Identification and cholesterol quantification of low density lipoprotein subclasses in young adults by VAP-II methodology

Measurement of cholesterol levels of lipoprotein subclasses in human serum using anion-exchange high-performance liquid chromatography with a linear concentration gradient of sodium perchlorate

BACKGROUND

Relationships between the subclasses of high-density lipoprotein (HDL) or low-density lipoprotein (LDL) and the risk of atherosclerotic cardiovascular disease have been studied, and using various methods, such as ultracentrifugation, electrophoresis, and nuclear magnetic resonance, for analysing lipoprotein subclasses. We established a method for HDL and LDL subclasses using anion-exchange high-performance liquid chromatography (AEX-HPLC) with a linear concentration gradient of sodium perchlorate (NaClO4).

METHOD

In the AEX-HPLC, the subclasses of HDL and LDL were separated, and detected using a post-column reactor with an enzymatic cholesterol reagent, that contained cholesterol esterase, cholesterol oxidase, and peroxidase as major ingredients. LDL subclasses were divided based on the absolute value of first-derivative chromatogram.

RESULT

Three HDL subclasses, HDL-P1, HDL-P2, and HDL-P3, and three LDL subclasses, LDL-P1, LDL-P2, and LDL-P3, were separated by AEX-HPLC, and detected in order. The major components of HDL-P2 and HDL-P3 were HDL3 and HDL2, respectively. The linearity was determined for each lipoprotein subclass. The coefficients of variation of cholesterol concentration of the subclasses for within-day assay (n = 10) and between-day assay (n = 10) ranged between 3.08-8.94% and 4.52-9.97%, respectively. Cholesterol levels in HDL-P1 of diabetic patients were positively correlated with oxidized LDL levels (r = 0.409, p = 0.002). Moreover, cholesterol levels in LDL-P2 and LDL-P3 were positively correlated with oxidized LDL levels (r = 0.393, p = 0.004 and r = 0.561, p < 0.001, respectively).

CONCLUSION

AEX-HPLC may be highly suitable as an assay to clinically assess lipoprotein subclasses.

Accuracy of 23 Equations for Estimating LDL Cholesterol in a Clinical Laboratory Database of 5,051,467 Patients

Background

Alternatives to the Friedewald low-density lipoprotein cholesterol (LDL-C) equation have been proposed.

Objective

To compare the accuracy of available LDL-C equations with ultracentrifugation measurement.

Methods

We used the second harvest of the Very Large Database of Lipids (VLDbL), which is a population-representative convenience sample of adult and pediatric patients (N = 5,051,467) with clinical lipid measurements obtained via the vertical auto profile (VAP) ultracentrifugation method between October 1, 2015 and June 30, 2019. We performed a systematic literature review to identify available LDL-C equations and compared their accuracy according to guideline-based classification. We also compared the equations by their median error versus ultracentrifugation. We evaluated LDL-C equations overall and stratified by age, sex, fasting status, and triglyceride levels, as well as in patients with atherosclerotic cardiovascular disease, hypertension, diabetes, kidney disease, inflammation, and thyroid dysfunction.

Results

Analyzing 23 identified LDL-C equations in 5,051,467 patients (mean±SD age, 56±16 years; 53.3% women), the Martin/Hopkins equation most accurately classified LDL-C to the correct category (89.6%), followed by the Sampson (86.3%), Chen (84.4%), Puavilai (84.1%), Delong (83.3%), and Friedewald (83.2%) equations. The other 17 equations were less accurate than Friedewald, with accuracy as low as 35.1%. The median error of equations ranged from -10.8 to 18.7 mg/dL, and was best optimized using the Martin/Hopkins equation (0.3, IQR-1.6 to 2.4 mg/dL). The Martin/Hopkins equation had the highest accuracy after stratifying by age, sex, fasting status, triglyceride levels, and clinical subgroups. In addition, one in five patients who had Friedewald LDL-C <70 mg/dL, and almost half of the patients with Friedewald LDL-C <70 mg/dL and triglyceride levels 150-399 mg/dL, had LDL-C correctly reclassified to >70 mg/dL by the Martin/Hopkins equation.

Conclusions

Most proposed alternatives to the Friedewald equation worsen LDL-C accuracy, and their use could introduce unintended disparities in clinical care. The Martin/Hopkins equation demonstrated the highest LDL-C accuracy overall and across subgroups.

Lipid analysis by ion mobility spectrometry combined with mass spectrometry: A brief update with a perspective on applications in the clinical laboratory

Ion mobility spectrometry (IMS) is an analytical technique where ions are separated in the gas phase based on their mobility through a buffer gas in the presence of an electric field. An ion passing through an IMS device has a characteristic collisional cross section (CCS) value that depends on the buffer gas used. IMS can be coupled with mass spectrometry (MS), which characterizes an ion based on a mass-to-charge ratio (m/z), to increase analytical specificity and provide further physicochemical information. In particular, IMS-MS is of ever-increasing interest for the analysis of lipids, which can be problematic to accurately identify and quantify in bodily fluids by liquid chromatography (LC) with MS alone due to the presence of isomers, isobars, and structurally similar analogs. IMS provides an additional layer of separation when combined with front-end LC approaches, thereby, enhancing peak capacity and analytical specificity. CCS (and also ion mobility drift time) can be plotted against m/z ion intensity and/or LC retention time in order to generate in-depth molecular profiles of a sample. Utilization of IMS-MS for routine clinical laboratory testing remains relatively unexplored, but areas do exist for potential implementation. A brief update is provided here on lipid analysis using IMS-MS with a perspective on some applications in the clinical laboratory.

Association of cardiovascular events and lipoprotein particle size: Development of a risk score based on functional data analysis

BACKGROUND

Functional data is data represented by functions (curves or surfaces of a low-dimensional index). Functional data often arise when measurements are collected over time or across locations. In the field of medicine, plasma lipoprotein particles can be quantified according to particle diameter by ion mobility.

