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CD163 和主要组织相容性复合体 I 类的表达作为特发性炎症性肌病的诊断标志物。

Expression of CD163 and major histocompatibility complex class I as diagnostic markers for idiopathic inflammatory myopathies.

机构信息

Division of Rheumatology, Jeju National University School of Medicine, Jeju National University Hospital, Jeju, Republic of Korea.

Division of Rheumatology, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.

出版信息

Arthritis Res Ther. 2024 Jul 30;26(1):144. doi: 10.1186/s13075-024-03364-z.

Abstract

BACKGROUND

To develop an inflammation-related immunohistochemistry marker-based algorithm that confers higher diagnostic ability for idiopathic inflammatory myopathies (IIMs) than IIM-related histopathologic features.

METHODS

Muscle biopsy tissues from 129 IIM patients who met the 2017 EULAR/ACR criteria and 73 control tissues from patients with non-inflammatory myopathies or healthy muscle specimens were evaluated for histological features and immunostaining results of CD3, CD4, CD8, CD20, CD68, CD163, MX1, MHC class I, MHC class II, and HLA-DR. Diagnostic algorithms for IIM were developed based on the results of the classification and regression tree (CART) analysis, which used immunostaining results as predictor variables for classifying patients with IIMs.

RESULTS

In the analysis set (IIM, n = 129; control, n = 73), IIM-related histopathologic features had a diagnostic accuracy of 87.6% (sensitivity 80.6%; specificity 100.0%) for IIMs. Notably, muscular expression of CD163 (99.2% vs. 20.8%, p < 0.001) and MHC class I (87.6% vs. 23.1%, p < 0.001) was significantly higher in the IIM group than in controls. Based on the CART analysis results, we developed an algorithm combining CD163 and MHC class I expression that conferred a diagnostic accuracy of 95.5% (sensitivity 96.1%; specificity 94.5%). In addition, our algorithm was able to correctly diagnose IIM in 94.1% (16/17) of patients who did not meet the 2017 EUALR/ACR criteria but were diagnosed as having IIMs by an expert physician.

CONCLUSIONS

Combination of CD163 and MHC class I muscular expression may be useful in diagnosing IIMs.

摘要

背景

开发一种与炎症相关的免疫组织化学标志物算法,该算法比特发性炎性肌病(IIM)相关的组织病理学特征能提供更高的诊断能力。

方法

评估了 129 名符合 2017 年 EULAR/ACR 标准的特发性炎性肌病患者的肌肉活检组织和 73 名非炎性肌病患者或健康肌肉标本的对照组织的组织学特征和免疫染色结果,包括 CD3、CD4、CD8、CD20、CD68、CD163、MX1、MHC Ⅰ类、MHC Ⅱ类和 HLA-DR。基于分类回归树(CART)分析的结果,开发了用于 IIM 的诊断算法,该分析使用免疫染色结果作为分类特发性炎性肌病患者的预测变量。

结果

在分析集(IIM,n=129;对照组,n=73)中,IIM 相关的组织病理学特征对 IIM 的诊断准确性为 87.6%(敏感性 80.6%;特异性 100.0%)。值得注意的是,CD163(99.2%对 20.8%,p<0.001)和 MHC Ⅰ类(87.6%对 23.1%,p<0.001)在 IIM 组的肌肉表达明显高于对照组。基于 CART 分析结果,我们开发了一种结合 CD163 和 MHC Ⅰ类表达的算法,其诊断准确性为 95.5%(敏感性 96.1%;特异性 94.5%)。此外,我们的算法能够正确诊断 94.1%(16/17)的未满足 2017 EUALR/ACR 标准但被专家医生诊断为 IIM 的患者。

结论

CD163 和 MHC Ⅰ类肌肉表达的组合可能有助于诊断 IIM。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/00b9/11290050/1dcbaa4bb52f/13075_2024_3364_Fig1_HTML.jpg

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