Khan Sikandar Hayat, Fazal Nadeem, Gilani Shah Athar Abbas, Manzoor Syed Mohsin, Asif Naveed, Ijaz Aamir, Niazi Najmusaqib Khan, Yasir Muhammad
Department of Pathology, PNS Hafeez, Islamabad, Pakistan.
Department of Medicine, PNS Hafeez, Islamabad, Pakistan.
J Lipids. 2017;2017:7967380. doi: 10.1155/2017/7967380. Epub 2017 Nov 28.
Recent literature in lipidology has identified LDL-fractions to be more atherogenic. In this regard, small density LDL-cholesterol (sdLDLc) has been considered to possess more atherogenicity than other LDL-fractions like large buoyant LDL-cholesterol (lbLDLc). Recently, Srisawasdi et al. have developed a method for calculating sdLDLc and lbLDLc based upon a regression equation. Using that in developing world may provide us with a valuable tool for ASCVD risk prediction.
(1) To correlate directly measured and calculated lipid indices with insulin resistance, UACR, glycated hemoglobin, anthropometric indices, and blood pressure. (2) To evaluate these lipid parameters in subjects with or without metabolic syndrome, nephropathy, and hypertension and among various groups based upon glycated hemoglobin results.
Cross-sectional study. From Jan 2016 to 15 April 2017.
Finally enrolled subjects (male: 110, female: 122) were evaluated for differences in various lipid parameters, including measured LDL-cholesterol (mLDLc), HDLc and calculated LDL-cholesterol (cLDLc), non-HDLc, sdLDLC, lbLDLC, and their ratio among subjects with or without metabolic syndrome, nephropathy, glycation index, anthropometric indices, and hypertension.
Significant but weak correlation was mainly observed between anthropometric indices, insulin resistance, blood pressure, and nephropathy for non-HDLc, sdLDLc, and sdLDLc/lbLDLc. Generally lipid indices were higher among subjects with metabolic syndrome [{sdLDLc: 0.92 + 0.33 versus 0.70 + 0.29 ( < 0.001)}, {sdLDLc/lbLDLc: 0.55 + 0.51 versus 0.40 + 0.38 ( = 0.010)}, {non-HDLc: 3,63 + 0.60 versus 3.36 + 0.65 ( = 0.002)}]. The fact that the sdLDLc levels provided were insignificant in Kruskall Wallis Test indicated a sharp increase in subjects with HbA1c > 7.0%. Subjects having nephropathy (UACR > 2.4 mg/g) had higher concentration of non-HDLc levels in comparison to sdLDLc [{non-HDLc: 3.68 + 0.59 versus 3.36 + 0.43} ( = 0.007), {sdLDLc: 0.83 + 0.27 versus 0.75 + 0.35 ( = NS)}].
Lipid markers including cLDLc and mLDLc are less associated with traditional ASCVD markers than non-HDLc, sdLDLc, and sdLDLc/lbLDLc in predicting metabolic syndrome, nephropathy, glycation status, and hypertension.
脂质学领域的最新文献表明，低密度脂蛋白（LDL）各亚组分具有更强的致动脉粥样硬化性。在这方面，小而密低密度脂蛋白胆固醇（sdLDLc）被认为比其他LDL亚组分，如大而轻的低密度脂蛋白胆固醇（lbLDLc），具有更强的致动脉粥样硬化性。最近，Srisawasdi等人基于回归方程开发了一种计算sdLDLc和lbLDLc的方法。在发展中国家应用该方法可能为我们提供一个预测动脉粥样硬化性心血管疾病（ASCVD）风险的宝贵工具。
（1）将直接测量和计算得到的血脂指标与胰岛素抵抗、尿白蛋白肌酐比值（UACR）、糖化血红蛋白、人体测量指标和血压进行相关性分析。（2）根据糖化血红蛋白结果，评估有无代谢综合征、肾病和高血压的受试者以及不同组别的这些血脂参数。
横断面研究。时间为2016年1月至2017年4月15日。
最终纳入的受试者（男性110名，女性122名）接受了各种血脂参数差异的评估，包括测量的低密度脂蛋白胆固醇（mLDLc）、高密度脂蛋白胆固醇（HDLc）以及计算得到的低密度脂蛋白胆固醇（cLDLc）、非高密度脂蛋白胆固醇（non-HDLc）、sdLDLC、lbLDLC及其在有无代谢综合征、肾病、糖化指数、人体测量指标和高血压受试者中的比例。
非高密度脂蛋白胆固醇、sdLDLc以及sdLDLc/lbLDLc与人体测量指标、胰岛素抵抗、血压和肾病之间主要观察到显著但较弱的相关性。一般来说，代谢综合征患者的血脂指标较高[{sdLDLc：0.92 + 0.33 vs 0.70 + 0.29（<0.001）}，{sdLDLc/lbLDLc：0.55 + 0.51 vs 0.40 + 0.38（=0.010）}，{非高密度脂蛋白胆固醇：3.63 + 0.60 vs 3.36 + 0.65（=0.002）}]。在Kruskal Wallis检验中，所提供的sdLDLc水平无显著差异，这表明糖化血红蛋白>7.0%的受试者中sdLDLc水平急剧升高。患有肾病（UACR>2.4mg/g）的受试者与sdLDLc相比，非高密度脂蛋白胆固醇水平更高[{非高密度脂蛋白胆固醇：3.68 + 0.59 vs 3.36 + 0.43}（=0.007），{sdLDLc：0.83 + 0.27 vs 0.75 + 0.35（=无显著性差异）}]。
在预测代谢综合征、肾病、糖化状态和高血压方面，包括cLDLc和mLDLc在内的血脂标志物与传统ASCVD标志物的相关性低于非高密度脂蛋白胆固醇、sdLDLc和sdLDLc/lbLDLc。
