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Apolipoprotein B is associated with CT-angiographic progression beyond low-density lipoprotein cholesterol and non-high-density lipoprotein cholesterol in patients with coronary artery disease



Accumulating evidence indicated that apolipoprotein B (apoB) was the principal lipid determinant of coronary artery disease (CAD). Nevertheless, the connection between apoB and angiographic progression of CAD remained undetermined.


Five hundred and forty-four CAD patients with twice coronary computed tomography angiography experiences were enrolled. The Gensini scoring system was used to assess angiographic progression. Incident angiographic progression was defined as an annual change rate of the Gensini score of > 1 point. The predictive efficacy of baseline apoB levels for angiographic progression was assessed using a receiver operating characteristic (ROC) curve. For comparative purposes, patients were categorized into three groups according to their baseline apoB tertiles. Furthermore, discordance analyses defined by the median were performed to assess the superiority of apoB over lipoprotein cholesterol in predicting angiographic progression of CAD.


Angiographic progression was observed in 184 patients (33.8%) during a follow-up period of 2.2-year. The area under the ROC curve was 0.565 (0.522–0.607, P = 0.013). The incidence of angiographic progression was elevated with increasing apoB tertile after adjusting for confounding factors [odds ratio (OR) for the medium apoB tertile: 1.92, 95% confidence interval (CI): 1.15–3.19, P = 0.012; OR for the high apoB tertile: 2.05, 95%CI:1.17–3.60, P = 0.013]. Additionally, discordance analyses showed that the higher apoB group had a significantly higher risk of CAD progression in the fully adjusted model (all P < 0.05).


ApoB could be used as an accurate and comprehensive indicator of angiographic progression in patients with CAD.


Although lowering of plasma low-density lipoprotein cholesterol (LDL-C) has been recognized to substantially decrease the risk of coronary artery disease (CAD), recent studies have shown a high residual cardiovascular risk after single LDL-C intervention [1,2,3]. Because the deposition and accumulation of LDL-C within the arterial lumen were the principal determinants of atherosclerosis, lowering LDL-C was strongly recommended by current guidelines [4, 5]. Though achieved guideline-recommended LDL-C goals with lipid lowering treatment, 22.7% of enrolled patients in the PROVE-IT 22 trial continued to experience major cardiovascular-related events during the 2-year follow-up [6]. Thus, a focus solely on LDL-C levels was insufficient as an optimal strategy for risk evaluation and management of CAD.

Apolipoprotein B (apoB) was the critical structural protein in the low-density lipoprotein (LDL) and triglyceride (TG)-rich lipoprotein [7]. Recently, Ference et al. demonstrated that lowering the amount of very low-density lipoprotein (VLDL) and LDL particles yielded a similar decrease in cardiovascular risk, indicating that both were equally atherogenic [8]. Thus, compared with the variable cholesterol content within them, the quantity of apoB-containing lipoprotein particles was considered a more comprehensive indicator of atherogenic risk [9]. Indeed, evidence from Mendelian randomization (MR) and discordance analyses revealed that apoB was a more precise biomarker in risk estimation and medication guidance compared with LDL-C and non-high-density lipoprotein cholesterol (non-HDL-C) alone [10, 11]. The effectiveness of apoB propelled its recommendation for risk assessment of CAD in ESC/EAS 2019 guidelines [5]. Notwithstanding its significance, the large data gap between apoB and CAD progression impeded its application. Furthermore, the advantage of apoB over usual biomarkers in estimating the angiographic progression (AP) of CAD remained debatable.

Hence, the current study aimed to elucidate the relation of apoB with AP in individuals diagnosed with CAD using coronary computed tomography angiography (CTA). A discordance analysis was performed to evaluate the effectiveness of apoB against other biomarkers in forecasting the possibility of AP.



Patients who underwent a series of non-invasive coronary angiography assessments of coronary CTA between January 2009 and December 2015 at the Third Affiliated Hospital, Sun Yet-sen University, were retrospectively reviewed. Initially, 1242 patients received coronary CTA twice with an interval of ≥ 6 months because of angina-like symptoms, abnormal ST-T segment changes on electrocardiography, abnormal regional wall motion on echocardiography, and routine monitoring to seek anatomical progression. Of these, patients with no CAD (recognized as having no prior reported CAD and no luminal stenosis on initial coronary CTA) were excluded [12]. Patients who had undergone coronary revascularization with interventional therapy or surgery were considered ineligible. Patients with malignancy or severe dysfunction of liver and kidney [estimated glomerular filtration rate (eGFR) < 30 mL/minutes/1.73m2, or those with hemodialysis or peritoneal dialysis] were also eliminated from the study. Finally, 544 patients were analyzed (as shown in Fig. 1). Among them, 72 (13.2%) patients received repeated CTA in 1-year because of new or recurrent ischemic symptoms, while the others underwent repeated CTA for routine follow-up during the 2.5-year (interquartile range: 1.7–3.6).

