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Selecting Predictive Markers for Pharmacogenetic Traits: Tagging vs. Data-Mining Approaches

机译:选择药物遗传学特征的预测标记:标记与数据挖掘方法

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Objective: The tagging approach appears as a promising tool to test the association of genetic variants with complex traits such as disease susceptibility or drug response. However, since tag markers are selected only on the basis of inter-marker LD properties, regardless of any phenotypes, it remains unclear to what extent they can be useful to predict variable drug responses, once typed in clinical material. We undertook a study to provide further insights into the usefulness of the tagging approach for selecting phenotype-associated markers relevant to drug response. Methods: Several tagging methods were applied to the genotyping data of two drug-metabolizing enzymes, NAT2 and CYP2D6, and the ability of the selected tagging markers to predict the individual metabolizer status was empirically evaluated. We also assessed the impact of LD levels, tagging thresholds and allele frequencies on tagging efficiency. Results: We found that the functional variation was adequately represented by the selected tagging markers, these latter providing a classification accuracy for the individual metabolizer status close to the maximal 100% value observed with the entire set of polymorphisms. Conclusion: The tagging approach is an interesting approach to select candidate gene markers predictive of drug response in pharmacogenomic studies. [PUBLICATION ABSTRACT]
机译:目的:标记方法似乎是检验遗传变异与复杂特征(如疾病易感性或药物反应)的关联的有前途的工具。但是,由于标签标记仅基于标记间的LD特性进行选择,而与任何表型无关,因此,一旦在临床材料中进行分类,它们在多大程度上可用于预测可变药物反应仍不清楚。我们进行了一项研究,以进一步了解标记方法在选择与药物反应相关的表型相关标记中的作用。方法:对两种药物代谢酶NAT2和CYP2D6的基因分型数据采用了几种标记方法,并通过经验评估了所选标记物预测个体代谢物状态的能力。我们还评估了LD水平,标记阈值和等位基因频率对标记效率的影响。结果:我们发现所选标记标记足以代表功能上的变化,这些标记提供了单个代谢物状态的分类准确度,接近整个多态性组所观察到的最大100%值。结论:标记方法是在药物基因组学研究中选择可预测药物反应的候选基因标记的有趣方法。 [出版物摘要]

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