Genetic Risk Stratification and the Primary Prevention of Coronary Artery Disease
Main Article Content
Abstract
Coronary artery disease (CAD) is the number cause of death in the world. It is estimated that 50% of Americans will experience a cardiac event in their lifetime. The underlying pathology leading to coronary artery disease and its clinical manifestations, such as angina, myocardial infarction, and sudden death is coronary atherosclerosis. While the disease is not usually manifested clinically until the sixth or seventh decade, the underlying pathology is initiated as early as the second or third decade. Numerous randomized clinical trials have shown cardiac morbidity and mortality can be prevented by lowering the risk of known conventional risk factors for CAD such as decreasing plasma cholesterol or controlling hypertension. Secondary prevention of these conventional risk factors has been very effective; however, primary prevention has been shown to be even more effective. A major barrier to primary prevention is the lack of markers to detect among young asymptomatic individuals those at risk for CAD. The conventional risk factors are often not present until the sixth or seventh decade which could be late for primary prevention. Genetic predisposition accounts for 50% of the risk for CAD. Recently over 200 genetic risk variants predisposing to CAD have been discovered. Based on these variants, one can express the genetic risk for CAD in a single number referred to as the Polygenic Risk Score (PRS). The PRS has been evaluated in over one million individuals and shown that those with high genetic risk have the highest incidence of heart disease and can be reduced by 40-50%, utilizing drugs (statins and PCSK9 inhibitors) or lifestyle changes (favorable diet and increased exercise). The genetic risk for CAD is determined at conception and thus can be predicted anytime from birth onward. The PRS detection of young asymptomatic individuals based on the PRS enables one to implement early primary prevention. Adoption of the PRS to risk stratify for CAD could represent a paradigm shift in the prevention of this pandemic disease.
Article Details
How to Cite
FAIR, Jacques; ACUNA, Esperanza; ROBERTS, Robert.
Genetic Risk Stratification and the Primary Prevention of Coronary Artery Disease.
Medical Research Archives, [S.l.], v. 10, n. 8, aug. 2022.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/3039>. Date accessed: 19 apr. 2024.
doi: https://doi.org/10.18103/mra.v10i8.3039.
Section
Research Articles
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
References
1. Marian AJ, Brugada R, Roberts R. MENDELIAN BASIS OF CONGENITAL AND OTHER CARDIOVASCULAR DISEASES. In: Fuster V, Harrington RA, Narula J, Eapen ZJ, eds. Hurst’s The Heart. 14th ed. McGraw-Hill Education; 2017. Accessed October 5, 2020. accessmedicine.mhmedical.com/content.aspx?aid=1161732392
2. Roberts R. New Gains in Understanding Coronary Artery Disease, Interview with Dr Robert Roberts. Affymetrix Microarray Bulletin, Spring 2007:3(2);1–4.
3. Hirschhorn JN, Daly MJ. Genome-wide association studies for common diseases and complex traits. Nat Rev Genet. 2005;6:95–108.
4. Wang WY, Barratt BJ, Clayton DG, Todd JA. Genome-wide association studies: theoretical and practical concerns. Nat Rev Genet. 2005;6:109–118.
5. Roberts R, Stewart AF, Wells GA, Williams KA, Kavaslar N, McPherson R. Identifying genes for coronary artery disease: An idea whose time has come. Can J Cardiol. 2007 Aug;23 Suppl A:7A-15A.
6. Kruglyak L, Nickerson DA. Variation is the spice of life. Nat Genet. 2001;27:234–236.
7. Sun JX, Helgason A, Masson G, Ebenesersdóttir SS, Li H, Mallick S, Gnerre S, Patterson N, Kong A, Reich D, Stefansson K. A direct characterization of human mutation based on microsatellites. Nat Genet. 2012;44:1161–1165.
8. Bhangale TR, Rieder MJ, Livingston RJ, Nickerson DA. Comprehensive identification and characterization of diallelic insertion-deletion polymorphisms in 330 human candidate genes. Hum Mol Genet. 2005;14:59–69.
9. Carlson C. Considerations for SNP selection. In: Winer MP, ed. Genetic Variation: A Laboratory Manual. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory Press; 2007:263–281.
10. Levy S, Sutton G, Ng PC, et al. The diploid genome sequence of an individual human. PLoS Biol. 2007;5(10):e254. doi:10.1371/journal.pbio.0050254
11. Stranger BE, Forrest MS, Dunning M, et al. Relative impact of nucleotide and copy number variation on gene expression phenotypes. Science. 2007;315(5813):848–853.