Fig. 1
figure 1

Flow chart of the present study. CTA, computed tomography angiography; CAD, coronary artery disease

Anthropometric and risk factor measurements

Information on demographics, height, weight, blood pressure (BP), smoking habits, case history and drug usage was collected during the initial coronary CTA examination. Body mass index (BMI) was obtained from weight/height squared (kg/m2). Hypertension (HTN) definition was adopted from a previous study [13]. Diagnostic criteria for diabetes mellitus (DM) were also adopted from a previous study [14]. Participants who smoked ≥ 1 cigarette per day within 1-year prior to the present study were considered current smokers.

Clinical Chemistry Parameters

Venous blood was collected after fasting for 12 h and measured in the laboratory. Baseline lipid profiles, fasting plasma glucose (FPG), uric acid (UA), liver function, and renal function were assessed using a biochemical analyzer (Hitachi 7600, Tokyo, Japan). Direct methods were used to detect LDL-C concentrations, as well as high-density lipoprotein cholesterol (HDL-C). Total cholesterol (TC) as well as TG levels were analyzed by enzyme colorimetry. Lipoprotein(a) levels were assessed using latex immunoturbidimetry. ApoB concentrations were detected using immunoturbidimetry (assay kit, cat. No CH0101158, Tokyo, Japan). Non-HDL-C was defined as TC level minus HDL-C level.

Non-invasive coronary angiography assessments and Scoring

Coronary CTA was performed using a 320-row multi-detector computed tomography (TOSHIBA, Tokyo, Japan) based on the recommendations in previous study [15]. The standard operating procedure was pre-fixed as previously described [16]. All images were reconstructed by an experienced cardiac radiologist (TOSHIBA, Tokyo, Japan) according to the Society of Cardiovascular CT (SCCT) guidelines [15]. CAD was diagnosed by initial coronary CTA examination and graded as no CAD (recognized as having no prior reported CAD and no luminal stenosis), non-obstructive CAD (defined as 1 − 49% of luminal diameter stenosis in an epicardial coronary artery), or obstructive CAD (considered as ≥ 50% stenosis) by visual evaluation [12].

The lesion of the coronary artery was scored using the Gensini score (GS) and considering the importance of the coronary artery, location of the stenosis, and extent of luminal stenosis [17]. The calculation was performed by two cardiologists, and inconsistencies were determined by a third cardiologist. Incident AP was defined as an annual change rate of GS > 1 point, as described in a previous study [18]. Otherwise, those with the annual change rate of GS ≤ 1 point were allocated into the non-progression group.

Statistical analysis

SPSS 23.0 software for Windows (IBM Corp., Armonk, NY, USA) was applied for data analyses. Normal and skewed distributed data were displayed as mean ± standard deviation (SD) and interquartile range, respectively. Categorical variables were showed as frequencies (percentages). Between-group differences were carried out using X2 test, analysis of variance, or Kruskal-wallis rank test. ApoB performance in predicting progression was evaluated using the receiver operating characteristic (ROC) curve in Medcalc 20.0.3 software (MedCalc, Ostend, Belgium). For logistic regression analysis, patients were assigned to the low, the medium, and the high group according to baseline apoB and LDL-C tertiles. Two logistic regression models with different levels of adjustment were established for the relationship between incident AP and baseline levels of apoB and LDL-C, using the low apoB and LDL-C group as reference, respectively. Significant variables (P < 0.1) in the univariate logistic regression analysis were selected for the models. Model 1 was adjusted for baseline age, BMI, sex, smoking status, HTN, DM, and obstructive CAD. Model 2 was additionally adjusted for hemoglobin A1c (HbA1c), HDL-C, lipoprotein(a), initial GS, statins, and β blocker used at baseline. Owing to its clinical importance, baseline LDL-C level was additionally included when adjusting for confounding factors in Model 2 to assess the performance of baseline apoB in predicting AP.

