Proteomics profiling reveals biomarkers for predicting diagnosis, disease activity and long-term disability outcome in multiple sclerosis

Abstract

To personalize multiple sclerosis (MS) treatment strategies, sensitive and reliable protein biomarkers are needed to predict disease trajectory. We used protein profiling based on the highly sensitive proximity extension assay combined with next generation sequencing (Olink Explore) to measure 1463 proteins in cerebrospinal fluid (CSF) and plasma from 143 people with early-stage MS and 43 healthy controls. With longitudinally followed discovery and replication cohorts we identified CSF proteins that consistently predicted both short- and long-term disease progression. Neurofilament light chain (NfL) in CSF was confirmed as superior for predicting the absence of disease activity 2 years after sampling (replication AUC = 0.77). Importantly, we also identified a combination of 11 CSF proteins (CXCL13, LTA, FCN2, ICAM3, LY9, SLAMF7, TYMP, CHI3L1, FYB1, TNFRSF1B, NfL) that could predict the severity of disability worsening according to the normalized age-related MS severity score (replication AUC = 0.90). Identified proteins elucidate pathogenetic processes and can aid decisions of treatment strategies for people with MS.