Clinical utility of polygenic risk scores for coronary artery disease
Open accessAbstract
Over the past decade, substantial progress has been made in the discovery of alleles contributing to the risk of coronary artery disease. In addition to providing causal insights into disease, these endeavours have yielded and enabled the refinement of polygenic risk scores. These scores can be used to predict incident coronary artery disease in multiple cohorts and indicate the clinical response to some preventive therapies in post hoc analyses of clinical trials. These observations and the widespread ability to calculate polygenic risk scores from direct-to-consumer and health-care-associated biobanks have raised many questions about responsible clinical adoption. In this Review, we describe technical and downstream considerations for the derivation and validation of polygenic risk scores and current evidence for their efficacy and safety. We discuss the implementation of these scores in clinical medicine for uses including risk prediction and screening algorithms for coronary artery disease, prioritization of patient subgroups that are likely to derive benefit from treatment, and efficient prospective clinical trial designs.
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Digital clinical trials could leverage multiple sources of participants' data to enable automatic phenotyping and subgrouping, which could be useful for adaptive clinical trial designs that use ongoing results to modify the trial in real time.
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Mach, F., Baigent, C., Catapano, A. L., Koskinas, K. C., Casula, M., Badimon, L., Chapman, M. J., De Backer, G. G., Delgado, V., Ference, B. A., et al. (2020) · European Heart Journal · doi:10.1093/eurheartj/ehz455 · Cited by 8,961 · see citing works
Genetics of Food Intake Self-Regulation in Childhood: Literature Review and Research Opportunities
Faith, M. S., Carnell, S., & Kral, T. V. E. (2013) · Human Heredity · doi:10.1159/000353879 · Cited by 7,628 · see citing works
Stone, N. J., Robinson, J. G., Lichtenstein, A. H., Bairey Merz, C. N., Blum, C. B., Eckel, R. H., Goldberg, A. C., Gordon, D., Levy, D., Lloyd-Jones, D. M., et al. (2014) · Circulation · doi:10.1161/01.cir.0000437738.63853.7a · Cited by 7,081 · see citing works
Grundy, S. M., Stone, N. J., Bailey, A. L., Beam, C., Birtcher, K. K., Blumenthal, R. S., Braun, L. T., de Ferranti, S., Faiella-Tommasino, J., Forman, D. E., et al. (2019) · Circulation · doi:10.1161/cir.0000000000000625 · Cited by 6,185 · see citing works
Evolocumab and Clinical Outcomes in Patients with Cardiovascular Disease
Sabatine, M. S., Giugliano, R. P., Keech, A. C., Honarpour, N., Wiviott, S. D., Murphy, S. A., Kuder, J. F., Wang, H., Liu, T., Wasserman, S. M., et al. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1615664 · Cited by 6,138 · see citing works
Mach, F., Baigent, C., Catapano, A. L., Koskinas, K. C., Casula, M., Badimon, L., Chapman, M. J., De Backer, G. G., Delgado, V., Ference, B. A., et al. (2019) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2019.08.014 · Cited by 4,854 · see citing works
Optimal Medical Therapy with or without PCI for Stable Coronary Disease
Boden, W. E., O'Rourke, R. A., Teo, K. K., Hartigan, P. M., Maron, D. J., Kostuk, W. J., Knudtson, M., Dada, M., Casperson, P., Harris, C. L., et al. (2007) · New England Journal of Medicine · doi:10.1056/nejmoa070829 · Cited by 4,699 · see citing works
(2019) · doi:10.1161/cir.0000000000000677 · Cited by 4,501 · see citing works
Endarterectomy for Asymptomatic Carotid Artery Stenosis
WALKER, M. D. (1995) · JAMA · doi:10.1001/jama.1995.03520420037035 · Cited by 4,435 · see citing works
Alirocumab and Cardiovascular Outcomes after Acute Coronary Syndrome
Schwartz, G. G., Steg, P. G., Szarek, M., Bhatt, D. L., Bittner, V. A., Diaz, R., Edelberg, J. M., Goodman, S. G., Hanotin, C., Harrington, R. A., et al. (2018) · New England Journal of Medicine · doi:10.1056/nejmoa1801174 · Cited by 3,634 · see citing works
Biological, clinical and population relevance of 95 loci for blood lipids
Teslovich, T. M., Musunuru, K., Smith, A. V., Edmondson, A. C., Stylianou, I. M., Koseki, M., Pirruccello, J. P., Ripatti, S., Chasman, D. I., Willer, C. J., et al. (2010) · Nature · doi:10.1038/nature09270 · Cited by 3,487 · see citing works
Stenting versus Endarterectomy for Treatment of Carotid-Artery Stenosis
Brott, T. G., Hobson, R. W., Howard, G., Roubin, G. S., Clark, W. M., Brooks, W. H., Mackey, A., Hill, M. D., Leimgruber, P. P., Sheffet, A. J., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa0912321 · Cited by 3,001 · see citing works
Coronary Calcium as a Predictor of Coronary Events in Four Racial or Ethnic Groups
Detrano, R., Guerci, A. D., Carr, J. J., Bild, D. E., Burke, G., Folsom, A. R., Liu, K., Shea, S., Szklo, M., Bluemke, D. A., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa072100 · Cited by 2,989 · see citing works