GOAL

We wanted to evaluate the utility of functional analysis for assessing the association of plasma lipoprotein size distribution with cardiovascular disease after adjustment for established risk factors including standard lipids.

METHODS

We developed a model to predict risk of cardiovascular disease among participants in a case-cohort study of the Malmö Prevention Project. We used a linear model with 311 coefficients, corresponding to measures of lipoprotein mass at each of 311 diameters, and assumed these coefficients varied smoothly along the diameter index. The smooth function was represented as an expansion of natural cubic splines where the smoothness parameter was chosen by assessment of a series of nested splines. Cox proportional hazards models of time to a first cardiovascular disease event were used to estimate the smooth coefficient function among a training set consisting of one half of the participants. The resulting model was used to calculate a functional risk score for the remaining half of the participants (test set) and its association with events was assessed in Cox models that adjusted for traditional cardiovascular risk factors.

RESULTS

In the test set, participants with a functional risk score in the highest quartile were found to be at increased risk of cardiovascular events compared with the lowest quartile (Hazard ratio = 1.34; 95% Confidence Interval: 1.05 to 1.70) after adjustment for established risk factors.

CONCLUSION

In an independent test set of Malmö Prevention Project participants, the functional risk score was found to be associated with cardiovascular events after adjustment for traditional risk factors including standard lipids.

Advanced lipoprotein testing for cardiovascular diseases risk assessment: a review of the novel approaches in lipoprotein profiling

With the increasing prevalence of cardiovascular diseases (CVD) worldwide, finding reliable and clinically relevant biomarkers to predict acute cardiovascular events has been a major aim of the scientific and medical community. Improvements of the understanding of the pathophysiological pathways of the disease highlighted the major role of lipoprotein particles, and these past decades have seen the emergence of a number of new methodologies to separate, measure and quantitate lipoproteins. Those methods, also known as advanced lipoprotein testing methods (ALT), have gained acceptance in the field of CVD risk assessment and have proven their clinical relevance. In the context of worldwide standardization and harmonization of biological assays, efforts have been initiated toward standardization of ALT methods. However, the complexity of lipoprotein particles and the multiple approaches and methodologies reported to quantify them have rendered these initiatives a critical issue. In this context and to better understand these challenges, this review presents a summary of the major methods available for ALT with the aim to point out the major differences in terms of procedures and quantities actually measured and to discuss the resulting comparability issues.

Toward Reliable Lipoprotein Particle Predictions from NMR Spectra of Human Blood: An Interlaboratory Ring Test

Lipoprotein profiling of human blood by ¹H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states in medicine and nutrition. However, lack of standardization of measurement protocols has prevented the use of NMR-based lipoprotein profiling in metastudies. In this study, a standardized NMR measurement protocol was applied in a ring test performed across three different laboratories in Europe on plasma and serum samples from 28 individuals. Data was evaluated in terms of (i) spectral differences, (ii) differences in LPD predictions obtained using an existing prediction model, and (iii) agreement of predictions with cholesterol concentrations in high- and low-density lipoproteins (HDL and LDL) particles measured by standardized clinical assays. ANOVA-simultaneous component analysis (ASCA) of the ring test spectral ensemble that contains methylene and methyl peaks (1.4–0.6 ppm) showed that 97.99% of the variance in the data is related to subject, 1.62% to sample type (serum or plasma), and 0.39% to laboratory. This interlaboratory variation is in fact smaller than the maximum acceptable intralaboratory variation on quality control samples. It is also shown that the reproducibility between laboratories is good enough for the LPD predictions to be exchangeable when the standardized NMR measurement protocol is followed. With the successful implementation of this protocol, which results in reproducible prediction of lipoprotein distributions across laboratories, a step is taken toward bringing NMR more into scope of prognostic and diagnostic biomarkers, reducing the need for less efficient methods such as ultracentrifugation or high-performance liquid chromatography (HPLC).

Comparison of four methods of analysis of lipoprotein particle subfractions for their association with angiographic progression of coronary artery disease

BACKGROUND

Compare gradient gel electrophoresis (GGE), vertical auto profile ultracentrifugation (VAP-II), nuclear magnetic resonance spectroscopy (NMR), and ion mobility for their ability to relate low- (LDL), intermediate- (IDL), very-low-density (VLDL) and high-density lipoprotein (HDL) subfraction concentrations to atherosclerotic progression.

METHODS AND RESULTS

Regression analyses of 136 patients who received baseline and follow-up coronary angiographies and subfraction measurements by all four methods in the HDL Atherosclerosis Treatment Study. Prior analyses have shown that the intervention primarily affected disease progression in proximal arteries with <30% stenoses at baseline. Three-year increases in percent stenoses were consistently associated with higher on-study plasma concentrations of small, dense LDL as measured by GGE (LDLIIIb, P=10(-6); LDLIVa, P=0.006; LDLIVb, P=0.02), VAP-II (LDL4, P=0.002), NMR (small LDL, P=0.001), and ion mobility (LDL IIb, P=0.04; LDLIIIa, P=0.002; LDLIIIb, P=0.0007; LDLIVa, P=0.05). Adjustment for triglycerides, HDL-cholesterol, and LDL-cholesterol failed to eliminate the statistical significance for on-study GGE estimated LDLIIIb (P=10(-5)) and LDLIVa (P=0.04); NMR-estimated small LDL (P=0.03); or ion mobility estimated large VLDL (P=0.02), LDLIIIa (P=0.04) or LDLIIIb (P=0.02). All methods show that the effects were significantly greater for the on-study than the baseline small, dense LDL concentrations, thus establishing that the values concurrent to the progression of disease were responsible. The rate of disease progression was also related to individual VLDL, IDL, and HDL subclasses to differing extents among the various analytic methods.

CONCLUSION

Four methodologies confirm the association of small, dense LDL with greater coronary atherosclerosis progression, and GGE, NMR, and ion mobility confirm that the associations were independent of standard lipid measurements.

CLINICAL TRIAL REGISTRATION

clinicaltrials.gov/ct2/show/NCT00000553.

