Association between lipoprotein(a) and atherosclerosis with different diabetic status: a cross-sectional study in a Chinese population

Introduction

Cardiovascular disease (CVD) remains one of the leading causes of death worldwide, with atherosclerosis serving as the primary underlying factor, contributing to the development of CVD and stroke in most cases (1,2). Coronary artery calcium (CAC) score, carotid intima-media thickness (cIMT) are surrogate markers of subclinical atherosclerosis. CAC and cIMT can be used to identify atherosclerosis before the manifestation of clinical symptoms and are closely associated with the incidence and mortality of atherosclerotic CVD (ASCVDs) (3,4). A CAC score ≥100 has been associated with increased 10-year ASCVD incidence (5). Additionally, the rupture of vulnerable carotid plaques is involved in the development of arterial embolism and ischemic stroke and is recognized as a noninvasive biomarker of atherosclerotic disease, even in the asymptomatic stage (6,7). Therefore, it is important to accurately identify the risk factors of coronary calcification and carotid arteriopathy to prevent and assess CVDs and stroke.

Lipoprotein(a) [Lp(a)] is a low-density lipoprotein-like particle characterized by the covalent binding of an apoB-100 molecule to apo(a). Elevated Lp(a) levels may promote atherosclerosis through mechanisms such as enhanced oxidative stress, interference with coagulation and fibrinolytic systems, and mediation of the release of inflammatory cells and factors (8). As confirmed by robust evidence from epidemiology, genome-wide association studies, and Mendelian randomization, there is a causal association between elevated Lp(a) levels and an increased risks of coronary artery disease (CAD) and coronary atherosclerosis. According to the “A Beijing Heart Society Expert Scientific Statement”, an Lp(a) level greater than 30 mg/dL is considered a risk-enhancing factor in the evaluation of CVD risk (9,10). However, the absence of standardized quantitative methods, variations in expression across races and ethnicities, and limited availability of authorized treatment guidelines and therapeutic options for elevated Lp(a) levels have constrained routine assessment and utilization of Lp(a) levels in clinical practice (11-14).

Diabetes mellitus (DM) is a complex metabolic disorder marked by insufficient insulin production or resistance to its effects. Prediabetes, which includes impaired glucose tolerance and fasting glucose abnormalities, is a precursor to DM (15,16). The “China Chronic Disease and Risk Factors Monitoring Report” highlights an increase in diabetes prevalence, from 10.9% in 2013 to 12.4% in 2018, while prediabetes rates also rose from 35.7% to 38.1% (17). Numerous studies have established a positive correlation between DM and prediabetes, the risk of CVD, and overall mortality (18-20). According to the 2019 European Society of Cardiology (ESC) guidelines on diabetes, prediabetes, and CVD, maintaining low-density lipoprotein cholesterol (LDL-C) levels below 1.4 mmol/L is recommended for patients with diabetes and ASCVD. Although reducing LDL-C can improve cardiovascular outcomes, patients with DM continue to face a higher absolute risk of cardiovascular events compared to those with normal glucose levels (21). This suggests that diabetes may affect cardiovascular health through mechanisms beyond LDL-C levels, warranting further investigation into how different diabetic states interact with other cardiovascular risk factors.

With the advent of Lp(a)-lowering medicines, a more effective targeted approach that extends beyond current risk-stratification paradigms should be established to implement safer therapies, particularly for patients with high Lp(a) levels. One strategy is to integrate Lp(a) testing with established CVD risks assessment tools, such as diabetic status (22-25). This strategy can improve the effectiveness of risk discrimination and generate a dual risk stratification system for a more precise CVD risk categorization. Nevertheless, few studies have reported consistent findings about the concurrent evaluation of these risk markers. Therefore, this study aimed to examine the independent and joint association of Lp(a) levels and diabetic status with subclinical atherosclerosis in the Chinese population. We hypothesized that elevated Lp(a) levels and DM are independently and jointly associated with subclinical atherosclerosis. We present this article in accordance with the STROBE reporting checklist (available at https://cdt.amegroups.com/article/view/10.21037/cdt-24-410/rc).

Methods

Study population

Overall, 1,066 patients presenting with stable chest pain underwent coronary computed tomography angiography (CCTA) and carotid ultrasonography at the First Affiliated Hospital of Chongqing Medical University, between June 2018 and February 2022. The inclusion and exclusion criteria were as follows: (I) patients with stable chest pain underwent CCTA and carotid ultrasound within 7 days to evaluate CAC and carotid arteriopathy, with images of sufficient quality for accurate analysis. (II) Patients who had no prior diagnosis or confirmed cases of CVD, including CAD, cerebrovascular diseases, severe arrhythmias, valvular heart disease, and New York Heart Association (NYHA) class III or above heart failure; or any related treatments (e.g., revascularization, pacemaker or defibrillator implantation, valve replacement, and nitroglycerin therapy). CAD was defined as ≥50% stenosis in at least one coronary artery on coronary angiography. Cerebrovascular disease was defined by the presence of acute ischemic or hemorrhagic stroke confirmed using neuroimaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI). Heart failure (NYHA class III or higher) is defined by the NYHA classification in which patients exhibit marked limitations in physical activity and experience symptoms of heart failure even with minimal exertion, as diagnosed via clinical evaluation and echocardiography (26). Severe arrhythmia was defined as the presence of significant arrhythmias, including conditions as ventricular tachycardia or atrial fibrillation with rapid ventricular response, confirmed through 24 h Holter monitoring or event recording. Valvular heart disease was defined by echocardiographic evaluation showing significant valvular stenosis or regurgitation, impacting cardiac function and requiring clinical intervention. (III) Secondary conditions or medication use that may lead to potential fluctuations in Lp(a) levels and blood glucose including severe acute infection, fever, cold, and other symptoms within 2 weeks, or taking antibiotics, malignant tumors (and undertreatment), liver cirrhosis, estimated glomerular filtration rate (eGFR) <30 mL/min/1.73 m², or a prior diagnosis of end-stage renal diseases (ESRDs) (and undergoing hemodialysis). (IV) Additionally, considering that Lp(a) levels are genetically controlled and racial and ethnic differences, patients were required to present ID card proving they were ≥18 years old, of Han Chinese ethnicity, and residents of Chongqing, China for more than 6 months. (V) Complete clinical data and biochemical indicators were collected using questionnaires in the electronic medical record system. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study protocol was approved by the Ethical Review Board of the First Affiliated Hospital of Chongqing Medical University (No. K2023-575) and individual consent for this retrospective analysis was waived.