Willer (2013) · doi:10.1038/ng.2797 · Cited by 2,983 · see citing works
Khera, A. V., Chaffin, M., Aragam, K. G., Haas, M. E., Roselli, C., Choi, S. H., Natarajan, P., Lander, E. S., Lubitz, S. A., Ellinor, P. T., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0183-z · Cited by 2,953 · see citing works
Self-citationCollaborators, C. T. T. (. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60367-5 · Cited by 2,833 · see citing works
Grundy, S. M., Stone, N. J., Bailey, A. L., Beam, C., Birtcher, K. K., Blumenthal, R. S., Braun, L. T., de Ferranti, S., Faiella-Tommasino, J., Forman, D. E., et al. (2019) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.11.003 · Cited by 2,691 · see citing works
Halliday, A. W., Mansfield, A. O., Marro, J., Peto, C., Peto, R., Potter, J. F., & Thomas, D. J. (2004) · The Lancet · doi:10.1016/s0140-6736(04)16146-1 · Cited by 2,497 · see citing works
Initial Invasive or Conservative Strategy for Stable Coronary Disease
Maron, D. J., Hochman, J. S., Reynolds, H. R., Bangalore, S., O’Brien, S. M., Boden, W. E., CHAITMAN, B. R., Senior, R., López-Sendón, J., Alexander, K. P., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa1915922 · Cited by 2,454 · see citing works
A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease
the CARDIoGRAMplusC4D Consortium (2015) · Nature Genetics · doi:10.1038/ng.3396 · Cited by 2,447 · see citing works
The “All of Us” Research Program
The All of Us Research Program Investigators (2019) · New England Journal of Medicine · doi:10.1056/nejmsr1809937 · Cited by 2,440 · see citing works
Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program
Taliun, D., Harris, D. N., Kessler, M. D., Carlson, J., Szpiech, Z. A., Torres, R., Taliun, S. A. G., Corvelo, A., Gogarten, S. M., Kang, H. M., et al. (2021) · Nature · doi:10.1038/s41586-021-03205-y · Cited by 2,213 · see citing works
Self-citationGenomewide Association Analysis of Coronary Artery Disease
Samani, N. J., Erdmann, J., Hall, A. S., Hengstenberg, C., Mangino, M., Mayer, B., Dixon, R. J., Meitinger, T., Braund, P., Wichmann, H.-E., et al. (2007) · New England Journal of Medicine · doi:10.1056/nejmoa072366 · Cited by 2,044 · see citing works
Tutorial: a guide to performing polygenic risk score analyses
Choi, S. W., Mak, T. S. H., & O’Reilly, P. F. (2020) · Nature Protocols · doi:10.1038/s41596-020-0353-1 · Cited by 1,913 · see citing works
23andMe Research Team, Liu, M., Psychiatry, H. A.-I., Jiang, Y., Wedow, R., Li, Y., Brazel, D. M., Chen, F., Datta, G., Davila-Velderrain, J., et al. (2019) · Nature Genetics · doi:10.1038/s41588-018-0307-5 · Cited by 1,896 · see citing works
2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease
Arnett, D. K., Blumenthal, R. S., Albert, M. A., Buroker, A. B., Goldberger, Z. D., Hahn, E. J., Himmelfarb, C. D., Khera, A., Lloyd-Jones, D., McEvoy, J. W., et al. (2019) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2019.03.010 · Cited by 1,896 · see citing works
Tunis (2003) · doi:10.1001/jama.290.12.1624 · Cited by 1,724 · see citing works
A Common Variant on Chromosome 9p21 Affects the Risk of Myocardial Infarction
Helgadottir, A., Thorleifsson, G., Manolescu, A., Gretarsdottir, S., Blondal, T., Jonasdottir, A., Jonasdottir, A., Sigurdsson, A., Baker, A., Palsson, A., et al. (2007) · Science · doi:10.1126/science.1142842 · Cited by 1,594 · see citing works
A Common Allele on Chromosome 9 Associated with Coronary Heart Disease
McPherson, R., Pertsemlidis, A., Kavaslar, N., Stewart, A., Roberts, R., Cox, D. R., Hinds, D. A., Pennacchio, L. A., Tybjaerg-Hansen, A., Folsom, A. R., et al. (2007) · Science · doi:10.1126/science.1142447 · Cited by 1,587 · see citing works
Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease
Khera, A. V., Emdin, C. A., Drake, I., Natarajan, P., Bick, A. G., Cook, N. R., Chasman, D. I., Baber, U., Mehran, R., Rader, D. J., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1605086 · Cited by 1,460 · see citing works
Self-citationFord, I., & Norrie, J. (2016) · New England Journal of Medicine · doi:10.1056/nejmra1510059 · Cited by 1,405 · see citing works
WALKER, M. D., Marler, J. R., Goldstein, M., Grady, P. A., Toole, J. F., Baker, W. H., Castaldo, J., Chambless, L. E., Moore, W. S., Robertson, J. T., et al. (1995) · JAMA · doi:10.1001/jama.273.18.1421 · Cited by 1,326 · see citing works
Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores
Vilhjálmsson, B. J., Yang, J., Finucane, H. K., Gusev, A., Lindström, S., Ripke, S., Genovese, G., Loh, P.-R., Bhatia, G., Do, R., et al. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.09.001 · Cited by 1,303 · see citing works
Rare and common variants: twenty arguments
Gibson, G. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3118 · Cited by 1,278 · see citing works
Genetic Susceptibility to Death from Coronary Heart Disease in a Study of Twins
Marenberg, M. E., RISCH, N. J., Berkman, L. F., Floderus, B., & Fairé, U. D. (1994) · New England Journal of Medicine · doi:10.1056/nejm199404143301503 · Cited by 1,256 · see citing works
