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药物基因组学中细胞毒性图谱关联方法的比较

A comparison of association methods for cytotoxicity mapping in pharmacogenomics.

作者信息

Brown Chad, Havener Tammy M, Everitt Lorraine, McLeod Howard, Motsinger-Reif Alison A

机构信息

Department of Statistics, North Carolina State University Raleigh, NC, USA.

出版信息

Front Genet. 2011 Dec 14;2:86. doi: 10.3389/fgene.2011.00086. eCollection 2011.

Abstract

Cytotoxicity assays of immortalized lymphoblastoid cell lines (LCLs) represent a promising new in vitro approach in pharmacogenomics research. However, previous studies employing LCLs in gene mapping have used simple association methods, which may not adequately capture the true differences in non-linear response profiles between genotypes. Two common approaches summarize each dose-response curve with either the IC50 or the slope parameter estimates from a hill slope fit and treat these estimates as the response in a linear model. The current study investigates these two methods, as well as four novel methods, and compares their power to detect differences between the response profiles of genotypes under a variety of different alternatives. The four novel methods include two methods that summarize each dose-response by its area under the curve, one method based off of an analysis of variance (ANOVA) design, and one method that compares hill slope fits for all individuals of each genotype. The power of each method was found to depend not only on the choice of alternative, but also on the choice for the set of dosages used in cytotoxicity measurements. The ANOVA-based method was found to be the most robust across alternatives and dosage sets for power in detecting differences between genotypes.

摘要

永生化淋巴母细胞系(LCLs)的细胞毒性测定是药物基因组学研究中一种很有前景的新体外方法。然而,先前在基因定位中使用LCLs的研究采用的是简单关联方法,可能无法充分捕捉不同基因型之间非线性反应谱的真实差异。两种常见方法分别用半数抑制浓度(IC50)或根据希尔斜率拟合得到的斜率参数估计值来总结每条剂量反应曲线,并将这些估计值作为线性模型中的反应。本研究对这两种方法以及四种新方法进行了研究,并比较了它们在各种不同替代情况下检测基因型反应谱差异的能力。这四种新方法包括两种通过曲线下面积总结每条剂量反应的方法、一种基于方差分析(ANOVA)设计的方法以及一种比较每种基因型所有个体的希尔斜率拟合的方法。发现每种方法的能力不仅取决于替代方案的选择,还取决于细胞毒性测量中所用剂量组的选择。基于方差分析的方法在检测基因型差异的能力方面,在各种替代方案和剂量组中最为稳健。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec25/3268638/eefefcb00ac3/fgene-02-00086-g001.jpg

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