Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Neuroimmunomodulation. 2022;29(3):220-230. doi: 10.1159/000519835. Epub 2021 Nov 25.
The immunological features between neuromyelitis optica spectrum disorder (NMOSD), multiple sclerosis (MS), and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), lacked systemic comparisons. Accordingly, we aimed to investigate immunological differences between NMOSD, MS, and MOGAD.
Patients with MOGAD, MS, and NMOSD who received immunological tests including cytokine profiles and cytometry analysis of the lymphocyte subgroups were retrospectively reviewed and divided into training and validation sets. Discriminatory models based on immunological data were established to identify optimal classifiers using orthogonal partial least square discriminant analysis (OPLS-DA). Constructed models were tested in another independent cohort.
OPLS-DA of the immunological data from 50 patients (26 NMOSD, 14 MS, and 10 MOGAD) demonstrated the discriminatory values of a relatively low level of T-lymphocyte subsets, especially the CD4+ T cells, in MOGAD; a decreased NK cell, eosinophil, and lymphocyte level; an elevated neutrophil-to-lymphocyte ratio in NMOSD; and a declined IFN-γ-producing CD4+ T cells/Th with an increased IL-8 concentration in MS. All the models (NMOSD vs. MS, NMOSD vs. MOGAD, and MS vs. MOGAD) exhibited a significant predictive value and accuracy (>85%).
NMOSD, MS, and MOGAD may be different in pathogenesis, and several immunological biomarkers can serve as potential classifiers clinically.
视神经脊髓炎谱系疾病（NMOSD）、多发性硬化症（MS）和髓鞘少突胶质细胞糖蛋白抗体相关疾病（MOGAD）之间的免疫学特征缺乏系统比较。因此，我们旨在研究 NMOSD、MS 和 MOGAD 之间的免疫学差异。
回顾性分析了接受免疫检查包括细胞因子谱和淋巴细胞亚群流式细胞术分析的 MOGAD、MS 和 NMOSD 患者，并将其分为训练集和验证集。基于免疫数据建立判别模型，使用正交偏最小二乘判别分析（OPLS-DA）确定最佳分类器。在另一个独立队列中测试构建的模型。
对 50 例患者（26 例 NMOSD、14 例 MS 和 10 例 MOGAD）的免疫数据进行 OPLS-DA 分析显示，MOGAD 中 T 淋巴细胞亚群，尤其是 CD4+T 细胞水平相对较低；NK 细胞、嗜酸性粒细胞和淋巴细胞水平降低；NMOSD 中中性粒细胞与淋巴细胞比值升高；MS 中 IFN-γ产生的 CD4+T 细胞/Th 下降，IL-8 浓度升高。所有模型（NMOSD 与 MS、NMOSD 与 MOGAD、MS 与 MOGAD）均表现出显著的预测值和准确性（>85%）。
NMOSD、MS 和 MOGAD 的发病机制可能不同，一些免疫学标志物可作为潜在的临床分类器。
