›› 2018, Vol. 38 ›› Issue (10): 1252-.doi: 10.3969/j.issn.1674-8115.2018.10.021

• Review • Previous Articles     Next Articles

Research progress on myasthenia gravis related autoantibody and detection approaches

HUANG Xin-xin1, ZHU De-sheng2, XU Jian-rong3, GUAN Yang-tai1, 2   

  1. 1. Department of Neurology, Changhai Hospital, Second Military Medical University, Shanghai 200433, China; 2. Department of Neurology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China; 3. Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University College of Medical Sciences, Shanghai 200025, China
  • Online:2018-10-28 Published:2018-11-18
  • Supported by:
    National Natural Science Foundation of China, 81471219; Translational Medicine Collaborative Innovation Cooperation Research Project of Shanghai Jiao Tong University School of Medicine, TM201508, TM201706

Abstract: Myasthenia gravis (MG) is an autoimmue disease mediated mainlyhumoral immunity, which is characterisedskeletal muscle weakness and fatigue. Its pathogensis is closely related to the autoantibodies against the postsynaptic membrane components at neuromuscular junction (NMJ), including acetylcholine receptor (AChR) antibody, muscle-specific receptor tyrosine kinase (MuSK) antibody, and low-density lipoprotein receptor-related protein 4 (LRP4) antibody. In recent years, autoantibodies against antigens such as agrin, collagen Q, and cortactin have been identified. Based on serum antibody patterns, MG can be divided into different subgroups: AChR-MG, MuSK-MG, LRP4-MG and seronegative MG. The detection of autoantibody is vital in clinical for subgroup diagnosis, treatment and prognosis. With the development of medical techniques, the antibody detection approaches were improved, providing new opportunities for precise diagnosis and treatment of different subgroups. Thus, this paper reviewed the latest progress of MG autoantibody classification and the antibody detection approaches.

Key words: myasthenia gravis, autoantibody, detection approach, disease subgroup

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