Clinical and laboratory values

Following standardized protocols and laboratory procedures, data on hypertension, diabetes, hyperlipidemia, smoking status (no, yes), and alcohol consumption (no, yes) of these patients were collected from medical records by experienced technicians. The height and weight of these patients were also measured to calculate the body mass index (BMI; kg/m²: the ratio of weight in kilograms to the square of height in meters).

To account for the potential impact of dietary intake on certain parameters, venous blood samples were collected in the morning after >10 h overnight fast. Blood tests were performed using an AU-5, 800 Chemistry Analyzer (Beckman Coulter Inc., Brea, CA, USA), including LDL-C, high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), total cholesterol (TC), hemoglobin A1c (HbA1c), hypersensitive C-reactive protein (hsCRP), creatinine (Cr), and uric acid (UA). The concentration of Lp(a) was measured using a latex-enhanced turbidimetric immunoassay (the circulating level: mg/L).

Echocardiography was used to evaluate the left ventricular ejection fractions (LVEFs).

CT scans

CCTA was conducted using a Siemens 64-slice multidetector CT scanner (from Siemens, Erlangen, Germany) with the following settings: 120 kV tube voltage, 80 mA tube current, 0.15–0.21 mm pitch, scan duration of 7–11 seconds, 0.62 mm slice thickness, and a rotation speed of 0.25 seconds per rotation. A total of 85–90 mL of Ultravist contrast agent (Bayer HealthCare, Berlin, Germany) was administered intravenously through the elbow using a high-pressure injector at a rate of 4.5–5.5 mL/s, followed by 40 mL of normal saline. After scanning, primary images were transferred to a dedicated workstation for CAC analysis. Calcified lesions were identified as areas with an attenuation of >130 Hounsfield units and a minimum area of 1 mm² on each slice. Calcification was defined as lesions with an attenuation >130 Hounsfield units and an area ≥1 mm² in each slice. CAC was quantified in Agatston units (AU) (27) and further classified as follows: 0 (normal), 0.1 to 99.9 (mild), 100 to 399.9 (moderate), and ≥400 (extensive) (28).

Carotid ultrasonography

All procedures adhered to the Chinese Stroke Vascular Ultrasound guidelines, performed by at least two professionally trained and experienced technicians (29). After a 15 min rest in the supine position, carotid plaque analysis was performed on patients using carotid artery Doppler ultrasonography with a 6–10 MHz linear-array probe to access atherosclerotic plaques and cIMT in the bilateral common carotid artery, bifurcation, and internal and external carotid arteries. Carotid arteriopathy was defined as the presence of an abnormal cIMT or plaques in any carotid segment. A mean cIMT value ≥1.0 mm indicated increased thickness, while a cIMT >1.5 mm or an atherosclerotic protrusion extending ≥50% into the arterial lumen signified plaque formation. Based on the acoustic and morphological characteristics of the carotid plaques, medium- and strong-echo plaques were classified as stable while low- and mixed-echo plaques were classified as vulnerable plaques. Patients with both stable and vulnerable plaques were classified as having vulnerable plaques (6).

Risk factor definition

According to the International Society of Hypertension guidelines, hypertension was defined as a condition characterized by a persistent elevation in systolic blood pressure (SBP) to >140 mmHg and a diastolic blood pressure (DBP) of at least 90 mmHg (30). Dyslipidemia is defined as the presence of one or more abnormal lipid concentrations, including LDL-C ≥4.14 mmol/L, HDL-C <1.04 mmol/L, TG ≥2.26 mmol/L, TC ≥6.22 mmol/L, or a previous diagnosis of dyslipidemia (31). According to the American Diabetes Association guidelines, prediabetes was defined as an HbA1c level: 5.7% to 6.4%, while DM was defined as an HbA1c level ≥6.5%, a prior DM diagnosis, or current use of antidiabetic medication (32).

Statistical model

As recommended in the Chinese guidelines, an Lp(a) level >30 mg/dL (>300 mg/L) was regarded as the CVD risk threshold following a small-sample population study (10). Therefore, in this study, participants were classified based on Lp(a) levels: <79.5 mg/L (the lower), 79.5–300 mg/L (the medium), and >300 mg/L (the elevated group), and by diabetic status: normal, prediabetes, and DM. After combining Lp(a) levels and diabetic status, nine subgroups were obtained.

Additionally, outcome variables included CAC scores and carotid plaques with Lp(a) level and diabetic status as the primary variables. The Kolmogorov-Smirnov test was used to assess the distribution of these variables. For continuous variables, the values were expressed as the mean ± standard deviation (SD) or median (25^th–75^th percentile); for categorical variables, the values were expressed as absolute values and proportions. In terms of comparison among groups, normally distributed data were analyzed using the independent samples t-test, while skewed data were analyzed using the Mann-Whitney U test. Furthermore, categorical variables were analyzed using Pearson’s Chi-squared test. Univariate logistic regression analysis was conducted to identify clinical factors significantly associated with CAC scores and carotid plaques. Subsequently, binary and multivariate logistic regression analyses were performed to identify the independent impact of diabetic status and Lp(a) levels on CAC scores and carotid plaques after the variables were adjusted with P<0.1 in the univariate analysis. The results were expressed as odds ratios (ORs) with corresponding 95% confidence intervals (95% CIs). All statistical analyses were conducted using SPSS (version 26.0; IBM Corp., Armonk, NY, USA), and a P value <0.05 was considered statistically significant.

