Assessing residual cardiovascular risk and vulnerable plaques via non-traditional lipids: From biomarkers to novel targets for precision therapy

Abstract

Coronary artery disease is a leading cause of death and disability-adjusted life-years worldwide. Acute coronary syndrome, a major clinical manifestation of coronary artery disease, commonly results from disruption of vulnerable atherosclerotic plaques. Conventional lipid parameters, especially low-density lipoprotein cholesterol, play a central role in cardiovascular risk assessment and management. However, these traditional markers have important limitations in their ability to fully capture the complexity of atherosclerotic risk, particularly residual cardiovascular risk. This review comprehensively discusses the biological and pathophysiological roles of emerging non-traditional lipid-related parameters, including lipoprotein(a), low-density lipoprotein particle number and small dense low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, apolipoprotein E, apolipoprotein A1, remnant cholesterol, and polyunsaturated fatty acids in the initiation, progression and rupture of vulnerable plaques. In addition, the clinical utility of these parameters as biomarkers is critically evaluated, along with current issues in their clinical implementation and potential future research directions. Collectively, this review presents an updated framework for the advancement of precision prevention and targeted therapeutic strategies in cardiovascular disease.

Key Words: Non-traditional lipid parameters; Vulnerable plaques; Residual cardiovascular risk; Atherosclerotic cardiovascular disease; Precision medicine; Lipoproteins

Core Tip: Traditional lipids may underestimate residual cardiovascular risk and do not fully identify biologically vulnerable plaques. This review critically evaluates lipoprotein(a), low-density lipoprotein particle number, small dense low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, apolipoproteins E and A1, remnant cholesterol, and polyunsaturated fatty acids. It distinguishes guideline-endorsed measures from investigational biomarkers, summarizes clinically relevant thresholds and therapeutic evidence, and highlights assay standardization, unit conversion, and reference-interval limitations. Integration with plaque imaging and artificial intelligence may improve individualized risk stratification and precision prevention.

INTRODUCTION

Coronary artery disease (CAD) is the highest contributor to the global burden of disease, in terms of both mortality and morbidity. In 2020, an estimated 19.05 million deaths worldwide were due to cardiovascular disease (CVD)[1]. Atherosclerosis, the pathological basis of CAD, is a chronic inflammatory disease with a high tendency for triggering thrombotic events[2]. Acute coronary syndrome (ACS) is most often the result of the rupture of so-called “vulnerable plaques”; this recognition has caused a shift in cardiovascular risk assessment away from the consideration of luminal stenosis alone, toward consideration of plaque composition and underlying biological characteristics[3].

Vulnerable plaques are defined as thin fibrous caps (< 65 μm), large lipid-rich cores, and significant infiltration of inflammatory cells. Inflammatory activity weakens the fibrous cap and softens the lipid core and greatly increases susceptibility to plaque rupture, in addition, intraplaque hemorrhage contributes to expansion and destabilization of necrotic cores[3-5]. As a result, assessment strategies based on conventional coronary angiography and the degree of luminal stenosis alone are not sufficient to accurately identify vulnerable plaques or “vulnerable patients” at increased risk of adverse events. This limitation highlights the need for new diagnostic modalities and reliable biomarkers that can more accurately define plaque composition and underlying biological activity[5].

CURRENT APPLICATION OF TRADITIONAL LIPID PARAMETERS

Traditional lipid parameters, such as total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG) are the cornerstone of CVD risk assessment. Therapeutic strategies aimed at lowering LDL-C, most notably statin therapy, have been found to greatly reduce the incidence of atherosclerotic CVD (ASCVD)[6,7].

Despite their widespread use, traditional lipid parameters have significant limitations in completely describing the range of lipid-related atherosclerotic risk. In some populations, using these markers may result in overestimation or underestimation of cardiovascular risk, thus affecting the accuracy of risk stratification. LDL-C is only a measure of the cholesterol content of the low-density lipoproteins and does not consider the number of particles, the heterogeneity of the particles or the contribution of other atherogenic lipoproteins such as lipoprotein(a) [Lp(a)] and very-low-density lipoproteins[8]. Moreover, a significant proportion of patients still have high cardiovascular risk even after very low LDL-C levels are reached by statin treatment. As shown in Figure 1, this continuing risk after good control of LDL-C is termed “residual cardiovascular risk”[7]. These observations suggest that there are factors other than LDL-C reduction driving atherosclerotic progression and plaque destabilization. The continued challenge of residual cardiovascular risk despite conventional lipid-lowering strategies points to a major gap in current understanding and management of atherosclerosis and provides a compelling impetus for the discovery of more comprehensive risk assessment tools and new therapeutic targets to address this unmet clinical need[9].

Figure 1 Diagram of the residual cardiovascular risk model. Although high-intensity statin therapy can significantly reduce risk, a considerable residual cardiovascular risk persists even after achieving the target level of low-density lipoprotein cholesterol, potentially attributable to factors such as lipoprotein(a) and remnant cholesterol. Lp(a): Lipoprotein(a); RC: Remnant cholesterol; HDL-C: High-density lipoprotein cholesterol; sdLDL-C: Small dense low-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; ASCVD: Atherosclerotic cardiovascular disease.

NON-TRADITIONAL LIPID PARAMETERS AND THEIR RELATIONSHIP WITH VULNERABLE PLAQUES AND CAD

Non-traditional lipid-related parameters, such as Lp(a), low-density lipoprotein particle number (LDL-P), non-HDL-C, apolipoprotein E (ApoE), apolipoprotein A1 (ApoA1), remnant cholesterol (RC) and polyunsaturated fatty acids (PUFAs), offer more nuanced and more comprehensive information for cardiovascular risk stratification and are particularly useful in identifying high-risk individuals who may be missed by conventional lipid-related parameters[7,10]. Accumulating evidence shows that these parameters are closely associated with atherosclerosis, ACS and CAD[11]. Accordingly, the aim of this review is to systematically assess the biological features and pathophysiological functions of these non-traditional lipid parameters and to cover the current difficulties and future opportunities associated with their clinical application.

