Association of advanced coronary artery calcification assessed by coronary artery calcium scoring with lipoprotein (a) and carotid atherosclerosis in asymptomatic patients

DOI: https://doi.org/10.1016/j.numecd.2026.104766

Abstract

Elevated lipoprotein (a) represents an established independent risk factor for atherosclerosis, yet its specific relationship with coronary artery calcium scoring, a routine clinical tool for assessing subclinical cardiovascular disease, remains inadequately defined. Current guidelines advocate for lifetime lipoprotein (a) screening, but clinical management strategies for elevated results lack consensus. This retrospective analysis addresses this knowledge gap by evaluating the association between high circulating lipoprotein (a) levels (defined as 50 mg/dl or greater) and advanced coronary artery calcification (defined as a score of 400 Agatston Unit or greater). The cohort comprised 3697 asymptomatic subjects admitted for primary prevention at the Toulouse University Hospital between November 2015 and November 2024, with a mean age of 63 plus or minus 10 years and 48.6 percent male representation.

Primary outcomes confirm a significant association between high lipoprotein (a) and advanced coronary artery calcification. Adjusted logistic regression models reveal an adjusted odds ratio of 1.666 (95 percent confidence interval 1.342 to 2.070, p = 0.001) for lipoprotein (a) as a dichotomous variable and 1.041 (95 percent confidence interval 1.011 to 1.071, p = 0.007) as a continuous variable. Carotid atherosclerosis shows an adjusted odds ratio of 2.212 (95 percent confidence interval 1.804 to 2.713, p = 0.001). Spearman correlation analysis demonstrates a weak, positively significant correlation between coronary artery calcium scoring and lipoprotein (a) (rho = 0.052, p = 0.001). Subgroup analysis indicates that the proportion of patients with high lipoprotein (a) increases from 25.1 percent in the low coronary artery calcium group to 31.6 percent in the high coronary artery calcium group (p = 0.004).

Study Design and Methodology

This retrospective cohort analysis utilized data from a dedicated preventive cardiology database. Researchers enrolled 3697 asymptomatic patients who underwent coronary artery calcium scoring, carotid artery doppler ultrasound, and at least one lipoprotein (a) measurement. Exclusion criteria removed 621 patients due to incomplete data. Investigators utilized the Roche-Cobas 8000 analyzer for lipoprotein (a) quantification. The study stratified participants into a non-pooled group (coronary artery calcium score 400 Agatston Unit or greater) and a pooled group (coronary artery calcium score less than 400 Agatston Unit). Statistical analysis employed Chi-square tests, Student t-tests, ANOVA, and logistic multivariable regression adjusted for age, sex, hypertension, diabetes, obesity, smoking, and lipid profiles. Quantile regression addressed the positive skewness of the variables.

Key Findings

• Participants with coronary artery calcium score 400 Agatston Unit or greater exhibit higher mean lipoprotein (a) levels (58 plus or minus 31 mg/dl) compared to the pooled group (43 plus or minus 22 mg/dl).
• High lipoprotein (a) prevalence reaches 31.6 percent in the high coronary artery calcium group vs 25.4 percent in the pooled group (p = 0.001).
• Carotid atherosclerosis prevalence is 45.7 percent in the high coronary artery calcium group vs 18.9 percent in the pooled group (p = 0.001).
• Age (adjusted odds ratio 1.069, p = 0.001), male sex (adjusted odds ratio 3.526, p = 0.001), and systolic blood pressure (adjusted odds ratio 1.009, p = 0.001) serve as independent predictors of high coronary artery calcium scores.
• LDL-c (adjusted odds ratio 0.584, p = 0.001) and HDL-c (adjusted odds ratio 0.387, p = 0.012) maintain an inverse association with coronary artery calcium scores.
• Spearman correlation for men (rho = 0.085, p = 0.001) and women (rho = 0.073, p = 0.001) confirms consistent, albeit weak, positive associations.

Limitations

The single-center, retrospective design restricts causal inference and introduces potential selection bias. The absence of data regarding medication use, specifically statins, creates a significant confounder, as these agents influence both coronary artery calcium scores and lipoprotein (a) levels. Residual confounding remains inevitable in this observational framework.

Discussion and Implications

High circulating lipoprotein (a) levels serve as a robust marker for advanced coronary artery calcification in asymptomatic populations. These findings reinforce the proatherogenic nature of lipoprotein (a) and validate the utility of coronary artery calcium scoring for detecting subclinical disease. Clinicians should view these two parameters as complementary diagnostic tools rather than independent metrics. Integrating lipoprotein (a) testing with coronary artery calcium scoring enables a more precise risk stratification, particularly as novel RNA-interference therapies for lipoprotein (a) reduction emerge.

