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. Author manuscript; available in PMC: 2021 Jul 1.
Published in final edited form as: Curr Opin Cardiol. 2020 Jul;35(4):405–411. doi: 10.1097/HCO.0000000000000740

Measuring LDL-cholesterol: What is the best way to do it?

Anna Wolska 1,*, Alan T Remaley 1
PMCID: PMC7360339  NIHMSID: NIHMS1602399  PMID: 32412961

Abstract

Purpose of review:

Cholesterol on Low-Density Lipoproteins (LDL-C) is one of the main drivers of atherosclerotic cardiovascular disease (ASCVD) and hence its measurement is critical in the management of patients at risk. Although LDL-C has routinely been either calculated by the Friedewald equation or measured with direct assays, these methods have limitations, particularly for patients with dyslipidaemias, low LDL-C and hypertriglyceridaemia. The focus of this review will be recent advances in the measurement of LDL for ASCVD risk management.

Recent findings:

We first describe the recent recommendations on how LDL-C is used in ASCVD risk assessment and management. We then review the current approaches to the measurement of LDL-C and recent developments on new more accurate equations for calculating LDL-C. Finally, we present new and emerging LDL assays that may be superior to LDL-C for risk assessment, such as LDL particle number and small dense LDL-C, as well as several LDL-based lipid tests in early development.

Summary:

LDL-C is valuable in ASCVD risk management but recent improvements in its measurement and the development of other LDL related tests may further improve its value.

Keywords: Low-Density Lipoproteins, cholesterol, risk markers, atherosclerosis, measurement

Introduction

Atherosclerotic Cardiovascular Disease (ASCVD) is a scourge of modern society; it is expected that the number of affected patients will top one million in the US by 2019 (1). Hence, the measurement of cholesterol, particularly cholesterol on Low-Density Lipoproteins (LDL-C), is a critical step in our approach to the prevention and treatment of this now global disease.

The first inkling that cholesterol on certain lipoprotein subfractions may be particularly atherogenic was revealed in the 1950s by the pioneering work of Dr. John Goffman. He showed with the analytical ultracentrifuge that cholesterol carried on a certain class of lipoproteins that were then named based on their sedimentation characteristics (Sf 10–30), but now are known as LDL, are especially pro-atherogenic (2). In contrast, cholesterol on High-Density Lipoproteins (HDL-C) is inversely related to ASCVD events, although recent studies in patients with very elevated HDL-C have revealed a more complex parabolic relationship between HDL-C and ASCVD (3). Furthermore, results from clinical trials on CETP-inhibitors for HDL-C pharmacologically did not show reduced adverse cardiovascular outcomes (4). Although anacetrapib reduced cardiovascular risk in the REVEAL trial showing a 11% decrease in coronary events in patients treated with anacetrapib and statin compared with a statin alone, it accumulated in adipose tissue and washed out very slowly (5) making its benefit‐risk profile difficult to assess and so its further development was discontinued.

.Besides its importance as a risk factor, the accurate measurement of LDL-C became an even more important issue after the development of statins in the late 1980s and the demonstration that LDL-C lowering reduced ASCVD events (6).

In this review, we will discuss how LDL-C is currently used for ASCVD risk management in the US (7) and then the routine methods for measuring LDL-C and some of their limitations. We will then discuss some recent advances in the measurement of LDL-C and conclude with a discussion on new and emerging methods for LDL-based diagnostic tests. It is important to note that there are other tests besides LDL-C for measuring pro-atherogenic lipoproteins, namely nonHDL-C and apolipoprotein B-100 (apoB-100), which may even be superior to LDL-C as risk markers (8, 9). This is likely true because patients with dyslipidaemias, particularly those with elevated triglycerides (TG), will have less cholesterol on LDL particles but more on other pro-atherogenic lipoprotein fractions called remnant lipoproteins that contain apoB and are also included in nonHDL-C (10). These alternative risk markers have been thoroughly reviewed elsewhere (11, 12) and will not be a topic of this review, because most ASCVD guidelines at this time still focus on LDL-C as one of the main parameters for managing patients.