TYPES AND BIOLOGICAL FEATURES OF NON-TRADITIONAL LIPID PARAMETERS

Non-traditional lipid parameters greatly contribute to a better understanding of the pathogenesis of atherosclerosis, as they are able to give more precise information on the composition, abundance, and functional characteristics of lipoproteins than traditional lipid indicators. A detailed comparison of the biological features, advantages, limitations, and roles in residual risk between traditional and non-traditional lipid parameters is summarized in Table 1 before examining each parameter below.

Table 1 Comparison of traditional and non-traditional lipid parameters in cardiovascular disease risk assessment.

Parameter type	Representative markers	Main characteristics	Advantages	Limitations	Role in residual risk
Traditional lipid parameters	TC, LDL-C, HDL-C, TG	Concentrations of cholesterol and triglycerides	Widely available; inexpensive; guideline-endorsed; LDL-C lowering reduces ASCVD events[7]	Cannot reflect particle number, composition, or other atherogenic lipoproteins; may underestimate residual risk[7]	Significant residual risk persists despite optimal LDL-C control
Non-traditional lipid parameters	Lp(a), LDL-P, sdLDL-C, non-HDL-C, ApoE, ApoA1, RC, PUFAs	Reflect lipoprotein quantity, quality, function and metabolism	Associated with plaque vulnerability[10,11]	Limited standardization; higher cost; limited availability; evidence for some markers remains observational[7,9]	May improve residual risk identification[12]

TC: Total cholesterol; LDL-C: Low-density lipoprotein cholesterol; HDL-C: High-density lipoprotein cholesterol; TG: Triglyceride; Lp(a): Lipoprotein(a); LDL-P: Low-density lipoprotein particle number; sdLDL-C: Small dense low-density lipoprotein cholesterol; ApoE: Apolipoprotein E; ApoA1: Apolipoprotein A1; RC: Remnant cholesterol; PUFAs: Polyunsaturated fatty acids; ASCVD: Atherosclerotic cardiovascular disease.

Lp(a)

Lp(a) is a multifaceted lipoprotein particle, which is formed by apolipoprotein B100 covalently conjugated to apolipoprotein(a) [Apo(a)] through disulfide bonds. Its plasma level is highly genetic in nature and tends to stay relatively constant in the life of an individual[9]. Lp(a) has been identified as a risk factor independent of ASCVD and having proatherogenic, proinflammatory and prothrombotic effects. Atherogenic activity of Lp(a) is mediated by various processes such as increased lipid deposition in the wall of the arteries and reduced fibrinolysis, which results in plaque formation and the growth of thrombus[12]. Figure 2 summarizes the main pathogenic pathways of Lp(a) that are associated with it. It is worth mentioning that Lp(a) remains a cardiovascular risk factor even when plasma LDL-C and apoB100 are brought to an effective level, which highlights its role as a unique and residual risk factor in the development of CVD[13]. Intriguing evidence on the special role of Lp(a) in plaque vulnerability is provided by a subgroup analysis of the PROSPECT II study that used intravascular near-infrared spectroscopy with ultrasound imaging. This study has shown that conventional atherogenic lipid markers such as TC and LDL-C were highly related to total coronary plaque volume and lipid burden throughout the coronary tree but not to the existence of focal vulnerable plaques. Conversely, higher levels of Lp(a) did not correlate with total plaque burden but were significantly related with locally vulnerable plaques, which were characterized by a plaque burden of ≥ 70% and a big lipid-rich core[14]. This association is further supported by findings of other high-resolution imaging modalities. Optical coherence tomography imaging of patients with ACS has demonstrated that an elevation in the Lp(a) levels is associated with a greater number of lipid-rich plaques and thin-cap fibroatheromas in the culprit lesion locations[15]. These findings support a direct correlation between Lp(a) and the most dangerous plaque phenotypes that are likely to rupture. Outside the coronary circulation, the relationship between Lp(a), plaque progression, and vulnerability has been repeatedly found to be the same in various vascular territories and populations. A prospective cohort study within a community setting found that high baseline Lp(a) levels were the independent predictors of carotid plaque progression during a 10-year follow-up period, and that plaque vulnerability scores had increased significantly[16]. In a similar study, longitudinal serial, coronary computed tomography angiography (CCTA) proved that higher Lp(a) levels were linked to a faster rate of coronary plaque burden, more low-attenuation (lipid-rich) plaques and more pericoronary adipose tissue inflammation, which is an emerging sign of vascular inflammatory activity[17]. Taken together, these longitudinal imaging data give strong support that Lp(a) has a sustained contribution to progression of the plaque to a high-risk, inflammatory and rupture-prone phenotype.

Figure 2 Pathogenic mechanism of lipoprotein(a). Lipoprotein(a) induces an inflammatory response through oxidized phospholipids, facilitates the accumulation of pro-atherosclerotic cholesterol in the vascular wall, and exerts a prothrombotic effect by inhibiting plasminogen activation. These properties collectively accelerate the progression and destabilization of vascular plaques. OxPL: Oxidized phospholipids; Lp(a): Lipoprotein(a); Apo(a): Apolipoprotein(a); VCAM-1: Vascular cell adhesion molecule-1; IL: Interleukin; VLDLR: Very low-density lipoprotein receptor; tPA: Tissue plasminogen activator.

