Cavallari Larisa H, Mason Darius L
Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL; Division of Nephrology and Hypertension, Albany Medical College, Albany, NY; and Department of Pharmacy Practice, Albany College of Pharmacy and Health Sciences, Albany, NY.
Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL; Division of Nephrology and Hypertension, Albany Medical College, Albany, NY; and Department of Pharmacy Practice, Albany College of Pharmacy and Health Sciences, Albany, NY.
Adv Chronic Kidney Dis. 2016 Mar;23(2):82-90. doi: 10.1053/j.ackd.2015.12.001.
CKD is an independent risk factor for cardiovascular disease (CVD). Thus, patients with CKD often require treatment with cardiovascular drugs, such as antiplatelet, antihypertensive, anticoagulant, and lipid-lowering agents. There is significant interpatient variability in response to cardiovascular therapies, which contributes to risk for treatment failure or adverse drug effects. Pharmacogenomics offers the potential to optimize cardiovascular pharmacotherapy and improve outcomes in patients with CVD, although data in patients with concomitant CKD are limited. The drugs with the most pharmacogenomic evidence are warfarin, clopidogrel, and statins. There are also accumulating data for genetic contributions to β-blocker response. Guidelines are now available to assist with applying pharmacogenetic test results to optimize warfarin dosing, selection of antiplatelet therapy after percutaneous coronary intervention, and prediction of risk for statin-induced myopathy. Clinical data, such as age, body size, and kidney function have long been used to optimize drug prescribing. An increasing number of institutions are also implementing genetic testing to be considered in the context of important clinical factors to further personalize drug therapy for patients with CVD.
慢性肾脏病（CKD）是心血管疾病（CVD）的独立危险因素。因此，CKD患者常需使用心血管药物进行治疗，如抗血小板药、抗高血压药、抗凝药和降脂药。患者对心血管治疗的反应存在显著个体差异，这会导致治疗失败或药物不良反应的风险增加。药物基因组学有望优化心血管药物治疗并改善CVD患者的治疗效果，尽管关于合并CKD患者的数据有限。药物基因组学证据最多的药物是华法林、氯吡格雷和他汀类药物。关于基因对β受体阻滞剂反应的影响也有越来越多的数据。现在已有指南可协助应用药物遗传学检测结果来优化华法林剂量、经皮冠状动脉介入治疗后抗血小板治疗的选择以及他汀类药物所致肌病风险的预测。临床数据，如年龄、体型和肾功能，长期以来一直用于优化药物处方。越来越多的机构也在开展基因检测，以便在重要临床因素的背景下加以考虑，从而进一步为CVD患者实现药物治疗的个体化。