To further evaluate whether baseline apoB levels were effective than baseline LDL-C and non-HDL-C levels in predicting AP, discordance analyses were performed as described in previous study [19]. Median cutoff points were chosen to define discordance: apoB below (<) the median and LDL-C at or above (≥) the median, or vice versa. In brief, participants were categorized into four groups according to their median values: low apoB/low LDL-C, low apoB/high LDL-C, high apoB/low LDL-C, and high apoB/high LDL-C. Similarly, four concordant/discordant categorizes of apoB and non-HDL-C were created. The characteristics of these categories were analyzed. Using the same fully adjusted model (Model2), the association between the concordant/discordant groups of apoB and LDL-C or non-HDL-C and incident AP was evaluated, using the low/low group as a reference. P < 0.05 was defined statistically significant.


The average age of the patients at baseline was 64.4 years: 56.4% were male and 43.6% were females. Overall, 72.6% had HTN, 49.1% had DM, 50.0% had obstructive CAD, 31.4% were current smokers, and 85.7% had received statins therapy at baseline. The demographic and clinical comorbidities, metabolic parameters, and medications of patients according to tertiles of baseline apoB were shown in Table 1. Patients who underwent repeated CTA within 1-year were comparable among the groups (14.4%, 13.2%, and 12.1% for the low, the medium, and the high apoB group, respectively; P = 0.803). Patients with high apoB levels were younger, and had more severe metabolic abnormalities, including higher baseline BMI, TC, non-HDL-C, UA, FPG, HbA1c, TG, and LDL-C, than those with low or medium apoB levels. However, HDL-C concentrations declined with elevated apoB tertiles.

Table 1 Baseline characteristics of patients categorized by apoB tertiles

Discordance was defined according to the median values. The median values at baseline were 1.00 g/L for apoB, 3.02 mmol/L for LDL-C, and 3.76mmol/L for non-HDL-C. Relative to LDL-C, the prevalence of low apoB/high LDL-C and high apoB/low LDL-C levels was 15.1% and 16.7%, respectively. Age, BMI, creatinine, eGFR, UA, TC, TG, HDL-C, non-HDL-C and lipoprotein(a) levels were significantly different between the four concordance/discordance groups, as listed in Table 2. Relative to non-HDL-C, the proportions of patients with low apoB/ high non-HDL-C and high apoB/low non-HDL-C levels were 12.1% and 13.8%, respectively. Significant differences attributed to age, BMI, prevalence of DM, smoking status, UA levels, and lipid profiles were observed among the four groups and were listed in Supplementary Table 1.

Table 2 Baseline characteristics in concordant and discordant groups by medians (apoB and LDL-C)

ROC curve was conducted to identify the efficacy of baseline apoB levels in predicting AP. The area under the ROC curve was 0.565 (0.522–0.607, P = 0.013). (Fig. 2)

Fig. 2
figure 2

The predictive efficacy of baseline apoB levels for angiographic progression in patients with CAD. apoB, apolipoprotein B; CAD, coronary artery disease; AUC, area under the curve

During the 2.2-year (interquartile range: 1.4–3.4) of follow-up, AP was found in 184 patients (33.8%). The relations of baseline apoB as well as LDL-C tertiles with AP were analyzed using multivariate logistic regression (Table 3). Compared with the low level of apoB group (reference), the odds ratio (OR) [95% confidence interval (CI)] of AP for the medium and high level of apoB was 1.42 (0.90–2.22) and 1.75 (1.12–2.72), respectively. The adjusted OR (95% CI) of the medium and high level of apoB was 1.83 (1.14–2.96) and 2.23 (1.38–3.61), respectively, for the risk of AP (all P < 0.05) in Model 1. After additionally adjusting for HbA1c, HDL-C, lipoprotein(a), initial GS, statins, and β blocker used at baseline in Model 2, the associations remained statistically significant (OR for the medium tertile: 1.93, 95%CI: 1.18–3.16, P = 0.009; OR for the high tertile:2.08, 95%CI: 1.27–3.43, P = 0.004). However, the results remained the same even after adjustment of baseline LDL-C in Model 2 (OR for the medium tertile: 1.92, 95%CI: 1.15–3.19, and P = 0.012; OR for the high tertile:2.05, 95%CI: 1.17–3.60, and P = 0.013). When stratified by baseline LDL-C tertile, elevated LDL-C levels showed no correlation with the risk of progression.

