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Remnant-C (RC) have been emerging as a CVD risk factor in recent years.
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Elevated RC was associated with increased risk of CVD events, stroke, and mortality.
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Per 1.0-mmol/L of RC increase was associated with the increased risk of CVD events and CHD.
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This association is independent on total cholesterol, triglyceride, ApoB levels or BMI.
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Clinicians should pay attention to RC in clinic.
Abstract
Background and aims
Lipid disorders are associated with the risk of cardiovascular diseases (CVDs). Remnant cholesterol (RC), a non-traditional previously neglected risk factor for CVD, has received much attention in recent years. The aim of this study is to evaluate the association of RC with the risks of CVD, stroke, and mortality.
Methods
MEDLINE, Web of Science, EMBASE, ClinicalTrials.gov, and Cochrane Central Register for Controlled Trials were searched. We included randomized controlled trials (RCTs), non-RCTs, and observational cohort studies assessing the association of RC with the risks of cardiovascular (CV) events, coronary heart disease (CHD), stroke, and mortality.
Results
Overall, 31 studies were included in this meta-analysis. Compared with low RC, elevated RC was associated with an increased risk of CVD, CHD, stroke, CVD mortality, and all-cause mortality (RR = 1.53, 95% CI 1.41–1.66; RR = 1.41, 95% CI 1.19–1.67; RR = 1.43, 95% CI 1.24–1.66; RR = 1.83, 95% CI 1.53–2.19; and RR = 1.39, 95% CI 1.27–1.50; respectively). A subgroup analysis demonstrated that each 1.0 mmol/L increase in RC was associated with an increased risk of CVD events and CHD. The association of RC with an increased CVD risk was not dependent on the presence or absence of diabetes, a fasted or non-fasted state, total cholesterol, or triglyceride or ApoB stratification.
Conclusions
Elevated RC is associated with an increased risk of CVD, stroke, and mortality. In addition to the traditional cardiovascular risk factors, such as total cholesterol and LDL-C, clinicians should also pay attention to RC in clinics.
Lipid disorders, especially those involving elevated cholesterol and low-density lipoprotein C (LDL-C), are major risk factors for cardiovascular diseases (CVDs) and ischemic stroke. Lipid-lowering therapy is associated with reduced risks of cardiovascular (CV) events and all-cause mortality in the general population. It is effective in both primary and secondary prevention [
]. A meta-analysis that included 26 randomized trials and 170,000 participants has demonstrated that the intensive lowering of LDL-C produces definite reductions in the incidence of heart attack, revascularization, and ischemic stroke. It was found that each 1.0 mmol/L reduction in LDL-C decreased the annual rate of these major vascular events by over one-fifth; no threshold was identified for the cholesterol range studied. This indicates that reducing LDL cholesterol by 2–3 mmol/L may reduce risk by approximately 40%–50% [
Cholesterol Treatment Trialists’ (CTT) Collaboration Efficacy and safety of more intensive lowering of LDL cholesterol: a meta-analysis of data from 170,000 participants in 26 randomised trials.
]. However, a significant CVD risk has still been observed, even when the goal of LDL-C < 100 mg/dL was achieved with intensive statin therapy in several large trials [
]. Remnant cholesterol (RC) is a potential risk factor associated with increased residual CV risk. RC is defined as the cholesterol content of remnants, which are a subset of triglyceride-rich lipoproteins. These include chylomicron remnants, very-low-density lipoproteins (VLDLs), and intermediate-density lipoproteins (IDLs). RC can be measured in the laboratory, as well as calculated based on LDL-C and HDL-C values. RC is calculated as the total cholesterol minus HDL-C minus LDL-C. RC is more abundant and larger, and on a per particle basis, remnants carry more cholesterol than LDL-C particles. It is also more harmful to the arterial endothelium [
]. RC is associated with inflammation, oxidative stress, accelerated atherosclerosis, and ischemic heart disease, in both fasting and non-fasting states [
]. Elevated RC levels have been observed to be a risk factor for coronary artery disease (CAD) and ischemic heart disease (IHD) in some prospective and retrospective cohort studies [
Extreme nonfasting remnant cholesterol vs extreme LDL cholesterol as contributors to cardiovascular disease and all-cause mortality in 90000 individuals from the general population.
Lipoprotein investigators collaborative (LIC) study group. Remnant lipoprotein cholesterol and incident coronary heart disease: the jackson heart and Framingham offspring cohort studies.
