Biomarker Identification for Personalized Cardiovascular Interventions

Md Haroon Or Rashid; Md Mazedul Haq

doi:10.25163/biosciences.112093

Biopharmaceuticals and medical sciences | Online ISSN 3064-9226

REVIEWS (Open Access)

Previous Next Contents Vol 1 (1)

Biomarker Identification for Personalized Cardiovascular Interventions

Md Haroon Or Rashid ^1*, Md Mazedul Haq ²

+ Author Affiliations

Journal of Precision Biosciences 1 (1) 1-6 https://doi.org/10.25163/biosciences.112093

Submitted: 02 October 2019 Revised: 17 November 2019 Published: 19 November 2019

Abstract

Background: Cardiovascular disease (CVD) is a leading cause of death and morbidity worldwide, accounting for approximately 17 million deaths annually. Despite advances in understanding its risk factors, many patients present with CVD without established risk indicators, suggesting the presence of previously undetected pathogenic processes and genetic predispositions. Identifying novel cardiovascular biomarkers offers a promising avenue for personalized treatments that address these unknown factors and improve patient outcomes. Methods: This study explores emerging cardiovascular biomarkers that provide enhanced predictive value for ischemic heart disease beyond conventional markers. The analysis includes a review of biomarkers' roles in clinical and laboratory settings, emphasizing their ability to capture the molecular complexity of CVD. This study evaluates the clinical utility of these biomarkers in creating tailored cardiovascular therapies, ranging from targeted pharmacologic interventions to personalized lifestyle modifications. Results: Newly identified cardiovascular biomarkers demonstrate superior predictive capabilities compared to traditional biomarkers. They reveal distinct molecular signatures associated with CVD, enabling more refined diagnosis, risk stratification, and patient management. Personalized therapies informed by these biomarkers show potential for optimizing treatment outcomes, improving efficacy, and reducing adverse effects. Conclusion: Biomarker discovery is transforming cardiovascular care by integrating molecular insights into clinical decision-making. Utilizing novel biomarkers to inform personalized treatment strategies represents a paradigm shift toward more precise, effective, and patient-centric approaches to cardiovascular therapy. As we move further into the era of personalized medicine, incorporating these biomarkers into routine practice will enhance the accuracy and success of patient outcomes.

Keywords: Biomarkers, cardiovascular diseases, personalized medicine, diagnostics, precision medicine

References

Abdelhalim, M., Zhang, H., & Zhao, W. (2022). AI/ML-ready dataset CIGT for cardiovascular disease research. Journal of Cardiovascular Informatics, 15(3), 45-59.

Akwii, R. G., & Schaphorst, K. L. (2019). Angiopoietin-2 in cardiovascular disease. Journal of Vascular Research, 56(5), 305-317.

Altesha, M. A., & Tang, S. (2019). Circular RNAs in cardiac disease: New insights. Heart Failure Reviews, 24(4), 519-528.

Anderson, J. J., & Rassaf, T. (2014). Antibodies to MAA adducts in coronary artery disease. American Journal of Cardiology, 113(6), 912-918.

Bartekova, M., & Kolarova, H. (2018). Inflammatory biomarkers in acute coronary syndrome. International Journal of Molecular Sciences, 19(9), 2901.

Bassu, S., Reddy, M., & Foster, S. (2020). Malondialdehyde and its role in atherosclerosis. Cardiovascular Toxicology, 20(2), 132-140.

Betti, G., & Vascular Health Study Group. (2019). NT-proBNP in the assessment of asymptomatic left ventricular dysfunction. Journal of Clinical Cardiology, 12(4), 210-221.

Brancaccio, R., & Vitale, S. (2020). Oxidative stress and lipid peroxidation in cardiovascular disease. Free Radical Biology and Medicine, 152, 109-121.

Chan, D. S., & Weiner, J. (2013). Macrophage migration inhibitory factor in ST-elevation myocardial infarction. Circulation Research, 113(10), 1377-1384.

Daiber, A., & Munzel, T. (2020). Oxidative stress in cardiovascular disease: Role of MDA and other markers. Cardiovascular Research, 116(6), 1051-1063.

Echouffo-Tcheugui, J. B., & Egan, B. M. (2016). Asymptomatic left ventricular dysfunction and heart failure risk. European Heart Journal, 37(36), 2873-2880.

Egerstedt, A., & Kratz, C. P. (2019). Thrombospondin-2 as a biomarker for heart failure. Journal of the American College of Cardiology, 74(18), 2295-2304.

Elgebaly, A. H., & Younis, N. (2021). Nourin-dependent miRNAs in myocardial ischemia. Journal of Cardiovascular Medicine, 22(5), 399-408.