Results

Baseline characteristics

The demographic characteristics of the population in the cross-sectional study are listed in Table 1. In this cross-sectional study, 98 individuals with a prior diagnosis of CAD, 9 individuals with malignant tumors, 12 individuals with an eGFR <30 mL/min/1.73 m², and 35 individuals with a lack of complete clinical data were excluded. Overall, 912 participants were included to explore the association between Lp(a) levels and atherosclerosis among different diabetic statuses. Overall, 912 patients with a median age of 67.0 (25^th–75^th percentile, 57.0, 73.0) years were included in this cross-sectional analysis. Of these, 430 (47.1%) were male, 295 (32.3%) were smokers while 256 (28.1%) consumed alcohol. A total of 569 (62.4%) patients were diagnosed with hypertension and 510 (55.9%) were diagnosed with dyslipidemia. CAC and carotid arteriopathy were diagnosed in 473 (51.9%) and 637 (69.8%) patients, respectively. Furthermore, 337 (37.0%) and 367 (40.2%) patients were diagnosed with DM and prediabetes, respectively. Among patients with CAC, there was a higher prevalence of hypertension, diabetes, and carotid arteriopathy, accompanied by elevated levels of hsCRP, HbA1c, and Cr. Patients with carotid arteriopathy had a higher prevalence of hypertension, hyperlipidemia, diabetes, as well as coronary calcification, accompanied by higher levels of Cr, Lp(a), HbA1c, and hsCRP. Moreover, these results revealed that patients with signs of CAC or carotid arteriopathy tended to present a lower LDL-C levels and higher utilization rates of antilipidemic medications.

Lp(a) levels, diabetic status, and CAC

As listed in Table 2, the univariate logistic regression analysis results showed that age ≥67 years (OR 3.60; 95% CI: 2.73–4.72, P<0.001), male gender (OR 1.32; 95% CI: 1.01–1.71, P=0.040), hypertension (OR 1.77; 95% CI: 1.35–2.32, P<0.001), DM (OR 2.39; 95% CI: 1.68–3.40, P<0.001), use of antilipidemic medication (OR 1.96; 95% CI: 1.40–2.75, P<0.001), use of antihypertensive medication (OR 2.19; 95% CI: 1.67–2.87, P<0.001), Cr level (OR 1.02; 95% CI: 1.01–1.03, P<0.001), Lp(a) >300 mg/L (OR 1.41; 95% CI: 0.99–2.00, P=0.054), HDL-C (OR 0.71; 95% CI: 0.50–1.01, P=0.06), hsCRP (OR 1.06; 95% CI: 1.02–1.09, P=0.001), and LVEF (OR 0.95; 95% CI: 0.93–0.97, P<0.001) were associated with CAC (Table 2, P<0.1). As for carotid arteriopathy, age ≥67 years (OR 4.06; 95% CI: 2.96–5.54, P<0.001), male gender (OR 1.50; 95% CI: 1.13–2.00, P=0.006), hypertension (OR 1.84; 95% CI: 1.38–2.46, P<0.001), dyslipidemia (OR 1.38; 95% CI: 1.03–1.83, P=0.03), DM (OR 1.57; 95% CI: 1.08–2.29, P=0.02), use of antilipidemic medication (OR 2.61; 95% CI: 1.86–3.67, P<0.001), use of antihypertensive medication (OR 1.92; 95% CI: 1.44–2.56, P<0.001), smoking (OR 1.36, 95% CI: 1.00–1.86, P=0.052), Lp(a) from 79.5 to 300 mg/L (OR 1.55, 95% CI: 1.11–2.15, P=0.009), Lp(a) >300 mg/L (1.96, 95% CI: 1.31–2.94, P=0.001), Cr level (OR 1.02; 95% CI: 1.01–1.03, P<0.001), TG (OR 0.89; 95% CI: 0.80–1.00, P=0.040), hsCRP (OR 1.04; 95% CI: 1.00–1.08, P=0.041), and LVEF (OR 0.97; 95% CI: 0.94–1.00, P=0.02) were associated with carotid arteriopathy (Table 2, P<0.10). These clinical factors could be regarded as confounding variables and were adjusted in the subsequent logistic regression analysis.

As listed in Table S1, the binary logistic regression crude model indicated that Lp(a) levels were not significantly associated with CAC. As shown in Figure 1 and Table S1, after adjusting for confounders (diabetic status, gender, age, hypertension, use of antilipidemic medication, use of antihypertensive medication, Cr, HDL-C, hsCRP, and LVEF), compared with lower Lp(a) levels, the higher Lp(a) levels were associated with the prevalence of CAC (OR 1.51, 95% CI: 1.02–2.24, P=0.040). Additionally, when compared with normal subjects, the difference in the prevalence of CAC in patients with prediabetes was not statistically significant (OR 0.89, 95% CI: 0.61–1.30, P=0.43), whereas the difference in patients with DM was statistically significant (OR 2.19, 95% CI: 1.49–3.22, P<0.001), after adjusting for Lp(a), gender, age, hypertension, antilipidemic use, antihypertensive use, Cr, HDL-C, hsCRP, LVEF. When analyzing combined Lp(a) levels and diabetic status, the binary logistic regression crude model also indicated that patient with DM having Lp(a) levels <79.5 mg/L, 79.5–300 mg/L and >300 mg/L were all associated with the prevalence of CAC (OR 2.85, 95% CI: 1.75–4.61, P<0.001), (OR 2.99, 95% CI: 1.71–5.22, P<0.001), and (OR 3.82, 95% CI: 1.96–7.44, P<0.001), compared to those with lower Lp(a) levels and normoglycemia. After, further adjustment for gender, age, hypertension, use of antilipidemic medication, use of antihypertensive medication, Cr, HDL-C, hsCRP, and LVEF were adjusted, the association was still statistically significant (OR 2.95, 95% CI: 1.74–4.98, P<0.001), (OR 2.58, 95% CI: 1.42–4.71, P=0.005), and (OR 3.59, 95% CI: 1.76–7.33, P=0.001), respectively. However, there was no statistically significant difference in the prevalence of CAC between the normoglycemia and prediabetes groups, regardless of Lp(a) level. As shown in Figure 2 and Table S2, adjusted for Model 1 (gender, age, hypertension, antilipidemic use, antihypertensive use, Cr, HDL-C, hsCRP, LVEF), there were significant associations between different Lp(a) levels and almost all CAC score categories in patient with DM (CAC score 0.1–99.9, 100–399.9, and ≥400). Among them, the DM group with Lp(a) level >300 mg/L presented the highest risk for all CAC score categories (OR 3.11, 95% CI: 1.34–7.22, P=0.008; OR 2.90, 95% CI: 1.04–8.06, P=0.041; OR 5.55, 95% CI: 1.80–17.15, P=0.003). Furthermore, patients with normoglycemia having medium Lp(a) levels showed an increased risk of mild CAC (CAC score =0.1–99.9) compared with normal controls (OR 2.62, 95% CI: 1.16–5.90, P=0.02). However, there was still no significant association between CAC scores and patients with prediabetes and Lp(a) levels (P>0.05). Finally, we conducted additional adjustments for Model 2 (dyslipidemia, TC, LDL-C, and HDL-C levels, in addition to Model 1). The final results were consistent with the aforementioned conclusions further reinforcing the robustness of our findings (Table S2).

