Changes in plasma triglyceride levels shift lipoprotein(a) density in parallel with that of LDL independently of apolipoprotein(a) size

Blood Nanoparticles - Influence on Extracellular Vesicle Isolation and Characterization

Blood is a rich source of disease biomarkers, which include extracellular vesicles (EVs). EVs are nanometer-to micrometer-sized spherical particles that are enclosed by a phospholipid bilayer and are secreted by most cell types. EVs reflect the physiological cell of origin in terms of their molecular composition and biophysical characteristics, and they accumulate in blood even when released from remote organs or tissues, while protecting their cargo from degradation. The molecular components (e.g., proteins, miRNAs) and biophysical characteristics (e.g., size, concentration) of blood EVs have been studied as biomarkers of cancers and neurodegenerative, autoimmune, and cardiovascular diseases. However, most biomarker studies do not address the problem of contaminants in EV isolates from blood plasma, and how these might affect downstream EV analysis. Indeed, nonphysiological EVs, protein aggregates, lipoproteins and viruses share many molecular and/or biophysical characteristics with EVs, and can therefore co-isolate with EVs from blood plasma. Consequently, isolation and downstream analysis of EVs from blood plasma remain a unique challenge, with important impacts on the outcomes of biomarker studies. To help improve rigor, reproducibility, and reliability of EV biomarker studies, we describe here the major contaminants of EV isolates from blood plasma, and we report on how different EV isolation methods affect their levels, and how contaminants that remain can affect the interpretation of downstream EV analysis.

Verification of Low-Density Lipoprotein Cholesterol Levels Measured by Anion-Exchange High-Performance Liquid Chromatography in Comparison with Beta Quantification Reference Measurement Procedure

BACKGROUND

A new lipoprotein testing method based on anion-exchange HPLC (AEX-HPLC) was recently established. We verified the accuracy of LDL-C levels, a primary therapeutic target for the prevention of cardiovascular disease (CVD), measured by AEX-HPLC comparing with LDL-C levels measured by beta quantification-reference measurement procedure (BQ-RMP), homogenous assays, and calculation methods.

METHODS

We compared LDL-C levels measured by AEX-HPLC (adLDL-Ch: LDL-Ch and IDL-Ch) and BQ-RMP using blood samples from 52 volunteers. AdLDL-Ch levels were also compared with those measurements by homogeneous assays and calculation methods (Friedewald equation, Martin equation, and Sampson equation) using blood samples from 411 participants with dyslipidemia and/or type 2 diabetes.

RESULTS

The precision and accuracy of adLDL-Ch were verified by BQ-RMP. The mean percentage bias [bias (%)] for LDL-C was 1.2%, and the correlation was y = 0.990x + 3.361 (r = 0.990). These results met the acceptable range of accuracy prescribed by the National Cholesterol Education Program. Additionally, adLDL-Ch levels were correlated with LDL-C levels measured by the 2 homogeneous assays (r > 0.967) and the calculation methods (r > 0.939), in serum samples from patients with hypertriglyceridemia.

CONCLUSIONS

AEX-HPLC is a reliable method for measuring LDL-C levels for CVD risk in daily clinical laboratory analyses.

A rapid anion-exchange chromatography for measurement of cholesterol concentrations in five lipoprotein classes and estimation of lipoprotein profiles in male volunteers without overt diseases

BACKGROUND

Analysis of lipoprotein profile gives important clinical information for lipid-lowering therapy which prevents atherosclerotic diseases. The lipoprotein classes can be isolated from serum with ultracentrifugation, which inevitably consumes a long time and needs large serum volume. We have established a method with anion-exchange chromatography with 1.0 µL of the injected volume in 5.2 min for assay of one sample.