Association between remnant lipoprotein cholesterol, high-sensitivity C-reactive protein, and risk of atherosclerotic cardiovascular disease events in the Multi-Ethnic Study of Atherosclerosis (MESA).
]. However, these also include some relatively smaller studies. It is also inconclusive whether increased RC elevates the risks of stroke and mortality. RC, while previously neglected, has attracted attention in recent years as a potential risk factor for CVD. It is therefore needed to perform a meta-analysis that includes all clinical trials to further confirm the relationship between RC and the risks of CVD, stroke, and mortality.
2. Materials and methods
A standard protocol was developed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [
]. This study was registered with the International Prospective Register of Systematic Reviews (PROSPERO), number CRD42022299183.
2.1 Search strategy and study selection
We searched for and extracted the relevant literature from several databases, including MEDLINE (PubMed, January 1, 1966, to January 31, 2023), Web of Science, EMBASE (January 1, 1966, to January 31, 2023), ClinicalTrials.gov, and the Cochrane Central Register of Controlled Trials. The following keywords were used: “remnant cholesterol” and “cardiovascular disease,” “coronary heart disease,” “stroke,” “cardiovascular death,” or “cardiovascular mortality,” “all-cause death,” or “all-cause mortality.” Manual searches of references cited by the identified original studies and relevant review articles were also performed. The selected papers were evaluated. All the studies included in this meta-analysis were published in English. The detailed steps are demonstrated in Supplementary Fig. 1 and Supplementary Table 1.
] reported that when RC ≥ 0.65 mmol/L (25 mg/dL), the volume of atherosclerotic plaques and the risk of atherosclerotic cardiovascular disease (ASCVD) increased. Based on this, we categorized patients according to their RC values as follows: patients with RC values of <0.65 mmol/L were categorized in the low-RC group, and patients with RC values of ≥0.65 mmol/L were categorized in the high-RC group.
Studies that met the following criteria were included in our meta-analysis: (1) randomized controlled trials (RCTs), non-RCTs, and observational studies; (2) high RC was compared with low RC; and (3) an outcome (CVD, coronary heart disease (CHD), stroke, all-cause mortality, or CVD mortality) was available.
Studies were excluded if they met any of the following criteria: (1) not being published in English; (2) not presenting a comparison of outcomes; (3) providing no description of CVD, CHD, stroke, or all-cause mortality; (4) analyzing the same population or duplicates; and (5) containing a maximum RC value of less than 0.65 mmol/L.
2.3 Data collection
Three researchers (Yang X.H., Zhang B.L., and Cheng Y.) performed the search and reviewed the results. Data were independently extracted and collected by these three researchers who reviewed all the study characteristics (i.e., the first author's surname, year of publication, study design, sample, follow-up, and outcomes). Any disagreement regarding data extraction was resolved by inter-reviewer discussion in consultation with the other authors (Jin H.M. and Fun S.K.). Considering the different methods used to measure or estimate RC may lead to heterogeneity, so we also collected the details on the specific methods used to either measure or estimate the RC in each study. Some studies measured RC directly using an automated assay by Denka Seiken. Most of the studies indirectly calculated RC. The indirect method of estimating RC is to calculate the total TC - LDL-C – HDL-C. Regardless of the level of triglycerides, some studies determined LDL-C directly. However, some studies estimated LDL-C using the Friedewald equation when plasma triglycerides were <4.0 mmol/L; otherwise, it was measured directly.
2.4 Summary measures and synthesis of results
The risk ratio (RRs) for CVD, CHD, stroke, all-cause mortality, and CVD mortality were extracted from each study or calculated by one of the researchers (Yang X.H.). The baseline characteristics, such as the study design, age, sex, pre-existing conditions, study type, method of obtaining RC, outcomes, follow-up, and quality, were also extracted from all included studies. CVD events were defined as the occurrence of CHD (including myocardial infarction and angina), heart failure, and cerebrovascular diseases (including stroke, transient cerebral ischemic attack, and cerebrovascular accident). This was based on the diagnosis codes in the International Classification of Diseases, 9th Revision, Clinical Modification.
2.5 Assessment of heterogeneity
Heterogeneity was evaluated using Galbraith plots and I2 statistics. Studies with I2 values of <50% were considered non-heterogeneous; thus, a fixed-effects model was used in their analysis. However, studies with I2 > 50% were considered heterogeneous (50–75% and >75% represented medium and high heterogeneities, respectively); therefore, they were analyzed using a random-effects model [
2.6 Quality assessment and risk of bias assessment
The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system (https://gdt.gradepro.org/app/) was used to evaluate the quality of the evidence. The Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) tool was also used to assess the quality of the included non-RCTs [
]. The studies were ranked as having a low, moderate, serious, or critical risk of bias in seven domains. Any discrepancies were resolved by discussion with a third author (Jin H.M.).
