Department of Rheumatology and Clinical Immunology, Charité Universitätsmedizin Berlin, Berlin, Germany.
Deutsches Rheumaforschungszentrum (DRFZ), Berlin, Germany.
Front Immunol. 2022 Apr 19;13:822885. doi: 10.3389/fimmu.2022.822885. eCollection 2022.
Vaccination is considered as most efficient strategy in controlling SARS-CoV-2 pandemic spread. Nevertheless, patients with autoimmune inflammatory rheumatic diseases receiving rituximab (RTX) are at increased risk to fail humoral and cellular responses upon vaccination. The ability to predict vaccination responses is essential to guide adequate safety and optimal protection in these patients.
B- and T- cell data before vaccination were evaluated for characteristics predicting vaccine responses in altogether 15 patients with autoimmune inflammatory rheumatic diseases receiving RTX. Eleven patients with rheumatoid arthritis (RA) on other therapies, 11 kidney transplant recipients (KTR) on regular immunosuppression and 15 healthy controls (HC) served as controls. A multidimensional analysis of B cell subsets UMAP algorithm and a correlation matrix were performed in order to identify predictive markers of response in patients under RTX therapy.
Significant differences regarding absolute B cell counts and specific subset distribution pattern between the groups were identified at baseline. In this context, the majority of B cells from vaccination responders of the RTX group (RTX IgG+) were naïve and transitional B cells, whereas vaccination non-responders (RTX IgG-) carried preferentially plasmablasts and double negative (CD27-IgD-) B cells. Moreover, there was a positive correlation between neutralizing antibodies and B cells expressing HLA-DR and CXCR5 as well as an inverse correlation with CD95 expression and CD21low expression by B cells among vaccination responders.
Substantial repopulation of the naïve B cell compartment after RTX therapy appeared to be essential for an adequate vaccination response, which seem to require the additional capability of antigen presentation and germinal center formation. Moreover, expression of exhaustion markers represent negative predictors of vaccination responses.
接种疫苗被认为是控制 SARS-CoV-2 大流行传播的最有效策略。然而,接受利妥昔单抗 (RTX) 治疗的自身免疫性炎症性风湿病患者在接种疫苗后出现体液和细胞应答失败的风险增加。预测接种反应的能力对于指导这些患者的充分安全性和最佳保护至关重要。
评估了总共 15 名接受 RTX 治疗的自身免疫性炎症性风湿病患者接种疫苗前的 B 细胞和 T 细胞数据,以寻找预测疫苗反应的特征。11 名接受其他治疗的类风湿关节炎 (RA) 患者、11 名接受常规免疫抑制治疗的肾移植受者 (KTR) 和 15 名健康对照 (HC) 作为对照。进行 B 细胞亚群的多维分析 UMAP 算法和相关矩阵,以确定 RTX 治疗患者中反应的预测标志物。
在基线时,各组之间的绝对 B 细胞计数和特定亚群分布模式存在显著差异。在这种情况下,RTX 组(RTX IgG+)的大多数疫苗接种应答者的 B 细胞为幼稚和过渡 B 细胞,而疫苗接种无应答者(RTX IgG-)则携带更多的浆母细胞和双阴性 (CD27-IgD-) B 细胞。此外,疫苗接种应答者中中和抗体与表达 HLA-DR 和 CXCR5 的 B 细胞之间呈正相关,与 B 细胞上的 CD95 表达和 CD21low 表达呈负相关。
RTX 治疗后幼稚 B 细胞区室的大量再填充似乎是充分接种反应的必要条件,这似乎需要抗原呈递和生发中心形成的额外能力。此外,衰竭标志物的表达是疫苗接种反应的负面预测因子。