METHODS

One-hundred-forty-one male volunteers without overt diseases were divided three groups (Group 1, non-dyslipidemia with LDL-cholesterol [LDL-C] <120 mg/dL and HDL-cholesterol (HDL-C) ≥40 mg/dL; Group 2, borderline dyslipidemia with 120 ≤ LDL-C < 140 mg/dL and HDL-C ≥40 mg/dL; Group 3, dyslipidemia with LDL-C ≥ 140 mg/dL or HDL-C < 40 mg/dL). Their lipoprotein profiles were evaluated by rapid anion-exchange chromatography, which measured concentrations of HDL-C, LDL-C, IDL-cholesterol, VLDL-cholesterol, and other fraction (chylomicron + lipoprotein [a])-cholesterol (other-C).

RESULTS

The within-day and between-day assay coefficients of variation of lipoprotein cholesterol values were 0.33-4.31% and 2.37-9.19%, respectively. The correlation coefficients between values of HDL-C, LDL-C, IDL-C and VLDL-C by the anion-exchange chromatography and those by ultracentrifugal method were 0.97, 0.92, 0.58 and 0.94, respectively. Group 3 had significantly lower HDL-C and higher concentrations of IDL-C, VLDL-C and other-C than did Group 1. Group 2, borderline dyslipidemia, had significantly higher concentrations of IDL-C and VLDL-C than did Group 1.

CONCLUSION

The rapid anion-exchange chromatography assay may be sufficiently applied to the assessment of borderline dyslipidemia.

Lipoprotein(a) mass: a massively misunderstood metric

The importance of lipoprotein (a)-Lp(a)-as a cardiovascular (CV) risk marker has been underscored by recent findings that CV risk is directly related to baseline Lp(a) levels, even in well-treated patients. Although there is currently little that can be done pharmacologically to lower Lp(a) levels, knowledge of its serum concentration is important in overall risk assessment. This review focuses on 1 aspect of Lp(a) that is rarely discussed directly: how to express its levels in serum. There is considerable confusion on this point, and a fuller understanding of what the concentration units mean will help improve study-to-study comparisons and thereby advance our understanding of the pathobiology of this lipoprotein particle. As discussed here, the term Lp(a) mass refers to the entire mass of the particle: lipids, proteins, and carbohydrates combined. At present, there are no commercially available assays that are completely insensitive to the variability in particle mass, which arises not only from differences in apo(a) isoform mass but also from variations in lipid mass. Because lipoprotein "particle number" (molar concentration) has been found to be superior to component-based metrics (ie, low-density lipoprotein particle vs cholesterol concentrations) for CV disease risk prediction, the development of a mass-insensitive Lp(a) assay should be a high priority.

Observational study of lipid profile and LDL particle size in patients with metabolic syndrome

Background

The atherogenic lipoprotein phenotype is characterized by an increase in plasma triglycerides, a decrease in high-density lipoprotein cholesterol (HDLc), and the prevalence of small, dense-low density lipoprotein cholesterol (LDLc) particles. The aim of this study was to establish the importance of LDL particle size measurement by gender in a group of patients with Metabolic Syndrome (MS) attending at a Cardiovascular Risk Unit in Primary Care and their classification into phenotypes.

Subjects and methods

One hundred eighty-five patients (93 men and 92 women) from several areas in the South of Spain, for a period of one year in a health centre were studied. Laboratory parameters included plasma lipids, lipoproteins, low-density lipoprotein size and several atherogenic rates were determinated.

Results

We found differences by gender between anthropometric parameters, blood pressure and glucose measures by MS status. Lipid profile was different in our two study groups, and gender differences in these parameters within each group were also remarkable, in HDLc and Apo A-I values. According to LDL particle size, we found males had smaller size than females, and patients with MS had also smaller than those without MS. We observed inverse relationship between LDL particle size and triglycerides in patients with and without MS, and the same relationship between all atherogenic rates in non-MS patients. When we considered our population in two classes of phenotypes, lipid profile was worse in phenotype B.

Conclusion

In conclusion, we consider worthy the measurement of LDL particle size due to its relationship with lipid profile and cardiovascular risk.

