A conceptual framework for pharmacodynamic genome-wide association studies in pharmacogenomics.
A conceptual framework for pharmacodynamic genome-wide association studies in pharmacogenomics.
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DOI：
10.1016/j.drudis.2011.09.001
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发表时间：
2011-10
影响因子：
7.4
通讯作者：
Israel, Elliot
中科院分区：
文献类型：
--
作者：
Wu, Rongling;Tong, Chunfa;Wang, Zhong;Mauger, David;Tantisira, Kelan;Szefler, Stanley J.;Chinchilli, Vernon M.;Israel, Elliot
全基因组关联研究 (GWAS) 已成为识别影响药物反应或对药物不良反应易感性的基因座的强大工具。然而，目前基于基因型和表型之间关联的简单分析的GWAS忽略了药物反应的生化反应，从而限制了对其遗传结构的推断范围。为了促进药物基因组学中 GWAS 的推断，我们试图通过计算模型对药物反应的药效过程进行数学整合。通过估计和测试药效学和药代动力学参数的遗传控制，这种机械方法不仅增强了显着遗传关联的生物学和临床相关性，而且还提高了基因检测的统计功效和稳健性。本报告讨论了基于药效学的 GWAS 的一般原理和发展，强调了该方法在解决各种药物基因组问题中的实际用途，并表明该方法将成为研究药物反应或反应的遗传结构的重要方法。
Genome-wide association studies (GWAS) have emerged as a powerful tool to identify loci that affect drug response or susceptibility to adverse drug reactions. However, current GWAS based on a simple analysis of associations between genotype and phenotype ignores the biochemical reactions of drug response, thus limiting the scope of inference about its genetic architecture. To facilitate the inference of GWAS in pharmacogenomics, we sought to undertake the mathematical integration of the pharmacodynamic process of drug reactions through computational models. By estimating and testing the genetic control of pharmacodynamic and pharmacokinetic parameters, this mechanistic approach does not only enhance the biological and clinical relevance of significant genetic associations, but also improve the statistical power and robustness of gene detection. This report discusses the general principle and development of pharmacodynamics-based GWAS, highlights the practical use of this approach in addressing various pharmacogenomic problems, and suggests that this approach will be an important method to study the genetic architecture of drug responses or reactions.
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DOI：
10.1164/rccm.2105013
发表时间：
2002-05-15
影响因子：
24.7
作者：
Martin, RJ;Szefler, SJ;Sorkness, CA
通讯作者：
Sorkness, CA
影响因子：
120.7
作者：
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通讯作者：
Gurbel, Paul A.
DOI：
10.1073/pnas.0903103106
发表时间：
2009-06-09
影响因子：
11.1
作者：
Hindorff, Lucia A.;Sethupathy, Praveen;Manolio, Teri A.
通讯作者：
Manolio, Teri A.
影响因子：
2.9
作者：
Yang Q;Cui J;Chazaro I;Cupples LA;Demissie S
通讯作者：
Demissie S
影响因子：
1.1
作者：
Lin, Min;Berg, Arthur;Wu, Rongling
通讯作者：
Wu, Rongling