| 1. |
- Scott, Robert A., et al.
(author)
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A genomic approach to therapeutic target validation identifies a glucose-lowering GLP1R variant protective for coronary heart disease
- 2016
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In: Science Translational Medicine. - : American Association for the Advancement of Science (AAAS). - 1946-6234 .- 1946-6242. ; 8:341
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Journal article (peer-reviewed)abstract
- Regulatory authorities have indicated that new drugs to treat type 2 diabetes (T2D) should not be associated with an unacceptable increase in cardiovascular risk. Human genetics may be able to guide development of antidiabetic therapies by predicting cardiovascular and other health endpoints. We therefore investigated the association of variants in six genes that encode drug targets for obesity or T2D with a range of metabolic traits in up to 11,806 individuals by targeted exome sequencing and follow-up in 39,979 individuals by targeted genotyping, with additional in silico follow-up in consortia. We used these data to first compare associations of variants in genes encoding drug targets with the effects of pharmacological manipulation of those targets in clinical trials. We then tested the association of those variants with disease outcomes, including coronary heart disease, to predict cardiovascular safety of these agents. A low-frequency missense variant (Ala316Thr; rs10305492) in the gene encoding glucagon-like peptide-1 receptor (GLP1R), the target of GLP1R agonists, was associated with lower fasting glucose and T2D risk, consistent with GLP1R agonist therapies. The minor allele was also associated with protection against heart disease, thus providing evidence that GLP1R agonists are not likely to be associated with an unacceptable increase in cardiovascular risk. Our results provide an encouraging signal that these agents may be associated with benefit, a question currently being addressed in randomized controlled trials. Genetic variants associated with metabolic traits and multiple disease outcomes can be used to validate therapeutic targets at an early stage in the drug development process.
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| 2. |
- Capella, Gabriel, et al.
(author)
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DNA repair polymorphisms and the risk of stomach adenocarcinoma and severe chronic gastritis in the EPIC-EURGAST study
- 2008
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In: International Journal of Epidemiology. - : Oxford University Press (OUP). - 1464-3685 .- 0300-5771. ; 37:6, s. 1316-1325
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Journal article (peer-reviewed)abstract
- Background The contribution of genetic variation in DNA repair genes to gastric cancer (GC) risk remains essentially unknown. The aim of this study was to explore the relative contribution of DNA repair gene polymorphisms to GC risk and severe chronic atrophic gastritis (SCAG). Method A nested case control study within the EPIC cohort was performed including 246 gastric adenocarcinomas and 1175 matched controls. Controls with SCAG (n 91), as defined by low pepsinogen A (PGA) levels, and controls with no SCAG (n 1061) were also compared. Twelve polymorphisms at DNA repair genes (MSH2, MLH1, XRCC1, OGG1 and ERCC2) and TP53 gene were analysed. Antibodies against Helicobacter pylori were measured. Results No association was observed for any of these polymorphisms with stomach cancer risk. However, ERCC2 K751Q polymorphism was associated with an increased risk for non-cardial neoplasm [odds ratio (OR) 1.78; 95 confidence interval (CI) 1.023.12], being ERCC2 K751Q and D312N polymorphisms associated with the diffuse type. ERCC2 D312N (OR 2.0; 95 CI 1.093.65) and K751Q alleles (OR 1.82; 95 CI 1.013.30) and XRCC1 R399Q (OR 1.69; 95 CI 1.022.79) allele were associated with an increased risk for SCAG. Conclusion Our study supports a role of ERCC2 in non-cardial GC but not in cardial cancer. A concordant result was observed for subjects with low PGA levels. XRCC1 allele was associated also with SCAG. This is the first prospective study suggesting that individual variation in DNA repair may be relevant for gastric carcinogenesis, a finding that will require further confirmation validation in larger independent studies.
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| 3. |
- Escala-Garcia, Maria, et al.
(author)
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A network analysis to identify mediators of germline-driven differences in breast cancer prognosis
- 2020
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In: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 11:1
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Journal article (peer-reviewed)abstract
- Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies similar to 7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.
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