GWAS Central: a comprehensive resource for the comparison and interrogation of genome-wide association studies

Beck, Tim; Hastings, Robert K.; Gollapudi, Sirisha; Free, Robert C; Brookes, Anthony J.

doi:10.1038/ejhg.2013.274

Cited by 157 publications

(123 citation statements)

References 9 publications

Supporting

Mentioning

122

Contrasting

Unclassified

Order By: Relevance

“…We used GWAS central (http://www.gwascentral.org/) to download all SNPs that are associated with T1D and T2D above a threshold of -log 10 p-value ≥ 4, resulting in 666 and 509 unique SNPs, respectively (BECK et al 2014); these SNPs are contained within Table S8. We then determined the number of T1D or T2D-associated SNPs occurring within a 1 Mbp genomic window, yielding the histograms shown for each chromosome in Fig.…”

Section: Identification Of Human Loci Syntenic To Mouse Qtl and Intementioning

confidence: 99%

Genetic Drivers of Pancreatic Islet Function

et al. 2018

View full text Add to dashboard Cite

The majority of gene loci that have been associated with type 2 diabetes play a role in pancreatic islet function. To evaluate the role of islet gene expression in the etiology of diabetes, we sensitized a genetically diverse mouse population with a Western diet high in fat (45%-kcal) and sucrose (34%) and carried out genome-wide association mapping of diabetes-related phenotypes. We quantified mRNA abundance in the islets and identified 18,820 expression quantitative trait loci. We applied mediation analysis to identify candidate causal driver genes at loci that affect the abundance of numerous transcripts. These include two genes previously associated with monogenic diabetes (PDX1 and HNF4A), as well as three genes with nominal association with diabetes-related traits in humans (FAM83E, IL6ST, and SAT2). We grouped transcripts into gene modules and mapped regulatory loci for modules enriched with transcripts specific for α-cells, and another specific for δ-cells. However, no single module enriched for β-cell-specific transcripts, suggesting heterogeneity of gene expression patterns within the β-cell population. A module enriched in transcripts associated with branched chain amino acid metabolism was the most strongly correlated with physiological traits that reflect insulin resistance. Although the mice in this study were not overtly diabetic, the analysis of pancreatic islet gene expression under dietary-induced stress enabled us to identify correlated variation in groups of genes that are functionally linked to diabetes-associated physiological traits. Our analysis suggests an expected degree of concordance between diabetes-associated loci in the mouse with those found in human populations and demonstrates how the mouse can provide evidence to support nominal associations found in human genome-wide association mapping.4

show abstract

Section: Identification Of Human Loci Syntenic To Mouse Qtl and Intementioning

confidence: 99%

Genetic Drivers of Pancreatic Islet Function

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Nucleotide variants were filtered against the dbSNP database [12], 1000 Genomes Project database [13], GWAS central database [14] and EN-SEMBL database [15]. Statistical significance of the differences between case and control groups in both allele and genotype frequencies was calculated using two-tailed Fisher's exact test.…”

Section: Statistical Analysis Of Nucleotide Variantsmentioning

confidence: 99%

Massively parallel targeted resequencing reveals novel genetic variants associated with aspergillosis in paediatric patients with haematological malignancies

Skonieczna¹,

Styczyński²,

Krenska³

et al. 2017

pjp

View full text Add to dashboard Cite

This study aimed to find novel genetic variants of susceptibility to aspergillosis in paediatric patients with haematological malignancies. Complete sequences of fifteen genes of human innate immunity (CCL2, CCR2, CD209, CLEC6A, CLEC7A and ten TLR genes) were studied in 40 patients diagnosed with haematological disorders (20 unaffected and 20 affected by aspergillosis). All samples were sequenced with MiSeq (Illumina) and 454 (Roche Diagnostics) technologies. Statistical significance of the differences between studied groups was determined using the twotailed Fisher's exact test. Sixty variants of potential importance were identified, the vast majority of which are located in non-coding parts of the targeted genes. At the threshold of p < 0.000005, one intergenic (TLR2 rs4585282) and one intronic variant (CLEC6A rs12099687) were found significant between the case and control groups for genotype and allele frequencies, respectively. Rs12099687 in CLE-C6A was predicted to constitute an alternative isoform or cryptic splice site, which potentially changes activity of the Dectin-2 protein. Overall, we assume that the two strongest associations reported in this study are expected to be reproducible even in the absence of other evidence, while another twelve associations may be strong enough to justify additional research in larger cohorts.

show abstract

“…Disease-associated variants data contained in ClinVar and the human gene mutation database (HGMD) are published gene variants responsible for human inherited diseases (25,26). Genome-wide association study (GWAS) SNPs from GWAS (27) are numerous common genetic variants associated with a trait or disease.…”

Section: Methodsmentioning

confidence: 99%

Prioritization of non-coding disease-causing variants and long non-coding RNAs in liver cancer

et al. 2016

Oncology Letters

View full text Add to dashboard Cite

Abstract. There are multiple bioinformatics tools available for the detection of coding driver mutations in cancers. However, the prioritization of pathogenic non-coding variants remains a challenging and demanding task. The present study was performed to discriminate non-coding disease-causing mutations and prioritize potential cancer-implicated long non-coding RNAs (lncRNAs) in liver cancer using a logistic regression model. A logistic regression model was constructed by combining 19,153 disease-associated ClinVar and human gene mutation database pathogenic variants as the response variable and non-coding features as the predictor variable. Genome-wide association study (GWAS) disease or trait-associated variants and recurrent somatic mutations were used to validate the model. Non-coding gene features with the highest fractions of load were characterized and potential cancer-associated lncRNA candidates were prioritized by combining the fraction of high-scoring regions and average score predicted by the logistic regression model. H3K9me3 and conserved regions were the most negatively and positively informative for the model, respectively. The area under the receiver operating characteristic curve of the model was 0.92. The average score of GWAS disease-associated variants was significantly increased compared with neutral single nucleotide polymorphisms (5.8642 vs. 5.4707; P<0.001), the average score of recurrent somatic mutations of liver cancer was significantly increased compared with non-recurrent somatic mutations (5.4101 vs. 5.2768; P=0.0125). The present study found regions in lncRNAs and introns/untranslated regions of protein coding genes where mutations are most likely to be damaging. In total, 847 lncRNAs were filtered out from the background. Characterization of this subset of lncRNAs showed that these lncRNAs are more conservative, less mutated and more highly expressed compared with other control lncRNAs. In addition, 23 of these lncRNAs were differentially expressed between 12 pairs of liver cancer and adjacent normal specimens. The logistic regression model is a useful tool to prioritize non-coding pathogenic variants and lncRNAs, and paves the way for the detection of non-coding driver lncRNAs in liver cancer.

show abstract

GWAS Central: a comprehensive resource for the comparison and interrogation of genome-wide association studies

Cited by 157 publications

References 9 publications

Genetic Drivers of Pancreatic Islet Function

Genetic Drivers of Pancreatic Islet Function

Massively parallel targeted resequencing reveals novel genetic variants associated with aspergillosis in paediatric patients with haematological malignancies

Prioritization of non-coding disease-causing variants and long non-coding RNAs in liver cancer

Contact Info

Product

Resources

About