Serum Exosome MicroRNAs Predict Multiple Sclerosis Disease Activity after Fingolimod Treatment

We and others have previously demonstrated the potential for circulating exosome microRNAs to aid in disease diagnosis. In this study, we sought the possible utility of serum exosome microRNAs as biomarkers for disease activity in multiple sclerosis patients in response to fingolimod therapy. We studied patients with relapsing-remitting multiple sclerosis prior to and 6 months after treatment with fingolimod. Disease activity was determined using gadolinium-enhanced magnetic resonance imaging. Serum exosome microRNAs were profiled using next-generation sequencing. Data were analysed using univariate/multivariate modelling and machine learning to determine microRNA signatures with predictive utility. Accordingly, we identified 15 individual miRNAs that were differentially expressed in serum exosomes from post-treatment patients with active versus quiescent disease. The targets of these microRNAs clustered in ontologies related to the immune and nervous systems and signal transduction. While the power of individual microRNAs to predict disease status post-fingolimod was modest (average 77%, range 65 to 91%), several combinations of 2 or 3 miRNAs were able to distinguish active from quiescent disease with greater than 90% accuracy. Further stratification of patients identified additional microRNAs associated with stable remission, and a positive response to fingolimod in patients with active disease prior to treatment. Overall, these data underscore the value of serum exosome microRNA signatures as non-invasive biomarkers of disease in multiple sclerosis and suggest they may be used to predict response to fingolimod in future clinical practice. Additionally, these data suggest that fingolimod may have mechanisms of action beyond its known functions.