Autoantibodies in myasthenia gravis: cluster analysis and clinical correlations

重症肌无力中的自身抗体:聚类分析和临床相关性

阅读:1

Abstract

OBJECTIVE: This study aimed to explore autoantibody clusters and their correlations with clinical features in 644 myasthenia gravis (MG) patients. METHODS: Medical records of 664 MG patients were reviewed. Five autoantibodies (AChR, MuSK, titin, RyR, and LRP4) were selected for cluster analysis. The various clinical manifestations were compared between clusters. Separate association analyses between individual autoantibodies and clinical manifestations as well as among different MGFA subtypes were also performed without prior clustering. RESULTS: Two separate autoantibody clusters were identified, with significantly different clinical manifestations. Cluster 1 (485 patients) was characterized by higher proportions of RyR-, titin-, and AChR-, while cluster 2 (179 patients) had higher proportions of RyR+, titin+, and AChR+. Cluster 2 patients were older and had elevated QMG scores and odds of complications, particularly hypertension, diabetes, cardiovascular and cerebrovascular diseases, and eye conditions. Individual antibody analysis revealed that male cases were more likely to be AChR+ and titin+, and older age was associated with AChR+, RyR+, and titin+. Among MGFA subtypes, significant differences were detected in AChR, MuSK, titin, complications, thymoma, and hypertension. As MG severity increased from types I to V, AChR+, RyR+, and titin+ proportions peaked at stage IIa. MuSK+ patients were relatively rare and mostly present in the subtype b group. Type b patients had higher MuSK+ prevalence and increased cardiovascular and cerebrovascular disease incidence rates than type a cases. CONCLUSION: Overall, cluster 2 features were less favorable to patients. This study provides valuable insights into the clinical and autoantibody profiles of Chinese MG patients.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。