Abstract
Purpose of Review
The potential of polygenic risk scores (PRS) to improve atherosclerotic cardiovascular disease (ASCVD) risk assessment and management has stoked significant interest in their incorporation into clinical management. The goal of this review is to apprise the readers of the latest developments and evidence of PRS readiness for clinical integration. We also discuss current limitations that must be addressed before PRS can be implemented into routine clinical practice.
Recent Findings
PRS have been shown to improve risk stratification for ASCVD and to identify patients who may derive increased benefit from primary and secondary prevention. Risk captured by PRS appears largely independent of traditional risk factors and can be ascertained at birth, prior to the development of traditional clinical risk factors. Genetic risk is modifiable through lifestyle modifications and medications.
Summary
PRS offers a valuable way to improve early identification of actionable CVD risk. However, further work is needed before PRS can be implemented clinically.
Similar content being viewed by others
References
Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance
• Khera AV, Chaffin M, Aragam KG, Haas ME, Roselli C, Choi SH, et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat Genet 2018. 50:1219–24 This study identified individuals with polygenic risk for coronary artery disease that was equivalent to individuals with familial hypercholesterolemia.
• 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: implications for primary prevention. J Am Coll Cardiol. 2018;72:1883–93 This study showed that a genome-wide polygenic risk score could characterize marked differences in lifetime trajectories of coronary artery disease risk between strata.
Damask A, Steg PG, Schwartz GG, Szarek M, Hagström E, Badimon L, 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;141:624–36.
•• Aragam KG, Dobbyn A, Judy R, Chaffin M, Chaudhary K, Hindy G, et al. Limitations of contemporary guidelines for managing patients at high genetic risk of coronary artery disease. J Am Coll Cardiol. 2020;75:2769–80 Original research demonstrating the added clinical utility of a coronary artery disease polygenic risk score over traditional risk factors.
Khan SS, Cooper R, Greenland P. Do polygenic risk scores improve patient selection for prevention of coronary artery disease? JAMA. 2020;323:614–5.
Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, et al. Heart disease and stroke statistics—2020 update: a report from the American Heart Association. Circulation. 2020;141:e139–596.
Mahmood SS, Levy D, Vasan RS, Wang TJ. The Framingham Heart Study and the epidemiology of cardiovascular disease: a historical perspective. Vol. 383. The Lancet. 2014;383:999–1008.
Dawber TR, Moore FE, Mann GV. Coronary heart disease in the Framingham study. Am J Public Health Nations Health. 1957;47(4 pt 2):4–24.
Muntner P, Colantonio LD, Cushman M, Goff DC, Howard G, Howard VJ, et al. Validation of the atherosclerotic cardiovascular disease Pooled Cohort risk equations. JAMA. 2014;311:1406–15.
Rana JS, Tabada GH, Solomon MD, Lo JC, Jaffe MG, Sung SH, et al. Accuracy of the atherosclerotic cardiovascular risk equation in a large contemporary, multiethnic population. J Am Coll Cardiol. 2016;67:2118–30.
McPherson R, Tybjaerg-Hansen A. Genetics of coronary artery disease. Circ Res. 2016;118:564–78.
Lloyd-Jones DM, Nam BH, D’Agostino RB, Levy D, Murabito JM, Wang TJ, et al. Parental cardiovascular disease as a risk factor for cardiovascular disease in middle-aged adults: a prospective study of parents and offspring. JAMA. 2004;291:2204–11.
Sharifi M, Futema M, Nair D, Humphries SE. Genetic architecture of familial hypercholesterolaemia. Curr Cardiol Rep. 2017;19:44.
• Musunuru K, Kathiresan S. Genetics of common, complex coronary artery disease. Cell. 2019;177:132–45 Review of the genetic architecture of coronary artery disease.
Dudbridge F, Gusnanto A. Estimation of significance thresholds for genomewide association scans. Genet Epidemiol. 2008;32:227–34.
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;114:1241–57.
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;316:1491–3.
Kathiresan S, Melander O, Anevski D, Guiducci C, Burtt NP, Roos C, et al. Polymorphisms associated with cholesterol and risk of cardiovascular events. N Engl J Med. 2008;358:1240–9.