12. Collins Francis S., Guyer Mark S., Chakravarti Aravinda. Variations on a Theme: Cataloging Human DNA Sequence Variation. Science. 1997;278(5343):1580-1581. doi:10.1126/science.278.5343.1580
13. Gibbs, R., Belmont, J., Hardenbol, P. et al. The International HapMap Project. Nature. 2003;426, 789–796.
14. Marian AJ, van Rooij E, Roberts R. Genetics and Genomics of Single-Gene Cardiovascular Diseases: Common Hereditary Cardiomyopathies as Prototypes of Single-Gene Disorders. J Am Coll Cardiol. 2016;68(25):2831-2849. doi:10.1016/j.jacc.2016.09.968
15. Kruglyak L. Prospects for whole-genome linkage disequilibrium mapping of common disease genes. Nat Genet. 1999;22:139–144.
16. Altshuler, D., Donnelly, P. A haplotype map of the human genome. Nature. 2005;437, 1299–1320.
17. International HapMap Consortium, Frazer KA, Ballinger DG, et al. A second generation human haplotype map of over 3.1 million SNPs. Nature. 2007;449(7164):851–861.
18. Klein RJ, Zeiss C, Chew EY, et al. Complement factor H polymorphism in age-related macular degeneration. Science. 2005;308(5720):385‐389. doi:10.1126/science.1109557.
19. Risch N, Merikangas K. The Future of Genetic Studies of Complex Human Diseases. Science. 1996;273(5281):1516. doi:10.1126/science.273.5281.1516
20. Chanock SJ, Manolio T, Boehnke M, et al. Replicating genotype–phenotype associations. Nature. 2007;447(7145):655-660. doi:10.1038/447655a
21. McPherson R, Pertsemlidis A, Kavaslar N, et al. A common allele on chromosome 9 associated with coronary heart disease. Science. 2007;316(5830):1488-1491. doi:10.1126/science.1142447
22. Helgadottir A, Thorleifsson G, Manolescu A, Gretarsdottir S, Blondal T, Jonasdottir A, et al. A common variant on chromosome 9p21 affects the risk of myocardial infarction. Science. 2007 Jun 8;316(5830):1491-3.
23. Assimes TL, Roberts R. Genetics: Implications for Prevention and Management of Coronary Artery Disease. J Am Coll Cardiol. 2016;68(25):2797-2818. doi:10.1016/j.jacc.2016.10.039
24. Preuss M, König IR, Thompson JR, et al.; CARDIoGRAM Consortium. Design of the Coronary ARtery DIsease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM) Study: a genome-wide association meta-analysis involving more than 22 000 cases and 60 000 controls. Circ Cardiovasc Genet. 2010;3:475–483.
25. The Coronary Artery Disease (C4D) Genetics Consortium. A genome-wide association study in Europeans and South Asians identifies five new loci for coronary artery disease. Nat Genet. 2011;43:339–344.
26. Roberts R, Fair J. Clinical Application of Genetic Prediction in the Management of CAD. IJIRMS. 2021;6(01):46-52. doi:10.23958/ijirms/vol06-i01/1025
27. Erdmann J, Kessler T, Munoz Venegas L, Schunkert H. A decade of genome-wide association studies for coronary artery disease: the challenges ahead. Cardiovasc Res. 2018;114(9):1241-1257. doi:10.1093/cvr/cvy084
28. Chan L, Boerwinkle E. Gene-environment interactions and gene therapy in atherosclerosis. Cardiology in Review. 1994; 2: 130-137.
29. Goldstein BA, Knowles JW, Salfati E, Ioannidis JP, Assimes TL. Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example. Front Genet 2014;5:254.
30. The Multiple Risk Factor Intervention Trial Group. Statistical design considerations in the NHLI multiple risk factor intervention trial (MRFIT). J Chronic Dis. 1977;30:261–275.
31. Cholesterol Treatment Trialists’ (CTT) Collaboration, Baigent C, Blackwell L, et al. Efficacy and safety of more intensive lowering of LDL cholesterol: a meta-analysis of data from 170,000 participants in 26 randomised trials. Lancet. 2010;376(9753):1670-1681. doi:10.1016/S0140-6736(10)61350-5
32. Roberts R, Chavira J, Acuna E. Therapeutic Implications of Genetic Risk Stratification for CAD. Int J Fam Med Prim Care. 2022; 3(1): 1059..