Table 3 ApoB levels, LDL-C levels, and concordance/discordance between ApoB and LDL-C or non-HDL-C categories in relation to risk of AP

Using the low apoB/low LDL-C group as a reference in the logistic regression model, discordance analysis was performed to evaluate the effectiveness of baseline apoB and LDL-C. Results were listed in Table 3., Compared with the reference in the model with full adjustments (Model 2), the adjusted OR for AP of high apoB/low LDL-C group and high apoB/high LDL-C group was 2.05 (95% CI:1.11–3.78, P = 0.022) and 2.32 (95% CI:1.42–3.81, P = 0.001), respectively. Contrastingly, in the low apoB/high LDL-C group, association to AP was not observed (OR:1.72, 95% CI: 0.94–3.16, P = 0.079). Similar relationships were explored across the concordance and discordance between apoB and non-HDL-C levels. Patients in the high apoB/low non-HDL-C and high apoB/high non-HDL-C groups were significantly correlated with AP (all P < 0.05), as opposed to patients in the low apoB/high non-HDL-C group, who had no correlation with AP. Results were displayed in Fig. 3.

Fig. 3
figure 3

Multivariable-adjusted odds ratios of angiographic progression by concordant versus discordant groups of apoB and LDL-C or non-HDL-C. apoB, apolipoprotein B; LDL-C, low-density lipoprotein cholesterol; non-HDL-C, non-high-density lipoprotein cholesterol; CI, confidence interval


This study suggested that incremental apoB levels were positively correlated with the incidence of AP in CAD patients apart from traditional risk factors and statins treatment. In the model with full adjustments, discordance analyses showed a significantly higher risk of AP in the higher apoB groups regardless of non-HDL-C or LDL-C levels. Thus, apoB was a more accurate and comprehensive indicator of AP than non-HDL-C and LDL-C in CAD patients.

Previously, LDL-C and VLDL-C were identified as biomarkers for cardiovascular risk and treatment targets, however, recent studies revealed their insufficiency [20, 21]. Many individuals with normal or guideline-recommended LDL-C levels experienced cardiovascular events or progression of atherosclerosis [22]. Recent MR studies determined that the atherogenic risk from a VLDL particle was similar to that from an LDL particle. Because of dynamic lipid metabolic processes and the inability of plasma LDL-C and TG levels to reflect the actual number of LDL and VLDL particles [8, 23], neither LDL-C nor TG were perfect indicators of cardiovascular risk.

Recently, mounting evidence showed that the quantity of apoB particles that entered and were retained within the arterial wall was the principal determinant of atherosclerosis [7, 9]. Though cholesterol deposition within the arterial lumen was regarded as a classic characteristic of atherosclerosis, it could not enter the arterial wall unless it was carried by apoB particles [7]. Smaller cholesterol-poor apoB particles could be easily retained within the arterial wall than larger cholesterol-rich ones because of their high affinity for glycosaminoglycans, whereas more cholesterol was deposited when larger cholesterol-rich apoB particles were retained. The net result indicated that each apoB particle was proatherogenic [24]. Furthermore, phospholipids, one of the components of apoB particles, were strong proatherogenic factors associated with poor prognosis in an oxidized state [25]. Thus, compared to LDL-C, apoB particles integrated more proatherogenic risk factors in most cases. Because each proatherogenic apoB particle contained only one molecule of apoB, apoB levels could provide a measure of the total levels of proatherogenic lipoprotein particles [26].

Growing evidence illustrated the importance of apoB in the prevalence of CAD [25, 27]; however, its predictive efficacy for CAD progression remained unclear. Richardson et al. performed a genome-wide association study of LDL-C, apoB, and TG in the UK Biobank and validated the associations using a second database, CARDIoGRAMplusC4D. When evaluated individually using MR, LDL-C, apoB, and TG levels were positively correlated with the incidence of CAD. Nevertheless, only apoB retained a robust positive association with multivariable MR [10]. Similarly, Zuber et al. confirmed apoB as the principal lipid detriment of CAD in multivariable MR models [28]. However, few real-world evidence studies assessed the relationship between apoB levels and progression of coronary atherosclerosis. Ohwada et al. identified that apoB levels had an association with the necrotic core volumes in culprit coronary artery lesions and plaque advancement in 115 patients with stable CAD [29]. Subsequently, Kim et al. found a dose-response relationship between baseline apoB levels and coronary artery calcification progression [30]. To further explore the effectiveness of apoB in secondary prevention, a retrospective study including 544 patients with CAD was conducted using a coronary CTA. Statins therapy was initially administered to 85.7% of the patients. In this present study, it was observed that the incidence of AP increased with an increasing number of apoB tertiles during follow-up.