HDL-cholesterol in coronary artery disease risk: function or structure?

High-density lipoproteins (HDL) are inversely related with coronary artery disease (CAD) and HDL-cholesterol is the only standardized and reproducible parameter available to estimate plasma concentration of these lipoproteins. However, pharmacological interventions intended to increase HDL-cholesterol have not been consistently associated to an effective CAD risk reduction. Among patients with a myocardial infarction, 43 and 44% of men and women, respectively, had normal plasma levels of HDL-cholesterol, whereas genetic studies have failed to show a causal association between HDL-cholesterol and CAD risk. Instead, HDL functionality seems to be the target to be evaluated, but the existing methods are still poorly reproducible and far to be adapted to the clinical laboratory. HDL subclasses rise as a potential alternative for the evaluation of CAD risk; HDL subclasses are a surrogate of intravascular metabolism of these lipoproteins and probably of their functionality. Low levels of large HDL and increased proportions of small particles are the most remarkable features associated to an increased risk of type 2 diabetes mellitus (T2DM) or CAD. However, inflammation and other environmental factors are related with abnormal HDL structure, and, as a consequence, more prospective studies are needed to better support the clinical usefulness of HDL subclasses. New insights from proteome and lipidome profiles of HDL will provide potential HDL-related biomarkers in the coming years.

Association of lipoprotein subfractions and coronary artery calcium in patient at intermediate cardiovascular risk

More precise estimation of the atherogenic lipid parameters could improve identification of residual risk beyond what is possible using traditional lipid risk factors. The aim of the present study was to explore the association between advanced analysis of lipoprotein subfractions and the prevalence of coronary artery calcium. Consecutive participants at intermediate cardiovascular risk who were undergoing computed tomographic assessment of coronary calcium (calcium score) were included. Using a validated ultracentrifugation method (the vertical autoprofile II test), cholesterol in eluting lipoprotein subfractions [i.e., low- (LDL), very-low-, intermediate-, and high-density lipoprotein subclasses, lipoprotein (a), and predominant LDL distribution] was directly quantified. A total of 410 patients were included (29% women, mean age 57 years), of whom 297 (72.4%) had coronary artery calcium. LDL pattern B (predominance of small dense particles) emerged as an independent predictor of coronary calcium after adjustment for traditional risk factors (odds ratio 4.46, 95% confidence interval 1.19 to 16.7). However, after additional stratification for dyslipidemia, as defined by conventional lipid profiling, a statistically significant prediction was only retained for high-density lipoprotein subfraction 2 (odds ratio 3.45, 95% confidence interval 2.03 to 50.1) and "real" LDL (odds ratio 6.10, 95% confidence interval 1.26 to 23.41) in the normolipidemia group and for lipoprotein (a) (odds ratio 7.81, 95% confidence interval 1.41 to 43.5) in the dyslipidemic group. In conclusion, advanced assessment of the lipoprotein subfractions [i.e., LDL pattern B, high-density lipoprotein subfraction 2, "real" LDL, and lipoprotein (a)] using the vertical autoprofile II test provided additional information to that of conventional risk factors on the prevalence of coronary artery calcium in patients at intermediate cardiovascular risk.

Contribution of diet and physical activity to metabolic parameters among survivors of childhood leukemia

PURPOSE

Determine the relationship between diet and metabolic abnormalities among adult survivors of childhood acute lymphoblastic leukemia (ALL).

METHODS

We surveyed 117 adult survivors of childhood ALL using the Harvard Food Frequency Questionnaire. Physical activity energy expenditure (PAEE) was measured with the SenseWear Pro2 Armband. Insulin resistance was estimated using the Homeostasis Model for Insulin Resistance (HOMA-IR). Visceral and subcutaneous adiposity were measured by abdominal CT. Adherence to a Mediterranean diet pattern was calculated using the index developed by Trichopoulou. Subjects were compared using multivariate analysis adjusted for age and gender.

RESULTS

Greater adherence to a Mediterranean diet pattern was associated with lower visceral adiposity (p = 0.07), subcutaneous adiposity (p < 0.001), waist circumference (p = 0.005), and body mass index (p = 0.04). For each point higher on the Mediterranean Diet Score, the odds of having the metabolic syndrome fell by 31 % (OR 0.69; 95 % CI 0.50, 0.94; p = 0.019). Higher dairy intake was associated with higher HOMA-IR (p = 0.014), but other individual components of the Mediterranean diet, such as low intake of meat or high intake of fruits and vegetables, were not significant. PAEE was not independently associated with metabolic outcomes, although higher PAEE was associated with lower body mass index.

CONCLUSIONS

Adherence to a Mediterranean diet pattern was associated with better metabolic and anthropometric parameters in this cross-sectional study of ALL survivors.

Atherogenic low density lipoprotein phenotype in long-term survivors of childhood acute lymphoblastic leukemia

Survivors of childhood acute lymphoblastic leukemia (ALL) have an increased risk of cardiovascular disease. Small density lipoproteins are atherogenic but have not been studied in this population. We conducted a cross-sectional analysis of 110 ALL survivors (mean age, 24.3 years) to determine prevalence of small dense LDL (pattern B) phenotype in ALL survivors and identify associated factors. Lipid subfractions were measured using Vertical Auto Profile-II. Participants with greater than 50% of LDL-cholesterol (LDL-c) in small dense LDL fractions (LDL(3+4)) were classified as LDL pattern B. Visceral and subcutaneous adipose tissue (VAT, SAT) volumes were also measured by computed tomography. While the mean LDL-c level of ALL survivors was 108.7 ± 26.8 mg/dl, 36% (40/110) of survivors had atherogenic LDL pattern B. This pattern was more common in males (26/47; 55%) than in females (14/63; 22%, P = 0.001) and more common in survivors treated with cranial radiotherapy (15/33; 45%) than in those who were treated with chemotherapy alone (25/77; 33%; P = 0.04, adjusted for age, gender, history of hypertension, and smoking history). VAT was associated with atherogenic lipids: LDL pattern B and LDL(3+4) levels. This association was independent of other measures of body fat. We conclude that a substantial proportion of ALL survivors had an atherogenic LDL phenotype despite normal mean LDL-c levels. An atherogenic LDL phenotype may contribute to the increase in cardiovascular mortality and morbidity in this population.

