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| 2. |
- Kalman, L. V., et al.
(author)
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Pharmacogenetic allele nomenclature: International workgroup recommendations for test result reporting
- 2016
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In: Clinical Pharmacology and Therapeutics. - : WILEY-BLACKWELL. - 0009-9236 .- 1532-6535. ; 99:2, s. 172-185
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Journal article (peer-reviewed)abstract
- This article provides nomenclature recommendations developed by an international workgroup to increase transparency and standardization of pharmacogenetic (PGx) result reporting. Presently, sequence variants identified by PGx tests are described using different nomenclature systems. In addition, PGx analysis may detect different sets of variants for each gene, which can affect interpretation of results. This practice has caused confusion and may thereby impede the adoption of clinical PGx testing. Standardization is critical to move PGx forward.
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| 3. |
- Garte, S, et al.
(author)
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Metabolic gene polymorphism frequencies in control populations
- 2001
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In: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. - 1055-9965. ; 10:12, s. 1239-1248
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Journal article (peer-reviewed)
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| 4. |
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| 5. |
- Obst, Matthias, 1974, et al.
(author)
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A Marine Biodiversity Observation Network for Genetic Monitoring of Hard-Bottom Communities (ARMS-MBON)
- 2020
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In: Frontiers in Marine Science. - : Frontiers Media SA. - 2296-7745. ; 7
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Journal article (peer-reviewed)abstract
- Marine hard-bottom communities are undergoing severe change under the influence of multiple drivers, notably climate change, extraction of natural resources, pollution and eutrophication, habitat degradation, and invasive species. Monitoring marine biodiversity in such habitats is, however, challenging as it typically involves expensive, non-standardized, and often destructive sampling methods that limit its scalability. Differences in monitoring approaches furthermore hinders inter-comparison among monitoring programs. Here, we announce a Marine Biodiversity Observation Network (MBON) consisting of Autonomous Reef Monitoring Structures (ARMS) with the aim to assess the status and changes in benthic fauna with genomic-based methods, notably DNA metabarcoding, in combination with image-based identifications. This article presents the results of a 30-month pilot phase in which we established an operational and geographically expansive ARMS-MBON. The network currently consists of 20 observatories distributed across European coastal waters and the polar regions, in which 134 ARMS have been deployed to date. Sampling takes place annually, either as short-term deployments during the summer or as long-term deployments starting in spring. The pilot phase was used to establish a common set of standards for field sampling, genetic analysis, data management, and legal compliance, which are presented here. We also tested the potential of ARMS for combining genetic and image-based identification methods in comparative studies of benthic diversity, as well as for detecting non-indigenous species. Results show that ARMS are suitable for monitoring hard-bottom environments as they provide genetic data that can be continuously enriched, re-analyzed, and integrated with conventional data to document benthic community composition and detect non-indigenous species. Finally, we provide guidelines to expand the network and present a sustainability plan as part of the European Marine Biological Resource Centre (www.embrc.eu).
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| 7. |
- Smits, KM, et al.
(author)
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Association of metabolic gene polymorphisms with tobacco consumption in healthy controls
- 2004
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In: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 110:2, s. 266-270
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Journal article (peer-reviewed)abstract
- Polymorphisms in genes that encode for metabolic enzymes have been associated with variations in enzyme activity between individuals. Such variations could be associated with differences in individual exposure to carcinogens that are metabolized by these genes. In this study, we examine the association between polymorphisms in several metabolic genes and the consumption of tobacco in a large sample of healthy individuals. The database of the International Collaborative Study on Genetic Susceptibility to Environmental Carcinogens was used. All the individuals who were controls from the case-control studies included in the data set with information on smoking habits and on genetic polymorphisms were selected (n = 20,938). Sufficient information was available on the following genes that are involved in the metabolism of tobacco smoke constituents: CYPIAI, GSTMI, GSTTI, NAT2 and GSTPI. None of the tested genes was clearly associated with smoking behavior. Information on smoking dose, available for a subset of subjects, showed no effect of metabolic gene polymorphisms on the amount of smoking. No association between polymorphisms in the genes studied and tobacco consumption was observed; therefore, no effect of these genes on smoking behavior should be expected.
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| 8. |
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| 9. |
- Benhamou, S, et al.
(author)
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Meta- and pooled analyses of the effects of glutathione S-transferase M1 polymorphisms and smoking on lung cancer risk
- 2002
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In: Carcinogenesis. - : Oxford University Press (OUP). - 0143-3334 .- 1460-2180. ; 23:8, s. 1343-1350
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Journal article (peer-reviewed)abstract
- Susceptibility to lung cancer may in part be attributable to inter-individual variability in metabolic activation or detoxification of tobacco carcinogens. The glutathione S-transferase M1 (GSTM1) genetic polymorphism has been extensively studied in this context; two recent meta-analyses of case-control studies suggested an association between GSTM1 deletion and lung cancer. At least 15 studies have been published after these overviews. We undertook a new meta-analysis to summarize the results of 43 published case-control studies including >18 000 individuals. A slight excess of risk of lung cancer for individuals with the GSTM1 null genotype was found (odds ratio (OR) = 1.17, 95% confidence interval (CI) 1.07-1.27). No evidence of publication bias was found (P = 0.4), however, it is not easy to estimate the extent of such bias and we cannot rule out some degree of publication bias in our results. A pooled analysis of the original data of about 9500 subjects involved in 21 case-control studies from the International Collaborative Study on Genetic Susceptibility to Environmental Carcinogens (GSEC) data set was performed to assess the role of GSTM1 genotype as a modifier of the effect of smoking on lung cancer risk with adequate power. Analyses revealed no evidence of increased risk of lung cancer among carriers of the GSTM1 null genotype (age-, gender- and center-adjusted OR = 1.08, 95% CI 0.98-1.18) and no evidence of interaction between GSTM1 genotype and either smoking status or cumulative tobacco consumption.
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