What is LDL?

As shown in Figure 1, LDL is a lipoprotein particle about 19–22 nm in diameter with an average density of 1.019–1.063 g/mL and like all other lipoproteins, the lipids it transports are in a micelle-like arrangement. The most hydrophobic lipids, namely cholesteryl ester and TG, are in the core of the particle, whereas the amphipathic lipids (free cholesterol, phosphatidylcholine, lysophosphatidylcholine, and sphingomyelin) that can interact with both lipids in the hydrophobic core and water outside the lipoprotein particle are located on the surface. Also on the surface of LDL are apolipoproteins that also have an amphipathic nature because they contain amphipathic alpha-helices and beta sheets (13). The main apolipoprotein on LDL is apoB-100, which helps maintain the structural integrity of the LDL and also serves as a ligand for the LDL-receptor, which removes LDL from the circulation. Based on these different components of LDL, different types of assays for quantifying LDL have been developed.

Figure 1. Structure and composition of an LDL particle.

Figure 1.

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Amphipathic lipids (phospholipids and free cholesterol) and apoB-100 are located on the surface, whereas the more hydrophobic lipids (triglycerides and cholesteryl esters) are located inside the core. Numbers in parenthesis indicate the percent of each lipid and protein component based on dry mass.

LDL is derived from the lipolysis of Very-Low Density Lipoproteins (VLDL), one of the main transporters of TG. Normally, LDL is quickly cleared by hepatic LDL receptors, but if it accumulates in the plasma, it gets deposited into the vessel wall where its cholesterol component triggers the development of atherosclerosis (14). Because cholesterol plays such a central role in the pathogenesis of atherosclerosis, the LDL-C test, which measures both the free cholesterol on the surface of the particle and cholesteryl esters in the core, has historically been the main way it is measured.

How is LDL-C currently used in ASCVD risk assessment?

The most recent US guidelines, the 2018-Multisociety Guideline on cholesterol management (7, 15), recommends that all adults 20 years or older should be screened with a lipid panel (total cholesterol (TC), TG, HDL-C, and a calculated or measured LDL-C) every 5 years. It is recommended that a 10-year ASCVD risk score be calculated based on risk factors (age, sex, race, TC, HDL-C, systolic blood pressure, smoking status, use of blood pressure medications and diabetes) except for low-risk patients with a LDL-C <70 mg/dL (<1.81 mmol/L) or high-risk patients with a LDL-C ≥190 mg/dL (≥4.91 mmol/L), who should be aggressively treated with high-intensity statins. Patients with LDL-C between 160–190 mg/dL (4.14–4.91 mmol/L) are considered to be at higher risk (risk enhancer), which would favor statin treatment. Finally, LDL-C is also used to monitor statin and other lipid-lowering treatments and it is recommended that patients at moderate risk be treated to reach an LDL-C <100 mg/dL (<2.59 mmol/L), whereas high-risk or secondary prevention patients should be treated to reach an LDL-C <70 mg/dL (<1.81 mmol/L).

Calculation of LDL-C

Until recently, LDL-C was most often calculated by the Friedewald formula, which was first described in 1972 (16):

LDC−C=TC−HDL−C−TG5[mg/dL]

With the development of this formula, it was no longer necessary to do ultracentrifugation to measure LDL-C, thus making it possible to measure LDL-C in routine clinical laboratories. It depends on the fact that in a fasting sample, cholesterol can only be found on either HDL, LDL or VLDL. The TG/5 (mg/dL) or TG/2.2 (mmol/L) terms provides an approximation for the amount of cholesterol on VLDL (VLDL-C), so if one subtracts HDL-C and VLDL-C (TG/5) from TC one can estimate LDL-C. Historically, HDL-C was determined by the selective precipitation of LDL and VLDL by various anionic polymers and the measurement of cholesterol on HDL in the supernatant, but it is now mostly measured by direct HDL-C assays.