Figure 1 Binary logistic regression analysis of the prevalence of CAC, carotid arteriopathy and Lp(a) levels with different diabetic status. The prevalence of CAC: (I) Group Lp(a) level: adjusted for diabetic status, gender, age, hypertension, antilipidemic use, antihypertensive use, Cr, HDL-C, hsCRP, LVEF. (II) Group diabetic status: adjusted for Lp(a), gender, age, hypertension, antilipidemic use, antihypertensive use, Cr, HDL-C, hsCRP, LVEF. (III) Group Lp(a) level and different diabetic status: adjusted for gender, age, hypertension, antilipidemic use, antihypertensive use, Cr, HDL-C, hsCRP, LVEF. The prevalence of carotid arteriopathy: (I) Group Lp(a) level: adjusted for diabetic status, gender, age, hypertension, dyslipidemia, antilipidemic use, antihypertensive use, smoking, Cr, TG, hsCRP, LVEF. (II) Group diabetic status: adjusted for Lp(a), gender, age, hypertension, dyslipidemia, antilipidemic use, antihypertensive use, smoking, Cr, TG, hsCRP, LVEF. (III) Group Lp(a) level and different diabetic status: adjusted for gender, age, hypertension, dyslipidemia, antilipidemic use, antihypertensive use, smoking, Cr, TG, hsCRP, LVEF. CAC, coronary artery calcium; OR, odds ratio; CI, confidence interval; Lp(a), lipoprotein(a); DM, diabetes mellitus; Cr, creatinine; HDL-C, high-density lipoprotein cholesterol; hsCRP, hypersensitive C-reactive protein; LVEF, left ventricular ejection fraction; TG, triglycerides.

Figure 2 Multivariable logistic regression analysis of CAC, carotid arteriopathy categories and Lp(a) levels with diabetic status. CAC severity group: Model 1 adjusted for gender, age, hypertension, antilipidemic use, antihypertensive use, Cr, HDL-C, hsCRP, LVEF. The carotid arteriopathy categories group: Model 1 adjusted for gender, age, hypertension, dyslipidemia, antilipidemic use, antihypertensive use, smoking, Cr, TG, hsCRP, LVEF. CAC, coronary artery calcium; OR, odds ratio; CI, confidence interval; cIMT, carotid intima-media thickness; Lp(a), lipoprotein(a); DM, diabetes mellitus; Cr, creatinine; HDL-C, high-density lipoprotein cholesterol; hsCRP, hypersensitive C-reactive protein; LVEF, left ventricular ejection fraction; TG, triglycerides.

Regarding the associations with carotid arteriopathy, as shown in Figure 1 and Table S3, after adjusting for diabetic status and Model 1 (sex, age, hypertension, dyslipidemia, antilipidemic use, antihypertensive use, smoking, Cr, TG, hsCRP, and LVEF), both moderate and high levels of Lp(a) were significantly associated with carotid arteriopathy compared with normal controls (OR 1.59; 95% CI: 1.10–2.29, P=0.01; OR 1.77, 95% CI: 1.10–2.86, P=0.02). However, prediabetes and DM showed no association with the prevalence of carotid arteriopathy compared with the normal controls. Furthermore, Figure 1 and Table S3 show that when combining Lp(a) levels with diabetic status, the multivariable logistic regression analysis indicated a significant association only in patients with DM having Lp(a) levels >300 mg/L (OR 3.38, 95% CI: 1.24–9.20, P=0.02), after accounting for the aforementioned confounding factors. Figure 2 and Table S4, further show that after adjusting for confounders (Model 1), increased cIMT, stable plaques, and vulnerable plaques were statistically significant only in patient with DM having elevated Lp(a) levels (OR 3.67, 95% CI: 1.10–12.30, P=0.04; OR 3.39, 95% CI: 1.09–10.55, P=0.04; OR 3.21, 95% CI: 1.07–9.65, P=0.04). There was insufficient evidence linking normoglycemia and prediabetes with the incidence of carotid arteriopathy. Finally, we conducted additional adjustments for Model 2 (TC, LDL-C, and HDL-C levels in addition to Model 1). The final results remained the same (Table S4).

Discussion

This study evaluated the effect of Lp(a) levels on subclinical atherosclerotic risk in patients with different diabetic statuses. First, elevated Lp(a) levels were independently associated with the prevalence of CAC and carotid arteriopathy, even after adjusting for relevant clinical risk factors. However, among the different diabetic statuses, an association with an increased CAC risk was only observed in patients with DM. Second, patients with DM having elevated Lp(a) levels showed a stronger association with both the presence and severity of CAC and carotid arteriopathy than those with only one elevated risk marker. Third, patients with DM having lower Lp(a) levels had a higher CAC risk than those with medium Lp(a) levels. Fourth, no statistically significant differences were observed in CAC scores and carotid arteriopathy between the prediabetes and normal groups.

Lp(a), DM and atherosclerosis

The pathogenic effects of Lp(a) are believed to involve several mechanisms: the deposition of LDL components within atherosclerotic plaques, a prothrombotic effect due to the apo(a) tail’s interference with plasminogen activation, the induction of a multi-tiered inflammatory response via oxidized phospholipids (OxPLs), and the facilitation of calcium accumulation in vascular tissues (23,33). Similar to previous studies, this study demonstrated a strong and independent association between elevated Lp(a) levels and atherosclerosis (13,34-36), and these findings were extended to the Chinese population. However, conclusions regarding the relationship between Lp(a) and CAC are inconsistent. For example, the Dallas Heart Study showed that, in white and black people, there was no consistent independent relationship between the size of the Lp(a) or apo(a) subtypes and the plasma level of CAC (37). In contrast, Kaiser et al. revealed that Lp(a) is associated with accelerated progression of low-attenuation plaques (necrotic cores) in patients with advanced multivessel coronary artery disease but not with coronary calcification (38). However, these two studies differ from ours in that our study subjects were non-CVD Chinese people with chest pain symptoms, were older, and had a higher proportion of multiple underlying diseases. Additionally, the influence of race-specific factors and genetic polymorphisms related to the Lp(a) gene—which affect circulating Lp(a) levels—may account for the variability in the relationship between Lp(a) and CAC across different populations (39).

