{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T12:14:28Z","timestamp":1775736868453,"version":"3.50.1"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,3,11]],"date-time":"2022-03-11T00:00:00Z","timestamp":1646956800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,3,11]],"date-time":"2022-03-11T00:00:00Z","timestamp":1646956800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Stowers Family Foundation"},{"DOI":"10.13039\/100006108","name":"U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["UL1TR002550"],"award-info":[{"award-number":["UL1TR002550"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Digit. Med."],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    We developed a smartphone application,\n                    <jats:italic>MyGeneRank<\/jats:italic>\n                    , to conduct a prospective observational cohort study (NCT03277365) involving the automated generation, communication, and electronic capture of response to a polygenic risk score (PRS) for coronary artery disease (CAD). Adults with a smartphone and an existing 23andMe genetic profiling self-referred to the study. We evaluated self-reported actions taken in response to personal CAD PRS information, with special interest in the initiation of lipid-lowering therapy. 19% (721\/3,800) of participants provided complete responses for baseline and follow-up use of lipid-lowering therapy. 20% (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u200919\/95) of high CAD PRS vs 7.9% (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u20098\/101) of low CAD PRS participants initiated lipid-lowering therapy at follow-up (\n                    <jats:italic>p<\/jats:italic>\n                    -value\u2009=\u20090.002). Both the initiation of statin and non-statin lipid-lowering therapy was associated with degree of CAD PRS: 15.2% (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u200914\/92) vs 6.0% (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u20096\/100) for statins (\n                    <jats:italic>p<\/jats:italic>\n                    -value\u2009=\u20090.018) and 6.8% (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u20098\/118) vs 1.6% (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u20092\/123) for non-statins (\n                    <jats:italic>p<\/jats:italic>\n                    -value\u2009=\u20090.022) in high vs low CAD PRS, respectively. High CAD PRS was also associated with earlier initiation of lipid lowering therapy (average age of 52 vs 65 years in high vs low CAD PRS respectively,\n                    <jats:italic>p<\/jats:italic>\n                    -value\u2009=\u20090.007). Overall, degree of CAD PRS was associated with use of any lipid-lowering therapy at follow-up: 42.4% (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u200956\/132) vs 28.5% (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u200937\/130) (\n                    <jats:italic>p<\/jats:italic>\n                    -value\u2009=\u20090.009). We find that digital communication of personal CAD PRS information is associated with increased and earlier lipid-lowering initiation in individuals of high CAD PRS. Loss to follow-up is the primary limitation of this study. Alternative communication routes, and long-term studies with EHR-based outcomes are needed to understand the generalizability and durability of this finding.\n                  <\/jats:p>","DOI":"10.1038\/s41746-022-00578-w","type":"journal-article","created":{"date-parts":[[2022,3,11]],"date-time":"2022-03-11T06:04:40Z","timestamp":1646978680000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Impact of polygenic risk communication: an observational mobile application-based coronary artery disease study"],"prefix":"10.1038","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5288-7462","authenticated-orcid":false,"given":"Evan D.","family":"Muse","sequence":"first","affiliation":[]},{"given":"Shang-Fu","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Shuchen","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Brianna","family":"Fernandez","sequence":"additional","affiliation":[]},{"given":"Brian","family":"Schrader","sequence":"additional","affiliation":[]},{"given":"Bhuvan","family":"Molparia","sequence":"additional","affiliation":[]},{"given":"Andr\u00e9 Nicol\u00e1s","family":"Le\u00f3n","sequence":"additional","affiliation":[]},{"given":"Raymond","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Neha","family":"Pubbi","sequence":"additional","affiliation":[]},{"given":"Nolan","family":"Mejia","sequence":"additional","affiliation":[]},{"given":"Christina","family":"Ren","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4922-4342","authenticated-orcid":false,"given":"Ahmed","family":"El-kalliny","sequence":"additional","affiliation":[]},{"given":"Ernesto","family":"Prado