Anderson, T. J., Grégoire, J., Pearson, G. J., Barry, A. R., Couture, P., Dawes, M., Francis, G. A., Genest, J., Grover, S., Gupta, M., et al. (2016) · Canadian Journal of Cardiology · doi:10.1016/j.cjca.2016.07.510 · Cited by 1,173 · see citing works
PRSice: Polygenic Risk Score software
Euesden, J., Lewis, C. M., & O’Reilly, P. F. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu848 · Cited by 1,149 · see citing works
Genome-wide meta-analyses identify multiple loci associated with smoking behavior
The Tobacco and Genetics Consortium (2010) · Nature Genetics · doi:10.1038/ng.571 · Cited by 1,098 · see citing works
Million Veteran Program: A mega-biobank to study genetic influences on health and disease
Gaziano, J. M., Concato, J., Brophy, M., Fiore, L., Pyarajan, S., Breeling, J., Whitbourne, S., Deen, J., Shannon, C., Humphries, D., et al. (2016) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.09.016 · Cited by 1,055 · see citing works
Al-Lamee, R. K., Thompson, D., Dehbi, H., Sen, S., Tang, K. H., Davies, J., Keeble, T., Mielewczik, M., Kaprielian, R., Malik, I. S., et al. (2017) · The Lancet · doi:10.1016/s0140-6736(17)32714-9 · Cited by 1,030 · see citing works
Khera, A. V., Won, H.-H., Peloso, G. M., Lawson, K. S., Bartz, T. M., Deng, X., van Leeuwen, E. M., Natarajan, P., Emdin, C. A., Bick, A. G., et al. (2016) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2016.03.520 · Cited by 942 · see citing works
Self-citationMcClelland, R. L., Chung, H., Detrano, R., Post, W., & Kronmal, R. A. (2006) · Circulation · doi:10.1161/circulationaha.105.580696 · Cited by 885 · see citing works
Pearson, G. J., Thanassoulis, G., Anderson, T. J., Barry, A. R., Couture, P., Dayan, N., Francis, G. A., Genest, J. J., Grégoire, J. C., Grover, S. A., et al. (2021) · Canadian Journal of Cardiology · doi:10.1016/j.cjca.2021.03.016 · Cited by 870 · see citing works
The “All of Us” Research Program
Sullivan, F., McKinstry, B., & Vasishta, S. (2019) · New England Journal of Medicine · doi:10.1056/nejmc1912496 · Cited by 855 · see citing works
Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults
Inouye, M., Abraham, G., Nelson, C. P., Wood, A., Sweeting, M. J., Dudbridge, F., Lai, F. Y., Kaptoge, S. K., Brożyńska, M., Wang, T., et al. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.07.079 · Cited by 814 · see citing works
New loci associated with kidney function and chronic kidney disease
Köttgen, A., Pattaro, C., Böger, C. A., Fuchsberger, C., Olden, M., Glazer, N. L., Parsa, A., Gao, X., Yang, Q., Smith, A. V., et al. (2010) · Nature Genetics · doi:10.1038/ng.568 · Cited by 801 · see citing works
Pe'er, I., Yelensky, R., Altshuler, D., & Daly, M. J. (2008) · Genetic Epidemiology · doi:10.1002/gepi.20303 · Cited by 783 · see citing works
Vujkovic, M., Keaton, J. M., Lynch, J. A., Miller, D. R., Zhou, J., Tcheandjieu, C., Huffman, J. E., Assimes, T. L., Lorenz, K., Zhu, X., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0637-y · Cited by 741 · see citing works
Self-citationAragam, K. G., Jiang, T., Goel, A., Kanoni, S., Wolford, B. N., Atri, D. S., Weeks, E. M., Wang, M., Hindy, G., Zhou, W., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01233-6 · Cited by 721 · see citing works
Improving polygenic prediction in ancestrally diverse populations
Ruan, Y., Lin, Y.-F., Feng, Y.-C. A., Chen, C.-Y., Lam, M., Guo, Z., Initiatives, S. G. A., Ahn, Y. M., Akiyama, K., Arai, M., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01054-7 · Cited by 707 · see citing works
Mega, J. L., Stitziel, N. O., Smith, J. G., Chasman, D. I., Caulfield, M. J., Devlin, J. J., Nordio, F., Hyde, C. L., Cannon, C. P., Sacks, F. M., et al. (2015) · The Lancet · doi:10.1016/s0140-6736(14)61730-x · Cited by 704 · see citing works
Herman, W. H., Hoerger, T. J., Brandle, M., Hicks, K., Sorensen, S., Zhang, P., Hamman, R. F., Ackermann, R. T., Engelgau, M. M., Ratner, R. E., et al. (2005) · Annals of Internal Medicine · doi:10.7326/0003-4819-142-5-200503010-00007 · Cited by 703 · see citing works
A brief history of human disease genetics
Claussnitzer, M., Cho, J. H., Collins, R., Cox, N. J., Dermitzakis, E. T., Hurles, M. E., Kathiresan, S., Kenny, E. E., Lindgren, C. M., MacArthur, D. G., et al. (2020) · Nature · doi:10.1038/s41586-019-1879-7 · Cited by 697 · see citing works
the eMERGE Team, McCarty, C. A., Chisholm, R. L., Chute, C. G., Kullo, I. J., Jarvik, G. P., Larson, E. B., Li, R., Masys, D. R., Ritchie, M. D., et al. (2011) · BMC Medical Genomics · doi:10.1186/1755-8794-4-13 · Cited by 692 · see citing works
The Polygenic Score Catalog as an open database for reproducibility and systematic evaluation
Lambert, S. A., Gil, L., Jupp, S., Ritchie, S. C., Xu, Y., Buniello, A., McMahon, A., Abraham, G., Chapman, M., Parkinson, H., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00783-5 · Cited by 690 · see citing works
Effect of PCI on quality of life in patients with stable coronary disease.
