A comparative study of four independent methods to measure LDL particle concentration

Carbon-based light addressable potential aptasensor based on the synergy of C-MXene@rGO and OPD@NGQDs for low-density lipoprotein detection

A novel carbon-based light-addressable potentiometric aptasensor (C-LAPS) was constructed for detection low-density lipoprotein (LDL) in serum. Carboxylated Ti3C2 MXene @reduced graphene oxide (C-MXene@rGO) was used as interface and o-phenylenediamine functionalized nitrogen-doped graphene quantum dots (OPD@NGQDs) as the photoelectric conversion element. The photosensitive layers composed of OPD@NGQDs/C-MXene@rGO exhibit superior photoelectric conversion efficiency and excellent biocompatibility, which contribute to an improved response signal. When LDL reacts with the LDL aptamer (LDLApt) immobilized on the photosensitive layers to form LDL-LDLApt complexes, the reaction process can induce the modification of the surface potential in the photosensitive layer, leading to potential shift observed through the I-V curves. The experimental conditions were successfully optimized with few planned tests by applying the Box-Behnken design and response surface methodology aspects of the Design-Expert software. Under the optimal condition, the potential shift had a linear relationship with concentrations of LDL from 0.02 to 0.30 μg/mL. The limit of detection (LOD) was 5.88 ng/mL (S/N = 3) and the sensitivity was 315.20 mV/μg·mL-1. In addition, the LDL C-LAPS demonstrated excellent specificity, reproducibility, and stability in detecting LDL. The sensor performed well in quantifying LDL in real samples. Therefore, the LDL C-LAPS has the potential for clinical applications.

Cholesteryl ester transfer protein (CETP) as a drug target for cardiovascular disease

Development of cholesteryl ester transfer protein (CETP) inhibitors for coronary heart disease (CHD) has yet to deliver licensed medicines. To distinguish compound from drug target failure, we compared evidence from clinical trials and drug target Mendelian randomization of CETP protein concentration, comparing this to Mendelian randomization of proprotein convertase subtilisin/kexin type 9 (PCSK9). We show that previous failures of CETP inhibitors are likely compound related, as illustrated by significant degrees of between-compound heterogeneity in effects on lipids, blood pressure, and clinical outcomes observed in trials. On-target CETP inhibition, assessed through Mendelian randomization, is expected to reduce the risk of CHD, heart failure, diabetes, and chronic kidney disease, while increasing the risk of age-related macular degeneration. In contrast, lower PCSK9 concentration is anticipated to decrease the risk of CHD, heart failure, atrial fibrillation, chronic kidney disease, multiple sclerosis, and stroke, while potentially increasing the risk of Alzheimer's disease and asthma. Due to distinct effects on lipoprotein metabolite profiles, joint inhibition of CETP and PCSK9 may provide added benefit. In conclusion, we provide genetic evidence that CETP is an effective target for CHD prevention but with a potential on-target adverse effect on age-related macular degeneration.

Distinct Differences in Lipoprotein Particle Number Evaluation between GP-HPLC and NMR: Analysis in Dyslipidemic Patients Administered a Selective PPARα Modulator, Pemafibrate

AIM

We established a method to evaluate the lipid concentrations, size and particle numbers (PNs) of lipoprotein subclasses by gel permeation chromatography (GP-HPLC). Nuclear magnetic resonance (NMR) is widely used to analyze these parameters of lipoprotein subclasses, but differences of the two methods are unknown. Current study compared the PNs of each lipoprotein subclass measured by GP-HPLC and NMR, and assessed the effect of a selective PPARα modulator, pemafibrate.

METHODS

Lipoprotein profiles of 212 patients with dyslipidemia who participated in the phase 2 clinical trial of a selective PPARα modulator, pemafibrate, were analyzed by two methods, GP-HPLC and NMR, which were performed with LipoSEARCH (Skylight Biotech) and LipoProfile 3 (LabCorp), respectively. GP-HPLC evaluated the PNs of 18 subclasses, consisting of CM, VLDL1-5, LDL1-6, and HDL1-6. NMR evaluated the PNs of 9 subclasses, consisting of large VLDL & CM, medium VLDL, small VLDL, IDL, large LDL, small LDL, large HDL, medium HDL and small HDL.

