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. 2025 Aug 3:2025:5528174.
doi: 10.1155/cdr/5528174. eCollection 2025.

Significance of APOB/APOA1 Ratio in the Prediction of Calcific Aortic Valve Disease

Yuxing Wang  1 , Ming Yu  1 , Song Yang  1 , Jiajie Mei  1 , Zhenzhu Liu  1 , Zhaohong Geng  1 , Wenli Xie  1 , Lijiao Zhang  1 , Hongyan Wang  1 , Nan Niu  1 , Peng Qu  1
Affiliations

Significance of APOB/APOA1 Ratio in the Prediction of Calcific Aortic Valve Disease

Yuxing Wang et al. Cardiovasc Ther. .

Abstract

Background: Calcific aortic valve disease (CAVD) is a prevalent heart valve disease. The ratio of two apolipoproteins with distinct functions, Apolipoprotein B/Apolipoprotein A1 (APOB/APOA1), has been proposed as a novel assessment index for the evaluation of cardiovascular diseases. The aim of this article is to discuss the role of lipid parameters such as APOB/APOA1 in CAVD and the risk factors for CAVD, to develop a predictive model for CAVD, and to evaluate the sensitivity and specificity of this model. Method: Patients who initially presented to the Department of Cardiology of the Second Affiliated Hospital of Dalian Medical University between 1 January 2023 and 31 December 2023 were retrospectively identified and included in the study. Patients were divided into an aortic valve calcification group (111 cases) and a control group (201 cases) based on computed tomography (CT) findings. The clinical data, laboratory examination results, and chest CT images of the patients were collected and analyzed. A variety of statistical methods were used to analyze risk factors for CAVD, to construct a CAVD prediction model, and to assess its sensitivity and specificity. Results: Lipid parameters APOA1, APOB/APOA1, cumulative low-density lipoprotein (LDL) exposure, and non-high-density lipoprotein/high-density lipoprotein (non-HDL/HDL) were significantly associated with aortic valve calcification. Age, history of diabetes, diastolic blood pressure (DBP), APOB/APOA1, Cystatin C (Cys-c), and neutrophil-to-lymphocyte ratio (NLR) are identified as independent risk factors for CAVD, and the combined model achieved an AUC of 0.796 for CAVD prediction, corresponding to a sensitivity of 0.769 and a specificity of 0.755. Conclusion: The lipid parameters APOA1, APOB/APOA1, cumulative LDL exposure, and non-HDL/HDL have been demonstrated to be associated with aortic valve calcification. Furthermore, APOB/APOA1 can be used for the prediction of CAVD, and the combination of APOB/APOA1 with age, history of diabetes, DBP, Cys-c, and NLR has better prediction performance for CAVD.

Keywords: APOB/APOA1; calcific aortic valve disease; prediction model.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Box plots comparing each general lipid parameter in the CAVD group and the control group. Note: ⁣∗p < 0.05, ⁣∗∗p < 0.01; compared to the control group, the difference was statistically significant.
Figure 2
Figure 2
Box plots comparing APOB/APOA1 in the CAVD group and the control group. Note: ⁣∗p < 0.05,∗∗p < 0.01; compared to the control group, the difference was statistically significant.
Figure 3
Figure 3
Forest map of CAVD risk factors. Note: DBP, diastolic blood pressure; APOB/APOA1, Apolipoprotein B/Apolipoprotein A1; Cys-c, cystatin C; NLR, neutrophil-to-lymphocyte ratio.
Figure 4
Figure 4
ROC curves for aortic valve calcification and various risk factors.
Figure 5
Figure 5
CAVD prediction model calibration curve. Note: Apparent, calibration curve for predicted incidence; bias-corrected, measured incidence curve; ideal, ideal reference line.
See this image and copyright information in PMC

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References

    1. Osnabrugge R. L., Mylotte D., Head S. J., et al. Aortic Stenosis in the Elderly. Journal of the American College of Cardiology . 2013;62(11):1002–1012. doi: 10.1016/j.jacc.2013.05.015. - DOI - PubMed
    1. Roth G. A., Mensah G. A., Johnson C. O., et al. Global Burden of Cardiovascular Diseases and Risk Factors, 1990-2019: Update From the GBD 2019 Study. Journal of the American College of Cardiology . 2020;76(25):2982–3021. doi: 10.1016/j.jacc.2020.11.010. - DOI - PMC - PubMed
    1. Sasakawa Y., Okamoto N., Fujii M., Kato J., Yuzawa Y., Inaguma D. Factors Associated With Aortic Valve Stenosis in Japanese Patients With End-Stage Kidney Disease. BMC Nephrology . 2022;23(1):p. 129. doi: 10.1186/s12882-022-02758-y. - DOI - PMC - PubMed
    1. Otto C. M., Lind B. K., Kitzman D. W., Gersh B. J., Siscovick D. S. Association of Aortic-Valve Sclerosis With Cardiovascular Mortality and Morbidity in the Elderly. New England Journal of Medicine . 1999;341(3):142–147. doi: 10.1056/NEJM199907153410302. - DOI - PubMed
    1. Liu L., Zhao Y. S., Wang S. W., et al. An Epidemiological Study on degenerated Heart valvular diseases among military Elderly Population in Beijing. Chinese Journal of Epidemiology . 2006;27(10):836–839. doi: 10.3760/j.issn:0254-6450.2006.10.003. - DOI - PubMed

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