Weintraub, W., Spertus, J., Kolm, P., Maron, D., Zhang, Z.-F., Jurkovitz, C., Zhang, W., Hartigan, P., Lewis, C., Veledar, E., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa072771 · Cited by 673 · see citing works
Said, M. A., Verweij, N., & van der Harst, P. (2018) · JAMA Cardiology · doi:10.1001/jamacardio.2018.1717 · Cited by 645 · see citing works
Clinical Genetic Testing for Familial Hypercholesterolemia
Sturm, A. C., Knowles, J. W., Gidding, S. S., Ahmad, Z., Ahmed, C. D., Ballantyne, C. M., Baum, S. J., Bourbon, M., Carrié, A., Cuchel, M., et al. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.05.044 · Cited by 619 · see citing works
Genetics of blood lipids among ~300,000 multi-ethnic participants of the Million Veteran Program
Klarin, D. M., Program, T. V. M. V., Damrauer, S. M., Cho, K., Sun, Y. V., Teslovich, T. M., Honerlaw, J. P., GAGNON, D. R., DuVall, S. L., Li, J., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0222-9 · Cited by 594 · see citing works
Self-citationNatarajan, P., Young, R., Stitziel, N. O., Padmanabhan, S., Baber, U., Mehran, R., Sartori, S., Fuster, V., Reilly, D. F., Butterworth, A., et al. (2017) · Circulation · doi:10.1161/circulationaha.116.024436 · Cited by 570 · see citing works
Self-citationMonogenic hypercholesterolemia: new insights in pathogenesis and treatment
Rader, D. J., Cohen, J. C., & Hobbs, H. H. (2003) · Journal of Clinical Investigation · doi:10.1172/jci18925 · Cited by 555 · see citing works
Hu, P., Dharmayat, K., Stevens, C. A. T., Sharabiani, M. T. A., Jones, R., Watts, G. F., Genest, J. J., Ray, K. K., & Vallejo‐Vaz, A. J. (2020) · Circulation · doi:10.1161/circulationaha.119.044795 · Cited by 554 · see citing works
Warren, H. R., Εvangelou, Ε., Cabrera, C. P., Gao, H., Ren, M., Mifsud, B., Ntalla, I., Surendran, P., Liu, C., Cook, J. P., et al. (2017) · Nature Genetics · doi:10.1038/ng.3768 · Cited by 545 · see citing works
Quality control and conduct of genome-wide association meta-analyses
Winkler, T. W., Day, F. R., Croteau‐Chonka, D. C., Wood, A. R., Locke, A. E., Mägi, R., Ferreira, T., Fall, T., Graff, M., Justice, A. E., et al. (2014) · Nature Protocols · doi:10.1038/nprot.2014.071 · Cited by 502 · see citing works
Personalized evidence based medicine: predictive approaches to heterogeneous treatment effects
Kent, D. M., Steyerberg, E. W., & Klaveren, D. V. (2018) · BMJ · doi:10.1136/bmj.k4245 · Cited by 487 · see citing works
FinnGen, Mars, N., Koskela, J. T., Ripatti, P., Kiiskinen, T., Havulinna, A. S., Lindbohm, J. V., Ahola‐Olli, A., Kurki, M., Karjalainen, J. M., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0800-0 · Cited by 486 · see citing works
Polygenic scores via penalized regression on summary statistics
Mak, T. S. H., Porsch, R. M., Choi, S. W., Zhou, X., & Sham, P. C. (2017) · Genetic Epidemiology · doi:10.1002/gepi.22050 · Cited by 472 · see citing works
Elliott, J., Bodinier, B., Bond, T. A., Chadeau‐Hyam, M., Εvangelou, Ε., Moons, K. G. M., Dehghan, A., Muller, D. C., Elliott, P., & Tzoulaki, I. (2020) · JAMA · doi:10.1001/jama.2019.22241 · Cited by 471 · see citing works
Improving reporting standards for polygenic scores in risk prediction studies
Wand, H., Lambert, S. A., Tamburro, C. P., Iacocca, M. A., O’Sullivan, J. W., Sillari, C. H., Kullo, I. J., Rowley, R. K., Dron, J. S., Brockman, D., et al. (2021) · Nature · doi:10.1038/s41586-021-03243-6 · Cited by 470 · see citing works
Monogenic hypercholesterolemia: new insights in pathogenesis and treatment
Rader, D. J., Cohen, J. C., & Hobbs, H. H. (2003) · Journal of Clinical Investigation · doi:10.1172/jci200318925 · Cited by 468 · see citing works
Pereira, N. L., Farkouh, M. E., So, D. Y. F., Lennon, R. J., Geller, N. L., Mathew, V., Bell, M. R., Bae, J., Jeong, M. H., Chavez, I. J., et al. (2020) · JAMA · doi:10.1001/jama.2020.12443 · Cited by 430 · see citing works
Ehret, G., Ferreira, T. C., Chasman, D. I., Jackson, A., Schmidt, E. M., Johnson, T., Þorleifsson, G., Luan, J., Donnelly, L. A., Kanoni, S., et al. (2016) · Nature Genetics · doi:10.1038/ng.3667 · Cited by 411 · see citing works
Screening for Abdominal Aortic Aneurysm
US Preventive Services Task Force, Owens, D. K., Davidson, K. W., Krist, A. H., Barry, M. J., Cabana, M. D., Caughey, A. B., Doubeni, C. A., Epling, J. W., Kubik, M., et al. (2019) · JAMA · doi:10.1001/jama.2019.18928 · Cited by 374 · see citing works
