Cholesterol Efflux Capacity, High-Density Lipoprotein Particle Number, and Incident Cardiovascular Events: An Analysis From the JUPITER Trial (Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin).
Cholesterol Efflux Capacity, High-Density Lipoprotein Particle Number, and Incident Cardiovascular Events: An Analysis From the JUPITER Trial (Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin).
复制标题
DOI：
10.1161/circulationaha.116.025678
复制
发表时间：
2017-06-20
期刊：
影响因子：
37.8
通讯作者：
Mora S
中科院分区：
文献类型：
--
作者：
Khera AV;Demler OV;Adelman SJ;Collins HL;Glynn RJ;Ridker PM;Rader DJ;Mora S
最近，在临床试验中，提高高密度脂蛋白胆固醇水平以减少心血管事件的药物失败，导致人们对高密度脂蛋白质量的替代指标，如胆固醇流出能力和高密度脂蛋白数量，如高密度脂蛋白颗粒数量，产生了越来越大的兴趣。然而，没有研究在当代人群中直接比较这些指标，包括有效的他汀类药物治疗和低密度脂蛋白胆固醇。在JUPITER试验的嵌套病例对照研究中，在基线和12个月时评估了高密度脂蛋白胆固醇水平、载脂蛋白A-I(apoA-I)、胆固醇外流能力和高密度脂蛋白颗粒数量。JUPITER试验是一项随机一级预防试验，在低密度脂蛋白水平正常但C反应蛋白水平升高的患者中，比较了瑞舒伐他汀治疗和安慰剂治疗。将314例心血管疾病(心肌梗死、不稳定型心绞痛、动脉血运重建、中风或心血管死亡)与年龄和性别匹配的对照组进行比较。调整危险因素的条件Logistic回归模型评估了高密度脂蛋白相关生物标记物和心血管事件之间的关联。胆固醇流出能力与高密度脂蛋白、载脂蛋白A-I和高密度脂蛋白颗粒数呈中度相关(Spearman相关系数分别为0.39、0.48和0.39；P<；0.001)。基线高密度脂蛋白颗粒数与心血管事件呈负相关(调整后每SD增量的优势比[OR/SD]0.69；95%CI 0.56-0.86；p<；0.001)，而与基线胆固醇流出能力(OR/SD 0.89；95%CI 0.72-1.10；p=0.28)、高密度脂蛋白胆固醇(OR/SD 0.82；95%CI 0.66-1.02；P=0.08)或载脂蛋白A-I(OR/SD 0.83；95%CI 0.67-1.03；P=0.08)。服用12个月的瑞舒伐他汀(20 mg/d)不改变胆固醇流出能力(平均百分比改变−1.5%，95%CI−13.3至+10.2；p=0.80)，但增加高密度脂蛋白胆固醇(+7.7%)、载脂蛋白A-I(+4.3%)和高密度脂蛋白颗粒数(+5.2%)。尽管高密度脂蛋白颗粒数再次成为最强的预测因子(OR/SD0.51；95%CI0.33-0.77；p<；0.001)，但他汀类胆固醇流出能力与心血管事件呈负相关(OR/SD0.62；95%CI0.42-0.92；p=0.02)。在JUPITER，服用有效他汀类药物的个体中，胆固醇流出能力与心血管事件相关，但与基线无关。对于基线和他汀类药物分析，高密度脂蛋白颗粒数是四个与高密度脂蛋白相关的生物标志物中最强的，作为事件发生的反向预测因子和残留风险的生物标志物。网址：http://www.clinicaltrials.gov.唯一标识：NCT00239681。
Recent failures of drugs that raised high-density lipoprotein (HDL) cholesterol levels to reduce cardiovascular events in clinical trials have led to increased interest in alternative indices of HDL quality, such as cholesterol efflux capacity, and HDL quantity, such as HDL particle number. However, no studies have directly compared these metrics in a contemporary population that includes potent statin therapy and low LDL cholesterol. HDL cholesterol levels, apolipoprotein A-I (apoA-I), cholesterol efflux capacity, and HDL particle number were assessed at baseline and 12 months in a nested case-control study of the JUPITER trial, a randomized primary prevention trial that compared rosuvastatin treatment to placebo in individuals with normal LDL cholesterol but increased C-reactive protein levels. 314 cases of incident cardiovascular disease (myocardial infarction, unstable angina, arterial revascularization, stroke, or cardiovascular death) were compared to age- and gender-matched controls. Conditional logistic regression models adjusting for risk factors evaluated associations between HDL-related biomarkers and incident CVD. Cholesterol efflux capacity was moderately correlated with HDL cholesterol, apoA-I, and HDL particle number (Spearman r= 0.39, 0.48, and 0.39 respectively; P<0.001). Baseline HDL particle number was inversely associated with incident CVD (adjusted odds ratio per SD increment [OR/SD] 0.69; 95%CI 0.56 – 0.86; p< 0.001), while no significant association was found for baseline cholesterol efflux capacity (OR/SD 0.89; 95%CI 0.72–1.10; p=0.28), HDL cholesterol (OR/SD 0.82; 95%CI 0.66–1.02; P = 0.08), or apoA-I (OR/SD 0.83; 95%CI 0.67–1.03; p=0.08). 12 months of rosuvastatin (20mg/day) did not change cholesterol efflux capacity (average percent change −1.5%, 95%CI −13.3 to +10.2; p=0.80), but increased HDL cholesterol (+7.7%), apoA-I (+4.3%), and HDL particle number (+5.2%). On-statin cholesterol efflux capacity was inversely associated with incident CVD (OR/SD 0.62; 95%CI 0.42–0.92; p=0.02), although HDL particle number again emerged as the strongest predictor (OR/SD 0.51; 95%CI 0.33–0.77; p< 0.001). In JUPITER, cholesterol efflux capacity was associated with incident CVD in individuals on potent statin therapy but not at baseline. For both baseline and on-statin analyses, HDL particle number was the strongest of four HDL-related biomarkers as an inverse predictor of incident events and biomarker of residual risk. URL: http://www.clinicaltrials.gov. Unique identifier: NCT00239681.