However, there was no association between the progression risk and elevated LDL-C levels while receiving statins therapy, which was in line with a previous study conducted by Yao et al. [31]. They concluded that higher apoB levels, rather than LDL-C levels were significantly correlated with new-onset CAD in participants who received statins therapy. Furthermore, Ference et al. suggested that the absolute reduction in the amount of apoB-containing lipoprotein particles, rather than the expected per-unit change in LDL-C, was a superior marker for predicting the cardiovascular events risk [32]. Moreover, Baik. et al. showed that apoB was positively correlated with symptomatic intracranial atherosclerotic stenosis, regardless of pre-admission statins use, whereas LDL-C was not, indicating apoB may be superior to LDL-C for residual risk evaluation under statins therapy [33]. Generally, LDL-C and apoB levels had closely correlation as well as similar information about atherogenic risk. When they became discordant, the predictive values of atherogenic risk differentiated. Under statins treatment, the LDL-C concentration may underestimate the residual atherogenic risk. However, apoB levels could integrate more atherogenic risk factors (including VLDL and its remnants) and serve as a comprehensive biomarker for risk evaluation. The present study identified that apoB levels could be used to monitor the progression of CAD in secondary prevention, even under statins treatment.

In this study, median values defined discordance analyses demonstrated the advantage of apoB in predicting AP. Regardless of the LDL-C/non-HDL-C levels, elevated apoB levels were associated with AP risk in patients with CAD. This was consistent with results obtained by Johannesen et al., who also employed medians to define the discordance analysis. They found that elevated apoB levels were correlated with all-cause mortality regardless of LDL-C and non-HDL-C levels [34]. Lawler et al. conducted a discordance analysis using 27,533 apparently healthy women to identify whether the count of apoB particles or the cholesterol amount could predict incident CAD risk [35]. Compared with non-HDL-C, they found that apoB levels had a stronger relationship with CAD risk. Overall, apoB could be a potential biomarker for cardiovascular risk prediction for both primary and secondary preventions. Application of lipidomic technologies could provide deeper insight into the correlation between CAD progression and the lipid composition of atherogenic particles [36]. Therefore, further studies are required to validate these findings using a lipidomic approach to identify more precise components for monitoring and guiding individualized therapy.

ApoB was considered not only an atherogenic biomarker but also a therapeutic target. Recent literatures supported the hypothesis that reducing apoB levels led to a decrease in risk of cardiovascular diseases [9]. The higher the concentration of autoantibodies against apoB in the plasma, the lower the rate of coronary atherosclerosis-related diseases [37]. Khan, et al. found that an absolute decrease in apoB correlated with a decrease in cardiovascular events in a meta-analysis study [38]. A more recent study by Hagström, et al. demonstrated that in patients with recent acute coronary syndrome, a higher baseline apoB level was associated with a higher incidence of major adverse cardiovascular events (MACE). Under alirocumab treatment, lower apoB levels resulted in a lower risk of MACE, even with guideline-recommended LDL-C or non-HDL-C levels [39]. Thus, lowering apoB levels with targeted therapy was a potential therapeutic strategy for CAD and further study employing small compounds or monoclonal antibodies screening are warranted.

Study strengths and Limitations

This retrospective longitudinal study included 544 patients with a relatively short follow-up period. With strict statistical adjustment, this real-world evidence study revealed that apoB was an effective biomarker for predicting disease progression in secondary prevention of CAD. The finding provided additional evidence to support the role and effectiveness of apoB in identifying lipid atherogenic risks and guiding individualized therapy in clinical practice.

Nonetheless, the study had some limitations. First, potential residual confounding factors were difficult to exclude because this was a retrospective observational study. Second, although the use of statins at baseline was adjusted for, information on adherence and changes in intensity dosage during follow-up were not confirmed. Third, the present study was a small sample size study with a relatively short follow-up period.


