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Multiple sclerosis-associated EBNA2 variants influence the response to peginterferon beta-1a therapy
Caterina Veroni1, Fortunata Carbone2, Daniela Ricci3
1Department of Neuroscience, Istituto Superiore di Sanità, Rome, Italy.
Background:
Strong evidence links Epstein-Barr virus (EBV) infection to Multiple Sclerosis (MS). Peginterferon beta-1a (peg-IFN), currently the most used interferon formulation among first-line treatments in MS, displays immunomodulatory, anti-inflammatory, and antiviral properties and remains also an important therapeutic option in conditions such as pregnancy, lactation and aging patients.
Objectives:
In this study we evaluated the ability of peg-IFN to restore a homeostatic EBV-host interaction in MS by regulating antiviral and immunometabolic responses.
Methods:
In people with MS (pwMS), peripheral blood mononuclear cells (PBMCs) were analyzed before (T0) and after six months (T6mos) of peg-IFN administration: IFN-stimulated gene (ISG) levels, EBV DNA load, Epstein-Barr nuclear antigen 2 (EBNA2) allele distribution, and T-lymphocyte phenotyping with glycolytic metabolism were assessed.
Results:
Peg-IFN increased ISG transcription and glycolysis in CD4+ T lymphocytes, and reduced EBV DNA load without altering EBNA2 allele distribution. Notably, ISG expression increase at T6mos in pwMS infected by the non-risk 1.3B EBNA2 allele, correlating with a better long-term response to peg-IFN after 2-years. Lower T-cell glycolytic capacity at T0 predicted higher peg-IFN responsiveness in pwMS carrying the 1.3B allele, suggesting that EBNA2 variants might be predictive of response to peg-IFN.
Conclusion:
Here, we found that infection with MS-associated EBNA2 variants might be involved in the clinical response to peg-IFN therapy. The predictive model developed, which integrates immunological and viral parameters, may help clinicians in a finer selection of first-line therapies tailored to patient profiles, supporting personalized medicine approaches.
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