Year : 2020 | Volume
: 8 | Issue : 2 | Page : 48--50
Low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, and apolipoprotein b for cardiovascular risk assessment – What is the right choice?
Shrikanth N Hegde
Anushri Medical and Diabetes Care Centre, Shivamogga, Karnataka, India
Dr. Shrikanth N Hegde
Anushri Medical and Diabetes Care Centre, Tilak Nagar, Behind SBI Bank, Shivamogga - 577 201, Karnataka
|How to cite this article:|
Hegde SN. Low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, and apolipoprotein b for cardiovascular risk assessment – What is the right choice?.APIK J Int Med 2020;8:48-50
|How to cite this URL:|
Hegde SN. Low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, and apolipoprotein b for cardiovascular risk assessment – What is the right choice?. APIK J Int Med [serial online] 2020 [cited 2021 Dec 8 ];8:48-50
Available from: https://www.ajim.in/text.asp?2020/8/2/48/282840
Atherosclerotic cardiovascular diseases (ASCVDs) are the leading cause of mortality and morbidity worldwide. There are several methods to assess and stratify the risk of ASCVD, and thereby, choose therapies to decrease the mortality and morbidity. Estimation of cholesterol content in the lipoproteins and reducing their circulating levels remains the cornerstone of both primary and secondary prevention. Total cholesterol (TC) is a measure of the TC content of the lipoproteins. In the fasting state, it includes cholesterol contents in the very low-density lipoprotein (VLDL), low-density lipoprotein (LDL), high-density lipoprotein (HDL), and lipoprotein (a) (Lp[a]). In the nonfasting state, in addition to these, it includes cholesterol in the chylomicrons and chylomicron remnants. Apolipoprotein B (apoB)-containing lipoproteins such as LDL, VLDL, and Lp (a) play an important role in the pathogenesis of atherosclerosis. These lipoproteins are retained and accumulated within the vascular intima of arteries and reactive inflammatory mechanisms result in atherosclerotic plaque formation. LDL-cholesterol (LDL-C) levels are directly related to the incidence of cardiovascular (CV) events and mortality. There is a strong evidence base showing reduction in LDL-C levels with statins significantly reduces mortality and morbidity and improves survival rates in patients with cardiovascular diseases (CVD). Naturally, LDL-C levels occupy the central stage in risk assessment and as therapeutic targets in CVD prevention. However, despite achieving a good LDL targets, many patients still develop CV events, and this residual risk is said to be due to increased levels of cholesterol in triglyceride (TG)-rich lipoproteins. These atherogenic Apo B-containing lipoproteins are measured by non-HDL-C and high-density lipoprotein cholesterol (HDL-C), which is TC minus HDL-C. In general, LDL particles comprise 90% apoB-containing lipoproteins, but in practice, it is the cholesterol content of LDL, namely LDL-C which is measured, not the LDL particles. When TGs levels are elevated, the cholesterol ester transfer protein causes redistribution of lipids across concentration gradients. The cholesterol-rich lipoproteins such as LDL and HDL receive TG in exchange for their cholesterol. The TGs are eventually catabolized, resulting in cholesterol depleted, less dense and smaller LDL particles which still have atherogenic potential. However, measuring cholesterol from these small and intermediate dense LDL particles does not reflect the total LDL particles. In this situation, non-HDL-C levels reflect a better estimate of atherogenic particles than LDL-C. Non-HDL-C includes cholesterol in LDL, small dense LDL, intermediate-density lipoprotein (IDL), chylomicron, and chylomicron remnant particles. While LDL-C or non-HDL-C are indirect measures of atherogenic particles, apoB represents all atherogenic particles. As each LDL-C, VLDL-cholesterol (VLDL-C), Lp (a) and remnant lipoprotein particles contain a single apoB molecule, estimation of apoB is a true representation of all atherogenic particles. LDL-C, non-HDL-C, and apoB are important markers of ASCVD risk assessment as well as targets to reduce the CV risk. Many clinical practice guidelines have identified LDL-C as a primary target, and some guidelines have included non-HDL-C and apoB as secondary targets in further reducing residual CVD risks.
LDL-C is considered as an important and primary target for risk screening, treatment, and prevention in several epidemiological studies and randomized control trials. There is a robust evidence regarding the cutoff values in different population segments. Despite being in the center stage of lipid management, estimation of LDL-C has some limitations. LDL-C is calculated using the Friedewald formula, LDL-C = TC − HDL − TG/5. The formula assumes that VLDL-C is TG/5, and in situ ations where TG is high, the formula underestimates LDL-C values. A fasting sample is necessary for the proper estimation of LDL-C to avoid the prandial elevation of TG and chylomicrons. When TG >400 mg/dl, Friedewald formula cannot be used for proper estimation of LDL-C. Direct assays of LDL-C are available but lack uniform standardization. Patients with diabetes or metabolic syndrome generally have high TG, low HDL-C, and normal or marginally elevated LDL-C, and these individuals have a predominantly small dense LDL and IDL particles. LDL-C levels in such individuals may underestimate the ASCVD risk.
