Homo sapiens
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PROVIDER: PRJNA564405 | ENA |
REPOSITORIES: ENA
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Project description:Genome-wide association studies (GWAS) have identified genomic loci associated with complex diseases but mechanistic insights are impeded by the lack of understanding of how specific risk variants functionally contribute to diseases. Here we describe an experimental strategy to robustly identify cis-acting effects of genetic variants in regulatory elements on gene expression by combining genome-wide epigenetic information with CRISPR/Cas genome editing in human pluripotent cells. Using this genetically controlled system, we identify a common Parkinson’s disease (PD)-associated risk variant in a non-coding distal enhancer element that regulates the expression of SNCA, a key gene implicated in the pathogenesis of PD. We provide data suggesting that the transcriptional deregulation of SNCA is associated with sequence-dependent binding of the brain-specific transcription factors EMX2 and NKX6-1. Our work provides a general experimental strategy to functionally connect genetic variation with disease relevant phenotypes.
2016-04-20 | GSE71278 | GEO
Project description:Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with disease. To facilitate moving from associations to disease mechanisms, we leveraged the role of pathogens in shaping human evolution with the Hi-HOST Phenome Project (H2P2): a catalog of cellular GWAS comprised of 79 phenotypes in response to 8 pathogens in 528 lymphoblastoid cell lines. Seventeen loci surpass genome-wide significance (p<5x10-8) for phenotypes ranging from pathogen replication to cytokine production. Combining H2P2 with clinical association data on 83,717 patients from the eMERGE Network and experimental validation revealed evidence for mechanisms and connections with diseases. We identified a SNP near CXCL10 as a cis-cytokine-QTL and risk factor for inflammatory bowel disease. A SNP in ZBTB20 demonstrated pleiotropy, likely through suppression of multiple target genes, and was associated with viral hepatitis. Data are in an H2P2 web portal to facilitate interpreting human genome variation through the lens of cell biology.
2018-07-26 | GSE116172 | 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:Monozygotic (MZ) twin pair discordance for childhood-onset Type 1 Diabetes (T1D) is ~50%, implicating roles for genetic and non-genetic factors in the aetiology of this complex autoimmune disease. Although significant progress has been made in elucidating the genetics of T1D in recent years, the non-genetic component has remained poorly defined. We hypothesized that epigenetic variation could underlie some of the non-genetic component of T1D aetiology and, thus, performed an epigenome-wide association study (EWAS) for this disease. We generated genome-wide DNA methylation profiles of purified CD14+ monocytes (an immune effector cell type relevant to T1D pathogenesis) from 15 T1D-discordant MZ twin pairs. This identified 132 different CpG sites at which the direction of the intra-MZ pair DNA methylation difference significantly correlated with the diabetic state, i.e. T1D-associated methylation variable positions (T1D-MVPs). We confirmed these T1D-MVPs display statistically significant intra-MZ pair DNA methylation differences in the expected direction in an independent set of T1D-discordant MZ pairs (P = 0.035). Then, to establish the temporal origins of the T1D-MVPs, we generated two further genome-wide datasets and established that, when compared with controls, T1D-MVPs are enriched in singletons both before (P = 0.001) and at (P = 0.015) disease diagnosis, and also in singletons positive for diabetes-associated autoantibodies but disease-free even after 12 years follow-up (P = 0.0023). Combined, these results suggest that T1D-MVPs arise very early in the etiological process that leads to overt T1D. Our EWAS of T1D represents an important contribution toward understanding the etiological role of epigenetic variation in type 1 diabetes, and it is also the first systematic analysis of the temporal origins of disease-associated epigenetic variation for any human complex disease. Bisulphite converted DNA from the 100 samples were hybridised to the Illumina Infinium 27k Human Methylation Beadchip v1.2
2014-04-09 | E-GEOD-56606 | biostudies-arrayexpress
Project description:Heritable epigenetic factors can contribute to complex disease etiology. In this study we examine, on a global scale, the contribution of DNA methylation to complex traits that are precursors to heart disease, diabetes and osteoporosis. We profiled DNA methylation patterns in the liver using bisulfite sequencing in 90 mouse inbred strains, genome-wide expression levels, proteomics, metabolomics and sixty-eight clinical traits, and performed epigenome-wide association studies (EWAS). We found associations with numerous clinical traits including bone mineral density, plasma cholesterol, insulin resistance, gene expression, protein and metabolite levels. A large proportion of associations were unique to EWAS and were not identified using GWAS. Methylation levels were regulated by genetics largely in cis, but we also found evidence of trans regulation, and we demonstrate that genetic variation in the methionine synthase reductase gene Mtrr affects methylation of hundreds of CpGs throughout the genome. Our results indicate that natural variation in methylation levels contributes to the etiology of complex clinical traits. Reduced representation bisulfite sequencing in mouse strains using liver genomic DNA
2015-04-02 | E-GEOD-67507 | biostudies-arrayexpress
