Abstract
Myasthenia gravis (MG) is a classic autoimmune neuromuscular disease with strong clinical heterogeneity. The concept of subgroup classification was proposed to guide the precise treatment of MG. Subgroups based on serum antibodies and clinical features include ocular MG, early-onset MG with AchR antibodies, late-onset MG with AchR antibodies, thymoma-associated MG, MuSK-associated MG, LRP4-associated MG, and seronegative MG. However, reliable objective biomarkers are still needed to reflect the individualized response to therapy. MicroRNAs (miRNAs) are small non-coding RNA molecules which can specifically bind to target genes and regulate gene expression at the post-transcriptional level, and then influence celluar biological processes. MiRNAs play an important role in the pathogenesis of autoimmune diseases, including MG. Several studies on circulating miRNAs in MG have been reported. However, there is rare systematic review to summarize the differences of these miRNAs in different subgroups of MG. Here, we summarize the potential role of circulating miRNAs in different subgroups of MG to promote personalized medicine.
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Funding
This work was supported by The Open Project of Key Laboratory of Colleges and Universities in Jiangsu Province (XZSYSKF2021041), Science and Technology Development Fund of Affiliated Hospital of Xuzhou Medical University (XYFM2021017), Medical research project of Jiangsu Provincial Health Commission (M2022118), Postgraduate Research & Practice Innovation Program of Jiangsu Province (SJCX22_1270, SJCX22_1289).
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X. Y. H. and Z. A. Z. conceptualized the study and wrote the manuscript. Y. Y. W., M. M. X., and X. D. participated in the production of figure and table. Y. Z. contributed to edit a drafting of the manuscript. All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.
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Huang, X., Zhang, Z., Wang, Y. et al. Circulating miRNAs drive personalized medicine based on subgroup classification in myasthenia gravis patients. Neurol Sci 44, 3877–3884 (2023). https://doi.org/10.1007/s10072-023-06933-3
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DOI: https://doi.org/10.1007/s10072-023-06933-3