Non-HDL-C is a much broader measure of apoB-containing lipoproteins and includes cholesterol estimation from LDL-C, VLDL-C, small dense LDL, IDL, and remnant chylomicrons. Calculation of non-HDL-C is simple, does not need a fasting sample, and incurs no additional cost. There are several studies and meta-analysis which have shown the usefulness of non-HDL-C as an effective marker of ASCVD risk. However, most guidelines still recommend non-HDL-C as a secondary target, and the recommended levels are arbitrary unlike with LDL-C goals.
ApoB is in principle a complete representation of all atherogenic particles and considered better than LDL-C and non-HDL-C estimation for CVD risk assessment in many studies. Estimation of apoB does not require a fasting sample and useful in the presence of high TG and low LDL-C. However, the test involves additional cost and despite available evidence, apoB is still recommended as a secondary target to be achieved after reaching the LDL-C goals.
LDL-C, non-HDL-C, and apoB are generally linearly related and correlated well. However, discordance is observed in individuals with moderate-to-severe hypertriglyceridemia.
In this issue of the journal, Prakash et al. have evaluated non-HDL-C levels as a surrogate marker of apoB in a cohort of individuals with metabolic syndrome. In this cross-sectional study, using good statistical methods of correlation, concordance-discordance analysis with kappa values, and area under the curve of receiver-operator characteristic authors have demonstrated that non-HDL-C values but not LDL-C values correlate well with apoB. Individuals with metabolic syndrome, Type 2 diabetes mellitus, and obesity are well known to have typical atherogenic dyslipidemia characterized by high TG, low HDL, and normal or slightly high LDL-C. Conventional LDL-C-based targets are most likely to underestimate the LDL-C levels and CVD risk in such individuals. Estimation of apoB and non-HDL-C is better in these individuals and by showing good concordance between non-HDL-C and apoB levels in most of the quintiles, authors validly put a strong argument for an easy and inexpensive method, non-HDL-C as a surrogate marker for apoB estimation. Despite showing a very high correlation between non-HDL-C and apoB, there are few limitations of the present study which needs to be considered before extrapolating the results to a larger population. The study is a cross-sectional observational study, not a prospective study and has no information about the usefulness of either apoB or non-HDL-C as a marker of CVD risk. The study was not aimed to evaluate the usefulness of either marker in ASCVD risk assessment or as a therapeutic target and intended only to find the correlation between non-HDL-C and apoB. Although the study proves a good correlation between non-HDL-C and apoB, it is difficult to assume the two as equivalent, because the equivalence is better demonstrated by concordance analysis than correlation analysis. In the present study, concordance between non-HDL-C and apoB is modest, Kappa analysis showed substantial agreement but not a perfect agreement between two markers. This means that estimates of risk for an individual by one method will frequently differ substantially from the risk predicted by the other. Hence, considering non-HDL-C in lieu of apoB may not be applicable always.
In a nested case–control study among 18,225 participants, non-HDL-C and apoB were shown to be strong predictors of CVD in men better than LDL-C: When apoB and non-HDL-C were compared, apoB was shown to be more predictive in the development of CVD than non-HDL-C. This suggests that concentration of atherogenic particles (measured by apoB) is more important than the cholesterol carried by these particles (represented by non-HDL-C). In contrast to this, another prospective cohort study of 15,632 healthy women with over 10-year follow -up showed that non-HDL-C and ratio of TC to HDL-C were as good as or better than apolipoprotein fractions in predicting CV events. A Dutch study involving 1517 elderly people non-HDL-C, LDL-C, and apoB were compared for detecting CV risk profile and supported the use of apoB as a first-choice marker and non-HDL-C as the second choice and both proved superior to LDL-C for risk assessment. In the EPIC-Norfolk study, 25,639 participants aged between 45 and 79 were followed up for more than 11 years, both non-HDL-C and apoB were strongly associated with the risk of CVD and both were comparable in their ability to predict the CV risk. A large meta-analysis including 233,455 patients and 22,950 CV events analyzed individually and head-to-head comparison between LDL-C, non-HDL-C and apoB; apoB was the most potent marker of CV risk, LDL-C was the least, and non-HDL-C was intermediate in risk prediction.
A question which naturally arises is where does the traditional and deeply entrenched risk marker LDL-C stand in this competition? With both non-HDL-C and apoB clearly establishing their superiority over LDL-C, is it time now for changing paradigm and adopting non-HDL-C and apoB markers instead of LDL-C? Beyond the importance of analytical and diagnostic accuracy, outcome studies and cost-benefit studies are needed to establish added benefits of these markers over the standard LDL-C centric approach.
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