Chromatin interactions at risk loci links ATP5MD to schizophrenia
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE171077 | GEO | 2021/03/30
REPOSITORIES: GEO
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Project description:Background Chromosome 16p11.2 is one of the most significant loci in the genome-wide association study (GWAS) of schizophrenia. Despite several integrative analyses and functional genomics studies have been carried out to identify possible risk genes, their impacts in the pathogenesis of schizophrenia remain to be fully characterized. Methods We performed expression quantitative trait loci (eQTL) and summary-data-based Mendelian randomization (SMR) analyses to identify schizophrenia risk genes in the 16p11.2 GWAS locus. We constructed the murine model with dysregulated expression of risk gene in the medial prefrontal cortex (mPFC) using stereotaxic injection of Adeno-associated Virus (AAV), followed by behavioral assessments, dendritic spine analyses and RNA sequencing. Findings We identified significant associations between elevated INO80E mRNA expression in frontal cortex and risk of schizophrenia. The mice overexpressing Ino80e in mPFC (Ino80e-OE) exhibited schizophrenia-like behaviors, including increased anxiety behavior, anhedonia, and impaired prepulse inhibition (PPI) when compared with control group. The neuronal sparse labeling assay showed that the density of mushroom spines in the pyramidal neurons of mPFC was significantly decreased in Ino80e-OE mice compared with control mice, accompanied by a notable increase in the density of stubby spines. Transcriptomic analysis in the mPFC revealed significant alterations in the mRNA levels of schizophrenia-related genes and processes related to synapses upon overexpressing Ino80e . Interpretation Our results suggest that upregulation of the Ino80e gene in mPFC may induce schizophrenia-like behaviors in mice, further supporting the hypothesis that INO80E is an authentic risk gene.
2024-10-01 | GSE276239 | GEO
Project description:Genome-wide association study (GWAS) was performed in 120 patient-parents trio samples from Japanese schizophrenia pedigrees ABSTRACT: Schizophrenia is a devastating neuropsychiatric disorder with genetically complex traits. Genetic variants should explain a considerable portion of the risk for schizophrenia, and genome-wide association study (GWAS) is a potentially powerful tool for identifying the risk variants that underlie the disease. Here, we report the results of a three-stage analysis of three independent cohorts consisting of a total of 2,535 samples from Japanese and Chinese populations for searching schizophrenia susceptibility genes using a GWAS approach. Firstly, we examined 115,770 single nucleotide polymorphisms (SNPs) in 120 patient-parents trio samples from Japanese schizophrenia pedigrees. In stage II, we evaluated 1,632 SNPs (1,159 SNPs of p < 0.01 and 473 SNPs of p < 0.05 that located in previously reported linkage regions). The second sample consisted of 1,012 case-control samples of Japanese origin. The most significant p value was obtained for the SNP in the ELAVL2 [(embryonic lethal, abnormal vision, Drosophila)-like 2] gene located on 9p21.3 (p = 0.00087). In stage III, we scrutinized the ELAVL2 gene by genotyping gene-centric tagSNPs in the third sample set of 293 family samples (1,163 individuals) of Chinese descent and the SNP in the gene showed a nominal association with schizophrenia in Chinese population (p = 0.026). The current data in Asian population would be helpful for deciphering ethnic diversity of schizophrenia etiology. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from peripheral blood samples. SUPPLEMENTARY FILES: CEL files were processed by manufacture's protocol. Genotype data were analyzed with the GeneSpring GT (Varia) 2.0 software package developed by Agilent Technologies (Santa Clara, CA). Matrix tables for the Genetic programs were produced (Linkage format: http://bioinformatics.med.utah.edu/~alun/software/docs/linkage.html) File 1: Matrix file_SNP_Map.txt File 2: Matrix file_Family_Information.txt File 3: Matrix file_Pedigree_Format.txt (Genotyping data of Linkage format) Transmission disequilibrium test was performed using the R program (http://www.r-project.org). File 4: Matrix file_results.txt
2011-06-13 | E-GEOD-27923 | biostudies-arrayexpress
Project description:Genome-wide association study (GWAS) was performed in 120 patient-parents trio samples from Japanese schizophrenia pedigrees ABSTRACT: Schizophrenia is a devastating neuropsychiatric disorder with genetically complex traits. Genetic variants should explain a considerable portion of the risk for schizophrenia, and genome-wide association study (GWAS) is a potentially powerful tool for identifying the risk variants that underlie the disease. Here, we report the results of a three-stage analysis of three independent cohorts consisting of a total of 2,535 samples from Japanese and Chinese populations for searching schizophrenia susceptibility genes using a GWAS approach. Firstly, we examined 115,770 single nucleotide polymorphisms (SNPs) in 120 patient-parents trio samples from Japanese schizophrenia pedigrees. In stage II, we evaluated 1,632 SNPs (1,159 SNPs of p < 0.01 and 473 SNPs of p < 0.05 that located in previously reported linkage regions). The second sample consisted of 1,012 case-control samples of Japanese origin. The most significant p value was obtained for the SNP in the ELAVL2 [(embryonic lethal, abnormal vision, Drosophila)-like 2] gene located on 9p21.3 (p = 0.00087). In stage III, we scrutinized the ELAVL2 gene by genotyping gene-centric tagSNPs in the third sample set of 293 family samples (1,163 individuals) of Chinese descent and the SNP in the gene showed a nominal association with schizophrenia in Chinese population (p = 0.026). The current data in Asian population would be helpful for deciphering ethnic diversity of schizophrenia etiology.