2.7 Statistical analyses
The data were analyzed using STATA version 17.0 (StataCorp LLC, TX, USA). The RRs for CVD, CHD, stroke, all-cause mortality, and CVD mortality were either calculated or extracted from the individual studies. This meta-analysis was stratified for the different methods used to determine or estimate RC for those outcomes. We conducted a sensitivity analysis in which each study was evaluated for its effect on the estimate. The sensitivity analysis was performed using the metaninf function (one-study removal approach). Subgroup analyses were also performed to evaluate the effects of different disease conditions, such as the presence or absence of diabetes, the fasted or non-fasted state, race, total cholesterol, or triglyceride or ApoB stratification, and body mass index (BMI) on the risk of CVD events. Egger's test or Begg's test was used to evaluate the presence of publication bias. The statistical significance for all analyses was set at p < 0.05.
3. Results
3.1 Study flow and characteristics
The decision-making process for the inclusion of studies in the meta-analysis is demonstrated in Supplementary Fig. 1. Overall, 31 studies involving 2,857,236 participants were included [
Extreme nonfasting remnant cholesterol vs extreme LDL cholesterol as contributors to cardiovascular disease and all-cause mortality in 90000 individuals from the general population.
Lipoprotein investigators collaborative (LIC) study group. Remnant lipoprotein cholesterol and incident coronary heart disease: the jackson heart and Framingham offspring cohort studies.
Association between remnant lipoprotein cholesterol, high-sensitivity C-reactive protein, and risk of atherosclerotic cardiovascular disease events in the Multi-Ethnic Study of Atherosclerosis (MESA).
Remnant cholesterol and its visit-to-visit variability predict cardiovascular outcomes in patients with type 2 diabetes: findings from the ACCORD cohort.
]. Table 1 displays the characteristics of the 31 included studies. CVD events were recorded in 20 studies, CHD was recorded in seven studies, stroke was recorded in seven studies, all-cause mortality was recorded in seven studies, and CVD mortality was recorded in seven studies. The number of studies that used indirect measures to estimate RC was 28. One study measured RC directly, and two studies both measured RC directly and used indirect methods to estimate RC.
Table 1Characteristics of 31 studies associated with CVD events, CHD, all/CVD mortality and stroke.
Extreme nonfasting remnant cholesterol vs extreme LDL cholesterol as contributors to cardiovascular disease and all-cause mortality in 90000 individuals from the general population.
Lipoprotein investigators collaborative (LIC) study group. Remnant lipoprotein cholesterol and incident coronary heart disease: the jackson heart and Framingham offspring cohort studies.
Association between remnant lipoprotein cholesterol, high-sensitivity C-reactive protein, and risk of atherosclerotic cardiovascular disease events in the Multi-Ethnic Study of Atherosclerosis (MESA).
Remnant cholesterol and its visit-to-visit variability predict cardiovascular outcomes in patients with type 2 diabetes: findings from the ACCORD cohort.
Calculated-1: Indirect measures estimate RC by calculating total cholesterol - LDL-cholesterol - HDL cholesterol. Regardless the levels of triglyceride, LDL-Cholesterol was determined directly.
Calculated-2: Indirect measures estimateRC by calculating total cholesterol - LDL-cholesterol - HDL cholesterol. LDL-Cholesterol was calculated by the Friedewald equation when plasma triglycerides were <4.0 mmol/L (<352 mg/dL), and otherwise measured directly.
Measured: RC was measured directly with an automated assay by Denka Seiken.
CVD events were recorded in 20 studies investigating high versus low RC, and CHD was recorded in seven studies. The results of the random-effects model's pooling of the RRs for the CVD events and CHD are demonstrated in Fig. 1, Fig. 2. Compared to the low-RC group, the high-RC group demonstrated an increased risk of CVD events (RR = 1.53, 95% CI 1.41–1.66, p < 0.0001; Fig. 1), with moderate heterogeneity between studies (Supplementary Fig. 2A). Similarly, the pooled results from the seven studies recording CHD indicated that high RC was associated with increased CHD outcomes (RR = 1.41, 95% CI 1.19–1.67, p < 0.0001; Fig. 2), with moderate heterogeneity between studies (Supplementary Fig. 2B). The stratification of RC was also analyzed in six studies, and the results indicated that CVD events increased with an increase in RC (Supplementary Table 2).
