Identification of Dysbetalipoproteinemia by an Enhanced Sampson-NIH Equation for Very Low-Density Lipoprotein-Cholesterol

Interaction Between Primary Hyperlipidemias and Type 2 Diabetes: Therapeutic Implications

There is a gap of knowledge about the clinical and pathophysiological implications resulting from the interaction between primary hyperlipidemias and type 2 diabetes (T2D). Most of the existing evidence comes from sub-analyses of cohorts; scant information derives from randomized clinical trials. The expected clinical implications of T2D in patients with primary hyperlipidemias is an escalation of their already high cardiovascular risk. There is a need to accurately identify patients with this dual burden and to adequately prescribe lipid-lowering therapies, with the current advancements in newer therapeutic options. This review provides an update on the interactions of primary hyperlipidemias, such as familial combined hyperlipidemia, familial hypercholesterolemia, multifactorial chylomicronemia, lipoprotein (a), and type 2 diabetes.

Evaluation of biochemical algorithms to screen dysbetalipoproteinemia in ε2ε2 and rare APOE variants carriers

OBJECTIVES

Dysbetalipoproteinemia (DBL) is a combined dyslipidemia associated with an increased risk of atherosclerotic cardiovascular diseases mostly occurring in ε2ε2 subjects and infrequently in subjects with rare APOE variants. Several algorithms have been proposed to screen DBL. In this work, we compared the diagnostic performances of nine algorithms including a new one.

METHODS

Patients were divided into 3 groups according to their APOE genotype: ε2ε2 ("ε2ε2", n=49), carriers of rare variants ("APOEmut", n=20) and non-carriers of ε2ε2 nor APOE rare variant ("controls", n=115). The algorithms compared were those from Fredrickson, Sniderman, Boot, Paquette, De Graaf, Sampson, eSampson, Bea and ours, the "Hospices Civils de Lyon (HCL) algorithm". Our gold standard was the presence of a ε2ε2 genotype or of a rare variant associated with triglycerides (TG) >1.7 mmol/L. A replication in the UK Biobank and a robustness analysis were performed by considering only subjects with both TG and low-density lipoprotein-cholesterol (LDLc) >90th percentile.

RESULTS

Total cholesterol (TC)/ApoB and NHDLC/ApoB are the best ratios to suspect DBL. In ε2ε2, according to their likelihood ratios (LR), the most clinically efficient algorithms were the HCL, Sniderman and De Graaf's. In APOEmut, Sniderman's algorithm exhibited the lowest negative LR (0.07) whereas the HCL's exhibited the highest positive LR (29). In both cohorts, the HCL algorithm had the best LR.

CONCLUSIONS

We proposed a powerful algorithm based on ApoB concentration and the routine lipid profile, which performs remarkably well in detecting ε2ε2 or APOE variant-related DBL. Additional studies are needed to further evaluate algorithms performances in DBL carriers of infrequent APOE variants.

An improved method for estimating low LDL-C based on the enhanced Sampson-NIH equation

BACKGROUND

The accurate measurement of Low-density lipoprotein cholesterol (LDL-C) is critical in the decision to utilize the new lipid-lowering therapies like PCSK9-inhibitors (PCSK9i) for high-risk cardiovascular disease patients that do not achieve sufficiently low LDL-C on statin therapy.

OBJECTIVE

To improve the estimation of low LDL-C by developing a new equation that includes apolipoprotein B (apoB) as an independent variable, along with the standard lipid panel test results.