Hyperglycemic damage is one of the most important mechanisms associated with DM. Hyperglycemia induces vascular inflammation and endothelial dysfunction by accumulating free radicals, and further increases oxidative stress by enhancing glucose oxidation (40). DM has been shown to be a risk factor for coronary calcification in many studies (41-44). However, the crude binary logistic regression model in this study showed a significant positive correlation between DM and carotid arteriopathy, and after adjusting for confounding factors, such as sex, age, hyperlipidemia, and medication history, the significant statistical association disappeared. This contrast with some previous studies (45-47). In this study, the proportion of previous cardiovascular interventions in patients with DM was higher than in patients without DM, and the proportion of treatments for hypertension and hyperlipidemia was also greater (48). Multiple studies revealed that elderly patients with type 2 diabetes mellitus (T2DM) treated with statins have lower cIMT values and increased plaque stability, further indicating that patients with T2DM treated with standardized lipid-lowering drugs can not only stabilize and reverse plaques but also significantly improve carotid arteriopathy (49,50). When Lp(a) was subsequently combined, the results showed that patients with DM having high Lp (a) levels were significantly associated with carotid arteriopathy and its severity, and the correlation was significantly higher than that in the high-level Lp(a) group or the DM group alone. In summary, patients with DM having high levels of Lp(a) may benefit from optimized treatment strategies to delay their progression and improve the clinical outcomes (51).

Lower Lp(a) level and atherosclerosis

It is worth noting that this study also suggested that patients with DM and lower Lp(a) levels (OR 2.95, 95% CI: 1.74–4.98, P<0.001) had a higher CAC correlation than DM patients with medium Lp(a) levels (OR 2.58, 95% CI: 1.42–4.71, P=0.005). Similar results were observed in the subgroup analyses of CAC severity. According to existing evidence, low Lp(a) levels are associated with an increased risk of prediabetes, diabetes, insulin resistance (IR), and hyperinsulinemia, and the CVD risk remains elevated (52-54). However, the underlying mechanisms remain unclear. Neele et al. showed that high insulin concentrations inhibited apo(a) synthesis at the transcriptional level in monkey liver cells, which may partially explain the phenomenon of lower Lp(a) levels in patients with T2DM and IR (55). Studies have also shown that apo(a) subtypes are significantly larger in individuals with elevated insulin or glucose levels, and it is well known that apo(a) size is negatively correlated with Lp(a) plasma concentration (56-58). Additionally, it has been reported that after Lp(a) treatment, low levels of Lp(a) may increase the risk of T2DM (9). Therefore, for patients with DM, the correlation between low levels of Lp(a) and CAC was higher than that of patients with DM with medium levels of Lp(a). The underlying mechanism is that a low level of Lp(a) leads to an increased risk of DM and high blood sugar damage, though further studies are required.

Prediabetes and atherosclerosis

Prediabetes is a stage of altered glucose metabolism associated with an increased risk of progression to DM and CVDs (59). The results of different studies vary due to the lack of standardized recommendations for the definition of prediabetes. In this study, patients with prediabetes were not found to be associated with subclinical atherosclerosis despite elevated Lp(a) levels. Previous studies have reported a crude association between prediabetes (based on HbA1c and FPG levels) and CAC, but only half of these studies demonstrated a significant association after statistical adjustment for confounding factors (60,61). DM has a detrimental effect on the arterial wall independent of the associated metabolic risk factors (62). In a study by Farhan et al., the risk profile of patients with prediabetes was more similar to that of patients with normal glucose metabolism than that of patients with DM (63). This observation, together with a recent controversial study in Science that defined prediabetes as a “dubious diagnosis”, has led to the view that prevention and treatment of prediabetes may cause more harm, leading to unnecessary medical interventions and burden (64,65). However, a recent large meta-analysis of 129 studies (involving >10 million participants) found that prediabetes was associated with an increased risk of all-cause mortality and CVDs (66). Given the controversial nature of prediabetes and the risk of progression to DM, efforts should continue to better identify individuals at risk of altered glucose metabolism and prevent complications such as vascular stenosis and thrombosis (62). Simultaneously, large-scale prospective studies on the relationship between prediabetes and atherosclerosis are warranted.

Over the past decade, Lp(a) has transitioned from being a relatively obscure risk factor for ASCVD to a key target in cardiovascular risk prevention. This change is due to: (I) robust epidemiological and genetic data consistently show that Lp(a) levels exceeding 30 mg/dL (or >75 nmol/L) are associated with an elevated ASCVD risk (67); (II) it has been observed that patients treated with statins continue to increase their Lp(a)-mediated ASCVD risk despite relatively good LDL-C control (68), and there are currently no specific therapeutic drugs for Lp(a) (69); (III) emerging therapies that effectively lower Lp(a) levels, such as proprotein convertase subtilisin kexin type 9 (PCSK9) inhibitors, apo(a) antisense oligonucleotide (pelacarsen), and apo(a) small interfering RNA (olpasiran, SLN360), have shown promise in improving cardiovascular outcomes and patients’ quality of life. As these treatments continue to evolve, the potential clinical benefits of reducing Lp(a) levels have become a central focus in the prevention and management of CVDs.

This study attempted to confirm that elevated Lp(a) levels help identify individuals with a higher risk of subclinical atherosclerosis in different diabetic statuses through logistic regression analysis. Similarly, if two risk markers are abnormal simultaneously, proper blood glucose control, high-intensity statin therapy, and active lifestyle changes are necessary to help reduce the risk of ASCVD (70). Additionally, in patients with DM, low Lp(a) levels were paradoxically associated with subclinical atherosclerosis, whereas in patients with prediabetes, Lp(a) levels did not stratify the disease. The study findings may provide support for broader testing of Lp(a) in a wider population.