Fig. 1RRs for CVD events associated with high vs. low RC from pooled studies.
Calculated-1: indirect method used to estimate RC by calculating total TC - LDL-C – HDL-C; regardless of the level of triglycerides, LDL-C was measured directly. Calculated-2: indirect method used to estimate RC by calculating total TC - LDL-C – HDL-C. LDL-C was calculated using the Friedewald equation when plasma triglycerides were <4.0 mmol/L; otherwise, it was measured directly. Measured: RC was measured directly using an automated assay by Denka Seiken.
Calculated-1: indirect method used to estimate RC by calculating total TC - LDL-C – HDL-C; regardless of the level of triglycerides, LDL-C was measured directly. Calculated-2: indirect method used to estimate RC by calculating total TC - LDL-C – HDL-C. LDL-C was calculated using the Friedewald equation when plasma triglycerides were <4.0 mmol/L; otherwise, it was measured directly. Measured: RC was measured directly using an automated assay by Denka Seiken.
Seven studies assessed stroke as an outcome, seven studies investigated all-cause mortality, and seven studies investigated CVD mortality. The results from the pooling of the RRs for stroke, CVD mortality, and all-cause mortality are demonstrated inFig. 3A-C, respectively. Compared to the low-RC group, the high-RC group demonstrated an increased risk of stroke (RR = 1.43, 95% CI 1.24–1.66, p < 0.0001; Fig. 3A), with moderate heterogeneity between studies (Supplementary Fig. 2C). The pooled results from the seven studies indicated that high RC was associated with increased CVD mortality when compared with low RC (RR = 1.83, 95% CI 1.53–2.19, p < 0.0001; Fig. 3B), with moderate heterogeneity between studies (Supplementary Fig. 2D). Similarly, the pooled results from the seven studies indicated that high RC was associated with increased all-cause mortality when compared with low RC (RR = 1.39, 95% CI 1.27–1.50, p < 0.0001; Fig. 3C), with non-heterogeneity between studies (Supplementary Fig. 2E).
Fig. 3RRs for stroke and mortality associated with high vs. low RC from pooled studies. (A) RRs for stroke associated with high RC. (B) RRs for CVD mortality associated with high RC. (C) RRs for all-cause mortality associated with high RC. Calculated-1: indirect method used to estimate RC by calculating total TC – LDL-C – HDL-C. Regardless of the level of triglycerides, LDL-C was measured directly. Calculated-2: indirect method used to estimate RC by calculating total TC - LDL-C – HDL-C. LDL-C was calculated using the Friedewald equation when plasma triglycerides were <4.0 mmol/L; otherwise, it was measured directly. Measured: RC was measured directly using an automated assay by Denka Seiken.
Fig. 3RRs for stroke and mortality associated with high vs. low RC from pooled studies. (A) RRs for stroke associated with high RC. (B) RRs for CVD mortality associated with high RC. (C) RRs for all-cause mortality associated with high RC. Calculated-1: indirect method used to estimate RC by calculating total TC – LDL-C – HDL-C. Regardless of the level of triglycerides, LDL-C was measured directly. Calculated-2: indirect method used to estimate RC by calculating total TC - LDL-C – HDL-C. LDL-C was calculated using the Friedewald equation when plasma triglycerides were <4.0 mmol/L; otherwise, it was measured directly. Measured: RC was measured directly using an automated assay by Denka Seiken.
Fig. 3RRs for stroke and mortality associated with high vs. low RC from pooled studies. (A) RRs for stroke associated with high RC. (B) RRs for CVD mortality associated with high RC. (C) RRs for all-cause mortality associated with high RC. Calculated-1: indirect method used to estimate RC by calculating total TC – LDL-C – HDL-C. Regardless of the level of triglycerides, LDL-C was measured directly. Calculated-2: indirect method used to estimate RC by calculating total TC - LDL-C – HDL-C. LDL-C was calculated using the Friedewald equation when plasma triglycerides were <4.0 mmol/L; otherwise, it was measured directly. Measured: RC was measured directly using an automated assay by Denka Seiken.