Estimation of the low-density lipoprotein (LDL) subclass phenotype using a direct, automated assay of small dense LDL-cholesterol without sample pretreatment

BACKGROUND

A new method (sLDL-EX "SEIKEN") is commercially available for the direct quantification of small dense LDL-cholesterol (sd-LDL) on automated chemistry analyzers, without manual sample pretreatment. We evaluated the performance of this direct assay to estimate the small dense LDL subclass phenotype ("non-A"), defined by polyacrylamide gel tube electrophoresis.

METHODS

Fasting serum samples from 189 healthy subjects (age 18-75y, 96 females) were collected. The direct sd-LDL assay (from Randox Laboratories) was applied on a Roche Modular P analyzer. The Quantimetrix Lipoprint(TM) LDL System was used to define LDL subclass phenotypes (A and non-A). ROC curve analysis was performed for sd-LDL and other lipids and apolipoproteins (apo) with respect to phenotype non-A.

RESULTS

sd-LDL concentrations (40.4+/-18.6mg/dl) in the total group correlated (P<0.0001) with apoB (r=0.831), apoB/A-I ratio (r=0.757), non-HDL-cholesterol (r=0.821), triglycerides (r=0.439), and LDL-cholesterol (r=0.641). Higher sd-LDL concentrations (P<0.0001) were measured in subjects with LDL phenotype non-A (53.6+/-17.0mg/dl, n=92) than in those with phenotype A (27.9+/-8.9mg/dl, n=97). In logistic regression analysis, sd-LDL and apoA-I were independently associated with LDL subclass phenotype non-A. Highest areas under ROC curves were obtained for sd-LDL (0.943), triglycerides (0.833), triglyceride/HDL-cholesterol (0.838) and apoB/A-I ratio (0.826) to predict phenotype non-A. The sd-LDL cut-off point for optimal sensitivity (87.9%) and specificity (92.8%) was >38.5mg/dl.

CONCLUSIONS

The direct, homogeneous sd-LDL method is easily applicable on an automated chemistry analyzer and shows acceptable performance to estimate the electrophoretic LDL subclass phenotype.

Anthropometric correlates of lipoprotein profile and blood pressure in high BMI African American children

OBJECTIVE

To explore the association of anthropometric indices with lipoprotein profile and blood pressure as risk factors of cardiovascular disease, in African American (AA) children.

METHODS

A cross-sectional analysis was carried out on children aged 9-13 years with BMI >85th percentile. Height, weight, waist and hip circumferences, % body fat and blood pressure [systolic (sBP) and diastolic (dBP)] were measured. Fasting plasma levels of triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), intermediate density lipoprotein cholesterol (IDL-C) and very low-density lipoprotein cholesterol (VLDL-C) were analysed.

RESULTS

After accounting for age, gender and pubertal status of the child, multiple linear regression models showed that waist circumference and BMIz were strong predictors for lipoprotein variables. In independent analysis, waist circumference and BMI z-scores were found to be interdependently associated with TG, LDL-C:HDL-C ratio, VLDL-C and sBPz. However, for HDL-C, TG:HDL-C ratio and dBPz, waist circumference was independently and more strongly associated with these risk factors than BMI.

CONCLUSION

Waist circumference was a stronger predictor for lipoprotein variables and blood pressure in high BMI AA children than other anthropometric indices, and may be adequate as a screening test to identify children who are at increased risk for cardiovascular disease.

Relationship of low-density lipoprotein (LDL) particle size to thyroid function status in Koreans

OBJECTIVE

Dyslipidaemia is a well-known manifestation of thyroid dysfunction. Recently, small low-density lipoprotein (LDL) particle size has been linked with development of cardiovascular disease. To better understand the effects of thyroid dysfunction on the development of cardiovascular disease, we examined LDL particle size and lipid profiles in subjects with different thyroid function.

METHODS

Included were 46 patients with overt hypothyroidism, 57 patients with subclinical hypothyroidism, 46 patients with overt hyperthyroidism, 51 patients with subclinical hyperthyroidism, and 110 age- and sex-matched healthy control subjects. We measured LDL particle size and lipid profiles in these subjects.

RESULTS

No significant differences were found in LDL particle size between the groups with different thyroid function. Serum total cholesterol and LDL-cholesterol levels were significantly higher in the cases of hypothyroidism than in the cases of hyperthyroidism and the healthy control subjects. Serum triglyceride levels were higher in subjects with overt hypothyroidism than in those with overt hyperthyroidism or healthy control subjects.

CONCLUSIONS

LDL particle size, the emerging risk factor for atherosclerosis, did not appear to be significantly affected by the degree of thyroid dysfunction. Increased risk of atherosclerosis in hypothyroidism does not appear to be associated with LDL particle size, the non-traditional cardiovascular risk factor.

Effects of fenofibrate and ezetimibe, both as monotherapy and in coadministration, on cholesterol mass within lipoprotein subfractions and low-density lipoprotein peak particle size in patients with mixed hyperlipidemia