2011-06-13 | GSE27923 | 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
Project description:Background: Autism spectrum disorder (ASD) is a severe early onset neurodevelopmental disorder with high heritability but significant heterogeneity. Traditional genome-wide approaches to test for association of common variants with autism susceptibility risk has met with limited success. However, novel methods to identify moderate risk alleles in attainable sample sizes are now gaining momentum. Methods:M-BM- In this study, we utilized publically available GWAS data from the Autism Genome Project (AGP) and annotated the results (p < 0.001) for eQTLs present in the parietal lobe, cerebellum, and lymphoblastoid cell lines. We then performed a test of enrichment by comparing these results to simulated data conditioned on minor allele frequency in order to generate an empirical p-value indicating statistically significant enrichment of eQTLs in top results from the autism GWAS. Results:M-BM- Our findings show a global enrichment of brain eQTLs, but not LCL eQTLs, among top SNPs from an autism GWAS. Additionally, the data implicates individual genesM-BM- SLC25A12,M-BM- PANX1M-BM- andM-BM- PANX2, as well as pathways previously implicated in autism. Conclusions:M-BM- These findings provide supportive rationale for the use of annotation-based approaches to GWAS. We use microarray technology to understand the etiology and pathology of psychiatric diseases at the transcriptomic level. Postmortem human brain samples came from the Stanley Medical Research InstituteM-bM-^@M-^Ys Neuropathology Consortium and Array collections, including schizophrenia, bipolar disorder and control samples.
2012-12-31 | E-GEOD-35974 | biostudies-arrayexpress
Project description:Background: Autism spectrum disorder (ASD) is a severe early onset neurodevelopmental disorder with high heritability but significant heterogeneity. Traditional genome-wide approaches to test for association of common variants with autism susceptibility risk has met with limited success. However, novel methods to identify moderate risk alleles in attainable sample sizes are now gaining momentum. Methods:M-BM- In this study, we utilized publically available GWAS data from the Autism Genome Project (AGP) and annotated the results (p < 0.001) for eQTLs present in the parietal lobe, cerebellum, and lymphoblastoid cell lines. We then performed a test of enrichment by comparing these results to simulated data conditioned on minor allele frequency in order to generate an empirical p-value indicating statistically significant enrichment of eQTLs in top results from the autism GWAS. Results:M-BM- Our findings show a global enrichment of brain eQTLs, but not LCL eQTLs, among top SNPs from an autism GWAS. Additionally, the data implicates individual genesM-BM- SLC25A12,M-BM- PANX1M-BM- andM-BM- PANX2, as well as pathways previously implicated in autism. Conclusions:M-BM- These findings provide supportive rationale for the use of annotation-based approaches to GWAS. We use microarray technology to understand the etiology and pathology of psychiatric diseases at the transcriptomic level. Postmortem human brain samples came from the Stanley Medical Research InstituteM-bM-^@M-^Ys Neuropathology Consortium and Array collections, including schizophrenia, bipolar disorder and control samples.
2012-12-31 | E-GEOD-35977 | biostudies-arrayexpress
Project description:Genome-wide association studies (GWAS) have identified multiple lung cancer risk loci including those that are distinct in the major histological types. However, most of these loci have not been functionally characterized. Here we employed massively parallel reporter assays (MPRA) to assess allelic transcriptional activity of risk-associated variants en masse. We tested 2,245 variants in 42 loci from 3 recent GWASs of East Asian and European populations in the context of lung adenocarcinoma and squamous cell carcinoma cells while incorporating exposure to a tobacco-smoke carcinogen, benzo[a]pyrene. At FDR < 0.01, we identified 844 MPRA-significant variants with allelic transcriptional activity across 88% of lung cancer loci. Further variant scoring using lung-specific epigenomic annotation demonstrated that 63% of the loci harbored multiple equally functional variants in linkage disequilibrium. Cell-type-specific variants were observed in 72% of the loci, a subset of which aligned with histology-specific association in the GWAS. Distinct subsets of transcription factors were predicted to bind to cell-type-specific variants and those affecting multiple GWAS loci in trans. Linking MPRA-significant variants to target genes based on four different approaches identified candidate susceptibility genes including essential genes for lung cancer cell growth. CRISPR-interference of a high-scoring MPRA-significant variant validated multiple variant-gene connections from different datasets, including RTEL1, SOX18, and ARFRP1. Our data provide a comprehensive catalog of functional characterization of lung cancer GWAS loci and the molecular basis of heterogeneity and polygenicity of lung cancer susceptibility.
