The DOI matches its Crossref record; 45 of the 46 references it cites were found in a registry or an index.
Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials
Open accessAbstract
Background Genetic variants have been associated with the risk of coronary heart disease. In this study, we tested whether or not a composite of these variants could ascertain the risk of both incident and recurrent coronary heart disease events and identify those individuals who derive greater clinical benefit from statin therapy.Methods A community-based cohort study (the Malmo Diet and Cancer Study) and four randomised controlled trials of both primary prevention (JUPITER and ASCOT) and secondary prevention (CARE and PROVE IT-TIMI 22) with statin therapy, comprising a total of 48,421 individuals and 3477 events, were included in these analyses. We studied the association of a genetic risk score based on 27 genetic variants with incident or recurrent coronary heart disease, adjusting for traditional clinical risk factors. We then investigated the relative and absolute risk reductions in coronary heart disease events with statin therapy stratified by genetic risk. We combined data from the different studies using a meta-analysis.Findings When individuals were divided into low (quintile 1), intermediate (quintiles 2-4), and high (quintile 5) genetic risk categories, a significant gradient in risk for incident or recurrent coronary heart disease was shown. Compared with the low genetic risk category, the multivariable-adjusted hazard ratio for coronary heart disease for the intermediate genetic risk category was 1·34 (95% CI 1·22-1·47, p<0·0001) and that for the high genetic risk category was 1·72 (1·55-1·92, p<0·0001). In terms of the benefit of statin therapy in the four randomised trials, we noted a significant gradient (p=0·0277) of increasing relative risk reductions across the low (13%), intermediate (29%), and high (48%) genetic risk categories. Similarly, we noted greater absolute risk reductions in those individuals in higher genetic risk categories (p=0·0101), resulting in a roughly threefold decrease in the number needed to treat to prevent one coronary heart disease event in the primary prevention trials. Specifically, in the primary prevention trials, the number needed to treat to prevent one such event in 10 years was 66 in people at low genetic risk, 42 in those at intermediate genetic risk, and 25 in those at high genetic risk in JUPITER, and 57, 47, and 20, respectively, in ASCOT.Interpretation A genetic risk score identified individuals at increased risk for both incident and recurrent coronary heart disease events. People with the highest burden of genetic risk derived the largest relative and absolute clinical benefit from statin therapy.Funding National Institutes of Health.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Our finding that a polygenic risk score has robust associations with incident coronary events is well aligned with previous studies of both primary and secondary prevention populations.16–24”
From Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease (2016) · cites this paper as [22]
In the citing paper
“For example, we previously showed that a high polygenic risk for CAD may be offset by either of two interventions: adherence to a healthy lifestyle or cholesterol-lowering therapy with statin medications.19–21”
From Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations (2018) · cites this paper as [20]