Coadministration of fenofibrate and ezetimibe (FENO + EZE) produced complementary and favorable effects on the major lipids and lipoproteins, low-density lipoprotein cholesterol (LDL-C), triglycerides, high-density lipoprotein cholesterol (HDL-C), and non-HDL-C levels, and was well tolerated in patients with mixed hyperlipidemia. The current analysis evaluates the effects of FENO and EZE, as monotherapies and in coadministration, on lipoprotein subfractions and LDL particle size distributions in these patients. In a 12-week, multicenter, randomized, double-blind, placebo-controlled, parallel-group study, patients with mixed hyperlipidemia were randomized in a 1:3:3:3 ratio to one of 4 treatment groups: placebo, FENO 160 mg/day, EZE 10 mg/day, or FENO 160 mg/day + EZE 10 mg/day. At baseline and study end point, the Vertical Auto Profile II method was used to measure the cholesterol associated with 2 very low-density lipoprotein (VLDL) subfractions (VLDL-C1 + 2 and VLDL-C3), intermediate-density lipoproteins (IDL-C), and 4 LDL subfractions (LDL-C1 through LDL-C4, from most buoyant to most dense), lipoprotein (Lp) (a), and 2 HDL-C subfractions (HDL-C2 and HDL-C3). The LDL particle size was determined using segmented gradient gel electrophoresis. Fenofibrate reduced cholesterol mass within VLDL, IDL, and dense LDL (primarily LDL-C4) subfractions, and increased cholesterol mass within the more buoyant LDL-C2 subfraction, consistent with a shift to a more buoyant LDL peak particle size. Ezetimibe reduced cholesterol mass within all of the apolipoprotein B-containing particles (eg, VLDL-C, IDL-C, and LDL-C) but did not lead to a shift in the LDL particle size distribution profile. Coadministration of FENO and EZE promoted more pronounced reductions in VLDL-C, IDL-C, and LDL-C, and a preferential decrease in dense LDL subfractions. Fenofibrate and FENO + EZE promoted similar increases in HDL-C2 and HDL-C3. Coadministration of FENO + EZE produced complementary and favorable changes in lipoprotein fractions and subfractions, as assessed by the Vertical Auto Profile II method, in patients with mixed hyperlipidemia. These changes reflected the combined effects of FENO in reducing triglycerides-rich lipoproteins and promoting a shift in the LDL particle distribution profile toward larger, more buoyant particles and of EZE in promoting reductions in cholesterol mass across the apolipoprotein B particle spectrum.

Small, dense low-density lipoprotein and C-reactive protein in obese subjects with and without other criteria for the metabolic syndrome

BACKGROUND

Although obesity is an important cardiovascular risk factor, growing evidence shows that a substantial portion of obese subjects can be considered metabolically healthy but obese (MHO). However the extent to which obese subjects manifest small, dense low-density lipoprotein (LDL) particles without other characteristics of the metabolic syndrome (MS) remains unknown.

OBJECTIVE

The purpose of this study was to determine the difference between MHO (only meeting the obesity criteria) and obese subjects meeting all the criteria for the MS with regard to LDL size and high-sensitivity C-reactive protein (hs-CRP), as a biomarker of inflammation.

METHODS

Two hundred obese subjects (168 women, mean age 36.5 ± 5 years [range, 20-60]; mean body mass index [BMI; calculated as kg/m(2)] 39 ± 5 [range, 30-80.4]) were studied for LDL particles size and hs-CRP levels.

RESULTS

Of 200 enrolled obese subjects, 55 were defined MHO subjects meeting only obesity criteria. The other 145 met all five criteria and were defined as having MS. Although MHO and MS subjects had similar BMI, MHO subjects had a lower percentage of small LDL particles (8% vs 29%, P < 0.001), higher average LDL diameter (274 ± 5 vs 270 ± 7 Å, P < 0.001), and lower hs-CRP levels (P < 0.05) than MS patients.

CONCLUSION

The major finding of this study is that MHO subjects compared to equally obese subjects meeting the criteria of the MS have statistically significant differences in size of LDL and concentration of hs-CRP. However, the absolute differences are very small and of uncertain clinical significance.

Assessment of lipoprotein profiles study (ALPS) and antioxidant activity in healthy subjects treated with AGI-1067

BACKGROUND

AGI-1067 (succinobucol) is a phenolic derivative of probucol that inhibits the vascular oxidative-inflammatory cascade and is intended to have an improved clinical profile.

OBJECTIVE

The Assessment of Lipoprotein Profiles (ALPS) study evaluated the effects of AGI-1067 on lipid, antioxidant, antiinflammatory and safety profiles in healthy subjects.

METHODS

This was a double-blind, placebo-controlled, 12-week, multicenter trial. Eligible subjects, aged 18 to 65 years, had low-density lipoprotein cholesterol (LDL-C) ≤ 190 mg/dL, triglyceride (TG) ≤ 600 mg/dL and Framingham risk <10%. Subjects were randomized 1:1 to oral 300 mg AGI-1067 (n = 127) or matching placebo (n = 127) once daily.

RESULTS

AGI-1067 and placebo treatment had small changes (mean) in: LDL-C (+2.98 vs -1.52 mg/dL, respectively; P = 0.057), apolipoprotein B (+1.48 vs -1.91 mg/dL; P = 0.267), high-density lipoprotein cholesterol (HDL-C) [-3.69 vs -0.29 mg/dL; P < 0.001], and apolipoprotein (Apo) A-I (-10.43 vs -6.14 mg/dL; P = 0.021). Subjects with baseline LDL-C > 130 mg/dL showed the largest decreases in HDL-C and ApoA-I, while subjects with LDL-C ≤130 mg/dL had insignificant changes in both parameters. Changes in cholesteryl ester transfer protein mass were significantly correlated (P < 0.0001) with LDL-C changes, but not HDL-C. Paraoxonase activity increased with AGI-1067 vs little change in placebo (+1.78 vs +0.15 U/L, respectively; P = 0.077). HDL particles isolated from AGI-1067 treated subjects showed significant antioxidant potency vs HDL particles from placebo subjects (thiobarbituric acid reactive substances in a LDL oxidation assay decreased -25.88% vs +7.88, respectively; P = 0.011).

CONCLUSION

The ALPS study demonstrated that AGI-1067 had minor effects on LDL and HDL cholesterol. More dramatic effects were observed for HDL-associated paraoxonase and thiobarbituric acid reactive substances activity, suggesting that the antiatherosclerotic properties of AGI-1067 may involve an HDL antioxidant mechanism consistent with inhibition of the oxidative-inflammatory cascade, rather than involving a lipid regulating pathway.