Lp(a) measurement remains method-dependent. Assays that minimize the influence of Apo(a) isoform size and are traceable to recognized reference materials are preferred. When molar calibration is available, results are generally reported in nmol/L. However, laboratories should retain the unit for which the assay was calibrated, because mg/dL and nmol/L reflect different properties of the particle. A single fixed conversion factor between the two units is therefore inappropriate[9,18]. For clinical interpretation, current consensus documents commonly use three approximate ranges. Values below 30 mg/dL or 75 nmol/L are generally associated with lower Lp(a)-related risk, whereas 30-50 mg/dL or 75-125 nmol/L represents an intermediate range. Concentrations of at least 50 mg/dL or 125 nmol/L are widely regarded as risk-enhancing for ASCVD[9,18]. These thresholds are intended for risk assessment rather than as treatment goals. Most contemporary recommendations support measuring Lp(a) at least once in adulthood, especially in patients with premature ASCVD, familial hypercholesterolemia, or a relevant family history[18]. In patients with elevated Lp(a), current management mainly focuses on intensive control of modifiable risk factors, particularly LDL-C. PCSK9 inhibitors can lower Lp(a) to a moderate extent, but their clinical benefit cannot be attributed specifically to this effect. New antisense oligonucleotide and small interfering RNA therapies produce much larger reductions in Lp(a); nevertheless, whether selective Lp(a) lowering reduces myocardial infarction, stroke, or cardiovascular death has not yet been confirmed by a completed outcome trial. Phase 3 outcome trials such as Lp(a)HORIZON are expected to clarify whether selective Lp(a) lowering improves cardiovascular outcomes, while olpasiran has shown substantial Lp(a)-lowering effects in dose-finding studies[19,20].

LDL-P, small, dense LDL-C

The physicochemical characteristics of LDL particles are important in the initiation and progression of atherosclerosis[21]. Among the LDL subclasses, small dense LDL (sdLDL) has significantly higher atherogenic potential, because it easily enters the subendothelial space and is more prone to modification by oxidants, promoting the formation of foam cells and plaque[22,23]. LDL-P indicates the total number of LDL particles in circulation. As the cholesterol content of individual LDL particles varies, sdLDL particles contain less cholesterol than larger, buoyant LDL particles. Consequently, LDL-C concentrations may not accurately reflect LDL-P in all individuals, a phenomenon termed “LDL discordance”[24]. In the case of discordance between LDL-C and LDL-P, LDL-P has been shown to be a better predictor of ASCVD risk. This observation underlines the importance of the amount and quality of atherogenic lipoproteins rather than cholesterol concentration alone in the cardiovascular risk stratification[22]. Clinical evidence also supports the pathogenic relevance of sdLDL. A prospective cohort study showed a significant positive relationship between high sdLDL-C levels, rather than LDL-C, and the occurrence of vulnerable carotid plaques. Of note, even in people with LDL-C levels in the normal range, higher concentrations of sdLDL-C were related to higher risk of plaque formation, suggesting a direct role of sdLDL in the instability of plaque[25]. In addition, directly measured sdLDL-C is an independent predictor of long-term risk of recurrent coronary events in patients with stable CAD, independent of levels of ApoB or non-HDL-C (hazard ratio = 1.47, 95% confidence interval: 1.15-1.89)[26]. Among non-diabetic individuals, an elevated sdLDL-C/LDL-C ratio has also been shown to be significantly associated with a higher prevalence of carotid artery plaques (interaction P = 0.014), with plaque risk increasing in parallel with increasing ratios[25]. Collectively, these findings suggest that patients can have apparently “normal” LDL-C levels but have a high LDL particle burden dominated by sdLDL and remain at high cardiovascular risk. This discordance offers a mechanistic explanation for residual cardiovascular risk that is not adequately explained by conventional lipid measurements. Advanced lipid profiling techniques, such as vertical auto profile technology, which uses vertical gradient ultracentrifugation to automatically separate lipoprotein subclasses, allow for the direct quantification of sdLDL, and for the identification of high-risk individuals who may be missed by standard lipid testing[27,28]. However, unlike Lp(a), there are currently no universally accepted thresholds for LDL-P or sdLDL-C to guide clinical decision-making. Although elevated LDL-P and sdLDL-C levels have consistently been associated with increased ASCVD risk and plaque vulnerability, differences in measurement techniques and assay standardization have limited their incorporation into routine clinical guidelines[26]. Therefore, these markers are currently considered promising tools for risk refinement rather than established therapeutic targets. LDL-P is most commonly quantified by nuclear magnetic resonance spectroscopy and is generally reported in nmol/L[27]. In contrast, sdLDL can be measured using several techniques, including ultracentrifugation, gradient gel electrophoresis, nuclear magnetic resonance spectroscopy, ion mobility analysis, and direct homogeneous assays[23,27]. Because these methods assess different properties of LDL particles, their results and reference ranges are not directly interchangeable[27]. No assay-independent and internationally validated intervention threshold has been established for either LDL-P or sdLDL-C[23,26,27]. Current international guidelines do not recognize either marker as a routine treatment target, and no randomized outcome trial has shown that treatment directed specifically toward LDL-P or sdLDL-C improves major cardiovascular outcomes[27,29,30]. Therefore, these measurements may be used selectively for risk refinement but should not currently be regarded as established therapeutic targets.

Non-HDL-C

Non-HDL-C is calculated as TC minus HDL-C. It reflects the cholesterol content of all ApoB-containing atherogenic lipoproteins, including LDL, very-low-density lipoprotein, intermediate-density lipoprotein, remnant particles, and Lp(a). By incorporating cholesterol carried by multiple atherogenic particles, non-HDL-C provides a more comprehensive estimate of atherogenic burden than LDL-C alone[7]. Clinical studies have shown that non-HDL-C predicts cardiovascular events and cardiovascular mortality and may provide greater prognostic value than LDL-C in selected populations[31]. Non-HDL-C levels correlate with high risk of cardiovascular death and have a strong association with subclinical markers of atherosclerosis, such as coronary artery calcification, especially in patients with diabetes or hypertriglyceridemia[32]. In addition to being associated with overall risk, non-HDL-C is associated with features of vulnerable plaques. Intravascular ultrasound studies in patients with ACS have shown that non-HDL-C levels are positively associated with total plaque burden and may independently predict necrotic core volume[33]. These results indicate the potential of non-HDL-C to identify individuals with residual cardiovascular risk in spite of target LDL-C achievement and support the clinical value of non-HDL-C as a comprehensive marker of atherogenic burden[7]. Non-HDL-C does not require a separate laboratory assay because it is calculated by subtracting HDL-C from TC and is reported in the same units, either mg/dL or mmol/L. Unlike LDL-P and sdLDL-C, non-HDL-C is recognized in current guidelines as a secondary treatment target, particularly in patients with hypertriglyceridemia, diabetes, obesity, or mixed dyslipidemia. The 2019 ESC/EAS guideline recommends a non-HDL-C goal 30 mg/dL (0.8 mmol/L) higher than the corresponding LDL-C goal[29]. More recent ACC/AHA guidance recommends a non-HDL-C goal of < 85 mg/dL (2.2 mmol/L) for secondary prevention patients at very high ASCVD risk[30]. However, lipid-lowering therapies are not directed exclusively at non-HDL-C; their clinical benefits mainly reflect reductions in the overall burden of apoB-containing lipoproteins. Therefore, non-HDL-C should be regarded as a practical, guideline-endorsed target for treatment monitoring rather than as an independent molecular therapeutic target.

