ArticleBrain communications2026
A novel multiplexed biomarker panel reveals key molecular pathways in progressive multiple sclerosis.
Article in Brain communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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15 authors.
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Abstract
Progressive multiple sclerosis is characterized by gradual neurological decline, often occurring independently of relapses or MRI activity-a phenomenon known as progression independent of relapse and MRI activity (PIRMA). Despite the effectiveness of disease-modifying therapies in controlling inflammatory activity, identifying individuals at risk of PIRMA remains an unmet clinical need. The objective of this exploratory study was to identify biomarkers and underlying molecular pathways associated with multiple sclerosis progression and especially PIRMA. Using the NUcleic acid Linked Immuno-Sandwich Assay (NULISA) inflammatory panel, we quantified 250 immune-related proteins in CSF and plasma from 49 controls, 49 patients with early active relapsing-remitting multiple sclerosis (RRMS) and 33 patients with inactive progressive multiple sclerosis (iPMS). Longitudinal clinical data were used to define PIRMA and conversion to secondary progressive multiple sclerosis (SPMS). We identified distinct proteomic signatures in CSF of both RRMS and iPMS patients compared with controls, with no significant differences in plasma. Both were associated with elevated markers of adaptive immunity, while iPMS showed a shift towards innate immune markers. Among RRMS patients, low baseline CSF concentrations of KIT ligand (KITLG) predicted both conversion to SPMS and future PIRMA events. Receiver operating characteristic analysis demonstrated KITLG's potential as a prognostic biomarker. Additionally, plasma concentrations of interleukin 1 beta and 36 gamma were elevated in RRMS patients who later developed SPMS. A model selection analysis identified a two-protein logistic regression model including interleukin 1 beta and interleukin 36 gamma as the best-performing combination (area under the curve = 0.990). Our findings reveal distinct immunological profiles across multiple sclerosis subtypes and identify KITLG as a promising biomarker for predicting disease progression and PIRMA. These results highlight potential targets for therapeutic intervention and demonstrate the utility of NULISA in uncovering novel molecular signatures in multiple sclerosis.
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