{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T08:42:15Z","timestamp":1789461735304,"version":"build-2803163510"},"reference-count":57,"publisher":"American Medical Association (AMA)","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Cardiol"],"published-print":{"date-parts":[[2023,6,1]]},"abstract":"\n Importance<\/jats:title>\n Primary prevention of atherosclerotic cardiovascular disease (ASCVD) relies on risk stratification. Genome-wide polygenic risk scores (PRSs) are proposed to improve ASCVD risk estimation.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To determine whether genome-wide PRSs for coronary artery disease (CAD) and acute ischemic stroke improve ASCVD risk estimation with traditional clinical risk factors in an ancestrally diverse midlife population.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This was a prognostic analysis of incident events in a retrospectively defined longitudinal cohort conducted from January 1, 2011, to December 31, 2018. Included in the study were adults free of ASCVD and statin naive at baseline from the Million Veteran Program (MVP), a mega biobank with genetic, survey, and electronic health record data from a large US health care system. Data were analyzed from March 15, 2021, to January 5, 2023.<\/jats:p>\n <\/jats:sec>\n \n Exposures<\/jats:title>\n PRSs for CAD and ischemic stroke derived from cohorts of largely European descent and risk factors, including age, sex, systolic blood pressure, total cholesterol, high-density lipoprotein (HDL) cholesterol, smoking, and diabetes status.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n Incident nonfatal myocardial infarction (MI), ischemic stroke, ASCVD death, and composite ASCVD events.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n A total of 79\u202f151 participants (mean [SD] age, 57.8 [13.7] years; 68\u202f503 male [86.5%]) were included in the study. The cohort included participants from the following harmonized genetic ancestry and race and ethnicity categories: 18\u202f505 non-Hispanic Black (23.4%), 6785 Hispanic (8.6%), and 53\u202f861 non-Hispanic White (68.0%) with a median (5th-95th percentile) follow-up of 4.3 (0.7-6.9) years. From 2011 to 2018, 3186 MIs (4.0%), 1933 ischemic strokes (2.4%), 867 ASCVD deaths (1.1%), and 5485 composite ASCVD events (6.9%) were observed. CAD PRS was associated with incident MI in non-Hispanic Black (hazard ratio [HR], 1.10; 95% CI, 1.02-1.19), Hispanic (HR, 1.26; 95% CI, 1.09-1.46), and non-Hispanic White (HR, 1.23; 95% CI, 1.18-1.29) participants. Stroke PRS was associated with incident stroke in non-Hispanic White participants (HR, 1.15; 95% CI, 1.08-1.21). A combined CAD plus stroke PRS was associated with ASCVD deaths among non-Hispanic Black (HR, 1.19; 95% CI, 1.03-1.17) and non-Hispanic (HR, 1.11; 95% CI, 1.03-1.21) participants. The combined PRS was also associated with composite ASCVD across all ancestry groups but greater among non-Hispanic White (HR, 1.20; 95% CI, 1.16-1.24) than non-Hispanic Black (HR, 1.11; 95% CI, 1.05-1.17) and Hispanic (HR, 1.12; 95% CI, 1.00-1.25) participants. Net reclassification improvement from adding PRS to a traditional risk model was modest for the intermediate risk group for composite CVD among men (5-year risk &amp;gt;3.75%, 0.38%; 95% CI, 0.07%-0.68%), among women, (6.79%; 95% CI, 3.01%-10.58%), for age older than 55 years (0.25%; 95% CI, 0.03%-0.47%), and for ages 40 to 55 years (1.61%; 95% CI, \u22120.07% to 3.30%).<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n Study results suggest that PRSs derived predominantly in European samples were statistically significantly associated with ASCVD in the multiancestry midlife and older-age MVP cohort. Overall, modest improvement in discrimination metrics were observed with addition of PRSs to traditional risk factors with greater magnitude in women and younger age groups.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamacardio.2023.0857","type":"journal-article","created":{"date-parts":[[2023,5,3]],"date-time":"2023-05-03T11:13:47Z","timestamp":1683112427000},"page":"564","source":"Crossref","is-referenced-by-count":44,"title":["Cardiovascular Disease Risk Assessment Using Traditional Risk Factors and Polygenic Risk Scores in the Million Veteran Program"],"prefix":"10.1001","volume":"8","author":[{"given":"Jason L.","family":"Vassy","sequence":"first","affiliation":[{"name":"Veterans Affairs Boston Healthcare System, Boston, Massachusetts"},{"name":"Department of Medicine, Brigham & Women\u2019s Hospital and Harvard Medical School, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel C.","family":"Posner","sequence":"additional","affiliation":[{"name":"Veterans Affairs Boston Healthcare System, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuk-Lam","family":"Ho","sequence":"additional","affiliation":[{"name":"Veterans Affairs Boston Healthcare System, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David R.","family":"Gagnon","sequence":"additional","affiliation":[{"name":"Veterans Affairs Boston Healthcare System, Boston, Massachusetts"},{"name":"Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ashley","family":"Galloway","sequence":"additional","affiliation":[{"name":"Veterans Affairs Boston Healthcare System, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vidisha","family":"Tanukonda","sequence":"additional","affiliation":[{"name":"Veterans Affairs Atlanta Healthcare System, Decatur, Georgia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Serena C.","family":"Houghton","sequence":"additional","affiliation":[{"name":"Veterans Affairs Boston Healthcare System, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ravi K.","family":"Madduri","sequence":"additional","affiliation":[{"name":"Data Science and Learning Division, Argonne National Laboratory, Lemont, Illinois"},{"name":"University of Chicago Consortium for Advanced Science and Engineering, The University of Chicago, Chicago, Illinois"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benjamin H.","family":"McMahon","sequence":"additional","affiliation":[{"name":"Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philip S.","family":"Tsao","sequence":"additional","affiliation":[{"name":"Palo Alto VA Healthcare System, Palo Alto, California"},{"name":"Stanford Cardiovascular Institute, Stanford University, Stanford, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Scott M.","family":"Damrauer","sequence":"additional","affiliation":[{"name":"Corporal Michael J. 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