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Timing and Predictive Value of Clinical Conditions Preceding Multiple Sclerosis in the UK Biobank
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Timing and Predictive Value of Clinical Conditions Preceding Multiple Sclerosis in the UK Biobank
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Timing and Predictive Value of Clinical Conditions Preceding Multiple Sclerosis in the UK Biobank
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Journal Article
Timing and Predictive Value of Clinical Conditions Preceding Multiple Sclerosis in the UK Biobank
2025
Overview
Objectives 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‐based cohort, which provided clinical history through ICD‐10 diagnosis codes. Methods 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‐PRS). Statistically significant conditions were included in a LASSO Cox regression (five‐fold cross‐validation on 70% training set) to identify key predictors, with performance assessed by the C‐index and age‐dependent area under the curve (AUC) in the 30% test set. Lastly, temporal trajectories of MS‐associated conditions were analyzed in MS cases. Results 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‐index from 0.65 to 0.71. Among the 30 model‐selected best predictors, ~25% were prodromal conditions, including neuromuscular diseases, thromboembolism, and depression which typically occurred more than five years before MS diagnosis. Including MS‐PRS further increased the C‐index to 0.78, with an age‐dependent AUC exceeding 0.80 in individuals over 50 years. Trajectory analysis highlighted migraine as a common early diagnosis, often followed by hypertension, depression, and dorsalgia. Interpretation 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‐onset cases.