Moore, T. J., Zhang, H., Anderson, G., & Alexander, G. C. (2018) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2018.3931 · Cited by 356 · see citing works
Koyama, S., Ito, K., Terao, C., Akiyama, M., Horikoshi, M., Momozawa, Y., Matsunaga, H., Ieki, H., Ozaki, K., Onouchi, Y., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0705-3 · Cited by 349 · see citing works
Mosley, J. D., Gupta, D. K., Tan, J., Yao, J., Wells, Q. S., Shaffer, C. M., Kundu, S., Robinson‐Cohen, C., Psaty, B. M., Rich, S. S., et al. (2020) · JAMA · doi:10.1001/jama.2019.21782 · Cited by 332 · see citing works
Khera, A. V., Chaffin, M., Zekavat, S. M., Collins, R. L., Roselli, C., Natarajan, P., Lichtman, J. H., D’Onofrio, G., Mattera, J., Dreyer, R., et al. (2019) · Circulation · doi:10.1161/circulationaha.118.035658 · Cited by 315 · see citing works
Self-citationTada, H., Melander, O., Louie, J. Z., Catanese, J. J., Rowland, C. M., Devlin, J. J., Kathiresan, S., & Shiffman, D. (2016) · European Heart Journal · doi:10.1093/eurheartj/ehv462 · Cited by 285 · see citing works
Multiethnic polygenic risk scores improve risk prediction in diverse populations
Márquez‐Luna, C., Loh, P., & Price, A. L. (2017) · Genetic Epidemiology · doi:10.1002/gepi.22083 · Cited by 280 · see citing works
Kowalski, M. H., Qian, H., Hou, Z., Rosen, J. D., Tapia, A. L., Shan, Y., Jain, D., Argos, M., Arnett, D. K., Avery, C. L., et al. (2019) · PLoS Genetics · doi:10.1371/journal.pgen.1008500 · Cited by 278 · see citing works
Schermerhorn, M. L., Liang, P., Eldrup-Jørgensen, J., Cronenwett, J. L., Nolan, B. W., Kashyap, V. S., Wang, G. J., Motaganahalli, R. L., & Malas, M. B. (2019) · JAMA · doi:10.1001/jama.2019.18441 · Cited by 270 · see citing works
Kullo, I. J., Jouni, H., Austin, E. E., Brown, S.-A., Kruisselbrink, T. M., Isseh, I. N., Haddad, R. A., Marroush, T. S., Shameer, K., Olson, J. E., et al. (2016) · Circulation · doi:10.1161/circulationaha.115.020109 · Cited by 267 · see citing works
Damask, A., Steg, P. G., Schwartz, G. G., Szarek, M. J., Hagström, E., Badimón, L., Chapman, M. J., Boileau, C., Tsimikas, S., Ginsberg, H. N., et al. (2019) · Circulation · doi:10.1161/circulationaha.119.044434 · Cited by 239 · see citing works
Klarin, D. M., Program, V. A. M. V., Busenkell, E., Judy, R., Lynch, J. A., Levin, M. G., Haessler, J., Aragam, K. G., Chaffin, M. D., Haas, M., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0519-3 · Cited by 236 · see citing works
Self-citationMarston, N., Kamanu, F., Nordio, F., Gurmu, Y., Roselli, C., Sever, P., Pedersen, T. R., KEECH, A. C., Wang, H., Pineda, A. L., et al. (2019) · Circulation · doi:10.1161/circulationaha.119.043805 · Cited by 216 · see citing works
Karmali, K. N., Goff, D. C., Ning, H., & Lloyd‐Jones, D. M. (2014) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2014.06.1186 · Cited by 204 · see citing works
Adaptive design clinical trials: a review of the literature and ClinicalTrials.gov
Bothwell, L. E., Avorn, J., Khan, N. F., & Kesselheim, A. S. (2018) · BMJ Open · doi:10.1136/bmjopen-2017-018320 · Cited by 198 · see citing works
Tota-Maharaj, R., Blaha, M. J., McEvoy, J. W., Blumenthal, R. S., Muse, E. D., Budoff, M. J., Shaw, L. J., Berman, D. S., Rana, J. S., Rumberger, J. A., et al. (2012) · European Heart Journal · doi:10.1093/eurheartj/ehs230 · Cited by 194 · see citing works
Amariuta, T., Ishigaki, K., Sugishita, H., Ohta, T., Koido, M., Dey, K. K., Matsuda, K., Murakami, Y., Price, A. L., Kawakami, E., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-00740-8 · Cited by 180 · see citing works
Genetic risk prediction in complex disease
Jostins, L., & Barrett, J. C. (2011) · Human Molecular Genetics · doi:10.1093/hmg/ddr378 · Cited by 179 · see citing works
Zhou, X., Siegel, K. R., Ng, B. P., Jawanda, S., Proia, K. K., Zhang, X., Albright, A. L., & Zhang, P. (2020) · Diabetes Care · doi:10.2337/dci20-0018 · Cited by 173 · see citing works
Coronary Artery Calcification and Family History of Premature Coronary Heart Disease
Nasir, K., Michos, E. D., Rumberger, J. A., Braunstein, J. B., Post, W. S., Budoff, M. J., & Blumenthal, R. S. (2004) · Circulation · doi:10.1161/01.cir.0000144464.11080.14 · Cited by 172 · see citing works
