华法林剂量预测公式和相关变异群研究

发布时间：2018-06-23 11:27

本文选题：华法林 + CYP2C9　；参考：《中南大学》2014年硕士论文

【摘要】：华法林是临床上最常用的香豆素类口服抗凝药,主要用预防和治疗多种血管栓塞性疾病。华法林通过抑制维生素K循环产生药理作用,在体内主要由细胞色素P450酶羟基化代谢后经肾脏排出体外。华法林临床应用特点是治疗窗窄、不良反应严重、个体差异大等,影响华法林个体差异的因素很多,遗传变异是导致剂量个体差异和种族的最主要原因。华法林药物代谢酶(CYP2C9)和药物作用靶点(VKOR1)基因多态性是影响华法林剂量个体差异的主要遗传因素,这两个基因突变最多可解释华法林剂量个体差异40%。美国FDA在华法林药物使用说明书上提示患者在服用华法林之前需要检测CYP2C9和VKORC1的基因型,根据基因型对患者的初始剂量进行预测,以缩短患者达到稳定剂量的时间、降低不良反应的发生率。由于华法林剂量存在较大的种族差异,中国人群和高加索人、非洲人等人群间剂量相差较大,因此我们希望通过大样本回顾性的临床研究,建立一个适合中国人群的华法林药物基因组学用药模型。由于已知遗传因素对华法林剂量个体差异的解释能力有限,而且现有模型对于高剂量和低剂量患者的预测准确度低,因此本研究希望在中国人群中使用目标区域捕获测序的方法研究除CYP2C9*3和VKORC1-1639变异外,其他变异与华法林稳定剂量的关系。同时开发适合高剂量和低剂量人群的华法林剂量模型,减少这些高危人群不良反应发生率。本课题主要研究结果如下： 1、本研究建立了一个新的华法林药物基因组学剂量预测模型,该模型可以解释华法林剂量个体差异的36.1%,模型预测准确度为56.2%,其中对于剂量在1.88-4mg/天患者的预测准确度为68%。 2、本研究通过对极端剂量样本进行二代测序发现了一些新的与华法林剂量相关的变异。使用数据挖掘的方法发现利用五种常见分类模型可以很好的将高剂量患者和低剂量患者区分开,预测准确度大于60%。
[Abstract]:Warfarin is the most commonly used oral anticoagulant of coumarins, which is mainly used to prevent and treat many vascular embolism diseases. Warfarin exerts pharmacological effect by inhibiting vitamin K cycle, which is mainly metabolized by cytochrome P450 enzyme hydroxylation in vivo and discharged from the kidney through the kidney. Warfarin clinical application is characterized by narrow therapeutic window, severe adverse reactions and large individual differences. There are many factors affecting warfarin individual differences. Genetic variation is the main cause of dose individual difference and race. The polymorphism of warfarin drug metabolizing enzyme (CYP2C9) and drug action target (VKOR1) gene is the main genetic factor affecting the individual difference of warfarin dose. The mutation of these two genes can explain the 40th difference of warfarin dose. The FDA indicated in the warfarin drug instruction that patients need to test the genotypes of CYP2C9 and VKORC1 before taking warfarin, and predict the initial dose of the patients according to the genotypes, so as to shorten the time for patients to reach stable doses. Reduce the incidence of adverse reactions. Due to the large ethnic differences in warfarin doses and the large differences in doses between Chinese and Caucasian and African populations, we hope that through a large sample of retrospective clinical studies, A drug genomics model of warfarin was established for Chinese population. Due to the limited ability of known genetic factors to explain individual differences in warfarin doses and the low accuracy of existing models in predicting high and low doses of warfarin, So we hope to use the method of target region capture and sequencing in Chinese population to study the relationship between the variation and the stable dose of warfarin except CYP2C9F3 and VKORC1-1639. At the same time, a warfarin dose model suitable for high dose and low dose population was developed to reduce the incidence of adverse reactions in these high-risk populations. The main results of this study are as follows: 1. A new dose prediction model for warfarin pharmacogenomics was established. The model can explain the individual difference of warfarin dose 36.1. The prediction accuracy of the model is 56.2, in which the prediction accuracy for patients with the dose on 1.88-4mg/ day is 68.2. In this study, the extreme dose samples were sequenced through the second generation. Some new variations related to warfarin dose are presented. By using data mining method, five common classification models can be used to distinguish high-dose patients from low-dose patients, and the prediction accuracy is more than 60%.
【学位授予单位】：中南大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：R96

【共引文献】