Xupeng Sun, Meijie Qu, Xi Rong, Mingxing Lv, Yunbin Zhao, Yunjun Yan, Lin Liu, Na Sun, Hua Yue, Min Liu
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引用次数: 0
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.
期刊介绍:
The section Stroke aims to quickly and accurately publish important experimental, translational and clinical studies, and reviews that contribute to the knowledge of stroke, its causes, manifestations, diagnosis, and management.