Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA162407 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Genome-wide association studies have identified a small region at chromosome 9p21.3 strongly associated with coronary heart disease risk. The region contains no protein-coding genes and the mechanism underlying its association with heart disease is unknown. We investigated associations between rs1333049, a single nucleotide polymorphism representing the 9p21.3 locus, and levels of cardiac gene expression in myocardial tissue from donors with no documented history of heart disease. Individual myocardial gene expression profiles were generated with Affymetrix Human Gene 1.0 ST arrays (n=108). DNA genotyping was performed with Taqman assays. Associations between genotype and gene expression were analyzed assuming a recessive effect.
2012-07-03 | E-GEOD-22253 | biostudies-arrayexpress
Project description:To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five new histotype-specific EOC risk regions (P-value < 5 x 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (P-value < 10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue data sets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (FDR < 0.05). Finally, by integrating genome-wide HiChIP interactome analysis with TWAS, variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8 and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by GWAS.
2024-03-27 | GSE255142 | GEO
Project description:Genome-wide association studies have identified a small region at chromosome 9p21.3 strongly associated with coronary heart disease risk. The region contains no protein-coding genes and the mechanism underlying its association with heart disease is unknown. We investigated associations between rs1333049, a single nucleotide polymorphism representing the 9p21.3 locus, and levels of cardiac gene expression in myocardial tissue from donors with no documented history of heart disease.
2012-07-04 | GSE22253 | GEO
Project description:Recent genome-wide association studies have identified single nucleotide polymorphisms (SNPs) at 7 loci influencing multiple myeloma (MM) risk. We generated expression quantitative trait loci (eQTL) data on malignant plasma cells from two patient series (totaling 848) to fine map the risk loci associations and gain insight into their functional basis. At 7p11.2 the strongest association with MM risk is provided by rs4487645, which is associated with allele–specific cis-regulation of the MYC-interacting gene CDCA7L (P=4.1x10-25). These data are compatible with increased expression of CDCA7L being the functional basis of the 7p11.2 association exerting its effects through an extended pathway involving IRF4 and MYC. Note: This dataset re-uses files from ArrayExpress accessions E-TABM-937, E-MTAB-362, E-MTAB-372.
2014-12-09 | E-MTAB-2299 | biostudies-arrayexpress
Project description:Accumulating evidence suggests a relationship between endometrial cancer and epithelial ovarian cancer. For example, endometrial cancer and epithelial ovarian cancer share epidemiological risk factors and molecular features observed across histotypes are held in common (e.g. serous, endometrioid and clear cell). Independent genome-wide association studies (GWAS) for endometrial cancer and epithelial ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. Using GWAS summary statistics, we explored the shared genetic etiology between endometrial cancer and epithelial ovarian cancer. Genetic correlation analysis using LD Score regression revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10-5). To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e. inverse-variance meta-analysis, co-localization, and M-values), and performed analyses by stratified by subtype. We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10-9). In addition, four novel regions at 7p22.2, 7q22.1, 9p12 and 11q13.3 were identified at a sub-genome wide threshold (P < 5 × 10-7). Integration with promoter-associated HiChIP chromatin loops from immortalized endometrium and epithelial ovarian cell lines, and expression quantitative trait loci (eQTL) data highlighted candidate target genes for further investigation.
2020-07-30 | GSE155328 | GEO
Project description:Endometriosis is associated with increased risk of epithelial ovarian cancers (EOCs). Using data from large endometriosis and EOC genome-wide association meta-analyses we estimate the genetic correlation and evaluate the causal relationship between genetic liability to endometriosis and EOC histotypes, and identify shared susceptibility loci. We estimate a significant genetic correlation (rg) between endometriosis and clear cell (rg=0.71), endometrioid (rg=0.48) and high-grade serous (rg=0.19) ovarian cancer, associations supported by Mendelian randomization analyses. Bivariate meta-analysis identify 28 loci associated with both endometriosis and EOC, including 19 with evidence for a shared underlying association signal. Differences in the shared risk suggest different underlying pathways may contribute to the relationship between endometriosis and the different histotypes. Functional annotation using transcriptomic and epigenomic profiles of relevant tissues/cells highlights several target genes. This comprehensive analysis reveals profound genetic overlap between endometriosis and EOC histotypes with valuable genomic targets for understanding the biological mechanisms linking the diseases.
2022-03-07 | GSE197928 | GEO
Project description:Background: The mechanisms of how genetic variants (SNPs) identified in genome-wide association studies act to influence body mass remain unknown for most of these SNPs, which continue to puzzle the scientific community. Recent evidence points to epigenetic and chromatin state of the genome to have an important role. Methods: 355 healthy young individuals were genotyped for 52 known obesity-associated SNPs and we obtained DNA methylation levels in their blood using the Illumina 450K BeadChip. Associations between alleles and methylation at proximal cytosine residues were tested using a linear model adjusted for age, sex, weight category and a proxy for blood cell type counts. For replication in other tissues, we used two open-access datasets (skin fibroblasts, n=62; four brain regions, n=121-133) and an additional dataset in subcutaneous and visceral fat (n=149). Results: We found that alleles at 28 of these obesity-associated SNPs associate with methylation levels at 107 proximal CpG sites. Out of 107 CpG sites, 38 are located in gene promoters, including genes strongly implicated in obesity (MIR148A, BDNF, PTPMT1, NR1H3, MGAT1, SCGB3A1, HOXC12, PMAIP1, PSIP1, RPS10-NUDT3, RPS10, SKOR1, MAP2K5, SIX5, AGRN, IMMP1L, ELP4, ITIH4, SEMA3G, POMC, ADCY3, SSPN, LGR4, TUFM, MIR4721, SULT1A1, SULT1A2, APOBR, CLN3, SPNS1,SH2B1, ATXN2L, and IL27). Interestingly, the associated SNPs are in known eQTLs for some of these genes. We also found that the 107 CpGs are enriched in enhancers in peripheral blood mononuclear cells. Finally, our results indicate that some of these associations are not be blood-specific as we successfully replicated four associations in skin fibroblasts. Conclusions: Our results strongly suggest that many obesity-associated SNPs are associated with proximal gene regulation, which was reflected by association of obesity risk allele genotypes with differential DNA methylation. This study highlights the importance of DNA methylation and other chromatin marks as a way to understand the molecular basis of genetic variants associated to human diseases and traits. Bisulphite converted DNA from 355 individuals aged 14-34 were hybridised to the Illumina Infinium 450k Human Methylation Beadchip.