RESULTS

Three major classes, total CM&VLDL, total LDL and total HDL were obtained by grouping of corresponding subclasses in both methods and PNs of these classes analyzed by GP-HPLC were correlated positively with those by NMR. The correlation coefficients in total CM&VLDL, total LDL and total HDL between GP-HPLC and NMR was 0.658, 0.863 and 0.798 (all p＜0.0001), respectively. The PNs of total CM&VLDL, total LDL and total HDL analyzed by GP-HPLC was 249.5±51.7nM, 1,679±359 nM and 13,273±1,564 nM, respectively, while those by NMR was 124.6±41.8 nM, 1,514±386 nM and 31,161±4,839 nM, respectively. A marked difference in the PNs between the two methods was demonstrated especially in total HDL. The number of apolipoprotein (Apo) B molecule per one ApoB-containing lipoprotein particle, total CM&VLDL plus total LDL, was 1.10±0.05 by GP-HPLC, while 1.32±0.18 by NMR. The number of ApoA-I per one HDL particle was 3.40±0.17 by GP-HPLC, but only 1.46±0.15 by NMR, much less than reported previously.From the phase 2 clinical trial, randomizing 212 patients to pemafibrate 0.025-0.2 mg BID, fenofibrate 100 mg QD, or placebo groups, pemafibrate reduced the PNs of CM, large VLDL1-VLDL3 and medium VLDL4, but not small VLDL5 by GP-HPLC. It significantly decreased the PNs of smaller LDL and larger HDL particles, but increased those of larger LDL and smaller HDL particles. In contrast, NMR showed marked variations in the effect of pemafibrate on lipoprotein PNs, and no significant size-dependent changes.

CONCLUSIONS

GP-HPLC evaluates the lipoprotein PNs more accurately than NMR and can be used for assessing the effects of lipid-lowering drugs on lipoprotein subclasses.

Atrial fibrillation is associated with alterations in HDL function, metabolism, and particle number

Increased morbidity and mortality in atrial fibrillation (AF) are related to the pro-fibrotic, pro-thrombotic, and pro-inflammatory processes that underpin the disease. High-density lipoproteins (HDL) have anti-inflammatory, anti-oxidative, and anti-thrombotic properties. Functional impairment of HDL may, therefore, associate with AF initiation or progression. We studied indices of HDL quality and quantity of AF patients and healthy controls, including HDL-particle number, HDL cholesterol, apolipoprotein (apo) A-I levels, serum amyloid A (SAA) content and HDL-cholesterol efflux capacity, and paraoxonase activity of apoB-depleted serum. Serum samples were collected from AF patients (n = 91) before catheter ablation and from age- and sex-matched control subjects (n = 54). HDL-cholesterol efflux capacity was assessed in a validated assay using [3H]-cholesterol-labeled J774 macrophages. Lecithin-cholesterol acyltransferase (LCAT) and paraoxonase activities were assessed using fluorometric assays, SAA levels were determined by ELISA, and total and subclass HDL-particle number was assessed by nuclear magnetic resonance spectroscopy. ApoA-I levels were determined by immunoturbidimetry. HDL-cholesterol efflux capacity, HDL-particle number, apoA-I levels, and LCAT activity were markedly reduced in AF patients when compared to healthy individuals (all p < 0.001), whereas HDL-associated paraoxonase activity and SAA content were not altered (p = 0.578, p = 0.681). Notably, cholesterol efflux capacity, HDL-particle number, apoA-I levels as well as LCAT activity recovered following restoration of sinus rhythm (all p < 0.001). We identified marked alterations in HDL function, HDL maturation, and HDL-particle number in AF patients. Assessing HDL-particle number and function in AF may be used as a surrogate marker of AF onset and progression and may help identifying patients at high risk.