3.4 Subgroup analysis of relative risk of CVD events
Age, sex, pre-existing conditions, a fasted or non-fasted state, race, total cholesterol or triglyceride levels, LDL-C or ApoB, the presence or absence of diabetes or hypertension, and BMI were potential confounders related to CVD outcomes. As demonstrated in Fig. 4, the estimated RRs indicated that high RC was associated with an increased risk of CVD events in participants aged <65 years, as well as in participants aged ≥65 years, compared to low RC (RR = 1.39, 95% CI 1.14–1.70, p < 0.0001; RR = 1.20, 95% CI 1.16–1.25, p < 0.0001, respectively). The estimated RRs also indicated that high RC increased the risk of CVD events irrespective of the male or female sex (RR = 1.31, 95% CI 1.26–1.36, p < 0.0001; RR = 1.27, 95% CI 1.23–1.31, p < 0.0001, respectively) when compared to low RC. The estimated RRs indicated that high RC was associated with the increased risk of CVD events whether in a fasted or non-fasted state (RR = 1.36, 95% CI 1.26–1.47, p < 0.0001; RR = 1.58, 95% CI 1.31–1.86, p < 0.0001, respectively). Similarly, high RC was also associated with an increased risk of CVD events regardless of the race, presence or absence of previous heart disease, with or without diabetes or hypertension and different BMI stratifications. Also this association was not dependent of high or low total directly measured cholesterol, triglycerides, LDL-C or ApoB levels. We also analyzed the risk of RC increase per 1.0 mmol/L of RC and CVD events in five studies. As demonstrated in Supplementary Fig. 3, a 1.0 mmol/L of RC increase was associated with an increased risk of CVD events and CHD (RR = 1.15, 95% CI 1.08–1.22; RR = 1.58, 95% CI 1.12–2.23, respectively).
Fig. 4Subgroup analysis of high RC for the risk of CVD events.
3.5 Subgroup analysis of relative risks of CHD, stroke, and mortality
To determine whether there were differences in outcomes (CHD, stroke, and mortality) between lipid profile measurements of RC taken in a fasted and a non-fasted state, we conducted a subgroup analysis according to fasted and non-fasted states. The results showed that high RC was associated with increased risks of CHD, stroke, and CVD mortality regardless of the fasted or non-fasted state (Supplementary Figs. 4A–C). As shown in Supplementary Fig. 4D, the estimated RR indicated that high RC was associated with an increased risk of all-cause mortality in the non-fasted state.
3.6 Sensitivity analysis and publication bias
Considering the importance of potential confounders in observational studies, sensitivity analyses were conducted by excluding studies with a serious risk of bias. After the exclusion of each study, no significant association emerged for the outcomes in the sensitivity analysis.
Publication bias was assessed using Egger's test or Begg's test. Consequently, no publication bias was found in the pooled studies on CHD, CVD mortality and all-cause mortality (CHD, p = 0.297; CVD mortality, p = 0.202; all-cause mortality, p = 0.288). However, there was a significant publication bias for CVD and stroke (CVD, p = 0.001; stroke, p = 0.022).
3.7 Risk of bias assessment and quality of evidence assessment
The detailed risk assessment of the included studies using the ROBINS-I tool is demonstrated in Supplementary Table 3. Eight studies were evaluated as having a low risk of overall bias, as they were graded as having a low risk of bias in all seven domains. Only one study was graded as having a serious risk, as it was graded as having a serious risk of bias in at least one domain. Twenty-two studies were graded as having a moderate risk of overall bias, with more than one domain being graded as having a moderate risk of bias.
The GRADE system was used to assess the quality of the evidence. The evaluation results are presented in Supplementary Table 4. In summary, the quality of the evidence was rated as moderate for CVD, CHD, stroke, all-cause mortality, and CVD mortality due to the observational nature of the studies or the risk of bias.
4. Discussion
This meta-analysis is the first pooled study that includes the largest number of studies and the largest sample size to assess the association between RC levels and the risks of CVD, stroke, and mortality. The main results indicate that elevated RC is associated with an increased risk of CVD events, stroke, and mortality, both in the general population and in patients with disease status. A subgroup analysis further indicated that this association was not dependent on the population (with or without disease), the presence or absence of diabetes, blood total cholesterol, triglyceride, ApoB levels, or BMI stratification.
