Ontology highlight
ABSTRACT:
PROVIDER: PRJEB41532 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| rs6265file.vcf.gz | Vcf | |||
| rs6265file.vcf.gz.tbi | Vcf |
Items per page: 5 1 - 2 of 2 |
Similar Datasets
Project description:BDNF gene?s role in schizophrenia: from risk allele to methylation implications
2020-12-15 | PRJEB41532 | EVA
Project description:DNA methylation of gene promoter regions represses transcription and is a mechanism via which environmental risk factors could affect cells during development in individuals at risk for schizophrenia. We investigated DNA methylation in patient-derived cells that might shed light on early development in schizophrenia. Induced pluripotent stem cells (iPS cells) may reflect a âground stateâ upon which developmental and environmental influences would be minimal. Olfactory neurosphere-derived cells (ONS cells) are an adult-derived neuro-ectodermal stem cell modified by developmental and environmental influences. Fibroblasts provide a non-neural control for life-long developmental and environmental influences. Genome-wide profiling of DNA methylation and gene expression was done in these three cell types from the same individuals. All cell types had distinct, statistically significant schizophrenia-associated differences in DNA methylation and linked gene expression, with Gene Ontology analysis showing that the differentially affected genes clustered in networks associated with cell growth, proliferation and movement, functions known to be affected in schizophrenia patient-derived cells. Only 5 gene loci were differentially methylated in all three cell types. These findings suggest that schizophrenia-associated DNA methylation may be a response to the homeostatic demands of different cell types in their local environments. Understanding the role of epigenetics in cell function in the brain in schizophrenia is likely to be complicated by similar cell type differences in intrinsic and environmentally-induced epigenetic regulation. This dataset represents the gene expression part of the study. The DNA methylation data is deposited under accession E-MTAB-2154.
2017-11-01 | E-MTAB-5016 | biostudies-arrayexpress
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:Recent studies suggest that genetic and environmental factors do not account for all the schizophrenia risk and epigenetics also plays a role in disease susceptibility. DNA methylation is a heritable epigenetic modification that can regulate gene expression. Genome-Wide DNA methylation analysis was performed on post-mortem human brain tissue from 24 patients with schizophrenia and 24 unaffected controls. DNA methylation was assessed at over 485 000 CpG sites using the Illumina Infinium Human Methylation450 Bead Chip. After adjusting for age and post-mortem interval (PMI), 4 641 probes corresponding to 2 929 unique genes were found to be differentially methylated. Of those genes, 1 291 were located in a CpG island and 817 were in a promoter region. These include NOS1, AKT1, DTNBP1, DNMT1, PPP3CC and SOX10 which have previously been associated with schizophrenia. More than 100 of these genes overlap with a previous DNA methylation study of peripheral blood from schizophrenia patients in which 27 000 CpG sites were analysed. Unsupervised clustering analysis of the top 3 000 most variable probes revealed two distinct groups with significantly more people with schizophrenia in cluster one compared to controls (p = 1.74x10-4). The first cluster was composed of 88% of patients with schizophrenia and only 12% controls while the second cluster was composed of 27% of patients with schizophrenia and 73% controls. These results strongly suggest that differential DNA methylation is important in schizophrenia etiology and add support for the use of DNA methylation profiles as a future prognostic indicator of schizophrenia Genome-Wide DNA methylation analysis was performed on post-mortem human brain tissue from 24 patients with schizophrenia and 24 unaffected controls. DNA methylation was assessed at over 485 000 CpG sites using the Illumina Infinium Human Methylation450 Bead Chip.
2014-09-05 | E-GEOD-61107 | biostudies-arrayexpress
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.
2016-08-01 | E-GEOD-80417 | biostudies-arrayexpress
Project description:Epigenetics describes mechanisms via which the environment can act on the genome, including DNA methylation of promoter regions of genes. This could be a way that environmental risk factors could affect neurodevelopment in individuals at risk for schizophrenia. Patient-derived cells provide a means whereby epigenetics and gene-environment interactions might be investigated. Induced pluripotent stem cells (iPS cells) present an attractive patient-derived cellular model because they can be differentiated into cell types of interest in schizophrenia. In this study the influence of the reprogramming process on schizophrenia-associated DNA methylation was investigated through genome-wide DNA methylation profiling and gene expression of patient-derived iPS cells and the fibroblasts from which they were derived. Olfactory neurosphere-derived cells (ONS cells) from the same patients were also profiled to provide a window on epigenetic regulation in three distinct cell types. Patient-derived cell were compared to cells derived from healthy controls to identify differences in DNA methylation and gene expression associated with schizophrenia in three cell types. The main finding is that iPS cells, prior to neuronal differentiation, demonstrated significant schizophrenia-associated differences in DNA methylation. This is in contrast to the fibroblasts from which they were derived, which show lesser schizophrenia-associated differences in DNA methylation. Like iPS cells, ONS cells showed robust significant schizophrenia-associated differences in DNA methylation. Notably, the schizophrenia-associated differences in DNA methylation were unique for each cell type, with little overlap between them, and only 5 genes commonly methylated in all cell types. Gene expression differences among the cell types mirrored the DNA methylation differences in magnitude, again with little overlap in specific genes affected. Gene Ontology analysis of the affected genes identified common cellular process affected in all three cell types without the same genes contributing. These data suggest that most DNA methylation differences are driven by the demands imposed by each cell type with schizophrenia-associated differences also being cell-type specific. Thus DNA methylation may not be a cause of schizophrenia-associated differences in cell functions in these cells but rather a downstream consequence of some unidentified causative mechanisms. This dataset represents the DNA methylation part of the study. The gene expression data is deposited under accession E-MTAB-5016.
2016-12-01 | E-MTAB-2154 | biostudies-arrayexpress
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.
2016-08-01 | E-GEOD-84727 | biostudies-arrayexpress
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