Disease phenotype prediction in multiple sclerosis

Progressive multiple sclerosis (PMS) is currently diagnosed retrospectively. Here, we work towards a set of biomarkers that could assist in early diagnosis of PMS. A selection of cerebrospinal fluid metabolites (n=15) was shown to differentiate between PMS and its preceding phenotype in an independent cohort (AUC=0.93). Complementing the classifier with conformal prediction showed that highly confident predictions could be made, and that three out of eight patients developing PMS within three years of sample collection were predicted as PMS at that time point. Finally, this methodology was applied to PMS patients part of a clinical trial for intrathecal treatment with rituximab. The methodology showed that 68% of the patients decreased their similarity to the PMS phenotype one year after treatment. In conclusion, the inclusion of confidence predictors contributes with more information compared to traditional machine learning, and this information is relevant for disease monitoring.

Cohort 1 assays are reported in the current study MTBLS1464.
Cohort 2 assays are reported in MTBLS558.