Disparate LDL Phenotypic Classification among 4 Different Methods Assessing LDL Particle Characteristics

Background: Our study seeks to clarify the extent of differences in analytical results, from a clinical perspective, among 4 leading technologies currently used in clinical reference laboratories for the analysis of LDL subfractions: gradient gel electrophoresis (GGE), ultracentrifugation–vertical auto profile (VAP), nuclear magnetic resonance (NMR), and tube gel electrophoresis (TGE).

Methods: We collected 4 simultaneous blood samples from 40 persons (30 males and 10 females) to determine LDL subclasses in 4 different clinical reference laboratories using different methods for analysis. LDL subfractions were assessed according to LDL particle size and the results categorized according to LDL phenotype. We compared results obtained from the different technologies.

Results: We observed substantial heterogeneity of results and interpretations among the 4 methods. Complete agreement among methods with respect to LDL subclass phenotyping occurred in only 8% (n = 3) of the persons studied. NMR and GGE agreed most frequently at 70% (n = 28), whereas VAP matched least often.

Conclusions: As measurement of LDL subclasses becomes increasingly important, standardization of methods is needed. Variation among currently available methods renders them unreliable and limits their clinical usefulness.

A new approach to the quantitative measurement of dense LDL subfractions

OBJECTIVES

Small dense low-density lipoproteins (LDLs) should be considered a major risk factor for cardiovascular disease, but there is still no recommended method for measuring them or expressing clinical values. We measured the dense LDL portion relatively simply by isolating it using density ultracentrifugation and then giving it a relative, quantitative value.

DESIGN AND METHODS

Dense LDLs (d=1.048-1.063 g/mL) were isolated from human plasma at the same time as total LDL (d=1.021-1.063 g/mL) by means of sequential ultracentrifugation, and the former was assessed as a percentage of the latter. A receiver operator characteristic (ROC) curve was used to compare the different LDL components as markers of dense LDLs. The proposed method was compared with non-denaturing gradient gel electrophoresis (NDGGE). In order to obtain clinical data, the dense LDL portion was measured in diabetic and postmenopausal subjects and healthy controls.

RESULTS

The ROC curve showed that cholesterol level was a more accurate marker of dense LDLs. The within-run precision (CV) was 2.28%, and the between-run CV was 5.1%. Analytical recovery was 80.2+/-1.6%. The correlation between the proposed method and NDGGE was r=0.90, p<0.001. The dense LDL percentage significantly correlated with serum triglyceride (r=0.57, p<0.001) and high-density lipoprotein cholesterol levels (r=-0.33, p<0.01), but not with the LDL-cholesterol/apolipoprotein B ratio. The diabetic patients and postmenopausal women had higher dense LDL values than the healthy controls.

CONCLUSIONS

The results obtained using this procedure are in line with those obtained using NDGGE, which is the conventional assay system for measuring LDL size. Determining the small dense LDL portion by means of its cholesterol content may be a better approach to characterising the risk of cardiovascular disease, even in the presence of relatively normal LDL-cholesterol levels.

Low-density lipoprotein subclass and its correlating factors in diabetics

OBJECTIVES

Small dense LDL, low density lipoprotein (LDL) particles with small size and high density, is regarded as a significant risk factor for cardiovascular diseases. Diabetes mellitus is one of the conditions accompanied by increased small dense LDL. We analyzed LDL subclass in type 2 diabetics and normal controls with LipoPrint LDL System to investigate the LDL heterogeneity in diabetics and factors affecting it.

DESIGN AND METHODS

We selected 40 normal controls and 40 type 2 diabetics with fasting blood glucose level over 7.0 mmol/L and HbA1c level over 7%. LDL subclass was determined with LipoPrint LDL System. LipoPrint LDL System fractionates LDL into seven parts (LDL1-7) by size and LDL3 to LDL7 are defined as small-sized LDL. In addition we estimated 'the percent of small-sized LDL over whole LDL' and defined it as 'small-sized LDL proportion'.

RESULTS

Mean small-sized LDL proportion was significantly higher in diabetics (23.4%) than in controls (11.8%) (p<0.001) and small-sized LDL proportion showed positive correlation with blood levels of glucose, HbA1c, total cholesterol, triglyceride, and oxidized LDL and negative correlation with HDL cholesterol level in univariate analysis (p<0.001). Of these parameters, triglyceride, HbA1c, oxidized LDL were statistically significant variables contributing to the small-sized LDL proportion in stepwise multiple regression analysis.

CONCLUSIONS

We analyzed small-sized LDL proportion in type 2 diabetics and found that it was significantly increased in diabetics than control subjects and it was independently correlated with triglyceride, HbA1c, oxidized LDL in descending order, which are reflecting lipid metabolism, glycation, and oxidative stress, respectively.

Effects of adding fenofibrate (200 mg/day) to simvastatin (10 mg/day) in patients with combined hyperlipidemia and metabolic syndrome

Combined hyperlipidemia predisposes subjects to coronary heart disease. Two lipid abnormalities--increased cholesterol and atherogenic dyslipidemia--are potential targets of lipid-lowering therapy. Successful management of both may require combined drug therapy. Statins are effective low-density lipoprotein (LDL) cholesterol-lowering drugs. For atherogenic dyslipidemia (high triglycerides, small LDL, and low high-density lipoprotein [HDL]), fibrates are potentially beneficial. The present study was designed to examine the safety and efficacy of a combination of low-dose simvastatin and fenofibrate in the treatment of combined hyperlipidemia. It was a randomized, placebo-controlled trial with a crossover design. Three randomized phases were employed (double placebo, simvastatin 10 mg/day and placebo, and simvastatin 10 mg/day plus fenofibrate 200 mg/day). Each phase lasted 3 months, and in the last week of each phase, measurements were made of plasma lipids, lipoprotein cholesterol, plasma apolipoproteins B, C-II, and C-III and LDL speciation on 3 consecutive days. Simvastatin therapy decreased total cholesterol by 27%, non-HDL cholesterol by 30%, total apolipoprotein B by 31%, very low-density lipoprotein (VLDL) + intermediate-density lipoprotein (IDL) cholesterol by 37%, VLDL + IDL apolipoprotein B by 14%, LDL cholesterol by 28%, and LDL apolipoprotein B by 21%. The addition of fenofibrate caused an additional decrease in VLDL + IDL cholesterol and VLDL + IDL apolipoprotein B by 36% and 32%, respectively. Simvastatin alone caused a small increase in the ratio of large-to-small LDL, whereas the addition of fenofibrate to simvastatin therapy caused a marked increase in the ratio of large-to-small LDL species. Simvastatin alone produced a small (6%) and insignificant increase in HDL cholesterol concentrations. When fenofibrate was added to simvastatin therapy, HDL cholesterol increased significantly by 23%. No significant side effects were observed with either simvastatin alone or with combined drug therapy. Therefore, a combination of simvastatin 10 mg/day and fenofibrate 200 mg/day appears to be effective and safe for the treatment of atherogenic dyslipidemia in combined hyperlipidemia.

