The role of interferon (IFN)-γ in multiple sclerosis (MS) and its animal model, experimental autoimmune encephalomyelitis (EAE), has remained as an enigmatic paradox for more than 30 years. Several studies attribute this cytokine a prominent proinflammatory and pathogenic function in these pathologies. However, accumulating evidence shows that IFN-γ also plays a protective role inducing regulatory cell activity and modulating the effector T cell response. Several innate and adaptive immune cells also develop opposite functions strongly associated with the production of IFN-γ in EAE. Even the suppressive activity of different types of regulatory cells is dependent on IFN-γ. Interestingly, recent data supports a stage-specific participation of IFN-γ in EAE providing a plausible explanation for previous conflicting results. In this review, we will summarize and discuss such literature, emphasizing the protective role of IFN-γ on immune cells. These findings are fundamental to understand the complex role of IFN-γ in the pathogenesis of these diseases and can provide basis for potential stage-specific therapy for MS targeting IFN-γ-signaling or IFN-γ-producing immune cells.

Multiple sclerosis (MS) is the principal cause of autoimmune neuroinflammation in humans, and its animal model, experimental autoimmune encephalomyelitis (EAE), is widely used to gain insight about their immunopathological mechanisms for and the development of novel therapies for MS. Most studies on the role of interferon (IFN)-γ in the pathogenesis and progression of EAE have focused on peripheral immune cells, while its action on central nervous system (CNS)-resident cells has been less explored. In addition to the well-known proinflammatory and damaging effects of IFN-γ in the CNS, evidence has also endowed this cytokine both a protective and regulatory role in autoimmune neuroinflammation. Recent investigations performed in this research field have exposed the complex role of IFN-γ in the CNS uncovering unexpected mechanisms of action that underlie these opposing activities on different CNS-resident cell types. The mechanisms behind these two-faced effects of IFN-γ depend on dose, disease phase, and cell development stage. Here, we will review and discuss the dual role of IFN-γ on CNS-resident cells in EAE highlighting its protective functions and the mechanisms proposed.

Multiple sclerosis (MS) is a chronic, inflammatory, and demyelinating disease of the central nervous system. It is a heterogeneous pathology that can follow different clinical courses, and the mechanisms that underlie the progression of the immune response across MS subtypes remain incompletely understood. Here, we aimed to determine differences in the immunological status among different MS clinical subtypes. Blood samples from untreated patients diagnosed with clinically isolated syndrome (CIS) (n = 21), different clinical forms of MS (n = 62) [relapsing–remitting (RRMS), secondary progressive, and primary progressive], and healthy controls (HCs) (n = 17) were tested for plasma levels of interferon (IFN)-γ, IL-10, TGF-β, IL-17A, and IL-17F by immunoanalysis. Th1 and Th17 lymphocyte frequencies were determined by flow cytometry. Our results showed that IFN-γ levels and the IFN-γ/IL-10 ratio were higher in CIS patients than in RRMS patients and HC. Th1 cell frequencies were higher in CIS and RRMS than in progressive MS, and RRMS had a higher Th17 frequency than CIS. The Th1/Th17 cell ratio was skewed toward Th1 in CIS compared to MS phenotypes and HC. Receiver operating characteristic statistical analysis determined that IFN-γ, the IFN-γ/IL-10 ratio, Th1 cell frequency, and the Th1/Th17 cell ratio discriminated among CIS and MS subtypes. A subanalysis among patients expressing high IL-17F levels showed that IL-17F and the IFN-γ/IL-17F ratio discriminated between disease subtypes. Overall, our data showed that CIS and MS phenotypes displayed distinct Th1- and Th17-related cytokines and cell profiles and that these immune parameters discriminated between clinical forms. Upon validation, these parameters might be useful as biomarkers to predict disease progression.

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