Effect of CYP2C19 Genotype on Ischemic Outcomes During Oral P2Y12 Inhibitor Therapy
Pereira, N. L., Rihal, C. S., Lennon, R. J., Marcus, G., Shrivastava, S., Bell, M. R., So, D. Y. F., Geller, N. L., Goodman, S. G., Hasan, A., et al. (2021) · JACC: Cardiovascular Interventions · doi:10.1016/j.jcin.2021.01.024 · Cited by 170 · see citing works
Statins in Familial Hypercholesterolemia
Besseling, J., Hovingh, G. K., Huijgen, R., Kastelein, J. J. P., & Hutten, B. A. (2016) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2016.04.054 · Cited by 169 · see citing works
Leveraging functional annotations in genetic risk prediction for human complex diseases
Hu, Y., Lu, Q., Powles, R. L., Yao, X., Yang, C., Fang, F., Xu, X., & Zhao, H. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005589 · Cited by 166 · see citing works
Integrated Polygenic Tool Substantially Enhances Coronary Artery Disease Prediction
Riveros-Mckay, F., Weale, M. E., Moore, R., Selzam, S., Krapohl, E. M. L., Sivley, R. M., Tarran, W. A., Sørensen, P. B., Lachapelle, A. S., Griffiths, J. A., et al. (2021) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.120.003304 · Cited by 159 · see citing works
YOUNG CANDIDATES FOR CORONARY HEART DISEASE
Gertler, M. M. (1951) · JAMA · doi:10.1001/jama.1951.03670240005002 · Cited by 150 · see citing works
Márquez‐Luna, C., Gazal, S., Loh, P., Kim, S. S., Furlotte, N. A., Auton, A., Agee, M., Alipanahi, B., Bell, R. K., Bryc, K., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25171-9 · Cited by 148 · see citing works
Association of Coronary Artery Calcium With Long-term, Cause-Specific Mortality Among Young Adults
Miedema, M. D., Dardari, Z., Nasir, K., Blankstein, R., Knickelbine, T., Oberembt, S., Shaw, L. J., Rumberger, J. A., Michos, E. D., Rozanski, A., et al. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.7440 · Cited by 147 · see citing works
Statins for people at low risk of cardiovascular disease – Authors' reply
Mihaylova, B., Emberson, J., Keech, A., Collins, R., & Baigent, C. (2012) · The Lancet · doi:10.1016/s0140-6736(12)62027-3 · Cited by 146 · see citing works
Polygenic Scores to Assess Atherosclerotic Cardiovascular Disease Risk
Aragam, K. G., & Natarajan, P. (2020) · Circulation Research · doi:10.1161/circresaha.120.315928 · Cited by 146 · see citing works
Self-citationPersonalized Genetic Risk Counseling to Motivate Diabetes Prevention
Grant, R. W., OʼBrien, K., Waxler, J. L., Vassy, J. L., Delahanty, L. M., Bissett, L., Green, R. C., Stember, K. G., Guiducci, C., Park, E. R., et al. (2012) · Diabetes Care · doi:10.2337/dc12-0884 · Cited by 142 · see citing works
Widén, E., Junna, N., Ruotsalainen, S., Surakka, I. L., Mars, N., Ripatti, P., Partanen, J., Aro, J., Mustonen, P., Tuomi, T., et al. (2022) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.121.003459 · Cited by 141 · see citing works
Genetic Architecture of Abdominal Aortic Aneurysm in the Million Veteran Program
Klarin, D. M., Verma, S. S., Judy, R., Dikilitas, O., Wolford, B. N., Paranjpe, I., Levin, M. G., Pan, C., Tcheandjieu, C., Spin, J. M., et al. (2020) · Circulation · doi:10.1161/circulationaha.120.047544 · Cited by 136 · see citing works
Self-citationAragam, K. G., Dobbyn, A. L., Judy, R., Chaffin, M. D., Chaudhary, K., Hindy, G., Cagan, A., Finneran, P., Weng, L.-C. C., Loos, R. J. F., et al. (2020) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2020.04.027 · Cited by 135 · see citing works
Self-citationCurtis, D. (2018) · Psychiatric Genetics · doi:10.1097/ypg.0000000000000206 · Cited by 132 · see citing works
Mapping eGFR loci to the renal transcriptome and phenome in the VA Million Veteran Program
Hellwege, J. N., Edwards, D. R. V., Giri, A., Qiu, C., Park, J., Torstenson, E. S., Keaton, J. M., Wilson, O. D., Robinson‐Cohen, C., Chung, C. P., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11704-w · Cited by 128 · see citing works
Self-citationCarver, R. B., Castéra, J., Gericke, N., et al. (2017) · PLoS ONE · doi:10.1371/journal.pone.0169808 · Cited by 120 · see citing works
Homburger, J. R., Neben, C. L., Mishne, G., Zhou, A. Y., Kathiresan, S., & Khera, A. V. (2019) · Genome Medicine · doi:10.1186/s13073-019-0682-2 · Cited by 120 · see citing works