METHODS

Using β-quantification (BQ) as the reference method, which was performed on a large dyslipidemic population (N = 24,406), the following enhanced Sampson-NIH equation (eS LDL-C) was developed by least-square regression analysis: [Formula: see text] RESULTS: The eS LDL-C equation was the most accurate equation for a broad range of LDL-C values based on regression related parameters and the mean absolute difference (mg/dL) from the BQ reference method (eS LDL-C: 4.51, Sampson-NIH equation [S LDL-C]: 6.07; extended Martin equation [eM LDL-C]: 6.64; Friedewald equation [F LDL-C]: 8.3). It also had the best area-under-the-curve accuracy score by Regression Error Characteristic plots for LDL-C < 100 mg/dL (eS LDL-C: 0.953; S LDL-C: 0.920; eM LDL-C: 0.915; F LDL-C: 0.874) and was the best equation for categorizing patients as being below or above the 70 mg/dL LDL-C treatment threshold for adding new lipid-lowering drugs by kappa score analysis when compared to BQ LDL-C for TG < 800 mg/dL (eS LDL-C: 0.870 (0.853-0.887); S LDL-C:0.763 (0.749-0.776); eM LDL-C:0.706 (0.690-0.722); F LDL-C:0.687 (0.672-0.701). Approximately a third of patients with an F LDL-C < 70 mg/dL had falsely low test results, but about 80% were correctly reclassified as higher (≥ 70 mg/dL) by the eS LDL-C equation, making them potentially eligible for PCSK9i treatment. The M LDL-C and S LDL-C equations had less false low results below 70 mg/dL than the F LDL-C equation but reclassification by the eS LDL-C equation still also increased the net number of patients correctly classified.

CONCLUSIONS

The use of the eS LDL-C equation as a confirmatory test improves the identification of high-risk cardiovascular disease patients, who could benefit from new lipid-lowering therapies but have falsely low LDL-C, as determined by the standard LDL-C equations used in current practice.

Low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol and apolipoprotein B for cardiovascular care

PURPOSE OF REVIEW

Some experts and consensus groups continue to argue that apolipoprotein B (apoB) should not be introduced broadly into clinical care. But, too often, the present approach to clinical care is not succeeding. An important reason for this failure, we believe, is that the conventional approach limits what the expert clinician can accomplish and is too complex, confusing, and contradictory for primary care physicians to apply effectively in their practise.

RECENT FINDINGS

There are four major reasons that apoB should be measured routinely in clinical care. First, apoB is a more accurate marker of cardiovascular risk than LDL-C or non-HDL-C. Second, the measurement of apoB is standardized whereas the measurements of LDL-C and non-HDL-C are not. Third, with apoB and a conventional lipid panel, all the lipid phenotypes can be simply and accurately distinguished. This will improve the care of the expert. Fourth, apoB, as the single measure to evaluate the success of therapy, would simplify the process of care for primary care physicians.

SUMMARY

By introducing apoB broadly into clinical care, the process of care will be improved for both the expert and the primary care physician, and this will improve the outcomes of care.

Triglyceride-rich lipoprotein cholesterol and cardiovascular risk

PURPOSE OF REVIEW

The triglyceride-rich apoB lipoprotein particles make up a minority of the apoB particles in plasma. They vary in size, in lipid, and in protein content. Most are small enough to enter the arterial wall and therefore most are atherogenic. But how important a contribution TRL particles make to the total risk created by the apoB lipoproteins remains controversial. A recent Mendelian randomization analysis determined that the cardiovascular risk related to the cholesterol within these apoB particles--the TRL cholesterol--was greater than--and independent of--the risk related to apoB. If correct, these observations have major clinical significance.

RECENT FINDINGS

Accordingly, we have analyzed these results in detail. In our view, the independent strength of the association between TRL cholesterol and apoB with cardiovascular risk seems inconsistent with the biological connections between apoB and cholesterol as integral and highly correlated constituents of apoB particles. These results are also inconsistent with other lines of evidence such as the results of the fibrate randomized clinical trials. Moreover, we are also concerned with other aspects of the analysis.

SUMMARY

We do not regard the issue as settled. However, this enquiry has led us to a fuller understanding of the determinants of the cholesterol content of the TRL apoB particles and the complex processing of cholesterol amongst the plasma lipoproteins.

