Use of Apolipoprotein B in the Era of Precision Medicine: Time for a Paradigm Change?

Lipids and apolipoproteins and the risk of vascular disease and mortality outcomes in women and men with type 2 diabetes in the ADVANCE study

AIM

Whether apolipoproteins (apolipoprotein A1, apolipoprotein B, apolipoprotein B/apolipoprotein A1 [ApoB/ApoA1] ratio) or very-low-density lipoprotein (VLDL) cholesterol are better risk predictors than established lipid risk markers, and whether there are sex differences, is uncertain, both in general populations and in patients with diabetes. The aim of this study was to assess the association between established risk markers, apolipoproteins and the risk of macro- and microvascular disease and death in a large study of women and men with diabetes and to assess the potential sex differences in the associations.

MATERIALS AND METHODS

Established lipid risk markers were studied in 11 140 individuals with type 2 diabetes from the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified-Release Controlled Evaluation (ADVANCE) trial, and apolipoproteins (A1, B, ApoB/ApoA1 ratio) and VLDL cholesterol from nuclear magnetic resonance (NMR) lipid analyses in biobanked samples from 3586 individuals included in the ADVANCE case-cohort study (ADVANCE CC). Primary outcomes were major macro- and microvascular events and death. Cox proportional hazards models adjusted for confounders were used to quantify the associations (hazard ratio [HR] and 95% confidence intervals [CIs]) between established lipid risk markers and apolipoproteins with study outcomes. To address potential effect modification by sex, we investigated the association between the lipid risk markers and outcomes in subgroup analyses by sex.

RESULTS

There was a lower risk of macrovascular complications for high-density lipoprotein (HDL) cholesterol (HR [95%CI] 0.88 [0.82-0.95]), a higher risk for total cholesterol (1.10 [1.04-1.17]), low-density lipoprotein (LDL) cholesterol (1.15 [1.08-1.22]), non-HDL cholesterol (1.13 [1.07-1.20]) and the total cholesterol/HDL ratio (1.20 [1.14-1.27]) but no significant associations with triglycerides from ADVANCE. There was a higher risk of macrovascular complications for the ApoB/ApoA1 ratio (1.13 [1.03-1.24]) from the ADVANCE CC. Only the ApoB/ApoA1 ratio (1.19 [1.06-1.34]), but none of the established lipid risk markers, was associated with a higher risk of microvascular complications. There were no statistically significant sex differences for any of the established lipid risk markers or apolipoproteins with any outcome. Using C-statistics and net reclassification improvement (NRI) did not detect significant improvement in predicting all outcomes by adding lipids or apolipoproteins to the models with confounding factors only.

CONCLUSIONS/INTERPRETATION

All established lipid risk markers, except triglycerides, were predictors of macrovascular complications, but not microvascular complications, in patients with type 2 diabetes. The ApoB/ApoA1 ratio was associated with major macro- and microvascular complications, but there was no evidence that apolipoproteins are better than established lipid risk markers in predicting cardiovascular complications in patients with type 2 diabetes.

An equation for estimating low-density lipoprotein-triglyceride content and its use for cardiovascular disease risk stratification

Background

The triglyceride (TG) content of low-density lipoprotein (LDL-TG) has been shown to be more predictive of atherosclerotic cardiovascular disease (ASCVD) events than the cholesterol content of LDL (LDL-C). The goal of our study was to develop an equation for estimating LDL-TG (eLDL-TG) based on the standard lipid panel and to compare it to estimated LDL-C as an ASCVD risk biomarker.

Methods

Using least-square regression analysis, the following eLDL-TG equation was developed: e LDL - TG = TG 38.5 + NonHDL - C 5.75 + 9 .75 TG NonHDL - C + 244 HDL - C - 2.95 . LDL-TG was measured by the β-quantification (BQ) reference method (N = 40,202). LDL-C was calculated by the Sampson-NIH equation. The association of LDL-C and eLDL-TG with ASCVD risk markers was performed in the National Heart and Nutrition Examination Survey (NHANES) (N = 37,053) and with ASCVD events in a primary prevention cohort from the UK Biobank (UKB) (N = 429,367) and the Atherosclerosis Risk in Communities (ARIC) study (N = 14,632).

