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- Bonfiglio, F., et al.
(författare)
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A meta-analysis of reflux genome-wide association studies in 6750 Northern Europeans from the general population
- 2017
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Ingår i: Neurogastroenterology and Motility. - : Wiley. - 1350-1925 .- 1365-2982. ; 29:2
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundGastroesophageal reflux disease (GERD), the regurgitation of gastric acids often accompanied by heartburn, affects up to 20% of the general population. Genetic predisposition is suspected from twin and family studies but gene-hunting efforts have so far been scarce and no conclusive genome-wide study has been reported. We exploited data available from general population samples, and studied self-reported reflux symptoms in relation to genome-wide single nucleotide polymorphism (SNP) genotypes. MethodsWe performed a GWAS meta-analysis of three independent population-based cohorts from Sweden, Finland, and UK. GERD cases (n=2247) and asymptomatic controls (n=4503) were identified using questionnaire-derived symptom data. Upon stringent quality controls, genotype data for more than 2.5M markers were used for association testing. Bioinformatic characterization of genomic regions associated with GERD included gene-set enrichment analysis (GSEA), in silico prediction of genetic risk effects on gene expression, and computational analysis of drug-induced gene expression signatures using Connectivity Map (cMap). Key resultsWe identified 30 GERD suggestive risk loci (P5x10(-5)), with concordant risk effects in all cohorts, and predicted functional effects on gene expression in relevant tissues. GSEA revealed involvement of GERD risk genes in biological processes associated with the regulation of ion channel and cell adhesion. From cMap analysis, omeprazole had significant effects on GERD risk gene expression, while antituberculosis and anti-inflammatory drugs scored highest among the repurposed compounds. ConclusionsWe report a large-scale genetic study of GERD, and highlight genes and pathways that contribute to further our understanding of its pathogenesis and therapeutic opportunities.
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| 2. |
- de Vries, Paul S., et al.
(författare)
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Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study
- 2017
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5x10(-8) is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5x10(-8)), the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development.
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