Although the Friedewald formula has been used many years, it has many well-known limitations (17). In particular, the TG/5 estimate for VLDL-C is increasingly inaccurate with TG greater than about 250 mg/dL (>2.82 mmol/L) and it is not recommended to be used for TG >400 mg/dL (>4.52 mmol/L). This issue has now become even more problematic for several reasons. The first is the recent guidance from the 2018-Multisociety recommendation on cholesterol (7) that non-fasting samples are suitable for the initial screening of ASCVD risk. As a consequence, more patients will present with elevated post-prandial TG making the estimation of LDL-C by the Friedewald equation less reliable. The frequency of hypertriglyceridaemia in the general population is also increasing because of obesity and about one third of adults now have a TG >150 mg/dL (>1.69 mmol/L) (18). Another reason is that with the advent of more effective lipid-lowering therapies like anti-proprotein convertase subtilisin/kexin type 9 (PCSK9) monoclonal antibodies, some patients reach LDL-C levels well below 70 mg/dL (<1.81 mmol/L). At these low levels, the Friedewald estimate of LDL-C can be wildly discrepant and usually shows a negative bias (19), thus discouraging more aggressive treatment that has been shown to be beneficial for high-risk patients. Because of these problems, the 2018-Multisociety guidelines on cholesterol (7) now recommends the following Martin equation (19) as the preferred way to calculate LDL-C:

LG−C=TC−HDL−C−TGadjustable factor[mg/dL]

It is similar to the Friedewald equation, but the Martin equation divides TG by an adjustable factor that can be found in a 180-cell table that lists the optimum factor, depending on the plasma TG and nonHDL-C level. These optimum factors were derived from nearly a million patients that were analyzed for LDL-C and other lipids by a vertical high density-gradient ultracentrifugation method called Vertical Auto Profile (VAP) test (20, 21). Compared with beta-quantification, the reference ultracentrifugation/precipitation method for LDL-C, the Martin equation is more accurate than the Friedewald equation, particularly for low LDL-C patients (22). The Martin equation, however, is not validated for TG >400 mg/dL (>4.52 mmol/L), and the VAP method upon which it is based is known to be inaccurate on such samples (20, 23). Furthermore, the implementation of the Martin equation is somewhat cumbersome to implement in most laboratory information software systems, because of the need for a conditional look-up table for the optimum factor values.

Recently, a new equation (Sampson Equation) (24) for LDL-C has been described. It appears to be more accurate than either the Friedewald or Martin equations and can be used for hypertriglyceridaemic samples with TG levels up to 800 mg/dL (9.03 mmol/L):

LDL−C=TC0.948−HDL−C0.971−(TG8.56+TG×nonHDL−C2140−TG216100)−9.44[mg/dL]

Unlike the other two equations or some of the other past LDL-C equations (25–37), the new equation uses higher order mathematical terms in the form of a bivariate quadratic equation that better accounts for the surface to volume relationships that determines the amount of TG in the core of lipoprotein particles (38). The part of the equation related to VLDL-C is in parenthesis and includes both TG and nonHDL-C as independent variables. Although the equation is much more complex to do by hand, it can be readily automated and easily performed by laboratory information systems. More studies are needed to assess its clinical utility, but when compared with the beta-quantification reference method it is much more accurate on hypertriglyceridaemic samples and on low LDL-C samples, particularly compared with the Friedewald equation. It also yields very comparable results to direct LDL-C tests on hypertriglyceridaemic and post-prandial samples, making it unnecessary as will be discussed below to automatically perform direct LDL-C on these types of samples.