Montes de Oca","sequence":"additional","affiliation":[]},{"given":"Hector","family":"Aguilar","sequence":"additional","affiliation":[]},{"given":"Arjun","family":"Ghoshal","sequence":"additional","affiliation":[]},{"given":"Raquel","family":"Dias","sequence":"additional","affiliation":[]},{"given":"Doug","family":"Evans","sequence":"additional","affiliation":[]},{"given":"Kai-Yu","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Yunyue","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4517-228X","authenticated-orcid":false,"given":"Nathan E.","family":"Wineinger","sequence":"additional","affiliation":[]},{"given":"Emily G.","family":"Spencer","sequence":"additional","affiliation":[]},{"given":"Eric J.","family":"Topol","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0232-8053","authenticated-orcid":false,"given":"Ali","family":"Torkamani","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,3,11]]},"reference":[{"key":"578_CR1","doi-asserted-by":"publisher","DOI":"10.1186\/s13073-021-00829-7","volume":"13","author":"ACF Lewis","year":"2021","unstructured":"Lewis, A. C. F. & Green, R. C. Polygenic risk scores in the clinic: new perspectives needed on familiar ethical issues. Genome Med. 13, 14 (2021).","journal-title":"Genome Med."},{"key":"578_CR2","doi-asserted-by":"publisher","unstructured":"Martin, A. R. et al. Clinical use of current polygenic risk scores may exacerbate health disparities. Nat. Genet. https:\/\/doi.org\/10.1038\/s41588-019-0379-x (2019).","DOI":"10.1038\/s41588-019-0379-x"},{"key":"578_CR3","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1038\/s41436-018-0058-9","volume":"21","author":"FK Martens","year":"2019","unstructured":"Martens, F. K., Tonk, E. C. M. & Janssens, A. C. J. W. Evaluation of polygenic risk models using multiple performance measures: a critical assessment of discordant results. Genet. Med. 21, 391\u2013397 (2019).","journal-title":"Genet. Med."},{"key":"578_CR4","doi-asserted-by":"publisher","first-page":"513","DOI":"10.18865\/ed.29.3.513","volume":"29","author":"MC Roberts","year":"2019","unstructured":"Roberts, M. C., Khoury, M. J. & Mensah, G. A. Perspective: The clinical use of polygenic risk scores: race, ethnicity, and health disparities. Ethn. Dis. 29, 513\u2013516 (2019).","journal-title":"Ethn. Dis."},{"key":"578_CR5","doi-asserted-by":"crossref","unstructured":"Hollands, G. J. et al. The impact of communicating genetic risks of disease on risk-reducing health behaviour: systematic review with meta-analysis. BMJ 352, i1102 (2016).","DOI":"10.1136\/bmj.i1102"},{"key":"578_CR6","doi-asserted-by":"publisher","unstructured":"Bloss, C. S., Schork, N. J. & Topol, E. J. Effect of direct-to-consumer genomewide profiling to assess disease risk. N. Engl. J. Med. https:\/\/doi.org\/10.1056\/NEJMoa1011893 (2011).","DOI":"10.1056\/NEJMoa1011893"},{"key":"578_CR7","doi-asserted-by":"publisher","first-page":"912","DOI":"10.1038\/nbt.3661","volume":"34","author":"JL Krieger","year":"2016","unstructured":"Krieger, J. L., Murray, F., Roberts, J. S. & Green, R. C. The impact of personal genomics on risk perceptions and medical decision-making. Nat. Biotechnol. 34, 912\u2013918 (2016).","journal-title":"Nat. Biotechnol."},{"key":"578_CR8","doi-asserted-by":"publisher","first-page":"e1002546","DOI":"10.1371\/journal.pmed.1002546","volume":"15","author":"JW Knowles","year":"2018","unstructured":"Knowles, J. W. & Ashley, E. A. Cardiovascular disease: the rise of the genetic risk score. PLoS Med. 15, e1002546 (2018).","journal-title":"PLoS Med"},{"key":"578_CR9","doi-asserted-by":"publisher","unstructured":"Inouye, M. et al. Genomic risk prediction of coronary artery disease in 480,000 adults: implications for primary prevention. J. Am. Coll. Cardiol. https:\/\/doi.org\/10.1016\/j.jacc.2018.07.079 (2018)","DOI":"10.1016\/j.jacc.2018.07.079"},{"key":"578_CR10","doi-asserted-by":"publisher","first-page":"1219","DOI":"10.1038\/s41588-018-0183-z","volume":"50","author":"AV Khera","year":"2018","unstructured":"Khera, A. V. et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat. Genet. 50, 1219\u20131224 (2018).","journal-title":"Nat. Genet."