There are some concerns as to whether calculated RC can accurately reflect real RC. Remnant lipoprotein levels are difficult to measure because of the heterogeneous nature of these macromolecules. Traditional methods using ultracentrifugation, agarose gel electrophoresis, low-concentration polyacrylamide gel electrophoresis, nuclear magnetic resonance, or high-performance liquid chromatography are complex and time-consuming [
]. RC is easy to calculate and use in clinical practice. It is especially suitable for application in large prospective cohort studies. There are some arguments for the use of calculated RC to evaluate CVD prognosis [
]. However, in the analysis of the association of both measured and calculated RC with all-cause mortality in patients with prior ischemic heart disease, calculated RC has been demonstrated to have the strongest association [
]. In a comparison and association of RC levels (estimated using calculated and measured LDL-C levels) with CHD, non-fasting estimated RC was observed to be an independent predictor of CHD risk in Chinese subjects with CHD [
]. This indicates that the non-fasting state of estimated RC is critical in determining the development of atherosclerosis. A comparison of calculated vs. directly measured RC using nuclear magnetic resonance also indicated that calculated RC was positively consistent with measured RC at high TG levels (≥150 mg/dL), and calculated RC had low correlations with measured RC when the TG levels were <150 mg/dL [
]. So, using calculated RC instead of directly measured RC when stratified by TG level to evaluate actual RC in clinical studies may be feasible. It is unclear whether the use of RC as a risk marker for initially identifying high-risk patients can improve the 10-year risk score or the European scoring system. No studies have explored or validated the 10-year risk score when using RC as a risk marker. The use of large cohorts in the future will confirm RC and the 10-year risk score or the European scoring system prediction model.
There are some concerns as to whether the risk of RC is dependent on LDL-C and triacylglyceride levels. In several clinic trials, LDL-C levels were not measured directly but instead calculated with the Friedewald formula if triglycerides were less than 4.5 mmol/L. According to the widely used Friedewald equation, LDL-C is assessed as total cholesterol minus HDL-C minus triglycerides in mg/dL divided by 5. Therefore, RC-calculated according to this definition is serum TGs in mg/dL divided by 5 (or TG in mmol/L divided by 2.2). In general, TGs are transported in the plasma in VLDL, chylomicrons, and their remnants during metabolism. The Friedewald equation assumes a fixed ratio between TGs and VLDL-C of 5:1. Data from individuals in the Framingham Heart Study who were free of coronary heart disease indicated that VLDL-C was easily estimated by multiplying the triglyceride value by 0.20 [
]. Therefore, the formula TC - LDL-C - HDL-C captures VLDL-C as well as other remnant-C.
The Copenhagen City Heart Study found that employing both direct assays and calculations using the Friedewald equation produced similar results in the LDL-C range from 1 to 10 mmol/L in the prediction of future cardiovascular events [
Directly measured vs. calculated remnant cholesterol identifies additional overlooked individuals in the general population at higher risk of myocardial infarction.
]. In our meta-analysis, we also confirm that RC levels determined from LDL-C levels both measured and calculated using the Friedewald equation are associated with an elevated CVD risk, indicating that it is feasible to use calculated LDL-C when assaying RC. In a study involving 10196 patients with diabetes, it was observed that visit-to-visit calculated RC variability was associated with major adverse cardiovascular events, independent of LDL-C levels [
Remnant cholesterol and its visit-to-visit variability predict cardiovascular outcomes in patients with type 2 diabetes: findings from the ACCORD cohort.
Usually, elevated levels of non-fasting/post-prandial triglycerides directly correlate with elevated RC in the general population, and elevated triglyceride levels act as excellent markers for elevated RC [
]. A previous meta-analysis demonstrated that elevated triglyceride levels were excellent markers of an increased CVD risk, but this association disappeared after adjustment for HDL cholesterol and non-HDL cholesterol [
]. A recent study showed that an RC of ≥1 mmol/L and plasma triglycerides of ≥2 mmol/L are associated with two-fold mortality from cardiovascular and other causes [
]. In patients with high triacylglyceride levels, a causal association between elevated levels of calculated RC and an increased risk of myocardial infarction was observed in the Copenhagen City Heart Study, indicating that the arteriosclerotic effect of RC does not depend on blood triglyceride levels [
]. In this meta-analysis, it was also observed that the relationship between RC and CVD is independent of blood triglyceride levels. The Prevention of Diet Mediterranean (PREDIMED) also showed that triglycerides (HR = 1.04, 95%CI 1.02–1.06) and RC (HR = 1.21, 95%CI 1.10–1.33) were independently associated with major adverse cardiovascular events (MACE) in high-risk primary prevention [
There are some controversies regarding the use of fasting or non-fasting remnant lipid profiles to predict potential CVD risk. In the past, a fasting state was recommended for many years; however, fasting lipid measurements are clinically inconvenient for some patients. Non-fasting lipid levels have been recommended in several guidelines. Non-fasting lipid levels might also be a better indicator of plasma atherogenic lipoprotein concentrations when compared with fasting state levels [
]. In the subgroup analysis, it was shown that, regardless of the use of fasting or non-fasting RC, elevated RC is associated with an elevated CVD risk, so it is convenient to use non-fasting RC in clinic follow-ups.