Direct LDL-C Assays

As its names implies, direct assays measure cholesterol on LDL rather than calculate it (39, 40). They are sometimes called homogenous assays because they measure LDL-C without having to separate LDL from the other lipoprotein particles in a sample. They achieve this by either selectively masking and/or consuming cholesterol on these other lipoprotein fractions so that the enzymes that measure cholesterol in the final step of the assay only detect cholesterol on LDL. There are at least 6 commonly used types of direct LDL-C assay that are produced by various manufacturers and they have been available since the mid-1990s. Despite the limitations of estimating LDL-C by an equation, the majority of clinical laboratories still do not routinely offer direct LDL-C for multiple reasons. First, several studies have shown (41–43) that the various direct assays can sometimes yield inaccurate results for dyslipidaemic patients, because the methods used to either selectively mask and or consume cholesterol on the other fractions besides LDL may not work correctly when there is an alteration in the composition and or size of lipoprotein particles. Furthermore, unlike the calculation of LDL-C, which is free because it just depends on other lipid tests in the standard lipid panel (TC, HDL-C and TG), there is also an additional cost in terms of reagents and labor for performing a direct LDL-C test. This combined with its analytical limitations has restricted the use of this direct test unlike the direct HDL-C tests, which have been universally adopted. Some direct LDL-C tests, however, perform reasonably well on high TG samples and have become more popular because they are not as affected by the fasting state unlike earlier LDL-C calculations (38). Also, some laboratories refer to a direct LDL-C test when TG >400 mg/dL, but this may no longer be necessary with the use of the Sampson equation, which works at much higher TG level and closely matches the direct LDL-C results on post-prandial samples (38). Recently, a direct LDL-C assay manufactured by Denka Seiken (44) has been shown to be superior to either the Friedewald or Martin equations in ASCVD risk prediction, so it is possible with further improvements in these assays that their extra costs may be justified based on improved performance (45).

New and emerging LDL assays

As can be seen in Figure 1, other components of LDL can also be used as a possible index for quantifying the amount of LDL. Two new LDL-based tests that differ from LDL-C have recently been approved by the FDA and there are several more that are in early stages of development.

LDL particle number

Perhaps the most fundamental way to quantify LDL is to measure the number of LDL particles (LDL-P) present in a sample. This was first done by nuclear magnetic resonance spectrometry (NMR), which quantifies the number of lipoprotein particles and their size by measuring the signal from the terminal methyl groups on lipids (46). The test is now approved by the FDA and is performed by a reference laboratory (LabCorp, Burlington, North Carolina, USA). It is known that two people with the same LDL-C can have widely different LDL-P values because LDL can vary in size (47). In other words, cholesterol on LDL can be carried by a smaller number of large LDL particles or in a larger number of small LDL particles. In general, ASCVD risk appears to more closely correlate with smaller LDL and hence when there is a discordance between LDL-P and LDL-C, which often occurs in patients with metabolic syndrome and diabetes, ASCVD risk tracks more closely with LDL-P (48). As shown in Table 1, there are now other methods for measuring LDL-P by other biophysical techniques and they are also available in reference laboratories. In addition, there are now multiple different NMR platforms for measuring LDL-P. All these different methods for LDL-P may not closely agree with each other, so one has to use method specific reference ranges to interpret the results and more effort is needed in the standardization and or harmonization of these assays (49).

Table 1.

Various methods of LDL measurements.

Analytes Method Limitations Status Ref.
Friedewald equation calculation Only for TG <400 mg/dL (<4.52 mmol/L) and fasting samples Routine (16)
Martin equation calculation Only for TG <400 mg/dL (<4.52 mmol/L) and fasting samples Routine (19)
Sampson equation calculation Only for TG <800 mg/dL (<9.03 mmol/L) Routine (38)
Direct LDL-C homogenous enzyme assay Inaccurate for some dyslipidaemic samples Routine (44)
LDL-P NMR Complex instrumentation Reference lab (48)
VAP High TG samples disturb lipoprotein isolation Reference lab (21)
DMS Complex sample preparation and analysis Reference lab (64)
Direct sd-LDL-C homogenous enzyme assay This method selectively decomposes d <1.044 kg/L lipoproteins FDA approved but not yet widely available (53)
LDL-TG homogenous enzyme assay - Under development (57)
LDL-SM MS Complex sample preparation and analysis Under development (60)
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DMS, differential ion mobility spectrometry; FDA, U.S. Food and Drug Administration; LC-MS, LDL, Low-Density Lipoproteins, LDL-C, LDL-cholesterol; LDL-P, LDL-particle number; LDL-SM, LDL-sphingomyelin; LDL-TG, LDL-triglycerides; sd-LDL-C, small dense LDL-C; MS, mass spectrometry; NMR, nuclear magnetic resonance spectroscopy; TG, triglycerides; VAP, vertical auto profile test.