In the citing paper
“These risk alleles, when aggregated into a polygenic risk score, are predictive of incident coronary events and provide a continuous and quantitative measure of genetic susceptibility.16–24”
From Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease (2016) · cites this paper as [22]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
1 retracted
Reduced dietary salt for the prevention of cardiovascular disease
Taylor, R. S., Ashton, K. E., Moxham, T., Hooper, L., & Ebrahim, S. B. J. (2013) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd009217.pub2 · Cited by 311
RetractedSacks, F. M., Pfeffer, M. A., Moye, L. A., Rouleau, J. L., Rutherford, J. D., Cole, T. G., Brown, L., Warnica, J. W., Arnold, J. M. O., Wun, C.-C., et al. (1996) · New England Journal of Medicine · doi:10.1056/nejm199610033351401 · Cited by 7,439
Self-citationRosuvastatin to Prevent Vascular Events in Men and Women with Elevated C-Reactive Protein
Ridker, P. M., Danielson, E., Fonseca, F. A. H., Genest, J., Gotto, A. M., Kastelein, J. J. P., Koenig, W., Libby, P., Lorenzatti, A. J., MacFadyen, J. G., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa0807646 · Cited by 6,674
Self-citationCholesterol Treatment Trialists' (CTT) Collaboration (2010) · The Lancet · doi:10.1016/s0140-6736(10)61350-5 · Cited by 6,550
Intensive versus Moderate Lipid Lowering with Statins after Acute Coronary Syndromes
Cannon, C. P., Braunwald, E., McCabe, C. H., Rader, D. J., Rouleau, J. L., Belder, R., Joyal, S. V., Hill, K. A., Pfeffer, M. A., & Skene, A. M. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa040583 · Cited by 4,938
Self-citationSever, P., Dahlöf, B., Poulter, N. R., Wedel, H., Beevers, G., Caulfield, M. J., Collins, R., Kjeldsen, S. E., Kristinsson, A., McInnes, G. T., et al. (2003) · The Lancet · doi:10.1016/s0140-6736(03)12948-0 · Cited by 3,790
Self-citationRosuvastatin to Prevent Vascular Events in Men and Women With Elevated C-Reactive Protein
Ridker, P. M., Danielson, E., Fonseca, F. A. H., Genest, J. J., Gotto, A. M., Kastelein, J. J. P., Köenig, W., Libby, P., Lorenzatti, A. J., MacFadyen, J. G., et al. (2009) · Obstetrical & Gynecological Survey · doi:10.1097/01.ogx.0000344393.60303.0a · Cited by 3,641
Self-citationCollaborators, C. T. T. (. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60367-5 · Cited by 2,833
Statins for the primary prevention of cardiovascular disease
Taylor, F., Huffman, M. D., Macedo, A. F., Moore, T. H., Burke, M., Davey Smith, G., Ward, K., Ebrahim, S., & Gay, H. C. (2013) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd004816.pub5 · Cited by 1,934
Cited by
Sorted by citations
Heart Disease and Stroke Statistics—2020 Update: A Report From the American Heart Association
Virani, S. S., Alonso, A., Benjamin, E. J., Bittencourt, M. S., Callaway, C. W., Carson, A. P., Chamberlain, A. M., Chang, A. R., Cheng, S., Delling, F. N., et al. (2020) · Circulation · doi:10.1161/cir.0000000000000757 · Cited by 9,175
Heart Disease and Stroke Statistics—2019 Update: A Report From the American Heart Association
Benjamin, E. J., Muntner, P., Alonso, A., Bittencourt, M. S., Callaway, C. W., Carson, A. P., Chamberlain, A. M., Chang, A. R., Cheng, S., Das, S. R., et al. (2019) · Circulation · doi:10.1161/cir.0000000000000659 · Cited by 9,036
2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes
