Peripheral HLA-DR hi CD141 + Classical Monocytes Predict Relapse Risk and Worsening in Multiple Sclerosis

This is the authors' abstract. We don't add key points for this paper.

BACKGROUND AND OBJECTIVES: Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the CNS characterized by a heterogeneous disease trajectory, highlighting the need for biomarkers to predict disease activity. Current disease-monitoring tools primarily reflect existing disease damage rather than impending activity. Peripheral blood mononuclear cells (PBMCs) are an ideal source of potential biomarkers due to their accessibility and their known role in MS pathology. Among PBMCs, myeloid cells are key players in MS pathogenic processes, yet they have not been as extensively studied than lymphocytes. The objective of our study was to identify indicators of MS disease activity through immune profiling. METHODS: We analyzed PBMCs using high-dimensional flow cytometry with a panel focusing on myeloid cells. We performed unsupervised clustering analyses to define a comprehensive immune landscape at a single-cell resolution. Supervised machine learning methods were used to extract immune features indicative of MS activity. RESULTS: CMs provided a stronger prognostic value for impending relapse risk, suggesting different kinetics related to the underlying pathology. DISCUSSION: CMs could serve as a valuable predictor of disease activity complementary to current clinical tools to guide evidence-based treatment decisions.