{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T10:33:01Z","timestamp":1788258781092,"version":"build-2803163510"},"reference-count":50,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"6","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["JAHA"],"published-print":{"date-parts":[[2026,3,17]]},"abstract":"<jats:sec xml:lang=\"en\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p xml:lang=\"en\">Blood\u2010based biomarkers for stroke subtyping could improve triage in emergency settings. We used cross\u2010platform proteomics to identify plasma biomarkers differentiating major stroke diagnostic groups.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p xml:lang=\"en\">We conducted a case\u2013control study using 2 biorepositories. Plasma was collected in the emergency department from adults with suspected stroke before therapeutic intervention. Differentially enriched proteins were identified across acute ischemic stroke, intracerebral hemorrhage, transient ischemic attack, and stroke mimics using SomaScan discovery proteomics (Grady). Differentially enriched proteins were nominated using pairwise and multigroup comparisons and adjusted for clinical covariates. Protein panels were created using least absolute shrinkage and selection operator logistic regression. Internal validation used repeated nested cross\u2010validation (rCV) and targeted mass spectrometry (MS), while external validation used data\u2010independent acquisition \u00a0mass spectrometry in an independent cohort (Yale).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p xml:lang=\"en\">We included 100 subjects (40 with acute ischemic stroke, 20 with intracerebral hemorrhage, 20 with transient ischemic attack, 20 with stroke mimics) in discovery and 80 subjects (20 per group) in external validation cohorts. SomaScan quantified 7307 proteins, of which 61 differentiated stroke subtypes. We identified 7 protein classifiers for acute ischemic stroke (rCV\u2010area under the curve, 0.82 [95% CI, 0.78\u20130.86]), 6 for intracerebral hemorrhage (rCV\u2010area under the curve, 0.70 [95% CI, 0.64\u20130.76]), 8 for transient ischemic attack (rCV\u2010area under the curve, 0.78 [95% CI, 0.73\u20130.84]), and 7 for stroke mimics (rCV\u2010area under the curve, 0.81 [95% CI, 0.77\u20130.86]). Targeted proteomics internally validated 11 proteins, and data\u2010independent acquisition\u2010mass spectrometry externally validated 32 proteins, including VTN (vitronectin), PLG (plasminogen), and S100A9 as top stroke mimics, transient ischemic attack, and intracerebral hemorrhage classifiers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p xml:lang=\"en\">This study highlights plasma proteomics as a valuable tool for discovering protein biomarkers of stroke diagnosis. These findings support further validation in larger, multicenter cohorts to facilitate biomarker\u2010guided stroke diagnosis in acute care.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1161\/jaha.125.048249","type":"journal-article","created":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T10:39:44Z","timestamp":1773139184000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":2,"title":["Cross\u2010Platform Proteomics and Machine Learning Algorithms Nominate Plasma Biomarkers of Stroke Diagnosis"],"prefix":"10.1161","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4920-2573","authenticated-orcid":false,"given":"Shubham","family":"Misra","sequence":"first","affiliation":[{"name":"Yale University School of Medicine","place":["New Haven, USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9700-5366","authenticated-orcid":false,"given":"Wooyoung 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