Strengths and limitations

This cross-sectional survey of subclinical atherosclerosis in hospitalized patients with stable chest pain provides latest data that objectively reflects the independent and joint associations between Lp(a) levels and CAC and carotid arteriopathy risk in different diabetic statuses (normal, prediabetes, and DM) in western China. However, there are certain limitations in this observational study, including the selection of only hospitalized patients with chest pain from a single center in China and the fact that all patient data were obtained from the electronic medical record system of a tertiary hospital, which may lead to potential selection bias. These results require further examination and verification in a multicenter study. In addition, we only measured the baseline levels of plasma Lp(a) and diabetic status, as well as the baseline CAC and carotid arteriopathy data at the time of admission. Therefore, the experimental design of this observational, cross-sectional study limits its ability to determine the correlation between the research indicators, as it is affected by unmeasured confounding factors that cannot be ruled out. This design does not allow for establishing the causal relationship between Lp(a), diabetic status, and subclinical atherosclerosis. Finally, this study is also limited by its small sample size; therefore, it is necessary to obtain more evidence through larger prospective studies and follow-ups to explore the impact on the prognosis of cardiovascular adverse events in patients.

Conclusions

In conclusion, Lp(a) level has emerged as an independent risk factor for subclinical atherosclerosis in CVD-negative Chinese patients with chest pain at baseline, demonstrating a synergistic effect with DM. Notably, DM patients with lower Lp(a) levels correlate with an additional risk of subclinical atherosclerosis, while prediabetes patients do not. Therefore, it is necessary to formulate early prevention strategies for subclinical atherosclerosis based on Lp(a) levels and diabetes status.

Acknowledgments

We express our gratitude to all professors for their guidance during the implementation of this project and study. Additionally, we acknowledge the Editage team (www.editage.cn) for language editing services.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://cdt.amegroups.com/article/view/10.21037/cdt-24-410/rc

Data Sharing Statement: Available at https://cdt.amegroups.com/article/view/10.21037/cdt-24-410/dss

Peer Review File: Available at https://cdt.amegroups.com/article/view/10.21037/cdt-24-410/prf