Thanassoulis G, Peloso GM, Pencina MJ, Hoffmann U, Fox CS, Cupples LA, et al. A genetic risk score is associated with incident cardiovascular disease and coronary artery calcium the Framingham Heart Study. Circ Cardiovasc Genet. 2012;5:113–21.
Ripatti S, Tikkanen E, Orho-Melander M, Havulinna AS, Silander K, Sharma A, et al. A multilocus genetic risk score for coronary heart disease: case-control and prospective cohort analyses. Lancet. 2010;376:1393–400.
Tada H, Melander O, Louie JZ, Catanese JJ, Rowland CM, Devlin JJ, et al. Risk prediction by genetic risk scores for coronary heart disease is independent of self-reported family history. Eur Heart J. 2016;37:561–7.
Privé F, Vilhjálmsson BJ, Aschard H, Blum MGB. Making the most of clumping and thresholding for polygenic scores. Am J Hum Genet. 2019;105:1213–21.
Abraham G, Havulinna AS, Bhalala OG, Byars SG, de Livera AM, Yetukuri L, et al. Genomic prediction of coronary heart disease. Eur Heart J. 2016;37:3267–78.
•• Aragam KG, Natarajan P. Polygenic scores to assess atherosclerotic cardiovascular disease risk: clinical perspectives and basic implications. Circ Res. 2020;126:1159–77 Recent review of the genetic basis of atherosclerotic cardiovascular disease and the clinical utility of polygenic risk scores for coronary artery disease.
Hindy G, Aragam K, Chaffin M, Orho-Melander M, Melander O, Khera AV, et al. Integration of a genome-wide polygenic score with ACC/ AHA pooled cohorts equation in prediction of coronary artery disease events in >285,000 participants [abstract]. Circulation. 2019;140:A16565.
• Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;139:e1082–143 2018 US cholesterol guidelines.
Mosley JD, Gupta DK, Tan J, Yao J, Wells QS, Shaffer CM, et al. Predictive accuracy of a polygenic risk score compared with a clinical risk score for incident coronary heart disease. JAMA. 2020;323:627–35.
Natarajan P. Polygenic risk scoring for coronary heart disease: the first risk factor. J Am Coll Cardiol. 2018;72(16):1894–7.
Khera A. Genetic risk, adherence to a healthy lifestyle, and coronary disease. N Engl J Med. 2016;375:2349–58.
Mega JL, Stitziel NO, Smith JG, Chasman DI, Caulfield MJ, Devlin JJ, 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;385:2264–71.
Marston NA, Kamanu FK, Nordio F, Gurmu Y, Roselli C, Sever PS, et al. Predicting benefit from evolocumab therapy in patients with atherosclerotic disease using a genetic risk score. Circulation. 2020;141:616–23.
Natarajan P, Young R, Stitziel NO, Padmanabhan S, Baber U, Mehran R, 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;135:2091–101.
Hu P, Dharmayat KI, Stevens CAT, Sharabiani MTA, Jones RS, Watts GF, et al. Prevalence of familial hypercholesterolemia among the general population and patients with atherosclerotic cardiovascular disease. Circulation. 2020;141:1742–59.
Watts GF, Gidding S, Wierzbicki AS, Toth PP, Alonso R, Brown WV, et al. Integrated guidance on the care of familial hypercholesterolaemia from the International FH Foundation. Int J Cardiol. 2014;171:309–25.
Sjouke B, Kusters DM, Kindt I, Besseling J, Defesche JC, Sijbrands EJG, et al. Homozygous autosomal dominant hypercholesterolaemia in the Netherlands: prevalence, genotype-phenotype relationship, and clinical outcome. Eur Heart J. 2015;36:560–5.
Nordestgaard BG, Chapman MJ, Humphries SE, Ginsberg HN, Masana L, Descamps OS, et al. Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease. Eur Heart J. 2013;34:3478–90.
• Khera A. Whole-genome sequencing to characterize monogenic and polygenic contributions in patients hospitalized with early-onset myocardial infarction. Circulation. 2019;139:1593–602 This article showed that of those with early myocardial infarction, high polygenic risk identified 10 times more individuals than did monogenic risk.