Development of novel aptamers for low-density lipoprotein particle quantification

Cardiovascular disease (CVD) remains the leading cause of death worldwide. Low-density lipoprotein cholesterol (LDL-C) is commonly used for CVD risk assessment; however, recent research has shown LDL particle (LDL-P) number to be a more sensitive indicator of CVD risk than both LDL-C and non-high-density lipoprotein cholesterol (HDL-C). Described herein are five single stranded DNA aptamers with dissociation constants in the low picomolar range specific to LDL-P and its subfractions. Furthermore, a set of antisense sequences have been developed and characterized that are capable of binding to the best aptamers and undergoing displacement by LDL-P for use in a simple, affordable diagnostic assay.

CVD Risk Stratification in the PCSK9 Era: Is There a Role for LDL Subfractions?

Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors reduce the risk of cardiovascular events and all-cause mortality in patients at high risk of cardiovascular disease (CVD). Due to high costs and unknown long-term adverse effects, critical evaluation of patients considered for PCSK9 inhibitors is important. It has been proposed that measuring low-density lipoprotein (LDL) subfractions, or LDL particle numbers (LDL-P), could be of value in CVD risk assessment and may identify patients at high risk of CVD. This review evaluates the evidence for the use of LDL subfractions, or LDL-P, when assessing CVD risk in patients for whom PCSK9 inhibitors are considered as a lipid-lowering therapy. Numerous methods for measuring LDL subfractions and LDL-P are available, but several factors limit their availability. A lack of standardization makes comparison between the different methods challenging. Longitudinal population-based studies have found an independent association between different LDL subfractions, LDL-P, and an increased risk of cardiovascular events, but definitive evidence that these measurements add predictive value to the standard risk markers is lacking. No studies have proven that these measurements improve clinical outcomes. PCSK9 inhibitors seem to be effective at lowering all LDL subfractions and LDL-P, but any evidence that measuring LDL subfractions and LDL-P yield clinically useful information is lacking. Such analyses are currently not recommended when considering whether to initiate PCKS9 inhibitors in patients at risk of CVD.

Quantifying Atherogenic Lipoproteins: Current and Future Challenges in the Era of Personalized Medicine and Very Low Concentrations of LDL Cholesterol. A Consensus Statement from EAS and EFLM

BACKGROUND

The European Atherosclerosis Society-European Federation of Clinical Chemistry and Laboratory Medicine Consensus Panel aims to provide recommendations to optimize atherogenic lipoprotein quantification for cardiovascular risk management.

CONTENT

We critically examined LDL cholesterol, non-HDL cholesterol, apolipoprotein B (apoB), and LDL particle number assays based on key criteria for medical application of biomarkers. (a) Analytical performance: Discordant LDL cholesterol quantification occurs when LDL cholesterol is measured or calculated with different assays, especially in patients with hypertriglyceridemia >175 mg/dL (2 mmol/L) and low LDL cholesterol concentrations <70 mg/dL (1.8 mmol/L). Increased lipoprotein(a) should be excluded in patients not achieving LDL cholesterol goals with treatment. Non-HDL cholesterol includes the atherogenic risk component of remnant cholesterol and can be calculated in a standard nonfasting lipid panel without additional expense. ApoB more accurately reflects LDL particle number. (b) Clinical performance: LDL cholesterol, non-HDL cholesterol, and apoB are comparable predictors of cardiovascular events in prospective population studies and clinical trials; however, discordance analysis of the markers improves risk prediction by adding remnant cholesterol (included in non-HDL cholesterol) and LDL particle number (with apoB) risk components to LDL cholesterol testing. (c) Clinical and cost-effectiveness: There is no consistent evidence yet that non-HDL cholesterol-, apoB-, or LDL particle-targeted treatment reduces the number of cardiovascular events and healthcare-related costs than treatment targeted to LDL cholesterol.

SUMMARY

Follow-up of pre- and on-treatment (measured or calculated) LDL cholesterol concentration in a patient should ideally be performed with the same documented test method. Non-HDL cholesterol (or apoB) should be the secondary treatment target in patients with mild to moderate hypertriglyceridemia, in whom LDL cholesterol measurement or calculation is less accurate and often less predictive of cardiovascular risk. Laboratories should report non-HDL cholesterol in all standard lipid panels.

