Common schizophrenia risk variants are implicated in the function of glutamatergic neurons
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PROVIDER: PRJNA601202 | ENA |
REPOSITORIES: ENA
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Project description:The epigenome of human brain cells encompasses key information in understanding brain function in both healthy and diseased states. To further explore this, we used ATAC-seq to profile chromatin structure in four distinct populations of cells (glutamatergic neurons, GABAergic neurons, oligodendrocytes, and microglia/astrocytes), from three different regions of the brain. Chromatin accessibility was found to vary vastly by cell type and, more moderately, by brain region, with glutamatergic neurons showing the greatest regional variability. Transcription factor footprinting pointed to cell-specific transcriptional regulators and inferred cell-specific regulation of protein coding genes, long intergenic noncoding RNAs, and microRNAs. In vivo transgenic mouse experiments validated the cell type specificity of a number of human-derived regulatory sequences. Open chromatin regions in glutamatergic neurons were enriched for neuropsychiatric risk variants, particularly those associated with schizophrenia. Combining differential chromatin accessibility analysis using ATAC-seq data from bulk tissue increased our statistical power to confirm glutamatergic neurons as the cell type most affected in schizophrenia. Jointly, these findings illustrate the utility of studying the cell type specific epigenome in complex tissues such as the human brain and implicate an association among chromatin accessibility in glutamatergic neurons and genetic risk for schizophrenia.
2020-08-20 | GSE143666 | GEO
Project description:We report changes in gene expression in schizophrenia developmental glutamatergic neurons by genome-wide transcriptome analysis.
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Project description:Genome binding/occupancy profiling was carried out by high throughput sequencing in human developmental cortical interneurons and developmental glutamatergic neurons derived from healthy control vs schizophrenia iPSCs
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Project description:ZNF804A was amongst the first genes robustly associated with schizophrenia based on findings from large-scale genomic studies. Previous research has implicated ZNF804A inthe regulation of gene expression and synaptic function, but the role this gene plays inneurodevelopment and in relation to schizophrenia pathogenesis remains unclear. To study the function of this gene during neurodevelopment, we generated isogenichuman induced pluripotent stem cells (hiPSCs) with reduced ZNF804A expression, differentiated them into developing cortical glutamatergic neurons and studied theirtranscriptomic, synaptic and protein signatures. Mutant neurons showed modest changes in gene expression. However, high-content confocal imaging revealed increased excitatory synapse density in mutant neurons. Cell-compartment specific proteomic analysis further revealed that mutant neurons had higher levels of ribosomal andtranslational proteins in their neurites, and high-content imaging confirming increased local protein synthesis efficiency. Overall, these results demonstrate that in human developing cortical glutamatergic neurons, ZNF804A regulates excitatory synapse formation potential via increased local protein translation.
2024-01-30 | GSE254523 | GEO
Project description:Genome-wide association studies (GWAS) have accelerated the discovery of numerous genetic variants associated with schizophrenia. However, most risk variants show a small effect size (odds ratio (OR)<1.2), suggesting that more functional risk variants remain to be identified. Here, we employed region-based multi-marker analysis of genomic annotation (MAGMA) to identify additional risk loci containing variants with large OR value from Psychiatry Genomics Consortium (PGC2) schizophrenia GWAS data and then employed summary-data-based mendelian randomization (SMR) to prioritize schizophrenia susceptibility genes. The top-ranked susceptibility gene ATP5MD, encoding an ATP synthase membrane subunit, is observed to be downregulated in schizophrenia by the risk allele of CNNM2-rs1926032 in the schizophrenia-associated 10q24.32 locus.
2021-03-30 | GSE171077 | GEO
Project description:Genetic association studies provide evidence for a substantial polygenic component to schizophrenia, although the neurobiological mechanisms underlying the disorder remain largely undefined. Building on recent studies supporting a role for developmentally regulated epigenetic variation in the molecular etiology of schizophrenia, this study aimed to identify epigenetic variation associated with both a diagnosis of schizophrenia and elevated polygenic risk burden for the disease across multiple brain regions. Genome-wide DNA methylation was quantified in 262 post-mortem brain samples, representing tissue from four brain regions (prefrontal cortex, striatum, hippocampus and cerebellum) from 41 schizophrenia patients and 47 controls. We identified multiple disease-associated and polygenic risk score-associated differentially methylated positions and regions, many residing in the vicinity of genes previously implicated in schizophrenia including NCAM1, SYNPO, GBP4, PRDM9, GADD45B and DISC1. Our study represents the first analysis of epigenetic variation associated with schizophrenia across multiple brain regions and highlights the utility of polygenic risk scores for identifying molecular pathways associated with etiological variation in complex disease.
