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Modeling sequence-sequence interactions for drug response

机译:建模药物相互作用的序列-序列相互作用

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Motivation: Genetic interactions or epistasis may play an important role in the genetic etiology of drug response. With the availability of large-scale, high-density single nucleotide polymorphism markers, a great challenge is how to associate haplotype structures and complex drug response through its underlying pharmacodynamic mechanisms. Results: We have derived a general statistical model for detecting an interactive network of DNA sequence variants that encode pharmacodynamic processes based on the haplotype map constructed by single nucleotide polymorphisms. The model was validated by a pharmacogenetic study for two predominant beta-adrenergic receptor (βAR) subtypes expressed in the heart, β1AR and β2AR. Haplotypes from these two receptors trigger significant interaction effects on the response of heart rate to different dose levels of dobutamine. This model will have implications for pharmacogenetic and pharmacogenomic research and drug discovery.
机译:动机:遗传相互作用或上位性可能在药物反应的遗传病因中起重要作用。随着大规模,高密度单核苷酸多态性标志物的获得,一个巨大的挑战是如何通过其潜在的药效学机制将单倍型结构和复杂的药物反应联系起来。结果:我们已经得出了一个一般的统计模型,该模型可用于检测由单核苷酸多态性构建的单倍型图谱编码的药代动力学过程的DNA序列变异体的相互作用网络。通过药物遗传学研究对心脏中表达的两种主要的β-肾上腺素能受体(βAR)亚型β1AR和β2AR进行了验证。这两个受体的单倍型在不同剂量的多巴酚丁胺对心率的反应中引发了显着的相互作用。该模型将对药物遗传学和药物基因组学研究以及药物发现产生影响。

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