Core lipid, surface lipid and apolipoprotein composition analysis of lipoprotein particles as a function of particle size in one workflow integrating asymmetric flow field-flow fractionation and liquid chromatography-tandem mass spectrometry

Lipoproteins are complex molecular assemblies that are key participants in the intricate cascade of extracellular lipid metabolism with important consequences in the formation of atherosclerotic lesions and the development of cardiovascular disease. Multiplexed mass spectrometry (MS) techniques have substantially improved the ability to characterize the composition of lipoproteins. However, these advanced MS techniques are limited by traditional pre-analytical fractionation techniques that compromise the structural integrity of lipoprotein particles during separation from serum or plasma. In this work, we applied a highly effective and gentle hydrodynamic size based fractionation technique, asymmetric flow field-flow fractionation (AF4), and integrated it into a comprehensive tandem mass spectrometry based workflow that was used for the measurement of apolipoproteins (apos A-I, A-II, A-IV, B, C-I, C-II, C-III and E), free cholesterol (FC), cholesterol esters (CE), triglycerides (TG), and phospholipids (PL) (phosphatidylcholine (PC), sphingomyelin (SM), phosphatidylethanolamine (PE), phosphatidylinositol (PI) and lysophosphatidylcholine (LPC)). Hydrodynamic size in each of 40 size fractions separated by AF4 was measured by dynamic light scattering. Measuring all major lipids and apolipoproteins in each size fraction and in the whole serum, using total of 0.1 ml, allowed the volumetric calculation of lipoprotein particle numbers and expression of composition in molar analyte per particle number ratios. Measurements in 110 serum samples showed substantive differences between size fractions of HDL and LDL. Lipoprotein composition within size fractions was expressed in molar ratios of analytes (A-I/A-II, C-II/C-I, C-II/C-III. E/C-III, FC/PL, SM/PL, PE/PL, and PI/PL), showing differences in sample categories with combinations of normal and high levels of Total-C and/or Total-TG. The agreement with previous studies indirectly validates the AF4-LC-MS/MS approach and demonstrates the potential of this workflow for characterization of lipoprotein composition in clinical studies using small volumes of archived frozen samples.

Update on the laboratory investigation of dyslipidemias

The role of the clinical laboratory is evolving to provide more information to clinicians to assess cardiovascular disease (CVD) risk and target therapy more effectively. Current routine methods to measure LDL-cholesterol (LDL-C), the Friedewald calculation, ultracentrifugation, electrophoresis and homogeneous direct methods have established limitations. Studies suggest that LDL and HDL size or particle concentration are alternative methods to predict future CVD risk. At this time there is no consensus role for lipoprotein particle or subclasses in CVD risk assessment. LDL and HDL particle concentration are measured by several methods, namely gradient gel electrophoresis, ultracentrifugation-vertical auto profile, nuclear magnetic resonance and ion mobility. It has been suggested that HDL functional assays may be better predictors of CVD risk. To assess the issue of lipoprotein subclasses/particles and HDL function as potential CVD risk markers robust, simple, validated analytical methods are required. In patients with small dense LDL particles, even a perfect measure of LDL-C will not reflect LDL particle concentration. Non-HDL-C is an alternative measurement and includes VLDL and CM remnant cholesterol and LDL-C. However, apolipoprotein B measurement may more accurately reflect LDL particle numbers. Non-fasting lipid measurements have many practical advantages. Defining thresholds for treatment with new measurements of CVD risk remain a challenge. In families with genetic variants, ApoCIII and lipoprotein (a) may be additional risk factors. Recognition of familial causes of dyslipidemias and diagnosis in childhood will result in early treatment. This review discusses the limitations in current laboratory technologies to predict CVD risk and reviews the evidence for emergent approaches using newer biomarkers in clinical practice.

