Cascading epigenomic analysis for identifying disease genes from the regulatory landscape of GWAS variants.
Ontology highlight
ABSTRACT:
SUBMITTER: Ng B
PROVIDER: S-EPMC8648125 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:It remains challenging to predict regulatory variants in particular tissues or cell types due to highly context-specific gene regulation. By connecting large-scale epigenomic profiles to expression quantitative trait loci (eQTLs) in a wide range of human tissues/cell types, we identify critical chromatin features that predict variant regulatory potential. We present cepip, a joint likelihood framework, for estimating a variant's regulatory probability in a context-dependent manner. Our method exhibits significant GWAS signal enrichment and is superior to existing cell type-specific methods. Furthermore, using phenotypically relevant epigenomes to weight the GWAS single-nucleotide polymorphisms, we improve the statistical power of the gene-based association test.
| S-EPMC5356314 | biostudies-literature
Project description:Concern about rising rates of obesity has prompted searches for obesity-related single nucleotide polymorphisms (SNPs) in genome-wide association studies (GWAS). Identifying plausible regulatory SNPs is very difficult partially because of linkage disequilibrium. We used an unusual epigenomic and transcriptomic analysis of obesity GWAS-derived SNPs in adipose versus heterologous tissues. From 50 GWAS and 121,064 expanded SNPs, we prioritized 47 potential causal regulatory SNPs (Tier-1 SNPs) for 14 gene loci. A detailed examination of seven loci revealed that four (CABLES1, PC, PEMT, and FAM13A) had Tier-1 SNPs positioned so that they could regulate use of alternative transcription start sites, resulting in different polypeptides being generated or different amounts of an intronic microRNA gene being expressed. HOXA11 and long noncoding RNA gene RP11-392O17.1 had Tier-1 SNPs in their 3' or promoter region, respectively, and strong preferences for expression in subcutaneous versus visceral adipose tissue. ZBED3-AS1 had two intragenic Tier-1 SNPs, each of which could contribute to mediating obesity risk through modulating long-distance chromatin interactions. Our approach not only revealed especially credible novel regulatory SNPs, but also helped evaluate previously highlighted obesity GWAS SNPs that were candidates for transcription regulation.
| S-EPMC8836216 | biostudies-literature
Project description:BackgroundThe remarkable growth of genome-wide association studies (GWAS) has created a critical need to experimentally validate the disease-associated variants, 90% of which involve non-coding variants.MethodsTo determine how the field is addressing this urgent need, we performed a comprehensive literature review identifying 36,676 articles. These were reduced to 1454 articles through a set of filters using natural language processing and ontology-based text-mining. This was followed by manual curation and cross-referencing against the GWAS catalog, yielding a final set of 286 articles.ResultsWe identified 309 experimentally validated non-coding GWAS variants, regulating 252 genes across 130 human disease traits. These variants covered a variety of regulatory mechanisms. Interestingly, 70% (215/309) acted through cis-regulatory elements, with the remaining through promoters (22%, 70/309) or non-coding RNAs (8%, 24/309). Several validation approaches were utilized in these studies, including gene expression (n = 272), transcription factor binding (n = 175), reporter assays (n = 171), in vivo models (n = 104), genome editing (n = 96) and chromatin interaction (n = 33).ConclusionsThis review of the literature is the first to systematically evaluate the status and the landscape of experimentation being used to validate non-coding GWAS-identified variants. Our results clearly underscore the multifaceted approach needed for experimental validation, have practical implications on variant prioritization and considerations of target gene nomination. While the field has a long way to go to validate the thousands of GWAS associations, we show that progress is being made and provide exemplars of validation studies covering a wide variety of mechanisms, target genes, and disease areas.
| S-EPMC8973751 | biostudies-literature
Project description:Utilizing data from published tuberculosis (TB) genome-wide association studies (GWAS), we use a bioinformatics pipeline to detect all polymorphisms in linkage disequilibrium (LD) with variants previously implicated in TB disease susceptibility. The probability that these variants had a predicted regulatory function was estimated using RegulomeDB and Ensembl's Variant Effect Predictor. Subsequent genotyping of these 133 predicted regulatory polymorphisms was performed in 400 admixed South African TB cases and 366 healthy controls in a population-based case-control association study to fine-map the causal variant. We detected associations between tuberculosis susceptibility and six intronic polymorphisms located in MARCO, IFNGR2, ASHAS2, ACACA, NISCH and TLR10. Our post-GWAS approach demonstrates the feasibility of combining multiple TB GWAS datasets with linkage information to identify regulatory variants associated with this infectious disease.