Knuuti, J., Wijns, W., Saraste, A., Capodanno, D., Barbato, E., Funck-Brentano, C., Prescott, E., Storey, R. F., Deaton, C., Cuisset, T., et al. (2020) · European Heart Journal · doi:10.1093/eurheartj/ehz425 · Cited by 7,166
Heart disease and stroke statistics-2018 update: a report from the american heart association
Benjamin, E. J., Virani, S. S., Callaway, C. W., Chamberlain, A. M., Chang, A. R., Cheng, S., Chiuve, S. E., Cushman, M., Delling, F. N., Deo, R., et al. (2018) · Circulation · doi:10.1161/cir.0000000000000558 · Cited by 7,146
2016 European Guidelines on cardiovascular disease prevention in clinical practice
Piepoli, M. F., Hoes, A. W., Agewall, S., Albus, C., Brotons, C., Catapano, A. L., Cooney, M.-T., Corrà, U., Cosyns, B., Deaton, C., et al. (2016) · European Heart Journal · doi:10.1093/eurheartj/ehw106 · Cited by 6,457
Heart Disease and Stroke Statistics—2021 Update: A Report From the American Heart Association
Virani, S. S., Alonso, A., Aparicio, H. J., Benjamin, E. J., Bittencourt, M. S., Callaway, C. W., Carson, A. P., Chamberlain, A. M., Cheng, S., Delling, F. N., et al. (2021) · Circulation · doi:10.1161/cir.0000000000000950 · Cited by 5,784
Ference, B. A., Ginsberg, H. N., Graham, I., Ray, K. K., Packard, C. J., Bruckert, E., Hegele, R. A., Krauss, R. M., Raal, F. J., Schunkert, H., et al. (2017) · European Heart Journal · doi:10.1093/eurheartj/ehx144 · Cited by 3,962
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
Self-citationBenefits and limitations of genome-wide association studies
Tam, V., Patel, N. K., Turcotte, M., Bossé, Y., Paré, G., & Meyre, D. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0127-1 · Cited by 2,208
The personal and clinical utility of polygenic risk scores
Torkamani, A., Wineinger, N. E., & Topol, E. J. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0018-x · Cited by 1,655
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
Self-citation2016 European Guidelines on cardiovascular disease prevention in clinical practice
Authors/Task Force Members, Piepoli, M. F., Hoes, A. W., Agewall, S., Albus, C., Brotons, C., Catapano, A. L., Cooney, M. T., Corrà, U., Cosyns, B., et al. (2016) · European Journal of Preventive Cardiology · doi:10.1177/2047487316653709 · Cited by 1,435
Polygenic risk scores: from research tools to clinical instruments
Lewis, C. M., & Vassos, E. (2020) · Genome Medicine · doi:10.1186/s13073-020-00742-5 · Cited by 1,360
van der Harst, P., & Verweij, N. (2018) · Circulation Research · doi:10.1161/circresaha.117.312086 · Cited by 1,141
Integrative omics for health and disease
Karczewski, K. J., & Snyder, M. P. (2018) · Nature Reviews Genetics · doi:10.1038/nrg.2018.4 · Cited by 1,158
Western Diet Triggers NLRP3-Dependent Innate Immune Reprogramming
Christ, A., Günther, P. S., Lauterbach, M., Duewell, P., Biswas, D., Pelka, K., Scholz, C. J., Oosting, M., Händler, K., Bassler, K. E., et al. (2018) · Cell · doi:10.1016/j.cell.2017.12.013 · Cited by 1,133
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 830
Developing and evaluating polygenic risk prediction models for stratified disease prevention
Chatterjee, N., Shi, J., & García‐Closas, M. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.27 · Cited by 712
Genetics of coronary artery disease: discovery, biology and clinical translation
Khera, A. V., & Kathiresan, S. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2016.160 · Cited by 659
Self-citationSaid, M. A., Verweij, N., & van der Harst, P. (2018) · JAMA Cardiology · doi:10.1001/jamacardio.2018.1717 · Cited by 663
