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

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.