Funding: This work was supported by the Natural Science Foundation of Chongqing (grant No. cstc2021jcyj-msxmX0077) and Chongqing Medical University School of Nursing - Nursing Discipline “Seed Plan” Research Project (Nursing “Heart” Team, grant No. 20240302). The funding bodies had no role in the study design, data collection, analysis, or interpretation, or drafting of the manuscript.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://cdt.amegroups.com/article/view/10.21037/cdt-24-410/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Ethical Review Board of the First Affiliated Hospital of Chongqing Medical University (No. K2023-575) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Ibanez B, Fernández-Ortiz A, Fernández-Friera L, et al. Progression of Early Subclinical Atherosclerosis (PESA) Study: JACC Focus Seminar 7/8. J Am Coll Cardiol 2021;78:156-79. [Crossref] [PubMed]
2. Biswas M, Saba L, Omerzu T, et al. A Review on Joint Carotid Intima-Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework. J Digit Imaging 2021;34:581-604. [Crossref] [PubMed]
3. Mehta A, Vasquez N, Ayers CR, et al. Independent Association of Lipoprotein(a) and Coronary Artery Calcification With Atherosclerotic Cardiovascular Risk. J Am Coll Cardiol 2022;79:757-68. [Crossref] [PubMed]
4. Wang J, Sun H, Wang Y, et al. Glucose metabolism status modifies the relationship between lipoprotein(a) and carotid plaques in individuals with fatty liver disease. Front Endocrinol (Lausanne) 2022;13:947914. [Crossref] [PubMed]
5. Patel J, Pallazola VA, Dudum R, et al. Assessment of Coronary Artery Calcium Scoring to Guide Statin Therapy Allocation According to Risk-Enhancing Factors: The Multi-Ethnic Study of Atherosclerosis. JAMA Cardiol 2021;6:1161-70. [Crossref] [PubMed]
6. Li X, Li J, Wu G. Relationship of Neutrophil-to-Lymphocyte Ratio with Carotid Plaque Vulnerability and Occurrence of Vulnerable Carotid Plaque in Patients with Acute Ischemic Stroke. Biomed Res Int 2021;2021:6894623. [Crossref] [PubMed]
7. Maloberti A, Meani P, Varrenti M, et al. Structural and Functional Abnormalities of Carotid Artery and Their Relation with EVA Phenomenon. High Blood Press Cardiovasc Prev 2015;22:373-9. [Crossref] [PubMed]
8. Koschinsky ML, Boffa MB. Oxidized phospholipid modification of lipoprotein(a): Epidemiology, biochemistry and pathophysiology. Atherosclerosis 2022;349:92-100. [Crossref] [PubMed]
9. Kamstrup PR. Lipoprotein(a) and Cardiovascular Disease. Clin Chem 2021;67:154-66. [Crossref] [PubMed]
10. Li JJ, Ma CS, Zhao D, et al. Lipoprotein(a) and Cardiovascular Disease in Chinese Population: A Beijing Heart Society Expert Scientific Statement. JACC Asia 2022;2:653-65. [Crossref] [PubMed]
11. Kim J, Choi SW, Lee YS, et al. Correlations Between Coronary Artery Disease, Coronary Artery Calcium Score, and Lipoprotein(a) Level in Korea. Ther Clin Risk Manag 2022;18:981-7. [Crossref] [PubMed]
12. Huffman MD, Kandula NR, Baldridge AS, et al. Evaluating the Potential Association Between Lipoprotein(a) and Atherosclerosis (from the Mediators of Atherosclerosis Among South Asians Living in America Cohort). Am J Cardiol 2019;123:919-21. [Crossref] [PubMed]
13. Steffen BT, Thanassoulis G, Duprez D, et al. Race-Based Differences in Lipoprotein(a)-Associated Risk of Carotid Atherosclerosis. Arterioscler Thromb Vasc Biol 2019;39:523-9. [Crossref] [PubMed]
14. Ruscica M, Rizzuto AS, Corsini A. Role of lipoprotein(a) in plaque progression. Eur Heart J Suppl 2022;24:I72-5. [Crossref] [PubMed]
15. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2022. Diabetes Care 2022;45:S17-38. [Crossref] [PubMed]
16. Lamprou S, Koletsos N, Mintziori G, et al. Microvascular and Endothelial Dysfunction in Prediabetes. Life (Basel) 2023;13:644. [Crossref] [PubMed]
17. Wang L, Peng W, Zhao Z, et al. Prevalence and Treatment of Diabetes in China, 2013-2018. JAMA 2021;326:2498-506. [Crossref] [PubMed]
18. Schlesinger S, Neuenschwander M, Barbaresko J, et al. Prediabetes and risk of mortality, diabetes-related complications and comorbidities: umbrella review of meta-analyses of prospective studies. Diabetologia 2022;65:275-85. [Crossref] [PubMed]
19. Brown OI, Drozd M, McGowan H, et al. Relationship Among Diabetes, Obesity, and Cardiovascular Disease Phenotypes: A UK Biobank Cohort Study. Diabetes Care 2023;46:1531-40. [Crossref] [PubMed]
20. Tian Y, Qiu Z, Wang F, et al. Associations of Diabetes and Prediabetes With Mortality and Life Expectancy in China: A National Study. Diabetes Care 2024;47:1969-77. [Crossref] [PubMed]
21. Cosentino F, Grant PJ, Aboyans V, et al. 2019 ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD. Eur Heart J 2020;41:255-323. [Crossref] [PubMed]
22. Langsted A, Nordestgaard BG, Kamstrup PR. Elevated Lipoprotein(a) and Risk of Ischemic Stroke. J Am Coll Cardiol 2019;74:54-66. [Crossref] [PubMed]
23. Mehta A, Shapiro MD. Apolipoproteins in vascular biology and atherosclerotic disease. Nat Rev Cardiol 2022;19:168-79. [Crossref] [PubMed]
24. Boffa MB, Koschinsky ML. Oxidized phospholipids as a unifying theory for lipoprotein(a) and cardiovascular disease. Nat Rev Cardiol 2019;16:305-18. [Crossref] [PubMed]
25. Toth PP. Subclinical atherosclerosis: what it is, what it means and what we can do about it. Int J Clin Pract 2008;62:1246-54. [Crossref] [PubMed]
26. Malik A, Brito D, Vaqar S, et al. Congestive Heart Failure. StatPearls. Treasure Island (FL) ineligible companies: StatPearls Publishing. Copyright © 2024, StatPearls Publishing LLC.; 2024.
27. Agatston AS, Janowitz WR, Hildner FJ, et al. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol 1990;15:827-32. [Crossref] [PubMed]
28. Rumberger JA, Brundage BH, Rader DJ, et al. Electron beam computed tomographic coronary calcium scanning: a review and guidelines for use in asymptomatic persons. Mayo Clin Proc 1999;74:243-52. [Crossref] [PubMed]
29. Wang X, Li W, Song F, et al. Carotid Atherosclerosis Detected by Ultrasonography: A National Cross-Sectional Study. J Am Heart Assoc 2018;7:e008701. [Crossref] [PubMed]
30. Charchar FJ, Prestes PR, Mills C, et al. Lifestyle management of hypertension: International Society of Hypertension position paper endorsed by the World Hypertension League and European Society of Hypertension. J Hypertens 2024;42:23-49. [Crossref] [PubMed]
31. Pan X, Hong F, Li S, et al. Long-term exposure to ambient PM(2.5) constituents is associated with dyslipidemia in Chinese adults. Ecotoxicol Environ Saf 2023;263:115384. [Crossref] [PubMed]
32. Diagnosis and Classification of Diabetes: Standards of Care in Diabetes-2024. Diabetes Care 2024;47:S20-42. [Crossref] [PubMed]
33. Garg PK, Guan W, Karger AB, et al. Lipoprotein (a) and risk for calcification of the coronary arteries, mitral valve, and thoracic aorta: The Multi-Ethnic Study of Atherosclerosis. J Cardiovasc Comput Tomogr 2021;15:154-60. [Crossref] [PubMed]
34. Lin L, Deng KQ, Chen Z, et al. Lipoprotein(a) distribution and its association with carotid arteriopathy in the Chinese population. Atherosclerosis 2023;372:1-9. [Crossref] [PubMed]
35. Qasim AN, Martin SS, Mehta NN, et al. Lipoprotein(a) is strongly associated with coronary artery calcification in type-2 diabetic women. Int J Cardiol 2011;150:17-21. [Crossref] [PubMed]