Combined effects of small apolipoprotein (a) isoforms and small, dense LDL on coronary artery disease risk

BACKGROUND AND AIMS

Lipoprotein (a) [Lp(a)] consists of low-density lipoprotein (LDL) and apolipoprotein (a) [apo(a)]. Both Lp(a) constituents are well-recognized risk factors for coronary artery disease (CAD). This study investigates the interrelationship of apo(a) and LDL size, as well as their possible synergistic effect on the increase of CAD risk.

METHODS

One hundred nine CAD patients and 102 apparently healthy subjects were included in the study. Lp(a) concentration was measured using immunoturbidimetry. The sizes of apo(a) isoforms were determined by SDS-agarose gel electrophoresis followed by immunoblotting. LDL particle size was determined by gradient gel electrophoresis.

RESULTS

We found an inverse correlation between apo(a) size and Lp(a) concentration (r(2) = 31%, p <0.001 in the control group and r(2) = 35%, p <0.001 in the CAD group). Individuals with smaller apo(a) isoforms and small, dense LDL (sdLDL) >50% had the highest risk of CAD development (OR = 4.23, p = 0.017). The synergy index (SIM) for the combination of smaller apo(a) isoforms and sdLDL >50% was 1.2. Adjustment for Lp(a) and triacylglycerol concentrations eliminated smaller apo(a)/sdLDL >50% related risk (p = 0.233 and p = 0.09, respectively).

CONCLUSIONS

Smaller apo(a) isoforms appear to be superior to sdLDL for the assessment of CAD risk. Their combined effect is synergistic.

Lp(a) and risk of recurrent cardiac events in obese postinfarction patients

Studies of recurrent coronary events in obese postinfarction patients show mixed results despite potential importance of obesity-related pathophysiologic processes and associated markers in establishing and predicting risk. The study aim was to determine specific markers of recurrent risk in obese postinfarction patients. Nondiabetic patients of the Thrombogenic Factors and Recurrent Coronary Events (THROMBO) postinfarction study were classified according to BMI as normal weight (<25 kg/m(2)), overweight (25.0-29.9 kg/m(2)), and obese (> or = 30 kg/m(2)). Cox multivariable regression with adjustment for significant clinical covariates was performed in each group monitoring outcome (cardiac death, myocardial infarction (MI), or unstable angina with 26 months follow-up) as a function of 17 thrombogenic, inflammatory, and metabolic blood markers and 17 cardiovascular disease-associated genetic polymorphisms. Results revealed no statistically significant genetic or blood marker variables in normal or overweight patients. For obese postinfarction patients, elevated lipoprotein(a) (Lp(a))was found to be a highly significant risk marker with hazard ratio and 95% confidence interval of 3.94 (2.11-7.35), P = 0.000017 (upper tertile vs. lower two tertiles). Additionally, elevated Lp(a) was found to interact with the -75G>A polymorphism of the apolipoprotein A-I gene and the -250G>A polymorphism of the hepatic lipase gene in establishing risk. We conclude that interactions of elevated Lp(a) with polymorphisms of the apolipoprotein A-I and hepatic lipase genes, primarily reflective of altered lipoprotein metabolism, play an important role in the establishment of recurrent coronary event risk in obese, nondiabetic postinfarction patients. These findings suggest close monitoring and consideration of weight reduction for obese postinfarction patients with elevated Lp(a) levels.

Practical management of dyslipidemia with elevated lipoprotein(a)

OBJECTIVE

To report a case and describe a practical approach to treating dyslipidemia in a very-high-risk patient with elevated lipoprotein(a) [Lp(a)].

SETTING

Pharmacist-managed lipid clinic, from November 2006 to July 2007.

PATIENT DESCRIPTION

A 50-year-old white woman with a recent history of multiple myocardial infarctions presented for management of dyslipidemia.