A positive association between high apoB levels and the incidence of AP in patients with CAD was observed after adjusting for LDL-C or non-HDL-C levels. Therefore, apoB could be used as an accurate and effective biomarker for risk evaluation of patients with CAD in secondary prevention. This study added to the literature on the role and effectiveness of apoB in identifying the lipid atherogenic risks. The importance of apoB particles in the initiation and progression of CAD will gradually be appreciated, and routine measurement of apoB should be advised to guide risk stratification and therapy in clinical practice.

Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.



Apolipoprotein B


Coronary artery disease


Low-density lipoprotein cholesterol


The pravastatin or atorvastatin evaluation and infection therapy


Low-density lipoprotein




Very low-density lipoprotein


Mendelian randomization


Non-high-density lipoprotein cholesterol


European society of cariology


European atherosclerosis society


Angiographic progression


Computed tomography angiography


Estimated glomerular filtration rate


Blood pressure


Body mass index




Diabetes mellitus


Fasting plasma glucose


Uric acid


Total cholesterol


High-density lipoprotein cholesterol


The society of cardiovascular computed tomography


Gensini score


Standard deviation


Receiver operating characteristic


Hemoglobin A1c


Odds ratio


Confidence interval


Major adverse cardiovascular events


  1. Khera AV, Kathiresan S. Genetics of coronary artery disease: discovery, biology and clinical translation. Nat Rev Genet. 2017;18(6):331–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Hoogeveen RC, Ballantyne CM. Residual Cardiovascular risk at low LDL: remnants, lipoprotein(a), and inflammation. Clin Chem. 2021;67(1):143–53.

    Article  PubMed  Google Scholar 

  3. Jang AY, Lim S, Jo SH, Han SH, Koh KK. New Trends in Dyslipidemia Treatment. Circ J. 2021;85(6):759–68.

    Article  CAS  PubMed  Google Scholar 

  4. Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA et al. /ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;139(25):e1082-e143.

  5. Zeitouni M, Sabouret P, Kerneis M, Silvain J, Collet JP, Bruckert E, et al. 2019 ESC/EAS guidelines for management of dyslipidaemia: strengths and limitations. Eur Heart J Cardiovasc Pharmacother. 2021;7(4):324–33.

    Article  PubMed  Google Scholar 

  6. Cannon CP, Braunwald E, McCabe CH, Rader DJ, Rouleau JL, Belder R, et al. Intensive versus moderate lipid lowering with statins after acute coronary syndromes. N Engl J Med. 2004;350(15):1495–504.

    Article  CAS  PubMed  Google Scholar 

  7. Sniderman AD, Thanassoulis G, Glavinovic T, Navar AM, Pencina M, Catapano A, et al. Apolipoprotein B particles and Cardiovascular Disease: a narrative review. JAMA Cardiol. 2019;4(12):1287–95.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Ference BA, Kastelein JJP, Ray KK, Ginsberg HN, Chapman MJ, Packard CJ, et al. Association of triglyceride-lowering LPL variants and LDL-C-Lowering LDLR variants with risk of Coronary Heart Disease. JAMA. 2019;321(4):364–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Behbodikhah J, Ahmed S, Elyasi A, Kasselman LJ, De Leon J, Glass AD et al. Apolipoprotein B and Cardiovascular Disease: Biomarker and potential therapeutic target. Metabolites. 2021;11(10).

  10. Richardson TG, Sanderson E, Palmer TM, Ala-Korpela M, Ference BA, Davey Smith G, et al. Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: a multivariable mendelian randomisation analysis. PLoS Med. 2020;17(3):e1003062.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Su X, Cai X, Pan Y, Sun J, Jing J, Wang M, et al. Discordance of apolipoprotein B with low-density lipoprotein cholesterol or non-high-density lipoprotein cholesterol and coronary atherosclerosis. Eur J Prev Cardiol. 2022;29(18):2349–58.

    Article  PubMed  Google Scholar 

  12. van Rosendael AR, Bax AM, Smit JM, van den Hoogen IJ, Ma X, Al’Aref S, et al. Clinical risk factors and atherosclerotic plaque extent to define risk for major events in patients without obstructive coronary artery disease: the long-term coronary computed tomography angiography CONFIRM registry. Eur Heart J Cardiovasc Imaging. 2020;21(5):479–88.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Cuspidi C, Tadic M, Grassi G, Mancia G. Treatment of hypertension: the ESH/ESC guidelines recommendations. Pharmacol Res. 2018;128:315–21.

