Chang Chia-Wei, Wang Hsin-Yao, Lin Wan-Ying, Wang Yu-Chiang, Lo Wei-Lin, Lin Ting-Wei, Yu Jia-Ruei, Tseng Yi-Ju
Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
BioData Min. 2024 Sep 16;17(1):36. doi: 10.1186/s13040-024-00389-7.
The high complexity of systemic autoimmune diseases (SADs) has hindered precise management. This study aims to investigate heterogeneity in SADs.
We applied a joint cluster analysis, which jointed multiple correspondence analysis and k-means, to immunomarkers and measured the heterogeneity of clusters by examining differences in immunomarkers and clinical manifestations. The electronic health records of patients who received an antinuclear antibody test and were diagnosed with SADs, namely systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and Sjögren's syndrome (SS), were retrieved between 2001 and 2016 from hospitals in Taiwan.
With distinctive patterns of immunomarkers, a total of 11,923 patients with the three SADs were grouped into six clusters. None of the clusters was composed only of a single SAD, and these clusters demonstrated considerable differences in clinical manifestation. Both patients with SLE and SS had a more dispersed distribution in the six clusters. Among patients with SLE, the occurrence of renal compromise was higher in Clusters 3 and 6 (52% and 51%) than in the other clusters (p < 0.001). Cluster 3 also had a high proportion of patients with discoid lupus (60%) than did Cluster 6 (39%; p < 0.001). Patients with SS in Cluster 3 were the most distinctive because of the high occurrence of immunity disorders (63%) and other and unspecified benign neoplasm (58%) with statistical significance compared with the other clusters (all p < 0.05).
The immunomarker-driven clustering method could recognise more clinically relevant subgroups of the SADs and would provide a more precise diagnosis basis.
系统性自身免疫性疾病（SADs）的高度复杂性阻碍了精准管理。本研究旨在调查SADs的异质性。
我们应用了一种联合聚类分析方法，即将多重对应分析和k均值法相结合，用于免疫标志物分析，并通过检查免疫标志物和临床表现的差异来测量聚类的异质性。我们检索了2001年至2016年间台湾地区医院中接受抗核抗体检测并被诊断为SADs（即系统性红斑狼疮（SLE）、类风湿关节炎（RA）和干燥综合征（SS））患者的电子健康记录。
根据独特的免疫标志物模式，共有11923例患有这三种SADs的患者被分为六个聚类。没有一个聚类仅由单一的SADs组成，并且这些聚类在临床表现上存在显著差异。SLE和SS患者在六个聚类中的分布更为分散。在SLE患者中，3组和6组的肾脏受累发生率（分别为52%和51%）高于其他组（p<0.001）。3组盘状红斑狼疮患者的比例（60%）也高于6组（39%；p<0.001）。3组中的SS患者最为独特，因为与其他组相比，免疫紊乱（63%）和其他及未指定的良性肿瘤（58%）的发生率具有统计学意义（所有p<0.05）。
免疫标志物驱动的聚类方法可以识别出更多临床上相关的SADs亚组，并将提供更精确的诊断依据。