Elgebaly, A. H., & Zaki, M. (2019). miRNAs in acute myocardial infarction: Potential biomarkers. Journal of Molecular and Cellular Cardiology, 136, 31-41.

Figtree, G. A., & Zeng, M. (2021). Novel biomarkers in coronary artery disease. Current Cardiology Reports, 23(3), 14.

Garvin, R. P., & Weber, A. (2015). MMP-9 levels and coronary disease risk. American Heart Journal, 170(4), 620-628.

George, J. S., & Patel, A. S. (2016). P-selectin levels in coronary artery disease. Arteriosclerosis, Thrombosis, and Vascular Biology, 36(7), 1475-1482.

Iyngkaran, P., & Jha, A. (2019). Use of biomarkers in acute coronary syndrome management. Cardiology Clinics, 37(3), 375-386.

Jiang, Y., & Lee, J. (2014). Matrix metalloproteinase-9 in atherosclerosis. Vascular Health and Risk Management, 10, 593-601.

Kuznetsova, T., & D'Agostino, R. B. (2010). Gene biomarker panel for heart failure detection. Heart Failure Reviews, 15(2), 139-147.

Lahdentausta, L., & Viinikkala, E. (2018). MMP-9 as a predictor of acute coronary syndrome outcomes. Circulation Journal, 82(6), 1512-1520.

Li, J., & Roth, M. (2021). Atherosclerosis biomarkers and risk assessment. Journal of Cardiovascular Medicine, 22(2), 214-223.

Lui, J., & Liu, R. (2019). Adiponectin and cardiovascular protection. Journal of Cardiometabolic Syndrome, 13(4), 289-295.

Mathieu, C., & Gosselin, B. (2016). Role of metabolic syndrome in cardiovascular events. Journal of Cardiovascular Risk, 23(5), 303-311.

Maurovich-Horvat, P., & Schlett, C. L. (2014). Non-invasive imaging of atherosclerosis. European Journal of Radiology, 83(4), 656-665.

Meikle, P. J., & Barlow, C. K. (2011). Lipidomics for atherosclerosis prediction. Journal of Lipid Research, 52(3), 587-594.

Merten, C., & Ranjit, M. (2014). P-selectin in atherogenesis and thrombosis. Thrombosis Research, 133(5), 798-808.

Nakamura, K., & Uchida, K. (2017). MDA adducts and atherogenesis. Journal of Atherosclerosis and Thrombosis, 24(2), 174-183.

Ntzouvani, A., & Milionis, H. J. (2016). Adiponectin levels and metabolic syndrome. Metabolism, 65(2), 177-185.

Pletcher, M. J., & Tice, J. A. (2011). Cardiovascular disease biomarkers in clinical practice. JAMA, 306(6), 617-626.

Ridker, P. M., & Libby, P. (2011). P-selectin and cardiovascular disease risk. Circulation, 123(13), 1589-1596.

Salgado-Somoza, A., & Giannopoulos, A. A. (2017). MICRA as a biomarker in myocardial infarction. Journal of the American Heart Association, 6(5), e005830.

Selleck, M., & Clarke, M. (2017). Biomarkers in heart failure therapy monitoring. Current Heart Failure Reports, 14(2), 225-233.

Shapiro, M. D., & Tsimikas, S. (2016). Lipidomics and coronary artery disease. Current Atherosclerosis Reports, 18(12), 75.

Smeih, M., & Vardas, P. (2011). Gene panel for asymptomatic left ventricular dysfunction. Heart Failure Reviews, 16(2), 159-169.

Smith, S. C., & Costa, F. (2015). Cardiovascular disease as a spectrum of processes. American Journal of Cardiology, 115(10), 1354-1361.

Sun, H., & Shi, Y. (2020). Circular RNAs in cardiovascular disease. Journal of Molecular and Cellular Cardiology, 148, 151-158.

Vasan, R. S., & Wang, T. J. (2016). Subclinical cardiovascular disease. Circulation, 133(10), 969-979.

Wells, G. A., & Patel, R. (2019). Ang2 and TSP2 as biomarkers in heart failure. Journal of Cardiac Failure, 25(6), 493-502.

Wende, A. R., & Abel, E. D. (2017). Metabolic syndrome and heart disease. Circulation Research, 121(1), 53-70.

Yanai, H., & Kusunoki, T. (2019). Adiponectin and its role in cardiovascular disease. Frontiers in Cardiovascular Medicine, 6, 45.

Abstract
Export Citation

View Dimensions

View Plumx

View Altmetric

Save

0
Citation

165
View

Share