Massively parallel functional dissection of schizophrenia associated non-coding genetic variants [RNA-seq]
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE225813 | GEO | 2023/10/16
REPOSITORIES: GEO
Similar Datasets
Project description:Schizophrenia (SCZ) is a highly polygenic disease and genome wide association studies have identified thousands of genetic variants that are statistically associated with this psychiatric disorder. However, our ability to translate these associations into insights on the disease mechanisms has been challenging since the causal genetic variants, their molecular function and their target genes remain largely unknown. In order to address these questions, we established a functional genomics pipeline in combination with induced pluripotent stem cell technology to functionally characterize 35,000 non-coding genetic variants associated with schizophrenia along with their target genes. This analysis identified a set of 620 (1.7%) single nucleotide polymorphisms as functional on a molecular level in a highly cell type and condition specific fashion. These results provide a high-resolution map of functional variant-gene combinations and offer comprehensive biological insights into the developmental context and stimulation dependent molecular processes modulated by SCZ associated genetic variation.
2023-10-16 | GSE225816 | GEO
Project description:Schizophrenia (SCZ) is a highly polygenic disease and genome wide association studies have identified thousands of genetic variants that are statistically associated with this psychiatric disorder. However, our ability to translate these associations into insights on the disease mechanisms has been challenging since the causal genetic variants, their molecular function and their target genes remain largely unknown. In order to address these questions, we established a functional genomics pipeline in combination with induced pluripotent stem cell technology to functionally characterize 35,000 non-coding genetic variants associated with schizophrenia along with their target genes. This analysis identified a set of 620 (1.7%) single nucleotide polymorphisms as functional on a molecular level in a highly cell type and condition specific fashion. These results provide a high-resolution map of functional variant-gene combinations and offer comprehensive biological insights into the developmental context and stimulation dependent molecular processes modulated by SCZ associated genetic variation.
2023-10-16 | GSE225815 | GEO
Project description:Schizophrenia (SCZ) is a highly polygenic disease and genome wide association studies have identified thousands of genetic variants that are statistically associated with this psychiatric disorder. However, our ability to translate these associations into insights on the disease mechanisms has been challenging since the causal genetic variants, their molecular function and their target genes remain largely unknown. In order to address these questions, we established a functional genomics pipeline in combination with induced pluripotent stem cell technology to functionally characterize 35,000 non-coding genetic variants associated with schizophrenia along with their target genes. This analysis identified a set of 620 (1.7%) single nucleotide polymorphisms as functional on a molecular level in a highly cell type and condition specific fashion. These results provide a high-resolution map of functional variant-gene combinations and offer comprehensive biological insights into the developmental context and stimulation dependent molecular processes modulated by SCZ associated genetic variation.
2023-10-16 | GSE225814 | GEO
Project description:Schizophrenia (SCZ) is a severe mental disorder affecting 1% of the world population. SCZ is characterized by an underlying genetic architecture that is highly polygenic. Genome wide association studies have identified thousands of genetic variants that are statistically linked to the disease. However, the translation of these associations into insights on the pathomechanisms has been challenging because the causal genetic variants, their molecular function, and their target genes remain largely unknown. To address these questions, we combined induced pluripotent stem cell technology with a massively parallel variant annotation pipeline (MVAP) to functionally characterize 35,000 SCZ associated non-coding genetic variants. This approach identified a set of 620 (1.7%) single nucleotide polymorphisms as functional on the molecular level in a highly cell type and condition specific fashion. Subsequent multi-modal integration of epigenomic data combined with CRISPR screening in human neurons enabled us to systematically translate SCZ variant associations into target genes, biological processes, and ultimately alterations of neuronal physiology. These results provide a new high-resolution map of functional variant-gene combinations and offer comprehensive biological insights into the developmental context and stimulus dependent molecular processes modulated by SCZ genetic variation beyond statistical association.
