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Published on: December 9, 2015
Peripheral HLA-DRhiCD141+ Classical Monocytes Predict Relapse Risk and Worsening in Multiple Sclerosis
Karine Thai1,2, Rose-Marie Rebillard1,2, Wendy Klement2
1Department of Neuroscience, Université de Montréal, Montréal, Canada.
Insights
A novel biomarker, HLA-DRhiCD141+ classical monocytes (CMs), in peripheral blood mononuclear cells (PBMCs) can predict multiple sclerosis (MS) relapses. This immune cell signature offers a promising tool for monitoring MS disease activity and guiding treatment decisions.
Area of Science:
- Neuroimmunology
- Cellular Immunology
- Biomarker Discovery
Background:
- Multiple sclerosis (MS) is a heterogeneous CNS demyelinating disease requiring biomarkers for activity prediction.
- Current tools assess existing damage, not impending disease activity.
- Peripheral blood mononuclear cells (PBMCs) are accessible sources for MS biomarkers, with myeloid cells playing a key role.
Purpose of the Study:
- To identify immune cell indicators of MS disease activity through comprehensive immune profiling.
- To investigate the potential of myeloid cell subpopulations as predictors of MS progression.
Main Methods:
- High-dimensional flow cytometry analysis of PBMCs, focusing on myeloid cell populations.
- Unsupervised clustering for single-cell immune landscape definition.
- Supervised machine learning to extract immune features associated with MS activity.
Main Results:
- Analysis of 135 MS patients and 44 healthy controls (HCs).
- Identification of a classical monocyte (CM) subpopulation (HLA-DRhiCD141+) as a predictor of 2-year relapse risk (HR 2.8) and disability worsening.
- This CM subpopulation, identifiable via manual gating, showed stronger prognostic value for relapse risk than serum neurofilament light chain.
Conclusions:
- The frequency of HLA-DRhiCD141+ CMs serves as a valuable predictor of MS disease activity.
- This biomarker can complement existing clinical tools for informed treatment decisions.
- Highlights the potential of myeloid cell profiling for advancing MS management.
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:
We analyzed PBMCs from 135 individuals with MS with retrospective longitudinal follow-up and 44 healthy controls (HCs). Among the individuals with MS, 53 were untreated and were compared with HCs. Using an elastic-net model, 20 immune features were identified as contributors to the classification of MS and HCs (receiver operating characteristic-AUC 0.8881). To explore associations between immune features and disease activity, we focused on individuals with relapsing-remitting MS (n = 106). We identified a subpopulation of classical monocytes (CMs) with high expression of human leukocyte antigen - DR isotype (HLA-DR) and positive for CD141 (HLA-DRhiCD141+) as a predictor of impending relapses over 2 years (hazard ratio [HR] 2.8, 95% CI 1.6-4.7) and disability worsening in patients with higher relapse activity. HLA-DRhiCD141+ CMs could be retrieved by manual gating using 9 parameters and were similarly indicative of 2-year relapse risk (HR 1.9, 95% CI 1.3-2.8), highlighting its potential as a practical, translational approach. Compared with the widely studied biomarker serum neurofilament light chain reflecting acute activity, HLA-DRhiCD141+ CMs provided a stronger prognostic value for impending relapse risk, suggesting different kinetics related to the underlying pathology.
Discussion:
Our findings suggest that the frequency of HLA-DRhiCD141+ CMs could serve as a valuable predictor of disease activity complementary to current clinical tools to guide evidence-based treatment decisions.