},{"key":"578_CR11","doi-asserted-by":"publisher","unstructured":"Aragam, K. G. & Natarajan, P. Polygenic scores to assess atherosclerotic cardiovascular disease risk: clinical perspectives and basic implications. Circ. Res. https:\/\/doi.org\/10.1161\/CIRCRESAHA.120.315928 (2020).","DOI":"10.1161\/CIRCRESAHA.120.315928"},{"key":"578_CR12","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1001\/jama.2019.21782","volume":"323","author":"JD Mosley","year":"2020","unstructured":"Mosley, J. D. et al. Predictive accuracy of a polygenic risk score compared with a clinical risk score for incident coronary heart disease. JAMA 323, 627 (2020).","journal-title":"JAMA"},{"key":"578_CR13","doi-asserted-by":"publisher","first-page":"636","DOI":"10.1001\/jama.2019.22241","volume":"323","author":"J Elliott","year":"2020","unstructured":"Elliott, J. et al. Predictive accuracy of a polygenic risk score\u2013enhanced prediction model vs a clinical risk score for coronary artery disease. JAMA 323, 636 (2020).","journal-title":"JAMA"},{"key":"578_CR14","doi-asserted-by":"publisher","DOI":"10.1186\/s13073-021-00828-8","volume":"13","author":"M Isgut","year":"2021","unstructured":"Isgut, M., Sun, J., Quyyumi, A. A. & Gibson, G. Highly elevated polygenic risk scores are better predictors of myocardial infarction risk early in life than later. Genome Med. 13, 13 (2021).","journal-title":"Genome Med"},{"key":"578_CR15","doi-asserted-by":"publisher","first-page":"e1003498","DOI":"10.1371\/journal.pmed.1003498","volume":"18","author":"L Sun","year":"2021","unstructured":"Sun, L. et al. Polygenic risk scores in cardiovascular risk prediction: a cohort study and modelling analyses. PLOS Med. 18, e1003498 (2021).","journal-title":"PLOS Med"},{"key":"578_CR16","doi-asserted-by":"publisher","first-page":"624","DOI":"10.1161\/CIRCULATIONAHA.119.044434","volume":"141","author":"A Damask","year":"2020","unstructured":"Damask, A. 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 141, 624\u2013636 (2020).","journal-title":"Circulation"},{"key":"578_CR17","doi-asserted-by":"publisher","first-page":"616","DOI":"10.1161\/CIRCULATIONAHA.119.043805","volume":"141","author":"NA Marston","year":"2020","unstructured":"Marston, N. A. et al. Predicting benefit from evolocumab therapy in patients with atherosclerotic disease using a genetic risk score. Circulation 141, 616\u2013623 (2020).","journal-title":"Circulation"},{"key":"578_CR18","doi-asserted-by":"publisher","first-page":"2264","DOI":"10.1016\/S0140-6736(14)61730-X","volume":"385","author":"JL Mega","year":"2015","unstructured":"Mega, J. L. et al. Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials. Lancet 385, 2264\u20132271 (2015).","journal-title":"Lancet"},{"key":"578_CR19","doi-asserted-by":"publisher","first-page":"2091","DOI":"10.1161\/CIRCULATIONAHA.116.024436","volume":"135","author":"P Natarajan","year":"2017","unstructured":"Natarajan, P. 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 135, 2091\u20132101 (2017).","journal-title":"Circulation"},{"key":"578_CR20","doi-asserted-by":"publisher","unstructured":"Bolli, A., Di Domenico, P., Pastorino, R., Busby, G. B. & Bott\u00e0, G. Risk of coronary artery disease conferred by low-density lipoprotein cholesterol depends on polygenic background. Circulation https:\/\/doi.org\/10.1161\/CIRCULATIONAHA.120.051843 (2021).","DOI":"10.1161\/CIRCULATIONAHA.120.051843"},{"key":"578_CR21","doi-asserted-by":"crossref","unstructured":"Ye, Y. et al. Interactions between enhanced polygenic risk scores and lifestyle for cardiovascular disease, diabetes, and lipid levels. Circ. Genomic Precis. Med. 14, e003128 (2021).","DOI":"10.1161\/CIRCGEN.120.003128"},{"key":"578_CR22","doi-asserted-by":"publisher","unstructured":"Severance, L. M., Carter, H., Contijoch, F. J. & McVeigh, E. R. Targeted coronary artery calcium screening in high-risk younger individuals using consumer genetic screening results. JACC Cardiovasc. Imaging https:\/\/doi.org\/10.1016\/j.jcmg.2020.11.013 (2021).","DOI":"10.1016\/j.jcmg.2020.11.013"},{"key":"578_CR23","doi-asserted-by":"publisher","unstructured":"Arnett, D. K. 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. Circulation https:\/\/doi.org\/10.1161\/CIR.0000000000000678 (2019).","DOI":"10.1161\/CIR.0000000000000678"},{"key":"578_CR24","doi-asserted-by":"publisher","first-page":"2769","DOI":"10.1016\/j.jacc.2020.04.027","volume":"75","author":"KG Aragam","year":"2020","unstructured":"Aragam, K. G. et al. Limitations of contemporary guidelines for managing patients at high genetic risk of coronary artery disease. J. Am. Coll. Cardiol. 75, 2769\u20132780 (2020).","journal-title":"J. Am. Coll. Cardiol."},{"key":"578_CR25","doi-asserted-by":"publisher","unstructured":"Kullo, I. J. 