Results

eLDL-TG showed better ASCVD risk stratification of UKB participants than LDL-C (Wilcoxon Chi-Square: 2,099.6 vs. 418.7, respectively). Receiving-operating characteristics analysis revealed that eLDL-TG had a stronger association with ASCVD events than LDL-C (AUC: 0.596 vs. 0.542, respectively) and other conventional lipid markers. Similar findings were found in ARIC. Discordance analysis in UKB showed that the group with low LDL-C/high eLDL-TG had a similar risk as the high LDL-C/high eLDL-TG group. Furthermore, these same two groups with the highest eLDL-TG levels and the highest ASCVD event rate also had higher mean levels of systolic blood pressure, Body Mass Index, hemoglobin A1C, and C-reactive protein than the two lower eLDL-TG groups. Using eLDL-TG > 44.6 mg/dl (80th percentile) as a cut-point leads to a hazard ratio of 1.32 (95% CI, 1.29-1.36) for ASCVD events, which remained significant after adjustment for LDL-C and apoB. Furthemore, using eLDL-TG as a risk-enhancer test leads to reclassification of 50% more high-risk individuals than current lipid-enhancer test rules.

Conclusions

Like LDL-C, LDL-TG can also be calculated from the results of the standard lipid panel. Compared to estimated LDL-C, eLDL-TG was a better risk marker for primary prevention and hence could improve initial ASCVD risk stratification.

The role of lipase maturation factor 1 in hypertriglyceridaemia and atherosclerosis: An update

Lipase maturation factor 1 is an endoplasmic reticulum-resident transmembrane protein, which acts as a critical chaperone necessary for the folding, dimerisation, and secretion of lipases. In this review, we summarise data about the recently revealed role of lipase maturation factor 1 in endoplasmic reticulum redox homeostasis, its novel interaction partners among oxidoreductases and lectin chaperones, and the identification of fibronectin and the low-density lipoprotein receptor as novel non-lipase client proteins of lipase maturation factor 1. Additionally, the role of lipase maturation factor 1-derived circular RNA in atherosclerosis progression via the miR-125a-3p/vascular endothelial growth factor A\Fibroblast Growth Factor 1 axis is discussed. Finally, we focus on the causative role of lipase maturation factor 1 variants in the development of hypertriglyceridaemia - a type of dyslipidaemia that significantly contributes to the development of atherosclerosis and other cardiovascular diseases via different mechanisms.

Polygenic Risk Scores: The Next Step for Improved Risk Stratification in Coronary Artery Disease?

Despite significant advances in the management of coronary artery disease (CAD) and reductions in annual mortality rates in recent decades, this disease remains the leading cause of death worldwide. Consequently, there is an ongoing need for efforts to address this situation. Current clinical algorithms to identify at-risk patients are particularly inaccurate in moderate-risk individuals. For this reason, the need for ancillary tests has been suggested, including predictive genetic screening. As genetic studies rapidly expand and genomic data becomes more accessible, numerous genetic risk scores have been proposed to identify and evaluate an individual's susceptibility to developing diseases, including CAD. The field of genetics has indeed made substantial contributions to risk prediction, particularly in cases where children have parents with premature CAD, resulting in an increased risk of up to 75%. The polygenic risk scores (PRSs) have emerged as a potentially valuable tool for understanding and stratifying an individual's genetic risk. The PRS is calculated as a weighted sum of single-nucleotide variants present throughout the human genome, identifiable through genome-wide association studies, and associated with various cardiometabolic diseases. The use of PRSs holds promise, as it enables the development of personalized strategies for preventing or diagnosing specific pathologies early. Furthermore, it can complement existing clinical scores, increasing the accuracy of individual risk prediction. Consequently, the application of PRSs has the potential to impact the costs and adverse outcomes associated with CAD positively. This narrative review provides an overview of the role of PRSs in the context of CAD.

