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Amartya kumar,
- Student, Department of Biotechnology, Dronacharya groups of institutions,Greater Noida, Uttar Pradesh, India
Abstract
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Cardiovascular diseases (CVDs) are the leading cause of death globally, with complex etiologies involving genetic, environmental, and lifestyle factors. Genome-wide association studies (GWAS) have significantly advanced the understanding of genetic underpinnings of CVDs by identifying numerous risk loci and variants associated with various cardiovascular conditions. This review explores the potential of GWAS to drive precision medicine in cardiovascular diseases by linking genetic data with clinical outcomes, providing insights into disease pathogenesis, and enabling the development of personalized therapeutic strategies. Although GWAS has provided extensive insights, challenges persist in applying these discoveries to clinical practice due to the intricate interplay between genes and the environment, as well as the multifaceted polygenic nature of CVDs.The review also highlights the importance of integrating GWAS data with other omics technologies, including transcriptomics and proteomics, to provide a more comprehensive understanding of cardiovascular health and disease. Finally, we discuss the need for diverse population representation in GWAS, emphasizing the importance of reducing health disparities through the inclusion of underrepresented ethnic groups. The future of precision medicine in CVDs relies on overcoming current challenges, incorporating multi-omics approaches, and ensuring equity in genomic research.
Keywords: Cardiovascular diseases (CVDs), Genome-wide association studies (GWAS), Genetic underpinnings, Risk loci, Clinical outcomes, Disease pathogenesis, Precision medicine, Personalized therapeutic strategies, Gene-environment interactions, Polygenic nature
[This article belongs to Research & Reviews : Journal of Computational Biology (rrjocb)]
Amartya kumar. Leveraging Genome-Wide Association Studies for Precision Medicine in Cardiovascular Diseases. Research & Reviews : Journal of Computational Biology. 2025; 14(01):-.
Amartya kumar. Leveraging Genome-Wide Association Studies for Precision Medicine in Cardiovascular Diseases. Research & Reviews : Journal of Computational Biology. 2025; 14(01):-. Available from: https://journals.stmjournals.com/rrjocb/article=2025/view=0
References
1. Cho SMJ, Koyama S, Honigberg MC, Surakka I, Haidermota S, Ganesh S, Patel AP, Bhattacharya R, Lee H, Kim HC, Natarajan P. Genetic, sociodemographic, lifestyle, and clinical risk factors of recurrent coronary artery disease events: a population-based cohort study. Eur Heart J. 2023 Sep 21;44(36):3456-3465. doi: 10.1093/eurheartj/ehad380
2. Harismendy O, Notani D, Song X, Rahim NG, Tanasa B, Heintzman N, Ren B, Fu XD, Topol EJ, Rosenfeld MG, Frazer KA. 9p21 DNA variants associated with coronary artery disease impair interferon-γ signalling response. Nature. 2011 Feb 10;470(7333):264-8. doi: 10.1038/nature09753.
3. “A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease.” Nature genetics 47, no. 10 (2015): 1121-1130.
4. Low SK, Takahashi A, Ebana Y, Ozaki K, Christophersen IE, Ellinor PT; AFGen Consortium; Ogishima S, Yamamoto M, Satoh M, Sasaki M, Yamaji T, Iwasaki M, Tsugane S, Tanaka K, Naito M, Wakai K, Tanaka H, Furukawa T, Kubo M, Ito K, Kamatani Y, Tanaka T. Identification of six new genetic loci associated with atrial fibrillation in the Japanese population. Nat Genet. 2017 Jun;49(6):953-958. doi: 10.1038/ng.3842.
5. McPherson R, Tybjaerg-Hansen A. Genetics of Coronary Artery Disease. Circulation Research 2016 Feb 18 118(4):564–78. Available from: https://www.ahajournals.org/doi/10.1161/circresaha.115.306566
6. Khera AV, Chaffin M, Aragam KG, Haas ME, Roselli C, Choi SH, Natarajan P, Lander ES, Lubitz SA, Ellinor PT, Kathiresan S. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat Genet. 2018 Sep;50(9):1219-1224. doi: 10.1038/s41588-018-0183-z.
7. Hartiala J, Schwartzman WS, Gabbay J, Ghazalpour A, Bennett BJ, Allayee H. The Genetic Architecture of Coronary Artery Disease: Current Knowledge and Future Opportunities. Curr Atheroscler Rep. 2017 Feb;19(2):6. doi: 10.1007/s11883-017-0641-6
8. Abramowitz Y, Roth A, Keren G, Isakov O, Shomron N, Laitman Y, Weissglas-Volkov D, Arbel Y, Banai S, Finkelstein A, Friedman E. Whole-exome sequencing in individuals with multiple cardiovascular risk factors and normal coronary arteries. Coron Artery Dis. 2016 Jun;27(4):257-66. doi: 10.1097/MCA.0000000000000357
9. Sethi Y, Patel N, Kaka N, Kaiwan O, Kar J, Moinuddin A, Goel A, Chopra H, Cavalu S. Precision Medicine and the future of Cardiovascular Diseases: A Clinically Oriented Comprehensive Review. J Clin Med. 2023 Feb 23;12(5):1799. doi: 10.3390/jcm12051799
10. Li C, Pan Y, Zhang R, Huang Z, Li D, Han Y, et al. Genomic Innovation in Early Life Cardiovascular Disease Prevention and Treatment. Circulation Research 2023 Jun 8 132(12):1628–47.
11. McPherson R, Pertsemlidis A, Kavaslar N, Stewart A, Roberts R, Cox DR, Hinds DA, Pennacchio LA, Tybjaerg-Hansen A, Folsom AR, Boerwinkle E, Hobbs HH, Cohen
JC. A common allele on chromosome 9 associated with coronary heart disease. Science. 2007 Jun 8;316(5830):1488-91. doi: 10.1126/science.1142447.
12. McLaren W, Pritchard B, Rios D, Chen Y, Flicek P, Cunningham F. Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor. Bioinformatics. 2010 Aug 15;26(16):2069-70.
13. Harrison PW, Amode MR, Austine-Orimoloye O, Azov AG, Barba M, Barnes I, Becker A, Bennett R, Berry A, Bhai J, Bhurji SK. Ensembl 2024. Nucleic acids research. 2024 Jan 5;52(D1):D891-9.
14. Curwen V, Eyras E, Andrews TD, Clarke L, Mongin E, Searle SM, Clamp M. The Ensembl automatic gene annotation system. Genome research. 2004 May 1;14(5):942-50.
15. Chen Y, Cunningham F, Rios D, McLaren WM, Smith J, Pritchard B, Spudich GM, Brent S, Kulesha E, Marin-Garcia P, Smedley D. Ensembl variation resources. BMC genomics. 2010 Dec;11:1-6.Gieger, C., et al. (2011). “New gene loci linked to coronary artery disease.” Nature, 471(7338), 639-645.
16. Chen Y, Cunningham F, Rios D, McLaren WM, Smith J, Pritchard B, Spudich GM, Brent S, Kulesha E, Marin-Garcia P, Smedley D. Ensembl variation resources. BMC genomics. 2010 Dec;11:1-6.
17. McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GR, Thormann A, Flicek P, Cunningham F. The ensembl variant effect predictor. Genome biology. 2016 Dec;17:1-4.
18. Cunningham F, Allen JE, Allen J, Alvarez-Jarreta J, Amode MR, Armean IM, Austine-Orimoloye O, Azov AG, Barnes I, Bennett R, Berry A. Ensembl 2022. Nucleic acids research. 2022 Jan 7;50(D1):D988-95.