Natarajan, 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
Self-citationCano-Gamez, E., & Trynka, G. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00424 · Cited by 613
Towards clinical utility of polygenic risk scores
Lambert, S. A., Abraham, G., & Inouye, M. (2019) · Human Molecular Genetics · doi:10.1093/hmg/ddz187 · Cited by 586
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 498
2016 European Guidelines on cardiovascular disease prevention in clinical practice
Piepoli, M. F., Hoes, A. W., Agewall, S., Albus, C., Brotons, C., Catapano, A. L., Cooney, M. T., Corrà, U., Cosyns, B., Deaton, C., et al. (2016) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2016.05.037 · Cited by 502
Responsible use of polygenic risk scores in the clinic: potential benefits, risks and gaps
Polygenic Risk Score Task Force of the International Common Disease Alliance, Adeyemo, A., Balaconis, M. K., Darnes, D. R., Fatumo, S., Granados Moreno, P., Hodonsky, C. J., Inouye, M., Kanai, M., Kato, K., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01549-6 · Cited by 413
O’Sullivan, J. W., Raghavan, S., Márquez‐Luna, C., Luzum, J. A., Damrauer, S. M., Ashley, E. A., O’Donnell, C. J., Willer, C. J., & Natarajan, P. (2022) · Circulation · doi:10.1161/cir.0000000000001077 · Cited by 443
Wilde, A. A. M., Semsarian, C., Márquez, M. F., Shamloo, A. S., Ackerman, M. J., Ashley, E. A., Sternick, E. B., Barajas-Martínez, H., Behr, E. R., Bezzina, C. R., et al. (2022) · EP Europace · doi:10.1093/europace/euac030 · Cited by 421
Genetics of Coronary Artery Disease
McPherson, R., & Tybjærg‐Hansen, A. (2016) · Circulation Research · doi:10.1161/circresaha.115.306566 · Cited by 384
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 353
Ganz, P., Heidecker, B., Hveem, K., Jonasson, C., Kato, S., Segal, M. R., Sterling, D. G., & Williams, S. A. (2016) · JAMA · doi:10.1001/jama.2016.5951 · Cited by 364
Genomic prediction of coronary heart disease
Abraham, G., Havulinna, A. S., Bhalala, O. G., Byars, S. G., De Livera, A. M., Yetukuri, L., Tikkanen, E., Perola, M., Schunkert, H., Sijbrands, E. J., et al. (2016) · European Heart Journal · doi:10.1093/eurheartj/ehw450 · Cited by 338
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
Self-citationA decade of genome-wide association studies for coronary artery disease: the challenges ahead
Erdmann, J., Kessler, T., Venegas, L. M., & Schunkert, H. (2018) · Cardiovascular Research · doi:10.1093/cvr/cvy084 · Cited by 331
Libby, P., Bornfeldt, K., & Tall, A. R. (2016) · Circulation Research · doi:10.1161/circresaha.116.308334 · Cited by 319
A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease
Patel, A. P., Wang, M., Ruan, Y., Koyama, S., Clarke, S. L., Yang, X., Tcheandjieu, C., Agrawal, S., Fahed, A. C., Ellinor, P. T., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02429-x · Cited by 309
Tada, 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
Self-citationCardiomyopathy in obesity, insulin resistance and diabetes
Nakamura, M., & Sadoshima, J. (2019) · The Journal of Physiology · doi:10.1113/jp276747 · Cited by 294
Schwedhelm, C., Boeing, H., HOFFMANN, G. E., Aleksandrova, K., & Schwingshackl, L. (2016) · Nutrition Reviews · doi:10.1093/nutrit/nuw045 · Cited by 279
Wilde, A. A. M., Semsarian, C., Márquez, M. F., Shamloo, A. S., Ackerman, M. J., Ashley, E. A., Sternick, E. B., Barajas-Martínez, H., Behr, E. R., Bezzina, C. R., et al. (2022) · Heart Rhythm · doi:10.1016/j.hrthm.2022.03.1225 · Cited by 287