| S-EPMC5383035 | biostudies-literature
Project description:Identifying noncoding risk variants remains a challenging task. Because noncoding variants exert their effects in the context of a gene regulatory network (GRN), we hypothesize that explicit use of disease-relevant GRNs can significantly improve the inference accuracy of noncoding risk variants. We describe Annotation of Regulatory Variants using Integrated Networks (ARVIN), a general computational framework for predicting causal noncoding variants. It employs a set of novel regulatory network-based features, combined with sequence-based features to infer noncoding risk variants. Using known causal variants in gene promoters and enhancers in a number of diseases, we show ARVIN outperforms state-of-the-art methods that use sequence-based features alone. Additional experimental validation using reporter assay further demonstrates the accuracy of ARVIN. Application of ARVIN to seven autoimmune diseases provides a holistic view of the gene subnetwork perturbed by the combinatorial action of the entire set of risk noncoding mutations.
| S-EPMC5816022 | biostudies-literature
Project description:Genome-wide association studies (GWAS) are useful for nominating candidate genes, but typically are unable to establish disease causality or differentiate between the effects of variants in linkage disequilibrium (LD). Additionally, some GWAS loci might contain multiple causative variants or genes that contribute to the overall disease susceptibility at a single locus. However, the majority of current GWAS lack the statistical power to test whether multiple causative genes underlie the same locus, prompting us to adopt an alternative approach to testing multiple GWAS genes empirically. We used gene targeting in a disease-susceptible rat model of genetic hypertension to test all six genes at the Agtrap-Plod1 locus (Agtrap, Mthfr, Clcn6, Nppa, Nppb, and Plod1) for blood pressure (BP) and renal phenotypes. This revealed that the majority of genes at this locus (five out of six) can impact hypertension by modifying BP and renal phenotypes. Mutations of Nppa, Plod1, and Mthfr increased disease susceptibility, whereas Agtrap and Clcn6 mutations decreased hypertension risk. Reanalysis of the human AGTRAP-PLOD1 locus also implied that disease-associated haplotype blocks with polygenic effects were not only possible, but rather were highly plausible. Combined, these data demonstrate for the first time that multiple modifiers of hypertension can cosegregate at a single GWAS locus.
| S-EPMC3847770 | biostudies-literature
Project description:Borrelia burgdorferi, the etiological agent of Lyme disease, persists in nature through an enzootic cycle consisting of a vertebrate host and an Ixodes tick vector. The sequence motifs modified by two well-characterized restriction/modification (R/M) loci of B. burgdorferi type strain B31 were recently described, but the methylation profiles of other Lyme disease Borrelia bacteria have not been characterized. Here, the methylomes of B. burgdorferi type strain B31 and 7 clonal derivatives, along with B. burgdorferi N40, B. burgdorferi 297, B. burgdorferi CA-11, B. afzelii PKo, B. afzelii BO23, and B. garinii PBr, were defined through PacBio single-molecule real-time (SMRT) sequencing. This analysis revealed 9 novel sequence motifs methylated by the plasmid-encoded restriction/modification enzymes of these Borrelia strains. Furthermore, while a previous analysis of B. burgdorferi B31 revealed an epigenetic impact of methylation on the global transcriptome, the current data contradict those findings; our analyses of wild-type B. burgdorferi B31 revealed no consistent differences in gene expression among isogenic derivatives lacking one or more restriction/modification enzymes. IMPORTANCE The principal causative agent of Lyme disease in humans in the United States is Borrelia burgdorferi, while B. burgdorferi, B. afzelii, and B. garinii, collectively members of the Borrelia burgdorferi sensu lato species complex, cause Lyme disease in Europe and Asia. Two plasmid-encoded restriction/modification systems have been shown to limit the genetic transformation of B. burgdorferi type strain B31 with foreign DNA, but little is known about the restriction/modification systems of other Lyme disease Borrelia bacteria. This paper describes the methylation motifs present on genomic DNAs of multiple B. burgdorferi, B. afzelii, and B. garinii strains. Contrary to a previous report, we did not find evidence for an epigenetic impact on gene expression by methylation. Knowledge of the motifs recognized and methylated by the restriction/modification enzymes of Lyme disease Borrelia will facilitate molecular genetic investigations of these important human pathogens. Additionally, the similar motifs methylated by orthologous restriction/modification systems of Lyme disease Borrelia bacteria and the presence of these motifs within recombinogenic loci suggest a biological role for these ubiquitous restriction/modification systems in horizontal gene transfer.
