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.
Abstract