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 https:\/\/doi.org\/10.1161\/CIRCULATIONAHA.115.020109 (2016).","DOI":"10.1161\/CIRCULATIONAHA.115.020109"},{"key":"578_CR26","doi-asserted-by":"publisher","unstructured":"Knowles, J. W. et al. Impact of a genetic risk score for coronary artery disease on reducing cardiovascular risk: a pilot randomized controlled study. Front. Cardiovasc. Med. https:\/\/doi.org\/10.3389\/fcvm.2017.00053 (2017).","DOI":"10.3389\/fcvm.2017.00053"},{"key":"578_CR27","doi-asserted-by":"publisher","unstructured":"Wid\u00e9n, E. et al. How Communicating Polygenic and Clinical Risk for Atherosclerotic Cardiovascular Disease Impacts Health Behavior: an Observational Follow-up Study. Circ Genom Precis Med. https:\/\/doi.org\/10.1161\/CIRCGEN.121.003459 (2022).","DOI":"10.1161\/CIRCGEN.121.003459"},{"key":"578_CR28","doi-asserted-by":"publisher","unstructured":"Klarin, D. & Natarajan, P. Clinical utility of polygenic risk scores for coronary artery disease. Nat. Rev. Cardiol. https:\/\/doi.org\/10.1038\/s41569-021-00638-w. (2021).","DOI":"10.1038\/s41569-021-00638-w"},{"key":"578_CR29","doi-asserted-by":"publisher","unstructured":"Perez, M. V. et al. Large-scale assessment of a smartwatch to identify atrial fibrillation. N. Engl. J. Med. https:\/\/doi.org\/10.1056\/nejmoa1901183 (2019).","DOI":"10.1056\/nejmoa1901183"},{"key":"578_CR30","doi-asserted-by":"publisher","unstructured":"Chen, S. F. et al. Genotype imputation and variability in polygenic risk score estimation. Genome Med. https:\/\/doi.org\/10.1186\/s13073-020-00801-x (2020).","DOI":"10.1186\/s13073-020-00801-x"},{"key":"578_CR31","doi-asserted-by":"publisher","first-page":"e2021476","DOI":"10.1001\/jamanetworkopen.2020.21476","volume":"3","author":"GC Alexander","year":"2020","unstructured":"Alexander, G. C. et al. Use and content of primary care office-based vs telemedicine care visits during the COVID-19 pandemic in the US. JAMA Netw. Open 3, e2021476 (2020).","journal-title":"JAMA Netw. Open"},{"key":"578_CR32","doi-asserted-by":"publisher","unstructured":"Muse, E. D. et al. Moving beyond clinical risk scores with a mobile app for the genomic risk of coronary artery disease. bioRxiv 101519. Preprint at https:\/\/doi.org\/10.1101\/101519 (2017).","DOI":"10.1101\/101519"},{"key":"578_CR33","doi-asserted-by":"publisher","first-page":"1121","DOI":"10.1038\/ng.3396","volume":"47","author":"M Nikpay","year":"2015","unstructured":"Nikpay, M. et al. A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease. Nat. Genet. 47, 1121\u20131130 (2015).","journal-title":"Nat. Genet"},{"key":"578_CR34","doi-asserted-by":"publisher","unstructured":"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. https:\/\/doi.org\/10.1093\/cvr\/cvy084 (2018).","DOI":"10.1093\/cvr\/cvy084"},{"key":"578_CR35","doi-asserted-by":"publisher","first-page":"1385","DOI":"10.1038\/ng.3913","volume":"49","author":"CP Nelson","year":"2017","unstructured":"Nelson, C. P. et al. Association analyses based on false discovery rate implicate new loci for coronary artery disease. Nat. Genet. 49, 1385\u20131391 (2017).","journal-title":"Nat. Genet."},{"key":"578_CR36","doi-asserted-by":"publisher","unstructured":"DiNardo, J. Natural Experiments and Quasi-Natural Experiments. in New Palgrave Dictionary of Economics. https:\/\/doi.org\/10.1057\/b.9780631218234.2008.X (2008).","DOI":"10.1057\/b.9780631218234.2008.X"}],"container-title":["npj Digital Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41746-022-00578-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-022-00578-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-022-00578-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T03:25:05Z","timestamp":1669346705000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41746-022-00578-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,11]]},"references-count":36,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["578"],"URL":"https:\/\/doi.org\/10.1038\/s41746-022-00578-w","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2021.04.26.21256141","asserted-by":"object"}]},"ISSN":["2398-6352"],"issn-type":[{"value":"2398-6352","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,11]]},"assertion":[{"value":"19 October 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 February 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 March 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 March 2022","order":4,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Update","order":5,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"In the original version of this article, the given and family names of Ernesto Prado Montes de Oca were incorrectly structured. The name was displayed correctly in all versions at the time of publication. The original article has been corrected.","order":6,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"A.T. and E.D.M. declare they are co-founders of geneXwell. The remaining authors declare that they have no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"30"}}