Smith Jennifer A, Arnett Donna K, Kelly Reagan J, Ordovas Jose M, Sun Yan V, Hopkins Paul N, Hixson James E, Straka Robert J, Peacock James M, Kardia Sharon L R
Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109-2029, USA.
Eur J Hum Genet. 2008 May;16(5):603-13. doi: 10.1038/sj.ejhg.5202003. Epub 2008 Jan 23.
Metabolic response to the triglyceride (TG)-lowering drug, fenofibrate, is shaped by interactions between genetic and environmental factors, yet knowledge regarding the genetic determinants of this response is primarily limited to single-gene effects. Since very low-density lipoprotein (VLDL) is the central carrier of fasting TG, identifying factors that affect both total TG and VLDL-TG response to fenofibrate is critical for predicting individual fenofibrate response. As part of the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study, 688 individuals from 161 families were genotyped for 91 single-nucleotide polymorphisms (SNPs) in 25 genes known to be involved in lipoprotein metabolism. Using generalized estimating equations to control for family structure, we performed linear modeling to investigate whether single SNPs, single covariates, SNP-SNP interactions, and/or SNP-covariate interactions had a significant association with the change in total fasting TG and fasting VLDL-TG after 3 weeks of fenofibrate treatment. A 10-iteration fourfold cross-validation procedure was used to validate significant associations and quantify their predictive abilities. More than one-third of the significant, cross-validated SNP-SNP interactions predicting each outcome involved just five SNPs, showing that these SNPs are of key importance to fenofibrate response. Multiple variable models constructed using the top-ranked SNP--covariate interactions explained 11.9% more variation in the change in TG and 7.8% more variation in the change in VLDL than baseline TG alone. These results yield insight into the complex biology of fenofibrate response, which can be used to target fenofibrate therapy to individuals who are most likely to benefit from the drug.
对降甘油三酯(TG)药物非诺贝特的代谢反应受遗传和环境因素相互作用的影响,然而关于这种反应的遗传决定因素的知识主要局限于单基因效应。由于极低密度脂蛋白(VLDL)是空腹TG的主要载体,识别影响总TG和VLDL-TG对非诺贝特反应的因素对于预测个体对非诺贝特的反应至关重要。作为降脂药物与饮食遗传学网络(GOLDN)研究的一部分,对来自161个家庭的688名个体进行了基因分型,检测了25个已知参与脂蛋白代谢的基因中的91个单核苷酸多态性(SNP)。使用广义估计方程来控制家族结构,我们进行线性建模以研究单个SNP、单个协变量、SNP-SNP相互作用和/或SNP-协变量相互作用是否与非诺贝特治疗3周后空腹总TG和空腹VLDL-TG的变化存在显著关联。采用10次迭代的四重交叉验证程序来验证显著关联并量化其预测能力。预测每种结果的超过三分之一的显著、经过交叉验证的SNP-SNP相互作用仅涉及5个SNP,表明这些SNP对非诺贝特反应至关重要。使用排名靠前的SNP-协变量相互作用构建的多变量模型比仅使用基线TG能多解释11.9%的TG变化和7.8%的VLDL变化。这些结果有助于深入了解非诺贝特反应的复杂生物学机制,可用于将非诺贝特治疗靶向最可能从该药物中获益的个体。