A role for non-coding variation in schizophrenia
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Panos Roussos
PROVIDER: E-GEOD-62391 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
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.
2014-10-17 | GSE62391 | GEO
Project description:Hsu Y, Nacu E, Liu R, Kim A, Tsafou K, Petrossian N, Crotty W, Suh JM, Pintacuda G, Riseman J, Martin J, Malolepsza E, Li T, Singh T, Ge T, Egri SB, Tanenbaum B, Stanclift CR, Apffel AM, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Stanley Global Asia Initiatives, Carr SA, Schenone M, Jaffe J, Fornelos N, Huang H, Eggan KC, Lage K. 2021. Genetics have nominated many schizophrenia risk genes that lack functional interpretation. To empower such interpretation, we executed interaction proteomics for six risk genes in human induced neurons and found the resulting protein network to be enriched for common variant risk of schizophrenia in Europeans and East Asians. The network is down-regulated in layer 5/6 cortical neurons of patients and can complement fine-mapping and eQTL data to prioritize additional genes in GWAS loci. A sub-network centered on HCN1 is enriched for common variant risk and also contains proteins (HCN4 and AKAP11) enriched for rare protein-truncating mutations in patients with schizophrenia and bipolar disease. Our findings establish brain cell-type-specific interactomes as an organizing framework to facilitate interpretation of genetic and transcriptomic data in schizophrenia and psychiatric diseases.
2021-05-25 | MSV000087514 | MassIVE
Project description:Background: Genome-wide association studies (GWAS) have reported hundreds of genomic loci associated with schizophrenia, yet identifying the functional risk variations is a key step in elucidating the underlying mechanisms. Methods: We applied multiple bioinformatics and molecular approaches, including expression quantitative trait loci (eQTL) analyses, epigenome signature identification, luciferase reporter assay, chromatin conformation capture (3C), homology-directed genome editing by CRISPR/Cas9, RNA-sequencing (RNA-Seq) and assay for transposase-accessible chromatin using sequencing (ATAC-Seq). Results: We found that the schizophrenia GWAS risk variations at 16p11.2 were significantly associated with mRNA levels of multiple genes in human brain, and one of the leading eQTL genes, MAPK3, located ~200-kb away from these risk variations in the genome. Further analyses based on the epigenome marks in human brain and cell lines suggested that a noncoding single nucleotide polymorphism (SNP) rs4420550 (p=2.36×10–9 in schizophrenia GWAS) was within a DNA enhancer region, which was validated via in vitro luciferase reporter assays. The 3C experiment showed that the rs4420550 region physically interacted with the MAPK3 promoter and TAOK2 promoter. Precise CRISPR/Cas9 editing of single base pair in cells followed by RNA-Seq further confirmed the regulatory effects of rs4420550 on the transcription of 16p11.2 genes, and ATAC-Seq demonstrated that rs4420550 affected chromatin accessibility at the 16p11.2 region. The rs4420550-[A/A] cells showed significantly higher proliferation rates compared with rs4420550-[G/G] cells. Conclusions: These results together suggest that rs4420550 is a functional risk variation, and this study illustrates an example of comprehensive functional characterization of schizophrenia GWAS risk loci.
2020-10-01 | GSE152177 | GEO
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:Nonsyndromic cleft lip with or without palate (NSCL/P) are common birth defects of complex etiology. Multiple interacting loci with possible additional environment factors influence the risk for NSCL/P. 12 single nucleotide polymorphisms (SNPs) in 7 candidate genes were tested using an allele-specific primer extension for both case-control and case-parents analyses in northeast China (236 unrelated patients, 185 mothers and 154 fathers, including 128 complete trios, 400 control individuals). TGFA and IRF6 genes showed a significant associations with NSCL/P. For IRF6, statistical evidence of association between rs2235371 (P=0.003), rs2013162 (P=0.000) and NSCL/P was found in case-control analyses. The Family Based Association Tests (FBAT) showed an over-transmission for C allele of rs2235371 polymorphic (p=0.007). For TGFA, associations between rs3771494, rs3771523 (G3822A), rs11466285 (T3851C) and NSCL/P could be observed both in case-control and FBAT analyses. However, we found no associations between other genes (BCL3, TGFB3, MTHFR1, PVRL1 and SUMO1) and NSCL/P. In the study present, 236 unrelated patient with NSCL/P addition with 185 mothers and 154 fathers and 400 control individuals were tested with the allele special primer extension microarray.
2013-04-09 | E-GEOD-45770 | biostudies-arrayexpress
Project description:Genome-wide association studies (GWAS) have identified 19 risk variants associated with colorectal cancer. As most of these risk variants reside outside the coding regions of genes, we conducted cis-expression quantitative trait loci (cis-eQTL) analyses to investigate possible regulatory functions on the expression of neighboring genes. Forty microsatellite stable and CpG island methylator phenotype-negative colorectal tumors and paired adjacent-normal colon tissues were used for genome-wide SNP and gene expression profiling in our cis-eQTL analyses. This submission represents transcriptome component of study.
2012-01-31 | E-GEOD-31737 | 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: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: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