    Article  PubMed  Google Scholar 

  14. American Diabetes A. 2. Classification and diagnosis of diabetes: Standards of Medical Care in Diabetes-2019. Diabetes Care. 2019;42(Suppl 1):13–S28.

    Article  Google Scholar 

  15. Abbara S, Blanke P, Maroules CD, Cheezum M, Choi AD, Han BK, et al. SCCT guidelines for the performance and acquisition of coronary computed tomographic angiography: a report of the society of Cardiovascular computed Tomography Guidelines Committee: endorsed by the North American Society for Cardiovascular Imaging (NASCI). J Cardiovasc Comput Tomogr. 2016;10(6):435–49.

    Article  PubMed  Google Scholar 

  16. Shui X, Chen Z, Wen Z, Tang L, Tang W, Liao Y, et al. Association of Atherogenic Index of plasma with angiographic progression in patients with suspected coronary artery disease. Angiology. 2022;73(10):927–35.

    Article  CAS  PubMed  Google Scholar 

  17. Xu L, Yan X, Tang Z, Feng B. Association between circulating oxidized OxLDL/LDL-C ratio and the severity of coronary atherosclerosis, along with other emerging biomarkers of cardiovascular disease in patients with type 2 diabetes. Diabetes Res Clin Pract. 2022;191:110040.

    Article  CAS  PubMed  Google Scholar 

  18. Patel RS, Su S, Neeland IJ, Ahuja A, Veledar E, Zhao J, et al. The chromosome 9p21 risk locus is associated with angiographic severity and progression of coronary artery disease. Eur Heart J. 2010;31(24):3017–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Wilkins JT, Li RC, Sniderman A, Chan C, Lloyd-Jones DM. Discordance between apolipoprotein B and LDL-Cholesterol in young adults predicts coronary artery calcification: the CARDIA Study. J Am Coll Cardiol. 2016;67(2):193–201.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Shaya GE, Leucker TM, Jones SR, Martin SS, Toth PP. Coronary heart disease risk: low-density lipoprotein and beyond. Trends Cardiovasc Med. 2022;32(4):181–94.

    Article  CAS  PubMed  Google Scholar 

  21. Sandesara PB, Virani SS, Fazio S, Shapiro MD. The forgotten lipids: triglycerides, remnant cholesterol, and atherosclerotic Cardiovascular Disease Risk. Endocr Rev. 2019;40(2):537–57.

    Article  PubMed  Google Scholar 

  22. Sinning D, Landmesser U. Is there a need to revise goals in the management of Dyslipidemias? Curr Cardiol Rep. 2019;21(6):51.

    Article  PubMed  Google Scholar 

  23. Stock J. Triglycerides and cardiovascular risk: apolipoprotein B holds the key. Atherosclerosis. 2019;284:221–2.

    Article  CAS  PubMed  Google Scholar 

  24. Glavinovic T, Sniderman AD. Apolipoprotein B: the Rosetta Stone of lipidology. Curr Opin Endocrinol Diabetes Obes. 2021;28(2):90–6.

    Article  CAS  PubMed  Google Scholar 

  25. Gilliland TC, Liu Y, Mohebi R, Miksenas H, Haidermota S, Wong M, et al. Lipoprotein(a), oxidized phospholipids, and coronary artery Disease Severity and Outcomes. J Am Coll Cardiol. 2023;81(18):1780–92.

    Article  CAS  PubMed  Google Scholar 

  26. White-Al Habeeb NMA, Higgins V, Wolska A, Delaney SR, Remaley AT, Beriault DR. The Present and Future of lipid testing in Cardiovascular Risk Assessment. Clin Chem. 2023;69(5):456–69.

    Article  PubMed  Google Scholar 

  27. Sniderman A, Langlois M, Cobbaert C. Update on apolipoprotein B. Curr Opin Lipidol. 2021;32(4):226–30.

    Article  CAS  PubMed  Google Scholar 

  28. Zuber V, Gill D, Ala-Korpela M, Langenberg C, Butterworth A, Bottolo L, et al. High-throughput multivariable mendelian randomization analysis prioritizes apolipoprotein B as key lipid risk factor for coronary artery disease. Int J Epidemiol. 2021;50(3):893–901.