2015-09-17 | E-GEOD-73103 | biostudies-arrayexpress
Project description:Hormone-dependent cancers (HDCs) share several risk factors, suggesting a common aetiology. Using data from genome-wide association studies, we showed spatial clustering of risk variants across four HDCs (breast, endometrial, ovarian and prostate cancers), contrasting with genetically uncorrelated traits. We identified 44 multi-HDC risk regions across the genome, defined as overlapping risk regions for at least two HDCs: two regions contained risk variants for all four HDCs, 13 for three HDCs and 28 for two HDCs. Integrating GWAS data, epigenomic profiling and promoter capture HiC maps from diverse cell line models, we annotated 53 candidate risk genes at 22 multi-HDC risk regions. These targets were enriched for established genes from the COSMIC Cancer Gene Census, but many had no previously reported pleiotropic roles. Additionally, we pinpointed lncRNAs as potential HDC targets and identified risk alleles in several regions that altered transcription factors motifs, suggesting regulatory mechanisms. Known drug targets were over-represented among the candidate multi-HDC risk genes, implying that some may serve as targets for therapeutic development or facilitate the repurposing of existing treatments for HDC. Our comprehensive approach provides a framework for identifying common target genes driving complex traits and enhances understanding of HDC susceptibility.
2024-11-10 | GSE278254 | GEO
Project description:Lung adenocarcinoma (LUAD) is the most common type of lung cancer. A recent genome-wide association study (GWAS) of LUAD in East Asia reported 28 independent susceptibility variants across 25 loci and identified 2 genes whose genetically predicted expression levels are associated with LUAD risk, using an ancestry-matched lung tissue expression quantitative trait loci (eQTL) dataset. It is desirable to identify additional susceptibility loci and to understand their underlying biological mechanisms. Using an expanded GWAS of LUAD in East Asia and ancestry-matched lung tissue eQTL and DNA methylation QTL datasets, we performed transcriptome-wide association studies and DNA methylome-wide association studies simultaneously and examined the association between measured expression of genes and DNA methylation of nearby CpGs (eQTM). Genes and nearby CpGs are termed CpG–gene–LUAD trios if these three associations hold simultaneously. At Bonferroni-corrected P<0.05, we identified a new susceptibility locus (6p21.31; lead SNP rs7772643), 10 LUAD-associated genes and 86 LUAD-associated CpGs. At false discovery rate q<0.05, we identified 28 LUAD-associated genes, 220 LUAD-associated CpGs, and 45 CpG–gene–LUAD trios; among them, 43 were direction-matched regarding these three associations. These show that 23 of the known 28 susceptibility variants for LUAD in East Asia are near these genes or CpGs and MARCH3, ELF5, IKZF3, GSDMB, CCDC116, and DSP are putative novel susceptibility loci. Few of them was reported in LUAD in European populations. This study substantially advances our understanding of the etiology of LUAD in East Asia and could be useful in developing translational applications.
2026-02-04 | GSE314841 | GEO
Project description:Lung adenocarcinoma (LUAD) is the most common type of lung cancer. A recent genome-wide association study (GWAS) of LUAD in East Asia reported 28 independent susceptibility variants across 25 loci and identified 2 genes whose genetically predicted expression levels are associated with LUAD risk, using an ancestry-matched lung tissue expression quantitative trait loci (eQTL) dataset. It is desirable to identify additional susceptibility loci and to understand their underlying biological mechanisms. Using an expanded GWAS of LUAD in East Asia and ancestry-matched lung tissue eQTL and DNA methylation QTL datasets, we performed transcriptome-wide association studies and DNA methylome-wide association studies simultaneously and examined the association between measured expression of genes and DNA methylation of nearby CpGs (eQTM). Genes and nearby CpGs are termed CpG–gene–LUAD trios if these three associations hold simultaneously. At Bonferroni-corrected P<0.05, we identified a new susceptibility locus (6p21.31; lead SNP rs7772643), 10 LUAD-associated genes and 86 LUAD-associated CpGs. At false discovery rate q<0.05, we identified 28 LUAD-associated genes, 220 LUAD-associated CpGs, and 45 CpG–gene–LUAD trios; among them, 43 were direction-matched regarding these three associations. These show that 23 of the known 28 susceptibility variants for LUAD in East Asia are near these genes or CpGs and MARCH3, ELF5, IKZF3, GSDMB, CCDC116, and DSP are putative novel susceptibility loci. Few of them was reported in LUAD in European populations. This study substantially advances our understanding of the etiology of LUAD in East Asia and could be useful in developing translational applications.
2026-02-04 | GSE314660 | GEO