33. Navar-Boggan AM, Peterson ED, D’Agostino RB, Neely B, Sniderman AD, Pencina MJ. Hyperlipidemia in early adulthood increases long-term risk of coronary heart disease. Circulation. 2015;131(5):451-458. doi:10.1161/CIRCULATIONAHA.114.012477
34. Ference BA, Yoo W, Alesh I, et al. Effect of Long-Term Exposure to Lower Low-Density Lipoprotein Cholesterol Beginning Early in Life on the Risk of Coronary Heart Disease. Journal of the American College of Cardiology. 2012;60(25):2631. doi:10.1016/j.jacc.2012.09.017
35. Swiger KJ, Martin SS, Blaha MJ, et al. Narrowing sex differences in lipoprotein cholesterol subclasses following mid-life: the very large database of lipids (VLDL-10B). J Am Heart Assoc. 2014;3(2):e000851. doi:10.1161/JAHA.114.000851
36. Roberts R, Fair J. A Less than Provocative Approach for the Primary Prevention of CAD. J Cardiovasc Transl Res. Published online June 14, 2021. doi:10.1007/s12265-021-10144-6
37. Murray CJ, Lopez AD. Measuring the global burden of disease. N Engl J Med 2013;369(5):448–57.
38. Mega JL, Stitziel NO, Smith JG, et al. Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials. Lancet. 2015;385(9984):2264-2271. doi:10.1016/S0140-6736(14)61730-X
39. Natarajan P, Young R, Stitziel NO, et al. Polygenic Risk Score Identifies Subgroup With Higher Burden of Atherosclerosis and Greater Relative Benefit From Statin Therapy in the Primary Prevention Setting. Circulation. 2017;135(22):2091-2101. doi:10.1161/CIRCULATIONAHA.116.024436
40. Marston Nicholas A., Kamanu Frederick K., Nordio Francesco, et al. Predicting Benefit From Evolocumab Therapy in Patients With Atherosclerotic Disease Using a Genetic Risk Score. Circulation. 2020;141(8):616-623. doi:10.1161/CIRCULATIONAHA.119.043805
41. Damask Amy, Steg P. Gabriel, Schwartz Gregory G., 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. 2020;141(8):624-636. doi:10.1161/CIRCULATIONAHA.119.044434
42. Abraham G, Havulinna AS, Bhalala OG, et al. Genomic prediction of coronary heart disease. Eur Heart J. 2016;37(43):3267–3278.
43. Khera AV, Chaffin M, Aragam KG, et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat Genet. 2018;50(9):1219-1224. doi:10.1038/s41588-018-0183-z
44. Inouye M, Abraham G, Nelson CP, Wood AM, Sweeting MJ, Dudbridge F, et al. Genomic risk prediction of coronary artery disease in 480,000 adults. J Am Coll Cardiol 2018;72(16):1883–93.
45. Khera AV, Emdin CA, Drake I, Natarajan P, Bick AG, Cook NR, et al. Genetic risk, adherence to a healthy lifestyle, and coronary disease. N Engl J Med 2016;375(24):2349–58.].
46. Tikkanen E, Gustafsson S, Ingelsson E. Associations of fitness, physical activity, strength, and genetic risk with cardiovascular disease: longitudinal analyses in the UK Biobank study. Circulation 2018;137(24):2583–91.
47. Elliott J, Bodinier B, Bond TA, et al. Predictive Accuracy of a Polygenic Risk Score–Enhanced Prediction Model vs a Clinical Risk Score for Coronary Artery Disease. JAMA. 2020;323(7):636–645.
48. Mosley JD, Gupta DK, Tan J, et al. Predictive Accuracy of a Polygenic Risk Score Compared With a Clinical Risk Score for Incident Coronary Heart Disease. JAMA. 2020;323(7):627–635.
