{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T01:25:15Z","timestamp":1772587515122,"version":"3.50.1"},"reference-count":54,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T00:00:00Z","timestamp":1750896000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Ann Clin Transl Neurol"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Objectives<\/jats:title><jats:p>Multiple sclerosis (MS) patients often experience a higher incidence of clinical conditions before diagnosis, suggesting a prodromal phase. However, their predictive value and temporal trajectories remain underexplored. We investigated these aspects using the large UK Biobank's population\u2010based cohort, which provided clinical history through ICD\u201010 diagnosis codes.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We assessed associations between 600 clinical conditions and MS risk in 477,421 individuals using Cox models adjusted for demographics, smoking, and MS polygenic risk score (MS\u2010PRS). Statistically significant conditions were included in a LASSO Cox regression (five\u2010fold cross\u2010validation on 70% training set) to identify key predictors, with performance assessed by the C\u2010index and age\u2010dependent area under the curve (AUC) in the 30% test set. Lastly, temporal trajectories of MS\u2010associated conditions were analyzed in MS cases.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We identified 192 conditions associated with MS, of which only ~20% were onset symptoms. Integrating these conditions into a predictive model already including demographics and smoking, improved the C\u2010index from 0.65 to 0.71. Among the 30 model\u2010selected best predictors, ~25% were prodromal conditions, including neuromuscular diseases, thromboembolism, and depression which typically occurred more than five years before MS diagnosis. Including MS\u2010PRS further increased the C\u2010index to 0.78, with an age\u2010dependent AUC exceeding 0.80 in individuals over 50\u2009years. Trajectory analysis highlighted migraine as a common early diagnosis, often followed by hypertension, depression, and dorsalgia.<\/jats:p><\/jats:sec><jats:sec><jats:title>Interpretation<\/jats:title><jats:p>Our findings highlight early conditions and diagnostic trajectories of MS, supporting the existence of a prodromal phase. These insights could improve MS prediction and facilitate earlier detection, particularly for late\u2010onset cases.<\/jats:p><\/jats:sec>","DOI":"10.1002\/acn3.70119","type":"journal-article","created":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T02:44:08Z","timestamp":1750992248000},"page":"1952-1961","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Timing and Predictive Value of Clinical Conditions Preceding Multiple Sclerosis in the <scp>UK<\/scp> Biobank"],"prefix":"10.1002","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7258-1938","authenticated-orcid":false,"given":"Andrea","family":"Nova","sequence":"first","affiliation":[{"name":"Department of Brain and Behavioral Sciences University of Pavia  Pavia Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Teresa","family":"Fazia","sequence":"additional","affiliation":[{"name":"Department of Brain and Behavioral 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