ApoE

ApoE exists mainly as three isoforms, ε2, ε3, and ε4. ApoE4 is associated with higher plasma cholesterol levels and increased CAD risk, whereas ApoE2 may predispose susceptible individuals to type III hyperlipoproteinemia[34]. Beyond its role in hepatic lipoprotein clearance, ApoE modulates vascular inflammation and cellular signaling, thereby contributing to atheroprotective effects[34]. Experimental evidence from ApoE-deficient animal models further highlights its role in plaque stability[35]. Similarly, acute perioperative stress has been shown to increase both plaque volume and vulnerability in these animals, which can be ablated by interventions such as statins and interleukin-6 inhibitors[36]. Although animal studies provide useful mechanistic evidence, their findings cannot be directly translated into clinical risk assessment. Clinical evaluation of ApoE should distinguish ApoE genotyping from measurement of circulating ApoE protein. Genotyping identifies the ε2, ε3, and ε4 alleles, whereas plasma ApoE measurement reflects the circulating protein concentration; these two approaches are not interchangeable[34]. At present, no validated plasma ApoE threshold has been established for ASCVD risk stratification or treatment initiation[34]. In addition, APOE genotype and plasma ApoE concentration are not established in current dyslipidemia guidelines as routine cardiovascular risk markers or therapeutic targets[29,34]. No randomized cardiovascular outcome trial has demonstrated that an intervention directed specifically at ApoE reduces myocardial infarction, stroke, or cardiovascular death[34]. Therefore, ApoE should currently be regarded as an investigational and mechanistic biomarker rather than a routinely actionable clinical target.

ApoA1

ApoA1 is the first protein constituent of HDL and the key in reverse cholesterol transport[37]. ApoA1 promotes cholesterol efflux from peripheral tissues to the liver for excretion and serves as a cofactor for lecithin-cholesterol acyltransferase, which catalyzes the synthesis of most plasma cholesteryl esters, as shown in Figure 3. ApoA1 deficiency leads to HDL deficiency and impairs cholesterol clearance. These findings support an important protective role of ApoA1 in limiting cholesterol accumulation within atherosclerotic lesions. The atheroprotective effect of ApoA1 is also supported by clinical and experimental evidence. Although ApoA1 infusion enhances cholesterol efflux and remains mechanistically attractive, the phase 3 AEGIS-II trial showed that four weekly infusions of CSL112 did not significantly reduce the 90-day composite risk of myocardial infarction, stroke, or cardiovascular death compared with placebo. Therefore, the clinical benefit of therapeutic ApoA1 infusion has not been established[38,39]. Other researchers have also found that ApoA1 can defend against the formation of necrotic cores in atherosclerotic plaques by suppressing macrophage necroptosis[40]. Additionally, below normal ApoA1 levels have been associated with symptomatic carotid plaques, which suggests that ApoA1 may be a possible biomarker of plaque instability[41]. These findings support a biological association between ApoA1 and plaque stability, but they do not establish a clinically actionable ApoA1 target.

Figure 3 Reverse cholesterol transport mediated by apolipoprotein A1. Cholesterol is expelled from macrophages via the ATP-binding cassette transporter A1 transporter protein and binds with apolipoprotein A1 to form nascent high-density lipoprotein. This high-density lipoprotein is subsequently matured by lecithin-cholesterol acyltransferase and ultimately taken up by the liver through scavenger receptor class B type I receptors, being excreted in the form of bile acids. ABCA1: ATP-binding cassette transporter A1; SR-BI: Scavenger receptor class B type I; ApoA1: Apolipoprotein A1; LCAT: Lecithin-cholesterol acyltransferase; CE: Cholesteryl ester; CER: Cholesteryl ester rich; HDL: High-density lipoprotein.

In addition to individual apolipoproteins, the ApoB/ApoA1 ratio has also been widely studied as a predictor of susceptible coronary plaques. The clinical evidence shows that patients with ACS have far more elevated ApoB/ApoA1 ratios than patients with chronic coronary syndrome and that this elevation is linked with increased prevalence of vulnerable plaque characteristics, such as rupture and erosion[42]. The ApoB/ApoA1 ratio has been established as an independent predictor of these high-risk plaque characteristics by multivariate logistic regression analyses, and its diagnostic value is supported by receiver operating characteristic curve analyses to identify patients at high risk of plaque instability[42]. Although ApoA1 and the ApoB/ApoA1 ratio have demonstrated prognostic value in numerous observational studies, they have not been widely adopted as routine therapeutic targets in current lipid management guidelines. At present, ApoA1 and the ApoB/ApoA1 ratio are mainly considered complementary biomarkers for cardiovascular risk assessment, and their clinical utility requires further validation in prospective studies[41,42]. Plasma ApoA1 is generally measured using immunoturbidimetric or immunonephelometric assays and is reported in mass units, commonly g/L or mg/dL[43]. Reference intervals may differ according to the analytical method, sex, age, and study population. Although individual studies have proposed risk-related values, no internationally validated intervention threshold has been established for either ApoA1 or the ApoB/ApoA1 ratio[43]. Current dyslipidemia guidelines do not recognize ApoA1 or the ApoB/ApoA1 ratio as routine treatment targets[29,30]. Therefore, these measures may provide complementary information for risk assessment, but treatment decisions should not currently be based on them alone.