CASE SUMMARY

At baseline, the patient had elevated low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), total cholesterol (TC), and Lp(a) (306 nmol/L) levels and low high-density lipoprotein cholesterol (HDL-C) levels. Early initiation of combination therapy with a statin and niacin extended release (ER) titration was started. After 3 months, despite progressive weight gain caused by dietary indiscretion, LDL-C decreased by 24% and TG and TC levels reached goal. Lp(a) levels did not change. Niacin ER titration continued, pravastatin was maximized, and ezetimibe 10 mg daily was started. Despite dramatic 9-month weight gain (68 lb total), LDL-C and HDL-C reached goal and Lp(a) levels decreased by 33% (204 nmol/L) after niacin ER maximization.

RESULTS

Lp(a) is an emerging risk factor in cardiovascular disease (CVD). Elevated Lp(a) (>30 mg/dL) has been implicated as both an independent and an additive risk factor for CVD and stroke, particularly in women. In this case, the patient did not reach the optimal goal (<30 mg/dL) but did experience more than 30% reduction in Lp(a) levels. Although multiple factors, including subclinical hypothyroidism, hormonal changes, and renal disease, increase Lp(a) levels, few beneficial treatment options exist (i.e., estrogen and niacin). Although the exact mechanism of action is unknown, niacin ER has been documented to reduce Lp(a) by 36% to 38%. Some effect of ezetimibe on Lp(a) in this patient cannot be ruled out.

CONCLUSION

This case illustrates a practical use of currently available therapy options to address Lp(a) as a secondary cardiovascular risk factor. Niacin is a preferred option for Lp(a) lowering in very-high-risk patients with coronary heart disease and dyslipidemia. The importance of moderate reductions in Lp(a) is not known.

Genetics of apolipoprotein B and apolipoprotein AI and premature coronary artery disease

Increased low-density lipoprotein (LDL) and decreased high-density lipoprotein cholesterol (HDL-C) predict premature coronary artery disease, as do elevated levels of apolipoprotein B or reduced levels of apolipoprotein AI. Probands were studied of families with common genetic forms of dyslipidaemia to determine if apo B or apo AI define genetic groups and if apo B or apo AI levels relate to premature coronary artery disease risk. Elevated apo B was characteristic of familial hypercholesterolaemia, familial combined hyperlipidaemia (FCHL), and was seen in individuals with elevated Lp(a). Normal apo B levels were seen in familial hypertriglyceridaemia and in 'coronary artery disease with low-HDL cholesterol'. Apo AI levels tended to be low in FCHL and were decreased in 'coronary disease with low-HDL cholesterol'. In familial hypertriglyceraemia, even though HDL-C levels were low, normal apo AI and apo B levels were seen in the absence of premature coronary artery disease. Therefore, in genetic dyslipidaemias elevated apo B levels and reduced apo AI levels (or increased apo B/AI ratio) differ and predict premature coronary artery disease.

Method for Lipoprotein(a) Density Profiling by BiEDTA Differential Density Lipoprotein Ultracentrifugation

In this article, we demonstrate the analytical power of linking density gradient ultracentrifugation with affinity separations. Here we address some of the analytical challenges in the study of lipoprotein(a), (Lp(a)). The mean density distribution of Lp(a) was determined by a differential density lipoprotein profile (DDLP). For DDLP, the lipoprotein density distribution of a serum sample with elevated Lp(a) levels was determined by ultracentrifugation using a BiEDTA complex as a density gradient. Lp(a) was removed from a second aliquot of the same serum sample by carbohydrate affinity using wheat germ agglutinin (WGA). WGA was demonstrated to have high specificity for Lp(a) in a serum sample. This sample was ultracentrifuged to obtain a lipoprotein density distribution in the absence of Lp(a). A DDLP was obtained after subtracting the Lp(a)-depleted lipoprotein density profile from the untreated lipoprotein density profile. The DDLP methodology reported herein gives relevant information of the lipoproteins in serum such as density, isoform, and subclass characteristics. Lp(a) was quantitatively isolated from serum with a recovery efficiency of 82%. Lp(a) was purified by ultracentrifugation. Lp(a) retained its inherent density (1.086 g/mL) and immunoreactivity. The major outcome of this research was the effectiveness of using affinity separations coupled with density ultracentrifugation for the isolation of pure Lp(a) from serum and its isoform characterization based on density by DDLP.

