as a number of unreported genes in their topological vicinity on the protein interaction network may drive structural brain network changes mediating the genetic risk of schizophrenia.This study was supported by grants from the European Commission (PSYSCAN - Translating neuroimaging findings from research into clinical practice; ID: 603196) and the NIHR Cambridge Biomedical Research Centre (Mental Health). SEM holds a Henslow Fellowship at Lucy Cavendish College, University of Cambridge, funded by the Cambridge Philosophical Society. PEV was supported by the Medical Research Council (MR/K020706/1) and an MQ fellowship (MQF17_24) and is a Fellow of the Alan Turing Institute funded under the EPSRC grant EP/N510129/1. KJW was funded by an Alan Turing Institute Research Fellowship under EPSRC Research grant TU/A/000017. ETB is supported by a NIHR Senior Investigator Award
Treating the placenta to prevent adverse effects of gestational hypoxia on fetal brain development.
Some neuropsychiatric disease, including schizophrenia, may originate during prenatal development, following periods of gestational hypoxia and placental oxidative stress. Here we investigated if gestational hypoxia promotes damaging secretions from the placenta that affect fetal development and whether a mitochondria-targeted antioxidant MitoQ might prevent this. Gestational hypoxia caused low birth-weight and changes in young adult offspring brain, mimicking those in human neuropsychiatric disease. Exposure of cultured neurons to fetal plasma or to secretions from the placenta or from model trophoblast barriers that had been exposed to altered oxygenation caused similar morphological changes. The secretions and plasma contained altered microRNAs whose targets were linked with changes in gene expression in the fetal brain and with human schizophrenia loci. Molecular and morphological changes in vivo and in vitro were prevented by a single dose of MitoQ bound to nanoparticles, which were shown to localise and prevent oxidative stress in the placenta but not in the fetus. We suggest the possibility of developing preventative treatments that target the placenta and not the fetus to reduce risk of psychiatric disease in later life
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