Combination protein biomarkers predict multiple sclerosis diagnosis and outcomes

Establishing biomarkers to predict multiple sclerosis (MS) diagnosis and prognosis has been challenging using a single biomarker approach. We hypothesised that a combination of biomarkers would increase the accuracy of prediction models to differentiate MS from other neurological disorders and enhance prognostication for people with MS. We measured 24 fluid biomarkers in the blood and CSF of 77 people with MS and 80 people with other neurological disorders, using ELISA or Single Molecule Array (SiMoA) assays. Primary outcomes were multiple sclerosis versus any other diagnosis, time to first relapse, and time to disability milestone (Expanded Disability Status Scale (EDSS) 6), adjusted for age and sex. Multivariate prediction models were calculated using the area under the curve (AUC) value for diagnostic prediction, and concordance statistics (the percentage of each pair of events that are correctly ordered in time for each of the Cox regression models) for prognostic predictions. Predictions using combinations of biomarkers were considerably better than single biomarker predictions. The combination of CSF[chitinase-3-like-1 + TNF-receptor-1 + solubleCD27] and serum[Osteopontin + MCP-1] had an AUC of 0.95 for diagnosis of MS compared to the best discriminative single marker in blood (Osteopontin: AUC 0.84) and CSF (chitinase-3-like-1: AUC 0.84). Prediction for time to next relapse was optimal with a combination of CSF[vitamin D binding protein + Factor I + C1inhibitor] + serum[Factor B + Interleukin-4 + C1inhibitor] (concordance 0.80), and time to EDSS 6 was optimally predicted by CSF[C9 + Neurofilament-light] + serum[chitinase-3-like-1 + CCL27 + vitamin D binding protein + C1inhibitor] (concordance 0.98). A combination of fluid biomarkers has a higher accuracy to differentiate MS from other neurological disorders and significantly improved the prediction of the development of sustained disability in MS. Serum models rivalled those of cerebrospinal fluid, holding promise for a non-invasive approach.