Performance of the enhanced Sampson-NIH equation for VLDL-C and LDL-C in a population with familial combined hyperlipidemia

INTRODUCTION

Low-density cholesterol (LDL-C) has long been estimated by the Friedewald formula (F-LDL-C); however, this method underestimates LDL-C in patients with hypertriglyceridemia (HTG) or low LDL-C levels. The Martin (M-LDL-C) and Sampson (S-LDL-C) formulas partially resolve these limitations. Recently, Sampson et al. developed a new equation (eS-VLDL-C) that includes ApoB. This new equation could be particularly useful in FCHL, which is characterized by the predominance of triglyceride-rich VLDL and a discordance between LDL-C and ApoB.

METHODS

Very low-density lipoproteins (VLDL-C) was measured in 336 patients with FCHL by sequential ultracentrifugation. LDL-C was estimated by subtracting VLDL-C, estimated by the different equations, from non-HDL cholesterol. Spearman correlations, R2, mean squared error (RMSE), and bias were used to compare the accuracy of the different equations. Concordance of the estimated LDL-C values with LDL-C thresholds and ApoB was also assessed by their kappa coefficients and ROC analysis.

RESULTS

Overall population had a mean age of 47 years, and 61.5% were women. 19.5% had type 2 diabetes, hypertension was present in 20.8%, and only 12.2% were on statin treatment. Both S-LDL-C and eS-LDL-C performed similarly, and better than M-LDL-C and F-LDL-C. In Bland-Altman analysis, eS-LDL-C showed the lowest bias, better performance in HTG, and better concordance with LDL-C treatment goals compared to other formulas (e.g. ρ: 0.87, 95% CI 0.84-0.89).

CONCLUSIONS

LDL-S and LDL-eS equations estimate the concentration of LDL-C with greater accuracy than other formulas. The LDL-eS has best performance in estimating LDL-C with lower RMSE than other formulas.

Diagnosis of Familial Dysbetalipoproteinemia Based on the Lipid Abnormalities Driven by APOE2/E2 Genotype

BACKGROUND

Familial dysbetalipoproteinemia (FDBL) is a monogenic disease due to variants in APOE with a highly variable phenotype. Current diagnostic lipid-based methods have important limitations. The objective is twofold: to define characteristics of dysbetalipoproteinemia (DBL) based on the analysis of APOE in patients from a lipid unit and in a sample from the general population, and to propose a screening algorithm for FDBL.

METHODS

Lipids and APOE genotype from consecutive unrelated subjects from Miguel Servet University Hospital (MSUH) (n 3603), subjects from the general population participants of the Aragon Workers Health Study (AWHS) (n 4981), and selected subjects from external lipid units (Ext) (n 390) were used to define DBL criteria and to train and validate a screening tool.

RESULTS

Thirty-five subjects from MSUH, 21 subjects from AWHS, and 31 subjects from Ext were APOE2/2 homozygous. The combination of non high-density lipoprotein cholesterol (non-HDLc)/apoB 1.7 plus triglycerides/apoB 1.35, in mg/dL (non-HDLc [mmol/L]/apolipoprotein B (apoB) [g/L] 4.4 and triglycerides [mmol/L]/apoB [g/L] 3.5), provided the best diagnostic performance for the identification of subjects with hyperlipidemia and APOE2/2 genotype (sensitivity 100 in the 3 cohorts, and specificity 92.8 [MSUH], 80.9 [AWHS], and 77.6 [Ext]). This improves the performance of previous algorithms. Similar sensitivity and specificity were observed in APOE2/2 subjects receiving lipid-lowering drugs.

CONCLUSIONS

The combination of non-HDLc/apoB and triglycerides/apoB ratios is a valuable tool to diagnose DBL in patients with hyperlipidemia with or without lipid-lowering drugs. FDBL diagnosis requires DBL and the presence of a compatible APOE genotype. Most adult APOE2/2 subjects express DBL, making FDBL as common as familial hypercholesterolemia in the population.