High-level lipoprotein [a] expression in transgenic mice: evidence for oxidized phospholipids in lipoprotein [a] but not in low density lipoproteins

Efforts to elucidate the role of lipoprotein [a] (Lp[a]) in atherogenesis have been hampered by the lack of an animal model with high plasma Lp[a] levels. We produced two lines of transgenic mice expressing apolipoprotein [a] (apo[a]) in the liver and crossed them with mice expressing human apolipoprotein B-100 (apoB-100), generating two lines of Lp[a] mice. One had Lp[a] levels of approximately 700 mg/dl, well above the 30 mg/dl threshold associated with increased risk of atherosclerosis in humans; the other had levels of approximately 35 mg/dl. Most of the LDL in mice with high-level apo[a] expression was covalently bound to apo[a], but most of the LDL in the low-expressing line was free. Using an enzyme-linked sandwich assay with monoclonal antibody EO6, we found high levels of oxidized phospholipids in Lp[a] from high-expressing mice but not in LDL from low-expressing mice or in LDL from human apoB-100 transgenic mice (P <0.00001), even though all mice had similar plasma levels of human apoB-100. The increase in oxidized lipids specific to Lp[a] in high-level apo[a]-expressing mice suggests a mechanism by which increased circulating levels of Lp[a] could contribute to atherogenesis.

Genome-wide scan for quantitative trait loci influencing LDL size and plasma triglyceride in familial hypertriglyceridemia

Small, dense LDLs and hypertriglyceridemia, two highly correlated and genetically influenced risk factors, are known to predict for risk of coronary heart disease. The objective of this study was to perform a whole-genome scan for linkage to LDL size and triglyceride (TG) levels in 26 kindreds with familial hypertriglyceridemia (FHTG). LDL size was estimated using gradient gel electrophoresis, and genotyping was performed for 355 autosomal markers with an average heterozygosity of 76% and an average spacing of 10.2 centimorgans (cMs). Using variance components linkage analysis, one possible linkage was found for LDL size [logarithm of odds (LOD) = 2.1] on chromosome 6, peak at 140 cM distal to marker F13A1 (closest marker D6S2436). With adjustment for TG and/or HDL cholesterol, the LOD scores were reduced, but remained in exactly the same location. For TG, LOD scores of 2.56 and 2.44 were observed at two locations on chromosome 15, with peaks at 29 and 61 cM distal to marker D15S822 (closest markers D15S643 and D15S211, respectively). These peaks were retained with adjustment for LDL size and/or HDL cholesterol. These findings, if confirmed, suggest that LDL particle size and plasma TG levels could be caused by two different genetic loci in FHTG.

The polymorphism of the beta3-adrenergic receptor gene is associated with reduced low-density lipoprotein particle size

