Precision Medicine in Coronary Artery Disease: Integrating Genomics and Clinical Data for Personalized Risk Assessment

Laura Vero^*
*Correspondence: Laura Vero, Department of Cardiology, University of Oulu, Pentti Kaiteran katu 1, 90570 Oulu, Finland, Email:

Introduction

Coronary Artery Disease remains a leading cause of morbidity and mortality worldwide. Precision medicine has emerged as a promising approach to enhance risk assessment and treatment strategies by considering individual genetic variability and clinical data. This article reviews the current state of precision medicine in CAD, focusing on the integration of genomics and clinical data for personalized risk assessment. We explore the advancements in genetic profiling techniques, the identification of genetic markers associated with CAD, and the integration of these markers with clinical information to develop comprehensive risk prediction models. Furthermore, we discuss the challenges and opportunities in implementing precision medicine approaches for CAD and emphasize the potential impact on improving patient outcomes and optimizing healthcare resources.

Coronary Artery Disease is a multifactorial cardiovascular disorder characterized by the accumulation of atherosclerotic plaques in coronary arteries, leading to reduced blood flow and potential myocardial infarction. Despite advancements in diagnostic and therapeutic interventions, CAD continues to pose a substantial health burden globally. Precision medicine, a patient-centric approach that considers individual variability in genes, environment, and lifestyle, has garnered attention as a means to enhance risk assessment, prevention, and treatment strategies for CAD [1-3].

Description

Recent technological advancements have revolutionized the field of genomics, enabling cost-effective and high-throughput sequencing of the entire genome or targeted gene panels. Genome-wide association studies have identified numerous genetic loci associated with CAD risk, shedding light on the complex genetic architecture underlying the disease. Furthermore, advancements in sequencing technology, such as next-generation sequencing, have facilitated the identification of rare variants and copy number variations that contribute to CAD susceptibility.

Several genetic markers have been identified as significant contributors to CAD risk. These markers include single nucleotide polymorphisms in genes involved in lipid metabolism, inflammation, endothelial function, and coagulation pathways. Integrating information from multiple genetic markers can provide a more accurate assessment of an individual's genetic predisposition to CAD. Polygenic risk scores amalgamate the effects of multiple genetic variants into a single score, enhancing risk prediction accuracy. To achieve personalized risk assessment, integration of genomic data with clinical information is essential. Electronic health records contain valuable clinical data such as medical history, laboratory results, and imaging findings. Combining genomic data with clinical data allows for the development of comprehensive risk prediction models that encompass genetic predisposition, lifestyle factors, and clinical indicators.

Implementing precision medicine in CAD presents several challenges, including data privacy concerns, ethical considerations, and the need for interdisciplinary collaboration. Additionally, the clinical utility of genetic information in risk stratification and treatment selection requires careful validation. However, precision medicine also offers substantial opportunities, including the identification of novel therapeutic targets, the development of targeted therapies, and the optimization of healthcare resource allocation. Personalized risk assessment through precision medicine can enable early identification of individuals at high risk for CAD. This facilitates the implementation of preventive measures, lifestyle modifications, and tailored interventions to mitigate risk. Additionally, precision medicine can enhance treatment selection by identifying patients likely to benefit from specific therapies, minimizing adverse effects and optimizing therapeutic outcomes [4-6].

Conclusion

Precision medicine holds great promise in revolutionizing the approach to coronary artery disease by integrating genomic information with clinical data for personalized risk assessment. As the field continues to evolve, interdisciplinary collaboration, robust validation, and ethical considerations will be critical to translating genomic insights into actionable strategies that improve patient outcomes and reduce the burden of CAD.

Acknowledgement

None.

Conflict of Interest

Authors declare no conflict of interest.

References

1. Heald, Adrian H., Mike Stedman, Mark Davies and Mark Livingston, et al. "Estimating life years lost to diabetes: Outcomes from analysis of National Diabetes Audit and Office of National Statistics data." Cardiovasc Endocrinol Metab 9 (2020): 183.

Google Scholar, Crossref, Indexed at

2. Wright, Alison K., Milton Fabian Suarez-Ortegon and Stephanie H. Read. "Risk factor control and cardiovascular event risk in people with type 2 diabetes in primary and secondary prevention settings." Circulation 142 (2020): 1925-1936.

Google Scholar, Crossref, Indexed at

3. Musunuru, Kiran and Sekar Kathiresan. "Genetics of common, complex coronary artery disease." Cell 177 (2019): 132-145.

Google Scholar, Crossref, Indexed at

4. Qi, Lu, Layla Parast, Tianxi Cai and Christine Powers, et al. "Genetic susceptibility to coronary heart disease in type 2 diabetes: 3 independent studies." J Am Coll Cardiol 58 (2011): 2675-2682.

Google Scholar, Crossref, Indexed at

5. Marston, Nicholas A., Frederick K. Kamanu, Francesco Nordio and Yared Gurmu, et al. "Predicting benefit from evolocumab therapy in patients with atherosclerotic disease using a genetic risk score: Results from the fourier trial." Circulation 141 (2020): 616-623.

Google Scholar, Crossref, Indexed at

6. Damask, Amy, P. Gabriel Steg, Gregory G. Schwartz and Michael Szarek, et al. "Patients with high genome-wide polygenic risk scores for coronary artery disease may receive greater clinical benefit from alirocumab treatment in the odyssey outcomes trial." Circulation 141 (2020): 624-636.

Google Scholar, Crossref, Indexed at