Correlation between Cholesterol, Triglycerides, Calculated, and Measured Lipoproteins: Whether Calculated Small Density Lipoprotein Fraction Predicts Cardiovascular Risks

Abstract

Background 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. Objective (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. Design Cross-sectional study. Place and Duration of Study. From Jan 2016 to 15 April 2017. Subjects and Methods 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. Results 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 (p < 0.001)}, {sdLDLc/lbLDLc: 0.55 + 0.51 versus 0.40 + 0.38 (p = 0.010)}, {non-HDLc: 3,63 + 0.60 versus 3.36 + 0.65 (p = 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} (p = 0.007), {sdLDLc: 0.83 + 0.27 versus 0.75 + 0.35 (p = NS)}]. Conclusion 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.

Prediction and Elucidation of Triglycerides Levels Using a Machine Learning and Linear Fuzzy Modelling Approach

“…The training dataset will be used to construct the model, while the validation dataset will be used to verify it. The Waist, HDL, and blood pressure status all have a significant effect on triglycerides, according to a multilayer perceptron analysis, and these results are in line with the recent study done on elderly Japanese men [ 14 ], concluding that triglycerides are positively associated with blood pressure and with hypertension [ 15 ].…”

Structural Equation Modelling for Predicting the Relative Contribution of Each Component in the Metabolic Syndrome Status Change

“…Indeed, the pathogenesis of MetS remains unclear, and several other components have been shown to have higher sensitivity and specificity for predicting MetS [27,64]. Nonetheless, the harmonised definition seems to have left out some important adjustments to the variables that report on each MetS component such as the waist-to-height ratio [64], waistto-hip ratio [65], mean arterial pressure [66] and LDL levels [67], all of which have been reported as better screening criteria for MetS. BMI has been previously considered in AACE and IDF definitions and retains its usefulness as an alternative parameter for the assessment of central obesity [23,24].…”

Small Dense Low-Density Lipoprotein as Risk Factor for Atherosclerosis in Type 2 Diabetes Mellitus

“…Although our study was limited for the T2DM subjects with normal lipid profile, within normal ranges, we observed the same pattern of changes in lipid profile parameters as it can be observed in diabetic dyslipidemia, which is associated with high levels of TG, total cholesterol, LDL and low levels of HDL along with predominant sdLDL-C 13,14 . High levels of sdLDL-C in T2DM is a major complication of diabetes that can induce atherosclerosis in diabetic patients 6,15,16 . In the present study, high sdLDL-C levels indicate that T2DM patients may have atherogenic risk despite the lipid profile within a normal range.…”

“…SdLDL also induces thickness in intima-media of blood vessels and numbers of sdLDL particles are associated with insulin resistance in T2DM 22 . Glycation rates are associated with increased atherosclerosis, morbidity and mortality in cardiovascular diseases (CVD) 6 . In this regard, our study (which did not include any dyslipidemic patient) demonstrated that there is a strong positive correlation between glycemic status and sdLDL-C in T2DM patients that may contribute for the induction of atherosclerosis and may lead towards CVD.…”

“…large buoyant LDL-C (lbLDL-C) and small dense LDL-C (sdLDL-C). SdLDL-C is highly atherogenic than lbLDL-C 6 . Elevated levels of sdLDL-C are closely associated with coronary artery disease (CAD) and it is an accepted risk factor for…”