Some previous prospective, retrospective, and case–control studies, as well as this meta-analysis, have clearly demonstrated that (1) elevated RC is strongly related to cardiovascular outcomes; (2) patients with clinically diagnosed CAD or CHD often display high RC levels; and (3) estimated or measured RC can predict the probability of future CVD events, stroke, and mortality.
There are some potential confounding factors that affect the outcomes of RC and CVD. The common factors are obesity or metabolic syndrome (MetS). The clinical diagnosis of MetS includes the presence of an increased waist circumference or abdominal obesity, reduced high-density lipoprotein levels, elevated blood pressure, and increased blood glucose and triacylglyceride levels. The effects on cholesterol in obesity or MetS are often neglected. Previous studies have demonstrated that a high BMI and an increased waist circumference are more associated with cholesterol levels than triacylglyceride levels in children [
]. In a previous study of the JCR:LA-cp rat model of metabolic syndrome (MetS), it was observed that the increased progression of atherosclerotic cardiovascular disease in the presence of MetS and type 2 diabetes mellitus might be explained by an increase in the arterial retention of cholesterol-rich remnants [
Arterial retention of remnant lipoproteins ex vivo is increased in insulin resistance because of increased arterial biglycan and production of cholesterol-rich atherogenic particles that can be improved by ezetimibe in the JCR:LA-cp rat.
Cholesterol-rich ApoB is another CVD risk factor. It has been established that elevated ApoB levels are causatively linked to the development of atherosclerotic CVD [
]. In a large cohort study involving 389529 individuals in the primary prevention group, the risk of myocardial infarction was best indicated by the number of ApoB-containing lipoproteins, independent from the lipid content (cholesterol or triacylglyceride) or type of lipoprotein (LDL or triacylglyceride-rich) [
Association of apolipoprotein B-containing lipoproteins and risk of myocardial infarction in individuals with and without atherosclerosis: distinguishing between particle concentration, type, and content.
]. The 2019 European Society of Cardiology/European Atherosclerosis Society Guidelines states that ApoB is a more accurate measure of cardiovascular risk and provides a better indication of the adequacy and efficacy of lipid-lowering therapy than LDL-C or non-high-density lipoprotein cholesterol (HDL-C) levels. The traditional model of atherosclerosis indicates that the mass of cholesterol within VLDL and LDL particles is the principal determinant of the mass of cholesterol that will be deposited within the arterial wall within ApoB, further driving atherogenesis. The newer ApoB particle model of atherogenesis proposes that the number of ApoB particles that enter and are trapped within the arterial wall is determined primarily by the number of ApoB particles within the arterial lumen [
]. Apart from cholesterol-rich lipoprotein, triglyceride-rich ApoB-containing remnant lipoproteins are also retained and modified within the arterial wall, leading to atherosclerosis [
The central role of arterial retention of cholesterol-rich apolipoprotein-B-containing lipoproteins in the pathogenesis of atherosclerosis: a triumph of simplicity.
Considering the potential evidence obtained from some large perspective cohorts and this meta-analysis for the use of RC in predicting MACE, it is reasonable to conclude that RC-lowering therapy can further reduce residual CVD risks. Statins increase the clearance of ApoB-containing lipoproteins and are therefore expected to reduce both LDL-C and RC levels. In the TNT trial, 80 mg/d of atorvastatin reduced RC to a greater extent than 10 mg/d of atorvastatin. Each SD percentage reduction in RC with atorvastatin resulted in a significantly lower risk of MACE (HR = 0.93, 95% CI 0.86–1.00) [
]. A combination therapy of statins with ezetimibe or a proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor to further lower RC could reduce residual CVD risks. There are several reports that have found that the combination of ezetimibe with statins reduces RC to a greater extent than using ezetimibe or statins alone [
]. Whether PCSK9 inhibitors alone or in combination with statins can reduce residual CVD risk and mortality requires further clinical trials for confirmation. There is a growing controversy about triglyceride-lowering therapy in combination with statins for further reducing residual CVD risks among high-risk patients [
]. In a previous study, pemafibrate, a potent and selective synthetic agonist of the PPARα nuclear receptor, which lowers plasma triglycerides by increasing the activity of lipoprotein lipase, was found to reduce triglyceride, VLDL-C, and RC levels in type 2 diabetes; however, it was not found to reduce CVD events as compared with a placebo during a 3.4-year follow-up [
]. One possible explanation for this is that it also leads to an increase in blood LDL-C; the median change from baseline % was 14 (−6.3 to 41.4) in the pemafibrate group as compared with 2.9 (−13.5 to 24.6) in the placebo group. Other confounding factors probably affect the composite endpoint, such as blood sugar and blood pressure control, age, and sex. In other non-diabetic patients with hypertriglyceridemia, triglyceride-lowering therapy using fibrates or icosapent ethyl has been found to reduce the risks of CVD events and mortality [
]. More clinical trials are needed to confirm the effect of triglyceride-lowering therapy on RC and CVD endpoints.