RC

RC is the cholesterol content of triglyceride-rich lipoprotein remnants and has emerged as an independent risk marker for ASCVD. It contributes substantially to residual cardiovascular risk, particularly in individuals with well-controlled LDL-C levels[44]. RC atherogenic effects are mediated by its retention in the arterial wall, the stimulation of oxidative stress, and the stimulation of inflammatory responses[45]. High levels of RC are closely related to low grade systemic inflammation and postprandial increases in RC have been linked to heightened oxidative stress and hastened atherosclerotic disease progression. These observations suggest the alleviation of oxidative stress as an essential therapeutic approach to balance RC-induced vascular injury. Clinical evidence also indicates the prognostic value of RC. It has been demonstrated in a number of studies that RC is a strong predictor of ASCVD risk and plaque instability, and its predictive capacity is independent of, and in certain instances surpasses, that of LDL-C. In a cross-sectional study of neurologically healthy participants, the higher the RC levels, the greater the occurrence of unstable carotid plaques, which was independently assessed[46]. Notably, the association was observed even in participants whose LDL-C levels were normal or low, which suggests that RC measures residual cardiovascular risk that is not captured by traditional lipid measures. Multivariable logistic regression demonstrated that elevated RC was independently associated with unstable carotid plaques, whereas ApoA1 showed an inverse association[46]. There is further evidence demonstrating the clinical relevance of RC in certain vascular conditions. RC and the atherosclerotic index of plasma were found to be independent predictors of restenosis after endovascular treatment in patients with intracranial atherosclerotic stenosis[47]. Taken together, these results indicate that RC is an important predictor of residual cardiovascular risk and plaque vulnerability, especially in patients with already well-controlled LDL-C levels.

In clinical studies, RC is commonly calculated from the standard lipid profile as TC minus HDL-C and LDL-C, and is reported in mg/dL or mmol/L. Direct assays and remnant-like particle cholesterol assays are also available; however, these methods do not measure identical lipoprotein fractions, and calculated RC is influenced by the method used to determine LDL-C. Therefore, results obtained using different approaches are not fully interchangeable[48,49]. At present, no assay-independent and internationally validated RC threshold has been established for treatment initiation or treatment monitoring. Current dyslipidemia guidelines do not define RC as a routine therapeutic target, and no completed cardiovascular outcome trial has demonstrated that treatment to a prespecified RC concentration reduces myocardial infarction, stroke, or cardiovascular death[30,49]. Thus, RC should currently be considered a complementary marker of residual cardiovascular risk rather than an established treat-to-target variable.

PUFAs

The phospholipid side chains of lipoprotein shells include PUFAs which are highly vulnerable to oxidation by free radicals due to their chemical structure. The diallylic hydrogen between the two double bonds is easily abstracted by the free radicals to produce lipid radicals which react with the molecular oxygen to produce lipid peroxide radicals. This triggers a cascade reaction that generates huge amounts of oxidized lipids and reactive aldehydes, which may alter proteins and other macromolecules[50]. Oxidative alteration of PUFAs is important in the development, advancement, and destabilization of atherosclerotic plaques, which eventually leads to the development of plaques that are vulnerable. The lipoproteins that are trapped in the arterial wall are oxidatively modified according to the retention-reaction hypothesis to become highly atherogenic particles[51]. There is clinical and experimental evidence that PUFAs, especially n-3 fatty acids, including eicosapentaenoic acid (EPA) and docosahexaenoic acid, can have a protective effect against plaque susceptibility. A meta-analysis of EPA, used alone or with docosahexaenoic acid, showed a decrease in cardiovascular events, such as myocardial infarction and cardiovascular mortality, which is probably mediated by anti-inflammatory and antioxidant effects that indirectly lower the risk of vulnerable plaque rupture[52]. The EVAPORATE trial demonstrated that prescription icosapent ethyl reduced low-attenuation coronary plaque volume in selected statin-treated patients with elevated triglyceride levels[53]. However, this study evaluated an imaging endpoint rather than myocardial infarction, stroke, or cardiovascular death. Its findings should therefore not be generalized to all n-3 PUFA formulations or over-the-counter supplements[52-54].

Mendelian randomization and observational studies have not consistently supported routine PUFA supplementation for CVD prevention or a reduction in peripheral artery disease risk[54-57]. Current guidelines do not recommend routine PUFA supplementation solely for plaque stabilization, although prescription icosapent ethyl may be considered in selected high-risk patients with persistent hypertriglyceridemia[29,58]. Therefore, individualized treatment decisions should be based on the overall cardiovascular risk profile and current evidence. Accordingly, PUFAs should be regarded as lipid-related therapeutic modifiers rather than routine stand-alone biomarkers or treat-to-target variables[29,54].

EVIDENCE ON THE ASSOCIATION BETWEEN NON-TRADITIONAL LIPID PARAMETERS AND VULNERABLE PLAQUES

Pathophysiology of vulnerable plaque formation and rupture

Atherosclerosis mainly occurs in areas of turbulent blood flow whereby the rupture of plaque or erosion of endothelium may trigger thrombosis[59]. The atherothrombotic events are triggered by two significant types of surface damage, namely, plaque rupture and endothelial erosion. A large lipid-filled necrotic core, inflammatory cell infiltration, and punctuate calcification, are characteristic features of plaque vulnerability[2,59]. Figure 4 represents the pathological morphology of vulnerable plaques.

Figure 4 Pathological morphology of vulnerable plaques. This figure depicts the pathological morphology of vulnerable plaques, featuring a large lipid core enveloped by a thin fibrous cap. This unstable structure is prone to rupture under the influence of blood flow shear stress, leading to thrombosis and subsequent acute cardiovascular events.