Ten things to know about ten cardiovascular disease risk factors
Bays, H. E., Taub, P. R., Epstein, E., Michos, E. D., Ferraro, R. A., Bailey, A. L., Kelli, H. M., Ferdinand, K. C., Echols, M. R., Weintraub, H., et al. (2021) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2021.100149 · Cited by 274
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
Dai, J., Lv, J., Zhu, M., Wang, Y., Qin, N., Ma, H., He, Y., Zhang, R., Tan, W., Fan, J., et al. (2019) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(19)30144-4 · Cited by 267
Sabatine, M. S., De Ferrari, G. M., Giugliano, R. P., Huber, K., Lewis, B. S., Ferreira, J., Kuder, J. F., Murphy, S. A., Wiviott, S. D., Kurtz, C. E., et al. (2018) · Circulation · doi:10.1161/circulationaha.118.034309 · Cited by 255
Self-citationJin, G., Lv, J., Yang, M., Wang, M., Zhu, M., Wang, T., Yan, C., Yu, C., Ding, Y., Li, G., et al. (2020) · The Lancet Oncology · doi:10.1016/s1470-2045(20)30460-5 · Cited by 259
Lipinski, M. J., Benedetto, U., Escarcega, R. O., Biondi-Zoccai, G., Lhermusier, T., Baker, N. C., Torguson, R., Brewer, H. B., & Waksman, R. (2016) · European Heart Journal · doi:10.1093/eurheartj/ehv563 · Cited by 256
2026 ACC/AHA/AACVPR/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Dyslipidemia
Blumenthal, R. S., Morris, P. B., Gaudino, M., Johnson, H. M., Anderson, T. S., Bittner, V. A., Blankstein, R., Brewer, L. C., Cho, L., de Ferranti, S. D., et al. (2026) · JACC · doi:10.1016/j.jacc.2025.11.016 · Cited by 304
Torkamani, A., Andersen, K. G., Steinhubl, S. R., & Topol, E. J. (2017) · Cell · doi:10.1016/j.cell.2017.08.007 · Cited by 253
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 241
Genetics of Common, Complex Coronary Artery Disease
Musunuru, K., & Kathiresan, S. (2019) · Cell · doi:10.1016/j.cell.2019.02.015 · Cited by 246
Self-citationRidker, P. M., Mora, S., & Rose, L. M. (2016) · European Heart Journal · doi:10.1093/eurheartj/ehw046 · Cited by 222
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 219
Self-citationAre PCSK9 Inhibitors the Next Breakthrough in the Cardiovascular Field?
Giugliano, R. P., & Sabatine, M. S. (2015) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2015.05.001 · Cited by 200
Self-citationGala, D., Behl, H., Shah, M., & Makaryus, A. N. (2024) · Healthcare · doi:10.3390/healthcare12040481 · Cited by 216
The dawn of a new era of targeted lipid-lowering therapies
Tokgözoğlu, L., & Libby, P. (2022) · European Heart Journal · doi:10.1093/eurheartj/ehab841 · Cited by 171
Prevention of atherosclerosis from childhood
Raitakari, O. T., Pahkala, K., & Magnussen, C. G. (2022) · Nature Reviews Cardiology · doi:10.1038/s41569-021-00647-9 · Cited by 197
Polygenic scores in biomedical research
Kullo, I. J., Lewis, C. M., Inouye, M., Martin, A. R., Ripatti, S., & Chatterjee, N. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-022-00470-z · Cited by 185
Kessler, T., Vilne, B., & Schunkert, H. (2016) · EMBO Molecular Medicine · doi:10.15252/emmm.201506174 · Cited by 180
Systematic comparison of family history and polygenic risk across 24 common diseases
Mars, N., Lindbohm, J. V., Parolo, P. D. B., Widén, E., Kaprio, J. A., Palotie, A. V., FinnGen, & Ripatti, S. (2022) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.10.009 · Cited by 176
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 163
Lu, X., Liu, Z., Cui, Q., Liu, F., Li, J., Niu, X., Shen, C., Hu, D., Huang, K., Chen, J., et al. (2022) · European Heart Journal · doi:10.1093/eurheartj/ehac093 · Cited by 165