2024-05-16 | GSE245699 | GEO
Project description:More than 200 asthma-associated genetic variants have been identified in genome-wide association studies (GWASs). Expression quantitative trait loci (eQTL) data resources can help identify causal genes of the GWAS signals, but it can be difficult to find an eQTL that reflects the disease state because most eQTL data are obtained from normal healthy subjects. We performed a blood eQTL analysis using transcriptomic and genotypic data from 436 Korean asthma patients. To identify asthma-related genes, we carried out colocalization and Summary-based Mendelian Randomization (SMR) analysis using the results of asthma GWASs and eQTL data. In addition, we compared the results of disease eQTL data and asthma-related genes with two normal blood eQTL data from Genotype-Tissue Expression (GTEx) project and a Japanese study. We identified 342,054 cis-eQTL and 2,931 eGenes from asthmatic eQTL analysis. We compared the disease eQTL results with GTEx and a Japanese study and found that 63.2 % of the 2,931 eGenes overlapped with the GTEx eGenes and 38.5 % with the Japanese eGenes. Following the integrated analysis of the asthmatic eQTL data with asthma GWASs, using colocalization and SMR methods, we identified 13 asthma-related genes specific to the Korean asthmatic eQTL data. We provided Korean asthmatic cis-eQTL data and identified asthma-related genes by integrating them with GWAS data. In addition, we suggested these asthma-related genes as therapeutic targets for asthma. We envisage that our findings will contribute to understanding the etiological mechanisms of asthma and provide novel therapeutic targets.
2023-03-08 | GSE226825 | GEO
Project description:DNA methylation (DNAm) is important in brain development, and potentially in schizophrenia. We characterized DNAm in prefrontal cortex from 335 non-psychiatric controls across the lifespan and 191 patients with schizophrenia, and identified widespread changes in the transition from prenatal to postnatal life. These DNAm changes manifest in the transcriptome, correlate strongly with a shifting cellular landscape, and overlap regions of genetic risk for schizophrenia. A quarter of published GWAS-suggestive loci (4,208/15,930, p<10-20) manifest as significant methylation quantitative trait loci (meQTLs), including 59.6% of GWAS-positive schizophrenia loci. We identified 2,104 CpGs that differ between schizophrenia patients and controls, enriched for genes related to development and neurodifferentiation. The schizophrenia-associated CpGs strongly correlate with changes related to the prenatal-postnatal transition and show slight enrichment for GWAS risk loci, while not corresponding to CpGs differentiating adolescence from later adult life. These data implicate an epigenetic component to the developmental origins of this disorder.
2015-10-21 | GSE74193 | GEO
Project description:The most recent genome-wide association study (GWAS) of cutaneous melanoma identified 54 risk-associated loci, but functional variants and their target genes for most have not been established. Here, we performed massively parallel reporter assays (MPRA) using malignant melanoma and normal melanocyte cells and further integrated multi-layer annotation to systematically prioritize functional variants and susceptibility genes from these GWAS loci. Of 1,992 risk-associated variants tested in MPRA, we identified 285 from 42 loci (78% of the known loci) displaying significant allelic transcriptional activities in either cell type (FDR < 1%). We further characterized MPRA-significant variants by motif prediction, epigenomic annotation, and statistical/functional fine-mapping to create integrative variant scores, which prioritized one to six plausible candidate variants per locus for the 42 loci and nominated a single variant for 43% of these loci. Overlaying the MPRA-significant variants with genome-wide significant expression or methylation quantitative trait loci (QTLs) from melanocytes or melanomas identified candidate susceptibility genes for 60% of variants (172 of 285 variants). CRISPRi of top-scoring variants validated their cis-regulatory effect on the eQTL target genes, MAFF (22q13.1) and GPRC5A (12p13.1). Finally, we identified 36 melanoma-specific and 45 melanocyte-specific MPRA-significant variants, a subset of which are linked to cell-type-specific target genes. Analyses of transcription factor availability in MPRA datasets and variant-transcription factor interaction in eQTL datasets highlighted the roles of transcription factors in cell-type-specific variant functionality. In conclusion, MPRA along with variant scoring effectively prioritized plausible candidates for most melanoma GWAS loci and highlighted cellular contexts where the susceptibility variants are functional.
2022-11-28 | GSE210355 | GEO