This meta-analysis has several potential limitations. First, the heterogeneity of the RC test methods may have led to unreliable results. Although we stratified the RC of the different tests, the high RC of each test was found to be associated with elevated CVD events after stratification, suggesting that the use of different RC methods to assess the risk of CVD is still clinically practical. The increased heterogeneity was also due to the different study designs (RCT, prospective, or retrospective cohorts) and the measured or calculated RC and LDL-C. Second, the subgroup analysis, which examined factors such as smoking status and HDL-C level, could not be re-analyzed for the risk of CVD or CHD with RC, because most of the included papers lacked these data. Future studies should include these data to further exclude those confounding factors. Third, we only found that increased RC was associated with increased CVD events, and we could not prove that they were causal. This needs to be further confirmed by a genome-wide association study (GWAS) and Mendelian randomization studies in the future.
In conclusion, this meta-analysis indicates that elevated RC is associated with increased risks of CVD events, CHD, stroke, cardiac death, and all-cause mortality. Each 1.0 mmol/L increase in RC was found to be associated with an increased risk of CVD events and CHD. Apart from conventional lipid parameters, RC should be of high concern to clinicians.
Financial support
This study was supported by Key Specialty of Plasma Purification in Shanghai Pudong Hospital (Zdzk2020-12) and Special Disease of Hyperlipidemia in Shanghai Pudong Hospital (Tszb2023-17).
Systematic review registration
PROSPERO CRD42022299183.
CRediT authorship contribution statement
Xiu Hong Yang: selected the articles, extracted, and, Formal analysis, interpreted the data and contributed to the writing of the final version of the manuscript, wrote the first draft of the manuscript. Bao Long Zhang: selected the articles, extracted, and, Formal analysis, wrote the first draft of the manuscript, interpreted the data and contributed to the writing of the final version of the manuscript. All authors agreed with the results and conclusions of this Article. Yun Cheng: selected the articles, extracted, and, Formal analysis, wrote the first draft of the manuscript. Shun Kun Fu: conceived and designed the study. Hui Min Jin: conceived and designed the study.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
All authors have approved the final version of the manuscript and have agreed to submit it to this journal. Zhang BL, Cheng Y and Yang XH contributed equally to this paper.
Appendix A. Supplementary data
The following are the Supplementary data to this article.
Extreme nonfasting remnant cholesterol vs extreme LDL cholesterol as contributors to cardiovascular disease and all-cause mortality in 90000 individuals from the general population.
Lipoprotein investigators collaborative (LIC) study group. Remnant lipoprotein cholesterol and incident coronary heart disease: the jackson heart and Framingham offspring cohort studies.
Association between remnant lipoprotein cholesterol, high-sensitivity C-reactive protein, and risk of atherosclerotic cardiovascular disease events in the Multi-Ethnic Study of Atherosclerosis (MESA).
Remnant cholesterol and its visit-to-visit variability predict cardiovascular outcomes in patients with type 2 diabetes: findings from the ACCORD cohort.
Directly measured vs. calculated remnant cholesterol identifies additional overlooked individuals in the general population at higher risk of myocardial infarction.
Arterial retention of remnant lipoproteins ex vivo is increased in insulin resistance because of increased arterial biglycan and production of cholesterol-rich atherogenic particles that can be improved by ezetimibe in the JCR:LA-cp rat.
Association of apolipoprotein B-containing lipoproteins and risk of myocardial infarction in individuals with and without atherosclerosis: distinguishing between particle concentration, type, and content.
The central role of arterial retention of cholesterol-rich apolipoprotein-B-containing lipoproteins in the pathogenesis of atherosclerosis: a triumph of simplicity.
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