The potential mechanistic role of non-traditional lipid parameters in vulnerable plaques

Non-traditional lipid parameters are involved in the plaque instability process, both directly and indirectly, through a complex interplay of oxidative stress, apoptosis and inflammatory pathways. Lp(a) contains oxidized phospholipids, which activate and amplify vascular inflammation[60,61]. sdLDL is highly prone to oxidation and drives foam cell formation, an important step in atherogenesis[25,45,62]. Non-HDL-C is an integrated indicator of total atherogenic burden, the cumulative impact of several proatherogenic lipoproteins[63]. Oxidative stress is a key factor in the pathogenesis of endothelial dysfunction and plaque vulnerability[64,65]. ApoE-deficient mouse models show severe oxidative stress in the vasculature, along with pronounced changes in gene expression involved in redox balance, inflammation, and endothelial function[66]. Excessive oxidation of PUFAs leads to the formation of large amounts of oxidized lipids and reactive aldehydes, which can cause protein modification, oxidative stress and worsen atherosclerotic progression[67]. Deficiency of ApoA1, which leads to low levels of HDL, induces apoptosis of myeloid cells through a Bcl-2-interacting mediator of cell death-dependent mechanism, leading to accelerated formation of necrotic cores and plaque progression[68]. Macrophage-derived ApoE is also important for maintaining vascular lipid homeostasis and controlling inflammatory responses[66]. RC adds to low-grade systemic inflammation, further encouraging plaque instability[45]. In contrast, n-3 PUFAs have strong anti-inflammatory effects through their influence on the composition of lipid rafts and membrane fluidity, gene expression, the inhibition of pro-inflammatory M1 macrophage polarization, the promotion of anti-inflammatory M2 polarization, the enhancement of phagocytic capacity, and the reduction of expression of pro-inflammatory cytokines and adhesion molecules[54].

Key molecular signaling pathways that have been implicated in plaque instability include the nuclear factor kappa B pathway, the Janus kinase-signal transducer and activator of transcription pathway, the NLRP3 inflammasome, and the endoplasmic reticulum stress-C/EBP homologous protein pathway[69-72]. These pathways work in concert to enhance inflammatory responses, cellular apoptosis, and plaque vulnerability, contributing to the development and progression of atherosclerosis and risk of acute cardiovascular events.

Current clinical assessment approaches and their limitations for vulnerable plaques

The evaluation of vulnerable plaques is mainly based on an integration of imaging and functional modalities. Non-invasive methods, including CCTA and cardiac magnetic resonance imaging, do not carry procedural risks and can provide valuable information regarding plaque morphology and composition[73]. In particular, CCTA has the capability to identify several high-risk plaque features, including low-attenuation plaques, positive remodeling, spotty calcification, and the napkin-ring sign[3]. However, these imaging techniques remain relatively expensive and may require specialized equipment and expertise for image acquisition and interpretation[74-80].

APPLICATION AND CHALLENGES OF NON-TRADITIONAL LIPID PARAMETERS IN CLINICAL SETTINGS

Current clinical and guideline status

The clinical status of the lipid-related parameters discussed in this review differs substantially. Lp(a) is recognized by current guidelines as a risk-enhancing factor, whereas non-HDL-C is recommended as a secondary treatment target[9,18,29]. LDL-P, sdLDL-C, and RC may provide additional information for risk refinement, but they do not have universally accepted intervention thresholds and are not established as routine therapeutic targets[26,27,49]. ApoE, ApoA1, and the ApoB/ApoA1 ratio remain mainly investigational or complementary biomarkers because their clinical thresholds and treatment implications have not been validated[34,39,41-43]. PUFAs should be regarded primarily as lipid-related therapeutic modifiers rather than routine stand-alone biomarkers, and evidence obtained with prescription EPA should not be generalized to all PUFA formulations or supplements[29,52-56,58]. The assay methods, target thresholds, clinical guideline recommendations, and practical limitations for each parameter are detailed in Table 2.

Table 2 Clinical applicability, measurement characteristics, and evidence status of major non-traditional lipid-related parameters.

Parameters	Definition/composition	Main biological characteristics	Atherosclerotic mechanism/potential	Clinical significance
Lp(a)	Lipoproteins containing apoB100 and Apo(a)	The structure is stable and not easily affected by lifestyle	Promote atherosclerosis, inflammation and thrombosis; even a low LDL-C level remains a risk factor[9,13]	Independent and causal ASCVD risk factors; a powerful marker of residual cardiovascular risk[9,56]
LDL-P, sdLDL-C	The total number and diameter of LDL particles; sdLDL-C refers to small and dense LDL-C	Cholesterol transport binds to receptors through apoB100	SdLDL particles are more likely to be filtered into the subendothelial space; more sensitive to oxidation, it promotes the formation of foam cells[57]	When LDL-C and LDL-P are inconsistent, LDL-P is superior to LDL-C in predicting the risk of ASCVD[58,59]
Non-HDL-C	The total amount of cholesterol in all atherosclerotic lipoproteins except HDL	Reflect the cholesterol load of all atherogenic lipoproteins	Better represents the overall atherosclerotic burden; related to coronary artery calcification and necrotic core volume[7,32]	Useful marker for assessing the risk of CVD, especially in patients with diabetes or high triglycerides; residual risks can be identified[7]
ApoE	The primary determinants in lipoprotein metabolism include three isomers: Ε2, ε3, and ε4	Mediate the clearance of plasma lipoproteins; regulate cellular cholesterol homeostasis; affect inflammation and cellular signaling	ApoE4 is associated with an increased risk of hyperlipidemia and atherosclerosis. It affects the inflammation and stability of plaques[60]	Genetic determinants of the risk of atherosclerosis; affecting the vulnerability of plaques[60]
ApoA1	Main structural protein of HDL	Key components involved in reverse cholesterol transport; facilitating cholesterol efflux from peripheral cells	Promote the outflow of cholesterol from lesions and reduce cholesterol accumulation; protect plaques from the development of necrotic cores[40]	Low levels are associated with unstable plaques; reverse cholesterol transport dysfunction is a cardiovascular risk factor[41]
RC	Cholesterol in triglyceride-rich lipoprotein metabolites	Metabolic residues of triglyceride-rich lipoproteins; high content in a non-fasting state	It penetrates and is retained within the arterial intima, leading to endothelial dysfunction, inflammation and atherosclerosis[12,61]	An important indicator for predicting the incidence of ASCVD; independently associated with unstable plaques; explaining the residual risk after good control of LDL-C[45,62]
PUFAs	Fatty acids containing two or more double bonds in their hydrocarbon chains, such as ω-3 PUFAs (e.g. EPA, docosahexaenoic acid)	Regulation of cell membrane fluidity lipid medium precursors; anti-inflammatory effect	ω-3 PUFAs can lower triglycerides, reduce inflammation, stabilize plaques and prevent plaque progression[63]	Potential adjunctive interventions; EPA may improve plaque characteristics in selected populations, but routine PUFA supplementation remains unsupported for plaque stabilization[63]

