The paper "High-dimensional immune profiling identifies a biomarker to monitor dimethyl fumarate response in multiple sclerosis" has published in PNAS.
Understanding the immunobiology of multiple sclerosis remains an unresolved challenge. Distinctive features of therapeutic response to effective treatments are one important source of insight into the underlying pathomechanisms. Here, we studied dimethyl fumarate, a routinely administered but mechanistically poorly understood compound. We developed an approach using multipanel immunophenotyping by mass cytometry in conjunction with a weakly supervised machine-learning algorithm to facilitate unprejudiced identification of rare but specific immune cell populations accounting for beneficial treatment response. This approach allowed identification of a subset of antigen-experienced T helper cells that are preferentially depleted in responding individuals. As a biomarker, this subset may guide clinical stratification.
Last updated 9 Aug 2022