49. Popejoy AB, Fullerton SM. Genomics is failing on diversity. Nature. 2016;538: 161–4.
50. Roberts R, Chang CC, Hadley T. Genetic Risk Stratification: A Paradigm Shift in Prevention of Coronary Artery Disease. JACC Basic Transl Sci. 2021;6(3):287-304. doi:10.1016/j.jacbts.2020.09.004
51. Iribarren C, Lu M, Jorgenson E, et al. Weighted Multi-marker Genetic Risk Scores for Incident Coronary Heart Disease among Individuals of African, Latino and East-Asian Ancestry. Sci Rep. 2018;8(1):6853. doi:10.1038/s41598-018-25128-x
52. Dikilitas O, Schaid DJ, Kosel ML, et al. Predictive Utility of Polygenic Risk Scores for Coronary Heart Disease in Three Major Racial and Ethnic Groups. Am J Hum Genet. 2020;106(5):707-716. doi:10.1016/j.ajhg.2020.04.002
53. Lloyd-Jones DM, Larson MG, Beiser A, Levy D. Lifetime risk of developing coronary heart disease. The Lancet. 1999;353(9147):89-92. doi:10.1016/S0140-6736(98)10279-9
54. American Heart Association: Heart and Stroke Statistical Update. American Heart Association. 2000 ed. Dallas: 2000.
55. Virmani R, Robinowitz M, Geer JC, Breslin PP, Beyer JC, McAllister HA. Coronary artery atherosclerosis revisited in Korean war combat casualties. Arch Pathol Lab Med. 1987;111(10):972-976.
56. Joseph A, Ackerman D, Talley JD, Johnstone J, Kupersmith J. Manifestations of coronary atherosclerosis in young trauma victims--an autopsy study. J Am Coll Cardiol. 1993;22(2):459-467. doi:10.1016/0735-1097(93)90050-b
2. Roberts R. New Gains in Understanding Coronary Artery Disease, Interview with Dr Robert Roberts. Affymetrix Microarray Bulletin, Spring 2007:3(2);1–4.
3. Hirschhorn JN, Daly MJ. Genome-wide association studies for common diseases and complex traits. Nat Rev Genet. 2005;6:95–108.
4. Wang WY, Barratt BJ, Clayton DG, Todd JA. Genome-wide association studies: theoretical and practical concerns. Nat Rev Genet. 2005;6:109–118.
5. Roberts R, Stewart AF, Wells GA, Williams KA, Kavaslar N, McPherson R. Identifying genes for coronary artery disease: An idea whose time has come. Can J Cardiol. 2007 Aug;23 Suppl A:7A-15A.
6. Kruglyak L, Nickerson DA. Variation is the spice of life. Nat Genet. 2001;27:234–236.
7. Sun JX, Helgason A, Masson G, Ebenesersdóttir SS, Li H, Mallick S, Gnerre S, Patterson N, Kong A, Reich D, Stefansson K. A direct characterization of human mutation based on microsatellites. Nat Genet. 2012;44:1161–1165.
8. Bhangale TR, Rieder MJ, Livingston RJ, Nickerson DA. Comprehensive identification and characterization of diallelic insertion-deletion polymorphisms in 330 human candidate genes. Hum Mol Genet. 2005;14:59–69.
9. Carlson C. Considerations for SNP selection. In: Winer MP, ed. Genetic Variation: A Laboratory Manual. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory Press; 2007:263–281.
10. Levy S, Sutton G, Ng PC, et al. The diploid genome sequence of an individual human. PLoS Biol. 2007;5(10):e254. doi:10.1371/journal.pbio.0050254
11. Stranger BE, Forrest MS, Dunning M, et al. Relative impact of nucleotide and copy number variation on gene expression phenotypes. Science. 2007;315(5813):848–853.
12. Collins Francis S., Guyer Mark S., Chakravarti Aravinda. Variations on a Theme: Cataloging Human DNA Sequence Variation. Science. 1997;278(5343):1580-1581. doi:10.1126/science.278.5343.1580
13. Gibbs, R., Belmont, J., Hardenbol, P. et al. The International HapMap Project. Nature. 2003;426, 789–796.
14. Marian AJ, van Rooij E, Roberts R. Genetics and Genomics of Single-Gene Cardiovascular Diseases: Common Hereditary Cardiomyopathies as Prototypes of Single-Gene Disorders. J Am Coll Cardiol. 2016;68(25):2831-2849. doi:10.1016/j.jacc.2016.09.968
15. Kruglyak L. Prospects for whole-genome linkage disequilibrium mapping of common disease genes. Nat Genet. 1999;22:139–144.
16. Altshuler, D., Donnelly, P. A haplotype map of the human genome. Nature. 2005;437, 1299–1320.
17. International HapMap Consortium, Frazer KA, Ballinger DG, et al. A second generation human haplotype map of over 3.1 million SNPs. Nature. 2007;449(7164):851–861.