Project description:There is increasing evidence that interindividual epigenetic variation is an etiological factor in common human diseases. Such epigenetic variation could be genetic or non-genetic in origin, and epigenome-wide association studies (EWASs) are underway for a wide variety of diseases/phenotypes. However, performing an EWAS is associated with a range of issues not typically encountered in genome-wide association studies (GWASs), such as the tissue to be analyzed. In many EWASs, it is not possible to analyze the target tissue in large numbers of live humans, and consequently surrogate tissues are employed, most commonly blood. But there is as yet no evidence demonstrating that blood is more informative than buccal cells, the other easily accessible tissue. To assess the potential of buccal cells for use in EWASs, we performed a comprehensive analysis of a buccal cell methylome using whole-genome bisulfite sequencing. Strikingly, a buccal vs. blood comparison reveals >6X as many hypomethylated regions in buccal. These tissue-specific differentially methylated regions (tDMRs) are strongly enriched for DNaseI hotspots. Almost 75% of these tDMRs are not captured by commonly used DNA methylome profiling platforms such as Reduced Representational Bisulfite Sequencing and the Illumina Infinium HumanMethylation450 BeadChip, and they also display distinct genomic properties. Buccal hypo-tDMRs show a statistically significant enrichment near SNPs associated to disease identified through GWASs. Finally, we find that, compared with blood, buccal hypo-tDMRs show significantly greater overlap with hypomethylated regions in other tissues. We propose that for non-blood based diseases/phenotypes, buccal will be a more informative tissue for EWASs. Bisulphite converted DNA from the 22 samples were hybridised to the Illumina Infinium 450k Human Methylation Beadchip
2013-03-28 | E-GEOD-45529 | biostudies-arrayexpress
Project description:There is increasing evidence that interindividual epigenetic variation is an etiological factor in common human diseases. Such epigenetic variation could be genetic or non-genetic in origin, and epigenome-wide association studies (EWASs) are underway for a wide variety of diseases/phenotypes. However, performing an EWAS is associated with a range of issues not typically encountered in genome-wide association studies (GWASs), such as the tissue to be analyzed. In many EWASs, it is not possible to analyze the target tissue in large numbers of live humans, and consequently surrogate tissues are employed, most commonly blood. But there is as yet no evidence demonstrating that blood is more informative than buccal cells, the other easily accessible tissue. To assess the potential of buccal cells for use in EWASs, we performed a comprehensive analysis of a buccal cell methylome using whole-genome bisulfite sequencing. Strikingly, a buccal vs. blood comparison reveals >6X as many hypomethylated regions in buccal. These tissue-specific differentially methylated regions (tDMRs) are strongly enriched for DNaseI hotspots. Almost 75% of these tDMRs are not captured by commonly used DNA methylome profiling platforms such as Reduced Representational Bisulfite Sequencing and the Illumina Infinium HumanMethylation450 BeadChip, and they also display distinct genomic properties. Buccal hypo-tDMRs show a statistically significant enrichment near SNPs associated to disease identified through GWASs. Finally, we find that, compared with blood, buccal hypo-tDMRs show significantly greater overlap with hypomethylated regions in other tissues. We propose that for non-blood based diseases/phenotypes, buccal will be a more informative tissue for EWASs. Buccal Profile generated from 14 Buccal Individuals
2013-05-02 | E-GEOD-46572 | biostudies-arrayexpress
Project description:There is increasing evidence that interindividual epigenetic variation is an etiological factor in common human diseases. Such epigenetic variation could be genetic or non-genetic in origin, and epigenome-wide association studies (EWASs) are underway for a wide variety of diseases/phenotypes. However, performing an EWAS is associated with a range of issues not typically encountered in genome-wide association studies (GWASs), such as the tissue to be analyzed. In many EWASs, it is not possible to analyze the target tissue in large numbers of live humans, and consequently surrogate tissues are employed, most commonly blood. But there is as yet no evidence demonstrating that blood is more informative than buccal cells, the other easily accessible tissue. To assess the potential of buccal cells for use in EWASs, we performed a comprehensive analysis of a buccal cell methylome using whole-genome bisulfite sequencing. Strikingly, a buccal vs. blood comparison reveals >6X as many hypomethylated regions in buccal. These tissue-specific differentially methylated regions (tDMRs) are strongly enriched for DNaseI hotspots. Almost 75% of these tDMRs are not captured by commonly used DNA methylome profiling platforms such as Reduced Representational Bisulfite Sequencing and the Illumina Infinium HumanMethylation450 BeadChip, and they also display distinct genomic properties. Buccal hypo-tDMRs show a statistically significant enrichment near SNPs associated to disease identified through GWASs. Finally, we find that, compared with blood, buccal hypo-tDMRs show significantly greater overlap with hypomethylated regions in other tissues. We propose that for non-blood based diseases/phenotypes, buccal will be a more informative tissue for EWASs. Bisulphite converted DNA from the 22 samples were hybridised to the Illumina Infinium 450k Human Methylation Beadchip
2013-05-02 | E-GEOD-46573 | 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:Deciphering the impact of genetic variation on gene regulation is fundamental to understanding common, complex human diseases. In this study, we obtained genome-wide RNA-Seq and ChIP-Seq (for H3K4me3 and H3K27ac histone modifications) data in the human liver. We mapped quantitative trait loci (QTLs) of gene expression levels and histone modification states. We integrated our findings with summary statistics of genome-wide association studies (GWAS) and identified candidate genes, gene regulatory regions, and variants in GWAS loci.
2019-06-13 | GSE128072 | GEO