Biomarker panel increases accuracy for identification of an MS relapse beyond sNfL.

BACKGROUND: For relapsing-remitting multiple sclerosis (RRMS), there is a need for biomarker development beyond clinical manifestations and MRI. Soluble neurofilament light chain (sNfL) has emerged as a biomarker for inflammatory activity in RRMS. However, there are limitations to the accuracy of sNfL in identifying relapses. Here, we sought to identify a panel of biomarkers that would increase the precision of distinguishing patients in relapse compared to sNfL alone. METHODS: We used a multiplex approach to measure levels of 724 blood proteins in two distinct RRMS cohorts. Multiple t-tests with covariate correction determined biomarkers that were differentially regulated in relapse and remission. Logistic regression models determined the accuracy of biomarkers to distinguish relapses from remission. RESULTS: The discovery cohort identified 37 proteins differentially abundant in active RRMS relapse compared to remission. The verification cohort confirmed four proteins, including sNfL, were altered in active RRMS relapse compared to remission. Logistic regression showed that the 4-protein panel identified active relapse with higher accuracy (AUC = 0.87) than sNfL alone (AUC = 0.69). CONCLUSION: Our studies confirmed that sNfL is elevated during relapses in RRMS patients. Furthermore, we identified three other blood proteins, uPA, hK8 and DSG3 that were altered during relapse. Together, these four biomarkers could be used to monitor disease activity in RRMS patients.

ELTD1 as a biomarker for multiple sclerosis: Pre-clinical molecular-targeted studies in a mouse experimental autoimmune encephalomyelitis model.

Multiple sclerosis (MS) and glioblastoma (GBM) are two distinct diseases that affect the central nervous system (CNS). However, perturbation in CNS vasculature are hallmarks of both diseases. ELTD1 (epidermal growth factor, latrophilin, and 7 transmembrane domain containing protein 1 on chromosome 1) is associated with vascular development, and has been linked with tumor angiogenesis. In glioblastomas, we detected over-expression of ELTD1, and found that an antibody targeting ELTD1 could increase animal survival and decrease tumor volumes in a xenograft GBM model. RNA-seq analysis of the preclinical data in the model for GBM identified that some of the molecular pathways affected by the anti-ELTD1 antibody therapy are also found to be associated with MS. In this study, we used molecular-targeted (mt) MR imaging and immunohistochemistry to assess ELTD1 levels in experimental autoimmune encephalomyelitis (EAE), a mouse model of MS. Specifically, we found that ELTD1 is readily detected in the brains of mice with EAE and is predominantly found in the corpus callosum. In addition, we found that the blood-brain barrier (BBB) was compromised in the brains of EAE mice using contrast-enhanced MRI (CE-MRI), as well as altered relative cerebral blood flow (rCBF) in the brains and cervical spinal cords of these mice using perfusion imaging, compared to controls. These findings indicate that ELTD1 may be a promising biomarker for CNS-inflammation in MS.