F. Piepoli, M. (2017) · International Journal of Behavioral Medicine · doi:10.1007/s12529-016-9583-6 · Cited by 162
Clinical utility of polygenic risk scores for coronary artery disease
Klarin, D., & Natarajan, P. (2022) · Nature Reviews Cardiology · doi:10.1038/s41569-021-00638-w · Cited by 152
Predictive Utility of a Coronary Artery Disease Polygenic Risk Score in Primary Prevention
Marston, N., Pirruccello, J. P., Melloni, G. E. M., Koyama, S., Kamanu, F., Weng, L.-C. C., Roselli, C., Kamatani, Y., Komuro, I., Aragam, K. G., et al. (2022) · JAMA Cardiology · doi:10.1001/jamacardio.2022.4466 · Cited by 149
Self-citationWidén, 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 147
Polygenic Scores to Assess Atherosclerotic Cardiovascular Disease Risk
Aragam, K. G., & Natarajan, P. (2020) · Circulation Research · doi:10.1161/circresaha.120.315928 · Cited by 148
Aragam, 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 137
Self-citationPharmacogenetics to guide cardiovascular drug therapy
Duarte, J. D., & Cavallari, L. (2021) · Nature Reviews Cardiology · doi:10.1038/s41569-021-00549-w · Cited by 119
2016 European Guidelines on cardiovascular disease prevention in clinical practice
Piepoli, M. F., Hoes, A. W., Agewall, S., Albus, C., Brotons, C., Catapano, A. L., Cooney, M. T., Corrà, U., Cosyns, B., Deaton, C., et al. (2016) · Kardiologia Polska · doi:10.5603/kp.2016.0120 · Cited by 152
Drapkina, O. M., Васильевна, К. А., Калинина, А. М., Avdeev, S. M., Викторович, А. М., Alexandrova, L. M., Анциферова, А. А., Dm, A., Ахмеджанов, Н. М., Balanova, Y. А., et al. (2022) · CARDIOVASCULAR THERAPY AND PREVENTION · doi:10.15829/1728-8800-2022-3235 · Cited by 197
PRSet: Pathway-based polygenic risk score analyses and software
Choi, S. W., García‐González, J., Ruan, Y., Wu, H. M., Porras, C., Johnson, J., Hoggart, C. J., & O’Reilly, P. F. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010624 · Cited by 133
Ten things to know about ten cardiovascular disease risk factors – 2022
Bays, H. E., Agarwala, A., German, C. A., Satish, P., Iluyomade, A., Dudum, R., Thakkar, A., Rifai, M. A., Mehta, A., Thobani, A., et al. (2022) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2022.100342 · Cited by 148
Emdin, C. A., Haas, M., Ajmera, V. H., Simon, T. G., Homburger, J. R., Neben, C. L., Jiang, L., Wei, W., Feng, Q., Zhou, A. Y., et al. (2020) · Gastroenterology · doi:10.1053/j.gastro.2020.12.011 · Cited by 131
Self-citationWriting Committee Members, Blumenthal, R. S., Morris, P. B., Gaudino, M., Johnson, H. M., Anderson, T. S., Bittner, V. A., Blankstein, R., Brewer, L. C., Cho, L., et al. (2026) · Circulation · doi:10.1161/cir.0000000000001423 · Cited by 122
FinnGen, Sakaue, S., Kanai, M., Karjalainen, J. M., Akiyama, M., Kurki, M., Matoba, N., Takahashi, A., Hirata, M., Kubo, M., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0785-8 · Cited by 121
Klarin, D. M., Emdin, C. A., Natarajan, P., Conrad, M. F., & Kathiresan, S. (2017) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.116.001643 · Cited by 118
Self-citationGenetics: Implications for Prevention and Management of Coronary Artery Disease
Assimes, T. L., & Roberts, R. (2016) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2016.10.039 · Cited by 118
Cardiovascular Precision Medicine in the Genomics Era
Dainis, A., & Ashley, E. A. (2018) · JACC Basic to Translational Science · doi:10.1016/j.jacbts.2018.01.003 · Cited by 119
