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Original article| Volume 56, 103229, November 2021

Myelin oligodendrocyte glycoprotein (MOG) antibody-mediated disease: The difficulty of predicting relapses

  • Samantha E. Epstein
    Correspondence
    Corresponding author at: 710 West 168th Street; Floor 2, New York, NY 10032.
    Affiliations
    Columbia Multiple Sclerosis Center & Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, 710 West 168th Street, New York, NY, USA 10032
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  • Seth Levin
    Affiliations
    Columbia Multiple Sclerosis Center & Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, 710 West 168th Street, New York, NY, USA 10032
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  • Kaho Onomichi
    Affiliations
    Columbia Multiple Sclerosis Center & Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, 710 West 168th Street, New York, NY, USA 10032
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  • Christopher Langston
    Affiliations
    Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Department of Neurology, Icahn School of Medicine at Mount Sinai, 5 East 98th Street, New York, NY, USA 10029
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  • Anusha Yeshokumar
    Affiliations
    Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Department of Neurology, Icahn School of Medicine at Mount Sinai, 5 East 98th Street, New York, NY, USA 10029
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  • Michelle Fabian
    Affiliations
    Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Department of Neurology, Icahn School of Medicine at Mount Sinai, 5 East 98th Street, New York, NY, USA 10029
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  • Ilana Katz Sand
    Affiliations
    Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Department of Neurology, Icahn School of Medicine at Mount Sinai, 5 East 98th Street, New York, NY, USA 10029
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  • Sylvia Klineova
    Affiliations
    Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Department of Neurology, Icahn School of Medicine at Mount Sinai, 5 East 98th Street, New York, NY, USA 10029
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  • Fred Lublin
    Affiliations
    Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Department of Neurology, Icahn School of Medicine at Mount Sinai, 5 East 98th Street, New York, NY, USA 10029
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  • Kiersten Dykstra
    Affiliations
    University of Pittsburgh, Department of Neurology, 811 Kaufmann Medical Building, 3471 Fifth Avenue, Pittsburgh, PA, USA 15213
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  • Zongqi Xia
    Affiliations
    University of Pittsburgh, Department of Neurology, 811 Kaufmann Medical Building, 3471 Fifth Avenue, Pittsburgh, PA, USA 15213
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  • Philip De Jager
    Affiliations
    Columbia Multiple Sclerosis Center & Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, 710 West 168th Street, New York, NY, USA 10032
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  • Libby Levine
    Affiliations
    Columbia Multiple Sclerosis Center & Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, 710 West 168th Street, New York, NY, USA 10032
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  • Rebecca Farber
    Affiliations
    Columbia Multiple Sclerosis Center & Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, 710 West 168th Street, New York, NY, USA 10032
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  • Claire Riley
    Affiliations
    Columbia Multiple Sclerosis Center & Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, 710 West 168th Street, New York, NY, USA 10032
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  • Wendy S. Vargas
    Affiliations
    Columbia Multiple Sclerosis Center & Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, 710 West 168th Street, New York, NY, USA 10032
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Published:August 28, 2021DOI:https://doi.org/10.1016/j.msard.2021.103229

      Highlights

      • Patients with MOG-AD may have a monophasic or relapsing disease course.
      • 57% of our cohort had a relapsing course.
      • The most common relapse phenotype was optic neuritis.
      • Neither age, gender, race, initial attack, or antibody titer predicted relapse risk.
      • 50% of patients on disease modifying therapy continued to relapse.

      Abstract

      Background

      While many patients with myelin oligodendrocyte glycoprotein antibody-mediated disease (MOG-AD) will have a monophasic course, 30-80% of patients will relapse after the initial attack. It is not known which factors predict relapse. Here we describe our clinical experience with MOG-AD and evaluate for factors that correlate with relapsing disease.

      Methods

      This was a retrospective, multi-institutional study of 54 patients with MOG-AD, including 17 children and 37 adults. Mann-Whitney U and Fischer's Exact tests were used for comparisons and logistic regression for correlations.

      Results

      Incident attack phenotype included acute disseminated encephalomyelitis (15%), unilateral optic neuritis (ON; 39%), bilateral ON (24%), transverse myelitis (TM; 11%) and ON with TM (11%). Pediatric patients were more likely than adults to present with ADEM (p = .009) and less likely to present with unilateral ON (p = .04). 31 patients (57%) had a relapsing disease course, with time to first relapse of 8.2 months and median annualized relapse rate of 0.97 months. In 40% of patients (n = 22) the first relapse occurred following the withdrawal of treatment for the incident attack. 5 patients converted to seronegative at follow up, 2 of whom later relapsed. Logistic regression revealed no significant relationship between age, gender, race, presentation phenotype, antibody titer, or cerebrospinal fluid results with risk of relapse. For patients who started disease modifying therapy (DMT) prior to the first relapse (n = 11), 64% remained monophasic. 50% (n = 15) of patients on DMT continued to have disease activity, requiring treatment adjustment.

      Conclusions

      It is difficult to predict which patients with MOG-AD will relapse. Research is needed to determine the optimal timing and choice of treatment.

      Keywords

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