Literature DB >> 29875313

Monocyte NOTCH2 expression predicts IFN-β immunogenicity in multiple sclerosis patients.

Marsilio Adriani1, Petra Nytrova2, Cyprien Mbogning3, Signe Hässler3, Karel Medek2, Poul Erik H Jensen4, Paul Creeke5, Clemens Warnke6,7, Kathleen Ingenhoven6, Bernhard Hemmer8, Claudia Sievers9, Raija Lp Lindberg Gasser9, Nicolas Fissolo10, Florian Deisenhammer11, Zsolt Bocskei12, Vincent Mikol12, Anna Fogdell-Hahn13, Eva Kubala Havrdova2, Philippe Broët3,14, Pierre Dönnes15, Claudia Mauri1, Elizabeth C Jury1.   

Abstract

Multiple sclerosis (MS) is an autoimmune disease characterized by CNS inflammation leading to demyelination and axonal damage. IFN-β is an established treatment for MS; however, up to 30% of IFN-β-treated MS patients develop neutralizing antidrug antibodies (nADA), leading to reduced drug bioactivity and efficacy. Mechanisms driving antidrug immunogenicity remain uncertain, and reliable biomarkers to predict immunogenicity development are lacking. Using high-throughput flow cytometry, NOTCH2 expression on CD14+ monocytes and increased frequency of proinflammatory monocyte subsets were identified as baseline predictors of nADA development in MS patients treated with IFN-β. The association of this monocyte profile with nADA development was validated in 2 independent cross-sectional MS patient cohorts and a prospective cohort followed before and after IFN-β administration. Reduced monocyte NOTCH2 expression in nADA+ MS patients was associated with NOTCH2 activation measured by increased expression of Notch-responsive genes, polarization of monocytes toward a nonclassical phenotype, and increased proinflammatory IL-6 production. NOTCH2 activation was T cell dependent and was only triggered in the presence of serum from nADA+ patients. Thus, nADA development was driven by a proinflammatory environment that triggered activation of the NOTCH2 signaling pathway prior to first IFN-β administration.

Entities:  

Keywords:  Immunology; Immunotherapy; Monocytes; Multiple sclerosis; Neuroscience

Mesh:

Substances:

Year:  2018        PMID: 29875313      PMCID: PMC6124413          DOI: 10.1172/jci.insight.99274

Source DB:  PubMed          Journal:  JCI Insight        ISSN: 2379-3708


  63 in total

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