18. Klein RJ, Zeiss C, Chew EY, et al. Complement factor H polymorphism in age-related macular degeneration. Science. 2005;308(5720):385‐389. doi:10.1126/science.1109557.
19. Risch N, Merikangas K. The Future of Genetic Studies of Complex Human Diseases. Science. 1996;273(5281):1516. doi:10.1126/science.273.5281.1516
20. Chanock SJ, Manolio T, Boehnke M, et al. Replicating genotype–phenotype associations. Nature. 2007;447(7145):655-660. doi:10.1038/447655a
21. McPherson R, Pertsemlidis A, Kavaslar N, et al. A common allele on chromosome 9 associated with coronary heart disease. Science. 2007;316(5830):1488-1491. doi:10.1126/science.1142447
22. Helgadottir A, Thorleifsson G, Manolescu A, Gretarsdottir S, Blondal T, Jonasdottir A, et al. A common variant on chromosome 9p21 affects the risk of myocardial infarction. Science. 2007 Jun 8;316(5830):1491-3.
23. Assimes TL, Roberts R. Genetics: Implications for Prevention and Management of Coronary Artery Disease. J Am Coll Cardiol. 2016;68(25):2797-2818. doi:10.1016/j.jacc.2016.10.039
24. Preuss M, König IR, Thompson JR, et al.; CARDIoGRAM Consortium. Design of the Coronary ARtery DIsease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM) Study: a genome-wide association meta-analysis involving more than 22 000 cases and 60 000 controls. Circ Cardiovasc Genet. 2010;3:475–483.
25. The Coronary Artery Disease (C4D) Genetics Consortium. A genome-wide association study in Europeans and South Asians identifies five new loci for coronary artery disease. Nat Genet. 2011;43:339–344.
26. Roberts R, Fair J. Clinical Application of Genetic Prediction in the Management of CAD. IJIRMS. 2021;6(01):46-52. doi:10.23958/ijirms/vol06-i01/1025
27. Erdmann J, Kessler T, Munoz Venegas L, Schunkert H. A decade of genome-wide association studies for coronary artery disease: the challenges ahead. Cardiovasc Res. 2018;114(9):1241-1257. doi:10.1093/cvr/cvy084
28. Chan L, Boerwinkle E. Gene-environment interactions and gene therapy in atherosclerosis. Cardiology in Review. 1994; 2: 130-137.
29. Goldstein BA, Knowles JW, Salfati E, Ioannidis JP, Assimes TL. Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example. Front Genet 2014;5:254.
30. The Multiple Risk Factor Intervention Trial Group. Statistical design considerations in the NHLI multiple risk factor intervention trial (MRFIT). J Chronic Dis. 1977;30:261–275.
31. Cholesterol Treatment Trialists’ (CTT) Collaboration, Baigent C, Blackwell L, et al. Efficacy and safety of more intensive lowering of LDL cholesterol: a meta-analysis of data from 170,000 participants in 26 randomised trials. Lancet. 2010;376(9753):1670-1681. doi:10.1016/S0140-6736(10)61350-5
32. Roberts R, Chavira J, Acuna E. Therapeutic Implications of Genetic Risk Stratification for CAD. Int J Fam Med Prim Care. 2022; 3(1): 1059..
33. Navar-Boggan AM, Peterson ED, D’Agostino RB, Neely B, Sniderman AD, Pencina MJ. Hyperlipidemia in early adulthood increases long-term risk of coronary heart disease. Circulation. 2015;131(5):451-458. doi:10.1161/CIRCULATIONAHA.114.012477
34. Ference BA, Yoo W, Alesh I, et al. Effect of Long-Term Exposure to Lower Low-Density Lipoprotein Cholesterol Beginning Early in Life on the Risk of Coronary Heart Disease. Journal of the American College of Cardiology. 2012;60(25):2631. doi:10.1016/j.jacc.2012.09.017
35. Swiger KJ, Martin SS, Blaha MJ, et al. Narrowing sex differences in lipoprotein cholesterol subclasses following mid-life: the very large database of lipids (VLDL-10B). J Am Heart Assoc. 2014;3(2):e000851. doi:10.1161/JAHA.114.000851
36. Roberts R, Fair J. A Less than Provocative Approach for the Primary Prevention of CAD. J Cardiovasc Transl Res. Published online June 14, 2021. doi:10.1007/s12265-021-10144-6