The Delayed-Start Study Design
D’Agostino, R. B. (2009) · New England Journal of Medicine · doi:10.1056/nejmsm0904209 · Cited by 119 · see citing works
Ye, Y., Chen, X. D., Han, J. J., Jiang, W., Natarajan, P., & Zhao, H. (2021) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.120.003128 · Cited by 116 · see citing works
Self-citationGenomic risk prediction of complex human disease and its clinical application
Abraham, G., & Inouye, M. (2015) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2015.06.005 · Cited by 111 · see citing works
Hindy, G., Aragam, K. G., Ng, K., Chaffin, M. D., Lotta, L. A., Baras, A., Drake, I., Orho‐Melander, M., Melander, O., Kathiresan, S., et al. (2020) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.120.314856 · Cited by 111 · see citing works
Improving Polygenic Prediction in Ancestrally Diverse PopulationsPreprint
Ruan, Y., Lin, K., Feng, Y. A., et al. (2021) · medRxiv · doi:10.1101/2020.12.27.20248738 · Cited by 109 · see citing works
The impact of age on genetic risk for common diseases
Jiang, X., Holmes, C. C., & McVean, G. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009723 · Cited by 108 · see citing works
Kaufman, D., Baker, R. G., Milner, L. C., Devaney, S. A., & Hudson, K. (2016) · PLoS ONE · doi:10.1371/journal.pone.0160461 · Cited by 99 · see citing works
Marnetto, D., Pärna, K., Läll, K., Molinaro, L., Montinaro, F., Haller, T., Metspalu, M., Mägi, R., Fischer, K., & Pagani, L. (2020) · Nature Communications · doi:10.1038/s41467-020-15464-w · Cited by 98 · see citing works
Polygenic Hyperlipidemias and Coronary Artery Disease Risk
Ripatti, P., Rämö, J. T., Mars, N. J., Fu, Y., Lin, J., Söderlund, S., Benner, C., Surakka, I., Kiiskinen, T., Havulinna, A. S., et al. (2020) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.119.002725 · Cited by 92 · see citing works
Hu, Y., Lu, Q., Liu, W., Zhang, Y., Li, M., & Zhao, H. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1006836 · Cited by 82 · see citing works
Coronary Artery Calcium Improves Risk Classification in Younger Populations
Paixao, A. R. M., Ayers, C. R., Sabbagh, A. E., Sanghavi, M., Berry, J. D., Rohatgi, A. K., Kumbhani, D. J., McGuire, D. K., Das, S. R., de Lemos, J. A., et al. (2015) · JACC. Cardiovascular imaging · doi:10.1016/j.jcmg.2015.06.015 · Cited by 81 · see citing works
Aragam, K. G., Jiang, T., Goel, A., Kanoni, S., Wolford, B. N., Weeks, E. M., Wang, M., Hindy, G., Zhou, W., Grace, C., et al. (2021) · medRxiv · doi:10.1101/2021.05.24.21257377 · Cited by 67 · see citing works
Genotype imputation and variability in polygenic risk score estimation
Chen, S., Dias, R., Evans, D., Salfati, E., Liu, S., Wineinger, N. E., & Torkamani, A. (2020) · Genome Medicine · doi:10.1186/s13073-020-00801-x · Cited by 58 · see citing works
Goldstein, B. A., Knowles, J. W., Salfati, E., Ioannidis, J. P. A., & Assimes, T. L. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00254 · Cited by 57 · see citing works
Knowles, J. W., Zarafshar, S., Pavlović, A., Goldstein, B. A., Tsai, S. A., Li, J., McConnell, M. V., Absher, D., Ashley, E. A., Kiernan, M., et al. (2017) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2017.00053 · Cited by 53 · see citing works
Márquez‐Luna, C., Gazal, S., Loh, P., Kim, S. S., Furlotte, N. A., Auton, A., & Price, A. L. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/375337 · Cited by 49 · see citing works
Riaz, M., Huq, A. J., Ryan, J. L., Orchard, S. G., Tiller, J. M., Lockery, J. E., Woods, R. L., Wolfe, R. S., Renton, A. E., Goate, A., et al. (2021) · Aging Cell · doi:10.1111/acel.13384 · Cited by 43 · see citing works
Muse, E. D., Chen, S., Liu, S., Fernandez, B., Schrader, B., Molparia, B., León, A. N., Lee, R., Pubbi, N., Mejia, N., et al. (2022) · npj Digital Medicine · doi:10.1038/s41746-022-00578-w · Cited by 43 · see citing works
Neumann, F., Riaz, M., Bakshi, A., Polekhina, G., Thảo, L. T. P., Nelson, M. R., Woods, R. L., Abraham, G., Inouye, M., Reid, C. M., et al. (2021) · Stroke · doi:10.1161/strokeaha.120.033670 · Cited by 40 · see citing works
Stability of polygenic scores across discovery genome-wide association studies
Schultz, L. M., Merikangas, A. K., Ruparel, K., Jacquemont, S., Glahn, D. C., Gur, R. E., Barzilay, R., & Almasy, L. A. (2022) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2022.100091 · Cited by 40 · see citing works
