Autoimmune GFAP Astrocytopathy—Beyond the Known Horizon, India’s First Multifaceted Institutional Experience

Background: Autoimmune glial fibrillary acidic protein (GFAP) astrocytopathy is an immune-mediated inflammatory disease of the central nervous system, the clinical phenotype of which includes meningoencephalitis, myelitis, optic neuritis, seizures, movement disorders, autonomic dysfunction among others, affecting people across all ages. Due to its recent discovery, there is a paucity of literature on this topic and an absolute lack of Indian case series. Purpose: This study aims to shed light on the variable presentations of anti-GFAP astrocytopathy and review the existing literature on the topic. Methods: This was a retrospective study that included all patients who tested positive in the cerebrospinal fluid(CSF) and/or serum for GFAP immunoglobulin G between February 2023 and August 2023, after obtaining ethical clearance. Relevant clinical, demographic data was collected from the electronic medical records. A descriptive analysis of data was done and the current available literature was reviewed. Results: Our case series included four patients (F:M::3:1) with a median age of 28 years at symptom onset. Two of the cases had a relapsing-remitting disease pattern, while the other two had monophasic illnesses. The clinical spectrum we encountered included ataxia, tremors, myoclonus, seizures, recurrent myelitis, brain stem syndromes, autonomic dysfunction and psychiatric manifestations. All four patients responded remarkably to steroids and two patients are on rituximab therapy. Conclusion: Autoimmune GFAP astrocytopathy encompasses an expanding clinical spectrum and should be considered in the context of myelitis, optic neuritis, ataxia, papillitis, seizures, autonomic dysfunction and movement disorders occurring in isolation or more commonly in varying combinations. Our case series, the first in India, shows a favourable clinical profile and the primary hurdle encountered in all four cases was to establish a diagnosis, further stressing the need for a predictive diagnostic algorithm.