2016-11-10 | GSE89706 | GEO
Project description:Genetic association studies provide evidence for a substantial polygenic component to schizophrenia, although the neurobiological mechanisms underlying the disorder remain largely undefined. Building on recent studies supporting a role for developmentally regulated epigenetic variation in the molecular etiology of schizophrenia, this study aimed to identify epigenetic variation associated with both a diagnosis of schizophrenia and elevated polygenic risk burden for the disease across multiple brain regions. Genome-wide DNA methylation was quantified in 262 post-mortem brain samples, representing tissue from four brain regions (prefrontal cortex, striatum, hippocampus and cerebellum) from 41 schizophrenia patients and 47 controls. We identified multiple disease-associated and polygenic risk score-associated differentially methylated positions and regions, many residing in the vicinity of genes previously implicated in schizophrenia including NCAM1, SYNPO, GBP4, PRDM9, GADD45B and DISC1. Our study represents the first analysis of epigenetic variation associated with schizophrenia across multiple brain regions and highlights the utility of polygenic risk scores for identifying molecular pathways associated with etiological variation in complex disease.
2016-11-10 | GSE89705 | GEO
Project description:Genetic association studies provide evidence for a substantial polygenic component to schizophrenia, although the neurobiological mechanisms underlying the disorder remain largely undefined. Building on recent studies supporting a role for developmentally regulated epigenetic variation in the molecular etiology of schizophrenia, this study aimed to identify epigenetic variation associated with both a diagnosis of schizophrenia and elevated polygenic risk burden for the disease across multiple brain regions. Genome-wide DNA methylation was quantified in 262 post-mortem brain samples, representing tissue from four brain regions (prefrontal cortex, striatum, hippocampus and cerebellum) from 41 schizophrenia patients and 47 controls. We identified multiple disease-associated and polygenic risk score-associated differentially methylated positions and regions, many residing in the vicinity of genes previously implicated in schizophrenia including NCAM1, SYNPO, GBP4, PRDM9, GADD45B and DISC1. Our study represents the first analysis of epigenetic variation associated with schizophrenia across multiple brain regions and highlights the utility of polygenic risk scores for identifying molecular pathways associated with etiological variation in complex disease.
2016-11-10 | GSE89703 | GEO
Project description:Genetic association studies provide evidence for a substantial polygenic component to schizophrenia, although the neurobiological mechanisms underlying the disorder remain largely undefined. Building on recent studies supporting a role for developmentally regulated epigenetic variation in the molecular etiology of schizophrenia, this study aimed to identify epigenetic variation associated with both a diagnosis of schizophrenia and elevated polygenic risk burden for the disease across multiple brain regions. Genome-wide DNA methylation was quantified in 262 post-mortem brain samples, representing tissue from four brain regions (prefrontal cortex, striatum, hippocampus and cerebellum) from 41 schizophrenia patients and 47 controls. We identified multiple disease-associated and polygenic risk score-associated differentially methylated positions and regions, many residing in the vicinity of genes previously implicated in schizophrenia including NCAM1, SYNPO, GBP4, PRDM9, GADD45B and DISC1. Our study represents the first analysis of epigenetic variation associated with schizophrenia across multiple brain regions and highlights the utility of polygenic risk scores for identifying molecular pathways associated with etiological variation in complex disease.
2016-11-10 | GSE89702 | GEO
Project description:Genome-wide association studies (GWAS) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium (LD) makes it challenging to discern causal variants. Computational finemapping prioritized thousands of credible variants, ~98% of which lie within poorly characterized non-coding regions. To functionally validate their regulatory effects, we performed a massively parallel reporter assay (MPRA) on 5,173 finemapped schizophrenia GWAS variants in primary human neural progenitors (HNPs). We identified 440 variants with allelic regulatory effects (MPRA-positive variants), with 72% of GWAS loci containing at least one MPRA-positive variant. Transcription factor binding had modest predictive power for predicting the allelic activity of MPRA-positive variants, while GWAS association, finemap posterior probability, enhancer overlap, and evolutionary conservation failed to predict MPRA-positive variants. Furthermore, 64% of MPRA-positive variants did not exhibit eQTL signature, suggesting that MPRA could identify yet unexplored variants with regulatory potentials. MPRA-positive variants differed from eQTLs, as they were more frequently located in distal neuronal enhancers. Therefore, we leveraged neuronal 3D chromatin architecture to identify 273 genes that physically interact with MPRA-positive variants. These genes annotated by chromatin interactome displayed higher mutational constraints and regulatory complexity than genes annotated by eQTLs, recapitulating a recent finding that eQTL- and GWAS-detected variants map to genes with different properties. Finally, we propose a model in which allelic activity of multiple variants within a GWAS locus can be aggregated to predict gene expression by taking chromatin contact frequency and accessibility into account. In conclusion, we demonstrate that MPRA can effectively identify functional regulatory variants and delineate previously unknown regulatory principles of schizophrenia.
2023-08-07 | GSE211045 | GEO