DeGorter Marianne K, Tirona Rommel G, Schwarz Ute I, Choi Yun-Hee, Dresser George K, Suskin Neville, Myers Kathryn, Zou GuangYong, Iwuchukwu Otito, Wei Wei-Qi, Wilke Russell A, Hegele Robert A, Kim Richard B
Department of Medicine, The University of Western Ontario, London, Canada.
Circ Cardiovasc Genet. 2013 Aug;6(4):400-8. doi: 10.1161/CIRCGENETICS.113.000099. Epub 2013 Jul 22.
A barrier to statin therapy is myopathy associated with elevated systemic drug exposure. Our objective was to examine the association between clinical and pharmacogenetic variables and statin concentrations in patients.
In total, 299 patients taking atorvastatin or rosuvastatin were prospectively recruited at an outpatient referral center. The contribution of clinical variables and transporter gene polymorphisms to statin concentration was assessed using multiple linear regression. We observed 45-fold variation in statin concentration among patients taking the same dose. After adjustment for sex, age, body mass index, ethnicity, dose, and time from last dose, SLCO1B1 c.521T>C (P<0.001) and ABCG2 c.421C>A (P<0.01) were important to rosuvastatin concentration (adjusted R(2)=0.56 for the final model). Atorvastatin concentration was associated with SLCO1B1 c.388A>G (P<0.01) and c.521T>C (P<0.05) and 4β-hydroxycholesterol, a CYP3A activity marker (adjusted R(2)=0.47). A second cohort of 579 patients from primary and specialty care databases were retrospectively genotyped. In this cohort, genotypes associated with statin concentration were not differently distributed among dosing groups, implying providers had not yet optimized each patient's risk-benefit ratio. Nearly 50% of patients in routine practice taking the highest doses were predicted to have statin concentrations greater than the 90th percentile.
Interindividual variability in statin exposure in patients is associated with uptake and efflux transporter polymorphisms. An algorithm incorporating genomic and clinical variables to avoid high atorvastatin and rosuvastatin levels is described; further study will determine whether this approach reduces incidence of statin myopathy.
他汀类药物治疗的一个障碍是与全身药物暴露增加相关的肌病。我们的目标是研究患者临床和药物遗传学变量与他汀类药物浓度之间的关联。
在一家门诊转诊中心前瞻性招募了总共299名服用阿托伐他汀或瑞舒伐他汀的患者。使用多元线性回归评估临床变量和转运体基因多态性对他汀类药物浓度的贡献。我们观察到服用相同剂量的患者中他汀类药物浓度存在45倍的差异。在调整性别、年龄、体重指数、种族、剂量和末次给药时间后,SLCO1B1 c.521T>C(P<0.001)和ABCG2 c.421C>A(P<0.01)对瑞舒伐他汀浓度很重要(最终模型的调整R² = 0.56)。阿托伐他汀浓度与SLCO1B1 c.388A>G(P<0.01)、c.521T>C(P<0.05)以及CYP3A活性标志物4β-羟基胆固醇相关(调整R² = 0.47)。对来自初级和专科护理数据库的579名患者的第二个队列进行了回顾性基因分型。在这个队列中,与他汀类药物浓度相关的基因型在给药组之间分布没有差异,这意味着医疗服务提供者尚未优化每位患者的风险效益比。在常规实践中,近50%服用最高剂量的患者预计他汀类药物浓度高于第90百分位数。
患者中他汀类药物暴露的个体间变异性与摄取和外排转运体多态性有关。描述了一种纳入基因组和临床变量以避免阿托伐他汀和瑞舒伐他汀高水平的算法;进一步的研究将确定这种方法是否能降低他汀类药物肌病的发生率。