People with a predominance of small, dense low-density lipoprotein (LDL) particles appear to be at increased risk for coronary disease, independent of LDL cholesterol levels. The Trp64Arg variant of the beta3-adrenergic receptor gene is reported to be associated with abdominal obesity and resistance to insulin, and as a consequence, this variant may be a genetic factor in the development of atherosclerosis. Therefore, we investigated whether the beta3-adrenergic receptor polymorphism contributes to the distribution of LDL particle size in 136 Japanese subjects, aged 33 to 59 years, who visited for a routine annual checkup. None of these subjects were taking any medication. The diameter of LDL particles was determined at their peak size using nondenaturing 2% to 16% polyacrylamide gradient gels using fresh plasma samples. The genotype frequencies were: Trp/Trp, 71.3%; Try/Arg, 22.1%; and Arg/Arg, 6.6%, with allele frequencies of 0.82 for Trp64 and 0.18 for Arg64. The subjects with the Arg/Arg genotype had significantly higher levels of fasting plasma insulin and triglycerides and an insulin resistance index of homeostasis model assessment (HOMA-R), and significantly smaller LDL particle size than did the subjects with the Trp/Trp genotype. After adjusting for fasting insulin, body mass index (BMI), and HOMA-R index, there was no longer an observed difference in LDL particle size. The number of the Arg64 allele in individuals was significantly related with fasting insulin, BMI, triglycerides, glycosylated hemoglobin (HbA1c), and fasting glucose, and it was inversely related with LDL particle size. After adjusting for triglyceride, fasting insulin levels, and HOMA-R index, LDL particle size was no longer inversely correlated with the Arg allele. These findings suggest that the Trp64Arg variant in the beta3-adrenergic receptor gene may be associated with reducing LDL particle size, probably due to insulin resistance.

The susceptibility of lipoprotein(a) to copper oxidation is correlated with the susceptibility of autologous low density lipoprotein to oxidation

OBJECTIVES

Lipoprotein(a) [Lp(a)] can be oxidized by copper in vitro in a way comparable to low-density lipoprotein (LDL). We sought to determine whether the susceptibility of Lp(a) to oxidation is correlated with the susceptibility of autologous heterogeneous LDL, with apolipoprotein(a) [apo(a)] molecular size, or with both factors.

DESIGN AND METHODS

We examined shifts in electrophoretic mobility of Lp(a) and LDL caused by copper oxidation in plasma samples from 81 healthy men. The effect of copper oxidation on different-sized apo(a) was also evaluated.

RESULTS

There was a close correlation between the relative electrophoretic mobilities of oxidized Lp(a) and oxidized LDL in subjects, especially with small-sized apo(a) (n = 25, r = 0.72, p < 0.0001). Oxidative processes in Lp(a) resulted in the degradation of large-, but not small-sized apo(a).

CONCLUSIONS

The susceptibility of Lp(a) to oxidation is correlated with that of autologous LDL. Large-sized apo(a) may be involved in the Lp(a) oxidation.

Lipoprotein(a) and the atherothrombotic process: mechanistic insights and clinical implications

Although many epidemiologic studies have pointed at an association between plasma levels of lipoprotein(a) (Lp(a)) and cardiovascular risk, the data obtained have been conflicting because of a number of factors, particularly those dealing with plasma storage, lack of assay standardization, population sample size, age, gender, ethnic variations, and variable disease endpoints. Moreover, the attention has been primarily focused on whole Lp(a), with relatively less emphasis on its constituent apolipoprotein(a) and on the apolipoprotein B100-containing lipoprotein, mainly low-density lipoprotein (LDL), to which apolipoprotein(a) is linked. According to recent studies, small-size apolipoprotein(a) isoforms may represent a cardiovascular risk factor either by themselves or synergistically with plasma Lp(a) concentration. Moreover, the density properties of the LDL moiety may have an impact on Lp(a) pathogenicity. It has also become apparent that Lp(a) can be modified by oxidative events and by the action of lipolytic and proteolytic enzymes with the generation of products that exhibit atherothrombogenic potential. The role of the O-glycans linked to the inter-kringle linkers of apolipoprotein(a) is also emerging. This information is raising the awareness of the pleiotropic functions of Lp(a) and is opening new vistas on pathogenetic mechanisms whose knowledge is essential for developing rational therapies against this complex cardiovascular pathogen.