Small LDL-C Subfraction

It has been known for many years that patients with the so called “atherogenic phenotype”, who have small dense LDL (sd-LDL) are at a much higher risk of ASCVD (50). The atherogenic phenotype often occurs in patients with diabetes and metabolic syndrome but a common denominator often appears to be hypertriglyceridaemia. Because of cholesteryl ester transfer protein (CETP)-mediated lipid exchange (51), cholesteryl esters on LDL become replaced with TG and when these TG undergoes lipolysis it generates a smaller size LDL (52). The same phenomenon also explains why these patients also have low HDL-C and small size HDL too. It has been proposed that sd-LDL more readily infiltrates into the vessel wall and thus better triggers atherosclerosis than large LDL (50), but it may be that sd-LDL is just a marker for this phenotype, which is predisposed to atherosclerosis for some other reason. Until recently sd-LDL could only be detected by tedious ultracentrifugation or electrophoresis based methods but a fully automated direct assay for cholesterol on sd-LDL (sd-LDL-C) has recently been described (53). In three large epidemiologic studies (45, 54–56), it was superior to LDL-C as an ASCVD risk marker, but more studies are needed to determine if it adds importance over traditional risk factors and or to find the patient population in which it provides the most value.

Other LDL-Based Lipid Tests

In terms of emerging LDL tests, two new tests that measure another lipid component of LDL have recently been described. The first is a direct test that measures the TG content of LDL (LDL-TG) (57). Consistent with an earlier ultracentrifugation based study (58), the new direct LDL-TG test in the Atherosclerosis Risk in Communities (ARIC) study was superior to LDL-C as a ASCVD risk predictor (59) and correlated more closely to a high-sensitivity C-reactive protein than LDL-C (58). The explanation for this stronger association with ASCVD is not understood but could be related to the same phenomena described for the atherogenic phenotype (59).

The other new lipid-based LDL assay measures the sphingomyelin (SM) content of LDL (LDL-SM) (60). The assay has yet to be simplified to the point that it can be carried out by routine clinical laboratories but early studies suggest that it may also predict ASCVD because of the link between SM and the propensity for LDL to aggregate (14). Once LDL enters the vessel wall, it is acted upon various enzymes, such as sphingomyelinase that then generates ceramide a fusogenic lipid that causes LDL to aggregate, which then triggers more effective uptake by macrophages. Much more work needs to be done in this area, but dietary and therapeutic manipulations in the content of SM on circulating lipoproteins may be an important future area of investigation (61).

Conclusions

Although we have known for over 60 years that LDL plays a central role in the pathogenesis of atherosclerosis, we are still uncertain about the best way to measure it. Furthermore, recent progress in lipid-lowering therapies and changes in ASCVD guidelines have changed the accuracy requirements for LDL-C testing. Although we describe some recent improvements in LDL-C and other LDL-based tests, going forward it may be necessary to consider moving away from LDL to alternative tests at least for the initial ASCVD risk assessment (8, 9, 11, 12, 62, 63).

Key points:

  • LDL-C is a key test for ASCVD risk management.

  • LDL-C is still most often calculated using the Friedewald equation, but this formula has several limitations, and should not be used for low LDL-C samples and when TG >400 mg/dL (>4.52 mmol/L).

  • Several new equations have been developed for LDL-C. The Sampson equation appears to be the most accurate and can be used for samples with TG levels up to 800 mg/dL (9.03 mmol/L).

  • Direct LDL-C assays also have some limitations on dyslipidaemic samples but may be useful for post-prandial samples.

  • There are other new measures of LDL (LDL-P, sd-LDL-C, LDL-TG and LDL-SM), which may offer some advantages over LDL-C.

Acknowledgements

The authors thank Maureen Sampson for help in illustration of Figure 1.

Financial support

Research was supported by the Intramural Research Program of the NHLBI at the National Institutes of Health.

Footnotes

Conflicts of interest

None

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