Khera, A. V., Won, H., Peloso, G. M., et al. (2016) · Journal of the American College of Cardiology · Cited by 38 · see citing works
Zeng, W., Stason, W. B., Fournier, S., Razavi, M., Ritter, G. A., Strickler, G. K., Bhalotra, S. M., & Shepard, D. S. (2013) · American Heart Journal · doi:10.1016/j.ahj.2013.01.018 · Cited by 37 · see citing works
Effect of Disclosing Genetic Risk for Coronary Heart Disease on Information Seeking and Sharing
Brown, S.-A. N., Jouni, H., Marroush, T. S., & Kullo, I. J. (2017) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.116.001613 · Cited by 36 · see citing works
Polygenic Risk Scoring for Coronary Heart Disease
Natarajan, P. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.08.1041 · Cited by 33 · see citing works
Self-citationPenalized regression and model selection methods for polygenic scores on summary statistics
Pattee, J. W., & Pan, W. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008271 · Cited by 33 · see citing works
WHITE, P. D. (1957) · New England Journal of Medicine · doi:10.1056/nejm195705232562101 · Cited by 29 · see citing works
Robinson, C. L., Jouni, H., Kruisselbrink, T., et al. (2015) · Clinical Genetics · doi:10.1111/cge.12577 · Cited by 28 · see citing works
Genomic Risk Stratification Predicts All-Cause Mortality After Cardiac Catheterization
Levin, M. G., Kember, R. L., Judy, R., Birtwell, D. L., Williams, H., Arany, Z. P., Giri, J. S., Guerraty, M. A., Cappola, T., Chen, J., et al. (2018) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.118.002352 · Cited by 25 · see citing works
Merino, J., Jablonski, K. A., Mercader, J. M., Kahn, S. E., Chen, L., Harden, M. V., Delahanty, L. M., Araneta, M. R. G., Walford, G. A., Jacobs, S. B. R., et al. (2019) · Diabetes · doi:10.2337/db19-0097 · Cited by 21 · see citing works
Widén, E., Junna, N., Ruotsalainen, S., et al. (2020) · medRxiv · doi:10.1101/2020.09.18.20197137 · Cited by 21 · see citing works
Nsengimana, J., Samani, N. J., Hall, A. S., et al. (2006) · European Journal of Human Genetics · doi:10.1038/sj.ejhg.5201752 · Cited by 20 · see citing works
The 21st Century Cures Act and Early Feasibility Studies for Cardiovascular Devices
Holmes, D. R., Hance, R. “., Jensen, T. S., et al. (2018) · JACC: Cardiovascular Interventions · doi:10.1016/j.jcin.2018.05.010 · Cited by 11 · see citing works
Lessons Learned From the COURAGE Trial: Generalizability, Limitations, and Implications
Franklin, B. A. (2007) · Preventive Cardiology · doi:10.1111/j.1520-037x.2007.06100.x · Cited by 4 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [84]Muse ED Response to polygenic risk: results of the MyGeneRank Mobile Application-Based Coronary Artery Disease Study. Preprint at MedRxiv 10.1101/2021.04.26.21256141 (2021). · DOI
Cited by
Sorted by citations
Acosta, J. N., Falcone, G. J., Rajpurkar, P., & Topol, E. J. (2022) · Nature Medicine · doi:10.1038/s41591-022-01981-2 · Cited by 1,365 · see citing works
Aherrahrou, R., Reinberger, T., Hashmi, S., & Erdmann, J. (2024) · Cardiovascular Research · doi:10.1093/cvr/cvae161 · Cited by 25 · see citing works
- Authors
- Klarin, D., & Natarajan, P.
- Affiliations
- Broad Institute (US)
- Corresponding author
- Natarajan, Pradeep
- Venue
- Nature Reviews Cardiology
- Published
- 2021-11-22
- Volume
- 19
- Issue
- 5
- Pages
- 291-301
- ISSN
- 1759-5002 (ISSN-L)
- 1759-5010
- PMC
- PMC10150334
- OpenAlex
- W3216708429
- Cited by
- 152
- References
- 143
- Citations by year
- 2026: 29 · 2025: 37 · 2024: 38 · 2023: 33 · 2022: 15
- FWCI
- 3.20
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature Reviews Cardiology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Heart, Lung, and Blood Institute (R01HL127564)
- National Human Genome Research Institute (U01HG011719)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Keywords
- polygenic risk score, coronary artery disease, clinical implementation, risk prediction, screening algorithm, clinical trial design, risk score validation
- MeSH terms
- Coronary Artery Disease, Humans, Prospective Studies, Risk Factors, Genetic Predisposition to Disease, Multifactorial Inheritance
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