Chan WV, Pearson TA, Bennett GC, Cushman WC, Gaziano TA, Gorman PN, et al. ACC/AHA special report: clinical practice guideline implementation strategies: a summary of systematic reviews by the NHLBI Implementation Science Work Group: a report of the American College of Cardiology/American Heart Association Task Force on clinical practice guidelines. Circulation. 2017;135:e122–37.
Martin AR, Kanai M, Kamatani Y, Okada Y, Neale BM, Daly MJ. Clinical use of current polygenic risk scores may exacerbate health disparities. Nat Genet. 2019;51:584–91.
Lambert SA, Abraham G, Inouye M. Towards clinical utility of polygenic risk scores. Hum Mol Genet. 2019;28:R133–42.
Kullo IJ, Jouni H, Austin EE, Brown SA, Kruisselbrink TM, Isseh IN, et al. Incorporating a genetic risk score into coronary heart disease risk estimates: effect on low-density lipoprotein cholesterol levels (the MI-GENES Clinical Trial). Circulation. 2016;133:1181–8.
Jouni H, Haddad RA, Marroush TS, Brown S-A, Kruisselbrink TM, Austin EE, et al. Shared decision-making following disclosure of coronary heart disease genetic risk: results from a randomized clinical trial. J Investig Med. 2017;65:681–8.
Knowles JW, Assimes TL, Kiernan M, Pavlovic A, Goldstein BA, Yank V, et al. Randomized trial of personal genomics for preventive cardiology. Circ Cardiovasc Genet. 2012;5:368–76.
Johnson HM, Einerson J, Korcarz CE, Aeschlimann SE, Stein JH. Long-term effects of carotid screening on patient outcomes and behaviors. Arch Intern Med. 2011;171:589–91.
O’Malley PG, Feuerstein IM, Taylor AJ. Impact of electron beam tomography, with or without case management, on motivation, behavioral change, and cardiovascular risk profile: a randomized controlled trial. JAMA. 2003;289:2215–23.
McEvoy JW, Blaha MJ, Nasir K, Yoon YE, Choi EK, Cho IS, et al. Impact of coronary computed tomographic angiography results on patient and physician behavior in a low-risk population. Arch Intern Med. 2011;171:1260–8.
Akbarpour S, Khalili D, Zeraati H, Mansournia MA, Ramezankhani A, Fotouhi A. Healthy lifestyle behaviors and control of hypertension among adult hypertensive patients. Sci Rep. 2018;8:8508.
Newson JT, Huguet N, Ramage-Morin PL, McCarthy MJ, Bernie J, Kaplan MS, et al. Health behaviour changes after diagnosis of chronic illness among Canadians aged 50 or older. Health Rep. 2012;23:49–53.
Masters R, Anwar E, Collins B, Cookson R, Capewell S. Return on investment of public health interventions: a systematic review. J Epidemiol Commun Health. 2017;71:827–34.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest
Trevor Hadley and Ali M. Agha have nothing to disclose. Christie M. Ballantyne has received grant/research support through his institution from Abbott Diagnostic, Akcea, Amgen, Esperion, Novartis, Regeneron, and Roche Diagnostic and is a consultant for Abbott Diagnostics, Akcea, Althera, Amarin, Amgen, Arrowhead, AstraZeneca, Corvidia, Denka Seiken, Esperion, Gilead, Janssen, Matinas BioPharma Inc, New Amsterdam, Novartis, Novo Nordisk, Pfizer, Regeneron, Roche Diagnostic and Sanofi-Synthelabo. He has received grant/research support through his institution from the National Institutes of Health, the American Heart Association, and the American Diabetes Association.
Human and Animal Rights and Informed Consent
This article does not contain any studies with human or animal subjects performed by any of the authors.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This article is part of the Topical Collection on Evidence-Based Medicine, Clinical Trials and Their Interpretations
Rights and permissions
About this article
Cite this article
Hadley, T.D., Agha, A.M. & Ballantyne, C.M. How Do We Incorporate Polygenic Risk Scores in Cardiovascular Disease Risk Assessment and Management?. Curr Atheroscler Rep 23, 28 (2021). https://doi.org/10.1007/s11883-021-00915-6
Accepted:
Published:
DOI: https://doi.org/10.1007/s11883-021-00915-6