    Article  PubMed  Google Scholar 

  29. Ohwada T, Sakamoto T, Kanno Y, Yokokawa S, Amami K, Nakazato K, et al. Apolipoprotein B correlates with intra-plaque necrotic core volume in stable coronary artery disease. PLoS ONE. 2019;14(2):e0212539.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Kim CW, Hong S, Chang Y, Lee JA, Shin H, Ryu S. Discordance between apolipoprotein B and low-density lipoprotein cholesterol and progression of coronary artery calcification in Middle Age. Circ J. 2021;85(6):900–7.

    Article  CAS  PubMed  Google Scholar 

  31. Yao T, Lu W, Ke J, Zhang H, Zhao X, Song B, et al. Residual risk of coronary atherosclerotic heart disease and severity of coronary atherosclerosis assessed by ApoB and LDL-C in participants with statin treatment: a retrospective cohort study. Front Endocrinol (Lausanne). 2022;13:865863.

    Article  PubMed  Google Scholar 

  32. Ference BA, Kastelein JJP, Ginsberg HN, Chapman MJ, Nicholls SJ, Ray KK, et al. Association of genetic variants related to CETP inhibitors and statins with lipoprotein levels and Cardiovascular Risk. JAMA. 2017;318(10):947–56.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Baik M, Nam HS, Heo JH, Lee HS, Kim YD. Differential association between apolipoprotein B and LDL cholesterol and cerebral atherosclerosis according to pre-stroke statin use. Atherosclerosis. 2023;371:14–20.

    Article  CAS  PubMed  Google Scholar 

  34. Johannesen CDL, Mortensen MB, Langsted A, Nordestgaard BG. Apolipoprotein B and Non-HDL cholesterol better reflect residual risk than LDL cholesterol in statin-treated patients. J Am Coll Cardiol. 2021;77(11):1439–50.

    Article  CAS  PubMed  Google Scholar 

  35. Lawler PR, Akinkuolie AO, Ridker PM, Sniderman AD, Buring JE, Glynn RJ, et al. Discordance between circulating atherogenic cholesterol Mass and Lipoprotein particle concentration in relation to future coronary events in women. Clin Chem. 2017;63(4):870–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Kostara CE, Papathanasiou A, Psychogios N, Cung MT, Elisaf MS, Goudevenos J, et al. NMR-based lipidomic analysis of blood lipoproteins differentiates the progression of coronary heart disease. J Proteome Res. 2014;13(5):2585–98.

    Article  CAS  PubMed  Google Scholar 

  37. Sjogren P, Fredrikson GN, Samnegard A, Ericsson CG, Ohrvik J, Fisher RM, et al. High plasma concentrations of autoantibodies against native peptide 210 of apoB-100 are related to less coronary atherosclerosis and lower risk of myocardial infarction. Eur Heart J. 2008;29(18):2218–26.

    Article  PubMed  Google Scholar 

  38. Khan SU, Khan MU, Valavoor S, Khan MS, Okunrintemi V, Mamas MA, et al. Association of lowering apolipoprotein B with cardiovascular outcomes across various lipid-lowering therapies: systematic review and meta-analysis of trials. Eur J Prev Cardiol. 2020;27(12):1255–68.

    Article  PubMed  Google Scholar 

  39. Hagstrom E, Steg PG, Szarek M, Bhatt DL, Bittner VA, Danchin N, et al. Apolipoprotein B, residual Cardiovascular Risk after Acute Coronary Syndrome, and Effects of Alirocumab. Circulation. 2022;146(9):657–72.

    Article  PubMed  PubMed Central  Google Scholar 

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All authors express sincere thanks to Chenshu Liu for his help in writing assistance.


This work was supported by the Natural Science Foundation of Guangdong Province (Grant No.2020A1515010362) to Zhen Wu.

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Conception and design the study: L C and Z W; Acquisition of data: LL T, WY T; Analysis and interpretation of data: RM D, ZF C, and X S; Article drafting: X S; Revising the article: ZQ W;All authors have read and approved the final version submitted for publication.

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Correspondence to Zhen Wu or Lin Chen.

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The present study was in accordance with the ethics standards established by the Declaration of Helsinki. The Ethics Committee of The Third Affiliated Hospital, Sun Yat-sen University approved the present study protocol and informed consents were gained from all patients.

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Shui, X., Wen, Z., Dong, R. et al. Apolipoprotein B is associated with CT-angiographic progression beyond low-density lipoprotein cholesterol and non-high-density lipoprotein cholesterol in patients with coronary artery disease. Lipids Health Dis 22, 125 (2023).

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