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 112
Self-citationImplementation and implications for polygenic risk scores in healthcare
Slunecka, J. L., van der Zee, M. D., Beck, J. J., Johnson, B. N., Finnicum, C. T., Pool, R., Hottenga, J., de Geus, E. J. C., & Ehli, E. A. (2021) · Human Genomics · doi:10.1186/s40246-021-00339-y · Cited by 120
Figtree, G. A., Vernon, S. T., Harmer, J. A., Gray, M. P., Arnott, C. G., Bachour, E., Barsha, G., Brieger, D. B., Brown, A. D. H., Celermajer, D. S., et al. (2023) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2023.06.045 · Cited by 118
Acute coronary syndromes: mechanisms, challenges, and new opportunities
Kraler, S. C., Mueller, C. E., Libby, P., & Bhatt, D. L. (2025) · European Heart Journal · doi:10.1093/eurheartj/ehaf289 · Cited by 128
Potential therapeutic effects of mTOR inhibition in atherosclerosis
Kurdi, A., Meyer, G. R. Y. D., & Martinet, W. (2015) · British Journal of Clinical Pharmacology · doi:10.1111/bcp.12820 · Cited by 111
Coronary Artery Disease Genetics Enlightened by Genome-Wide Association Studies
Kessler, T., & Schunkert, H. (2021) · JACC Basic to Translational Science · doi:10.1016/j.jacbts.2021.04.001 · Cited by 111
Genetics of coronary artery disease in the post‐GWAS era
Chen, Z., & Schunkert, H. (2021) · Journal of Internal Medicine · doi:10.1111/joim.13362 · Cited by 111
Clinical utility and implementation of polygenic risk scores for predicting cardiovascular disease
Schunkert, H., Angelantonio, E. D., Inouye, M., Patel, R. S., Ripatti, S., Widén, E., Sanderson, S. C., Kaski, J. P., McEvoy, J. W., Vardas, P. E., et al. (2024) · European Heart Journal · doi:10.1093/eurheartj/ehae649 · Cited by 107
How precision medicine and screening with big data could increase overdiagnosis
Vogt, H., Green, S., Ekstrøm, C. T., & Brodersen, J. (2019) · BMJ · doi:10.1136/bmj.l5270 · Cited by 103
JCS 2018 Guideline on Diagnosis of Chronic Coronary Heart Diseases
Yamagishi, M., Tamaki, N., Akasaka, T., Ikeda, T., Ueshima, K., Uemura, S., Otsuji, Y., Kihara, Y., Kimura, K., Kimura, T., et al. (2021) · Circulation Journal · doi:10.1253/circj.cj-19-1131 · Cited by 100
Recent advances in polygenic scores: translation, equitability, methods and FAIR tools
Xiang, R., Kelemen, M., Xu, Y., Harris, L. W., Parkinson, H., Inouye, M., & Lambert, S. A. (2024) · Genome Medicine · doi:10.1186/s13073-024-01304-9 · Cited by 102
Genetics of ADHD: What Should the Clinician Know?
Grimm, O., Kranz, T. M., & Reif, A. (2020) · Current Psychiatry Reports · doi:10.1007/s11920-020-1141-x · Cited by 97
A polygenic risk score predicts atrial fibrillation in cardiovascular disease
Marston, N., Garfinkel, A. C., Kamanu, F., Melloni, G. E. M., Roselli, C., Jarolím, P., Berg, D. D., Bhatt, D. L., Bonaca, M. P., Cannon, C. P., et al. (2022) · European Heart Journal · doi:10.1093/eurheartj/ehac460 · Cited by 87
Self-citationAdvancements in Myocardial Infarction Management: Exploring Novel Approaches and Strategies
Sachdeva, P., Kaur, K., Fatima, S., Mahak, F., Noman, M., Siddenthi, S. M., Surksha, M. A., Munir, M., Fatima, F., Sultana, S. S., et al. (2023) · Cureus · doi:10.7759/cureus.45578 · Cited by 92
Romeo, S., Vidal‐Puig, A., Husain, M., Ahima, R. S., Arca, M., Bhatt, D. L., Diehl, A. M., Fontana, L., Foo, R., Frühbeck, G., et al. (2025) · European Heart Journal · doi:10.1093/eurheartj/ehaf314 · Cited by 93
