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Incremental Value of Polygenic Risk Scores in Primary Prevention of Coronary Heart DiseaseA Review

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Abstract

Importance  Risk prediction for coronary heart disease (CHD) is a cornerstone of primary prevention strategies. Polygenic risk scores (PRSs) have emerged as a new approach to predict risk in asymptomatic people. Polygenic risk scores for CHD have been studied in several populations, but there is lack of agreement about the incremental value of PRS beyond traditional risk factor scores in the primary prevention of CHD.

Observations  This narrative review critically appraised the 5 most highly cited studies published through 2021 that also included a large number (>45 000) of single-nucleotide variations (formerly single-nucleotide polymorphisms) and evaluated the incremental value of PRS in CHD risk prediction according to published PRS reporting standards. The cohorts studied included the Atherosclerosis Risk in Communities Study, FINRISK, the Framingham Heart Study, the Multi-Ethnic Study of Atherosclerosis, and the UK Biobank. All of the studies focused predominantly on populations of European ancestry. The hazard ratio per standard deviation of PRS ranged from 1.24 (95% CI, 1.15-1.34) to 1.74 (95% CI, 1.61-1.86). The C statistic for PRS alone ranged from 0.549 to 0.623. The change in C statistic when PRS was added to a standard risk factor model ranged between −0.001 to +0.021. Net reclassification index was reported in 4 of the 5 studies and varied from 0.001 to 0.097. At a sensitivity (true-positive rate) of 90%, positive predictive values ranged from 1.8% to 16.6%, and false-positive rates ranged from 77.1% to 85.7%.

Conclusions and Relevance  In this review, PRS was significantly associated with CHD risk in all studies. The degree of improvement in C statistic and the net reclassification indexes when PRS was added to traditional risk scores ranged from negligible to modest. Based on established metrics to assess risk prediction scores, the addition of PRS to traditional risk scores does not appear to provide meaningful improvements in clinical decision-making in primary prevention populations.

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Article Information

Accepted for Publication: June 6, 2022.

Published Online: August 22, 2022. doi:10.1001/jamainternmed.2022.3171

Corresponding Author: Philip Greenland, MD, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 N Lake Shore Dr, Ste 1400, Chicago, IL 60611 (p-greenland@northwestern.edu).

Author Contributions: Drs Greenland and Khan had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: All authors.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Groenendyk.

Administrative, technical, or material support: Greenland, Khan.

Supervision: Greenland, Khan.

Conflict of Interest Disclosures: Dr Greenland reported receiving grants from the National Institutes of Health and the American Heart Association outside the submitted work. Dr Khan reported receiving grants from the American Heart Association (19TPA34890060) and the National Institutes of Health (R01HL159250, R01HL161514, and U01HL160279) outside the submitted work. No other disclosures were reported.