36. Pechlivanis S, Mahabadi AA, Hoffmann P, et al. Association between lipoprotein(a) (Lp(a)) levels and Lp(a) genetic variants with coronary artery calcification. BMC Med Genet 2020;21:62. [Crossref] [PubMed]
37. Guerra R, Yu Z, Marcovina S, et al. Lipoprotein(a) and apolipoprotein(a) isoforms: no association with coronary artery calcification in the Dallas Heart Study. Circulation 2005;111:1471-9. [Crossref] [PubMed]
38. Kaiser Y, Daghem M, Tzolos E, et al. Association of Lipoprotein(a) With Atherosclerotic Plaque Progression. J Am Coll Cardiol 2022;79:223-33. [Crossref] [PubMed]
39. Obisesan OH, Kou M, Wang FM, et al. Lipoprotein(a) and Subclinical Vascular and Valvular Calcification on Cardiac Computed Tomography: The Atherosclerosis Risk in Communities Study. J Am Heart Assoc 2022;11:e024870. [Crossref] [PubMed]
40. Won KB, Han D, Lee JH, et al. Evaluation of the impact of glycemic status on the progression of coronary artery calcification in asymptomatic individuals. Cardiovasc Diabetol 2018;17:4. [Crossref] [PubMed]
41. Kowall B, Lehmann N, Mahabadi AA, et al. Progression of coronary artery calcification is stronger in poorly than in well controlled diabetes: Results from the Heinz Nixdorf Recall Study. J Diabetes Complications 2017;31:234-40. [Crossref] [PubMed]
42. Kronmal RA, McClelland RL, Detrano R, et al. Risk factors for the progression of coronary artery calcification in asymptomatic subjects: results from the Multi-Ethnic Study of Atherosclerosis (MESA). Circulation 2007;115:2722-30. [Crossref] [PubMed]
43. Won KB, Han D, Lee JH, et al. Impact of optimal glycemic control on the progression of coronary artery calcification in asymptomatic patients with diabetes. Int J Cardiol 2018;266:250-3. [Crossref] [PubMed]
44. Cheng X, Li Z, Yang M, et al. Association of HbA1c with carotid artery plaques in patients with coronary heart disease: a retrospective clinical study. Acta Cardiol 2023;78:442-50. [Crossref] [PubMed]
45. Takase M, Nakaya N, Nakamura T, et al. Carotid Intima Media Thickness and Risk Factor for Atherosclerosis: Tohoku Medical Megabank Community-Based Cohort Study. J Atheroscler Thromb 2023;30:1471-82. [Crossref] [PubMed]
46. Lu SX, Wu TW, Chou CL, et al. Combined effects of hypertension, hyperlipidemia, and diabetes mellitus on the presence and severity of carotid atherosclerosis in community-dwelling elders: A community-based study. J Chin Med Assoc 2023;86:220-6. [Crossref] [PubMed]
47. Katsiki N, Mikhailidis DP. Diabetes and carotid artery disease: a narrative review. Ann Transl Med 2020;8:1280. [Crossref] [PubMed]
48. Scholtes VP, Peeters W, van Lammeren GW, et al. Type 2 diabetes is not associated with an altered plaque phenotype among patients undergoing carotid revascularization. A histological analysis of 1455 carotid plaques. Atherosclerosis 2014;235:418-23. [Crossref] [PubMed]
49. Chen W, Tian T, Wang S, et al. Characteristics of carotid atherosclerosis in elderly patients with type 2 diabetes at different disease course, and the intervention by statins in very elderly patients. J Diabetes Investig 2018;9:389-95. [Crossref] [PubMed]
50. Spagnoli LG, Mauriello A, Palmieri G, et al. Relationships between risk factors and morphological patterns of human carotid atherosclerotic plaques. A multivariate discriminant analysis. Atherosclerosis 1994;108:39-60. [Crossref] [PubMed]
51. Yahagi K, Kolodgie FD, Lutter C, et al. Pathology of Human Coronary and Carotid Artery Atherosclerosis and Vascular Calcification in Diabetes Mellitus. Arterioscler Thromb Vasc Biol 2017;37:191-204. [Crossref] [PubMed]
52. Ding L, Song A, Dai M, et al. Serum lipoprotein (a) concentrations are inversely associated with T2D, prediabetes, and insulin resistance in a middle-aged and elderly Chinese population. J Lipid Res 2015;56:920-6. [Crossref] [PubMed]
53. Fu Q, Hu L, Xu Y, et al. High lipoprotein(a) concentrations are associated with lower type 2 diabetes risk in the Chinese Han population: a large retrospective cohort study. Lipids Health Dis 2021;20:76. [Crossref] [PubMed]
54. Ward NC, Vickneswaran S, Watts GF. Lipoprotein (a) and diabetes mellitus: causes and consequences. Curr Opin Endocrinol Diabetes Obes 2021;28:181-7. [Crossref] [PubMed]
55. Neele DM, de Wit EC, Princen HM. Insulin suppresses apolipoprotein(a) synthesis by primary cultures of cynomolgus monkey hepatocytes. Diabetologia 1999;42:41-4. [Crossref] [PubMed]
56. Ruscica M, Sirtori CR, Corsini A, et al. Lipoprotein(a): Knowns, unknowns and uncertainties. Pharmacol Res 2021;173:105812. [Crossref] [PubMed]
57. Fogacci F, Di Micoli V, Avagimyan A, et al. Assessment of Apolipoprotein(a) Isoform Size Using Phenotypic and Genotypic Methods. Int J Mol Sci 2023;24:13886. [Crossref] [PubMed]
58. Lejawa M, Goławski M, Fronczek M, et al. Causal associations between insulin and Lp(a) levels in Caucasian population: a Mendelian randomization study. Cardiovasc Diabetol 2024;23:316. [Crossref] [PubMed]
59. Ferrannini E, Gastaldelli A, Iozzo P. Pathophysiology of prediabetes. Med Clin North Am 2011;95:327-39. vii-viii. [Crossref] [PubMed]
60. Xing FY, Neeland IJ, Gore MO, et al. Association of prediabetes by fasting glucose and/or haemoglobin A1c levels with subclinical atherosclerosis and impaired renal function: observations from the Dallas Heart Study. Diab Vasc Dis Res 2014;11:11-8. [Crossref] [PubMed]
61. Rutter MK, Massaro JM, Hoffmann U, et al. Fasting glucose, obesity, and coronary artery calcification in community-based people without diabetes. Diabetes Care 2012;35:1944-50. [Crossref] [PubMed]
62. Tuzcu EM, Puri R. Unraveling the Cardiovascular PROSPECTs of Patients With Prediabetes. JACC Cardiovasc Imaging 2019;12:742-4. [Crossref] [PubMed]
63. Farhan S, Redfors B, Maehara A, et al. Impact of Pre-Diabetes on Coronary Plaque Composition and Clinical Outcome in Patients With Acute Coronary Syndromes: An Analysis From the PROSPECT Study. JACC Cardiovasc Imaging 2019;12:733-41. [Crossref] [PubMed]
64. Piller C. Dubious diagnosis. Science 2019;363:1026-31. [Crossref] [PubMed]
65. Nguyen BM, Lin KW, Mishori R. Public health implications of overscreening for carotid artery stenosis, prediabetes, and thyroid cancer. Public Health Rev 2018;39:18. [Crossref] [PubMed]
66. Cai X, Zhang Y, Li M, et al. Association between prediabetes and risk of all cause mortality and cardiovascular disease: updated meta-analysis. BMJ 2020;370:m2297. [Crossref] [PubMed]
67. Tsimikas S, Fazio S, Ferdinand KC, et al. NHLBI Working Group Recommendations to Reduce Lipoprotein(a)-Mediated Risk of Cardiovascular Disease and Aortic Stenosis. J Am Coll Cardiol 2018;71:177-92. [Crossref] [PubMed]
68. Willeit P, Ridker PM, Nestel PJ, et al. Baseline and on-statin treatment lipoprotein(a) levels for prediction of cardiovascular events: individual patient-data meta-analysis of statin outcome trials. Lancet 2018;392:1311-20. [Crossref] [PubMed]
69. Wu MF, Xu KZ, Guo YG, et al. Lipoprotein(a) and Atherosclerotic Cardiovascular Disease: Current Understanding and Future Perspectives. Cardiovasc Drugs Ther 2019;33:739-48. [Crossref] [PubMed]
70. Cainzos-Achirica M, Miedema MD, McEvoy JW, et al. Coronary Artery Calcium for Personalized Allocation of Aspirin in Primary Prevention of Cardiovascular Disease in 2019: The MESA Study (Multi-Ethnic Study of Atherosclerosis). Circulation 2020;141:1541-53. [Crossref] [PubMed]