{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T06:56:35Z","timestamp":1777964195510,"version":"3.51.4"},"reference-count":53,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"18","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["JAHA"],"published-print":{"date-parts":[[2022,9,20]]},"abstract":"<jats:sec sec-type=\"background\" xml:lang=\"en\">\n            <jats:title>Background<\/jats:title>\n            <jats:p xml:lang=\"en\">Cardiorespiratory fitness is a powerful predictor of health outcomes that is currently underused in primary prevention, especially in young adults. We sought to develop a blood\u2010based biomarker of cardiorespiratory fitness that is easily translatable across populations.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Methods and Results<\/jats:title>\n            <jats:p xml:lang=\"en\">\n              Maximal effort cardiopulmonary exercise testing for quantification of cardiorespiratory fitness (by peak oxygen uptake) and profiling of &gt;200 metabolites at rest were performed in the FHS (Framingham Heart Study; 2016\u20132019). A metabolomic fitness score was derived\/validated in the FHS and was associated with long\u2010term outcomes in the younger CARDIA (Coronary Artery Risk Development in Young Adults) study. In the FHS (derivation, N=451; validation, N=914; age 54\u00b18\u2009years, 53% women, body mass index 27.7\u00b15.3\u2009kg\/m\n              <jats:sup>2<\/jats:sup>\n              ), we used LASSO (least absolute shrinkage and selection operator) regression to develop a multimetabolite score to predict peak oxygen uptake (correlation with peak oxygen uptake\n              <jats:italic>r<\/jats:italic>\n              =0.77 in derivation, 0.61 in validation; both\n              <jats:italic>P<\/jats:italic>\n              &lt;0.0001). In a linear model including clinical risk factors, a \u22481\u2010SD higher metabolomic fitness score had equivalent magnitude of association with peak oxygen uptake as a 9.2\u2010year age increment. In the CARDIA study (N=2300, median follow\u2010up 26.9\u2009years, age 32\u00b14\u2009years, 44% women, 44% Black individuals), a 1\u2010SD higher metabolomic fitness score was associated with a 44% lower risk for mortality (hazard ratio [HR], 0.56 [95% CI, 0.47\u20130.68];\n              <jats:italic>P<\/jats:italic>\n              &lt;0.0001) and 32% lower risk for cardiovascular disease (HR, 0.68 [95% CI, 0.55\u20130.84];\n              <jats:italic>P<\/jats:italic>\n              =0.0003) in models adjusted for age, sex, and race, which remained robust with adjustment for clinical risk factors.\n            <\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p xml:lang=\"en\">A blood\u2010based biomarker of cardiorespiratory fitness largely independent of traditional risk factors is associated with long\u2010term risk of cardiovascular disease and mortality in young adults.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1161\/jaha.122.026670","type":"journal-article","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T10:36:24Z","timestamp":1662633384000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":7,"title":["Blood\u2010Based Fingerprint of Cardiorespiratory Fitness and Long\u2010Term Health Outcomes in Young Adulthood"],"prefix":"10.1161","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4471-7156","authenticated-orcid":false,"given":"Ravi V.","family":"Shah","sequence":"first","affiliation":[{"name":"Vanderbilt Translational and Clinical Research Center Cardiology Division Vanderbilt University Medical Center Nashville TN"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patricia","family":"Miller","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Boston University School of Public Health Boston MA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9322-705X","authenticated-orcid":false,"given":"Laura A.","family":"Colangelo","sequence":"additional","affiliation":[{"name":"Department of Preventive Medicine Feinberg School of Medicine Northwestern University Chicago IL"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7104-409X","authenticated-orcid":false,"given":"Ariel","family":"Chernofsky","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Boston University School of Public Health Boston MA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicholas E.","family":"Houstis","sequence":"additional","affiliation":[{"name":"Cardiology Division Department of Medicine Massachusetts General Hospital Harvard Medical School Boston MA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0120-4630","authenticated-orcid":false,"given":"Rajeev","family":"Malhotra","sequence":"additional","affiliation":[{"name":"Cardiology Division Department of Medicine Massachusetts General Hospital Harvard Medical School Boston MA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2725-2692","authenticated-orcid":false,"given":"Raghava S.","family":"Velagaleti","sequence":"additional","affiliation":[{"name":"Cardiology Section Department of Medicine Boston VA Healthcare System West Roxbury MA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7232-0543","authenticated-orcid":false,"suffix":"Jr","given":"David R.","family":"Jacobs","sequence":"additional","affiliation":[{"name":"Division of Epidemiology and Community Health School of Public Health University of Minnesota Minneapolis 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IL"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8259-9245","authenticated-orcid":false,"given":"Clary B.","family":"Clish","sequence":"additional","affiliation":[{"name":"Broad Institute of MIT and Harvard Cambridge MA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9631-1254","authenticated-orcid":false,"given":"Martin G.","family":"Larson","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Boston University School of Public Health Boston MA"},{"name":"Boston University\u2019s and National Heart, Lung, and Blood Institute\u2019s Framingham Heart Study Framingham MA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7357-5970","authenticated-orcid":false,"given":"Ramachandran S.","family":"Vasan","sequence":"additional","affiliation":[{"name":"Boston University\u2019s and National Heart, Lung, and Blood Institute\u2019s Framingham Heart Study Framingham MA"},{"name":"Sections of Cardiovascular Medicine and Preventive Medicine and Epidemiology Department of Medicine Boston University School of Medicine Boston MA"},{"name":"Department of Epidemiology Boston University School of Public Health, and the Center for Computing and Data Sciences Boston University Boston MA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7901-1321","authenticated-orcid":false,"given":"Venkatesh L.","family":"Murthy","sequence":"additional","affiliation":[{"name":"Department of Epidemiology Boston University School of Public Health, and the Center for Computing and Data Sciences Boston University Boston MA"},{"name":"Division of Cardiovascular Medicine Department of Medicine, and Frankel Cardiovascular Center University of Michigan Ann Arbor 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