Lin Min, Wu Rongling
Department of Statistics, University of Florida, Gainesville, 32611, USA.
Genetics. 2005 Jun;170(2):919-28. doi: 10.1534/genetics.104.039958. Epub 2005 Mar 31.
Almost all drugs that produce a favorable response (efficacy) may also produce adverse effects (toxicity). The relative strengths of drug efficacy and toxicity that vary in human populations are controlled by the combined influences of multiple genes and environmental influences. Genetic mapping has proven to be a powerful tool for detecting and identifying specific DNA sequence variants on the basis of the haplotype map (HapMap) constructed from single-nucleotide polymorphisms (SNPs). In this article, we present a novel statistical model for sequence mapping of two different but related drug responses. This model is incorporated by mathematical functions of drug response to varying doses or concentrations and the statistical device used to model the correlated structure of the residual (co)variance matrix. We implement a closed-form solution for the EM algorithm to estimate the population genetic parameters of SNPs and the simplex algorithm to estimate the curve parameters describing the pharmacodynamic changes of different genetic variants and matrix-structuring parameters. Extensive simulations are performed to investigate the statistical properties of our model. The implications of our model in pharmacogenetic and pharmacogenomic research are discussed.
几乎所有能产生有益反应(疗效)的药物也可能产生不良反应(毒性)。药物疗效和毒性在人群中的相对强度差异受多种基因和环境因素的综合影响。基于单核苷酸多态性(SNP)构建的单倍型图谱(HapMap),基因定位已被证明是检测和识别特定DNA序列变异的有力工具。在本文中,我们提出了一种用于两种不同但相关药物反应序列定位的新型统计模型。该模型由药物对不同剂量或浓度反应的数学函数以及用于对残差(协)方差矩阵的相关结构进行建模的统计方法组成。我们为EM算法实现了一个封闭形式的解,以估计SNP的群体遗传参数,为单纯形算法实现了一个封闭形式的解,以估计描述不同基因变异药效学变化的曲线参数和矩阵结构参数。进行了广泛的模拟以研究我们模型的统计特性。讨论了我们的模型在药物遗传学和药物基因组学研究中的意义。