| S-EPMC8262957 | biostudies-literature
Project description:We performed an analysis of 489 GWAS variants that are associated with RA disease or are markers of RA drug efficacy. These variants were analyzed for: 1) their spatial interactions in three-dimensions, as captured by proximity ligation; 2) chromatin markers of regulatory functions (DNAse Hypersensitivity Sites, transcription factor binding site motifs, luciferase allele-specific SNP enhancer activity); and 3) their ability to affect linked gene expression (i.e. act as an eQTL). SNPs rs3184504, rs653178, and rs11545078 show evidence of differential long distance spatial associations in HL-60/S4 cells in undifferentiated versus differentiated cell states. RA associated variants at the SH2B3 locus (rs3184504/rs653178)) have a spatially-reinforced eQTL with BAZ2A, ~60Mb away, which affects platelet formation. Similarly, a variant at the GGH locus, which is associated with methotrexate toxicity, forms an inter-chromosomal spatially-reinforced eQTL with MGEA5, which is overexpressed in peripheral blood mononuclear cells.
2019-12-01 | GSE101812 | GEO
Project description:Alzheimer's disease (AD) is a genetically complex, multifactorial neurodegenerative disease. It affects more than 45 million people worldwide and currently remains untreatable. Although genome-wide association studies (GWAS) have identified many AD-associated common variants, only about 25 genes are currently known to affect the risk of developing AD, despite its highly polygenic nature. Moreover, the risk variants underlying GWAS AD-association signals remain unknown. Here, we describe a deep post-GWAS analysis of AD-associated variants, using an integrated computational framework for predicting both disease genes and their risk variants. We identified 342 putative AD risk genes in 203 risk regions spanning 502 AD-associated common variants. 246 AD risk genes have not been identified as AD risk genes by previous GWAS collected in GWAS catalogs, and 115 of 342 AD risk genes are outside the risk regions, likely under the regulation of transcriptional regulatory elements contained therein. Even more significantly, for 109 AD risk genes, we predicted 150 risk variants, of both coding and regulatory (in promoters or enhancers) types, and 85 (57%) of them are supported by functional annotation. In-depth functional analyses showed that AD risk genes were overrepresented in AD-related pathways or GO terms-e.g., the complement and coagulation cascade and phosphorylation and activation of immune response-and their expression was relatively enriched in microglia, endothelia, and pericytes of the human brain. We found nine AD risk genes-e.g., IL1RAP, PMAIP1, LAMTOR4-as predictors for the prognosis of AD survival and genes such as ARL6IP5 with altered network connectivity between AD patients and normal individuals involved in AD progression. Our findings open new strategies for developing therapeutics targeting AD risk genes or risk variants to influence AD pathogenesis.
| S-EPMC8519945 | biostudies-literature
Project description:Thyroid carcinoma (TC) is the most common endocrine malignancy. The incidence rate of thyroid cancer has increased rapidly in recent years. The occurrence and development of thyroid cancers are highly related to the massive genetic and epigenetic changes. Therefore, it is essential to explore the mechanism of thyroid cancer pathogenesis. Genome-Wide Association Studies (GWAS) have been widely used in various diseases. Researchers have found multiple single nucleotide polymorphisms (SNPs) are significantly related to TC. However, the biological mechanism of these SNPs is still unknown. In this paper, we used one GWAS dataset and two eQTL datasets, and integrated GWAS with expression quantitative trait loci (eQTL) in both thyroid and blood to explore the mechanism of mutations and causal genes of thyroid cancer. Finally, we found rs1912998 regulates the expression of IGFALS (P = 1.70E-06) and HAGH (P = 5.08E-07) in thyroid, which is significantly related to thyroid cancer. In addition, KEGG shows that these genes participate in multiple thyroid cancer-related pathways.
| S-EPMC7889963 | biostudies-literature