Lp(a): Lipoprotein(a); LDL-P: Low-density lipoprotein particle number; sdLDL-C: Small dense low-density lipoprotein cholesterol; HDL-C: High-density lipoprotein cholesterol; ApoE: Apolipoprotein E; ApoA1: Apolipoprotein A1; RC: Remnant cholesterol; PUFAs: Polyunsaturated fatty acids; Apo(a): Apolipoprotein(a); EPA: Eicosapentaenoic acid; ASCVD: Atherosclerotic cardiovascular disease; CVD: Cardiovascular disease.

Evidence from targeted intervention trials

An association between a lipid-related parameter and cardiovascular risk does not necessarily indicate that targeted modification of that parameter improves clinical outcomes. Selective Lp(a) lowering has not yet been shown in a completed cardiovascular outcome trial to reduce myocardial infarction, stroke, or cardiovascular death, and ongoing phase 3 trials are designed to address this question[19,20]. Similarly, current evidence has not established that treatment directed toward prespecified LDL-P, sdLDL-C, ApoE, or RC targets improves major cardiovascular outcomes[27,34,49]. For ApoA1, the phase 3 AEGIS-II trial did not significantly reduce its primary 90-day composite cardiovascular endpoint[39]. In contrast, the REDUCE-IT trial demonstrated that icosapent ethyl reduced ischemic cardiovascular events in selected statin-treated high-risk patients with elevated triglyceride levels; however, this benefit should not be extrapolated to all PUFA preparations or routine PUFA testing[53,54,58]. Non-HDL-C remains a guideline-endorsed secondary treatment target, although it reflects the overall burden of ApoB-containing lipoproteins rather than a separately targetable molecular pathway[29].

Practical barriers to clinical implementation

Several practical barriers limit the routine clinical implementation of these parameters. First, assay standardization remains incomplete. Lp(a) measurement may be affected by Apo(a) isoform size, and fixed conversion between mg/dL and nmol/L is not recommended[9,18]. LDL-P and sdLDL-C results vary across nuclear magnetic resonance spectroscopy, ultracentrifugation, ion mobility analysis, and direct homogeneous assays, making reference ranges difficult to harmonize across platforms[27]. RC may be calculated or directly measured, but these approaches do not necessarily quantify identical remnant lipoprotein fractions[49]. Second, reference intervals and decision thresholds may differ according to population, analytical method, and clinical setting. Third, compared with routine lipid profiles, advanced lipid testing may be less available, more costly, and variably reimbursed across healthcare systems[27,81,82]. These issues support a selective, clinically contextual use of non-traditional lipid parameters rather than indiscriminate routine testing.

Risk assessment and stratification

Traditional cardiovascular risk scores, including the Framingham Risk Score, have limitations in predicting individual residual risk[83]. Non-traditional lipid parameters may refine risk stratification, particularly among patients who remain at high cardiovascular risk despite guideline-directed statin therapy[84]. Beyond the assessment of individual vulnerable plaques, the broader concept of the “vulnerable patient” is also relevant to the development of acute coronary thrombotic events[85]. Non-invasive imaging modalities provide opportunities to detect high-risk plaques and assess subclinical atherosclerosis. Integrating circulating biomarkers with imaging findings may improve the identification and risk stratification of individuals at high risk of acute vascular events[86].

Potential therapeutic implications

Non-traditional lipid-related parameters may have therapeutic implications for residual cardiovascular risk and plaque stabilization, but their readiness as treatment targets differs substantially. Although statins are effective in lowering LDL-C, persons at high cardiovascular risk still have significant residual risk of plaque progression[87]. This constant risk has led to the search for new therapeutic approaches to reduce residual cardiovascular risk. Lp(a) is a major contributor to residual risk and PCSK9 inhibitors have been shown to be effective at reducing Lp(a) levels. Elevated Lp(a) has been linked to the progression of low attenuation (necrotic core) plaques in CAD, and to the progression and vulnerability of carotid artery plaques[87]. Emerging therapies that lower Lp(a) through modulation of Apo(a), such as antisense oligonucleotides and small interfering RNA molecules, have shown substantial Lp(a)-lowering effects in clinical trials, although their effects on cardiovascular outcomes remain under investigation[88]. Other parameters, including sdLDL-C, non-HDL-C, and RC, may be modified indirectly by therapies targeting LDL-C, triglyceride-rich lipoproteins, and overall atherogenic burden. However, only non-HDL-C is currently established as a guideline-endorsed secondary treatment target, whereas sdLDL-C and RC remain emerging biomarkers. Pharmacologic interventions that modify these lipoproteins, including triglyceride-lowering agents such as niacin, fibrates, and n-3 PUFAs, may improve lipid profiles, but evidence for plaque stabilization and hard-outcome benefit varies according to drug class, formulation, and patient population[54,89,90].

Limitations and controversies

Although non-traditional lipid parameters have great potential in cardiovascular risk evaluation and prediction of vulnerable plaques, their clinical use is still limited and remains a matter of discussion. High detection costs, complicated measurement procedures, and the unclear status of guideline recommendations limit their widespread use[81,82]. Currently, most international guidelines acknowledge non-HDL-C as a secondary therapeutic target, but its prioritization in complex lipid disorders remains a matter of debate[63]. Focusing only on “vulnerable plaques” may also underestimate overall patient risk, and emphasizes the importance of adopting the broader concept of “vulnerable patients” and stressing comprehensive assessment of disease burden[91]. Recent research has increasingly focused on this approach and the importance of disease burden as a predictor of cardiovascular risk[85]. These limitations and controversies call for further studies to clarify the clinical utility, positioning of guidelines, and therapeutic implications of non-traditional lipid parameters. Accordingly, the clinical use of non-traditional lipid-related parameters should be selective rather than universal. These markers are most useful when interpreted together with conventional lipid profiles, global ASCVD risk, plaque imaging findings, patient phenotype, and the strength of available outcome evidence. Overinterpretation of observational associations should be avoided, particularly when validated treatment thresholds or randomized outcome evidence are lacking.