Effects of bezafibrate and pravastatin on remnant-like lipoprotein particles and lipoprotein subclasses in type 2 diabetes

The effects of bezafibrate and pravastatin on remnant-like lipoprotein particles (RLPs) and lipoprotein subclasses were compared in type 2 diabetes. Bezafibrate (400 mg/day) and pravastatin (10 mg/day) were given to 27 Japanese diabetics in a randomized crossover design. RLP cholesterol (RLP-C) and RLP triglyceride (RLP-TG) were measured by an immunoseparation technique. LDL and HDL were separated each into three subclasses (large, medium, small) and their cholesterol (C) contents were measured by an HPLC method. RLP-C was reduced more effectively by pravastatin (bezafibrate -16.0% vs. pravastatin -40.6%, P < 0.05), whereas RLP-TG was reduced more effectively by bezafibrate (-55.2% vs. -35.0%, P < 0.05). Further, pravastatin decreased large and small LDL-C levels equally (large; -23.6%; medium; -17.2%, small; -21.0%), while bezafibrate produced a relatively larger reduction in small LDL-C (-12.1; -16.9; -21.5%). Whereas bezafibrate significantly decreased large HDL-C and increased medium and small HDL-C (-49.6; 34.1; 35.8%), pravastatin significantly increased only medium HDL-C (5.2; 9.4; 5.9%). Bezafibrate reduced RLP-C and RLP-TG more effectively in patients with high TG levels, whereas pravastatin's effect was not markedly influenced by the initial TG level. Thus measurements of RLP-C, RLP-TG, and HPLC subclasses revealed that bezafibrate and pravastatin differently influence the lipoprotein status in type 2 diabetes.

Small, dense low-density lipoprotein: risk or myth?

Based on the particle diameter of the major subpopulation of low-density lipoprotein (LDL) in plasma, an individual may be classified either as having phenotype A (desirable phenotype; large, buoyant LDL) or phenotype B (high risk; small, dense LDL). This article reviews the clinical significance of LDL particle diameter determination and proposes a strategy for incorporating this information in the new guidelines of the National Cholesterol Education Program's Adult Treatment Panel III.

Specialized lipid profiles

Individuals with abnormal blood lipids and lipoproteins are at increased risk for cardiovascular disease. With the development of effective dietary, behavioral, and pharmaceutical treatments to optimize blood lipoproteins, accurate clinical assessment of blood lipids and lipoproteins are essential for patient management and research. This article discusses the use of a variety of lipid analyses currently available. The use of traditional lipoprotein measurements, including Friedewald calculation of low-density lipoprotein (LDL) cholesterol and ultracentrifugation methods to measure blood lipoproteins, are discussed. Newer analytic techniques, including the vertical analytic profile, nuclear magnetic resonance, direct LDL measurement, LDL size determination, and triglyceride-rich lipoprotein remnants, are also described. Despite the development of a number of lipid and lipoprotein assays, lipoprotein analysis with a Friedewald- calculated LDL measurement remains the lipoprotein analysis performed in approximately 93% of clinical laboratories. It remains to be determined if the alternative lipid and lipoprotein assays currently available will become more widely utilized in the future.

Development of a Rapid, Quantitative Method for LDL Subfractionation with Use of the Quantimetrix Lipoprint LDL System

Background: Recent evidence suggests that the presence of small, dense LDL is independently associated with increased risk of developing coronary artery disease. Current methods to subfractionate LDL are time-consuming and/or technically demanding. Therefore, we have sought the development of a less complex LDL subfractionation procedure.

Methods: LDL subfractions were separated using the Quantimetrix LipoprintTM LDL System. High-resolution 3% polyacrylamide gel tubes were scanned densitometrically (610 nm) with a Helena EDC system. A computerized method to identify and quantitatively score the resolved LDL subfractions was developed. Results from the Quantimetrix method were compared using 51 plasma samples with values obtained by nondenaturing gradient gel electrophoresis (NDGGE) and nuclear magnetic resonance (NMR) spectroscopy.

Results: LDL subfractionation scores correlated significantly (P &lt;0.05) with triglyceride, HDL-cholesterol, apolipoprotein B100, and LDL-cholesterol/apolipoprotein B100 (r = 0.591, −0.392, 0.454, and −0.411, respectively). For 51 samples, the Quantimetrix method classified 21 with small, 14 with intermediate, and 16 with large LDL. Of the 21 samples classified as small by Quantimetrix, 20 (95%) were classified as small (n = 18) or intermediate (n = 2) by NDGGE. All of the 16 specimens classified as large by Quantimetrix were either large (n = 14) or intermediate (n = 2) by NDGGE. LDL score was inversely correlated (r = −0.674; P &lt;0.0001) with LDL particle size determined by NMR spectroscopy.

Conclusions: A quantitative method for the assessment of LDL particle size phenotype was developed using the Quantimetrix Lipoprint LDL System. The method can be performed in less than 3 h in batch mode and is suitable for routine use in clinical laboratories.

