Targeted proteomics of cerebrospinal fluid in treatment naïve multiple sclerosis patients identifies immune biomarkers of clinical phenotypes.

Multiple sclerosis (MS) is an inflammatory demyelinating disease with heterogeneous clinical presentations and variable long-term disability accumulation. There are currently no standard criteria to accurately predict disease outcomes. In this study we investigated the cross-sectional relationship between disease phenotype and immune-modulating cytokines and chemokines in cerebrospinal fluid (CSF). We analyzed CSF from 20 DMT-naïve MS patients using Olink Proteomics' Target 96 Inflammation panel and correlated the resulting analytes with respect to (1) disease subtype, (2) patient age and sex, (3) extent of clinical disability, and (4) MRI segmental brain volumes. We found that intrathecal IL-4 correlated with higher Expanded Disability Status Scale (EDSS) scores and longer 25-foot walk times, and CD8A correlated with decreased thalamic volumes and longer 9-hole peg test times. Male sex was associated with higher FGF-19 expression, and Tumefactive MS with elevated CCL4. Several inflammatory markers were correlated with older age at the time of LP. Finally, higher intrathecal IL-33 correlated with increased MS lesion burden and multi-compartment brain atrophy. This study confirms immune heterogeneity underlying CSF profiles in MS, but also identifies several inflammatory protein biomarkers that may be of use for predicting clinical outcomes in future algorithms.

Multi-omics analysis of magnetically levitated plasma biomolecules.

We recently discovered that superparamagnetic iron oxide nanoparticles (SPIONs) can levitate plasma biomolecules in the magnetic levitation (MagLev) system and cause formation of ellipsoidal biomolecular bands. To better understand the composition of the levitated biomolecules in various bands, we comprehensively characterized them by multi-omics analyses. To probe whether the biomolecular composition of the levitated ellipsoidal bands correlates with the health of plasma donors, we used plasma from individuals who had various types of multiple sclerosis (MS), as a model disease with significant clinical importance. Our findings reveal that, while the composition of proteins does not show much variability, there are significant differences in the lipidome and metabolome profiles of each magnetically levitated ellipsoidal band. By comparing the lipidome and metabolome compositions of various plasma samples, we found that the levitated biomolecular ellipsoidal bands do contain information on the health status of the plasma donors. More specifically, we demonstrate that there are particular lipids and metabolites in various layers of each specific plasma pattern that significantly contribute to the discrimination of different MS subtypes, i.e., relapsing-remitting MS (RRMS), secondary-progressive MS (SPMS), and primary-progressive MS (PPMS). These findings will pave the way for utilization of MagLev of biomolecules in biomarker discovery for identification of diseases and discrimination of their subtypes.