Self-citationPolygenic risk scores: An overview from bench to bedside for personalised medicine
Cross, B., Turner, R., & Pirmohamed, M. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.1000667 · Cited by 86
Meisner, A., Kundu, P., Zhang, Y., Lan, L. V., Kim, S.-W., Ghandwani, D., Choudhury, P. P., Berndt, S. I., Freedman, N. D., García‐Closas, M., et al. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.07.002 · Cited by 76
Atherosclerosis and Coronary Artery Disease
Zaromitidou, M., Siasos, G., Παπαγεωργίου, Ν., Oikonomou, E. K., & Tousoulis, D. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-803312-8.00002-1 · Cited by 82
LNK/SH2B3 Loss of Function Promotes Atherosclerosis and Thrombosis
Wang, W., Tang, Y., Wang, Y., Tascau, L., Balcerek, J., Tong, W., Levine, R. L., Welch, C. L., Tall, A. R., & Wang, N. (2016) · Circulation Research · doi:10.1161/circresaha.116.308955 · Cited by 79
The emerging field of polygenic risk scores and perspective for use in clinical care
Yanes, T., McInerney-Leo, A. M., Law, M. H., & Cummings, S. A. (2020) · Human Molecular Genetics · doi:10.1093/hmg/ddaa136 · Cited by 75
Abraham, G., Rutten‐Jacobs, L. C. A., & Inouye, M. (2021) · Stroke · doi:10.1161/strokeaha.120.032619 · Cited by 78
Mokrý, M., Boltjes, A., Slenders, L., Bel-Bordes, G., Cui, K., Brouwer, E., Mekke, J. M., Depuydt, M. A. C., Timmerman, N., Waissi, F., et al. (2022) · Nature Cardiovascular Research · doi:10.1038/s44161-022-00171-0 · Cited by 80
Metadata
- Authors
- 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., Poulter, N. R., Sever, P. S., Ridker, P. M., Braunwald, E., Melander, O., Kathiresan, S., & Sabatine, M. S.
- Affiliations
- Brigham and Women's Hospital (US)
- Washington University in St. Louis (US)
- Broad Institute (US)
- Queen Mary University of London (GB)
- Quest Diagnostics (United States) (US)
- Pfizer (United States) (US)
- Imperial College London (GB)
- Lund University (SE)
- Corresponding author
- Mega, Jessica L
- Stitziel, Nathan O
- ORCID
- Venue
- The Lancet
- Publisher
- Elsevier BV
- Published
- 2015-06
- Volume
- 385
- Issue
- 9984
- Pages
- 2264-2271
- ISSN
- 0099-5355 (ISSN-L)
- 0140-6736
- PMC
- PMC4608367
- OpenAlex
- W2171705978
- Cited by
- 704
- References
- 46
- Citations by year
- 2026: 40 · 2025: 48 · 2024: 51 · 2023: 69 · 2022: 78 · 2021: 83 · 2020: 78 · 2019: 59 · 2018: 62 · 2017: 53 · 2016: 57 · 2015: 25
- FWCI
- 12.58
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- The Lancet (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (acceptedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- Spiral (Imperial College London) (submittedVersion, cc-by-nc-nd)
- Funders
- National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH) (RC1 HL099634)
- NIH and the NHLBI (grant K08 HL114642)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Keywords
- coronary artery disease, polygenic risk score, genetic variants, statin therapy, primary prevention, secondary prevention, number needed to treat, risk stratification, JUPITER trial, ASCOT trial, CARE trial, PROVE IT-TIMI 22, recurrent cardiovascular events, Malmö Diet and Cancer Study, cardiovascular risk prediction, treatment benefit stratification, LDL cholesterol lowering
- MeSH terms
- Coronary Disease, Humans, Primary Prevention, Recurrence, Treatment Outcome, Risk Assessment, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Secondary Prevention, Numbers Needed To Treat
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review