Multiple sclerosis endophenotypes identified by high-dimensional blood signatures are associated with distinct disease trajectories

Gross Catharina , Schulte-Mecklenbeck Andreas , Steinberg Vsevolodivna Olga , Wirth Timo , Lauks Sarah , Bittner Stefan , Schindler Patrick , Baranzini Sergio , Groppa Sergiu , Bellmann-Strobl Judith , Buenger Nora , Chien Claudia , Dawin Eva , Eveslage Maria , Fleischer Vinzenz , Escamilla Gonzalez Gabriel , Gisevius Barbara , Haas Juergen , Kerschensteiner Martin , Kirstein Lucienne , Korsukewitz Catharina , Revie Lisa , Lunemann Jan , Luessi Felix , Horste zu Meyer Gerd , Motte Jeremias , Ruck Tobias , Ruprecht Klemens , Schwab Nicholas , Steffen Falk , Meuth G. Sven , paul friedemann , Wildemann Brigitte , Kümpfel Tania , Gold Ralf , Hahn Tim , Zipp Frauke , Klotz Luisa , Wiendl Heinz , Aktas Orhan , Ayzenberg Ilya , Bahn Erik , Bayas Antonios , Berger Klaus , Berthele Achim , Brück Wolfgang , Engel Sina , Friede Tim , Heesen Christoph , Hellwig Kerstin , Hemmer Bernhard

Research article (journal) | Peer reviewed

Abstract

The autoimmune disease multiple sclerosis (MS) is a highly heterogeneous disease with many different treatment options. However, it is not clear whether certain features of MS are associated with distinct immune signatures or would benefit from particular therapies. Here, Gross et al. used peripheral blood mononuclear cells and serum collected from two independent cohorts of patients with MS to identify three endophenotypes of the disease. These peripheral blood immune signatures distinguished patients with distinct clinical disease trajectories and efficacy of interferon-β treatment. These data suggest that peripheral blood analysis could be used to guide personalized treatment regimens for patients with MS.

Details about the publication

JournalScience translational medicine (Sci Transl Med)
Volume16
Issue740
StatusPublished
Release year2024 (27/03/2024)
DOI10.1126/scitranslmed.ade8560
Link to the full texthttp://dx.doi.org/10.1126/scitranslmed.ade8560
KeywordsMultiple Sclerosis; Immunephenotyping; Machine Learning; Translational

Authors from the University of Münster

Wirth, Timo
Department for Neurology