Cardiovascular disease in diabetes mellitus type 2: a potential role for novel cardiovascular risk factors

A major consequence of diabetes mellitus type 2 is the accelerated development of atherosclerosis. Assessment of conventional risk factors such as plasma lipids, lipoproteins and hypertension only partly account for the excessive risk of developing cardiovascular disease in this population. Increasing evidence has emerged suggesting that conditions associated with diabetes mellitus type 2, such as insulin resistance, hyperinsulinemia and hyperglycemia, may also play a significant role in regulating 'novel' cardiovascular risk factors. These factors and their potential roles in the development of atherosclerosis and cardiovascular events are discussed in this review.

Association between elevated plasma fibrinogen and the small, dense low-density lipoprotein phenotype among postmenopausal women

A predominance of small, dense low-density lipoprotein (LDL) particles (subclass pattern B) has been associated with a 2- to threefold increase in coronary heart disease risk. Recently, it has been reported that LDL subclass pattern B is associated with hyperfibrinogenemia, which is also a coronary heart disease risk factor. The present study examined the relation between hyperfibrinogenemia and LDL subclass pattern in 258 postmenopausal women. A significant univariate correlation was observed between the concentration of cholesterol carried in small, dense LDL particles and plasma fibrinogen concentration (r = 0.17, p = 0.01). The prevalence of LDL subclass pattern B was 41.9% in the highest fibrinogen tertile, compared with 27.9% and 24.4% in the first and second tertiles, respectively (global chi-square 6.8, p = 0.03). The crude odds ratio (OR) for LDL subclass pattern B among women in the highest fibrinogen tertile, compared with the lower tertiles, was 2.03 (95% confidence interval [CI] 1.18 to 3.51, p = 0.01). After adjustment for age and plasma lipids (log(e) triglycerides, LDL cholesterol, and high-density lipoprotein cholesterol), the OR was 2.14 (95% CI 1.17 to 3.96, p = 0.01). Further adjustment for hematocrit, indicators of carbohydrate homeostasis, body mass index, waist circumference, and several variables related to lifestyle did not attenuate this association (OR 2.56, 95% CI 1.27 to 5.27, p = 0.01). These data suggest that hyperfibrinogenemia and LDL subclass pattern B may be 2 components of a common syndrome and suggest that hyperfibrinogenemia may contribute to the increased coronary heart disease risk associated with LDL subclass pattern B.

Low-density lipoprotein subclass distribution pattern and adiposity-associated dyslipidemia in postmenopausal women

OBJECTIVE

A predominance of small, dense low-density lipoprotein (LDL) particles (subclass pattern B) is associated with increased risk for coronary heart disease and is characterized by elevated triglycerides and depressed high-density lipoprotein (HDL) cholesterol concentrations. The present analysis was undertaken to assess the impact of LDL subclass distribution pattern and adiposity on serum lipids in postmenopausal women.

METHODS

Anthropometric measurements and fasting lipid data were obtained from 254 postmenopausal women 70 years of age or younger, not receiving sex hormone replacement, who were participating in a clinical trial designed to assess the influence of hormone replacement regimens on coronary heart disease risk markers.

RESULTS

The prevalence of LDL subclass pattern B was 32%. Triglyceride levels were higher and HDL cholesterol lower (both p<0.001) in women with pattern B vs. pattern A, but total and LDL cholesterol levels did not differ. LDL subclass pattern contributed independently to the variance in HDL cholesterol (p<0.001) and log(e) triglyceride (p<0.001) concentrations explained by anthropometric variables (waist circumference or body mass index). Compared to women with LDL subclass pattern A and waist circumference below the median value of 83.0 centimeters, those with pattern B and waist > or =83.0 centimeters had markedly lower HDL cholesterol levels [44.0 (41.6-47.4) vs. 57.2 (54.1-60.3) mg/dL, mean (95% CI)] and increased triglyceride concentrations [geometric mean 147.8 (131.6-165.7) vs. 95.4 (88.2-102.5) mg/dL].

CONCLUSIONS

These data suggest that adiposity and LDL subclass distribution pattern are independent determinants of plasma triglyceride and HDL cholesterol concentrations in postmenopausal women.

Increased prevalence of smaller and denser LDL particles in Asian Indians

There is increasing evidence to believe that Asian Indians are at an increased risk of coronary heart disease (CHD), which cannot be attributed to the common risk factors. Individuals with small, dense LDL phenotype are also known to be at increased risk of CHD. Our objective was to examine whether the prevalence of smaller and denser LDL particles is increased in Asian Indians. Thirty-nine Asian Indians (22 men and 17 women), aged 25 to 45 years, were matched with 39 whites for age and gender. Cholesterol profiles of lipoprotein classes and LDL subclasses were measured using the Vertical Auto Profile-II (VAP-II) and LDL-VAP-II methods, respectively. Six LDL subclasses (LDL1 to LDL6) have been identified using the LDL-VAP-II, with LDL1 and LDL6, respectively, being the most and least buoyant subclasses. The prevalence of small, dense LDL type (subjects with major LDL subclass 5 or 6) was significantly higher in Asian Indians compared with white subjects (44% versus 21%; P<0.05). The relative position of the major LDL density peak (LDL-Rf) on 0 to 1 scale in LDL-VAP-II density gradient was also significantly decreased in Asian Indians (0.462+/-0.076 versus 0. 505+/-0.086; P<0.02), suggesting an increased LDL density. Furthermore, this increased prevalence of small, dense LDL type appears to be due to the increased triglycerides (TG) (r for LDL-Rf versus TG=0.681, P<0.001), with fasting insulin being one of the important determinants of TG (r for TG versus fasting insulin=0.572, P<0.001). In addition, fasting insulin was significantly increased in Asian Indians with small, dense LDL type compared with other Asian Indians, suggesting a significant role of insulin resistance in increasing the prevalence of small, dense LDL type. We conclude that the increased prevalence of small, dense LDL observed in Asian Indians might contribute to their increased CHD risk.