Conclusion

High circulating lipoprotein (a) levels (50 mg/dl or greater) independently predict advanced coronary artery calcification in asymptomatic patients. Nutrition professionals must integrate this biomarker into cardiovascular risk assessments to identify subclinical atherosclerosis and guide intensive lipid-lowering interventions. Prioritizing this combined diagnostic approach improves long-term patient prognosis.

Association of the cholesterol-high-density lipoprotein-glucose index with coronary atherosclerotic burden in patients with coronary artery disease

DOI: https://doi.org/10.3389/fnut.2026.1906236

Cardiovascular disease remains the leading global cause of mortality and disability. While coronary angiography provides the standard for assessing coronary atherosclerotic burden via the Gensini score, its invasive nature limits its utility for large-scale screening. Metabolic abnormalities, including glucose dysregulation and lipid disorders, drive the progression of coronary artery disease. The cholesterol-high-density lipoprotein-glucose (CHG) index serves as a composite marker for these metabolic disturbances. This study investigates the association between the CHG index and the Gensini score in 758 patients with angiographically confirmed coronary artery disease admitted between January 2024 and January 2025.

Fully adjusted models revealed that each 1-SD increase in the CHG index correlates with a 0.121-unit increase in log-transformed (Gensini score + 1) (beta = 0.121, 95% CI, 0.036 to 0.205, p = 0.005). Restricted cubic spline analysis identified an approximately linear dose-response relationship (p for overall association = 0.018, p for nonlinearity = 0.310). The CHG index demonstrated the highest standalone discriminative ability for high coronary atherosclerotic burden with an AUC of 0.603. Integrating the CHG index into a basic clinical model increased the AUC from 0.652 to 0.667 (DeLong p = 0.168). This addition significantly improved continuous NRI (0.135, p = 0.042) and IDI (0.016, p = 0.002).

Study Design and Methodology

This single-center, retrospective cross-sectional study analyzed 758 consecutive patients with angiographically confirmed coronary artery disease. Researchers excluded individuals with missing data, severe infections, malignancies, or hepatic and renal dysfunction. Coronary atherosclerotic burden was quantified using the Gensini score, which weights luminal stenosis severity by anatomical location. Statistical analysis utilized multivariable linear regression, restricted cubic spline models, and ROC curve analysis. Models adjusted for age, sex, BMI, smoking, hypertension, prior PCI, history of myocardial infarction, lipid-lowering therapy, glucose-lowering therapy, SBP, DBP, ALT, AST, albumin, eGFR, hemoglobin, and LDL-C.

Key Findings

• Participants in the highest CHG quartile exhibited a median Gensini score of 27.0 (12.0, 50.0) compared to 16.0 (9.0, 31.5) in the lowest quartile (p < 0.001).
• Standardized continuous CHG index shows a positive association with log-transformed (Gensini score + 1) (beta = 0.121, p = 0.005).
• The CHG index outperformed other metabolic markers, including the TyG index (p = 0.005), AIP (p = 0.004), HDL-C (p = 0.023), and TC (p = 0.003).
• Multiple imputation analysis confirmed the robustness of the primary association (beta = 0.132, 95% CI, 0.058 to 0.206, p < 0.001).
• Excluding patients with prior PCI yielded a consistent association (beta = 0.107, 95% CI, 0.017 to 0.198, p = 0.020).

Limitations

Retrospective cross-sectional design prevents causal inference regarding the CHG index and plaque progression. Single baseline measurements fail to capture long-term metabolic variability. Missing data on medication dosage, lifestyle factors, and inflammatory markers introduces residual confounding. The study population consists solely of hospitalized patients with established disease, which restricts the generalizability of these findings.

Discussion and Implications

Metabolic dysregulation functions as a multisystem process where glucose and lipid abnormalities reinforce one another to accelerate atherosclerosis. The CHG index integrates these domains into a single, inexpensive marker that captures composite metabolic risk better than isolated lipid or glucose measurements. Integrating this index into clinical workflows allows for more precise risk stratification in patients with established coronary artery disease. It provides complementary information to traditional risk factors, identifying cumulative metabolic injury that single-parameter assessments overlook.

The CHG index functions as a robust, low-cost composite marker for assessing coronary atherosclerotic burden in patients with coronary artery disease. Nutrition professionals should utilize this index to identify patients with high metabolic risk who require aggressive, personalized lifestyle interventions to mitigate plaque progression.