References
1.
Zeinomar  N , Chung  WK .  Cases in precision medicine: the role of polygenic risk scores in breast cancer risk assessment.   Ann Intern Med. 2021;174(3):408-412. doi:10.7326/M20-5874 PubMedGoogle ScholarCrossref
2.
Green  ED , Gunter  C , Biesecker  LG ,  et al.  Strategic vision for improving human health at the forefront of genomics.   Nature. 2020;586(7831):683-692. doi:10.1038/s41586-020-2817-4 PubMedGoogle ScholarCrossref
3.
Lambert  SA , Abraham  G , Inouye  M .  Towards clinical utility of polygenic risk scores.   Hum Mol Genet. 2019;28(R2):R133-R142. doi:10.1093/hmg/ddz187 PubMedGoogle ScholarCrossref
4.
Arnold  N , Koenig  W .  Polygenic risk score: clinically useful tool for prediction of cardiovascular disease and benefit from lipid-lowering therapy?   Cardiovasc Drugs Ther. 2021;35(3):627-635. doi:10.1007/s10557-020-07105-7 PubMedGoogle ScholarCrossref
5.
German  CA , Shapiro  MD .  Polygenic risk scores to identify CVD risk and tailor therapy: hope or hype?   Curr Atheroscler Rep. 2021;23(9):47. doi:10.1007/s11883-021-00950-3 PubMedGoogle ScholarCrossref
6.
Klarin  D , Natarajan  P .  Clinical utility of polygenic risk scores for coronary artery disease.   Nat Rev Cardiol. 2022;19(5):291-301. doi:10.1038/s41569-021-00638-wPubMedGoogle ScholarCrossref
7.
McPherson  R .  2018 George Lyman Duff Memorial Lecture: genetics and genomics of coronary artery disease: a decade of progress.   Arterioscler Thromb Vasc Biol. 2019;39(10):1925-1937. doi:10.1161/ATVBAHA.119.311392 PubMedGoogle ScholarCrossref
8.
Inouye  M , Abraham  G , Nelson  CP ,  et al; UK Biobank CardioMetabolic Consortium CHD Working Group.  Genomic risk prediction of coronary artery disease in 480,000 adults: implications for primary prevention.   J Am Coll Cardiol. 2018;72(16):1883-1893. doi:10.1016/j.jacc.2018.07.079 PubMedGoogle ScholarCrossref
9.
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 PubMedGoogle ScholarCrossref
10.
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. doi:10.1001/jama.2019.21782 PubMedGoogle ScholarCrossref
11.
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. doi:10.1001/jama.2019.22241 PubMedGoogle ScholarCrossref
12.
Visseren  FLJ , Mach  F , Smulders  YM ,  et al; ESC National Cardiac Societies; ESC Scientific Document Group.  2021 ESC Guidelines on cardiovascular disease prevention in clinical practice.   Eur Heart J. 2021;42(34):3227-3337. doi:10.1093/eurheartj/ehab484 PubMedGoogle ScholarCrossref
13.
Arnett  DK , Blumenthal  RS , Albert  MA ,  et al.  2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.   J Am Coll Cardiol. 2019;74(10):e177-e232. doi:10.1016/j.jacc.2019.03.010 PubMedGoogle ScholarCrossref
14.
Hlatky  MA , Greenland  P , Arnett  DK ,  et al; American Heart Association Expert Panel on Subclinical Atherosclerotic Diseases and Emerging Risk Factors and the Stroke Council.  Criteria for evaluation of novel markers of cardiovascular risk: a scientific statement from the American Heart Association.   Circulation. 2009;119(17):2408-2416. doi:10.1161/CIRCULATIONAHA.109.192278 PubMedGoogle ScholarCrossref
15.
Jakobsdottir  J , Gorin  MB , Conley  YP , Ferrell  RE , Weeks  DE .  Interpretation of genetic association studies: markers with replicated highly significant odds ratios may be poor classifiers.   PLoS Genet. 2009;5(2):e1000337. doi:10.1371/journal.pgen.1000337 PubMedGoogle ScholarCrossref
16.
Wald  NJ , Morris  JK .  Assessing risk factors as potential screening tests: a simple assessment tool.   Arch Intern Med. 2011;171(4):286-291. doi:10.1001/archinternmed.2010.378 PubMedGoogle ScholarCrossref
17.
Wald  NJ , Old  R .  The illusion of polygenic disease risk prediction.   Genet Med. 2019;21(8):1705-1707. doi:10.1038/s41436-018-0418-5 PubMedGoogle ScholarCrossref
18.
Thanassoulis  G , Peloso  GM , Pencina  MJ ,  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(1):113-121. doi:10.1161/CIRCGENETICS.111.961342 PubMedGoogle ScholarCrossref
19.