37. Murray CJ, Lopez AD. Measuring the global burden of disease. N Engl J Med 2013;369(5):448–57.
38. Mega JL, Stitziel NO, Smith JG, et al. Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials. Lancet. 2015;385(9984):2264-2271. doi:10.1016/S0140-6736(14)61730-X
39. Natarajan P, Young R, Stitziel NO, et al. Polygenic Risk Score Identifies Subgroup With Higher Burden of Atherosclerosis and Greater Relative Benefit From Statin Therapy in the Primary Prevention Setting. Circulation. 2017;135(22):2091-2101. doi:10.1161/CIRCULATIONAHA.116.024436
40. Marston Nicholas A., Kamanu Frederick K., Nordio Francesco, et al. Predicting Benefit From Evolocumab Therapy in Patients With Atherosclerotic Disease Using a Genetic Risk Score. Circulation. 2020;141(8):616-623. doi:10.1161/CIRCULATIONAHA.119.043805
41. Damask Amy, Steg P. Gabriel, Schwartz Gregory G., 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. 2020;141(8):624-636. doi:10.1161/CIRCULATIONAHA.119.044434
42. Abraham G, Havulinna AS, Bhalala OG, et al. Genomic prediction of coronary heart disease. Eur Heart J. 2016;37(43):3267–3278.
43. Khera AV, Chaffin M, Aragam KG, et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat Genet. 2018;50(9):1219-1224. doi:10.1038/s41588-018-0183-z
44. Inouye M, Abraham G, Nelson CP, Wood AM, Sweeting MJ, Dudbridge F, et al. Genomic risk prediction of coronary artery disease in 480,000 adults. J Am Coll Cardiol 2018;72(16):1883–93.
45. Khera AV, Emdin CA, Drake I, Natarajan P, Bick AG, Cook NR, et al. Genetic risk, adherence to a healthy lifestyle, and coronary disease. N Engl J Med 2016;375(24):2349–58.].
46. Tikkanen E, Gustafsson S, Ingelsson E. Associations of fitness, physical activity, strength, and genetic risk with cardiovascular disease: longitudinal analyses in the UK Biobank study. Circulation 2018;137(24):2583–91.
47. Elliott J, Bodinier B, Bond TA, et al. Predictive Accuracy of a Polygenic Risk Score–Enhanced Prediction Model vs a Clinical Risk Score for Coronary Artery Disease. JAMA. 2020;323(7):636–645.
48. Mosley JD, Gupta DK, Tan J, et al. Predictive Accuracy of a Polygenic Risk Score Compared With a Clinical Risk Score for Incident Coronary Heart Disease. JAMA. 2020;323(7):627–635.
49. Popejoy AB, Fullerton SM. Genomics is failing on diversity. Nature. 2016;538: 161–4.
50. Roberts R, Chang CC, Hadley T. Genetic Risk Stratification: A Paradigm Shift in Prevention of Coronary Artery Disease. JACC Basic Transl Sci. 2021;6(3):287-304. doi:10.1016/j.jacbts.2020.09.004
51. Iribarren C, Lu M, Jorgenson E, et al. Weighted Multi-marker Genetic Risk Scores for Incident Coronary Heart Disease among Individuals of African, Latino and East-Asian Ancestry. Sci Rep. 2018;8(1):6853. doi:10.1038/s41598-018-25128-x
52. Dikilitas O, Schaid DJ, Kosel ML, et al. Predictive Utility of Polygenic Risk Scores for Coronary Heart Disease in Three Major Racial and Ethnic Groups. Am J Hum Genet. 2020;106(5):707-716. doi:10.1016/j.ajhg.2020.04.002
53. Lloyd-Jones DM, Larson MG, Beiser A, Levy D. Lifetime risk of developing coronary heart disease. The Lancet. 1999;353(9147):89-92. doi:10.1016/S0140-6736(98)10279-9
54. American Heart Association: Heart and Stroke Statistical Update. American Heart Association. 2000 ed. Dallas: 2000.
55. Virmani R, Robinowitz M, Geer JC, Breslin PP, Beyer JC, McAllister HA. Coronary artery atherosclerosis revisited in Korean war combat casualties. Arch Pathol Lab Med. 1987;111(10):972-976.
56. Joseph A, Ackerman D, Talley JD, Johnstone J, Kupersmith J. Manifestations of coronary atherosclerosis in young trauma victims--an autopsy study. J Am Coll Cardiol. 1993;22(2):459-467. doi:10.1016/0735-1097(93)90050-b