Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.
Malcom Randall VA Medical Center, Gainesville, FL 32610, USA; Department of Surgery, University of Florida, Box 100128, Gainesville, FL 32610, USA; Department of Biomedical Engineering, University of Florida, Gainesville, FL 32610, USA.
Drug Discov Today. 2019 Mar;24(3):883-889. doi: 10.1016/j.drudis.2019.01.009. Epub 2019 Jan 25.
The personalized therapy for hypertension needs comprehensive knowledge about how blood pressures (BPs; systolic and diastolic) and their pulsatile and steady components are controlled by genetic factors. Here, we propose a unified pharmacodynamic (PD) functional mapping framework for identifying specific quantitative trait loci (QTLs) that mediate multivariate response-dose curves of BP. This framework can characterize how QTLs govern pulsatile and steady components through jointly regulating systolic and diastolic pressures. The model can quantify the genetic effects of individual QTLs on maximal drug effect, the maximal rate of drug response, and the dose window of maximal drug response. This unified mapping framework provides a tool for identifying pharmacological genes potentially useful to design the right medication and right dose for patients.
高血压的个性化治疗需要综合了解血压（收缩压和舒张压）及其脉动和稳定成分受遗传因素控制的方式。在这里，我们提出了一个统一的药效动力学（PD）功能映射框架，用于识别介导血压多变量反应-剂量曲线的特定数量性状位点（QTL）。该框架可以通过共同调节收缩压和舒张压来描述 QTL 如何控制脉动和稳定成分。该模型可以量化单个 QTL 对最大药物效应、药物反应最大速率以及最大药物反应剂量窗口的遗传效应。这个统一的映射框架为识别潜在的药理学基因提供了一种工具，这些基因可能有助于为患者设计正确的药物和剂量。
