Advancements and prospects of novel biologicals for myasthenia gravis: toward personalized treatment based on autoantibody specificities.

Myasthenia gravis (MG) is an antibody-mediated autoimmune disease with a prevalence of 150-250 cases per million individuals. Autoantibodies include long-lived antibodies against the acetylcholine receptor (AChR), mainly of the IgG1 subclass, and IgG4, produced almost exclusively by short-lived plasmablasts, which are prevalent in muscle-specific tyrosine kinase (MuSK) myasthenia gravis. Numerous investigations have demonstrated that MG patients receiving conventional medication today still do not possess satisfactory symptom control, indicating a substantial disease burden. Subsequently, based on the type of the autoantibody and the pathogenesis, we synthesized the published material to date and reached a conclusion regarding the literature related to personalized targeted therapy for MG. Novel agents for AChR MG have shown their efficacy in clinical research, such as complement inhibitors, FcRn receptor antagonists, and B-cell activating factor (BAFF) inhibitors. Rituximab, a representative drug of anti-CD20 therapy, has demonstrated benefits in treatment of MuSK MG patients. Due to the existence of low-affinity antibodies or unidentified antibodies that are inaccessible by existing methods, the treatment for seronegative MG remains complicated; thus, special testing and therapy considerations are necessary. It may be advantageous to initiate the application of novel biologicals at an early stage of the disease. Currently, therapies can also be combined and individualized according to different types of antibodies. With such a wide range of drugs, how to tailor treatment strategies to patients with various conditions and find the most suitable solution for each MG profile are our necessary and urgent aims.
Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
(Copyright © 2024 Ma, Liu, Wang, Yang and Zhu.)