A Routine 'Top-Down' Approach to Analysis of the Human Serum Proteome

Serum provides a rich source of potential biomarker proteoforms. One of the major obstacles in analysing serum proteomes is detecting lower abundance proteins owing to the presence of hyper-abundant species (e.g., serum albumin and immunoglobulins). Although depletion methods have been used to address this, these can lead to the concomitant removal of non-targeted protein species, and thus raise issues of specificity, reproducibility, and the capacity for meaningful quantitative analyses. Altering the native stoichiometry of the proteome components may thus yield a more complex series of issues than dealing directly with the inherent complexity of the sample. Hence, here we targeted method refinements so as to ensure optimum resolution of serum proteomes via a top down two-dimensional gel electrophoresis (2DE) approach that enables the routine assessment of proteoforms and is fully compatible with subsequent mass spectrometric analyses. Testing included various fractionation and non-fractionation approaches. The data show that resolving 500 µg protein on 17 cm 3–10 non-linear immobilised pH gradient strips in the first dimension followed by second dimension resolution on 7–20% gradient gels with a combination of lithium dodecyl sulfate (LDS) and sodium dodecyl sulfate (SDS) detergents markedly improves the resolution and detection of proteoforms in serum. In addition, well established third dimension electrophoretic separations in combination with deep imaging further contributed to the best available resolution, detection, and thus quantitative top-down analysis of serum proteomes.

Serum Concentration of HDL Particles Predicts Mortality in Acute Heart Failure Patients

Clinical studies have shown that assessing circulating concentrations of high-density lipoprotein (HDL) particles by nuclear magnetic resonance (NMR) spectroscopy is superior to HDL-cholesterol in predicting cardiovascular risk. We tested the hypothesis that circulating concentrations of HDL particles predict 3-month mortality of patients with acute heart failure (AHF). Out of 152 included patients, 52% were female, additionally the mean patient age was 75.2 ± 10.3 years, and three-month mortality was 27%. Serum lipoprotein profile at admission was determined by NMR spectroscopy. Univariate logistic regression analyses revealed a significant inverse association of total (odds ratio (OR) 0.38 per 1-SD increase, 95% confidence interval (CI) 0.23-0.60, p < 0.001) and small HDL particle concentrations (OR 0.35 per 1-SD increase, 95% CI 0.19-0.60, p < 0.001) with 3-month mortality, whereas concentrations of large HDL particles (p = 0.353) or HDL-cholesterol (p = 0.107) showed no significant association. After adjustment for age, sex, mean arterial pressure, low-density lipoprotein cholesterol, glomerular filtration rate, urea, and N-terminal pro-brain natriuretic peptide, both the total and small HDL particle concentrations remained significantly associated with 3-month mortality. Based on our results, we conclude that total and small HDL particle concentrations strongly and independently predict 3-month mortality in AHF patients.

Impact of menopause and diabetes on atherogenic lipid profile: is it worth to analyse lipoprotein subfractions to assess cardiovascular risk in women?

Cardiovascular disease is the leading cause of death in women at advanced age, who are affected a decade later compared to men. Cardiovascular risk factors in women are not properly investigated nor treated and events are frequently lethal. Both menopause and type 2 diabetes substantially increase cardiovascular risk in the female sex, promoting modifications on lipid metabolism and circulating lipoproteins. Lipoprotein subfractions suffer a shift after menopause towards a more atherogenic lipid profile, consisted of hypertriglyceridemia, lower levels of both total high density lipoprotein (HDL) and its subfraction HDL2, but also higher levels of HDL3 and small low-density lipoprotein particles. This review discusses the impact of diabetes and menopause to the lipid profile, challenges in lipoprotein subfractions determination and their potential contribution to the cardiovascular risk assessment in women. It is still unclear whether lipoprotein subfraction changes are a major driver of cardiometabolic risk and which modifications are predominant. Prospective trials with larger samples, methodological standardizations and pharmacological approaches are needed to clarify the role of lipoprotein subfractions determination on cardiovascular risk prediction and intervention planning in postmenopausal women, with or without DM.