Paynter  NP , Chasman  DI , Paré  G ,  et al.  Association between a literature-based genetic risk score and cardiovascular events in women.   JAMA. 2010;303(7):631-637. doi:10.1001/jama.2010.119 PubMedGoogle ScholarCrossref
20.
Agbaedeng  TA , Noubiap  JJ , Mofo Mato  EP ,  et al.  Polygenic risk score and coronary artery disease: a meta-analysis of 979,286 participant data.   Atherosclerosis. 2021;333:48-55. doi:10.1016/j.atherosclerosis.2021.08.020 PubMedGoogle ScholarCrossref
21.
Muse  ED , Chen  S-F , Torkamani  A .  Monogenic and polygenic models of coronary artery disease.   Curr Cardiol Rep. 2021;23(8):107. doi:10.1007/s11886-021-01540-0 PubMedGoogle ScholarCrossref
22.
Medical Screening Society. Accessed January 20, 2022. https://www.medicalscreeningsociety.com/
23.
Wald  NJ , Hackshaw  AK , Frost  CD .  When can a risk factor be used as a worthwhile screening test?   BMJ. 1999;319(7224):1562-1565. doi:10.1136/bmj.319.7224.1562 PubMedGoogle ScholarCrossref
24.
Wand  H , Lambert  SA , Tamburro  C ,  et al.  Improving reporting standards for polygenic scores in risk prediction studies.   Nature. 2021;591(7849):211-219. doi:10.1038/s41586-021-03243-6 PubMedGoogle ScholarCrossref
25.
Abraham  G , Havulinna  AS , Bhalala  OG ,  et al.  Genomic prediction of coronary heart disease.   Eur Heart J. 2016;37(43):3267-3278. doi:10.1093/eurheartj/ehw450 PubMedGoogle ScholarCrossref
26.
Mars  N , Koskela  JT , Ripatti  P ,  et al; FinnGen.  Polygenic and clinical risk scores and their impact on age at onset and prediction of cardiometabolic diseases and common cancers.   Nat Med. 2020;26(4):549-557. doi:10.1038/s41591-020-0800-0 PubMedGoogle ScholarCrossref
27.
Pepe  MS , Janes  H , Longton  G , Leisenring  W , Newcomb  P .  Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker.   Am J Epidemiol. 2004;159(9):882-890. doi:10.1093/aje/kwh101 PubMedGoogle ScholarCrossref
28.
Pencina  MJ , D’Agostino  RB  Sr , D’Agostino  RB  Jr , Vasan  RS .  Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond.   Stat Med. 2008;27(2):157-172. doi:10.1002/sim.2929 PubMedGoogle ScholarCrossref
29.
Paynter  NP , Ridker  PM , Chasman  DI .  Are genetic tests for atherosclerosis ready for routine clinical use?   Circ Res. 2016;118(4):607-619. doi:10.1161/CIRCRESAHA.115.306360 PubMedGoogle ScholarCrossref
30.
Janssens  ACJW , Joyner  MJ .  Polygenic risk scores that predict common diseases using millions of single nucleotide polymorphisms: is more, better?   Clin Chem. 2019;65(5):609-611. doi:10.1373/clinchem.2018.296103 PubMedGoogle ScholarCrossref
31.
Martens  FK , Tonk  ECM , Janssens  ACJW .  Evaluation of polygenic risk models using multiple performance measures: a critical assessment of discordant results.   Genet Med. 2019;21(2):391-397. doi:10.1038/s41436-018-0058-9 PubMedGoogle ScholarCrossref
32.
Weale  ME , Riveros-Mckay  F , Selzam  S ,  et al.  Validation of an integrated risk tool, including polygenic risk score, for atherosclerotic cardiovascular disease in multiple ethnicities and ancestries.   Am J Cardiol. 2021;148:157-164. doi:10.1016/j.amjcard.2021.02.032 PubMedGoogle ScholarCrossref
33.
Lu  X , Liu  Z , Cui  Q ,  et al.  A polygenic risk score improves risk stratification of coronary artery disease: a large-scale prospective Chinese cohort study.   Eur Heart J. 2022;43(18):1702-1711. doi:10.1093/eurheartj/ehac093 PubMedGoogle ScholarCrossref
34.
Hasbani  NR , Ligthart  S , Brown  MR ,  et al.  American Heart Association’s Life’s Simple 7: lifestyle recommendations, polygenic risk, and lifetime risk of coronary heart disease.   Circulation. 2022;145(11):808-818. doi:10.1161/CIRCULATIONAHA.121.053730 PubMedGoogle ScholarCrossref
35.
Pencina  MJ , Navar  AM , Wojdyla  D ,  et al.  Quantifying importance of major risk factors for coronary heart disease.   Circulation. 2019;139(13):1603-1611. doi:10.1161/CIRCULATIONAHA.117.031855 PubMedGoogle ScholarCrossref
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