S3 Swedish schizophrenia case-control study
Ontology highlight
ABSTRACT:
PROVIDER: EGAS00001006772 | EGA |
REPOSITORIES: EGA
Similar Datasets
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:A large portion of common variant loci associated with genetic risk for schizophrenia reside within non-coding sequence of unknown function. Here, we demonstrate promoter and enhancer enrichment in schizophrenia variants associated with expression quantitative trait loci (eQTL). The enrichment is greater when functional annotations derived from human brain are used relative to peripheral tissues. Regulatory trait concordance analysis ranked genes within schizophrenia genome-wide significant loci, based on co-localization of a risk SNP, eQTL and regulatory element sequence. These include physical interactions of non-contiguous gene-proximal and distal elements bypassing the linear genome, which was verified in prefrontal cortex and human induced pluripotent stem cell derived neurons for the L-type calcium channel (CACNA1C) risk locus. Our findings point to a functional link between schizophrenia-associated non-coding SNPs and 3-dimensional genome architecture associated with chromosomal loopings and transcriptional regulation in the brain. Examination of H3K4me3 histone modifications in 3 samples.
2014-10-17 | E-GEOD-62391 | biostudies-arrayexpress
Project description:Schizophrenia (SZ) is a devastating psychiatric illness affecting 1% of the world population. In addition to genetic predisposition, environmental factors contribute to the risk for developing SZ. Such genome environment interactions frequently activate epigenetic and epitranscriptomic mechansims. There are emerging evidence that genetic and environmental risk factors merge at the level of microRNA expression, which are discussed as biomarker and therapeutic target in various disorders including neuropsychiatric diseases. In this study we analyzed the blood microRNAome of healthy individuals and SZ patients via small RNA sequencing. By combining these data with a corresponding analysis of post-mortem human brain tissue, we identify one candidate microRNA that is down-regulated in patients. Moreover, its expression is significantly correlated to disease phenotypes. Manipulation of this microRNAs in mouse prefrontal cortex causes schizophrenia-like phenotypes. Functional analysis revealed the cellular processes affected by this microRNA and allowed us to develop an arsenal of RNA-based therapeutic approaches that are able to ameliorate molecular disease phenotypes in mouse and human-based cellular systems as well as the behavioral phenotypes. In conclusion, we identify a novel microRNA as target for stratified RNA-therapeutics in schizophrenia.
2024-03-26 | GSE224142 | GEO
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:Schizophrenia is a complex psychiatric disorder encompassing a range of symptoms and etiology dependent upon the interaction of genetic and environmental factors. Several risk genes, such as DISC1, have been associated with schizophrenia as well as bipolar disorder (BPD) and major depressive disorder (MDD), consistent with the hypothesis that a shared genetic architecture could contribute to divergent clinical syndromes. The present study compared gene expression profiles across three brain regions in post-mortem tissue from matched subjects with schizophrenia, BPD or MDD and unaffected controls. Post-mortem brain tissue was collected from control subjects and well-matched subjects with schizophrenia, BPD, and MDD (n=19 from each group). RNA was isolated from hippocampus, Brodmann Area 46, and associative striatum and hybridized to U133_Plus2 Affymetrix chips. Data were normalized by RMA, subjected to pairwise comparison followed by Benjamini and Hochberg False Discovery Rate correction (FDR). Samples derived from patients with schizophrenia exhibited many more changes in gene expression across all brain regions than observed in BPD or MDD. Several genes showed changes in both schizophrenia and BPD, though the magnitude of change was usually larger in schizophrenia. Several genes that have variants associated with schizophrenia were found to have altered expression in multiple regions of brains from subjects with schizophrenia. Continued evaluation of circuit-level alterations in gene expression and gene-network relationships may further our understanding of how genetic variants may be influencing biological processes to contribute to psychiatric disease. Pre-frontal cortex, striatum and hippocampus were obtained from subjects with schizophrenia, bipolar disorder, major depressive disorder and matched controls.
2014-01-11 | E-GEOD-53987 | 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
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: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