Cardiovascular Nutrition Laboratory Jean Mayer United States Department of Agriculture Human Nutrition Research Center on Aging at Tufts University Boston MA.
Tufts University School of Medicine Boston MA.
J Am Heart Assoc. 2021 Feb;10(5):e019140. doi: 10.1161/JAHA.120.019140. Epub 2021 Feb 15.
Background Elevated plasma levels of direct low-density lipoprotein cholesterol (LDL-C), small dense LDL-C (sdLDL-C), low-density lipoprotein (LDL) triglycerides, triglycerides, triglyceride-rich lipoprotein cholesterol, remnant lipoprotein particle cholesterol, and lipoprotein(a) have all been associated with incident atherosclerotic cardiovascular disease (ASCVD). Our goal was to assess which parameters were most strongly associated with ASCVD risk. Methods and Results Plasma total cholesterol, triglycerides, high-density lipoprotein cholesterol, direct LDL-C, sdLDL-C, LDL triglycerides, remnant lipoprotein particle cholesterol, triglyceride-rich lipoprotein cholesterol, and lipoprotein(a) were measured using standardized automated analysis (coefficients of variation, <5.0%) in samples from 3094 fasting subjects free of ASCVD. Of these subjects, 20.2% developed ASCVD over 16 years. On univariate analysis, all ASCVD risk factors were significantly associated with incident ASCVD, as well as the following specialized lipoprotein parameters: sdLDL-C, LDL triglycerides, triglycerides, triglyceride-rich lipoprotein cholesterol, remnant lipoprotein particle cholesterol, and direct LDL-C. Only sdLDL-C, direct LDL-C, and lipoprotein(a) were significant on multivariate analysis and net reclassification after adjustment for standard risk factors (age, sex, hypertension, diabetes mellitus, smoking, total cholesterol, and high-density lipoprotein cholesterol). Using the pooled cohort equation, many specialized lipoprotein parameters individually added significant information, but no parameter added significant information once sdLDL-C (hazard ratio, 1.42; <0.0001) was in the model. These results for sdLDL-C were confirmed by adjusted discordance analysis versus calculated non-high-density lipoprotein cholesterol, in contrast to LDL triglycerides. Conclusions sdLDL-C, direct LDL-C, and lipoprotein(a) all contributed significantly to ASCVD risk on multivariate analysis, but no parameter added significant risk information to the pooled cohort equation once sdLDL-C was in the model. Our data indicate that small dense LDL is the most atherogenic lipoprotein parameter.
背景：血浆中直接低密度脂蛋白胆固醇（LDL-C）、小而密的 LDL-C（sdLDL-C）、低密度脂蛋白（LDL）甘油三酯、甘油三酯、富含甘油三酯的脂蛋白胆固醇、残粒脂蛋白颗粒胆固醇和脂蛋白（a）的水平升高均与动脉粥样硬化性心血管疾病（ASCVD）的发生有关。我们的目标是评估哪些参数与 ASCVD 风险的相关性最强。
方法和结果：在 3094 名无 ASCVD 的空腹受试者的样本中，使用标准化自动分析（变异系数<5.0%）测量血浆总胆固醇、甘油三酯、高密度脂蛋白胆固醇、直接 LDL-C、sdLDL-C、LDL 甘油三酯、残粒脂蛋白颗粒胆固醇、富含甘油三酯的脂蛋白胆固醇和脂蛋白（a）。在这些受试者中，有 20.2%在 16 年内发生了 ASCVD。在单变量分析中，所有 ASCVD 危险因素均与 ASCVD 的发生显著相关，以及以下特殊脂蛋白参数：sdLDL-C、LDL 甘油三酯、甘油三酯、富含甘油三酯的脂蛋白胆固醇、残粒脂蛋白颗粒胆固醇和直接 LDL-C。只有 sdLDL-C、直接 LDL-C 和脂蛋白（a）在多变量分析和调整标准危险因素（年龄、性别、高血压、糖尿病、吸烟、总胆固醇和高密度脂蛋白胆固醇）后的净重新分类中具有统计学意义。使用合并队列方程，许多特殊脂蛋白参数单独提供了重要信息，但在 sdLDL-C（危险比 1.42；<0.0001）进入模型后，没有参数提供了显著的信息。sdLDL-C 的这些结果通过与计算得出的非高密度脂蛋白胆固醇相比，经过调整的不一致性分析得到了证实，而 LDL 甘油三酯则不然。
结论：sdLDL-C、直接 LDL-C 和脂蛋白（a）在多变量分析中均对 ASCVD 风险有显著贡献，但在 sdLDL-C 进入模型后，没有参数为合并队列方程提供了显著的风险信息。我们的数据表明，小而密的 LDL 是最具致动脉粥样硬化性的脂蛋白参数。
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