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Data supporting the use of apolipoproteins (APOs) in the assessment of chronic disease continues to mount, with a recent analysis published in the American Journal of Clinical Nutrition suggesting that ApoA1 has a protective effect that extends to dying from all causes, including cardiovascular disease and lung cancer, and that ApoB increases the risk for all-cause and cardiovascular disease mortality. This large-scale prospective cohort included over 340,000 individuals from the UK Biobank cohort, providing both observational and Mendelian randomization (MR) analyses, with the latter pointing to potentially causative relationships. Specifically, both observational and MR analyses indicate ApoB is positively linked and ApoA1 is inversely linked to all-cause and CVD-related mortality, while MR also suggests that ApoA1 is also inversely linked to lung cancer mortality (MR did not support an association between cancer mortality and ApoB).
Also, just published in Cardiovascular Diabetology are the results of an MR using the Integrative Epidemiology Unit Open GWAS (Genome-Wide Association Study) database, the largest European GWAS, including data from over 115,000 individuals. Although unfortunately limited to individuals of European descent, there are many takeaways from this study that help to highlight the potentially causal role of these apolipoproteins. The ratio of ApoB to ApoA1 was found to be significantly and positively related to many ischemic diseases, including heart disease, cerebrovascular disease, and peripheral arterial disease. Increases in ApoB/ApoA1 also led to an increase in MACE (major adverse cardiovascular events) as well as the incidence of aortic aneurysm, atrial flutter/fibrillation, and non-rheumatic valve diseases, with multivariate analyses indicating that ApoB/ApoA1 has a causal role in myocardial infarction, abdominal aortic aneurysm, and MACE. ApoB/ApoA1 also had strong causal associations with biomarkers of glucose metabolism and weight control, including hemoglobin A1c, fasting insulin, BMI, etc., as well as behavioral risk factors, including smoking and sedentary behavior.
Of course, LDL-C and HDL-C are typically utilized to capture the same types of risk that appear to be causally associated with ApoB and ApoA1, respectively, and it’s worth describing what each apolipoprotein represents in comparison. ApoB is a structural protein, with a single ApoB particle (of which there are two types, ApoB48 and ApoB100) encircling a number of different lipoproteins, including VLDL, LDL, IDL, Lp(a), and chylomicrons. While the concentration of cholesterol and triglycerides may vary within each type of lipoprotein (i.e., an LDL-C measures the average concentration of cholesterol within the LDL particles, not the number of LDL particles), the number of ApoB particles is fixed at one per lipoprotein particle.
The model of atherosclerosis that has gained traction in recent years, reviewed in JAMA Cardiology, proposes that it is the number of ApoB lipoprotein particles (rather than the mass of cholesterol contained in them) that actually promotes atherosclerosis in the lumen of an artery, driving the process from start to finish. These particles become trapped in the subintimal space of an artery wall and initiate the subsequent inflammation that follows. Similarly, ApoA1 is the structural protein found encircling HDL particles, again an indicator of the number of particles not the concentration of cholesterol within them.
Even though they are highly correlated, there are a number of advantages of ApoB as a marker of risk compared to LDL-C, with multiple trials indicating that when they are discordant, ApoB is a better predictor of risk than either LDL-C or even non-HDL-C (reviewed in JAMA Cardiology). For example, a recent retrospective analysis published in Lipids in Health and Disease collected data from 544 patients with coronary artery disease, and compared the ability of ApoB to both LDL-C and non-HDL-C to predict angiographic progression (AP) over a follow-up of 2.2 years (using coronary computed tomography angiography). Not only was ApoB positively associated with the incidence of AP after multivariate adjustment (including adjustment for HbA1c, HDL-C, Lp(a), statin use, etc.), LDL-C did not correlate with AP when stratified by baseline levels. When LDL-C and ApoB were discordant, ApoB was predictive of AP while LDL-C was not, with a similar lack of predictive value observed for non-HDL-C. Overall, the study continues to support the conclusion that ApoB may be a better biomarker for risk of disease progression (perhaps because it reflects causality more directly than LDL-C and non-HDL-C), and may identify risk that is not captured by standard lipid assessments. Also, because ApoB appears to be causally related, therapies that significantly lower ApoB, such as red yeast rice extract, omega-3 fatty acids, and phytosterols, could potentially be slowing the process of atherosclerosis itself, not simply improving a biomarker.
The use of ApoB and ApoA1 in combination with standard lipid panels may also have value. For instance, an analysis of over 12,000 participants in NHANES (2005 to 2014), again published in Lipids in Health and Disease, utilized the LDL-C to ApoB ratio (LAR) to predict cardiovascular and all-cause mortality over a nearly 6-year period. The ratio is an attempt to estimate LDL particle size, with smaller particles (referred to as pattern B) thought to be more atherogenic, as they more easily enter and become trapped in the arterial wall. Again, it is the number of particles posing a risk, not the cholesterol content within the particles. This NHANES analysis found that LAR was linearly (negatively) associated with all-cause and cardiovascular mortality, irrespective of other standard risk factors, supporting its value as a long-term prognostic indicator.
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