Differential apolipoprotein(a) isoform expression in heterozygosity is an independent contributor to lipoprotein(a) levels variability

BACKGROUND AND METHODS

Lipoprotein(a) [Lp(a)] levels represent an independent risk factor for cardio- and cerebrovascular diseases. Since lipoprotein(a) levels show a wide variability even in subjects with similar apolipoprotein(a) isoforms, we investigated the contribution of apolipoprotein(a) heterozygosity to lipoprotein(a) variance. Lipoprotein(a) levels, apolipoprotein(a) isoforms identification and expression, and the correlation with other lipo-apolipoprotein parameters have been investigated in 628 subjects >18 years of age.

RESULTS

In our study, 246 subjects were found heterozygous for apolipoprotein(a) isoforms. Lipoprotein(a) levels were higher in females. About 40% of the subjects expressed the larger isoform more intensely than the dominant isoform. Lipoprotein(a) was correlated with apolipoprotein(a) dominant isoform size, HDL-cholesterol and smaller apolipoprotein(a) isoform expression rate. Lipoprotein(a) was independently correlated with the smaller apolipoprotein(a) isoform, with its expression rate and with LDL-cholesterol. The inclusion of the smaller apolipoprotein(a) expression rate in a multiple regression model explained at least an additional 4% of the lipoprotein(a) variance after correction for apolipoprotein(a) size.

CONCLUSIONS

The smaller isoforms are not always effectively dominant in heterozygosis since 40% of the subjects expressed more the larger isoform. The individual variability of apolipoprotein(a) isoform expression in heterozygosis could explain part of the lipoprotein(a) levels variability.

Issues concerning the monitoring of statin therapy in hypercholesterolemic subjects with high plasma lipoprotein(a) levels

Most studies on the topic have shown that statin therapy decreases plasma LDL levels but not those of lipoprotein(a) [Lp(a)]. This specificity of action, although previously noted, has not been systematically investigated. In the current study we approached this problem by monitoring LDL- and Lp(a) cholesterol in 80 hypercholesterolemic subjects with high Lp(a) levels, at entry and 8 mon after initiation of statin therapy. We found that commonly used direct and indirect LDL cholesterol assays gave an LDL cholesterol value that comprised both true LDL- and Lp(a) cholesterol. We estimated these two analytes from the values of Lp(a) protein determined by ELISA and from knowledge of the Lp(a) chemical composition, complemented by data from immunochemical and ultracentrifugal analyses. Statin therapy, while not affecting plasma Lp(a) protein levels (21.7+/-10.4, before, and 22.0+/-10.1 mg/dL, after), caused a decrease in the estimated or true LDL cholesterol (P < 0.0001) to values in some cases as low as 10 mg/dL. This drop in true LDL was validated by the decrease in the LDL band in the ultracentrifugation profiles, and its magnitude was proportional to the degree of total cholesterol lowering and to the pretreatment true LDL/Lp(a) cholesterol weight ratio. We conclude that true LDL but not Lp(a) cholesterol is affected by statin therapy and that this specific response cannot be monitored by current LDL cholesterol assays and must, rather, rely on estimates of these two analytes.

The role of lipoprotein(a) in the pathogenesis of atherosclerotic cardiovascular disease and its utility as predictor of coronary heart disease events

Lipoprotein(a), is a highly heterogeneous lipoprotein, due to variations in the size of apolipoprotein(a), and the density of the apoB100-containing particles to which apo(a) is linked. Although high plasma levels of Lp(a) have been associated with an increased risk for atherosclerotic cardiovascular disease, the mechanism underlying this association is still largely undetermined, as is the potential role played by the particle's heterogeneity. Lp(a) pathogenicity may also be influenced by the action of environmental factors and post-translational events relating to oxidative processes, and the action of lipolytic and proteolytic enzymes. Complicating the study of Lp(a) are the competing methods for its quantification due to its complex structure, and the lack of standardized methodologies. The recognition that Lp(a) particles may not all be alike in atherogenic potential should encourage studies to identify genetic and nongenetic factors underlying its heterogeneity, in order to reach a better understanding of its actual impact on atherosclerotic cardiovascular disease.