FUTURE DIRECTIONS

Establishing validated thresholds and treatment targets

Prospective cohort studies are needed to validate assay- and population-specific risk thresholds, whereas randomized controlled trials are required to determine whether targeted modification of these parameters improves cardiovascular outcomes[11]. This is particularly important because residual cardiovascular risk may persist despite conventional lipid-lowering strategies[83]. Non-traditional lipid markers such as Lp(a), sdLDL-C, non-HDL-C and RC have been found to be independently linked with a higher risk of cardiovascular events[64,92]. Considering the importance of individual genetic backgrounds, such as Lp(a) and ApoE genotypes, as well as metabolic profiles, future studies should explore how these factors can support more individualized cardiovascular risk assessment and lipid management[93,94]. Moreover, standardization of laboratory assays, harmonization of measurement units, and establishment of population- and assay-specific reference intervals are prerequisites for the broader clinical implementation of non-traditional lipid biomarkers.

Integrated multimodal prediction models

Constructing comprehensive predictive models incorporating multiple biomarkers and imaging data is critical to the future assessment of vulnerable plaques. Traditional risk scoring tools have significant limitations in their ability to accurately predict individual risk[91]. Looking to the future, the combination of multi-omics datasets, including genomics, transcriptomics, proteomics, and metabolomics, will allow for the further understanding of the molecular mechanisms underlying atherosclerosis and the identification of novel biomarkers and therapeutic targets[71,86]. The combination of advanced imaging modalities, such as CCTA, intravascular ultrasound, and optical coherence tomography, with circulating biomarkers, such as non-traditional lipid parameters, can provide more information regarding plaque characteristics, improve risk stratification, and support precise, personalized therapeutic interventions[84,85].

Targeting non-traditional lipid parameters for plaque stabilization and regression

The reversal of atherosclerotic plaques is a complex process that involves the removal of lipids and necrotic material and restoration of endothelial function and repair of damaged vascular regions[95,96]. Although complete plaque regression is rarely achieved, aggressive lipid-lowering therapy has been shown to stabilize plaques and induce partial plaque regression[97]. High-intensity statins are the best available therapy and have been shown to significantly reduce plaque volume, including percent atheroma volume, and total atheroma volume[97]. Adjunctive agents such as ezetimibe and PCSK9 inhibitors have also shown significant plaque regression effects[96]. Additionally, EPA, an omega-3 fatty acid, has been shown to significantly decrease the volume of coronary plaque[96]. Given the central role of non-traditional lipid parameters in plaque formation and instability, examining whether targeted interventions can directly promote the reversal of vulnerable plaques is a promising avenue for future cardiovascular therapeutics[98].

Integration of artificial intelligence with non-traditional lipid parameters

Artificial intelligence (AI) and machine learning provide high potential tools for integrating data from various sources, building personalized cardiovascular risk models, and making precise and targeted interventions[99-101]. The prospective evolution of combining non-traditional lipid parameters with AI-based approaches is presented in Figure 5. AI-driven plaque analysis can conduct fast, reproducible and comprehensive assessments of coronary artery imaging, reliably detecting characteristics of vulnerability, such as lipid-rich necrotic cores and calcification[102]. Despite its great promise, the clinical use of AI has several challenges, such as the need for large-scale, multicenter data sets, the development of interpretable AI frameworks, and prospective validation on meaningful patient outcomes[102]. Addressing these challenges will be critical to bring AI-driven insights to routine clinical practice.

Figure 5 Future development directions for the application of non-traditional lipid parameters. After analysis and processing by algorithms such as artificial intelligence, non-traditional lipid parameters and imaging data can be utilized to stratify patient risk and devise personalized treatment plans targeting these parameters. These advanced therapies can further mitigate residual cardiovascular risk by precisely modulating lipoprotein metabolism. Lp(a): Lipoprotein(a); RC: Remnant cholesterol; ApoE: Apolipoprotein E; ApoA1: Apolipoprotein A1; CCTA: Coronary computed tomography angiography; OCT: Optical coherence tomography; PET: Positron emission tomography; AOS: Antisense oligonucleotides; siRNA: Small interfering RNA; sdLDL: Small dense low-density lipoprotein; RC: Remnant cholesterol; EPA: Eicosapentaenoic acid; TG: Triglyceride; IL-6: Interleukin-6; RCT: Reverse cholesterol transport; LCAT: Lecithin-cholesterol acyltransferase.

CONCLUSION

Non-traditional lipid-related parameters provide complementary information for understanding residual cardiovascular risk and plaque vulnerability, but their clinical applicability differs markedly. Among the parameters reviewed, Lp(a) is currently useful as a guideline-recognized risk-enhancing factor, and non-HDL-C is established as a practical secondary treatment target. In contrast, LDL-P, sdLDL-C, ApoE, ApoA1, and RC remain mainly complementary or investigational markers because validated intervention thresholds and hard-outcome evidence are still lacking. Prescription EPA represents a specific therapeutic option for selected high-risk patients with persistent hypertriglyceridemia, but its evidence should not be generalized to all PUFA formulations or supplements. Therefore, these parameters should not be interpreted as uniformly ready for routine clinical use. Their future value will depend on assay standardization, harmonized units and reference intervals, cost-effective implementation, and randomized outcome trials demonstrating that targeted modification improves myocardial infarction, stroke, cardiovascular death, or other clinically meaningful endpoints.

ACKNOWLEDGEMENTS

The authors thank their colleagues and research team members for their support during the preparation of this review.