Modification of lipoprotein metabolism and function driving atherogenesis in diabetes

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease, characterized by raised blood glucose levels and impaired lipid metabolism resulting from insulin resistance and relative insulin deficiency. In diabetes, the peculiar plasma lipoprotein phenotype, consisting in higher levels of apolipoprotein B-containing lipoproteins, hypertriglyceridemia, low levels of HDL cholesterol, elevated number of small, dense LDL, and increased non-HDL cholesterol, results from an increased synthesis and impaired clearance of triglyceride rich lipoproteins. This condition accelerates the development of the atherosclerotic cardiovascular disease (ASCVD), the most common cause of death in T2DM patients. Here, we review the alteration of structure, functions, and distribution of circulating lipoproteins and the pathophysiological mechanisms that induce these modifications in T2DM. The review analyzes the influence of diabetes-associated metabolic imbalances throughout the entire process of the atherosclerotic plaque formation, from lipoprotein synthesis to potential plaque destabilization. Addressing the different pathophysiological mechanisms, we suggest improved approaches for assessing the risk of adverse cardiovascular events and clinical strategies to reduce cardiovascular risk in T2DM and cardiometabolic diseases.

Metabolic dysfunction-associated steatotic liver disease and atherosclerosis

PURPOSE OF REVIEW

To update information about the relationship between metabolic dysfunction-associated steatotic liver disease (MASLD) and atherosclerosis. This review emphasizes the potential mechanisms linking MASLD with atherosclerosis and the possible causal relationships between these conditions.

RECENT FINDINGS

An increased risk of cardiovascular disease is related to MASLD. Several molecular, cellular, and metabolic mechanisms have been described to explain the development of atherothrombosis in MASLD patients. These include atherogenic dyslipidemia, low-grade vascular inflammation, endothelial dysfunction, foam cell formation, proliferation of vascular smooth muscle cells, insulin resistance, gut microbiota dysbiosis, activation of renin-angiotensin and sympathetic nervous systems, hypercoagulability, and decreased fibrinolysis. Also, there is recent evidence suggesting an association between genetically driven liver fat and coronary heart disease mediated by the causal effect of apoB-containing lipoproteins. Several meta-analyses and systematic reviews have reported a strong association between MASLD and cardiovascular outcomes. MASLD is an important and independent risk factor for atherosclerosis development. Multiple mechanisms may be involved in this association. Further research is required to establish a causal association between MASLD and atherosclerosis.

Blood Lipids, Lipoproteins, and Apolipoproteins With Risk of Coronary Heart Disease: A Prospective Study Among Racially Diverse Populations

BACKGROUND

Comprehensive blood lipoprotein profiles and their association with incident coronary heart disease (CHD) among racially and geographically diverse populations remain understudied.

METHODS AND RESULTS

We conducted nested case-control studies of CHD among 3438 individuals (1719 pairs), including 1084 White Americans (542 pairs), 1244 Black Americans (622 pairs), and 1110 Chinese adults (555 pairs). We examined 36 plasma lipids, lipoproteins, and apolipoproteins, measured by nuclear magnetic resonance spectroscopy, with incident CHD among all participants and subgroups by demographics, lifestyle, and metabolic health status using conditional or unconditional logistic regression adjusted for potential confounders. Conventionally measured blood lipids, that is, total cholesterol, triglycerides, low-density lipoprotein-cholesterol, and high-density lipoprotein-cholesterol, were each associated with incident CHD, with odds ratios (ORs) being 1.33, 1.32, 1.24, and 0.79 per 1-SD increase among all participants. Seventeen lipoprotein biomarkers showed numerically stronger associations than conventional lipids, with ORs per 1-SD among all participants ranging from 1.35 to 1.57 and a negative OR of 0.78 (all false discovery rate <0.05), including apolipoprotein B100 to apolipoprotein A1 ratio (OR, 1.57 [95% CI, 1.45-1.7]), low-density lipoprotein-triglycerides (OR, 1.55 [95% CI, 1.43-1.69]), and apolipoprotein B (OR, 1.49 [95% CI, 1.37-1.62]). All these associations were significant and consistent across racial groups and other subgroups defined by age, sex, smoking, obesity, and metabolic health status, including individuals with normal levels of conventionally measured lipids.

CONCLUSIONS

Our study highlighted several lipoprotein biomarkers, including apolipoprotein B/ apolipoprotein A1 ratio, apolipoprotein B, and low-density lipoprotein-triglycerides, strongly and consistently associated with incident CHD. Our results suggest that comprehensive lipoprotein measures may complement the standard lipid panel to inform CHD risk among diverse populations.

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.