| EGAS00001007542 | EGA
Project description:Whole-genome expression studies in peripheral tissues of patients affected by schizophrenia (SCZ) can provide new insights into the molecular basis of the disorder and innovative biomarkers that may be of great usefulness in the clinical practice. Recent evidence suggests that skin fibroblasts could represent a non-neural peripheral model useful to investigate molecular alterations in psychiatric disorders. A microarray expression study was conducted comparing transcriptomic profiles of skin fibroblasts from SCZ patients and controls. Fibroblasts can be more advantageous to discover mental disorder aetiological mechanisms since they seem more similar to neurons and less affected by the environmental confounders. Transcriptomic profiles of human skin fibroblasts obtained from 20 schizophrenia patients were compared to 20 controls
2015-02-17 | E-GEOD-62333 | 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: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:We utilized patient-derived induced pluripotent stem cells (iPSCs) to generate 3D cerebral organoids to model neuropathology of Scz during this critical period. We discovered that Scz organoids exhibited ventricular neuropathology resulting in altered progenitor survival and disrupted neurogenesis. cz organoids principally differed not in their proteomic diversity, but specifically in their total quantity of disease and neurodevelopmental factors at the molecular level. Provides unique insights into the proteome landscape of schizophrenia in patient-derived cerebral organoids
2021-11-17 | PXD027812 | Pride
Project description:Genome-wide association studies indicate allele variants in MIR137, the host gene of microRNA-137 (miR137), confer an increased risk of schizophrenia (SCZ). Expression of miR137 and its targets, many of which regulate synaptic functioning, are also associated with an increased risk of SCZ. As a result, miR137 represents an attractive target aimed at correcting the molecular basis for synaptic dysfunction in individuals with high genetic risk for SCZ. Advancements in nanotechnology utilize lipid nanoparticles (LNPs) to transport and deliver therapeutic RNA. However, there remains a gap in using LNPs to regulate gene and protein expression in the brain. To study the delivery of nucleic acids by LNPs to the brain, we found that LNPs released miR137 cargo and inhibited synaptic target transcripts in neuronal cultures. Biodistribution of LNPs loaded with firefly luciferase mRNA remained localized to the mouse prefrontal cortex (PFC) injection site without circulating to off-target organs. LNPs encapsulating Cre mRNA preferentially co-expressed in neuronal over microglial or astrocytic cells. Using quantitative proteomics, we found miR137 modulated glutamatergic synaptic protein networks that are commonly dysregulated in SCZ. These studies support engineering the next generation of brain-specific LNPs to deliver personalized RNA therapeutics and improve symptoms of central nervous system disorders.
2023-09-05 | PXD041648 | Pride
Project description:Susceptibility genes for Autism Spectrum Disorder (ASD), Fragile X Syndrome (FXS), monogenetic disorders with intellectual disabilities (ID) or schizophrenia (SCZ) converge on processes related to neuronal function and differentiation. Furthermore, ASD risk genes are enriched for FMRP (Fragile X Mental Retardation Protein) targets and for genes implicated in ID. In addition, a significant co-heritability was observed between ASD and SCZ. The genetic overlap between ASD, FXS, ID and SCZ together with the symptomatic differences gives rise to the question if pathomechanisms impair the same or different regulatory patterns activated during neuronal differentiation (ND). To test this idea, we performed transcriptome analysis of in-vitro differentiation of the neuroblastoma cell line model SH-SY5Y and identified genes that were differentially expressed, dynamically regulated, and coordinately expressed. The identified genetic modules activated during ND are enriched for genetic risk factors for these four disorders. Although risk genes for the disorders significantly overlap, we observed disorder specific enrichments: ASD or FXS implicated genes were likely to be positive regulators of ND whereas ID implicated genes were related to negative regulation. ASD and SCZ genes were specifically enriched among cholesterol and fatty acid associated modules. ID genes were overrepresented among cell cycle modules. In addition, we show that ASD genes are likely to be hub genes. We hypothesize that knowledge about genetic variants of an individual combined with network and pathway context of the related genes will allow differentiating between psychiatric disorders. 21 samples, consisting of 3 replicates harvested at 7 different time-points of RA+BDNF-induced neuronal differentiation
2016-06-01 | E-GEOD-69838 | biostudies-arrayexpress